|
1
|
Wu D, Hao X, Gong Z, Cui R, Xia L, Liu L. Risk factors and clinical risk stratification of distant metastasis in early-stage lung cancer in never smokers. World J Surg Oncol 2025; 23:238. [PMID: 40533740 PMCID: PMC12175467 DOI: 10.1186/s12957-025-03892-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2025] [Accepted: 06/08/2025] [Indexed: 06/22/2025] Open
Abstract
BACKGROUND Risk factors for distant metastasis in early-stage lung cancer in never smokers (LCINS) remain poorly understood. This study aimed to identify key risk factors and to develop a clinical risk stratification model for early-stage LCINS. METHODS We retrospectively analyzed patients diagnosed with early-stage LCINS at West China Hospital, Sichuan University, from 2015 to 2020. Univariable and multivariable Cox regression analyses were performed to identify independent risk factors for distant metastasis. A predictive model was developed and internally validated using bootstrap resampling, with performance assessed by the concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis. RESULTS A total of 1,406 patients with pathological stage I-II LCINS were included, among whom 76 (5.41%) developed distant metastasis during follow-up. Multivariable Cox regression analysis revealed that independent risk factors included advanced pathological T and N stages, higher consolidation-to-tumor ratio, and histologic subtype, particularly solid/micropapillary predominant adenocarcinoma. Based on these predictors, a predictive model was developed, demonstrating strong discrimination with a C-index of 0.799 and AUC values of 0.809, 0.791, and 0.783 for predicting 1-, 2-, and 3-year distant metastasis, respectively. Calibration and decision curve analyses confirmed the reliability and clinical utility of the model. CONCLUSIONS This study identified risk factors and developed a clinical risk stratification model for distant metastasis in early-stage LCINS. This validated model enables risk stratification and personalized monitoring to facilitate early detection of distant recurrence in LCINS.
Collapse
Affiliation(s)
- Dongsheng Wu
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Xiaohu Hao
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Zhipeng Gong
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Ruichen Cui
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Liang Xia
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China
| | - Lunxu Liu
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, Sichuan, China.
| |
Collapse
|
|
2
|
Wu B, Zhu Y, Hu Z, Wu J, Zhou W, Si M, Cao X, Wu Z, Zhang W. Machine learning predictive models and risk factors for lymph node metastasis in non-small cell lung cancer. BMC Pulm Med 2024; 24:526. [PMID: 39438836 PMCID: PMC11515794 DOI: 10.1186/s12890-024-03345-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 10/15/2024] [Indexed: 10/25/2024] Open
Abstract
BACKGROUND The prognosis of non-small cell lung cancer (NSCLC) is substantially affected by lymph node metastasis (LNM), but there are no noninvasive, inexpensive methods of relatively high accuracy available to predict LNM in NSCLC patients. METHODS Clinical data on NSCLC patients were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Risk factors for LNM were recognized LASSO and multivariate logistic regression. Six predictive models were constructed with machine learning based on risk factors. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the model. Subgroup analysis with different T-stages was performed on an optimal model. A webpage LNM risk calculator for optimal model was built using the Shinyapps.io platform. RESULTS We enrolled 64,012 NSCLC patients, of whom 26,611 (41.57%) had LNM. Using multivariate logistic regression, we finally identified 10 independent risk factors for LNM: age, sex, race, histology, primary site, grade, T stage, M stage, tumor size, and bone metastases. GLM is the optimal model among all six machine learning models in both the training and validation cohorts. Subgroup analyses revealed that GLM has good predictability for populations with different T staging. A webpage LNM risk calculator based on GLM was posted on the shinyapps.io platform ( https://wubopredict.shinyapps.io/dynnomapp/ ). CONCLUSION The predictive model based on GLM can be used to precisely predict the probability of LNM in NSCLC patients, which was proven effective in all subgroup analyses according to T staging.
Collapse
Affiliation(s)
- Bo Wu
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
- Department of Cardiac Surgery, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Yihui Zhu
- School of Data Science, Chinese University of Hong Kong (Shenzhen), Shenzhen, China
| | - Zhuozheng Hu
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Jiajun Wu
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Weijun Zhou
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Maoyan Si
- Department of Thoracic Surgery, The First Affiliated Hospital of Gannan Medical University, 23 Qingnian Road, Zhanggong District, Ganzhou, Jiangxi, 341000, China
| | - Xiying Cao
- Department of Thoracic Surgery, The First Affiliated Hospital of Gannan Medical University, 23 Qingnian Road, Zhanggong District, Ganzhou, Jiangxi, 341000, China
| | - Zhicheng Wu
- Department of Thoracic Surgery, The First Affiliated Hospital of Gannan Medical University, 23 Qingnian Road, Zhanggong District, Ganzhou, Jiangxi, 341000, China.
| | - Wenxiong Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| |
Collapse
|
|
3
|
Sun F, Chen Z, Zhou D, Li Z, Wang H, Zhao R, Xian J, Peng J, Peng X, Jiang C, Shi M, Li D. Regularity and correlation analysis of regional lymph node metastasis in nonoperative patients with non-small cell lung cancer based on positron emission tomography/computed tomography images. Radiat Oncol 2024; 19:137. [PMID: 39375779 PMCID: PMC11457444 DOI: 10.1186/s13014-024-02523-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 09/13/2024] [Indexed: 10/09/2024] Open
Abstract
BACKGROUND Definitive concurrent chemoradiotherapy (CCRT) is the standard treatment for locally advanced, inoperable non-small cell lung cancer (NSCLC). Previous studies have mainly focused on examining local failure and recurrence patterns after surgery and the principles of lymph node metastasis (LNM) in surgical candidates with NSCLC. However, these studies were just only able to guide postoperative radiotherapy (PORT) and the patterns of LNM in patients with resected NSCLC was inadequate to represent that in locally advanced inoperable NSCLC patients for guiding target volume delineation of CCRT. In this study, we aimed to analyze the metastasis regularities and establish the correlations between different lymph node levels in NSCLC patients without any intervention using positron emission tomography/computed tomography (PET/CT) images. METHODS Overall, 358 patients with N1-N3 NSCLC admitted in our hospital between 2018 and 2022 were retrospectively analyzed. The diagnosis of metastatic lymph nodes was reviewed and determined using the European Organization for Research and Treatment of Cancer standard and the standardized value of the PET/CT examination. Univariate and multivariate analysis were performed to investigate the correlations between the different levels were evaluated by using of the chi-square test and logistic regression model. RESULTS The lymph nodes with the highest metastasis rates in patients with left lung cancer were in order as follows: 10L, 4L, 5, 4R, and 7; while in those with right lung cancer they were 10R, 4R, 7, 2R, and 1R. Notably, we found left lung patients were more likely to have contralateral hilar, mediastinal and supraclavicular lymph nodes involved, and the right lung group exhibited a higher propensity for ipsilateral mediastinum and supraclavicular lymph node invasion. Furthermore, correlation analysis revealed there were significant correlative patterns in the LNM across different levels. CONCLUSIONS This study elucidated the patterns of primary LNM in patients with NSCLC who had not undergone surgery (without any treatment interventions) and the correlations between lymph node levels. These findings were expected to provide useful reference for target volume delineation in definitive concurrent chemoradiotherapy in locally advanced NSCLC patients.
Collapse
Affiliation(s)
- Feifan Sun
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China
| | - Zhiming Chen
- Department of Nuclear Medicine, The General Hospital of Western Theater Command, Chengdu, PR China
| | - Daijun Zhou
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China
| | - Zhihui Li
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China
| | - Haoyang Wang
- Department of Nuclear Medicine, The General Hospital of Western Theater Command, Chengdu, PR China
| | - Rong Zhao
- Department of Nuclear Medicine, The General Hospital of Western Theater Command, Chengdu, PR China
| | - Jing Xian
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China
| | - Jingjing Peng
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China
| | - Xingchen Peng
- Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, PR China.
| | - Chaoyang Jiang
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China.
| | - Mei Shi
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shanxi Province, 710000, PR China.
| | - Dong Li
- Department of Oncology, The General Hospital of Western Theater Command, Chengdu, Sichuan Province, 610083, PR China.
| |
Collapse
|
|
4
|
Xie T, Qiu BM, Luo J, Diao YF, Hu LW, Liu XL, Shen Y. Distant metastasis patterns among lung cancer subtypes and impact of primary tumor resection on survival in metastatic lung cancer using SEER database. Sci Rep 2024; 14:22445. [PMID: 39341901 PMCID: PMC11438988 DOI: 10.1038/s41598-024-73389-6] [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] [Received: 04/11/2024] [Accepted: 09/17/2024] [Indexed: 10/01/2024] Open
Abstract
This research aimed to systematically uncover the metastatic characteristics and survival rates of lung cancer subtypes and to evaluate the impact of surgery at the primary tumor site on cancer-specific survival in DM lung cancer. We used the Surveillance, Epidemiology, and End Results (SEER) database (2010-2019) to identify primary lung cancers with DM at presentation (M1). Kaplan-Meier (KM) survival curves were generated and compared utilizing log-rank tests. Cox regression methods were employed to determine hazard ratios (HR) and 95% confidence intervals related to CSS factors. Inverse probability of treatment weighting (IPTW) was applied to reduce bias. We analyzed 77,827 M1 lung cancer cases, with 41.22% having DM at presentation. Bone metastasis was most common in ADC, ASC, SCC, LCC; brain in LCNEC; liver in SCLC. Lung was common in TC + AC and SCC. Long-term survival was best in TC + AC and worst in SCLC (p < 0.001). Male gender, age < 50, primary tumor site (main bronchus, lower lobe), large tumor diameter, ADC/SCLC/SCC pathology, and regional lymph node involvement were significant risk factors for multiorgan metastasis. Age ≥ 50, male, large tumor diameter, positive lymph nodes, and multiorgan metastases were associated with lower CSS. In contrast, radiotherapy, chemotherapy, systemic therapy, and surgery were associated with higher CSS rates. Primary tumor resection improved survival in lung cancer patients (excluding small cell lung cancer, SCLC) with single organ metastases (KM log rank p < 0.001, HR = 0.6165; 95% CI (0.5468-0.6951)), especially in brain (p < 0.001, HR = 0.6467; 95% CI (0.5505-0.7596)) and bone (p = 0.182, HR = 0.6289; p < 0.01), but not in liver or intrapulmonary metastases after IPTW. Significant differences in DM patterns and corresponding survival rates exist among lung cancer subtypes. Primary tumor resection improves survival in lung cancer patients (excluding small cell lung cancer, SCLC) with single organ metastases, with better outcomes in patients with brain and bone metastases, while no significant benefit was seen in patients with liver and intrapulmonary metastases.
Collapse
Affiliation(s)
- Tian Xie
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
- Key Laboratory of Molecular Medicine, Nanjing University, Nanjing, 210093, Jiangsu, China
| | - Bing-Mei Qiu
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Jing Luo
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yi-Fei Diao
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Li-Wen Hu
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Xiao-Long Liu
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Yi Shen
- Department of Cardiothoracic Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
| |
Collapse
|
|
5
|
Dong Y, Zhou S, Li J, Zhang Y, Che G. Distant metastatic patterns in young and old non-small cell lung cancer patients: A dose‒response analysis based on SEER population. Heliyon 2024; 10:e36657. [PMID: 39281448 PMCID: PMC11401064 DOI: 10.1016/j.heliyon.2024.e36657] [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: 06/01/2024] [Revised: 08/19/2024] [Accepted: 08/20/2024] [Indexed: 09/18/2024] Open
Abstract
Background Few research has explored the risk of distant metastasis dynamically changes with age in non-small cell lung cancer patients. The objective of this study was to explore the risk factors of developing distant metastasis with changing age. Methods This retrospective cohort study was based on a large population of patients with non-small cell lung cancer from the SEER database. Logistic regression was applied to identify risk factors for distant metastasis. The clinicopathological features were compared between the young group (≤50 years old) and the old group (>50 years old). Dose-response analyses were conducted to explore risk of distant metastasis changes with age. Results A total of 18,711 patients were studied in this study. According to the univariate and multivariate logistic regression analyses, ten factors were found to be risk factors for distant metastasis. Young patients have a greater incidence of each pattern of metastasis. However, the survival time of younger patients was longer. Dose-response analyses indicated that the risks of pleural or pericardial metastasis and overall distant metastasis gradually decreased with age at younger ages, but they intend to increase at older ages. Conclusions Age, sex, ethnicity, histology, T category, N category, differentiation grade, primary site of the tumor, ipsilateral metastases are factors associated with distant metastasis in NSCLC patients. Young patients have a greater risk of distant metastasis. The distant metastasis may decrease with the increasing age in patients younger than 70 years, but increase with the climb of age for patients older than 70 years.
Collapse
Affiliation(s)
- Yingxian Dong
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- West China Clinical Medical College, Sichuan University, Chengdu, Sichuan, China
| | - Sicheng Zhou
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- West China Clinical Medical College, Sichuan University, Chengdu, Sichuan, China
| | - Jue Li
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- West China Clinical Medical College, Sichuan University, Chengdu, Sichuan, China
| | - Yin Zhang
- Department of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Diseases, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Pulmonary Immunology and Inflammation, Frontiers Science Center for Disease-related Molecular Network, Sichuan University, Chengdu, China
| | - Guowei Che
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Lung Cancer Center/Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- West China Clinical Medical College, Sichuan University, Chengdu, Sichuan, China
| |
Collapse
|
|
6
|
Wang Y, Zhang YJ. Tankyrase 2 promotes lung cancer cell malignancy. World J Clin Oncol 2024; 15:755-764. [PMID: 38946832 PMCID: PMC11212605 DOI: 10.5306/wjco.v15.i6.755] [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: 02/25/2024] [Revised: 05/09/2024] [Accepted: 05/28/2024] [Indexed: 06/24/2024] Open
Abstract
BACKGROUND Tankyrase 2 (TNKS2) is a potential candidate molecular target for the prognosis and treatment of non-small cell lung cancer (NSCLC), but its biological functions are unclear. AIM To investigate the biological functions of TNKS2 in NSCLC. METHODS Using a lentiviral vector, we generated H647 model cells with TNKS2 knockdown by RNA interference and A549 model cells with TNKS2 overexpression by transfection with a TNKS2 overexpressing plasmid. Increased and decreased expression levels of TNKS2 in the two cell lines were verified using real-time reverse transcriptase-polymerase chain reaction and Western blot analyses. Cell apoptosis, proliferation, and migration were determined using flow cytometry, carboxyfluorescein succinimidyl ester staining, and scratch assay, respectively. Immunofluorescence staining was conducted to examine TNKS2 and β-catenin expression levels in the two transfected cell lines and the non-transfected cells. RESULTS TNKS2 mRNA and protein expression was significantly higher in the highly malignant NCI-H647 cells, while it remained at a low level in the less malignant A549 cells. Lentivirus-mediated overexpression of TNKS2 in A549 cells resulted in a 3-fold increase in gene expression and a 1.7-fold increase in protein expression (P < 0.01). Conversely, shRNA interference targeting TNKS2 Led to an 8-fold decrease in gene expression and a 3-fold decrease in protein expression (P < 0.01) in NCI-H647 cells. Furthermore, the cell apoptosis rate was significantly reduced (50%) and cell migration rate was increased (35%) in the TNKS2 overexpression group than in the control group (P < 0.05). In contrast, shTNKS2 promoted apoptosis by more than one fold and reduced migration by 60% (P < 0.05). Immunofluorescence analysis revealed enhanced nuclear localization of β-catenin fluorescence signal associated with high TNKS2 expression levels. Western blot analysis investigating TNKS2/β-catenin-related proteins indicated consistent changes between TNKS2 and β-catenin expression in lung cancer cells, whereas Axin displayed an opposite trend (P < 0.05). CONCLUSION The obtained results revealed that TNKS2 may serve as an adverse prognostic factor and a potential therapeutic target in NSCLC.
Collapse
Affiliation(s)
- Ying Wang
- Department of Gynecological Oncology, Zhejiang Cancer Hospital, Hangzhou 310022, Zhejiang Province, China
| | - Yong-Jun Zhang
- Department of Integrated Traditional Chinese and Western Medicine, Zhejiang Cancer Hospital, Hangzhou 310022, Zhejiang Province, China
| |
Collapse
|
|
7
|
Shah KA, Rawal RM. A novel algorithm to differentiate between primary lung tumors and distant liver metastasis in lung cancers using an exosome based multi gene biomarker panel. Sci Rep 2024; 14:13769. [PMID: 38877052 PMCID: PMC11178885 DOI: 10.1038/s41598-024-63252-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/27/2024] [Indexed: 06/16/2024] Open
Abstract
The lack of non-invasive methods for detection of early metastasis is a crucial reason for the poor prognosis of lung cancer (LC) liver metastasis (LM) patients. In this study, the goal was to identify circulating biomarkers based on a biomarker model for the early diagnosis and monitoring of patients with LCLM. An 8-gene panel identified in our previous study was validated in CTC, cfRNA and exosomes isolated from primary lung cancer with & without metastasis. Further multivariate analysis including PCA & ROC was performed to determine the sensitivity and specificity of the biomarker panel. Model validation cohort (n = 79) was used to verify the stability of the constructed predictive model. Further, clinic-pathological factors, survival analysis and immune infiltration correlations were also performed. In comparison to our previous tissue data, exosomes demonstrated a good discriminative value with an AUC of 0.7247, specificity (72.48%) and sensitivity (96.87%) for the 8-gene panel. Further individual gene patterns led us to a 5- gene panel that showed an AUC of 0.9488 (p = < 0.001) and 0.9924 (p = < 0.001) respectively for tissue and exosomes. Additionally, on validating the model in a larger cohort a risk score was obtained (RS > 0.2) for prediction of liver metastasis with an accuracy of 95%. Survival analysis and immune filtration markers suggested that four exosomal markers were independently associated with poor overall survival. We report a novel blood-based exosomal biomarker panel for early diagnosis, monitoring of therapeutic response, and prognostic evaluation of patients with LCLM.
Collapse
Affiliation(s)
- Kanisha A Shah
- Division of Biological and Life Science, Ahmedabad University, Ahmedabad, Gujarat, India
| | - Rakesh M Rawal
- Department of Life Science, School of Sciences, Gujarat University, Navrangpura, Ahmedabad, Gujarat, 380009, India.
| |
Collapse
|
|
8
|
Zhu L, Yu X, Tang X, Hu C, Wu L, Liu Y, Zhou Q. Evolving landscape of treatments targeting the microenvironment of liver metastases in non-small cell lung cancer. Chin Med J (Engl) 2024; 137:1019-1032. [PMID: 38251678 PMCID: PMC11062672 DOI: 10.1097/cm9.0000000000002981] [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] [Received: 12/05/2023] [Indexed: 01/23/2024] Open
Abstract
ABSTRACT Liver metastases (LMs) are common in lung cancer. Despite substantial advances in diagnosis and treatment, the survival rate of patients with LM remains low as the immune-suppressive microenvironment of the liver allows tumor cells to evade the immune system. The impact of LMs on the outcomes of immune checkpoint inhibitors in patients with solid tumors has been the main focus of recent translational and clinical research. Growing evidence indicates that the hepatic microenvironment delivers paracrine and autocrine signals from non-parenchymal and parenchymal cells. Overall, these microenvironments create pre- and post-metastatic conditions for the progression of LMs. Herein, we reviewed the epidemiology, physiology, pathology and immunology, of LMs associated with non-small cell lung cancer and the role and potential targets of the liver microenvironment in LM in each phase of metastasis. Additionally, we reviewed the current treatment strategies and challenges that should be overcome in preclinical and clinical investigations. These approaches target liver elements as the basis for future clinical trials, including combinatorial interventions reported to resolve hepatic immune suppression, such as immunotherapy plus chemotherapy, immunotherapy plus radiotherapy, immunotherapy plus anti-angiogenesis therapy, and surgical resection.
Collapse
Affiliation(s)
- Lingling Zhu
- Lung Cancer Center, Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
- Key Laboratory of Drug Targeting and Drug Delivery Systems, Ministry of Education, West China School of Pharmacy, College of Polymer Science and Engineering, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xianzhe Yu
- Department of Gastrointestinal Surgery, Chengdu Second People’s Hospital, Chengdu, Sichuan 610041, China
| | - Xiaojun Tang
- Lung Cancer Center, Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chenggong Hu
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Lei Wu
- Core Facility of West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yanyang Liu
- Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qinghua Zhou
- Lung Cancer Center, Lung Cancer Institute, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| |
Collapse
|
|
9
|
Yang B, Teng M, You H, Dong Y, Chen S. A Nomogram for Predicting Survival in Advanced Non-Small-Cell Lung Carcinoma Patients: A Population-Based Study. Cancer Invest 2023; 41:672-685. [PMID: 37490629 DOI: 10.1080/07357907.2023.2241547] [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] [Received: 07/27/2022] [Revised: 12/17/2022] [Accepted: 07/21/2023] [Indexed: 07/27/2023]
Abstract
Non-small-cell lung cancer (NSCLC) remains the most common malignant cancer. We identified 43140 advanced NSCLC patients from the SEER database to develop and validate a new prognostic model. The prognostic performance was evaluated by P value, concordance index, net reclassification index, integrated discrimination improvement, and decision curve analysis. The following variables were contained in the final prognostic model: age, sex, race, TNM stage, and grade and treatment options. Compared to the AJCC staging system, this prognostic model is conducive to the implementation of individualized clinical treatment schemes and can be an important part of the precise medical care of NSCLC tumors.
Collapse
Affiliation(s)
- Bo Yang
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, China
| | - Mengmeng Teng
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, China
| | - Haisheng You
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, China
| | - Yalin Dong
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, China
| | - Siying Chen
- Department of Pharmacy, First Affiliated Hospital of Xi'an Jiaotong University, Shannxi, China
| |
Collapse
|
|
10
|
Zhang M, Yang W, Yang Y, Cai C, Zhao D, Han B. Nomogram for predicting the likelihood of liver metastases at initial diagnosis in patients with Siewert type II gastroesophageal junction adenocarcinoma. Sci Rep 2023; 13:11032. [PMID: 37419904 PMCID: PMC10329020 DOI: 10.1038/s41598-023-37318-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 06/20/2023] [Indexed: 07/09/2023] Open
Abstract
The liver is one of the most ordinary metastatic sites of gastroesophageal junction adenocarcinoma and significantly affects its prognosis. Therefore, this study tried to construct a nomogram that can be applied to predict the likelihood of liver metastases from gastroesophageal junction adenocarcinoma. 3001 eligible patients diagnosed with gastroesophageal junction adenocarcinoma between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were involved in the analysis. Patients were randomly divided into a training cohort and an internal validation cohort using R software, with an allocation ratio of 7:3. According to the consequences of univariate and multivariate logistic regression, we constructed a nomogram for predicting the risk of liver metastases. The discrimination and calibration ability of the nomogram was appraised by the C-index, ROC curve, calibration plots, and decision curve analysis (DCA). We also used Kaplan-Meier survival curves to compare differences in overall survival in patients with gastroesophageal junction adenocarcinoma with and without liver metastases. Liver metastases developed in 281 of 3001 eligible patients. The overall survival of patients with gastroesophageal junction adenocarcinoma with liver metastases before and after propensity score matching (PSM) was obviously lower than that of patients without liver metastases. Six risk factors were finally recognized by multivariate logistic regression, and a nomogram was constructed. The C-index was 0.816 in the training cohort and 0.771 in the validation cohort, demonstrating the good predictive capacity of the nomogram. The ROC curve, calibration curve, and decision curve analysis further demonstrated the good performance of the predictive model. The nomogram can accurately predict the likelihood of liver metastases in gastroesophageal junction adenocarcinoma patients.
Collapse
Affiliation(s)
- Min Zhang
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China
| | - Wenwen Yang
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China
| | - Yanjiang Yang
- Qilu Hospital of Shandong University, Shandong University, Jinan, 250355, Shandong Province, China
| | - Chengfeng Cai
- Department of Urology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), No. 568, Zhongxing North Road, Shaoxing, 312000, Zhejiang, China
| | - Dan Zhao
- Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Biao Han
- Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu Province, China.
- Gansu Province International Cooperation Base for Research and Application of Key Technology of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu Province, China.
| |
Collapse
|
|
11
|
Muniz AHR, Rosa KSDC, Resende JMDD, Sampaio SGDSM, Oliveira LCD. Fatores Associados ao Karnofsky Performance Status e sua Trajetória no Último Mês de Vida em Pacientes com Câncer Terminal. REVISTA BRASILEIRA DE CANCEROLOGIA 2023. [DOI: 10.32635/2176-9745.rbc.2023v69n1.2754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Introdução: O Karnofsky Performance Status (KPS) pode caracterizar o impacto da doença em pacientes com câncer. Objetivo: Avaliar os fatores associados ao KPS e a sua trajetória no último mês de vida em pacientes com câncer terminal. Método: Estudo de coorte retrospectivo, com pacientes com câncer terminal internados em uma unidade de cuidados paliativos, falecidos entre julho e agosto de 2019. A variável dependente foi o KPS avaliado diariamente no último mês de vida. Uma análise transversal dos fatores associados ao KPS inicial foi realizada por meio de regressões logísticas ordinais. Para verificar a trajetória do KPS no último mês de vida, foram realizadas análises gráficas longitudinais. Resultados: Foram avaliados 108 pacientes, cuja maioria possuía >60 anos (68,5%) e era do sexo feminino (62,0%). Os sítios tumorais mais prevalentes foram o trato gastrointestinal (TGI) (24,3%), mama (18,7%) e cabeça e pescoço (CP) (16,8%). No modelo múltiplo, os sítios tumorais primários permaneceram associados ao KPS. Durante o último mês de vida, a redução do KPS foi mais pronunciada naqueles com tumor no TGI, CP e tecido ósseo conjuntivo, que apresentaram valores mais elevados de KPS no trigésimo dia antes do óbito quando comparados aos demais. Por outro lado, aqueles com câncer no sistema nervoso central e pulmão iniciaram o período de seguimento com valores de KPS mais baixos e tiveram redução menos exacerbada que os demais. Conclusão: Os valores de KPS diminuem no último mês de vida, porém com intensidade diferente de acordo com o local do tumor em pacientes com câncer terminal.
Collapse
|
|
12
|
Li MP, Liu WC, Sun BL, Zhong NS, Liu ZL, Huang SH, Zhang ZH, Liu JM. Prediction of bone metastasis in non-small cell lung cancer based on machine learning. Front Oncol 2023; 12:1054300. [PMID: 36698411 PMCID: PMC9869148 DOI: 10.3389/fonc.2022.1054300] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/21/2022] [Indexed: 01/12/2023] Open
Abstract
OBJECTIVE The purpose of this paper was to develop a machine learning algorithm with good performance in predicting bone metastasis (BM) in non-small cell lung cancer (NSCLC) and establish a simple web predictor based on the algorithm. METHODS Patients who diagnosed with NSCLC between 2010 and 2018 in the Surveillance, Epidemiology and End Results (SEER) database were involved. To increase the extensibility of the research, data of patients who first diagnosed with NSCLC at the First Affiliated Hospital of Nanchang University between January 2007 and December 2016 were also included in this study. Independent risk factors for BM in NSCLC were screened by univariate and multivariate logistic regression. At this basis, we chose six commonly machine learning algorithms to build predictive models, including Logistic Regression (LR), Decision tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), Naive Bayes classifiers (NBC) and eXtreme gradient boosting (XGB). Then, the best model was identified to build the web-predictor for predicting BM of NSCLC patients. Finally, area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity were used to evaluate the performance of these models. RESULTS A total of 50581 NSCLC patients were included in this study, and 5087(10.06%) of them developed BM. The sex, grade, laterality, histology, T stage, N stage, and chemotherapy were independent risk factors for NSCLC. Of these six models, the machine learning model built by the XGB algorithm performed best in both internal and external data setting validation, with AUC scores of 0.808 and 0.841, respectively. Then, the XGB algorithm was used to build a web predictor of BM from NSCLC. CONCLUSION This study developed a web predictor based XGB algorithm for predicting the risk of BM in NSCLC patients, which may assist doctors for clinical decision making.
Collapse
Affiliation(s)
- Meng-Pan Li
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- The First Clinical Medical College of Nanchang University, Nanchang, China
| | - Wen-Cai Liu
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- The First Clinical Medical College of Nanchang University, Nanchang, China
- Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Bo-Lin Sun
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Institute of Spine and Spinal Cord, Nanchang University, Nanchang, China
| | - Nan-Shan Zhong
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Institute of Spine and Spinal Cord, Nanchang University, Nanchang, China
| | - Zhi-Li Liu
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Institute of Spine and Spinal Cord, Nanchang University, Nanchang, China
| | - Shan-Hu Huang
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Institute of Spine and Spinal Cord, Nanchang University, Nanchang, China
| | - Zhi-Hong Zhang
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Institute of Spine and Spinal Cord, Nanchang University, Nanchang, China
| | - Jia-Ming Liu
- Department of Orthopedic Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
- Institute of Spine and Spinal Cord, Nanchang University, Nanchang, China
| |
Collapse
|
|
13
|
Xie B, Chen X, Deng Q, Shi K, Xiao J, Zou Y, Yang B, Guan A, Yang S, Dai Z, Xie H, He S, Chen Q. Development and Validation of a Prognostic Nomogram for Lung Adenocarcinoma: A Population-Based Study. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:5698582. [PMID: 36536690 PMCID: PMC9759395 DOI: 10.1155/2022/5698582] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 01/22/2024]
Abstract
PURPOSE To establish an effective and accurate prognostic nomogram for lung adenocarcinoma (LUAD). Patients and Methods. 62,355 LUAD patients from 1975 to 2016 enrolled in the Surveillance, Epidemiology, and End Results (SEER) database were randomly and equally divided into the training cohort (n = 31,179) and the validation cohort (n = 31,176). Univariate and multivariate Cox regression analyses screened the predictive effects of each variable on survival. The concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were used to examine and validate the predictive accuracy of the nomogram. Kaplan-Meier curves were used to estimate overall survival (OS). RESULTS 10 prognostic factors associated with OS were identified, including age, sex, race, marital status, American Joint Committee on Cancer (AJCC) TNM stage, tumor size, grade, and primary site. A nomogram was established based on these results. C-indexes of the nomogram model reached 0.777 (95% confidence interval (CI), 0.773 to 0.781) and 0.779 (95% CI, 0.775 to 0.783) in the training and validation cohorts, respectively. The calibration curves were well-fitted for both cohorts. The AUC for the 3- and 5-year OS presented great prognostic accuracy in the training cohort (AUC = 0.832 and 0.827, respectively) and validation cohort (AUC = 0.835 and 0.828, respectively). The Kaplan-Meier curves presented significant differences in OS among the groups. CONCLUSION The nomogram allows accurate and comprehensive prognostic prediction for patients with LUAD.
Collapse
Affiliation(s)
- Bin Xie
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Xi Chen
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Qi Deng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Ke Shi
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Jian Xiao
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Yong Zou
- Department of Emergency Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Baishuang Yang
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Anqi Guan
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Shasha Yang
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Ziyu Dai
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Huayan Xie
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Shuya He
- Institute of Biochemistry and Molecular Biology, Hengyang Medical College, University of South China, Hengyang 421001, China
| | - Qiong Chen
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China
| |
Collapse
|
|
14
|
Luo Y, Mou K, Wang J, Luo J, Peng L, Ye H, Lin S. Colon metastasis from lung adenocarcinoma with BRAF V600E mutation: A case report. Front Immunol 2022; 13:970879. [PMID: 36003386 PMCID: PMC9393296 DOI: 10.3389/fimmu.2022.970879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/14/2022] [Indexed: 11/13/2022] Open
Abstract
Symptomatic colon metastasis from primary lung cancer is rare in clinical practice. We report the case of a 58-year-old patient with advanced lung adenocarcinoma who developed abdominal symptoms, including abdominal distention and difficulty defecating, after immunotherapy and chemotherapy. The patient was diagnosed with lung adenocarcinoma, and systemic positron emission tomography-computed tomography confirmed multiple lymph node, pleural, and adrenal metastases. Molecular detection indicated BRAF V600E mutation and high programmed death-ligand 1 (PD-L1) expression. After first-line anti-programmed cell death protein 1 immunotherapy combined with chemotherapy, the nodes in the chest remarkably diminished. However, it was followed by colon obstruction, incomplete ileus, and bone metastasis. Endoscopic histological examination confirmed adenocarcinoma but could not identify primary or secondary tumors due to insufficient tissue. We performed colon resection to remove the obstruction, and postoperative tissue pathological microscopy confirmed metastasis from the lung adenocarcinoma. We corroborated the BRAF V600E mutation and high PD-L1 expression and supported the molecular features of lung adenocarcinoma. During hospitalization, the patient presented with unbearable pain in the bone metastases, and palliative radiotherapy was administered. Then, the patient received dabrafenib plus trametinib as the second-line therapy. This report discusses the clinical characteristics, pathology, imaging, molecular profile assessments, and treatment of primary lung adenocarcinoma with colon metastasis.
Collapse
Affiliation(s)
- Yuhao Luo
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- *Correspondence: Yuhao Luo, ; Sheng Lin,
| | - Kelin Mou
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
| | - Jianmei Wang
- Department of Pathology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jing Luo
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Lin Peng
- Department of Bone and Joint, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Hua Ye
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Sheng Lin
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- *Correspondence: Yuhao Luo, ; Sheng Lin,
| |
Collapse
|
|
15
|
Schlachtenberger G, Fabian D, Hruy M, Hagmeyer L, Bennink G, Gaisendrees C, Wahlers T, Hekmat K, Heldwein MB. Sublobar resection without staging and lymphadenectomy for ≤2 cm Non-Small Cell Lung Cancer is no adequate therapy. Surg Oncol 2022; 44:101840. [DOI: 10.1016/j.suronc.2022.101840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 08/12/2022] [Accepted: 08/19/2022] [Indexed: 11/28/2022]
|
|
16
|
Oncogenic Alterations in Histologically Negative Lymph Nodes Are Associated with Prognosis of Patients with Stage I Lung Adenocarcinoma. Cancers (Basel) 2022; 14:cancers14030824. [PMID: 35159091 PMCID: PMC8834139 DOI: 10.3390/cancers14030824] [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: 12/19/2021] [Revised: 02/02/2022] [Accepted: 02/03/2022] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Lymph nodes (LNs) metastasis is one of the most important factors affecting the outcome of non-small cell lung. The aim of this study is to explore whether presence of oncogenic alterations in histologically-negative lymph nodes (LNs) can be of prognostic significance in stage I lung adenocarcinoma (LUAD). We confirmed that presence of oncogenic alterations in regional LN may be associated with higher risks of postsurgical recurrence of Stage I LUAD, particularly for certain molecular subgroups. These results warranted future studies on larger cohort of NSCLC patients using more comprehensive cancer gene panels to establish the clinical impact of molecular LN occult metastasis for localized NSCLC and identify Stage I patients at high risks for recurrence for appropriate adjuvant therapy. Abstract Background: Survival of patients with stage I non-small cell lung cancer (NSCLC) varies greatly. We sought to explore whether presence of oncogenic alterations in histologically-negative lymph nodes (LNs) can be of prognostic significance in stage I lung adenocarcinoma (LUAD). Methods: Genomic analysis of oncogenic alterations was applied to 123 stage I LUAD tumors. The same genomic variants identified in primary tumors were examined in corresponding histologically-negative LNs. Results: A total of 102 (82.9%) patients had at least one canonical oncogenic alteration detected in primary tumors, and 57 LNs from 12 patients (11.8%) were found to carry the identical oncogenic alterations detected in the corresponding primary tumor tissues, including EGFR mutations (six cases), KRAS mutations (three cases), ALK fusion (one case), BRAF mutation (one case) and HER2 & NRAS co-mutations (one case). None of these LNs was found to have occult tumor cells by routine pathological assessment or immunohistochemistry staining using antibodies against pan-cytokeratins (AE1/AE3) and the epithelial marker Ber-EP4. The detection rate of oncogenenic alterations in LN was significantly higher in RAS-mutant tumors than EGFR mutant tumors (36.36% verse 7.41%, p = 0.017). Patients with oncogenic alterations in LN showed inferior disease-free survival (DFS, p = 0.025) and overall survival (OS, p = 0.027). Furthermore, patients with RAS-mutations detected in LN had the worst DFS and OS (p = 0.001). Among the 11 patients with RAS mutation in primary tumors, DFS and OS in the four patients with mutations detected in LN were significantly shorter than the remaining seven patients without mutations LN (DFS, p = 0.001, OS, p = 0.002). Conclusions: Genomic analysis has the potential to detect oncogenic alterations in regional LNs for localized LUAD and presence of oncogenic alterations in regional LN may be associated with inferior clinical outcome of stage I LUAD, particularly for certain molecular subgroups. ClinicalTrials.gov ID NCT04266691
Collapse
|
|
17
|
Jiang C, Li X, Sun B, Zhang N, Li J, Yue S, Hu X. Extracellular vesicles promotes liver metastasis of lung cancer by ALAHM increasing hepatocellular secretion of HGF. iScience 2022; 25:103984. [PMID: 35281743 PMCID: PMC8914534 DOI: 10.1016/j.isci.2022.103984] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/09/2022] [Accepted: 02/21/2022] [Indexed: 11/18/2022] Open
Affiliation(s)
- Chunyang Jiang
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, 190 Jieyuan Road, Hongqiao District, Tianjin 300121, Tianjin, China
- Corresponding author
| | - Xu Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Bingsheng Sun
- Department of Thoracic Surgery, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, Tianjin, China
| | - Na Zhang
- Department of Respiratory Medicine, Tianjin Union Medical Center, Nankai University, 190 Jieyuan Road, Hongqiao District, Tianjin 300121, Tianjin, China
| | - Jing Li
- Department of Respiratory Medicine, Tianjin Union Medical Center, Nankai University, 190 Jieyuan Road, Hongqiao District, Tianjin 300121, Tianjin, China
| | - Shijing Yue
- The State Key Laboratory of Medicinal Chemical Biology, School of Medicine, The State International Science & Technology Cooperation Base of Tumor Immunology and Biological Vaccines, Nankai University, 94 Weijin Road, Nankai District, Tianjin 300071, Tianjin, China
- Corresponding author
| | - Xiaoli Hu
- Department of Respiratory Medicine, The Second People’|'s Hospital of Linhai City, 198 Dubei Road, Linhai 317016, Zhejiang Province, China
- Corresponding author
| |
Collapse
|
|
18
|
Li N, Chu Y, Song Q. Brain Metastasis in Patients with Small Cell Lung Cancer. Int J Gen Med 2022; 14:10131-10139. [PMID: 34992434 PMCID: PMC8710975 DOI: 10.2147/ijgm.s342009] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/10/2021] [Indexed: 12/16/2022] Open
Abstract
Purpose To characterize the risk factors for brain metastasis (BM) at presentation and analyze the prognostic factors for patients with small cell lung cancer (SCLC). Patients and Methods Patients were recruited from the SEER database between 2010 and 2016. They were divided into two groups according to BM status. The incidence trends of SCLC and its BM were analyzed by joinpoint software. The risk factors for BM in SCLC were identified by binary logistic regression models. The prognostic factors for SCLC patients with BM were identified by Cox proportional hazard models. Results The incidence of SCLC and its BM significantly decreased after 2010. Totally 11,093 patients were collected, including 1717 (15.5%) patients with BM and 9376 (84.5%) patients without BM. In multivariate logistic regression analysis, age, male and higher T stage were independent risk factors for BM in SCLC patients at presentation. SCLC patients with BM showed inferior survival to those without BM. In multivariate Cox regression analysis, increasing age, large tumor size, and higher N stage were risk factors for poor prognosis, while other race, surgery, adjuvant radiotherapy, and chemotherapy were protective factors for SCLC patients with BM. A nomogram was developed for prognosis evaluation of such patients. Conclusion Age, male and higher T stage were risk factors for BM in SCLC patients at presentation. Increasing age, large tumor size, and advanced N stage may predict poor survival for SCLC patients with BM. Multidisciplinary therapies may provide clinical benefits. This study will help identify patients with higher BM risk and hopefully improve their clinical outcome.
Collapse
Affiliation(s)
- Na Li
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, People's Republic of China
| | - Yuxin Chu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, People's Republic of China
| | - Qibin Song
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, People's Republic of China
| |
Collapse
|
|
19
|
Chai X, Yinwang E, Wang Z, Wang Z, Xue Y, Li B, Zhou H, Zhang W, Wang S, Zhang Y, Li H, Mou H, Sun L, Qu H, Wang F, Zhang Z, Chen T, Ye Z. Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value. Front Oncol 2021; 11:692788. [PMID: 34722241 PMCID: PMC8552022 DOI: 10.3389/fonc.2021.692788] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 08/30/2021] [Indexed: 12/25/2022] Open
Abstract
Lung cancer is the leading cause of cancer-related death worldwide. Bone metastasis, which usually accompanies severe skeletal-related events, is the most common site for tumor distant dissemination and detected in more than one-third of patients with advanced lung cancer. Biopsy and imaging play critical roles in the diagnosis of bone metastasis; however, these approaches are characterized by evident limitations. Recently, studies regarding potential biomarkers in the serum, urine, and tumor tissue, were performed to predict the bone metastases and prognosis in patients with lung cancer. In this review, we summarize the findings of recent clinical research studies on biomarkers detected in samples obtained from patients with lung cancer bone metastasis. These markers include the following: (1) bone resorption-associated markers, such as N-terminal telopeptide (NTx)/C-terminal telopeptide (CTx), C-terminal telopeptide of type I collagen (CTx-I), tartrate-resistant acid phosphatase isoform 5b (TRACP-5b), pyridinoline (PYD), and parathyroid hormone related peptide (PTHrP); (2) bone formation-associated markers, including total serum alkaline phosphatase (ALP)/bone specific alkaline phosphatase(BAP), osteopontin (OP), osteocalcin (OS), amino-terminal extension propeptide of type I procollagen/carboxy-terminal extension propeptide of type I procollagen (PICP/PINP); (3) signaling markers, including epidermal growth factor receptor/Kirsten rat sarcoma/anaplastic lymphoma kinase (EGFR/KRAS/ALK), receptor activator of nuclear factor κB ligand/receptor activator of nuclear factor κB/osteoprotegerin (RANKL/RANK/OPG), C-X-C motif chemokine ligand 12/C-X-C motif chemokine receptor 4 (CXCL12/CXCR4), complement component 5a receptor (C5AR); and (4) other potential markers, such as calcium sensing receptor (CASR), bone sialoprotein (BSP), bone morphogenetic protein 2 (BMP2), cytokeratin 19 fragment/carcinoembryonic antigen (CYFRA/CEA), tissue factor, cell-free DNA, long non-coding RNA, and microRNA. The prognostic value of these markers is also investigated. Furthermore, we listed some clinical trials targeting hotspot biomarkers in advanced lung cancer referring for their therapeutic effects.
Collapse
Affiliation(s)
- Xupeng Chai
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Eloy Yinwang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Zenan Wang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Zhan Wang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Yucheng Xue
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Binghao Li
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Hao Zhou
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Wenkan Zhang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Shengdong Wang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Yongxing Zhang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Hengyuan Li
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Haochen Mou
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Lingling Sun
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Hao Qu
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Fangqian Wang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Zengjie Zhang
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Tao Chen
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| | - Zhaoming Ye
- Department of Orthopedics, Musculoskeletal Tumor Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.,Institute of Orthopedic Research, Zhejiang University, Hangzhou, China
| |
Collapse
|