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Wang Y, Yue X, Lou S, Feng P, Cui B, Liu Y. Gene Swin transformer: new deep learning method for colorectal cancer prognosis using transcriptomic data. Brief Bioinform 2025; 26:bbaf275. [PMID: 40515391 PMCID: PMC12165829 DOI: 10.1093/bib/bbaf275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2025] [Revised: 04/27/2025] [Accepted: 05/19/2025] [Indexed: 06/16/2025] Open
Abstract
Transcriptome sequencing has become essential in clinical tumor research, providing in-depth insights into the biology and functionality of tumor cells. However, the vast amount of data generated and the complex relationships between gene expressions make it challenging to effectively identify clinically relevant information. In this study, we developed a method called Gene Swin Transformer to address these challenges. This approach converts transcriptomic data into Synthetic Image Elements (SIEs). We utilized data from 12 datasets, including GSE17536-GSE103479 datasets (n = 1771) and The Cancer Genome Atlas (n = 459), to generate SIEs. These elements were then classified based on survival time using deep learning algorithms to predict colorectal cancer prognosis and build a reliable prognostic model. We trained and evaluated four deep learning models-BeiT, ResNet, Swin Transformer, and ViT Transformer-and compared their performance. The enhanced Swin-T model outperformed the other models, achieving weighted precision, recall, and F1 scores of 0.708, 0.692, and 0.705, respectively, along with area under the curve values of 80.2%, 72.7%, and 76.9% across three datasets. This model demonstrated the strongest prognostic prediction capabilities among those evaluated. Additionally, the PEX10 gene was identified as a key prognostic marker through both visual attention matrix analysis and bioinformatics methods. Our study demonstrates that the Gene Swin model effectively transforms Ribonucleic Acid (RNA) sequencing data into SIEs, enabling prognosis prediction through attention-based algorithms. This approach supports the development of a data-driven, unified, and automated model, offering a robust tool for classification and prediction tasks using RNA sequencing data. This advancement presents a novel clinical strategy for cancer treatment and prognosis forecasting.
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Affiliation(s)
- Yangyang Wang
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang 150081, China
| | - Xinyu Yue
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang 150081, China
| | - Shenghan Lou
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang 150081, China
| | - Peinan Feng
- School of Computer Science and Engineering, Northeastern University, No.195 Innovation Road, Hunnan District, Shenyang, Liaoning 110169, China
| | - Binbin Cui
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang 150081, China
| | - Yanlong Liu
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang 150081, China
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Ding C, Wang J, Wang J, Niu J, Xiahou Z, Sun Z, Zhao Z, Zeng D. Heterogeneity of cancer-associated fibroblast subpopulations in prostate cancer: Implications for prognosis and immunotherapy. Transl Oncol 2025; 52:102255. [PMID: 39721245 PMCID: PMC11732565 DOI: 10.1016/j.tranon.2024.102255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 12/03/2024] [Accepted: 12/15/2024] [Indexed: 12/28/2024] Open
Abstract
BACKGROUND Prostate cancer stands as the second most common malignancy among men, notorious for its intricate heterogeneity, especially evident in metastatic disease. This complexity presents substantial challenges in treatment efficacy and patient prognosis. OBJECTIVE This study endeavors to elucidate the multifaceted roles of cancer-associated fibroblasts within the tumor microenvironment of prostate cancer, with a focus on their implications for disease prognosis and the potential for novel immunotherapeutic strategies. METHODS Leveraging advanced single-cell RNA sequencing technology, we meticulously characterized the diverse CAF subpopulations within prostate cancer samples. Our analysis identified four predominant subsets: C0 IER2+, C1 ABCA8+, C2 ABI3BP+, and C3 MEOX2+. We conducted comprehensive gene expression profiling to construct a robust prognostic model reflecting the clinical relevance of these subpopulations. RESULTS C1 ABCA8+ fibroblasts demonstrated heightened proliferative activity, underscoring their pivotal role in fostering tumor growth and metastasis via intricate signaling pathways. In vitro experiments verified that the T transcription factor NFAT5 of C1 ABCA8+ fibroblasts subpopulation was knocked down in LNCaP clone FGC and 22Rv1 cell lines, which was closely related to the proliferation of PC. Moreover, we identified key genes linked to patient outcomes and immune landscape alterations, reinforcing the prognostic significance of CAF characteristics in this context. CONCLUSION This investigation illuminates the critical potential of targeting CAFs to augment immunotherapeutic approaches in prostate cancer. Our findings contribute to a deeper understanding of the TME's complexity, advocating for further exploration into CAF-targeted therapies aimed at enhancing treatment responses and ultimately improving patient outcomes.
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Affiliation(s)
- Chen Ding
- Department of Urology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, 136 Jingzhou Street, Xiangyang, Hubei 441021, PR China
| | - Jiange Wang
- Department of Urology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, 136 Jingzhou Street, Xiangyang, Hubei 441021, PR China
| | - Jie Wang
- Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, Jilin 130000, China; Department of Urology, The Second People's Hospital of Meishan City, Meishan, Sichuan, China
| | - Jiqiang Niu
- Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, Jilin 130000, China
| | - Zhikai Xiahou
- China Institute of Sport and Health Science, Beijing Sport University, Beijing, China
| | - Zhou Sun
- Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, Jilin 130000, China.
| | - Zhenzhen Zhao
- The first clinical medical college of Shandong university of Traditional Chinese Medicine, Jinan 250014, China.
| | - Dongyang Zeng
- Department of Urology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, 136 Jingzhou Street, Xiangyang, Hubei 441021, PR China.
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Razumovskaya A, Silkina M, Poloznikov A, Kulagin T, Raigorodskaya M, Gorban N, Kudryavtseva A, Fedorova M, Alekseev B, Tonevitsky A, Nikulin S. Predicting patient outcomes with gene-expression biomarkers from colorectal cancer organoids and cell lines. Front Mol Biosci 2025; 12:1531175. [PMID: 39886381 PMCID: PMC11774744 DOI: 10.3389/fmolb.2025.1531175] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Accepted: 01/02/2025] [Indexed: 02/01/2025] Open
Abstract
Introduction Colorectal cancer (CRC) is characterized by an extremely high mortality rate, mainly caused by the high metastatic potential of this type of cancer. To date, chemotherapy remains the backbone of the treatment of metastatic colorectal cancer. Three main chemotherapeutic drugs used for the treatment of metastatic colorectal cancer are 5-fluorouracil, oxaliplatin and irinotecan which is metabolized to an active compound SN-38. The main goal of this study was to find the genes connected to the resistance to the aforementioned drugs and to construct a predictive gene expression-based classifier to separate responders and non-responders. Methods In this study, we analyzed gene expression profiles of seven patient-derived CRC organoids and performed correlation analyses between gene expression and IC50 values for the three standard-of-care chemotherapeutic drugs. We also included in the study publicly available datasets of colorectal cancer cell lines, thus combining two different in vitro models relevant to cancer research. Logistic regression was used to build gene expression-based classifiers for metastatic Stage IV and non-metastatic Stage II/III CRC patients. Prognostic performance was evaluated through Kaplan-Meier survival analysis and log-rank tests, while independent prognostic significance was assessed using multivariate Cox proportional hazards modeling. Results A small set of genes showed consistent correlation with resistance to chemotherapy across different datasets. While some genes were previously implicated in cancer prognosis and drug response, several were linked to drug resistance for the first time. The resulting gene expression signatures successfully stratified Stage II/III and Stage IV CRC patients, with potential clinical utility for improving treatment outcomes after further validation. Discussion This study highlights the advantages of integrating diverse experimental models, such as organoids and cell lines, to identify novel prognostic biomarkers and enhance the understanding of chemotherapy resistance in CRC.
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Affiliation(s)
- Alexandra Razumovskaya
- Faculty of Biology and Biotechnologies, National Research University Higher School of Economics, Moscow, Russia
| | - Mariia Silkina
- Faculty of Biology and Biotechnologies, National Research University Higher School of Economics, Moscow, Russia
- P. A. Hertsen Moscow Oncology Research Center, Branch of the National Medical Research Radiological Center, Ministry of Health of the Russian Federation, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Andrey Poloznikov
- P. A. Hertsen Moscow Oncology Research Center, Branch of the National Medical Research Radiological Center, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Timur Kulagin
- Faculty of Biology and Biotechnologies, National Research University Higher School of Economics, Moscow, Russia
| | - Maria Raigorodskaya
- P. A. Hertsen Moscow Oncology Research Center, Branch of the National Medical Research Radiological Center, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Nina Gorban
- Central Clinical Hospital with Polyclinic, Administration of the President of the Russian Federation, Moscow, Russia
| | - Anna Kudryavtseva
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Maria Fedorova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Boris Alekseev
- P. A. Hertsen Moscow Oncology Research Center, Branch of the National Medical Research Radiological Center, Ministry of Health of the Russian Federation, Moscow, Russia
| | - Alexander Tonevitsky
- Faculty of Biology and Biotechnologies, National Research University Higher School of Economics, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Art Photonics GmbH, Berlin, Germany
| | - Sergey Nikulin
- Faculty of Biology and Biotechnologies, National Research University Higher School of Economics, Moscow, Russia
- P. A. Hertsen Moscow Oncology Research Center, Branch of the National Medical Research Radiological Center, Ministry of Health of the Russian Federation, Moscow, Russia
- Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, Ministry of Health of the Russian Federation, Moscow, Russia
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Zhai M, Yang W, Zou C, Du S, Wu B, Wang C, Lu Y, Zheng Y. Predictive role of HPGD gene in carcinogenesis and immune environment monitoring in human cervical cancer. Cancer Biomark 2024; 41:18758592241296277. [PMID: 40095474 DOI: 10.1177/18758592241296277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2025]
Abstract
Background15-Hydroxyprostaglandin dehydrogenase (15-PGDH, gene symbol HPGD) is considered a tumor suppressor, and its expression is often proportional to the anticancer response. However, the clinical significance of HPGD/15-PGDH in predicting immune response and its diagnosis and prognosis value in cervical cancer remains unclear.ObjectiveThis study aims to explore the clinical significance of HPGD/15-PGDH in predicting carcinogenesis, prognosis, and sensitivity to immuno- and chemotherapy in cervical cancer.MethodsA comprehensive evaluation of the diagnostic, treatment-sensitive, and prognostic value of HPGD/15-PGDH in cervical cancer was conducted by bioinformatics analysis of public databases and validation of real cohort data.ResultsBioinformatics analysis showed that HPGD expression was decreased in cervical cancer and did not independently predict patient prognosis. Low HPGD expression was linked to resistance to certain chemotherapies, potentially due to immunosuppression triggered by low HPGD levels. Validation in clinical samples from the local hospital confirmed the decreased 15-PGDH expression and increased COX-2 expression in HPV16-positive cervical cancer patients and increased immune suppression during cancer progression.ConclusionsHPGD/15-PGDH is a potential biomarker for predicting the progression, immune response, and chemotherapy sensitivity of cervical cancer, with implications that it is of great value for the diagnosis and individual-based treatment of cervical cancer.
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Affiliation(s)
- Mingzhu Zhai
- Department of Clinical Pathology, Jinan University First Affiliated Hospital, Guangzhou, China
- Center for Medical Experiments (CME), Shenzhen Guangming District People's Hospital, Shenzhen, China
| | - Weihua Yang
- Center for Medical Experiments (CME), Shenzhen Guangming District People's Hospital, Shenzhen, China
| | - Chen Zou
- Center for Medical Experiments (CME), Shenzhen Guangming District People's Hospital, Shenzhen, China
| | - Shan Du
- Department of Pathology, Shenzhen Guangming District People's Hospital, Shenzhen, China
| | - Benqing Wu
- Center for Medical Experiments (CME), Shenzhen Guangming District People's Hospital, Shenzhen, China
| | - Changshan Wang
- Center for Medical Experiments (CME), Shenzhen Guangming District People's Hospital, Shenzhen, China
| | - Yuanzhi Lu
- Department of Clinical Pathology, Jinan University First Affiliated Hospital, Guangzhou, China
| | - Yi Zheng
- Center for Medical Experiments (CME), Shenzhen Guangming District People's Hospital, Shenzhen, China
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Xu Y, Ma Z, Wang Y, Zhang L, Ye J, Chen Y, Yuan Z. CuPCA: a web server for pan-cancer association analysis of large-scale cuproptosis-related genes. Database (Oxford) 2024; 2024:baae075. [PMID: 39231258 PMCID: PMC11373563 DOI: 10.1093/database/baae075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 06/13/2024] [Accepted: 08/26/2024] [Indexed: 09/06/2024]
Abstract
Copper-induced cell death is a novel mechanism of cell death, which is defined as cuproptosis. The increasing level of copper can produce toxicity in cells and may cause the occurrence of cell death. Several previous studies have proved that cuproptosis has a tight association with various cancers. Thus, the discovery of relationships between cuproptosis-related genes (CRGs) and human cancers is of great importance. Pan-cancer analysis can efficiently help researchers find out the relationship between multiple cancers and target genes precisely and make various prognostic analyses on cancers and cancer patients. Pan-cancer web servers can provide researchers with direct results of pan-cancer prognostic analyses, which can greatly improve the efficiency of their work. However, to date, no web server provides pan-cancer analysis about CRGs. Therefore, we introduce the cuproptosis pan-cancer analysis database (CuPCA), the first database for various analysis results of CRGs through 33 cancer types. CuPCA is a user-friendly resource for cancer researchers to gain various prognostic analyses between cuproptosis and cancers. It provides single CRG pan-cancer analysis, multi-CRGs pan-cancer analysis, multi-CRlncRNA pan-cancer analysis, and mRNA-circRNA-lncRNA conjoint analysis. These analysis results can not only indicate the relationship between cancers and cuproptosis at both gene level and protein level, but also predict the conditions of different cancer patients, which include their clinical condition, survival condition, and their immunological condition. CuPCA procures the delivery of analyzed data to end users, which improves the efficiency of wide research as well as releases the value of data resources. Database URL: http://cupca.cn/.
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Affiliation(s)
- Yishu Xu
- College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
| | - Zhenshu Ma
- College of Computer Science and Technology, Beijing Forestry University, Beijing 100083, China
| | - Yajie Wang
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Long Zhang
- College of Art, Beijing Forestry University, Beijing 100083, China
| | - Jiaming Ye
- College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
| | - Yuan Chen
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Zhengrong Yuan
- College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
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Zhang Y, Xue X, Li F, Zhang B, Zheng P, Mi Y. Integrative nomogram model based on anoikis-related genes enhances prognostic evaluation in colorectal cancer. Heliyon 2024; 10:e33637. [PMID: 39040248 PMCID: PMC11261108 DOI: 10.1016/j.heliyon.2024.e33637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 07/24/2024] Open
Abstract
Background Revealing the role of anoikis resistance plays in CRC is significant for CRC diagnosis and treatment. This study integrated the CRC anoikis-related key genes (CRC-AKGs) and established a novel model for improving the efficiency and accuracy of the prognostic evaluation of CRC. Methods CRC-ARGs were screened out by performing differential expression and univariate Cox analysis. CRC-AKGs were obtained through the LASSO machine learning algorithm and the LASSO Risk-Score was constructed to build a nomogram clinical prediction model combined with the clinical predictors. In parallel, this work developed a web-based dynamic nomogram to facilitate the generalization and practical application of our model. Results We identified 10 CRC-AKGs and a risk-related prognostic Risk-Score was calculated. Multivariate COX regression analysis indicated that the Risk-Score, TNM stage, and age were independent risk factors that significantly associated with the CRC prognosis(p < 0.05). A prognostic model was built to predict the outcome with satisfied accuracy (3-year AUC = 0.815) for CRC individuals. The web interactive nomogram (https://yuexiaozhang.shinyapps.io/anoikisCRC/) showed strong generalizability of our model. In parallel, a substantial correlation between tumor microenvironment and Risk-Score was discovered in the present work. Conclusion This study reveals the potential role of anoikis in CRC and sets new insights into clinical decision-making in colorectal cancer based on both clinical and sequencing data. Also, the interactive tool provides researchers with a user-friendly interface to input relevant clinical variables and obtain personalized risk predictions or prognostic assessments based on our established model.
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Affiliation(s)
- Yuexiao Zhang
- Henan Key Laboratory of Helicobacter Pylori & Microbiota and Gastrointestinal Cancer, Marshall B. J. Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
| | - Xia Xue
- Henan Key Laboratory of Helicobacter Pylori & Microbiota and Gastrointestinal Cancer, Marshall B. J. Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
| | - Fazhan Li
- Henan Key Laboratory of Helicobacter Pylori & Microbiota and Gastrointestinal Cancer, Marshall B. J. Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
| | - Bo Zhang
- Henan Key Laboratory of Helicobacter Pylori & Microbiota and Gastrointestinal Cancer, Marshall B. J. Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
| | - Pengyuan Zheng
- Henan Key Laboratory of Helicobacter Pylori & Microbiota and Gastrointestinal Cancer, Marshall B. J. Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
| | - Yang Mi
- Henan Key Laboratory of Helicobacter Pylori & Microbiota and Gastrointestinal Cancer, Marshall B. J. Medical Research Center, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
- Department of Gastroenterology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, PR China
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Zhou YJ, Tan ZE, Zhuang WD, Xu XH. Analysis of cancer-specific survival in patients with metastatic colorectal cancer: A evidence-based medicine study. World J Gastrointest Surg 2024; 16:1791-1802. [PMID: 38983329 PMCID: PMC11230018 DOI: 10.4240/wjgs.v16.i6.1791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 04/29/2024] [Accepted: 05/16/2024] [Indexed: 06/27/2024] Open
Abstract
BACKGROUND Metastatic colorectal cancer (mCRC) is a common malignancy whose treatment has been a clinical challenge. Cancer-specific survival (CSS) plays a crucial role in assessing patient prognosis and treatment outcomes. However, there is still limited research on the factors affecting CSS in mCRC patients and their correlation. AIM To predict CSS, we developed a new nomogram model and risk grading system to classify risk levels in patients with mCRC. METHODS Data were extracted from the United States Surveillance, Epidemiology, and End Results database from 2018 to 2023. All eligible patients were randomly divided into a training cohort and a validation cohort. The Cox proportional hazards model was used to investigate the independent risk factors for CSS. A new nomogram model was developed to predict CSS and was evaluated through internal and external validation. RESULTS A multivariate Cox proportional risk model was used to identify independent risk factors for CSS. Then, new CSS columns were developed based on these factors. The consistency index (C-index) of the histogram was 0.718 (95%CI: 0.712-0.725), and that of the validation cohort was 0.722 (95%CI: 0.711-0.732), indicating good discrimination ability and better performance than tumor-node-metastasis staging (C-index: 0.712-0.732). For the training set, 0.533, 95%CI: 0.525-0.540; for the verification set, 0.524, 95%CI: 0.513-0.535. The calibration map and clinical decision curve showed good agreement and good potential clinical validity. The risk grading system divided all patients into three groups, and the Kaplan-Meier curve showed good stratification and differentiation of CSS between different groups. The median CSS times in the low-risk, medium-risk, and high-risk groups were 36 months (95%CI: 34.987-37.013), 18 months (95%CI: 17.273-18.727), and 5 months (95%CI: 4.503-5.497), respectively. CONCLUSION Our study developed a new nomogram model to predict CSS in patients with synchronous mCRC. In addition, the risk-grading system helps to accurately assess patient prognosis and guide treatment.
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Affiliation(s)
- Yin-Jie Zhou
- Department of Oncology, The First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang 443000, Hubei Province, China
| | - Zhi-E Tan
- Department of Nuclear Medicine, The First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang 443000, Hubei Province, China
| | - Wei-Da Zhuang
- Department of Athe and Intestinal Surgery, Cancer Hospital of The Chinese Academy of Medical Sciences, Beijing 100021, China
| | - Xin-Hua Xu
- Department of Oncology, The First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang 443000, Hubei Province, China
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Zhang ZW, Zhang KX, Liao X, Quan Y, Zhang HY. Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction. iScience 2024; 27:109859. [PMID: 38799582 PMCID: PMC11126775 DOI: 10.1016/j.isci.2024.109859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/15/2024] [Accepted: 04/27/2024] [Indexed: 05/29/2024] Open
Abstract
Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.
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Affiliation(s)
- Zhi-Wen Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Ke-Xin Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Xuan Liao
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Yuan Quan
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Hong-Yu Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China
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Zhu LH, Yang J, Zhang YF, Yan L, Lin WR, Liu WQ. Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data. World J Clin Oncol 2024; 15:329-355. [PMID: 38455135 PMCID: PMC10915942 DOI: 10.5306/wjco.v15.i2.329] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 12/24/2023] [Accepted: 01/15/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND Pyroptosis impacts the development of malignant tumors, yet its role in colorectal cancer (CRC) prognosis remains uncertain. AIM To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration. METHODS Gene expression data were obtained from The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus (GEO). Pyroptosis-related gene expression in cell clusters was analyzed, and enrichment analysis was conducted. A pyroptosis-related risk model was developed using the LASSO regression algorithm, with prediction accuracy assessed through K-M and receiver operating characteristic analyses. A nomogram predicting survival was created, and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations. Finally, the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database. RESULTS An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B, SDHB, BST2, UBE2D2, GJA1, AIM2, PDCD6IP, and SEZ6L2 (P < 0.05). Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis (P < 0.05). Patients with higher risk scores demonstrated increased death risk and reduced overall survival (P < 0.05). Significant differences in immune infiltration were observed between low- and high-risk groups, correlating with pyroptosis-related gene expression. CONCLUSION We developed a pyroptosis-related prognostic model for CRC, affirming its correlation with immune infiltration. This model may prove useful for CRC prognostic evaluation.
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Affiliation(s)
- Li-Hua Zhu
- Department of Surgical Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China
| | - Jun Yang
- Department of Surgical Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China
| | - Yun-Fei Zhang
- Department of Surgical Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China
| | - Li Yan
- Department of Internal Medicine-Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China
| | - Wan-Rong Lin
- Department of Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China
| | - Wei-Qing Liu
- Department of Internal Medicine-Oncology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, Yunnan Province, China
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Bai S, Chen L, Zhu G, Xuan W, Hu F, Liu W, Li W, Lan N, Chen M, Yan Y, Li R, Yang Y, Ren J. Prognostic value of extrahepatic metastasis on colon cancer with liver metastasis: a retrospective cohort study. Front Oncol 2023; 13:1172670. [PMID: 37346071 PMCID: PMC10280983 DOI: 10.3389/fonc.2023.1172670] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 05/10/2023] [Indexed: 06/23/2023] Open
Abstract
INTRODUCTION The occurrence of metastasis is a threat to patients with colon cancer (CC), and the liver is the most common metastasis organ. However, the role of the extrahepatic organs in patients with liver metastasis (LM) has not been distinctly demonstrated. Therefore, this research aimed to explore the prognostic value of extrahepatic metastases (EHMs). METHODS In this retrospective study, a total of 13,662 colon patients with LM between 2010 and 2015 were selected from the Surveillance, Epidemiology, and End Results database (SEER). Fine and Gray's analysis and K-M survival analysis were utilized to explore the impacts of the number of sites of EHMs and different sites of EHMs on prognosis. Finally, a prognostic nomogram model based on the number of sites of EHMs was constructed, and a string of validation methods was conducted, including concordance index (C-index), receiver operating characteristic curves (ROC), and decision curve analysis (DCA). RESULTS Patients without EHMs had better prognoses in cancer-specific survival (CSS) and overall survival (OS) than patients with EHMs (p < 0.001). Varied EHM sites of patients had different characteristics of primary location site, grade, and histology. Cumulative incidence rates for CSS surpassed that for other causes in patients with 0, 1, 2, ≥ 3 EHMs, and the patients with more numbers of sites of EHMs revealed worse prognosis in CSS (p < 0.001). However, patients with different EHM sites had a minor difference in cumulative incidence rates for CSS (p = 0.106). Finally, a nomogram was constructed to predict the survival probability of patients with EHMs, which is based on the number of sites of EHMs and has been proven an excellent predictive ability. CONCLUSION The number of sites of EHMs was a significant prognostic factor of CC patients with LM. However, the sites of EHMs showed limited impact on survival. Furthermore, a nomogram based on the number of sites of EHMs was constructed to predict the OS of patients with EHMs accurately.
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Affiliation(s)
- Shuheng Bai
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Ling Chen
- Department of Chemotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Guixian Zhu
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Wang Xuan
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Fengyuan Hu
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Wanyi Liu
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Wenyang Li
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Ning Lan
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Min Chen
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yanli Yan
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Rong Li
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yiping Yang
- Department of Radiotherapy, Radiotherapy Clinical Medical Research Center of Shaanxi Province, Xi’an, China
| | - Juan Ren
- Department of Radiotherapy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Jiang J, Qu H, Zhan X, Liu D, Liang T, Chen L, Huang S, Sun X, Chen J, Chen T, Li H, Yao Y, Liu C. Identification of osteosarcoma m6A-related prognostic biomarkers using artificial intelligence: RBM15. Sci Rep 2023; 13:5255. [PMID: 37002245 PMCID: PMC10066227 DOI: 10.1038/s41598-023-28739-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 01/24/2023] [Indexed: 04/03/2023] Open
Abstract
Osteosarcoma has the worst prognosis among malignant bone tumors, and effective biomarkers are lacking. Our study aims to explore m6A-related and immune-related biomarkers. Gene expression profiles of osteosarcoma and healthy controls were downloaded from multiple public databases, and their m6A-based gene expression was utilized for tumor typing using bioinformatics. Subsequently, a prognostic model for osteosarcoma was constructed using the least absolute shrinkage and selection operator and multivariate Cox regression analysis, and its immune cell composition was calculated using the CIBERSORTx algorithm. We also performed drug sensitivity analysis for these two genes. Finally, analysis was validated using immunohistochemistry. We also examined the RBM15 gene by qRT-PCR in an in vitro experiment. We collected routine blood data from 1738 patients diagnosed with osteosarcoma and 24,344 non-osteosarcoma patients and used two independent sample t tests to verify the accuracy of the CIBERSORTx analysis for immune cell differences. The analysis based on m6A gene expression tumor typing was most reliable using the two typing methods. The prognostic model based on the two genes constituting RNA-binding motif protein 15 (RBM15) and YTDC1 had a much lower survival rate for patients in the high-risk group than those in the low-risk group (P < 0.05). CIBERSORTx immune cell component analysis demonstrated that RBM15 showed a negative and positive correlation with T cells gamma delta and activated natural killer cells, respectively. Drug sensitivity analysis showed that these two genes showed varying degrees of correlation with multiple drugs. The results of immunohistochemistry revealed that the expression of these two genes was significantly higher in osteosarcoma than in paraneoplastic tissues. The results of qRT-PCR experiments showed that the expression of RBM15 was significantly higher in both osteosarcomas than in the control cell lines. Absolute lymphocyte value, lymphocyte percentage, hematocrit and erythrocyte count were lower in osteosarcoma than in the control group (P < 0.001). RBM15 and YTHDC1 can serve as potential prognostic biomarkers associated with m6A in osteosarcoma.
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Affiliation(s)
- Jie Jiang
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Haishun Qu
- Department of Traditional Chinese Medicine, The People's Hospital of Guangxi Zhuang Autonmous Region, Nanning, 530016, People's Republic of China
| | - Xinli Zhan
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Dachang Liu
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Tuo Liang
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Liyi Chen
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Shengsheng Huang
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Xuhua Sun
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Jiarui Chen
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Tianyou Chen
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Hao Li
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Yuanlin Yao
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China
| | - Chong Liu
- The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China.
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Microdissecting the Hypoxia Landscape in Colon Cancer Reveals Three Distinct Subtypes and Their Potential Mechanism to Facilitate the Development of Cancer. JOURNAL OF ONCOLOGY 2023; 2023:9346621. [PMID: 36925652 PMCID: PMC10014161 DOI: 10.1155/2023/9346621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/09/2022] [Accepted: 11/25/2022] [Indexed: 03/09/2023]
Abstract
Background Hypoxia contributes to tumor progression and confers drug resistance. We attempted to microdissect the hypoxia landscape in colon cancer (CC) and explore its correlation with immunotherapy response. Materials and Methods The hypoxia landscape in CC patients was microdissected through unsupervised clustering. The "xCell" algorithms were applied to decipher the tumor immune infiltration characteristics. A hypoxia-related index signature was developed via the LASSO (least absolute shrinkage and selection operator) Cox regression in The Cancer Genome Atlas (TCGA)-colon adenocarcinoma (COAD) cohort and validated in an independent dataset from the Gene Expression Omnibus (GEO) database. The tumor immune dysfunction and exclusion (TIDE) algorithm was utilized to evaluate the correlation between the hypoxia-related index (HRI) signature and immunotherapy response. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blotting were performed to verify the mRNA expression levels of five key genes. The Cell Counting Kit-8 (CCK-8) assay and flow cytometry were performed to examine the cell viability and cell apoptosis. Results Patients were classified into hypoxia-high, hypoxia-median, and hypoxia-low clusters in TCGA-COAD and verified in the GSE 17538 dataset. Compared with the hypoxia-low cluster, the hypoxia-high cluster consistently presented an unfavorable prognosis, higher immune scores, and stromal scores and elevated infiltration levels of several critical immune and stromal cells. Otherwise, we also found 600 hypoxia-related differentially expressed genes (HRDEGs) between the hypoxia-high cluster and the hypoxia-low cluster. Based on the 600 HRDEGs, we constructed the HRI signature which consists of 11 genes and shows a good prognostic value in both TCGA-COAD and GSE 17538 (AUC of 6-year survival prediction >0.75). Patients with low HRI scores were consistently predicted to be more responsive to immunotherapy. Of the 11 HRI signature genes, RGS16, SNAI1, CDR2L, FRMD5, and FSTL3 were differently expressed between tumors and adjacent tissues. Low expression of SNAI1, CDR2L, FRMD5, and FSTL3 could induce cell viability and promote tumor cell apoptosis. Conclusion In our study, we discovered three hypoxia clusters which correlate with the clinical outcome and the tumor immune microenvironment in CC. Based on the hypoxia cluster and HRDEGs, we constructed a reliable HRI signature that could accurately predict the prognosis and immunotherapeutic responsiveness in CC patients and discovered four key genes that could affect tumor cell viability and apoptosis.
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Li Z, Cui Y, Zhang S, Xu J, Shao J, Chen H, Chen J, Wang S, Zeng M, Zhang H, Lu S, Qian ZR, Xing G. Novel hypoxia-related gene signature for predicting prognoses that correlate with the tumor immune microenvironment in NSCLC. Front Genet 2023; 14:1115308. [PMID: 37091782 PMCID: PMC10115983 DOI: 10.3389/fgene.2023.1115308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 03/16/2023] [Indexed: 04/25/2023] Open
Abstract
Background: Intratumoral hypoxia is widely associated with the development of malignancy, treatment resistance, and worse prognoses. The global influence of hypoxia-related genes (HRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response is unclear in patients with non-small cell lung cancer (NSCLC). Method: RNA-seq and clinical data for NSCLC patients were derived from The Cancer Genome Atlas (TCGA) database, and a group of HRGs was obtained from the MSigDB. The differentially expressed HRGs were determined using the limma package; prognostic HRGs were identified via univariate Cox regression. Using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, an optimized prognostic model consisting of nine HRGs was constructed. The prognostic model's capacity was evaluated by Kaplan‒Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis in the TCGA (training set) and GEO (validation set) cohorts. Moreover, a potential biological pathway and immune infiltration differences were explained. Results: A prognostic model containing nine HRGs (STC2, ALDOA, MIF, LDHA, EXT1, PGM2, ENO3, INHA, and RORA) was developed. NSCLC patients were separated into two risk categories according to the risk score generated by the hypoxia model. The model-based risk score had better predictive power than the clinicopathological method. Patients in the high-risk category had poor recurrence-free survival in the TCGA (HR: 1.426; 95% CI: 0.997-2.042; p = 0.046) and GEO (HR: 2.4; 95% CI: 1.7-3.2; p < 0.0001) cohorts. The overall survival of the high-risk category was also inferior to that of the low-risk category in the TCGA (HR: 1.8; 95% CI: 1.5-2.2; p < 0.0001) and GEO (HR: 1.8; 95% CI: 1.4-2.3; p < 0.0001) cohorts. Additionally, we discovered a notable distinction in the enrichment of immune-related pathways, immune cell abundance, and immune checkpoint gene expression between the two subcategories. Conclusion: The proposed 9-HRG signature is a promising indicator for predicting NSCLC patient prognosis and may be potentially applicable in checkpoint therapy efficiency prediction.
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Affiliation(s)
- Zhaojin Li
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
| | - Yu Cui
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
| | - Shupeng Zhang
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
- *Correspondence: Shupeng Zhang,
| | - Jie Xu
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
| | - Jianping Shao
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
| | - Hekai Chen
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
| | - Jingzhao Chen
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Shun Wang
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Meizhai Zeng
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Hao Zhang
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Siqian Lu
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Zhi Rong Qian
- Beidou Precision Medicine Institute, Guangzhou, China
| | - Guoqiang Xing
- Department of General Surgery, Tianjin Fifth Central Hospital, Tianjin, China
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Cui J, Guo F, Yu Y, Ma Z, Hong Y, Su J, Ge Y. Development and validation of a prognostic 9-gene signature for colorectal cancer. Front Oncol 2022; 12:1009698. [PMID: 36465397 PMCID: PMC9714635 DOI: 10.3389/fonc.2022.1009698] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/01/2022] [Indexed: 01/04/2025] Open
Abstract
INTRODUCTION Colorectal cancer (CRC) is one of the most prevalent cancers globally with a high mortality rate. Predicting prognosis using disease progression and cancer pathologic stage is insufficient, and a prognostic factor that can accurately evaluate patient prognosis needs to be developed. In this study, we aimed to infer a prognostic gene signature to identify a functional signature associated with the prognosis of CRC patients. METHODS First, we used univariate Cox regression, least absolute shrinkage and selection operator (lasso) regression, and multivariate Cox regression analyses to screen genes significantly associated with CRC patient prognosis, from colorectal cancer RNA sequencing data in The Cancer Genome Atlas (TCGA) database. We then calculated the risk score (RS) for each patient based on the expression of the nine candidate genes and developed a prognostic signature. RESULTS Based on the optimal cut-off on the receiver operating characteristic (ROC) curve, patients were separated into high- and low-risk groups, and the difference in overall survival between the two groups was examined. Patients in the low-risk group had a better overall survival rate than those in the high-risk group. The results were validated using the GSE72970, GSE39582, and GSE17536 Gene Expression Omnibus (GEO) datasets, and the same conclusions were reached. ROC curve test of the RS signature also indicated that it had excellent accuracy. The RS signature was then compared with traditional clinical factors as a prognostic indicator, and we discovered that the RS signature had superior predictive ability. CONCLUSION The RS signature developed in this study has excellent predictive power for the prognosis of patients with CRC and broad applicability as a prognostic indicator for patients.
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Affiliation(s)
- Junpeng Cui
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Fangyu Guo
- Department of Endocrinology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yifan Yu
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Zihuan Ma
- Department of Scientific Research Projects, ChosenMed Technology Co. Ltd, Beijing, China
| | - Yuting Hong
- Department of Scientific Research Projects, ChosenMed Technology Co. Ltd, Beijing, China
| | - Junyan Su
- Department of Scientific Research Projects, ChosenMed Technology Co. Ltd, Beijing, China
| | - Yang Ge
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
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The Expressions and Functions of lncRNA Related to m6A in Hepatocellular Carcinoma from a Bioinformatics Analysis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:1395557. [PMID: 36276996 PMCID: PMC9581679 DOI: 10.1155/2022/1395557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022]
Abstract
Hepatocellular carcinoma (HCC) is one of the most common cancer in these days. Besides, N6-methyladenosine (m6A) plays an important role in the occurrence and development of hepatocellular carcinoma. Meanwhile, it is known to us that long noncoding RNAs (lncRNA) have the capability to control the expression of genes which means some lncRNA can adjust the expression of some m6A.Thus, it is indispensable to dig the m6A-related lncRNA in hepatocellular carcinoma about its potential regulatory mechanism and immune analysis as well as its potential drugs. In this experiment, expression profile and clinical information of lncRNA are obtained by downloading the liver cancer data set from The Cancer Genome Atlas (TCGA) database. GO enrichment analysis is used to predict potential regulatory mechanism of lncRNA. Correlation analysis of clinical parameters are calculated via chisq.test. The Cox regression model is used in univariate and multivariate analysis, and the difference is statistically significant when P < 0.05. The results show that many kinds of lncRNA have influence on the prognosis of patients with HCC, and enrichment analysis discloses some pathways that can be used to evaluate mechanism underlying in HCC. The screening of targeted drugs can provide new clues for further experiments and clinical treatment.
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Fletcher T, Thompson AJ, Ashrafian H, Darzi A. The measurement and modification of hypoxia in colorectal cancer: overlooked but not forgotten. Gastroenterol Rep (Oxf) 2022; 10:goac042. [PMID: 36032656 PMCID: PMC9406947 DOI: 10.1093/gastro/goac042] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 05/18/2022] [Accepted: 07/21/2022] [Indexed: 11/14/2022] Open
Abstract
Tumour hypoxia is the inevitable consequence of a tumour's rapid growth and disorganized, inefficient vasculature. The compensatory mechanisms employed by tumours, and indeed the absence of oxygen itself, hinder the ability of all treatment modalities. The clinical consequence is poorer overall survival, disease-free survival, and locoregional control. Recognizing this, clinicians have been attenuating the effect of hypoxia, primarily with hypoxic modification or with hypoxia-activated pro-drugs, and notable success has been demonstrated. However, in the case of colorectal cancer (CRC), there is a general paucity of knowledge and evidence surrounding the measurement and modification of hypoxia, and this is possibly due to the comparative inaccessibility of such tumours. We specifically review the role of hypoxia in CRC and focus on the current evidence for the existence of hypoxia in CRC, the majority of which originates from indirect positron emission topography imaging with hypoxia selective radiotracers; the evidence correlating CRC hypoxia with poorer oncological outcome, which is largely based on the measurement of hypoxia inducible factor in correlation with clinical outcome; the evidence of hypoxic modification in CRC, of which no direct evidence exists, but is reflected in a number of indirect markers; the prognostic and monitoring implications of accurate CRC hypoxia quantification and its potential in the field of precision oncology; and the present and future imaging tools and technologies being developed for the measurement of CRC hypoxia, including the use of blood-oxygen-level-dependent magnetic resonance imaging and diffuse reflectance spectroscopy.
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Affiliation(s)
- Teddy Fletcher
- Department of Surgery and Cancer, Queen Elizabeth the Queen Mother Wing, St Mary’s Hospital, Imperial College London, London, UK
| | - Alex J Thompson
- The Hamlyn Centre, Institute of Global Health Innovation, Imperial College London, London, UK
| | - Hutan Ashrafian
- Department of Surgery and Cancer, Queen Elizabeth the Queen Mother Wing, St Mary’s Hospital, Imperial College London, London, UK
| | - Ara Darzi
- Department of Surgery and Cancer, Queen Elizabeth the Queen Mother Wing, St Mary’s Hospital, Imperial College London, London, UK
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Liu Y, Wang T, Li R. A prognostic Risk Score model for oral squamous cell carcinoma constructed by 6 glycolysis-immune-related genes. BMC Oral Health 2022; 22:324. [PMID: 35922788 PMCID: PMC9351085 DOI: 10.1186/s12903-022-02358-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/26/2022] [Indexed: 12/23/2022] Open
Abstract
Background Oral squamous cell carcinoma (OSCC) is the most frequent tumor of the head and neck. The glycolysis-related genes and immune-related genes have been proven prognostic values in various cancers. Our study aimed to test the prognostic value of glycolysis-immune-related genes in OSCC. Methods Data of OSCC patients were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Enrichment analysis was applied to the glycolysis- and immune-related genes screened by differential expression analysis. Univariate Cox and LASSO Cox analyses were used to filtrate the genes related to the prognosis of OSCC and to construct Risk Score model. Results A Risk Score model was constructed by six glycolysis-immune-related genes (including ALDOC, VEGFA, HRG, PADI3, IGSF11 and MIPOL1). High risk OSCC patients (Risk Score >−0.3075) had significantly worse overall survival than that of low risk patients (Risk Score <−0.3075). Conclusions The Risk Score model constructed basing on 6 glycolysis-immune-related genes was reliable in stratifying OSCC patients with different prognosis.
Supplementary Information The online version contains supplementary material available at 10.1186/s12903-022-02358-0.
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Affiliation(s)
- Yi Liu
- Department of Stomatology, Tianjin First Central Hospital, Nankai District, No.24 Fukang Road, Tianjin, 300192, People's Republic of China.
| | - Tong Wang
- Department of Stomatology, Tianjin First Central Hospital, Nankai District, No.24 Fukang Road, Tianjin, 300192, People's Republic of China
| | - Ronghua Li
- Department of Stomatology, Tianjin First Central Hospital, Nankai District, No.24 Fukang Road, Tianjin, 300192, People's Republic of China
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An analysis of the significance of the Tre2/Bub2/CDC 16 (TBC) domain protein family 8 in colorectal cancer. Sci Rep 2022; 12:13245. [PMID: 35918393 PMCID: PMC9345998 DOI: 10.1038/s41598-022-15629-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 06/27/2022] [Indexed: 11/09/2022] Open
Abstract
The TBC (Tre-2/Bub2/Cdc16, TBC) structural domain is now considered as one of the factors potentially regulating tumor progression. However, to date, studies on the relationship between TBC structural domains and tumors are limited. In this study, we identified the role of TBC1 domain family member 8 (TBC1D8) as an oncogene in colorectal cancer (CRC) by least absolute shrinkage and selection operator (LASSO) and Cox regression analysis, showing that TBC1D8 may independently predict CRC outcome. Functional enrichment and single-cell analysis showed that TBC1D8 levels were associated with hypoxia. TBC1D8 levels were also positively correlated with M2 macrophage infiltration, which may have a complex association with hypoxia. Taken together, these results show that the TBC1D8 gene is involved in colorectal carcinogenesis, and the underlying molecular mechanisms may include hypoxia and immune cell infiltration.
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Zhong ME, Huang ZP, Wang X, Cai D, Li CH, Gao F, Wu XJ, Wang W. A Transcription Factor Signature Can Identify the CMS4 Subtype and Stratify the Prognostic Risk of Colorectal Cancer. Front Oncol 2022; 12:902974. [PMID: 35847938 PMCID: PMC9280271 DOI: 10.3389/fonc.2022.902974] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 05/26/2022] [Indexed: 12/24/2022] Open
Abstract
BackgroundColorectal cancer (CRC) is a heterogeneous disease, and current classification systems are insufficient for stratifying patients with different risks. This study aims to develop a generalized, individualized prognostic consensus molecular subtype (CMS)-transcription factors (TFs)-based signature that can predict the prognosis of CRC.MethodsWe obtained differentially expressed TF signature and target genes between the CMS4 and other CMS subtypes of CRC from The Cancer Genome Atlas (TCGA) database. A multi-dimensional network inference integrative analysis was conducted to identify the master genes and establish a CMS4-TFs-based signature. For validation, an in-house clinical cohort (n = 351) and another independent public CRC cohort (n = 565) were applied. Gene set enrichment analysis (GSEA) and prediction of immune cell infiltration were performed to interpret the biological significance of the model.ResultsA CMS4-TFs-based signature termed TF-9 that includes nine TF master genes was developed. Patients in the TF-9 high-risk group have significantly worse survival, regardless of clinical characteristics. The TF-9 achieved the highest mean C-index (0.65) compared to all other signatures reported (0.51 to 0.57). Immune infiltration revealed that the microenvironment in the high-risk group was highly immune suppressed, as evidenced by the overexpression of TIM3, CD39, and CD40, suggesting that high-risk patients may not directly benefit from the immune checkpoint inhibitors.ConclusionsThe TF-9 signature allows a more precise categorization of patients with relevant clinical and biological implications, which may be a valuable tool for improving the tailoring of therapeutic interventions in CRC patients.
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Affiliation(s)
- Min-Er Zhong
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ze-Ping Huang
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xun Wang
- Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, China
| | - Du Cai
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Cheng-Hang Li
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Feng Gao
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Wei Wang, ; Xiao-Jian Wu, ; Feng Gao,
| | - Xiao-Jian Wu
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Wei Wang, ; Xiao-Jian Wu, ; Feng Gao,
| | - Wei Wang
- Biomedical Big Data Centre, Department of Gynaecology, Huzhou Maternity & Child Health Care Hospital, Huzhou, China
- *Correspondence: Wei Wang, ; Xiao-Jian Wu, ; Feng Gao,
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Shao D, Li Y, Wu J, Zhang B, Xie S, Zheng X, Jiang Z. An m6A/m5C/m1A/m7G-Related Long Non-coding RNA Signature to Predict Prognosis and Immune Features of Glioma. Front Genet 2022; 13:903117. [PMID: 35692827 PMCID: PMC9178125 DOI: 10.3389/fgene.2022.903117] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 05/03/2022] [Indexed: 01/14/2023] Open
Abstract
Background: Gliomas are the most common and fatal malignant type of tumor of the central nervous system. RNA post-transcriptional modifications, as a frontier and hotspot in the field of epigenetics, have attracted increased attention in recent years. Among such modifications, methylation is most abundant, and encompasses N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1 methyladenosine (m1A), and 7-methylguanosine (m7G) methylation.Methods: RNA-sequencing data from healthy tissue and low-grade glioma samples were downloaded from of The Cancer Genome Atlas database along with clinical information and mutation data from glioblastoma tumor samples. Forty-nine m6A/m5C/m1A/m7G-related genes were identified and an m6A/m5C/m1A/m7G-lncRNA signature of co-expressed long non-coding RNAs selected. Least absolute shrinkage and selection operator Cox regression analysis was used to identify 12 m6A/m5C/m1A/m7G-related lncRNAs associated with the prognostic characteristics of glioma and their correlation with immune function and drug sensitivity analyzed. Furthermore, the Chinese Glioma Genome Atlas dataset was used for model validation.Results: A total of 12 m6A/m5C/m1A/m7G-related genes (AL080276.2, AC092111.1, SOX21-AS1, DNAJC9-AS1, AC025171.1, AL356019.2, AC017104.1, AC099850.3, UNC5B-AS1, AC006064.2, AC010319.4, and AC016822.1) were used to construct a survival and prognosis model, which had good independent prediction ability for patients with glioma. Patients were divided into low and high m6A/m5C/m1A/m7G-LS groups, the latter of which had poor prognosis. In addition, the m6A/m5C/m1A/m7G-LS enabled improved interpretation of the results of enrichment analysis, as well as informing immunotherapy response and drug sensitivity of patients with glioma in different subgroups.Conclusion: In this study we constructed an m6A/m5C/m1A/m7G-LS and established a nomogram model, which can accurately predict the prognosis of patients with glioma and provides direction toward promising immunotherapy strategies for the future.
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21
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Lin H, Xia L, Lian J, Chen Y, Zhang Y, Zhuang Z, Cai H, You J, Guan G. Delineation of colorectal cancer ligand-receptor interactions and their roles in the tumor microenvironment and prognosis. J Transl Med 2021; 19:497. [PMID: 34876143 PMCID: PMC8650275 DOI: 10.1186/s12967-021-03162-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 11/22/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Immunotherapies targeting ligand-receptor interactions (LRIs) are advancing rapidly in the treatment of colorectal cancer (CRC), and LRIs also affect many aspects of CRC development. However, the pattern of LRIs in CRC and their effect on tumor microenvironment and clinical value are still unclear. METHODS We delineated the pattern of LRIs in 55,539 single-cell RNA sequencing (scRNA-seq) samples from 29 patients with CRC and three bulk RNA-seq datasets containing data from 1411 CRC patients. Then the influence of tumor microenvironment, immunotherapy and prognosis of CRC patients were comprehensively investigated. RESULTS We calculated the strength of 1893 ligand-receptor pairs between 25 cell types to reconstruct the spatial structure of CRC. We identified tumor subtypes based on LRIs, revealed the relationship between the subtypes and immunotherapy efficacy and explored the ligand-receptor pairs and specific targets affecting the abundance of tumor-infiltrating lymphocytes. Finally, a prognostic model based on ligand-receptor pairs was constructed and validated. CONCLUSION Overall, through the comprehensive and in-depth investigation of the existing ligand-receptor pairs, this study provides new ideas for CRC subtype classification, a new risk screening tool for CRC patients, and potential ligand-receptor pair targets and pathways for CRC therapy.
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Affiliation(s)
- Hexin Lin
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou City, 350001, Fujian, China
| | - Lu Xia
- Xiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University. School of Medicine, Xiamen University, Xiamen, China
| | - Jiabian Lian
- Department of Laboratory Medicine, Xiamen Key Laboratory of Genetic Testing, The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Yinan Chen
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Yiyi Zhang
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou City, 350001, Fujian, China
| | - Zhicheng Zhuang
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou City, 350001, Fujian, China
| | - HuaJun Cai
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou City, 350001, Fujian, China
| | - Jun You
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Xiamen University, Xiamen, China.,School of Clinical Medicine, Fujian Medical University, Fuzhou, China
| | - Guoxian Guan
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou City, 350001, Fujian, China.
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22
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Shi X, Tu S, Zhu L. Risk characteristics with seven epithelial-mesenchymal transition-related genes are used to predict the prognosis of patients with hepatocellular carcinoma. J Gastrointest Oncol 2021; 12:1884-1894. [PMID: 34532136 DOI: 10.21037/jgo-21-394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 08/16/2021] [Indexed: 11/06/2022] Open
Abstract
Background Epithelial-mesenchymal transition (EMT)-related genes (ERGs) have been shown to play an important role in cancer invasion, tumor resistance, and tumor metastasis of hepatocellular carcinoma. This study sought to examine the prognostic value of ERGs and other pre-hepatoma genes. Methods Relevant data from The Cancer Genome Atlas (TCGA) were analyzed and synthesized. Specifically, 1,014 ERGs were downloaded and subject to a gene set enrichment analysis; 318 different EAG expressions were found, and the possible molecular mechanism of EAG was predicted by GO analysis and KEGG analysis. To determine the prediction of ERGS, a Cox regression model was used to establish a risk hypothesis. Based on risk patterns, patients were divided into high- or low-risk groups. Kaplan-Meier and receiver operating characteristic (ROC) curves confirmed the predictive value of the model. Results Seven prognostically relevant ERGs (i.e., ECT2, EZH2, MYCN, ROR2, SPP1, SQSTM1, and STC2) were identified. Using Cox's regression analysis method, appropriate cases were selected to establish a new risk prediction model. Under the risk model, the overall survival rate of the low-risk group samples was higher than that of the high-risk group samples (P<0.00001). Conclusions In short, we developed a risk model for liver cancer based on ERGs terminology. This model improve the postpartum treatment of patients with liver cancer.
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Affiliation(s)
- Xianqing Shi
- Department of Oncology, Liyang People's Hospital, Liyang, China
| | - Shuhuan Tu
- Department of Oncology, Liyang People's Hospital, Liyang, China
| | - Liqun Zhu
- Department of Oncology, Liyang People's Hospital, Liyang, China
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Zhao F, Wang M, Zhu J. Hypoxia-related lncRNAs to build prognostic classifier and reveal the immune characteristics of EGFR wild type and low expression of PD-L1 squamous and adenocarcinoma NSCLC. Cancer Med 2021; 10:6099-6113. [PMID: 34250747 PMCID: PMC8419766 DOI: 10.1002/cam4.4126] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/16/2021] [Accepted: 06/25/2021] [Indexed: 02/05/2023] Open
Abstract
Background Recently, the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have achieved remarkable survival benefits in non‐small cell lung cancer (NSCLC) treatment. However, epidermal growth factor receptor (EGFR) wild type and low expression of programmed death‐ligand 1 (PD‐L1) NSCLC remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a hypoxia‐related lncRNAs (hypolncRNAs) classifier that could successfully identify the high‐risk patients and reveal its underlying molecular immunology characteristics. Methods By identifying the bottom 25% PD‐L1 expression level as low expression of PD‐L1 and removing EGFR mutant samples, a total of 222 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) samples and 93 adjacent non‐tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). A 0 or 1 matrix was constructed by cyclically pairing hypoxia‐related long non‐coding RNAs (hypolncRNAs) and divided into the train set and test set. The univariate Cox regression analysis determined the prognostic hypolncRNAs pairs. Then, the prognostic classifier contained nine hypolncRNAs pairs which were generated by Lasso regression and multivariate Cox analysis. It successfully stratified EGFR wild type and low expression of PD‐L1 squamous and adenocarcinoma NSCLC (double‐negative LUAD and LUSC) patients into the high‐ and low‐risk groups, whose accuracy was proved by the time‐dependent receiver operating characteristic (ROC) curve. Furthermore, diverse acknowledged immunology methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT‐ABS, CIBERSORT, and the single‐sample gene set enrichment analysis (ssGSEA) revealed its underlying antitumor immunosuppressive status in the high‐risk patients. Conclusions It is noteworthy that hypolncRNAs are associated with the survival of double‐negative LUAD and LUSC patients, for which the possible mechanism is inhibiting the antitumor immune process.
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Affiliation(s)
- Fang Zhao
- Department of Intensive Care Unit, The Peoples Hospital of Tongliang District, Chongqing, China
| | - Min Wang
- Department of Respiratory and Geriatrics, Chongqing Public Health Medical Center, Chongqing, China
| | - Jie Zhu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
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Chen HM, MacDonald JA. Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis. iScience 2021; 24:102831. [PMID: 34368650 PMCID: PMC8326195 DOI: 10.1016/j.isci.2021.102831] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 06/04/2021] [Accepted: 07/07/2021] [Indexed: 12/13/2022] Open
Abstract
Colon adenocarcinoma is a prevalent malignancy with significant mortality. Hence, the identification of molecular biomarkers with prognostic significance is important for improved treatment and patient outcomes. Clinical traits and RNA-Seq of 551 patient samples in the UCSC Toil Recompute Compendium of The Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (primary_site = colon) were used for weighted gene co-expression network analysis to reveal the association between gene networks and cancer cell invasion. One module, containing 151 genes, was significantly correlated with lymphatic invasion, a histopathological feature of higher risk colon cancer. DAPK3 (death-associated protein kinase 3) was identified as the pseudohub of the module. Gene ontology identified gene enrichment related to cytoskeletal organization and apoptotic signaling processes, suggesting modular involvement in tumor cell survival, migration, and epithelial-mesenchymal transformation. Although DAPK3 expression was reduced in patients with colon cancer, high expression of DAPK3 was significantly correlated with greater lymphatic invasion and poor overall survival.
WCGNA reveals a gene module linked to lymphatic invasion in colon adenocarcinoma DAPK3 is a pseudohub gene with differential expression in colon cancer Gene ontology identified relationships to cytoskeletal organization and apoptosis DAPK3 was correlated with lymphatic invasion and poor overall survival
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Affiliation(s)
- Huey-Miin Chen
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB T2N 4Z6, Canada
| | - Justin A MacDonald
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB T2N 4Z6, Canada
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Huang C, Zhao J, Zhu Z. Prognostic Nomogram of Prognosis-Related Genes and Clinicopathological Characteristics to Predict the 5-Year Survival Rate of Colon Cancer Patients. Front Surg 2021; 8:681721. [PMID: 34222322 PMCID: PMC8242155 DOI: 10.3389/fsurg.2021.681721] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 05/13/2021] [Indexed: 12/18/2022] Open
Abstract
Background: The Cancer Genome Atlas (TCGA) has established a genome-wide gene expression profile, increasing our understanding of the impact of tumor heredity on clinical outcomes. The aim of this study was to construct a nomogram using data from the TCGA regarding prognosis-related genes and clinicopathological characteristics to predict the 5-years survival rate of colon cancer (CC) patients. Methods: Kaplan-Meier and Cox regression analyses were used to identify genes associated with the 5-years survival rate of CC patients. Cox regression was used to analyze the relationship between the clinicopathological features and prognostic genes and overall survival rates in patients with CC and to identify independent risk factors for the prognosis of CC patients. A nomogram for predicting the 5-years survival rate of CC patients was constructed by R software. Results: A total of eight genes (KCNJ14, CILP2, ATP6V1G2, GABRD, RIMKLB, SIX2, PLEKHA8P1, and MPP2) related to the 5-years survival of rate CC patients were identified. Age, stage, and PLEKHA8P1 were independent risk factors for the 5-years survival rate in patients with CC. The accuracy, sensitivity and specificity of the nomogram model constructed by age, TNM staging, and PLEKHA8P1 for predicting the 5-years survival of rate CC patients were 83.3, 83.97, and 85.79%, respectively. Conclusion: The nomogram can correctly predict the 5-year survival rate of patients with CC, thus aiding the individualized decision-making process for patients with CC.
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Affiliation(s)
| | | | - Zhengming Zhu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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Liu J, Li Y, Gan Y, Xiao Q, Tian R, Shu G, Yin G. Identification of ZNF26 as a Prognostic Biomarker in Colorectal Cancer by an Integrated Bioinformatic Analysis. Front Cell Dev Biol 2021; 9:671211. [PMID: 34178996 PMCID: PMC8226143 DOI: 10.3389/fcell.2021.671211] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/11/2021] [Indexed: 01/12/2023] Open
Abstract
The dysregulation of transcriptional factors (TFs) leads to malignant growth and the development of colorectal cancer (CRC). Herein, we sought to identify the transcription factors relevant to the prognosis of colorectal cancer patients. We found 526 differentially expressed TFs using the TCGA database of colorectal cancer patients (n = 544) for the differential analysis of TFs (n = 1,665) with 210 upregulated genes as well as 316 downregulated genes. Subsequently, GO analysis and KEGG pathway analysis were performed for these differential genes for investigating their pathways and function. At the same time, we established a genetic risk scoring model for predicting the overall survival (OS) by using the mRNA expression levels of these differentially regulated TFs, and defined the CRC into low and high-risk categories which showed significant survival differences. The genetic risk scoring model included four high-risk genes (HSF4, HEYL, SIX2, and ZNF26) and two low-risk genes (ETS2 and SALL1), and validated the OS in two GEO databases (p = 0.0023 for the GSE17536, p = 0.0193 for the GSE29623). To analyze the genetic and epigenetic changes of these six risk-related TFs, a unified bioinformatics analysis was conducted. Among them, ZNF26 is progressive in CRC and its high expression is linked with a poor diagnosis as well. Knockdown of ZNF26 inhibits the proliferative capacity of CRC cells. Moreover, the positive association between ZNF26 and cyclins (CDK2, CCNE2, CDK6, CHEK1) was also identified. Therefore, as a novel biomarker, ZNF26 may be a promising candidate in the diagnosis and prognostic evaluation of colorectal cancer.
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Affiliation(s)
- Jiaxin Liu
- Department of Pathology, Xiangya Hospital, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Yimin Li
- Department of Pathology, Xiangya Hospital, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Yaqi Gan
- Department of Pathology, Xiangya Hospital, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Qing Xiao
- Department of Pathology, Xiangya Hospital, School of Basic Medical Sciences, Central South University, Changsha, China
| | - Ruotong Tian
- School of Basic Medical Sciences, Central South University, Changsha, China
| | - Guang Shu
- School of Basic Medical Sciences, Central South University, Changsha, China
| | - Gang Yin
- Department of Pathology, Xiangya Hospital, School of Basic Medical Sciences, Central South University, Changsha, China.,China-Africa Research Center of Infectious Diseases, School of Basic Medical Sciences, Central South University, Changsha, China
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27
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Zhang Y, Yang F, Peng X, Li X, Luo N, Zhu W, Fu M, Li Q, Hu G. Hypoxia Constructing the Prognostic Model of Colorectal Adenocarcinoma and Related to the Immune Microenvironment. Front Cell Dev Biol 2021; 9:665364. [PMID: 33959617 PMCID: PMC8093637 DOI: 10.3389/fcell.2021.665364] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/26/2021] [Indexed: 01/05/2023] Open
Abstract
Background: Hypoxia is a common phenomenon in solid tumors, which plays an important role in tumor proliferation, apoptosis, angiogenesis, invasion and metastasis, energy metabolism and chemoradiotherapy resistance. However, comprehensive analysis of hypoxia markers in colorectal adenocarcinoma (COAD) is still lacking. And there is a need for mechanism exploration and clinical application. Methods: The gene expression, mutation and clinical data of COAD were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, respectively. Tumor samples from TCGA were randomly divided into the training and internal validation groups, while tumor samples from GEO were used as the external validation group. Univariate COX—LASSO—multivariate COX method was applied to construct the prognostic model. We clustered all TCGA tumor samples into high, medium and low hypoxia groups, evaluated the correlation between hypoxia degree and immunoactivity, and explored the combined effect of mutation for common target genes and model riskscore on survival in COAD patients. Finally, we developed a dynamic nomograph App online for direct clinical application and carried out multiple validations of the prognostic model. Results: Our hypoxia-related prognostic model for COAD patients is accurate and has been successfully validated internally and externally. Single Sample Gene Set Enrichment Analysis (ssGSEA) and Gene Set Enrichment Analysis (GSEA) results suggest that for COAD patients with higher hypoxia, the stronger the associated immunosuppressive activity, providing a possible mechanism for the lower survival rate. Finally, the dynamic nomograph App online enhances the clinical translational significance of the study. Conclusion: In this study, an accurate prognostic model for COAD patients was established and validated. In addition, our innovative findings include correlations between hypoxia levels and immune activity, as well as an in-depth exploration of common target gene mutations.
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Affiliation(s)
- Yuanyuan Zhang
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Yang
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaohong Peng
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaoyu Li
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Na Luo
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenjun Zhu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Min Fu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qianxia Li
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guangyuan Hu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Improving the Prognosis of Colon Cancer through Knowledge-Based Clinical-Molecular Integrated Analysis. BIOMED RESEARCH INTERNATIONAL 2021; 2021:9987819. [PMID: 33928165 PMCID: PMC8051523 DOI: 10.1155/2021/9987819] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 03/19/2021] [Accepted: 03/23/2021] [Indexed: 12/25/2022]
Abstract
Background Colon cancer has high morbidity and mortality rates among cancers. Existing clinical staging systems cannot accurately assess the prognostic risk of colon cancer patients. This study was aimed at improving the prognostic performance of the colon cancer clinical staging system through knowledge-based clinical-molecular integrated analysis. Methods 374 samples from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset were used as the discovery set. 98 samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset were used as the validation set. After converting gene expression data into pathway dysregulation scores (PDSs), the random survival forest and Cox model were used to identify the best prognostic supplementary factors. The corresponding clinical-molecular integrated prognostic model was built, and the improvement of prognostic performance was assessed by comparing with the clinical prognostic model. Results The PDS of 14 pathways played important roles in prognostic prediction together with clinical prognostic factors through the random survival forest. Further screening with the Cox model revealed that the PDS of the pathway hsa00532 was the best clinical prognostic supplementary factor. The integrated prognostic model constructed with clinical factors and the identified molecular factor was superior to the clinical prognostic model in discriminative performance. Kaplan-Meier (KM) curves of patients grouped by PDS suggested that patients with a higher PDS had a poorer prognosis, and stage II patients could be distinctly distinguished. Conclusions Based on the knowledge-based clinical-molecular integrated analysis, a clinical-molecular integrated prognostic model and corresponding nomogram for colon cancer overall survival prognosis was built, which showed better prognostic performance than the clinical prognostic model. The PDS of the pathway hsa00532 is a considerable clinical prognostic supplementary factor for colon cancer and may represent a potential prognostic marker for stage II colon cancer. The PDS calculation involves only 16 genes, which supports its potential for clinical application.
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Wang W, Wang L, Xie X, Yan Y, Li Y, Lu Q. A gene-based risk score model for predicting recurrence-free survival in patients with hepatocellular carcinoma. BMC Cancer 2021; 21:6. [PMID: 33402113 PMCID: PMC7786458 DOI: 10.1186/s12885-020-07692-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 11/25/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) remains the most frequent liver cancer, accounting for approximately 90% of primary liver cancers worldwide. The recurrence-free survival (RFS) of HCC patients is a critical factor in devising a personal treatment plan. Thus, it is necessary to accurately forecast the prognosis of HCC patients in clinical practice. METHODS Using The Cancer Genome Atlas (TCGA) dataset, we identified genes associated with RFS. A robust likelihood-based survival modeling approach was used to select the best genes for the prognostic model. Then, the GSE76427 dataset was used to evaluate the prognostic model's effectiveness. RESULTS We identified 1331 differentially expressed genes associated with RFS. Seven of these genes were selected to generate the prognostic model. The validation in both the TCGA cohort and GEO cohort demonstrated that the 7-gene prognostic model can predict the RFS of HCC patients. Meanwhile, the results of the multivariate Cox regression analysis showed that the 7-gene risk score model could function as an independent prognostic factor. In addition, according to the time-dependent ROC curve, the 7-gene risk score model performed better in predicting the RFS of the training set and the external validation dataset than the classical TNM staging and BCLC. Furthermore, these seven genes were found to be related to the occurrence and development of liver cancer by exploring three other databases. CONCLUSION Our study identified a seven-gene signature for HCC RFS prediction that can be used as a novel and convenient prognostic tool. These seven genes might be potential target genes for metabolic therapy and the treatment of HCC.
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Affiliation(s)
- Wenhua Wang
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China.,Department of Biostatistics and Epidemiology, School of Public Health, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Lingchen Wang
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China.,Department of Biostatistics and Epidemiology, School of Public Health, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Xinsheng Xie
- Center for Experimental Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Yehong Yan
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Yue Li
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China.,Department of Biostatistics and Epidemiology, School of Public Health, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Quqin Lu
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China. .,Department of Biostatistics and Epidemiology, School of Public Health, Nanchang University, Nanchang, 330006, Jiangxi, China.
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Xu K, He J, Zhang J, Liu T, Yang F, Ren T. A novel prognostic risk score model based on immune-related genes in patients with stage IV colorectal cancer. Biosci Rep 2020; 40:BSR20201725. [PMID: 33034614 PMCID: PMC7584813 DOI: 10.1042/bsr20201725] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 09/09/2020] [Accepted: 10/09/2020] [Indexed: 12/24/2022] Open
Abstract
PURPOSE The aims of the present study were to explore immune-related genes (IRGs) in stage IV colorectal cancer (CRC) and construct a prognostic risk score model to predict patient overall survival (OS), providing a reference for individualized clinical treatment. METHODS High-throughput RNA-sequencing, phenotype, and survival data from patients with stage IV CRC were downloaded from TCGA. Candidate genes were identified by screening for differentially expressed IRGs (DE-IRGs). Univariate Cox regression, LASSO, and multivariate Cox regression analyses were used to determine the final variables for construction of the prognostic risk score model. GSE17536 from the GEO database was used as an external validation dataset to evaluate the predictive power of the model. RESULTS A total of 770 candidate DE-IRGs were obtained, and a prognostic risk score model was constructed by variable screening using the following 12 genes: FGFR4, LGR6, TRBV12-3, NUDT6, MET, PDIA2, ORM1, IGKV3D-20, THRB, WNT5A, FGF18, and CCR8. In the external validation set, the survival prediction C-index was 0.685, and the AUC values were 0.583, 0.731, and 0.837 for 1-, 2- and 3-year OS, respectively. Univariate and multivariate Cox regression analyses demonstrated that the risk score model was an independent prognostic factor for patients with stage IV CRC. High- and low-risk patient groups had significant differences in the expression of checkpoint coding genes (ICGs). CONCLUSION The prognostic risk score model for stage IV CRC developed in the present study based on immune-related genes has acceptable predictive power, and is closely related to the expression of ICGs.
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Affiliation(s)
- Ke Xu
- Department of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China
| | - Jie He
- Department of Pulmonary and Critical Care Medicine, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China
| | - Jie Zhang
- Department of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China
| | - Tao Liu
- Department of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China
| | - Fang Yang
- Department of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China
| | - Tao Ren
- Department of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People’s Republic of China
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Xiong C, Wang G, Bai D. A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes. Bioengineered 2020; 11:1034-1046. [PMID: 32951492 PMCID: PMC8291854 DOI: 10.1080/21655979.2020.1822715] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Several epithelial-mesenchymal transition (EMT)-associated genes (EAGs) have been confirmed to correlate with the prognosis of hepatocellular carcinoma (HCC) patients. Herein, we explored the value of EAGs in the prognosis of HCC relying on data from The Cancer Genome Atlas (TCGA) database. A total of 200 EMT-associated genes were downloaded from the Gene set enrichment analysis (GSEA) website. Moreover, 96 differentially expressed EAGs were identified. Using Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we forecasted the potential molecular mechanisms of EAGs. To identify prognostic EAGs, Cox regression was used in developing a prognostic risk model. Then, the Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the prognostic significance of the model. A total of 5 prognostic correlated EAGs (P3H1, SPP1, MMP1, LGALS1, and ITGB5) were screened via Cox regression, which provided the basis for developing a novel prognostic risk model. Based on the risk model, patients were subdivided into high-risk and low-risk groups. The overall survival of the low-risk group was better compared to the high-risk group (P < 0.00001). The ROC curve of the risk model showed a higher AUC (Area under Curve) (AUC = 0.723) compared to other clinical features (AUC ≤ 0.511). A nomogram based on this model was constructed to predict the 1-year, 2-year, and 3-year overall survival rates (OS) of patients. Conclusively, we developed a novel HCC prognostic risk model based on the expression of EAGs, which help advance the prognostic management of HCC patients. Abbreviations: HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; EMT: epithelial-mesenchymal transition; EAGs: EMT-associated genes; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PPI: protein-protein interaction; TF: transcription factor; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; FDR: false discovery rate; TNM: Tumor size/lymph nodes/distance metastasis.
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Affiliation(s)
- Chen Xiong
- Dalian Medical University , Dalian, P.R. China
| | - Guifu Wang
- Dalian Medical University , Dalian, P.R. China
| | - Dousheng Bai
- Department of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University , Yangzhou, P.R. China
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Li W, Yu W, Jiang X, Gao X, Wang G, Jin X, Zhao Z, Liu Y. The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer. Front Genet 2020; 11:583. [PMID: 32714366 PMCID: PMC7344331 DOI: 10.3389/fgene.2020.00583] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 05/13/2020] [Indexed: 12/11/2022] Open
Abstract
Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop and validate a composite clinicopathologic–genomic nomogram using The Cancer Genome Atlas (TCGA) database. To construct the ceRNA network in CRC, we analyzed the mRNAseq, miRNAseq data, and clinical information from TCGA database. LncRNA, miRNA, and mRNA signatures were identified to construct risk score as independent indicators of the prognostic value in CRC patients. A composite clinicopathologic–genomic nomogram was developed to predict the overall survival (OS). One hundred sixty-one CRC-specific lncRNAs, 97 miRNAs, and 161 mRNAs were identified to construct the ceRNA network. Multivariate Cox proportional hazards regression analysis indicated that nine-lncRNA signatures, eight-miRNA signatures, and five-mRNA signatures showed a significant prognostic value for CRC. Furthermore, a clinicopathologic–genomic nomogram was constructed in the primary cohort, which performed well in both the primary and validation sets. This study presents a nomogram that incorporates the CRC-specific ceRNA expression profile, clinical features, and pathological factors, which demonstrate its excellent differentiation and risk stratification in predicting OS in CRC patients.
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Affiliation(s)
- Wei Li
- Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Weifang Yu
- Departments of Endoscopy Center, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xia Jiang
- Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xian Gao
- Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Guiqi Wang
- Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xiaojing Jin
- Department of Emergency, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Zengren Zhao
- Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yuegeng Liu
- Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang, China
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Zhang YF, Meng LB, Hao ML, Yang JF, Zou T. Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke. Front Neurol 2020; 11:184. [PMID: 32265825 PMCID: PMC7105800 DOI: 10.3389/fneur.2020.00184] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 02/25/2020] [Indexed: 12/19/2022] Open
Abstract
Atrial fibrillation (AF) increases the risk of ischemic stroke and systemic arterial embolism. However, the risk factors or predictors of stroke in AF patients have not been clarified. Therefore, it is necessary to find effective diagnostic and therapeutic targets. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network and significant module, and the receiver operator characteristic (ROC) curve analysis were performed. A total of 524 DEGs were common to both datasets. Analysis of KEGG pathways indicated that the top canonical pathways associated with DEGs were ubiquitin-mediated proteolysis, endocytosis, spliceosome, and so on. Ten hub genes (SMURF2, CDC42, UBE3A, RBBP6, CDC5L, NEDD4L, UBE2D2, UBE2B, UBE2I, and MAPK1) were identified from the PPI network and were significantly associated with a diagnosis of atrial fibrillation and stroke (AFST). In summary, a total of 524 DEGs and 10 hub genes were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. These genes may serve as the target of early diagnosis or treatment of AF complicated by stroke.
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Affiliation(s)
- Yan-Fei Zhang
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Ling-Bing Meng
- Neurology Department, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Meng-Lei Hao
- Department of Geriatric Medicine, Affiliated Hospital of Qinghai University, Xining, China
| | - Jie-Fu Yang
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Tong Zou
- Department of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, China
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Lu YJ, Wang H, Fang LY, Wang WJ, Song W, Wang Y, Huang YQ, Din ZL. A nomogram for predicting overall survival in patients with uterine leiomyosarcoma: a SEER population-based study. Future Oncol 2020; 16:573-584. [PMID: 32141309 DOI: 10.2217/fon-2019-0674] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Aim: To establish and validate a nomogram for the estimation of overall survival of patients with uterine leiomyosarcoma (uLMS). Methods: Information on patients diagnosed as uLMS was retrospectively retrieved from the Surveillance, Epidemiology, and End Results database. The patients were randomly assigned into the training and the validation cohorts. Univariate and multivariate analyses were used to determine the independent prognostic factors for building a nomogram for predicting overall survival. The predictive accuracy was evaluated based on the concordance indices and the calibration plots. Results: A nomogram that combined age, marital status, tumor size, Surveillance, Epidemiology, and End Result stage, surgery and radiation was established. The internal and external concordance indices were 0.748 and 0.745, respectively. The calibration plots approached 45 degrees. Conclusion: The nomogram might be an effective tool for predicting the survival of patients with uLMS.
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Affiliation(s)
- Yu-Jie Lu
- Department of Oncology, The First Affiliated Hospital of Soochow University, Suzhou 215006, PR China
| | - Han Wang
- Department of Oncology, Jining Cancer Hospital, Jining, PR China
| | - Lin-Yan Fang
- Department of General Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215001, PR China
| | - Wen-Jie Wang
- Department of Radio-Oncology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215001, PR China
| | - Wei Song
- Department of Intervention & Vascular Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215001, PR China
| | - Ying Wang
- Department of Oncology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215001, PR China
| | - Yue-Qing Huang
- Department of General Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215001, PR China
| | - Zhi-Liang Din
- Department of Neurosurgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu 215001, PR China
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Wu Y, Zhang S, Yan J. IRF1 association with tumor immune microenvironment and use as a diagnostic biomarker for colorectal cancer recurrence. Oncol Lett 2020; 19:1759-1770. [PMID: 32194669 PMCID: PMC7039159 DOI: 10.3892/ol.2020.11289] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 11/27/2019] [Indexed: 12/13/2022] Open
Abstract
Colorectal cancer (CRC) is considered to be one of the most lethal cancer types globally, and its recurrence is a major treatment challenge. Identifying the factors involved when determining the risk of CRC recurrence is required to improve personalized therapy for patients with CRC. Based on the GSE39582 dataset, the present study demonstrated that a higher ratio of M1 macrophages and activated memory CD4+ T cells indicated a better recurrence-free survival (RFS) time for CRC, using CIBERSORT and Pearson's correlation analysis. Through weighted correlation network analysis (WGCNA), an immune-associated module was identified that was significantly positively correlated with the ratio of M1 macrophages and activated memory CD4+ T cells. In this module, using WGCNA and a protein-protein interaction network, interferon regulatory factor 1 (IRF1), chemokine ligand 5, ubiquitin/ISG15-conjugating enzyme E2 L6, guanylate binding protein 1 and interleukin 2 receptor subunit beta were identified as hub genes. Among these genes, univariate Cox and multivariate Cox analysis revealed that IRF1 may be a potential diagnostic biomarker for RFS in patients with CRC. This was further validated using The Cancer Genome Atlas data. Gene set enrichment analysis demonstrated that IRF1 influenced the genes and pathways that are associated with immune cell recruitment and activation. Additionally, the DNA methylation of cg27587780 and cg15375424 CpG sites in the IRF1 gene region was indicated to be negatively correlated with IRF1 mRNA expression and positively correlated with the recurrence of CRC. Collectively, the results of the present study demonstrated that IRF1 may be a potential diagnostic biomarker for RFS in patients with CRC.
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Affiliation(s)
- Yanfang Wu
- Department of Gastroenterology, The Fourth People's Hospital of Shaanxi, Xi'an, Shanxi 710032, P.R. China
| | - Shuju Zhang
- Hunan Children's Research Institute, Hunan Children's Hospital, University of South China, Changsha, Hunan 410007, P.R. China
| | - Jun Yan
- Center of Hepatobiliary Pancreatic Disease, Beijing Tsinghua Changgung Hospital, Beijing 102218, P.R. China
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Abou Khouzam R, Goutham HV, Zaarour RF, Chamseddine AN, Francis A, Buart S, Terry S, Chouaib S. Integrating tumor hypoxic stress in novel and more adaptable strategies for cancer immunotherapy. Semin Cancer Biol 2020; 65:140-154. [PMID: 31927131 DOI: 10.1016/j.semcancer.2020.01.003] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 12/10/2019] [Accepted: 01/07/2020] [Indexed: 12/14/2022]
Abstract
Immunotherapy is poised to become an increasingly utilized therapy in the treatment of cancer. However, several abnormalities in the tumor microenvironment (TME) that can thwart the efficacy of immunotherapies have been established. Microenvironmental hypoxia is a determining factor in shaping aggressiveness, metastatic potential and treatment resistance of solid tumors. The characterization of this phenomenon could prove beneficial for determining a patient's treatment path and for the introduction of novel targetable factors that can enhance therapeutic outcome. Indeed, the ablation of hypoxia has the potential to sensitize tumors to immunotherapy by metabolically remodeling their microenvironment. In this review, we discuss the intrinsic contributions of hypoxia to cellular plasticity, heterogeneity, stemness and genetic instability in the context of immune escape. In addition, we will shed light on how managing hypoxia can ameliorate response to immunotherapy and how integrating hypoxia gene signatures could play a role in this pursuit.
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Affiliation(s)
- Raefa Abou Khouzam
- Thumbay Research Institute for Precision Medicine, Gulf Medical University, Ajman, 4184, United Arab Emirates.
| | - Hassan Venkatesh Goutham
- Thumbay Research Institute for Precision Medicine, Gulf Medical University, Ajman, 4184, United Arab Emirates.
| | - Rania Faouzi Zaarour
- Thumbay Research Institute for Precision Medicine, Gulf Medical University, Ajman, 4184, United Arab Emirates.
| | - Ali N Chamseddine
- Département d'Oncologie Médicale, Gustave Roussy Cancer Campus Grand Paris, Villejuif, France.
| | - Amirtharaj Francis
- Thumbay Research Institute for Precision Medicine, Gulf Medical University, Ajman, 4184, United Arab Emirates.
| | - Stéphanie Buart
- INSERM UMR 1186, Integrative Tumor Immunology and Genetic Oncology, Gustave Roussy, EPHE, Faculty. De médecine Univ. Paris-Sud, University Paris-Saclay, Villejuif F-94805, France
| | - Stéphane Terry
- INSERM UMR 1186, Integrative Tumor Immunology and Genetic Oncology, Gustave Roussy, EPHE, Faculty. De médecine Univ. Paris-Sud, University Paris-Saclay, Villejuif F-94805, France.
| | - Salem Chouaib
- Thumbay Research Institute for Precision Medicine, Gulf Medical University, Ajman, 4184, United Arab Emirates; INSERM UMR 1186, Integrative Tumor Immunology and Genetic Oncology, Gustave Roussy, EPHE, Faculty. De médecine Univ. Paris-Sud, University Paris-Saclay, Villejuif F-94805, France.
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