Hepatocellular carcinoma (HCC) recurrence was previously characterized into four types, and patients with progression/hyper-progression recurrence (type III-IV) have an extremely poor prognosis. However, the immune background of resectable HCC, particularly in patients who experience recurrence, remains underexplored. Therefore, this study aimed to describe the immune landscape of resectable HCC, especially postoperative type III-IV recurrent HCC, and explore potential immune-targeted anti-relapse strategies for treated populations.

The differences in gene expression in patients with recurrent HCC (type I-II (solitary or multi-intrahepatic oligo recurrence) vs. type III-IV) were investigated using bulk sequencing. Multiple immune infiltration methods (single-sample gene set enrichment analysis (GSEA), Microenvironment Cell Populations-counter and ESTIMATE) were used, and patients were divided into four groups to identify four distinct immune subtypes: immune-enrichment/matrix-poor (IE1), immune-enrichment/matrix-rich (IE2), immune intermediate/matrix-rich (ITM) and immune desert/matrix-poor (ID). Co-expression and protein interaction analyses were used to identify characteristic genes in ITM closely associated with type III-IV recurrence, which was matched with drug targets for Huaier granules (HG) and lenvatinib. Virtual docking was used to identify potential therapeutic targets, and the results were verified using single-nuclei RNA sequencing and histological analysis.

ITM was closely related to type III-IV recurrence and exhibited immunotherapy potential. The potential efficacy of inhibiting CCNA2, VEGFA, CXCL8, PLK2, TIMP1, ITGB2, ALDOA, ANXA5 and CSK in ITM reversal was determined. Molecular docking demonstrated that the proteins of these genes could bind to HG or lenvatinib. The immunohistochemical findings demonstrated differential VEGFA (p < .01) and PLK2 (p < .001) expression in ITM type and ID in type III-IV recurrent HCC.

Three primary immunotypes of resectable HCC (IE2, ITM and ID) were identified, and HG and lenvatinib could potentially overcome immune checkpoint blockade (ICB) resistance in ITM patients with HCC, particularly those classified as type III-IV.

Membrane-associated RING-CH8 (MARCH8) is a member of the recently discovered MARCH family of ubiquitin ligases. MARCH8 has been shown to participate in immune responses. However, the role of MARCH8 in prognosis and immunology in human cancers remains largely unknown. The expression of MARCH8 protein was detected via immunohistochemistry in non-small cell lung cancer (NSCLC) and non-cancerous lung tissues. The study investigated the role of MARCH8 in tumor immunity through pan-cancer analysis of multiple databases. MARCH8 genetic alternations and expression were explored with the cBioPortal, GTEx, and TCGA databases. We investigated the role of MARCH8 expression in clinical relevance, prognosis, tumor immune microenvironment, immune checkpoint (ICP) with a series of bioinformatics tools and methods, such as TISIDB database, ESTIMATE, and CIBERSORT method. MARCH8 expression showed cancer-specific dysregulation and was associated with the prognosis of patients in various cancers. MARCH8 was related to the tumor microenvironment and participated in tumor immune regulation. Furthermore, low expression of MARCH8 was associated with poor prognosis and might serve as an independent prognostic biomarker for NSCLC patients. The comprehensive pan-cancer analysis revealed the potential of MARCH8 in tumor-targeted therapy, and suggested MARCH8 as a promising prognostic and immunological pan-cancer biomarker.

Tumor-resident immune cells play a crucial role in eliciting anti-tumor immunity and immunomodulatory drug responses, yet these functions have been difficult to study without tractable models of the tumor immune microenvironment (TIME). Patient-derived ex vivo models contain authentic resident immune cells and therefore, could provide new mechanistic insights into how the TIME responds to tumor or immune cell-directed therapies. Here, we assessed the reproducibility and robustness of immunomodulatory drug responses across two different ex vivo models of breast cancer TIME and one of renal cell carcinoma. These independently developed TIME models were treated with a panel of clinically relevant immunomodulators, revealing remarkably similar changes in gene expression and cytokine profiles among the three models in response to T cell activation and STING-agonism, while still preserving individual patient-specific response patterns. Moreover, we found two common core signatures of adaptive or innate immune responses present across all three models and both types of cancer, potentially serving as benchmarks for drug-induced immune activation in ex vivo models of the TIME. The robust reproducibility of immunomodulatory drug responses observed across diverse ex vivo models of the TIME underscores the significance of human patient-derived models in elucidating the complexities of anti-tumor immunity and therapeutic interventions.

Programmed cell death (PCD) is a significant factor in the progression of hepatocellular carcinoma (HCC) and might serve as a crucial marker for predicting HCC prognosis and therapy response. However, the classification of HCC based on diverse PCD patterns requires further investigation. This study identified a novel molecular classification named PCD subtype (C1, C2, and C3) based on the genes associated with 19 PCD patterns, distinguished by clinical, biological functional pathways, mutations, immune characteristics, and drug sensitivity. Validated in 4 independent datasets, diverse cell death pathways were enriched in the C3 subtype, including apoptosis, pyroptosis, and autophagy, it also exhibited a highly infiltrative immunosuppressive microenvironment and demonstrated higher sensitivity to compounds such as Paclitaxel, Bortezomib, and YK-4-279, while C1 subtype was significantly enriched in cuproptosis and metabolism-related pathways, suggesting that it may be more suitable for cuproptosis-inducing agent therapy. Subsequently, utilizing the machine learning algorithms, we constructed a cell death-related index (CDRI) with 22 gene features and constructed prognostic nomograms with high predictive performance by combining CDRI with clinical features. Notably, we found that CDRI effectively predicted the response of HCC patients to therapeutic strategies, where patients with high CDRI were more suitable for sorafenib drug therapy and patients with low CDRI were more ideal for transarterial chemoembolization (TACE). In conclusion, the PCD subtype and CDRI demonstrate significant efficacy in predicting the prognosis and therapeutic outcomes for patients with HCC. These findings offer valuable insights for the development of precise, individualized treatment strategies.

Peritoneal metastasis following gastric cancer surgery is often associated with a poor prognosis. This study aimed to investigate the mechanisms underlying peritoneal metastasis and to develop a predictive model for the risk of postoperative peritoneal metastases in gastric cancer. We performed a comprehensive analysis of the protein mass spectra and tumor microenvironment in paraffin-embedded primary tumor sections from gastric cancer patients, both with and without postoperative peritoneal metastases. Using proteomic profiling, we identified 9595 proteins and stratified patients into three distinct proteomic subgroups (Pro1, Pro2, Pro3) based on differential protein expression. Simultaneously, immune cell profiling allowed us to classify patients into four immune subgroups (IG-I, IG-II, IG-III, IG-IV). The relationships between these proteomic, immune, and metastasis classifications were further explored to uncover potential associations and mechanisms driving metastasis. Building on these insights, we developed an integrative model combining proteomics, immunological, and radiomics data for predicting postoperative peritoneal metastases. This model demonstrated high predictive efficacy, offering a robust tool for identifying high-risk patients. Our findings provide a deeper understanding of the biological processes underlying peritoneal metastasis in gastric cancer, highlighting the interplay between proteomic and immune factors. By establishing novel patient subgroups and an effective prediction model, this study lays the groundwork for early diagnosis and tailored therapeutic strategies to improve outcomes for gastric cancer patients.

JOURNAL/nrgr/04.03/01300535-202504000-00029/figure1/v/2024-07-06T104127Z/r/image-tiff Recent research has demonstrated the impact of physical activity on the prognosis of glioma patients, with evidence suggesting exercise may reduce mortality risks and aid neural regeneration. The role of the small ubiquitin-like modifier (SUMO) protein, especially post-exercise, in cancer progression, is gaining attention, as are the potential anti-cancer effects of SUMOylation. We used machine learning to create the exercise and SUMO-related gene signature (ESLRS). This signature shows how physical activity might help improve the outlook for low-grade glioma and other cancers. We demonstrated the prognostic and immunotherapeutic significance of ESLRS markers, specifically highlighting how murine double minute 2 (MDM2), a component of the ESLRS, can be targeted by nutlin-3. This underscores the intricate relationship between natural compounds such as nutlin-3 and immune regulation. Using comprehensive CRISPR screening, we validated the effects of specific ESLRS genes on low-grade glioma progression. We also revealed insights into the effectiveness of Nutlin-3a as a potent MDM2 inhibitor through molecular docking and dynamic simulation. Nutlin-3a inhibited glioma cell proliferation and activated the p53 pathway. Its efficacy decreased with MDM2 overexpression, and this was reversed by Nutlin-3a or exercise. Experiments using a low-grade glioma mouse model highlighted the effect of physical activity on oxidative stress and molecular pathway regulation. Notably, both physical exercise and Nutlin-3a administration improved physical function in mice bearing tumors derived from MDM2-overexpressing cells. These results suggest the potential for Nutlin-3a, an MDM2 inhibitor, with physical exercise as a therapeutic approach for glioma management. Our research also supports the use of natural products for therapy and sheds light on the interaction of exercise, natural products, and immune regulation in cancer treatment.

As the objective overall response rate to immune checkpoint inhibitors (ICIs) is less than 30% in late stage or metastatic bladder cancer (BLCA), elucidating the intrinsic mechanisms of immune evasion is of great importance for the discovery of predictive and prognostic biomarkers and the exploration of novel targets for intervention. Recent studies have shown that OBSCN and the cytoskeletal protein it encodes, obscurin, play an important role in tumour progression. However, no studies have reported the role of OBSCN in BLCA.

RNA sequencing and clinical data were downloaded from multiple public databases including The Cancer Genome Atlas and the Gene Expression Omnibus. Immunohistochemistry (IHC) was performed on tissue microarrays including 80 BLCA patients from Shuguang Hospital. Kaplan-Meier curves with log-rank test, univariate and multivariate COX regression were performed to evaluate the prognostic efficacy of OBSCN expression. In vitro experiments were conducted to determine the role of OBSCN deficiency in promoting BLCA progression. Pan-cancer tumour immune microenvironment (TIME) analysis was performed to explore the potential correlation between OBSCN deficiency and immune evasion.

Pan-cancers and single-cell sequencing analysis revealed that the expression level and proportion of OBSCN was significantly decreased in BLCA cells compared to normal urothelium. Survival curves showed that BLCA patients with low OBSCN expression had a worse prognosis, yet a better clinical response to PD-L1 ICIs. Gene set variation analysis and Gene set enrichment analysis revealed that epithelial-mesenchymal transition (EMT) and immune-related processes were significantly enriched in BLCA samples with low OBSCN expression. In vitro experiments identified that OBSCN-deficient BLCA cells enhanced invasion, migration and EMT. Pan-cancer analysis of TIME revealed that neoantigen, tumor mutation burden, CD8+T cells and immune checkpoints were significantly negatively associated with OBSCN expression. IHC and Western blot assay identified that BLCA samples with low OBSCN expression had more CD8+ T-cell infiltration and higher PD-L1 expression.

This study confirmed that BLCA patients with low OBSCN expression had a worse prognosis but a superior response to ICIs, providing a reference for individualised treatment of BLCA patients.

Cancer immunoediting reflects the role of the immune system in eliminating tumor cells and shaping tumor immunogenicity, which leaves marks in the genome. In this study, we systematically evaluate four methods for quantifying immunoediting. In colorectal cancer samples from The Cancer Genome Atlas, we found that these methods identified 78.41%, 46.17%, 36.61%, and 4.92% of immunoedited samples, respectively, covering 92.90% of all colorectal cancer samples. Comparison of 10 patient-derived xenografts (PDXs) with their original tumors showed that different methods identified reduced immune selection in PDXs ranging from 44.44% to 60.0%. The proportion of such PDX-tumor pairs increases to 77.78% when considering the union of results from multiple methods, indicating the complementarity of these methods. We find that observed-to-expected ratios highly rely on neoantigen selection criteria and reference datasets. In contrast, HLA-binding mutation ratio, immune dN/dS, and enrichment score of cancer cell fraction were less affected by these factors. Our findings suggest integration of multiple methods may benefit future immunoediting analyses.

Immune evasion is a hallmark of cancer progression but the role of steroid hormones in this evasion has long been underrated. This oversight is particularly notable for glucocorticoids given that exogenous glucocorticoids remain a cornerstone therapy in various oncological treatment regimens, supportive care and treatment of immune-related adverse events caused by immune-checkpoint inhibitors. Cortisol, the main endogenous glucocorticoid in humans, is secreted by the adrenal cortex in response to stress. Additionally, cortisol and its inactive metabolite cortisone can be interconverted to further modulate tissue-dependent glucocorticoid action. In the past 5 years, intratumoural production of glucocorticoids, by both immune and tumour cells, has been shown to support tumour immune evasion. Here, we summarize current progress at the crossroads of endocrinology and immuno-oncology. We outline the known effects of steroid hormones on different immune cell types with a focus on glucocorticoids and androgens. We conclude with options for pharmaceutical intervention, including the engineering of cell-based therapies that resist the immunosuppressive action of steroid hormones. Overall, local steroid production and metabolism are emerging elements of tumour immune suppression that are potentially amenable to therapeutic intervention. Targeting steroid hormones to enhance anticancer therapies could increase their efficacy but will require expertise in endocrine care.

Upfront combination chemoradiotherapy (CRT) represents the standard of care for patients affected by stage III squamous cell carcinoma (SCC) of the anal canal, achieving satisfactory results both in terms of overall survival and local disease control. However, a non-negligible fraction of patients obtain incomplete responses, highlighting the need for innovative prognostic tools. We report the preliminary results of a customized radiomic algorithm designed to predict tumor response to CRT in patients affected by SCC of the anal canal.

We manually annotated pretreatment T2-weighted turbo spin-echo images of 26 consecutive patients with stage III SCC of the anal canal treated with CRT at our institution from 2012 to 2022. Each patient was classified as complete response (CR, 17 patients), or non-complete response (non-CR, 9 patients) based on the absence or presence of residual disease at imaging and endoscopy after treatment. A total of 132 three-dimensional radiomic features were extracted for each patient and fed to a dedicated machine-learning classifier.

Models trained with gray-level co-occurrence matrix features achieved the best performances (accuracy 0.846 ± 0.064, sensitivity 0.900 ± 0.122, specificity 0.833 ± 0.175, area under receiver operating characteristics curve 0.867 ± 0.055), highlighting a more homogeneous distribution of voxel intensities and lower spatial complexity in non-CR patients.

Our radiomic tool accurately predicted tumor response to CRT in patients with stage III SCC of the anal canal, highlighting a more homogeneous tissue composition in poor responders.

The more homogeneous radiomic texture observed in non-CR patients may be imputable to a dominant neoplastic clone with a relatively low mitotic index (therefore, limited tissue necrosis), intrinsically more resistant to CRT than faster-proliferating tumors.

A non-negligible fraction of patients with anal SCC respond unsatisfactorily to CRT. Our radiomic model predicted response to CRT based on pretreatment MRI. We observed a more homogeneous tissue composition in poor responders. The slow proliferation of a dominant clone may explain non-CR to CRT.

The constrained cross-talk between myeloid cells and T cells in the tumor immune microenvironment (TIME) restricts cancer immunotherapy efficacy, whereas the underlying mechanism remains elusive. Parkin, an E3 ubiquitin ligase renowned for mitochondrial quality control, has emerged as a regulator of immune response. Here, we show that both systemic and macrophage-specific ablations of Parkin in mice lead to attenuated tumor progression and prolonged mouse survival. By single-cell RNA-seq and flow cytometry, we demonstrate that Parkin deficiency reshapes the TIME through activating both innate and adaptive immunities to control tumor progression and recurrence. Mechanistically, Parkin activation by AMP-activated protein kinase rather than PTEN-induced kinase 1 mediated major histocompatibility complex I down-regulation on macrophages via Autophagy related 5-dependent autophagy. Furthermore, Parkin deletion synergizes with immune checkpoint blockade treatment and Park2-/- signature aids in predicting the prognosis of patients with solid tumor. Our findings uncover Parkin's involvement in suppressing macrophage antigen presentation for coordinating the cross-talk between macrophages and T cells.

Clonal hematopoiesis (CH)-the expansion of somatically mutated hematopoietic cells-is common in solid cancers. CH is associated with systemic inflammation, but its impact on tumor biology is underexplored. Here, we report the effects of CH on the tumor microenvironment (TME) using 1,550 treatment-naive patient samples from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) cohort. CH is present in 18.3% of patients, with one-third of CH mutations also detectable in tumor-derived DNA from the same individual (CH-Tum), reflecting CH-mutant leukocyte infiltration. Across cancers, the presence of CH-Tum is associated with worse survival outcomes. Molecular analyses reveal an association between CH-Tum and an immune-rich, inflammatory TME that is notably distinct from age-related gene expression changes. These effects are most prominent in glioblastoma, where CH correlates with pronounced macrophage infiltration, inflammation, and an aggressive, mesenchymal phenotype. Our findings demonstrate that CH shapes the TME, with potential applications as a biomarker in precision oncology.

As a common malignancy of the lower respiratory tract, non-small cell lung cancer (NSCLC) represents a major oncological challenge globally, characterized by high incidence and mortality rates. Recent research highlights the critical involvement of somatic mutations in the onset and development of NSCLC. Stratification of NSCLC patients based on somatic mutation data could facilitate the identification of patients likely to respond to personalized therapeutic strategies. However, stratification of NSCLC patients using somatic mutation data is challenging due to the sparseness of this data. In this study, based on sparse somatic mutation data from 4581 NSCLC patients from the Memorial Sloan Kettering Cancer Center (MSKCC) database, we systematically evaluate the metabolic pathway activity in NSCLC patients through the application of network propagation algorithm and computational biology algorithms. Based on these metabolic pathways associated with prognosis, as recognized through univariate Cox regression analysis, NSCLC patients are stratified using the deep clustering algorithm to explore the optimal classification strategy, thereby establishing biologically meaningful metabolic subtypes of NSCLC patients. The precise NSCLC metabolic subtypes obtained from the network propagation algorithm and deep clustering algorithm are systematically evaluated and validated for survival benefits of immunotherapy. Our research marks progress towards developing a universal approach for classifying NSCLC patients based solely on somatic mutation profiles, employing deep clustering algorithm. The implementation of our research will help to deepen the analysis of NSCLC patients' metabolic subtypes from the perspective of tumor microenvironment, providing a strong basis for the formulation of more precise personalized treatment plans.

The pancreas tumor microbiota may influence tumor microenvironment and influence survival in early-stage pancreatic ductal adenocarcinoma (PDAC); however, current studies are limited and small. We investigated the relationship of tumor microbiota to survival in 201 surgically resected patients with localized PDAC (Stages I-II), from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts. We characterized the tumor microbiome using RNA-sequencing data. We examined the association of the tumor microbiome with overall survival (OS), via meta-analysis with the Cox PH model. A microbial risk score (MRS) was calculated from the OS-associated microbiota. We further explored whether the OS-associated microbiota is related to host tumor immune infiltration. PDAC tumor microbiome α- and β-diversities were not associated with OS; however, 11 bacterial species, including species of Gammaproteobacteria, confirmed by extensive resampling, were significantly associated with OS (all Q < 0.05). The MRS summarizing these bacteria was related to a threefold change in OS (hazard ratio = 2.96 per standard deviation change in the MRS, 95% confidence interval = 2.26-3.86). This result was consistent across the two cohorts and in stratified analyses by adjuvant therapy (chemotherapy/radiation). Identified microbiota and the MRS also exhibited association with memory B cells and naïve CD4+ T cells, which may be related to the immune landscape through BCR and TCR signaling pathways. Our study shows that a unique tumor microbiome structure, potentially affecting the tumor immune microenvironment, is associated with poorer survival in resected early-stage PDAC. These findings suggest that microbial mechanisms may be involved in PDAC survival, potentially informing PDAC prognosis and guiding personalized treatment strategies.IMPORTANCEMuch of the available data on the PDAC tumor microbiome and survival are derived from relatively small and heterogeneous studies, including those involving patients with advanced stages of pancreatic cancer. There is a critical knowledge gap in terms of the tumor microbiome and survival in early-stage patients treated by surgical resection; we expect that advancements in survival may initially be best achieved in these patients who are treated with curative intent.

CD70, a member of the tumor necrosis factor family, has been implicated in various cellular processes associated with tumorigenesis. Despite its known expression in certain cancers, a detailed pan-cancer analysis and functional validation in clear cell renal cell carcinoma (ccRCC) have not been comprehensively explored. We conducted a pan-cancer analysis using publicly available databases to investigate the expression and prognostic significance of CD70 across various cancer types. For functional validation, immunohistochemistry was performed on ccRCC and adjacent normal tissues to evaluate CD70 expression levels. Additionally, ccRCC organoid model was developed and subjected to CAR-T cell cytotoxicity assays to evaluate the efficacy of targeting CD70 in vitro. The pan-cancer analysis revealed elevated expression of CD70 in several cancer types, including ccRCC, where it correlated with poor prognosis. Immunohistochemical analysis confirmed significant overexpression of CD70 in ccRCC tissues compared to normal tissues. In the ccRCC organoid model, CAR-T cells targeting CD70 demonstrated effective cytotoxicity against organoids expressing CD70. The overexpression of CD70 across diverse cancer types underscores its potential as a universal biomarker. Importantly, our findings underscore the clinical relevance of CD70 as a critical oncogenic factor and a promising therapeutic target in ccRCC, with implications for advancing personalized medicine.

The current understanding of the prognostic value of routine pre-treatment laboratory parameters in patients with high-risk soft tissue sarcoma (HR-STS) is limited. We sought to analyze several inflammatory biomarkers in a large cohort of HR-STS patients undergoing neoadjuvant therapy followed by curative surgical resection.

123 patients with locally advanced high-risk undifferentiated pleomorphic sarcoma (UPS), liposarcoma (LPS), leiomyosarcoma (LMS), and synovial sarcoma (SS) who underwent preoperative chemotherapy and regional hyperthermia (RHT) between 2014 and 2022 were retrospectively evaluated. The association of several pre-treatment laboratory parameters with radiologic treatment response, event-free survival (EFS), and overall survival (OS), were analyzed.

Low pre-treatment hemoglobin (HR 2.51, p = 0.018; HR 2.78, p = 0.030) and lactate dehydrogenase (LDH, HR 0.29, p = 0.0044; HR 0.23, p = 0.010) were significantly associated with EFS and OS in the multivariable analysis. Systemic inflammatory indices such as the neutrophil-to-lymphocyte ratio (NLR) did not have a significant impact on survival. Low C-reactive protein (CRP) and high albumin values were associated with poor radiologic response according to RECIST (p = 0.021 and p = 0.010, respectively).

Pre-treatment LDH and hemoglobin are strong independent predictors of survival in HR-STS patients. Systemic inflammatory indices based on circulating immune cells may not serve as reliable prognostic factors for HR-STS patients undergoing curative-intent treatment. Higher pre-treatment albumin levels and lower CRP values may reflect a reduced inflammatory status and could be associated with a poorer radiologic response to preoperative treatment.

Melanoma is a highly invasive malignancy with poor prognoses in advanced stages. Developing a risk model that can accurately assess prognosis and guide personalized treatment is crucial for improving the clinical management of melanoma. This study aims to develop and validate an immune-based prognostic risk model for melanoma through comprehensive bioinformatics analysis. We collected transcriptomic data from multiple public databases and identified 9 immune features significantly associated with prognosis using single-sample Gene Set Enrichment Analysis (ssGSEA) and Cox regression. These features were utilized to construct the risk model, which was subsequently validated using relevant bulk transcriptomic datasets and single-cell transcriptomic datasets from the GEO database, encompassing diverse patient populations and sample types. The model effectively stratified patients into high-risk and low-risk groups with distinct survival outcomes. Further analysis revealed significant associations between the risk model and genomic heterogeneity indicators, such as tumor mutational burden (TMB), loss of heterozygosity (LOH), and immune checkpoint gene expression. The model robustness was confirmed using single-cell transcriptomic data, highlighting key genes with potential therapeutic relevance. Our findings provide a reliable prognostic tool and novel insights for personalized melanoma treatment, emphasizing the need for further clinical validation.

CD161, encoded by the killer cell lectin-like receptor B1 (KLRB1) gene, exhibits varied roles among different tumors. This study aimed to explore both the potential value of CD161 as a prognostic biomarker for hepatocellular carcinoma (HCC) and its association with immune cell infiltration.

A total of 109 HCC patients who underwent surgery were retrospectively analyzed. Immunohistochemistry, bioinformatic analyses, and statistical measurements were used to investigate the associations between CD161 expression, immune cell infiltration, and clinical outcomes in both public databases and in-house cohorts.

CD161 was highly expressed at both protein and mRNA levels in adjacent normal tissues compared to tumor tissues of HCC patients. Meanwhile, CD161 was enriched in HCC cases characterized by smaller tumor sizes (≤5 cm) and the absence of portal vein tumor thrombus. Individuals with high CD161 expression showed extended overall survival (OS) and relapse free survival (RFS) compared to those with lower CD161 levels. CD161 was identified as an independent prognostic indicator for both OS and RFS. In addition, the enrichment analysis indicated a close correlation between CD161 and immune response, as well as between CD161 and the signaling pathways of cytokines and chemokines, implying its role in immune regulation during cancer development. Specifically, CD161 expression was positively associated with immunomodulators and tumor-infiltrating immune cells, especially CD8+T cells, CD4+T cells, and dendritic cells. Multiple public databases showed that patients with high CD161 expression were more likely to derive benefits from immunotherapy.

CD161 was identified as a promising prognostic biomarker for HCC, as its expression indicates a favorable prognosis. Additionally, CD161 is closely linked to high infiltration of immune cells, participates in the regulation of the tumor immune microenvironment, and holds promise as a potential biomarker for predicting the efficacy of immunotherapy.

The phospholipid-modifying enzyme MBOAT2 plays a crucial role in iron homeostasis by inhibiting iron sequestration, thus preventing iron-induced cell death. It achieves this by remodeling the phospholipid composition of cell membranes through phospholipid metabolism. Although multiple studies have highlighted the significance of MBOAT2 in tumorigenesis, a comprehensive pan-cancer analysis has not been conducted to date.

In this study, we analyzed the expression levels of MBOAT2 using RNA sequencing data from the TCGA and GTEx databases. We also investigated MBOAT2 protein information using resources such as the Human Protein Atlas (HPA), GeneCards, and String databases. To assess the prognostic value of MBOAT2, we conducted survival analysis based on clinical data from TCGA. Additionally, we performed enrichment analysis using the R package "clusterProfiler" and explored the relationship between MBOAT2 expression and immune cell infiltration, as well as immune checkpoint interactions in TCGA datasets. Furthermore, we examined the correlation between MBOAT2 expression and clinical pathology through immunohistochemical analysis of breast, prostate, lung, and liver cancer tissues in the HPA database. Finally, western blotting was used to validate MBOAT2 protein expression in breast and prostate cancer cell lines.

Our analysis revealed that MBOAT2 was highly expressed in a wide range of cancer types, with its expression correlating with improved survival outcomes in the TCGA dataset. Moreover, we found a significant association between MBOAT2 expression and immune regulation, particularly in relation to immune cell infiltration and immune checkpoint interactions.

MBOAT2 holds promise as a prognostic biomarker and may serve as a target for immunotherapy in various malignancies. Further investigation into its role in cancer immunity could offer new insights into potential therapeutic strategies.

To enhance immunotherapy efficacy in pancreatic cancer, it is crucial to characterize its immune landscape and identify key factors driving immune alterations. To achieve this, we quantitatively analyzed the immune microenvironment using multiplex immunohistochemistry, assessing the spatial relationships between immune and tumor cells to correlate with patient survival rates and oncological factors. Additionally, through Whole Exome Sequencing analysis based on public data, we explored genetic mutations that could drive these compositions. Finally, we validated T cell (Tc) migration mechanisms using patient-derived tumor organoids with induced KRAS mutation subtypes. Through this approach, we obtained the following meaningful results. First, immune cells in pancreatic cancer are denser in stromal regions than near tumor cells, with higher Tc distribution linked to increased patient survival rates. Second, the distance between tumor and Tc was within 100 μm, with higher Tc density found within 15-30 μm of the tumor cells. Third, while increasing CAF levels correspond to higher Tc density, higher ECM density tends to decrease Tc presence. Fourth, compared to KRAS G12D, KRAS G12V mutation increases various immune cells, notably Tc, which is closely linked to a dramatic rise in vascular cells. Finally, Tc migration was enhanced in tumor organoids with the G12V mutation, attributed to a reduction in the secretion of immunosuppressive cytokines. Our results indicate that KRAS mutation subtypes influence immune cell composition and function in the pancreatic cancer microenvironment, leading to varied immunotherapy responses. This underscores the need for personalized immune therapeutics and research models specific to KRAS mutations.

Nucleolar and spindle-associated protein 1 (PLIN3), a member of the perilipin family, plays a critical role in lipid droplet dynamics and is implicated in promoting tumor progression across several cancers. However, its influence on the tumor immune microenvironment and its potential as a prognostic indicator regarding immunotherapy responses have yet to be systematically evaluated. This study leverages data retrieved from multiple databases to address these questions.

PLIN3 mRNA and protein expressions were analyzed across a diverse range of normal and cancerous tissues, utilizing data retrieved from multiple databases. The potential of PLIN3 as a diagnostic and prognostic biomarker in cancers was assessed. Advanced computational algorithms were employed to examine the impact of PLIN3 on immune cell infiltration. The association between PLIN3 expression and the presence of M2 macrophages was validated through analyses incorporating bulk and single-cell transcriptomics, spatial transcriptomics, and multicolor fluorescence staining techniques. Furthermore, the effects of PLIN3 on tumor malignancy and growth were investigated in vitro in lung adenocarcinoma (LUAD) cells. Potential compounds targeting PLIN3 were identified using the Connectivity Map (cMap) web tool, and their efficacy was further assessed through molecular docking.

PLIN3 was predominantly upregulated in various cancers, correlating with adverse prognostic outcomes. A strong positive association was observed between PLIN3 levels and M2 macrophage infiltration in several cancer types, establishing it as a potential pan-cancer marker for M2 macrophage presence. This was confirmed by integrative multi-omics analysis and multiple fluorescence staining. Additionally, PLIN3 knockdown in LUAD cells diminished their malignant traits, resulting in decreased proliferation and migration. In LUAD, clofibrate was identified as a potential inhibitor of PLIN3's pro-oncogenic functions.

PLIN3 may serve as a potential biomarker and oncogene, particularly in LUAD. It plays a key role in mediating M2 macrophage infiltration in various cancers and presents a promising immunotherapeutic target.

Mesothelin (MSLN), a cell surface glycoprotein, is commonly expressed in several cancers, including 40% of triple negative breast cancer (TNBC) cases. Although its cellular or physiologic functions remain unclear, MSLN has been leveraged as a target for molecular therapies. This study investigates MSLN's potential role in TNBC, the breast cancer (BC) subtype with poorest outcomes.

The breast cancer (BC) cohorts from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 313), The Cancer Genome Atlas (TCGA, n = 160), and SCAN-B (n = 155) were used to obtain biological variables and gene expression data.

High MSLN expression was primarily observed in epithelial cells, and its expression was associated with reduced stromal adipocytes in the tumor microenvironment (TME), supporting its role as a TNBC surface marker. MSLN expression was also associated with the TNBC subtype and advanced N stages in BC. However, MSLN expression did not correlate with long-term survival outcomes, including overall survival (OS), disease-specific survival (DSS), or disease-free survival (DFS); nevertheless, it was still associated with favorable response to neoadjuvant chemotherapy (NAC). Indeed, MSLN-high tumors exhibited a proinflammatory microenvironment, higher cancer-testis antigen (CTA) scores, and increased immune cell activity, notably immature dendritic cells (iDCs) and M1 macrophages. Biologically, MSLN expression was linked to increased cellular proliferation, with gene set enrichment analysis (GSEA) showing enrichment in pathways related to rapid proliferation, such as G2M checkpoint and E2F targets.

MSLN-high TNBC is characterized by increased tumor grade, enhanced cell proliferation, and a proinflammatory microenvironment, showing better response to neoadjuvant chemotherapy without significant impact on long-term survival outcomes.

Immune checkpoint blockade (ICB)-based immunotherapy has significantly improved survival in advanced melanoma. However, many patients exhibit resistance to these therapies. This study examines the impact of BTLA promoter methylation on its expression, immune cell infiltration, and clinical outcomes, evaluating its potential as a prognostic and predictive biomarker for immunotherapy response.

We analyzed methylation and gene expression data from public datasets (The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO)) and an in-house cohort of melanoma patients treated with ICB therapy at the First Affiliated Hospital of Zhengzhou University. We developed a quantitative methylation-specific PCR (qMSP) assay to measure methylation levels of the cg24157392 and cg03995631 CpG sites, and a targeted bisulfite sequencing assay was used to validate the accuracy of qMSP. We measured BTLA protein expression using multiplex immunofluorescence and immunohistochemical staining methods. Pearson correlation, survival analysis, and immune cell infiltration estimation were conducted to explore the associations between BTLA promoter methylation, mRNA and protein expression, clinical outcomes, and immune characteristics.

Hypomethylation at CpG sites cg24157392 and cg03995631 in the BTLA promoter were significantly associated with higher BTLA mRNA and protein expression. In the TCGA dataset, low methylation at these sites predicted longer overall survival and was validated in an independent cohort of 50 stage III/IV melanoma patients, with an area under the curve of 0.94 for predicting 5-year survival. Furthermore, BTLA promoter hypomethylation correlated with higher infiltration of immune cells, such as CD8+T cells, CD4+T cells, B cells, and macrophages. Additionally, low methylation at cg24157392 and cg03995631, as quantified by the qMSP assay, was significantly associated with better progression-free survival in patients treated with immune checkpoint inhibitors. These findings were further validated using GEO datasets.

BTLA promoter hypomethylation serves as a significant biomarker for favorable prognosis and enhanced response to ICB therapy in melanoma. The developed qMSP assays for cg24157392 and cg03995631 accurately quantified methylation levels and demonstrated their potential for clinical application in patient stratification and personalized immunotherapy.

Disulfidptosis, a novel form of disulfide stress-induced cell death involved in tumor progression, hasn't be well defined the function in tumor progression. And the clinical impacts of disulfidptosis-related genes (DRGs) in pancreatic adenocarcinoma (PAAD) remain largely unclear. In this study, we identified two distinct disulfidptosis subtypes and found that multilayer DRG alterations were associated with prognosis and TME infiltration characteristics. A three-gene prognostic signature was constructed to predict prognosis, and its clinical significance was characterized in the TCGA-PAAD cohort. The disulfidptosis signature was significantly correlated with prognosis, molecular subtype, CD8 T-cell infiltration, response to immune checkpoint inhibitors and chemotherapeutic drug sensitivity, and its predictive capability in PAAD patients was validated in multiple cohorts. Meanwhile, two anti-PD-L1 immunotherapy cohorts confirmed that low-risk patients exhibited substantially enhanced clinical response and treatment advantages. Furthermore, the expression patterns of DRGs were validated by quantitative real-time PCR. The expression and prognostic predictive capability of GLUT1 were verified by 87 PAAD patients from our cohort. These findings may help us understand the roles of DRGs in PAAD and the molecular characterization of disulfidptosis subtypes. The disulfidptosis signature could be a promising biomarker for prognosis, molecular subtypes, TME infiltration characteristics and immunotherapy efficacy.

Recent studies suggest that the human microbiome influence tumor development. Endometrial carcinoma (EC) is the sixth most common malignancy in women. Recent research has demonstrated the microbes play a critical role in the development and metastasis of EC. However, it remains unclear whether intratumoral microbes are associated with tumor microenvironment (TME) and prognosis of EC. In this study, we collected the EC microbiome data from cBioPortal and constructed a prognostic model based on Resident Microbiome of Endometrium (RME). We then examined the relationship between the RME score, immune cell infiltration, immunotherapy-related signature, and prognosis. The findings demonstrated the independent prognostic value of the RME score for EC. The group with low RME scores had higher enrichment of immune cells. Drug sensitivity analysis revealed that the RME score may serve as a potential predictor of chemotherapy efficacy. In conclusion, our research offers new perspectives on the relationships between tumor immunity and microbes.

Lymphatic metastasis is a well-known factor for initiating distant metastasis of head and neck squamous cell carcinoma (HNSCC), which caused major death in most patients with cancer. Meanwhile, metabolic reprogramming to support metastasis is regarded as a prominent hallmark of cancers. However, how metabolic disorders drive in HNSCC remains unclear. We firstly established a new classification of HNSCC patients based on metabolism gene expression profiles from the TCGA and GEO database, and identified an enriched carbohydrate metabolism subgroup which was significantly associated with lymphatic metastasis and worse clinical outcome. Moreover, we found that highly activated pyruvate metabolism endowed tumors with EPHB2 upregulation and promoted tumor lymphangiogenesis independently of VEGF-C/VEGFR3 signaling pathway. Mechanically, high nuclear acetyl-CoA production from pyruvate metabolism promoted histone acetylation, which in turn transcriptionally upregulated EPHB2 expression and secretion in tumor cells. EPHB2 bound with EFNB1 in lymphatic endothelial cells promoted YAP/TAZ cytoplasmic retention, which alleviated YAP/TAZ-mediated prospero homeobox protein 1 (PROX1) transcriptional repression, and then triggered tumor lymphangiogenesis. Importantly, combined treatment with EFNB1-Fc and VEGFR3 inhibitor synergistic abrogated lymphangiogenesis in vitro and in vivo, suggesting that targeting EPHB2 might be a potential strategy to patients with no or slight response to VEGFR3 inhibitor. These findings uncover the mechanism by which pyruvate metabolism is linked to lymphatic metastasis of tumor and provides a promising therapeutic strategy for the prevention of HNSCC metastasis.

Metastatic uveal melanoma (mUM) is an aggressive cancer predominately affecting the liver. Peritoneal metastases (PM) occur rarely, and there is limited knowledge about this subgroup´s clinical course and biology.

We analyzed 41 mUM patients with confirmed PM from the Charité-Universitätsmedizin Berlin database, focusing on clinical characteristics, immune cell infiltrates, genetic alterations and tumor mutational burden (TMB).

The incidence of PM in mUM was 4.27 %. Metastatic disease was diagnosed 3.6 years after primary UM, with PM developing later (median: 4.7 years). Median overall survival (OS) from mUM diagnosis was 22.4 months. Prognosis correlated with metastatic pattern. Patients presenting with synchronous liver and peritoneal metastases or primary hepatic metastases followed by secondary peritoneal dissemination showed a median OS of 19.7 and 17.7 months, respectively. However, PM patients with exclusive extrahepatic disease at diagnosis of mUM had a significantly longer OS of 48.6 months and this metastatic pattern showed highly significant correlation with low and intermediate genetic risk. Metastasis-free survival and OS upon mUM diagnosis were significantly shorter in patients with high-risk UM tumors. TMB also correlated with metastatic pattern, being lowest in patients presenting with only extrahepatic disease. Higher TMB was generally associated with shorter OS.

PM in mUM patients is rare and in contrast to other extra-abdominal tumors does not worsen prognosis. Prognosis is greatly influenced by the metastatic pattern, which is determined by tumor biology, as evidenced by its correlation with genetic risk groups and TMB.

In advanced adrenocortical carcinoma (ACC), the response rate to immune checkpoint inhibition (ICI) is only ~15%. Glucocorticoid (GC) secretion and the activation of the Wnt/β-catenin pathway have been suggested to contribute to low tumour immune cell infiltration. The transcription factor lymphoid enhancer factor 1 (LEF-1) transduces β-catenin (CTNNB1)-mediated transcriptional activation.

To understand the contribution of Wnt/β-catenin pathway activation and glucocorticoid receptor (GR) signalling to the immunologically cold ACC tumour microenvironment.

Semi-quantitative immunohistochemistry (IHC) of β-catenin (CTNNB1), LEF-1, GR and T cell markers CD3, CD4, CD8, Fox P3 in 59 ACC samples. Targeted RNA expression analysis of 354 immune-related genes in 58 additional ACC tissue specimens. Correlative analyses with clinical data.

Nuclear LEF-1 and CTNNB1 protein expression were positively correlated in ACC tissue (Pearson R2 = 0.1283, p=0.0046). High, moderate and low protein expression was detected in 24.1%, 53.2% and 19.3% of samples for LEF-1, and 30.6%, 43.5% and 19.3% for CTNNB1, respectively. We found higher LEF-1 expression in GC-secreting tumours which did not differ from inactive tumours in terms of GR expression. T cell markers, as evaluated by IHC, were not associated with expression of Wnt/β-catenin pathway markers. At RNA level, tumours with high LEF-1 expression showed significant downregulation of 37 transcripts (including 8 involved in antigen presentation). High LEF-1 expression levels correlated with worse overall survival in this cohort. This was not the case for CTNNB1 and GR.

Lef-1 expression is useful as a biomarker of activated Wnt/β-catenin signalling in ACC. Wnt/β-catenin pathway activation was not associated with reduced immune cell markers in ACC but GC secretion and may be related to tumoural antigen presentation.

The escalating global cancer burden, projected to reach 35 million new cases by 2050, underscores the urgent need for innovative cancer biomarkers to improve treatment efficacy and patient outcomes. The TMED family, particularly TMED9, has garnered attention for its involvement in cancer progression; however, its comprehensive role across various cancer types remains poorly understood.

Utilizing multi-omics data, we analyzed the expression pattern, prognostic significance, genomic alterations, and immunological features of TMED9 in various cancer types. Through in vitro experiments, we paid special attention to its role in glioma, especially its correlation with glioma cell migration and invasion behavior.

Our findings reveal that TMED9 is significantly overexpressed in various tumor tissues and is associated with poor prognosis in cancers such as glioblastoma and lower-grade gliomas. Genetic analysis shows TMED9 mutations predominantly in kidney renal clear cell carcinoma, with its expression linked to chromosomal instability. Immunological analysis indicates that TMED9 correlates positively with immune cell infiltration, particularly macrophages, suggesting its role in promoting tumor immunity. Furthermore, TMED9 expression was negatively correlated with tumor stemness, indicating its potential influence on chemotherapy resistance. Knockdown of TMED9 led to reduced migration and invasion in glioma cell lines.

Our comprehensive analysis positions TMED9 as a critical player in cancer progression and immune modulation, especially in gliomas. Elevated TMED9 expression correlates with poorer outcomes and may serve as a prognostic marker and therapeutic target. Future research should focus on elucidating TMED9's mechanistic pathways and validating its role in clinical settings to enhance glioma treatment strategies.

Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.

CD8+ T-cell abundance is insufficient to assess antitumor immunity and shows poor performance in predicting breast cancer prognosis and immunotherapy response, presumably owing to the complexity of CD8+ T-cell functionalities. Although single-cell RNA sequencing can dissect the multifaceted functions of CD8+ T cells for better immune assessment, its clinical application is limited. In this study, we developed bulk RNA sequencing-based FuncDimen models from integrative analysis of single-cell RNA sequencing and matched bulk RNA sequencing data to evaluate CD8+ T-cell functionalities across five dimensions: tumor reactivity, cytotoxicity, IFNγ secretion, proliferation, and apoptosis. The FuncDimen models quantifying different functional dimensions of CD8+ T cells were validated in our breast cancer cohort and external databases using immunofluorescence and imaging mass cytometry. We calculated the FuncAggre score by weighted aggregation of all five FuncDimen models to encapsulate the overall antitumor immunity. In our breast cancer cohort and external databases, the FuncAggre score demonstrated superior predictive performance for breast cancer prognosis (time-dependent AUC: 0.56-0.70) and immunotherapy response (AUC: 0.71-0.83) over other immune biomarkers, regardless of the breast cancer molecular subtype. Together, the FuncDimen models offer a refined assessment of antitumor immunity mediated by CD8+ T cells in the clinic, enhancing prognostic prediction and aiding personalized immunotherapy in breast cancer.

Prior studies have demonstrated the association between immune cells and colorectal cancer (CRC). However, the causal link to specific immunophenotypes is limited. This study intends to elucidate the causal relationship of immune cell signatures on CRC.

We performed a bi-directional and two-sample mendelian randomization (MR) study, utilizing GWAS summary data of 731 immune cell traits (n = 3,757) and CRC statistics (n = 470,002). The primary MR methodology was inverse-variance weighted (IVW) method. Furthermore, heterogeneity was evaluated by Cochran's Q test. MR-PRESSO and MR-Egger were employed to assess horizontal and vertical pleiotropy respectively. Sensitivity analysis and FDR correction were conducted in our results. These results were validated in both the UK Biobank and FinnGen cohorts. We also extracted transcriptomic data of CRC and adjacent non-tumor tissues from TCGA, and used CIBERSORT to compare the infiltration patterns of 22 immune cell panels between normal tissues and the tumor microenvironment (TME).

Our study indicated nine immune cell signatures had significant causality with the risk of CRC after sensitivity analysis and FDR correction. The positive results covered four panels: B cell, CD8 + T cell, Treg, and monocyte. IgD- CD38br and IgD + CD38br B cell, CD8dim and CD28 + CD45RA- CD8dim T cell, and CD14 on CD14 + CD16- monocyte were the protective factors of CRC. However, CD39 + resting Treg, CX3CR1 on CD14- CD16 + monocyte, FSC-A on HLA DR + T cell, and BAFF-R on B cell increased the risk of CRC. The results were validated in the UK Biobank data and FinnGen cohorts. The data from the TCGA database also confirmed the infiltration of B cell, CD8 + T cell, Treg, and monocyte panels in the TME.

This study highlights the causal link between specific immune cell phenotypes and CRC, providing valuable insights into the immune microenvironment's role in CRC. The validation of our findings using large-scale datasets (UK Biobank, FinnGen) and TCGA underscores the robustness of our results, offering new potential therapeutic targets for CRC treatment.

Analyzing gene expression data from the Cancer Genome Atlas (TCGA) and similar repositories often requires advanced coding skills, creating a barrier for many researchers. To address this challenge, we developed The Cancer Genome Explorer (TCGEx), a user-friendly, web-based platform for conducting sophisticated analyses such as survival modeling, gene set enrichment analysis, unsupervised clustering, and linear regression-based machine learning. TCGEx provides access to preprocessed TCGA data and immune checkpoint inhibition studies while allowing integration of user-uploaded data sets. Using TCGEx, we explore molecular subsets of human melanoma and identify microRNAs associated with intratumoral immunity. These findings are validated with independent clinical trial data on immune checkpoint inhibitors for melanoma and other cancers. In addition, we identify cytokine genes that can be used to predict treatment responses to various immune checkpoint inhibitors prior to treatment. Built on the R/Shiny framework, TCGEx offers customizable features to adapt analyses for diverse research contexts and generate publication-ready visualizations. TCGEx is freely available at https://tcgex.iyte.edu.tr , providing an accessible tool to extract insights from cancer transcriptomics data.

SLC25A13, a pivotal component of the mitochondrial aspartate-glutamate carrier, is integral to cellular metabolism and has been linked to various diseases. However, its role in cancer biology remains largely unexplored. In this study, we employed multi-omics data to elucidate the genetic landscape, expression profile, and prognostic value of SLC25A13 in a pan-cancer context. Additionally, we examined the correlation between SLC25A13 and the immune microenvironment across various cancers. By applying multiple machine learning methods, we identified seven core SLC25A13 co-expressed genes and developed a nomogram to predict the prognosis of glioma patients, validating its efficacy across multiple independent datasets. Furthermore, in vitro and in vivo experiments demonstrated that SLC25A13 is significantly overexpressed in glioblastoma tissues compared to paraneoplastic tissues, promoting glioblastoma cell proliferation and migration while inhibiting apoptosis. Collectively, our study positions SLC25A13 as a promising biomarker for cancer prognosis and a potential therapeutic target, particularly in glioma, thereby laying the groundwork for future research into its therapeutic exploitation in cancer.