SEARCH · Search PubMed

Results for “TCGA”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

PubMed2026

Reduced VEPH1 expression is associated with an invasive phenotype and poor prognosis in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) remains a clinically heterogeneous urologic malignancy, and improved biomarkers are needed to refine prognostic stratification. VEPH1 has been implicated in cancer biology, but its role in ccRCC is incompletely defined. This study aimed to investigate the expression, prognostic relevance, and functional effects of VEPH1 in ccRCC. METHODS: VEPH1 transcript expression and prognostic relevance were evaluated using The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset and the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) and validated in paired ccRCC and adjacent normal renal tissues. The ability of VEPH1 transcript expression to distinguish tumor from normal tissues within the TCGA-KIRC dataset was assessed by receiver operating characteristic analysis. Gain- and loss-of-function experiments were performed in 786-O and 769-P ccRCC cells to determine the effects of VEPH1 on epithelial-mesenchymal transition (EMT)-related markers, migration, and invasion. AKT and ERK phosphorylation was evaluated by western blotting. RESULTS: VEPH1 transcript expression was significantly lower in ccRCC tissues than in normal renal tissues and distinguished tumor from normal samples within the TCGA-KIRC dataset. Low VEPH1 transcript expression was associated with poorer overall survival. Validation in 11 paired clinical specimens confirmed reduced VEPH1 messenger RNA (mRNA) and VEPH1 protein expression in tumor tissues. Functionally, VEPH1 overexpression increased E-cadherin, decreased N-cadherin, and suppressed migration and invasion, whereas partial VEPH1 knockdown produced the opposite changes. In exploratory signaling analyses, VEPH1 overexpression was associated with reduced AKT and ERK phosphorylation without altering total AKT or ERK levels. CONCLUSIONS: Reduced VEPH1 transcript expression was associated with poorer overall survival, whereas experimental VEPH1 depletion was associated with invasive and EMT-related features in ccRCC cells. VEPH1 may represent a candidate prognostic indicator in ccRCC; however, its relationship with AKT and ERK signaling and its clinical relevance require further mechanistic and independent-cohort validation.

Clear cell renal cell carcinoma (ccRCC)↗

PubMed2026

A machine learning-derived intratumoral heterogeneity-related signature predicts the prognosis for and therapeutic response in patients with skin cutaneous melanoma.

BACKGROUND: Reliable biomarkers for predicting prognosis and therapeutic response in skin cutaneous melanoma (SKCM) remain limited. This study aimed to develop an intratumoral heterogeneity (ITH)-related prognostic signature for SKCM using integrative machine learning. METHODS: RNA sequencing (RNA-seq) data from 472 SKCM patients in The Cancer Genome Atlas (TCGA) and 214 patients in the GSE65904 cohort were analyzed. ITH scores were calculated using the DEPTH2 algorithm. Differentially expressed genes (DEGs) were identified between high- and low-ITH groups [|log2fold change (FC)| ≥1, false discovery rate (FDR) <0.05]. Based on 38 prognostic DEGs identified by univariate Cox regression, we employed an integrative framework of 101 machine learning algorithm combinations to construct prognostic models in the TCGA training cohort. The model with the highest average concordance index (C-index) was validated in the GSE65904 cohort and selected as the prognostic ITH-related signature (PIRS). Associations of the PIRS risk score with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint gene expression, and drug sensitivity were systematically evaluated. Model performance was assessed using receiver operating characteristic (ROC) curves and Cox regression analyses. RESULTS: A 38-gene PIRS was constructed using the plsRcox algorithm. Patients with high PIRS risk scores exhibited significantly poorer overall survival (OS) in both the TCGA and Gene Expression Omnibus (GEO) cohorts. The PIRS was identified as an independent prognostic factor, with area under the curve (AUC) values of 0.779, 0.734, and 0.756 for 1-, 3-, and 5-year survival, respectively. High-risk samples displayed significantly lower TMB (P<0.05), reduced immune and stromal cell infiltration (P<0.001), downregulated immune function, and decreased expression of immune checkpoint genes. Additionally, high- and low-PIRS risk score groups exhibited distinct sensitivity patterns to different classes of targeted agents. CONCLUSIONS: The machine learning-derived PIRS robustly predicts prognosis in SKCM patients. Its clinical application is promising for optimizing patient risk stratification and treatment decisions, though further prospective validation is warranted.

Skin cutaneous melanoma (SKCM)↗

PubMed2026

SERPINE1-centric inflammatory signature associates with treatment resistance and survival in laryngeal squamous cell carcinoma.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) prognosis remains poor despite treatment advances. More accurate prognostic assessment models can help guide individualized treatment and improve prognosis. Chronic inflammation contributes to tumorigenesis, yet inflammatory response-related genes (IRGs) in LSCC prognosis are underexplored. This study aimed to construct an IRG prognostic signature for LSCC and further dissect core IRG-mediated mechanisms of immune escape and chemoresistance. METHODS: Transcriptional profiles and clinical data from LSCC patients were retrieved from The Cancer Genome Atlas (TCGA). IRGs were sourced from Gene Set Enrichment Analysis (GSEA) hallmark gene set. We identified differentially expressed IRGs linked to survival outcomes in LSCC. Key IRGs were subsequently selected using least absolute shrinkage and selection operator (LASSO) Cox regression analysis to establish an inflammatory risk score model. This model underwent internal validation within the TCGA cohort and external validation using independent Gene Expression Omnibus (GEO) datasets. We further assessed the model's association with the tumor immune microenvironment and the impact of IRGs on chemotherapy response. Finally, the functional roles of interested signature IRG were experimentally validated in LSCC cell lines. RESULTS: Four significant IRGs (AQP9, ITGA5, LCK, SERPINE1) were identified to build the risk score model. The model stratified LSCC patients into distinct prognostic groups: TCGA cohort: 5-year area under the curve (AUC) =0.836, P<0.001; GSE25727 cohort: 5-year AUC =0.706, P=0.02; GSE27020 cohort: 5-year AUC =0.798, P<0.01. Multivariate analysis confirmed the risk score as an independent prognostic factor (P<0.05). High-risk patients showed reduced immune cell infiltration (CD8+ T cells, dendritic cells) and suppressed immune pathways. Multi-algorithm immune analysis further revealed defective antigen presentation and reduced anti-tumor immune infiltration in high-risk LSCC, promoting tumor immune escape. GSEA/Gene Ontology (GO) enrichment combined with drug sensitivity prediction further revealed that high-risk tumors activate invasive signaling and acquire broad chemoresistance alongside impaired anti-tumor immunity. SERPINE1 might be associated with chemotherapy resistance and exhibited the highest alteration frequency (predominantly amplification) and overexpression in LSCC tissues. Its knockdown significantly suppressed proliferation, migration, invasion and chemoresistance in LSCC cells. Immunohistochemistry (IHC) confirmed tumor SERPINE1 overexpression (P=0.002 vs. normal tissues), correlating with poor survival (P<0.001). CONCLUSIONS: The 4-IRG risk signature is a reliable prognostic indicator reflecting immune dysfunction in LSCC. SERPINE1 is validated as a therapeutic target and biomarker, enriching our understanding of gene regulation dynamics in LSCC.

Laryngeal cancer↗

PubMed2026

PDE4DIP-Derived MMG8 Supports Proliferation, Migration, and Tumor Growth in Hepatocellular Carcinoma Models.

BACKGROUND: PDE4DIP encodes a scaffold protein that has been implicated in compartmentalized signaling and cytoskeletal organization, but the role of its myomegalin variant 8 (MMG8) isoform in hepatocellular carcinoma (HCC) remains unclear. To address this gap, we examined PDE4DIP expression in public HCC datasets and investigated the functional role of MMG8 in HCC models. METHODS: PDE4DIP expression was analyzed in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and two Gene Expression Omnibus (GEO) cohorts (GSE14520, GSE36376). MMG8 function was assessed in Huh7 cells using siRNA-mediated knockdown and in Hepa1-6 cells using lentiviral Clustered Regularly Interspaced Short Palindromic Repeats - CRISPR-associated protein 9 (CRISPR-Cas9)-mediated knockout. Cell proliferation in MMG8-KD Huh7 cells and MMG8-KO Hepa1-6 cells was assessed using Cell Counting Kit-8 (CCK-8) assays, while Huh7 cell migration was evaluated using Transwell assays. Tumor growth was assessed using a murine subcutaneous tumor model. Immunohistochemical staining for Ki67 and cleaved caspase-3 was employed to assess tumor cell proliferation and apoptosis-associated changes, respectively. Gene set enrichment analysis was performed in TCGA-LIHC tumors stratified based on PDE4DIP expression. RESULTS: PDE4DIP expression differed between tumor and non-tumor tissues across HCC cohorts, although the directionality of this difference was not uniform. MMG8 knockdown in Huh7 cells reduced proliferation and migratory activity. A single-cell-derived MMG8-KO Hepa1-6 clone exhibited reduced proliferation in vitro and formed smaller tumors in vivo, with lower Ki67 positivity but no significant difference in cleaved caspase-3 positivity between groups. In tumors from the TCGA-LIHC cohort, PDE4DIP expression was associated with distinct transcriptional programs. Specifically, PDE4DIP-high tumors presented with positive normalized enrichment score (NES) values for several metabolic pathways, whereas adhesion/extracellular matrix (ECM), cell cycle/proliferation, and translation/ribosome-related pathways exhibited negative NES values. CONCLUSIONS: These findings support a functional contribution of MMG8 to proliferative, migratory, and tumor-growth phenotypes in the tested HCC models. Bulk gene-level PDE4DIP expression in human tumors was associated with context-dependent transcriptional states and should not be interpreted as a direct surrogate for MMG8 function.

Liver Neoplasms↗

PubMed2026

Machine learning-integrated multi-omics risk prediction for pulmonary fungal infection in COPD and lung cancer: a transcriptomic and immune profiling study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and lung cancer are major risk factors for invasive pulmonary fungal infection (IPFI), carrying an attributable mortality of 30%-80%. Their coexistence further amplifies immunosuppression, while current diagnostic criteria remain inadequate for early risk identification. METHODS: Transcriptomic data from the GEO dataset GSE296912 (scRNA-seq; 12,078 cells from normal and COPD lung tissue) and The Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) bulk RNA-seq cohort (539 tumor and 59 normal samples) underwent differential expression and cross-omics integration analysis. Five machine learning models were constructed: logistic regression, SVM, random forest, XGBoost, and LASSO. Candidate genes were validated by qRT-PCR in A549 cells and THP-1-derived macrophages stimulated with heat-inactivated Aspergillus fumigatus conidia, a protocol selected to ensure BSL-2 biosafety compliance and isolate PAMP-mediated innate immune signaling. Model performance was evaluated using 5-fold stratified cross-validation with AUC, calibration curves, and decision curve analysis. RESULTS: Single-cell transcriptomic analysis of 12,078 cells identified 14 distinct cell populations, with marked myeloid expansion and immune dysregulation in COPD lung tissue. Cross-omics integration with TCGA-LUAD data identified 1,145 shared genes (79 immune-related), converging on NF-κB, TLR4, and cytokine receptor signaling. The random forest model achieved excellent discriminative performance (5-fold CV AUC = 0.988), with Treg infiltration, TLR4, and MMP9 as the top predictors. qRT-PCR confirmed significant upregulation of all five candidate genes (DEFB4A, S100A8, IL-8, MMP9, and TLR4) in both A549 and THP-1 cells following fungal stimulation. CONCLUSION: This multi-omics machine learning model integrating scRNA-seq and TCGA transcriptomic data demonstrates excellent discriminative performance (AUC = 0.988), with mechanistic convergence of NF-κB, TLR4, and oncogenic signaling pathways identified across shared immune gene signatures. In vitro qRT-PCR validation confirms the biological relevance of five key antifungal immune genes, providing a transcriptomic foundation for future prospective IPFI risk stratification in patients with COPD and lung cancer.

TLR4↗

PubMed2025

MicroRNA-122 overexpression suppresses the colon cancer cell proliferation by downregulating the astrocyte elevated gene-1/metadherin oncoprotein.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNAs that regulate essential cellular functions, such as cell adhesion, proliferation, migration, invasion, and programmed cell death, and therefore, alterations in miRNAs can contribute to carcinogenesis. Previous studies have shown that miRNA-122 is abundant in the liver and regulates cell proliferation, migration, and apoptosis. However, the expression pattern and mechanism of actions of miR-122 remain primarily unknown in colon cancer. METHODS: In this study, we analyzed The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) database to assess the clinical significance of astrocyte elevated gene-1 (AEG-1)/metadherin (MTDH) and miR-122 in colon cancer. MiR-122 overexpression studies were performed in HCT116, SW480, and SW620 cell lines. Dual-luciferase assay was carried out to confirm the interaction between AEG-1 and miR-122. In vivo-JetPEI-transfection reagent was used for in-vivo transient transfection of miR-122 in the AOM/DSS-induced colon tumor mouse model. RESULTS: Our results demonstrate that miR-122 was downregulated in colon cancer cells, and it influences the expressions of apoptotic factors and inflammatory cytokines. MiR-122 overexpression in HCT116, SW480, and SW620 cells showed upregulation of Caspase 3, Caspase 9, and BAX and decreased expression of BCL2, which are pro-apoptotic and anti-apoptotic members that maintain a ratio between cellular survival and cell death. In vivo transient transfection of miR-122 mimic in AOM/DSS induced colon tumor mouse model showed less inflammation and disease activity. The TCGA-COAD data indicated that AEG-1 expression was higher in patients with low expression of miR-122 and lower AEG-1 expression in patients with higher expression miR-122. CONCLUSION: Our findings highlight the key role of miR-122 in the high grade of colonic inflammation, and possibly in colon cancer, and the use of miR-122 mimic might be a therapeutic option.

MicroRNAs↗

PubMed2026

Tumor Suppressive Role of Hsa-miR-328-3p in Colon Cancer by Regulating EN2.

BACKGROUND/AIM: Colon cancer is a prevalent and life-threatening malignancy worldwide. Recent studies have focused on how microRNAs (miRNAs) act as post-transcriptional modulators in colon cancer progression. Herein, this study aimed to identify the impact of miRNAs that are decreased in colon cancer and to investigate their regulatory mechanisms. MATERIALS AND METHODS: Differentially expressed miRNAs (DEmiRNAs) and genes (DEGs) were identified through analysis of miRNA sequencing and RNA sequencing data from normal and tumor tissues in The Cancer Genome Atlas (TCGA). Expression levels were validated by quantitative polymerase chain reaction (qPCR) in both tissues and cell lines. Functional effects of miRNAs were evaluated by assessing cell viability, proliferation, migration, and invasion following transfection with miRNA mimics. RESULTS: Analysis of miRNA-seq data from the TCGA database identified hsa-miR-328-3p as a miRNA consistently downregulated across all stages of colon cancer. This downregulation was independently validated in colon cancer patient tissues by qPCR. Functional assays demonstrated that enforced expression of hsa-miR-328-3p significantly reduced cell viability, proliferation, migration, and invasion in colon cancer cell lines, supporting its tumor-suppressive role. To elucidate the molecular mechanism underlying these inhibitory effects, target gene analysis was performed. Engrailed homeobox 2 (EN2) was identified as a potential target of hsa-miR-328-3p, and a dual-luciferase assay confirmed that EN2 is directly regulated by hsa-miR-328-3p. CONCLUSION: Collectively, these findings indicate that hsa-miR-328-3p is frequently downregulated in colon cancer and functions as a tumor suppressor by negatively regulating its target gene, EN2, thereby contributing to colon cancer malignancy. EN2 may serve as a potential diagnostic biomarker for colon cancer, while restoration of hsa-miR-328-3p expression represents a promising therapeutic strategy. Further studies are needed to clarify the precise molecular mechanisms linking the hsa-miR-328-3p/EN2 axis to colon cancer progression.

Humans↗

PubMed2025

CS Ratio is an immune-related prognostic biomarker for cervical cancer.

BACKGROUND: The tumor microenvironment (TME) plays a crucial role in cancer progression but its complex structure significant variability among patients present considerable challenges for research. Recent studies have demonstrated that macrophage polarization states defined by the expression levels of CXCL9 SPP1 (CS Ratio) are more prognostically relevant than traditional M1/M2 markers. The CS polarization state reflects a highly coordinated network of pro-tumor anti-tumor variables offering a simplified yet effective immune response indicator for the complex TME. The CS Ratio has been shown to correlate with the abundance of anti-tumor immune cells the gene expression programs of tumor-infiltrating cells responses to immunotherapy. Cervical cancer, one of the most common gynecological malignancies, still faces limited therapeutic options. CXCL9, a member of the CXC chemokine family, plays a critical role in immune regulation, inflammation, tumor growth, angiogenesis, and metastasis. Similarly, SPP1, a cytokine, influences immune-related pathways by regulating molecules such as interferon-γ and interleukin-12. However, no studies have systematically investigated the role of the CS Ratio in cervical cancer or its relationship with immunotherapy characteristics. Research in this area could provide critical insights into the role and clinical potential of the CS Ratio in cervical cancer and related tumors. METHODS: The expression ratio of CXCL9 to SPP1 was analyzed in cervical cancer patients using data from the Gene Expression Omnibus (GEO) database, which revealed significant differences. Data for cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database. The optimal cutoff value for the CS Ratio was determined using the maxstat package in R, and Kaplan-Meier (KM) survival curves were constructed. Patients were categorized into High and Low groups based on the median CS Ratio. Immune scores were analyzed, and immune cell infiltration was assessed using CIBERSORT. Differences in the CS Ratio were evaluated across patients with varying pathological T stages and FIGO stages. Additionally, receiver operating characteristic (ROC) analysis was performed using the pROC package in R to calculate the area under the curve (AUC). Univariate and multivariate Cox regression analyses were performed to evaluate the potential of the CS Ratio as an independent prognostic factor in cervical cancer. A Cox regression-based nomogram integrating four key features was subsequently developed for the TCGA-CESC cohort. Nomogram performance was assessed using calibration curves and ROC analysis. RESULTS: The CS Ratio was significantly lower in cervical cancer patients compared to normal controls (P < 0.05). KM survival curves indicated that patients in the CS High group exhibited better prognoses. Immune score analysis revealed significantly higher immune scores (P < 0.05) and lower tumor purity (P < 0.05)in the CS High group compared to the Low group. CIBERSORT analysis revealed significantly higher proportions of CD8+ T cells (P < 0.05) and M1 macrophages (P < 0.05), and a significantly lower proportion of M2 macrophages (P < 0.05), in the CS High group compared to the Low group. The CS Ratio significantly decreased with advancing FIGO stage (P < 0.05). Both univariate (P < 0.05) and multivariate Cox regression analyses (P < 0.05) confirmed the CS Ratio as an independent prognostic factor. ROC analysis demonstrated that the CS Ratio had higher AUC values for predicting 1-year (AUC=0.69), 3-year (AUC=0.66), and 5-year OS (AUC=0.68) than CXCL9 or SPP1 alone. The Cox regression-based nomogram integrating four key features demonstrated predictive capability for 1-, 3-, and 5-year OS in CESC patients (Concordance Index = 0.751; 95% CI: 0.678-0.824; p = 1.50Í10-11). Significant survival differences were observed between the high-risk and low-risk groups based on the nomogram score. ROC analysis yielded high AUC values for survival prediction: 0.85 (95% CI: 0.94-0.75) at 1-year, 0.74 (95% CI:0.84-0.64) at 3-year, and 0.72 (95% CI:0.84-0.61) at 5-year. CONCLUSION: The CS Ratio may serve as a more effective prognostic biomarker for cervical cancer patients.

CXCL9↗

PubMed2026

Profibrogenic Gremlin-1 expression in prostate cancer and the clinicopathologic association.

BACKGROUND: Gremlin-1 (GREM1) is a profibrogenic molecule involved in TGF-β signaling. Recent studies have implicated GREM1 in androgen receptor (AR)-independent signaling and castration resistance in advanced prostate cancer. However, its compartment expression patterns and clinicopathologic significance in primary prostate cancer remain unclear. METHODS: GREM1 mRNA expression and clinicopathologic associations were analyzed in the Cancer Genome Atlas (TCGA) prostate adenocarcinoma (TCGA-PRAD), the Memorial Sloan Kettering Cancer Center (MSKCC), and the German Cancer Research Center (DKFZ) primary prostate cancer cohorts. Correlations between GREM1 and genes related to TGF-β signaling, extracellular matrix organization, fibroblast activation, and AR signaling were evaluated by Spearman analysis. GREM1 protein expression was examined by immunohistochemistry in commercial human prostate cancer tissue microarrays (TMAs) using compartment-specific QuPath-based H-scores. RESULTS: GREM1 expression was relatively elevated in prostate and bladder cancers. Across the three prostate cancer cohorts, higher GREM1 expression was associated with adverse pathologic features and was most consistently correlated with FAP. Inverse correlations were observed with selected AR-related genes, whereas no significant correlation was found with AR itself. Higher GREM1 expression was associated with shorter disease-free survival only in MSKCC but was not an independent prognostic factor after clinicopathologic adjustment. Quantitative immunohistochemistry in 43 patients showed higher epithelial than stromal GREM1 H-scores (median, 3.10 vs 1.41; P < 0.0001), with heterogeneous staining in both compartments. Neither epithelial nor stromal H-scores were associated with Gleason score or pathologic T stage. CONCLUSIONS: GREM1 mRNA expression in primary prostate cancer was associated with adverse clinicopathologic features, and a fibroblast-associated transcriptional context but did not demonstrate independent prognostic value. At the protein-level, GREM1 expression was heterogeneous in both epithelial and stromal compartments, with higher epithelial H-scores on average. These findings support further investigation of the biological significance of GREM1 expression in primary prostate cancer.

TCGA↗

PubMed2026

Effect of Tertiary Lymphoid Structures on Immune Cell Infiltration in the Tumor Microenvironment and Prognosis in Lung Adenocarcinoma.

Tertiary lymphoid structures (TLSs) modulate immune responses in various solid tumors, but their comprehensive role in lung adenocarcinoma (LUAD) remains unclear. In this study, we analyzed RNA-seq data from 539 LUAD patients in The Cancer Genome Atlas (TCGA) and microarray data from 223 samples from the Gene Expression Omnibus (GEO, GSE13213, and GSE37745). TLS signatures were evaluated via unsupervised consensus clustering based on 12 chemokine transcriptome signatures. The relationships between TLS and clinical characteristics, tumor microenvironment (TME) cell infiltration, and prognosis were assessed using ESTIMATE and CIBERSORT. A prognostic model was established using LASSO regression and validated with external datasets. Additionally, H&E and IHC analyses were performed to explore associations between intratumoral TLS density, immune-related molecular expression, and patient prognosis in LUAD. Consensus clustering of the TCGA cohort revealed two distinct LUAD patient clusters according to TLS abundance. Cluster 1 exhibited greater immune cell infiltration, more favorable prognosis, and increased expression of immune checkpoint molecules. We developed a prognostic model comprising eight survival-associated genes that act as independent prognostic factors for patient survival. H&E/IHC analyses revealed that TLS density-regardless of pathological stage-was associated with better prognosis; higher intratumoral TLS density/proportion was also related to more favorable outcomes. IHC confirmed that survival-associated genes (CD5, HLA-DMB, and P2RY13) are independent prognostic indicators in LUAD. Our study demonstrated the close relationship between TLS signatures and an active immune microenvironment, highlighting their potential as independent prognostic indicators in LUAD.

Humans↗

PubMed2026

Comprehensive In Silico Analysis Identifies MSTO1 and LIG1 as Candidate Biomarkers With Diagnostic and Prognostic Relevance in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and remains a major cause of cancer-related mortality worldwide. Its poor clinical outcomes are largely attributed to late-stage diagnosis and the limited accuracy of currently available diagnostic and prognostic biomarkers. Therefore, identifying novel molecular markers with improved sensitivity, specificity, and therapeutic relevance is essential for enhancing early detection and guiding personalized treatment strategies. AIMS: To identify and prioritize novel candidate HCC biomarkers with diagnostic and prognostic value and potential therapeutic vulnerability using integrated multi-omics, survival, functional dependency, and tumor microenvironment analyses. METHODS AND RESULTS: We examined the mRNA and protein expression levels of 8 DEGs in HCC tissues in the TCGA and CPTAC datasets using UALCAN, which showed that MSTO1 and LIG1 were overexpressed consistently in HCC relative to normal liver tissues. Moreover, elevated expression levels of these genes were significantly associated with higher tumor grade and advanced stage. Kaplan-Meier plotter survival data confirmed that increased expression of MSTO1 and LIG1 was associated with poorer overall survival. The DepMap CRISPR knockout data confirmed a functional dependency of both genes in HCC cell lines. CBioPortal analyses provided characterization of genomic alterations and enabled enrichment analysis of co-expressed genes, and the TCGA-UALCAN pan-cancer analyses supported the assessment of tissue specificity across tumor types. TIMER3 analyses linked candidate gene expression with immune cell infiltration patterns. Diagnostic performance by ROC analysis showed excellent discrimination for MSTO1 (AUC = 0.987) and good discrimination for LIG1 (AUC = 0.897). Multivariate Cox regression with Benjamini-Hochberg FDR correction across the eight genes supported MSTO1 as a candidate independent prognostic factor after adjustment for tumor stage, grade, etiology, age, and sex (HR = 1.29, p = 0.035), whilst LIG1 showed no independent prognostic value. Promoter methylation of MSTO1 and ADH4, assessed via UALCAN, showed that both genes were significantly differentially methylated in the promoter region of primary HCC tissues compared with normal liver tissues. Our study also confirmed the biological and clinical relevance of established HCC biomarkers: TERT, IRAK1, and ADH4. CONCLUSION: MSTO1 and LIG1 emerged as candidate diagnostic biomarkers in HCC. Additionally, MSTO1 showed a candidate prognostic association with overall survival that remained significant after adjusting for tumor stage, grade, and etiology, as well as patients' age, but not after further adjustment for AFP status. Functional data also highlighted MSTO1 as a candidate therapeutic dependency. On the other hand, LIG1 showed no independent prognostic association in either multivariate model. Their differential expression and functional essentiality in HCC cell lines highlighted their value for further experimental and independent-cohort validation before potential integration into biomarker development pipelines aimed at improving early detection and targeted therapy in HCC.

Humans↗

PubMed2025

The protective role of γδ T cells in endometrial cancer.

Γδ T cells are non-conventional T cells that are not MHC restricted and have T cell receptors (TCRs) that are stimulated by phosphoantigens, stress-induced proteins, lipids, and other antigens. These cells are prognostic across cancer types in The Cancer Genome Atlas (TCGA) but have not been well studied in endometrial cancer, which has a rising incidence and mortality rate. Endometrial cancer patients have variable responses to checkpoint inhibitors which are related to the molecular subtype of their cancer. As such, there is a pressing need to understand the immune microenvironment in endometrial cancer. This study addresses this gap in knowledge by investigating γδ T cell repertoires and transcriptomes in this disease site. γδ T cell repertoires were obtained for 543 endometrial cancer patients within the TCGA and from 5 endometrial cancer patients in the single cell dataset SRP349751 using TRUST4. GLIPH2 was used to identify TCRs predicted to bind the same antigen. Transcriptomes were investigated in the single cell dataset. DNA Polymerase Epsilon Exonuclease (POLE) and Microsatellite Instability High (MSI-H) endometrial cancer subtypes had the most γδ T cell infiltration. Vδ1 and Vδ3 γδ T cell infiltration was prognostic independent of stage and molecular subtype. GLIPH2 analysis revealed TCRδ motifs for TDK, YTD, and GEL were public across all four molecular subtypes and were present in the single cell data set. Vδ1 γδ T cell transcriptomes were associated with cytotoxicity and recent TCR stimulation. These data support further investigation of immunotherapies targeting γδ T cells in endometrial cancer.

Humans↗

PubMed2025

Integrating necroptosis and immune landscapes: a multi-omics-derived NecropImmScore stratifies prognosis and therapy in ovarian cancer.

BACKGROUND: Ovarian cancer (OC) remains the deadliest gynecologic malignancy, largely due to its immunosuppressive tumor microenvironment (TME) and resistance to therapy. Necroptosis, a regulated lytic cell death pathway mediated by the RIPK1-RIPK3-MLKL axis, can trigger immunogenic cell death, but its specific role in shaping the OC immune landscape and its clinical translation potential are posorly understood. METHODS: We employed multi-omics analysis (transcriptomics, genomics, clinical data) from TCGA-OV (n = 380), ICGC OV-AU, and IMvigor210 cohorts, combined with rigorous in vitro functional validation using OC cell lines (SKOV3, HEY), macrophages (THP-1 derived), and T cells (Jurkat). Computational immunology approaches (ESTIMATE, CIBERSORT, ssGSEA) quantified immune infiltration. We identified MLKL-associated immune genes, performed survival analysis (Kaplan-Meier, Cox regression), and constructed a necroptosis-immune signature (NecropImmScore) using consensus clustering and PCA of 102 prognostic genes. Drug sensitivity was predicted via pRRophetic and CellMiner. RESULTS: MLKL emerged as a protective prognostic biomarker (p = 0.018), significantly correlated with enhanced immune infiltration (ImmuneScore, StromalScore, ESTIMATEScore; p < 2.22e-16), M1 macrophage polarization (p = 0.006), activated CD4 + T cells (p = 0.003), and elevated immune checkpoint expression (PD-L1, CTLA4, LAG3, TIGIT). In vitro, MLKL overexpression in OC cells promoted M1 polarization (p < 0.05), activated Jurkat T cells (upregulated CCR4/5/7/9, CD69, CD3D/E, GZMB; p < 0.05), and induced key chemokines (CXCL9/10/11/13) critical for immune cell recruitment. Integration of MLKL-related and immune-related DEGs (n = 632) revealed enrichment in T-cell activation, chemokine signaling, and antigen presentation pathways (FDR < 0.05). Consensus clustering based on 102 survival-associated genes defined three molecular subtypes (Clusters A-C) with divergent survival (p = 0.019), necroptosis activity, and immune infiltration (Cluster C: best prognosis, highest MLKL/ImmuneScore). The derived NecropImmScore robustly stratified patients: high-score correlated with superior overall survival (TCGA: p < 0.001; ICGC: p = 0.014), inflamed TME phenotype, elevated checkpoint expression, and improved response to anti-PD-L1 in IMvigor210. Critically, high NecropImmScore predicted higher BRCA1 mutation frequency (AUC = 0.802), synergy with BRCA1 status for prognosis, higher homologous recombination deficiency (HRD) score, sensitivity to cisplatin (p = 0.014), paclitaxel (p = 0.016), gemcitabine (p = 0.017), and provided superior prognostic stratification when combined with TMB and HRD score (p < 0.001). CONCLUSION: This study establishes MLKL as a master regulator of anti-tumor immunity in OC, driving chemokine-mediated immune cell recruitment and TME reprogramming. The novel NecropImmScore is a multifaceted biomarker that effectively predicts prognosis, immunotherapy response, BRCA1 deficiency, and chemosensitivity, offering significant potential for guiding precision therapeutic strategies in OC.

Humans↗

PubMed2025

Low expression of HSP27 and HSP70 predicts poor prognosis in laryngeal squamous cell carcinoma.

PURPOSE: Molecular alterations drive the pathogenesis of laryngeal squamous cell carcinoma (LSCC), yet reliable prognostic biomarkers remain elusive. Heat shock proteins (HSPs), which mediate cellular stress responses, are implicated in cancer progression and treatment resistance. This study aimed to evaluate whether HSP27 and HSP70 expression correlate with clinicopathological features and survival outcomes in LSCC. Specifically, we assessed their potential as prognostic biomarkers in this malignancy. METHODS: Immunohistochemistry was performed on 158 LSCC tissue samples from 40 patients and compared to 30 normal laryngeal tissue samples. Expression levels of HSP27 and HSP70 were correlated with clinicopathological variables. Validation was conducted using transcriptomic and survival data from 112 LSCC cases in The Cancer Genome Atlas (TCGA). Kaplan-Meier and Cox regression analyses were used to assess survival. RESULTS: HSP27 was significantly overexpressed in LSCC tissues compared to controls and was associated with advanced tumor stage, nodal metastasis, alcohol abstinence, and older age. HSP70 expression correlated with higher tumor grade and female sex but did not differ significantly between cancerous and noncancerous tissues. In the TCGA cohort, low expression of HSP27 and HSP70 was significantly associated with worse overall survival. Low HSP27 expression emerged as an independent predictor of shorter survival (hazard ratio 2.28; 95% confidence interval, 1.11-4.67; p = 0.024). CONCLUSION: HSP27 and HSP70 show potential as prognostic biomarkers in LSCC, with high expression linked to favorable outcomes. These findings warrant further investigation into their mechanistic roles in tumor progression, therapy resistance, and their potential utility as therapeutic targets.

Humans↗

PubMed2026

Integrative Transcriptomic and Proteomic Profiling Identifies S100P as a Potential Functional Biomarker for Sessile Serrated Lesions.

BACKGROUND: Sessile serrated lesions (SSLs) account for 15% of colorectal cancers (CRCs) but detection remains difficult due to flat morphology, mucinous features, and subtle histology. AIMS: This study aimed to identify novel and functionally relevant biomarkers of SSLs using transcriptomic screening and multi-omics validation. METHODS: Paired SSL and normal mucosa specimens (n = 6) underwent RNA sequencing. Differentially expressed genes (DEGs) were filtered for membrane or secretory proteins and validated across TCGA and adenoma transcriptomes. Functional significance was assessed using CRISPR dependency profiling, proteotranscriptomic concordance, pharmacogenomic sensitivity, and connectivity map analysis. RESULTS: We identified 216 upregulated genes in SSLs, including 68 encoding secretory/membrane proteins that better discriminated SSLs from controls and were enriched for adhesion and neuronal signaling while suppressing TNFα-NFκB inflammatory pathways. Cross-cohort comparison revealed five overlapping candidates between SSLs and TCGA CMS1 tumors. Among them, S100P emerged as the primary biomarker candidate, showing consistent upregulation in SSLs and CMS1 tumors while remaining low in normal mucosa and conventional adenomas. TFF1 also showed RNA-level upregulation but appeared more context-dependent. S100P demonstrated strong RNA-protein concordance in CRC cell-line profiling, supporting its detectability as a biomarker candidate. Pharmacogenomic profiling of LS411N cells revealed marked sensitivity to SN-38 and fluoropyrimidines, consistent with serrated CRC vulnerabilities. Connectivity map analysis identified perturbations, including MAPK1 and histone acetyltransferase suppression, that may reverse parts of the SSL transcriptional program. CONCLUSION: These findings prioritize S100P as a promising biomarker candidate for SSLs that warrants further validation in larger cohorts and clinically applicable platforms.

Humans↗

PubMed2026

Intratumoral PD-1+LAG-3+CD8+ T cells are associated with improved prognosis in gastric cancer.

PURPOSE: PD-1 and LAG-3 are frequently used as markers of T cell exhaustion, yet the prognostic relevance and phenotypic characteristics of PD-1+LAG-3+CD8+ T cells in gastric cancer (GC) remain poorly defined. This study aimed to investigate their association with clinical outcomes and characterize their immune characteristics across independent GC cohorts. METHODS: Four independent GC cohorts were analyzed: the Zhongshan Hospital cohort (ZSGC, n = 298), The Cancer Genome Atlas cohort (TCGA, n = 371), an Immune Checkpoint Blockade cohort (ICB, n = 45), and the Yonsei cohort (n = 433). Intratumoral PD-1+LAG-3+CD8+ T cell infiltration was quantified by immunofluorescence staining and transcriptomic gene signature scoring. Survival analysis was performed using Kaplan-Meier estimation and multivariate Cox regression. Functional characterization was performed by flow cytometry on resected GC tissue. The immune microenvironment composition was evaluated using computational analyses. RESULTS: PD-1+LAG-3+CD8+ T cells were enriched within tumors compared to adjacent normal mucosa, and their infiltration correlated with advanced tumor stage, poor differentiation, microsatellite instability, and Epstein-Barr virus (EBV)-positive molecular subtypes. High intratumoral infiltration was significantly associated with improved overall survival in both the ZSGC and TCGA cohorts, whereas single-positive PD-1+CD8+ or LAG-3+CD8+ T cells showed no such association. In the ICB cohort, higher infiltration was associated with a higher response rate to pembrolizumab. Intratumoral PD-1+LAG-3+CD8+ T cells exhibit an activated phenotype characterized by increased expression of CD137, IFN-γ, perforin, and CXCL13, along with elevated TCF7 and lower PD-1 levels, suggesting a tumor-reactive, pre-exhausted state. High infiltration was further associated with an immune-active tumor microenvironment. CONCLUSIONS: High intratumoral infiltration of PD-1+LAG-3+CD8+ T cells is associated with favorable prognosis and an immune-active microenvironment in GC. These cells display phenotypic features consistent with a pre-exhausted state and may serve as independent prognostic biomarkers and candidate predictive biomarkers for immunotherapy stratification.

Humans↗

PubMed2026

Bioinformatic analysis reveals the potential association of ESRP1 with the splicing of cytoskeleton-associated genes in doxorubicin-resistant MCF7 breast cancer cells.

BACKGROUND: Breast cancer remains one of the most prevalent malignancies among women, with doxorubicin resistance posing a significant challenge that undermines treatment success and survival outcomes. Aberrant alternative splicing (AS), driven by dysregulation or mutations in splicing factors (SFs), is implicated in cancer initiation, progression, and drug resistance. This study aims to investigate the association of the epithelial cell-specific splicing factor ESRP1 with doxorubicin resistance in breast cancer, focusing on how ESRP1 deficiency correlates with AS changes that promote chemoresistance. METHODS: We analyzed RNA-sequencing (RNA-seq) data from doxorubicin-resistant (MCF7-DR) and parental (MCF7) breast cancer cell lines to identify enhanced alternative splicing events (ASEs) and changes in ESRP1 expression; we further leveraged The Cancer Genome Atlas (TCGA)-BRCA cohort to construct an SF-RASE correlation network for screening core SFs (including ESRP1). An integrative analysis combining crosslinking immunoprecipitation (CLIP-seq) data and The Cancer Genome Atlas (TCGA) database was performed to validate ESRP1 binding targets and assess the association between ESRP1-related splicing and cytoskeleton organization. RESULTS: We observed extensive AS changes and significantly downregulated ESRP1 expression in MCF7-DR cells. Integrative analysis identified 61 high-confidence ASEs that correlate with ESRP1 expression. Further bioinformatic integration suggests that ESRP1 expression is associated with the splicing patterns of SPTBN1, MAP2K7, FGFR3, and CYB561A3-four genes involved in cytoskeleton organization-though direct experimental verification to confirm a causal regulatory relationship between ESRP1 and the splicing of these genes is still pending. CONCLUSIONS: Our findings suggest that ESRP1 expression is closely associated with doxorubicin resistance in breast cancer cells, with concomitant alterations in key ASEs linked to cytoskeletal remodeling that correlate with ESRP1. Exploring the ESRP1-related splicing network may offer new strategies to overcome chemoresistance and improve patient outcomes. However, the small cell line sample size (n = 2 per group) constrains the robustness of ASE and SF-ASE correlation findings, and these results should be interpreted with caution and require further validation with larger sample cohorts.

Alternative splicing↗

PubMed2026

ceRNA network of lncRNAs and mRNAs in OSF-to-OSCC progression: Diagnostic biomarkers and functional pathways.

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic potentially malignant disorder that can progress to oral squamous cell carcinoma (OSCC). Although dysregulated non-coding RNAs have been implicated in oral carcinogenesis, the competing endogenous RNA (ceRNA)-mediated regulatory mechanisms underlying OSF-to-OSCC progression remain poorly understood. This study aimed to identify candidate regulatory molecules and construct a putative lncRNA-miRNA-mRNA network associated with malignant transformation. METHODS: Publicly available microarray datasets (GSE117973 and GSE125866) were analyzed to identify differentially expressed genes between OSF and OSCC. Differentially expressed transcripts were classified into mRNAs and lncRNAs based on public transcript annotations. Highly correlated lncRNA-mRNA pairs were identified using Pearson correlation analysis and integrated with multiMiR-supported miRNA-mRNA interactions obtained from public databases to construct a putative ceRNA regulatory network. Functional characterization focused on apoptosis, epithelial-mesenchymal transition (EMT), and immune checkpoint-related pathways. Receiver operating characteristic (ROC) analysis was performed to evaluate diagnostic performance, and selected biomarkers were externally validated using The Cancer Genome Atlas (TCGA) OSCC cohort. RESULTS: Integrated transcriptomic analysis identified several dysregulated mRNAs and lncRNAs associated with OSF-to-OSCC progression. Network analysis highlighted TBC1D3B, RREB1, TEAD3, SREBF1, TMEM41B, FOXK2, and KIAA1958 as prominent hub genes within the putative regulatory network. Functional analyses demonstrated significant associations with apoptosis-, EMT-, and immune checkpoint-related genes, suggesting potential involvement in multiple biological processes contributing to malignant transformation. Several hub genes exhibited strong diagnostic performance, with ROC analysis yielding AUC values ranging from 0.891 to 1.000, indicating excellent discrimination between OSF and OSCC samples. External validation using TCGA further supported the relevance of the identified biomarkers in OSCC. CONCLUSIONS: This study provides a comprehensive transcriptomic framework describing putative lncRNA-miRNA-mRNA regulatory interactions associated with OSF progression to OSCC. The identified hub genes and regulatory networks represent candidate biomarkers for early detection and provide a foundation for future mechanistic and experimental validation. As the proposed ceRNA interactions are computationally inferred, further biological validation is required before clinical application.

RNA, Long Noncoding↗