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PubMed2026

FGF19 as a site-specific candidate biomarker in colorectal neuroendocrine carcinomas.

PURPOSE: Gastrointestinal neuroendocrine carcinomas (GI-NECs) are aggressive tumors with marked site-specific heterogeneity, yet molecular markers for colorectal origin are lacking. This study characterized genomic and protein expression profiles to identify origin-specific biomarkers. METHODS: Nineteen GI-NECs (7 esophageal, 6 gastric, 6 colorectal) were analyzed by targeted next-generation sequencing (NGS) of 425 genes and immunohistochemistry (IHC). Genetic variations across primary sites were compared, and associations between FGF19 expression, clinicopathological features, microsatellite (MS) status, and tumor mutational burden (TMB) were assessed. FGF19 transcriptional expression was further examined in The Cancer Genome Atlas (TCGA) colorectal cohort using the UALCAN platform. RESULTS: A total of 163 genomic alterations were identified. FGF19 was the only gene showing site-specific alterations, being exclusively mutated or amplified in colorectal NECs (50%, 95% CI: 11.8-88.2%) with significantly elevated protein expression (83.3%, 95% CI: 35.9-99.6%) compared with other sites. A microsatellite instability-high (MSI-H) subgroup (10.5%, 95% CI: 1.3-33.1%) exhibited markedly higher TMB. TCGA data confirmed upregulated FGF19 in colorectal tumors but showed no survival association, consistent with the prognostic neutrality in our cohort. CONCLUSIONS: FGF19 may act as a site-specific candidate biomarker for colorectal NECs, with 83.3% protein positivity and exclusive site-specific alterations in 50% of cases. Detection of MSI-H suggests that mismatch repair (MMR) testing may be considered in selected patients with suggestive clinical or family histories to inform immunotherapy decisions.

FGF19↗

PubMed2026

A targetable dependency on nonsense-mediated decay for cellular homeostasis and immune control in small cell lung cancer.

Small cell lung cancer (SCLC) is one of the most aggressive malignancies, characterized by rapid metastatic dissemination and poor overall survival. Despite harboring excessive alterations, expectedly resulting in immunogenic neoantigens, patients with SCLC remain largely refractory to immunotherapy. We found abundant frameshift mutations in SCLC, regarded as highly immunogenic, counterbalanced by a hyperactive nonsense-mediated decay (NMD) pathway, responsible for frameshift-mRNA degradation. NMD activity correlated with tumor mutational burden (TMB) across cancers, suggesting that SCLC and other TMBhigh cancers may depend on NMD to limit the accumulation of mutation-derived byproducts in order to maintain cellular homeostasis and evade immune recognition. In TMBhigh SCLC models, inhibition of NMD impaired cell proliferation and induced ER stress-dependent apoptosis due to the accumulation of misfolded proteins. Genetic and pharmacological NMD inhibition in vivo effectively controlled TMBhigh tumor growth without overt toxicity. By integrating genome and transcriptome sequencing with MHC-I immunopeptidomics and functional in vitro and in vivo assays, we identified that NMD inhibition boosted neoantigen expression and presentation by tumor cells and increased T cell recognition, thus enhancing overall tumor immunogenicity and further improving immunotherapy efficacy in vivo. Our work shows that SCLC - as a TMBhigh cancer - relies on NMD for survival and immune escape, uncovering a novel TMB-dependent tractable vulnerability for this devastating disease.

Humans↗

PubMed2026

Multi-Omics Integration Identifies a Five-Gene Metabolic Signature With Experimental Validation in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is hallmarked by profound metabolic reprogramming; however, its intricate crosstalk with the tumor immune microenvironment (TIME) and its clinical ramifications remain inadequately elucidated. This study aims to systematically decipher the metabolic-immune interplay in ccRCC through multi-omics integration, with the goal of identifying robust prognostic biomarkers and actionable therapeutic vulnerabilities. AIMS: This study aims to systematically decipher the metabolic-immune interplay in clear cell renal cell carcinoma (ccRCC) through multi‑omics integration, and to identify robust prognostic biomarkers and actionable therapeutic vulnerabilities that can inform precision risk stratification and individualized treatment strategies. METHODS: We integrated bulk transcriptomic, genomic, and clinical data from multiple ccRCC cohorts. Differential expression and functional enrichment analyses were performed to characterize metabolic pathway alterations. Mendelian randomization (MR) was employed to infer causal relationships between metabolic disorders and ccRCC risk. A machine learning-based prognostic framework, incorporating SHAP (SHapley Additive exPlanations) for feature interpretability, was constructed and rigorously validated. TIME heterogeneity was dissected using deconvolution algorithms, while drug sensitivity, tumor mutation burden (TMB), and TIDE scores were utilized to assess therapeutic responses and immune evasion. Candidate gene function was evaluated through in vitro gain- and loss-of-function assays, with expression validated via TCGA, HPA, western blot, and qRT-PCR. RESULTS: Enrichment analysis identified coordinated dysregulation in lipid metabolism, energy homeostasis, and hypoxia response pathways. MR analysis confirmed lipid metabolism disorders as a causal risk factor for ccRCC. Our machine-learning model, centered on five core SHAP-identified features (SUCLA2, ACAT1, PC, SUCLG1, and HMGCS2), demonstrated superior predictive accuracy over conventional clinical staging. Immune profiling unveiled dichotomous TIME states: the low-risk group retained active immune surveillance, whereas the high-risk group was enriched with immunosuppressive subsets. Drug sensitivity screening pinpointed LY2109761 and carmustine as high-risk-specific candidate agents. Furthermore, TMB and TIDE analyses stratified high-risk patients displaying genomic instability and immune evasion phenotypes. Functionally, SUCLA2 knockdown significantly enhanced ccRCC cell proliferation and invasion, while its overexpression suppressed these malignant phenotypes, corroborating its tumor-suppressive role. Expression patterns of the hub genes were consistently validated across multi-level datasets and experimental assays. CONCLUSION: This study establishes a precision oncology framework for ccRCC by functionally linking metabolic biomarkers, immunophenotypes, and stratified therapeutic strategies. Importantly, we identify SUCLA2 as a potential functional tumor suppressor and a promising target for further mechanistic and translational investigation.

Humans↗

PubMed2025

Comprehensive Analysis of Clinical and Molecular Features in Cancer Patients Associated With Major Human Oncoviruses.

Viral infections contribute to a higher incidence of cancer than any other individual risk factor. This study aimed to compare the clinical and molecular features of four viral-associated cancers: stomach adenocarcinoma (STAD), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and cervical squamous cell carcinoma (CESC). Patients were categorized based on viral infection status, as provided in the clinical data, into virus-associated and non-virus-associated groups, followed by a comprehensive comparison of clinical and molecular features. Our analysis disclosed that viral infections confer unique clinical and molecular signatures to their associated tumors. Specifically, human papillomavirus-associated (HPV+) HNSC and hepatitis B virus-associated (HBV+) LIHC patients were predominantly male, younger, and exhibited better clinical prognoses. Virus-associated tumors displayed enhanced immune microenvironments and high DNA damage response scores, while non-virus-associated tumors were enriched in stromal signatures. HPV+ HNSC and Epstein-Barr virus-associated (EBV+) STAD showed similarities across multi-omics features, including better responses to immunotherapy, lower TP53 mutation rates, tumor mutation burden (TMB), and copy number alteration (CNA). Conversely, HBV+, Hepatitis C virus-associated (HCV+) LIHCs and HPV+ CESC were more genomically unstable due to high TP53 mutation rates, TMB, and CNA. At the protein level, Caspase-7 and Syk were upregulated in HPV+ HNSC and EBV+ STAD, and positively correlated with the enrichment levels of CD8 + T cell, PD-L1, and cytolytic activity. Patient stratification based on infection status has significant clinical implications, particularly for patient prognosis and drug response.

Humans↗

PubMed2026

Sodium Overload-Related Molecular Subtypes and a Four-Gene Prognostic Signature Predict Survival, Immune Landscape, and Therapeutic Response in Acute Myeloid Leukemia.

Sodium overload has recently emerged as a critical metabolic stressor involved in cancer progression; however, its molecular characteristics and clinical relevance in acute myeloid leukemia (AML) remain unexplored. RNA-seq data sets, clinical annotations, and mutational profiles of AML patients were annotations from The Cancer Genome Atlas and integrated with Genotype-Tissue Expression normal samples. Sodium overload-related genes (SORGs) were obtained from GeneCards. Differentially expressed SORGs (DESORGs) screened by applying the limma statistical model, followed by univariate Cox proportional hazards regression, consensus clustering, functional enrichment, immune infiltration analysis, and pathway evaluation. A prognostic signature was developed through least absolute shrinkage and selection operator regression followed by multivariate Cox modeling. The model's performance was further verified in two external GEO data sets (GSE71014 and GSE37642). Nomogram construction, subgroup analysis, tumor mutational burden (TMB) assessment, drug sensitivity prediction, transcription factor (TF) analysis, and competing endogenous RNA (ceRNA) network analyses were also performed. A total of 57 DESORGs were identified, and 2 sodium overload-related molecular subtypes exhibited distinct survival, immune infiltration, and inflammatory pathway activation. A robust four-gene signature (DOCK1, GABRE, HTR7, ACSM1) stratified patients into high- and low-risk categories with significantly different survival across training and validation cohorts. High-risk patients displayed increased immune infiltration, higher TMB, reduced sensitivity to multiple chemotherapeutic drugs, and inferior predicted response to PD-L1 blockade. TF and ceRNA networks revealed multilayered transcriptional and post-transcriptional regulation of the signature genes. This study identifies sodium overload-related molecular heterogeneity in AML and establishes a validated four-gene prognostic signature that integrates genomic, immunologic, and therapeutic features, offering potential utility for personalized risk assessment and treatment optimization.

Humans↗

PubMed1979

Acquired hydrocephalus. IV. Determination of the absorption rate of albumin from the cerebrospinal fluid.

By quantitative isotope ventriculography (QIV), the absorption rate (lambda 2) of albumin in the cerebrospinal fluid (CSF) was determined. Regard was paid to the rate constants for the exchange of the albumin molecule between the serum and extravascular phase. The rate constant lambda 2 and mean biological transit time Tmb-2 were determined in 22 patients suspected of acquired hydrocephalus. QIV revealed that 8 patients were hydrocephalic, while 13 were non-hydrocephalic, and the findings were uncertain in one. In the patients with acquired hydrocephalus, it was demonstrated that lambda 2 and Tmb-2 were significantly reduced as compared with the non-hydrocephalic patients. By means of QIV, a curve was calculated and plotted for the biological decay from the head--the retention curve. From the initial slope of this curve (0--24 hours), the rate constant lambda 2 was calculated. A comparison of lambda 4 and lambd 2 revealed a highly significant correlation, which means that the retention curve gives an acceptable measure of the absorption rate of CSF-albumin.

Absorption↗

PubMed2026

Integrated pan-cancer profiling highlights OSR2 as a prognostic indicator and immune-associated biomarker.

BACKGROUND: Odd-skipped-related 2 (OSR2), encoded by the OSR2 gene, has been reported to function as a checkpoint associated with CD8⁺ T-cell exhaustion in the tumor microenvironment of solid malignancies, suggesting its potential as a therapeutic target to improve immunotherapeutic responses. Nevertheless, the molecular and clinical significance of OSR2 across diverse cancer types has not yet been systematically investigated, and its pan-cancer expression profile, prognostic implications, and associations with tumor immunity remain to be fully elucidated. METHODS: In this study, we integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) portal, and the Human Protein Atlas to construct a systematic pan-cancer profile of OSR2. The prognostic value of OSR2 was comprehensively assessed using univariate Cox regression, survival analysis, and receiver operating characteristic (ROC) curve analysis. In addition, we performed an in-depth analysis of the relationships between OSR2 and multiple molecular and immunological features, including copy number variation (CNV), DNA methylation, tumor mutational burden (TMB), microsatellite instability (MSI), immune-related gene expression, immune cell infiltration, and drug sensitivity, with the aim of exploring its potential immunological associations with the tumor microenvironment. RESULTS: OSR2 expression was significantly upregulated or downregulated in the majority of tumor tissues relative to normal counterparts and exhibited distinct cancer-type-specific patterns across clinical stages. CNV alterations and aberrant DNA methylation were closely associated with abnormal OSR2 mRNA expression in multiple cancers. Prognostic analyses indicated that OSR2 expression was significantly associated with overall survival, disease-specific survival, disease-free interval, and progression-free interval across multiple cancer types, showing either risk-associated or protective associations in a tumor-context-dependent manner. Furthermore, OSR2 expression showed strong associations with immune cell infiltration, particularly T-cell subsets, and was significantly correlated with the expression of multiple immune checkpoint-related genes across diverse malignancies. OSR2 expression was also closely associated with TMB, MSI, and sensitivity to multiple anticancer agents. CONCLUSION: Taken together, these findings suggest that OSR2 is associated with prognosis and immune-related features across multiple cancer types. OSR2 may be linked to features of the tumor immune microenvironment through its relationships with immune cell infiltration, immune checkpoint gene expression, and genomic instability, and thus may serve as a candidate biomarker for further investigation in cancer immunotherapy.

CD8⁺ T-cell↗

PubMed2026

Molecular and immune profiling of HER2-low, HER2 ultra-low, and HER2-null male breast cancer.

BACKGROUND: HER2 expression is described along a biological continuum from null to positive and serves as a critical biomarker for therapeutic guidance in breast cancer (BC). While HER2-low and ultra-low categories have emerged as actionable targets for antibody-drug conjugates (ADCs) in female BC, their molecular and immune characteristics remain largely unexplored in male breast cancer. METHODS: We profiled 214 male breast tumors using next-generation sequencing and whole-transcriptome sequencing to assess mutational, transcriptomic, and immune landscapes. Tumor mutational burden (TMB) was defined as high if > 10 mutations/Mb. Immune cell fractions were inferred using Quantiseq deconvolution. RESULTS: Among 214 samples, 66 (30.8%) were HER2-null, 53 (24.8%) HER2 ultra-low, 80 (37.4%) HER2-low, and 15 (7.0%) HER2-positive. HER2 ultra-low tumors exhibited a higher prevalence of PIK3CA mutations (39.2% vs 22.6%, p ≤ 0.05) compared to HER2-null. No significant differences were observed in TMB-high frequency or PD-L1 expression across subgroups. Immune composition differed primarily between HER2-null and HER2-expressing subgroups: HER2-ultra-low tumors showed higher B-cell infiltration, whereas HER2-null tumors were enriched in neutrophils. Transcriptomic analysis revealed upregulation of selected stemness-associated genes (NANOG, KLF4, POU5F1) and CEACAM1 in HER2-null tumors, while HER2-low and HER2-ultra-low tumors were largely similar across most molecular and immune readouts in this cohort. CONCLUSIONS: HER2-null male breast cancer appears to represent the most biologically divergent subgroup within the HER2-negative spectrum, whereas HER2-low and HER2-ultra-low tumors were largely similar in this cohort. These findings support further investigation of HER2-null disease as a distinct biological state and provide hypothesis-generating data for biomarker development in this rare population.

Male↗

PubMed2026

Integrating germline and tumor sequencing to improve hereditary cancer diagnosis and care.

A subset of cancers arises due to inherited germline pathogenic variants in specific genes, known as hereditary cancers. These genes typically include tumor suppressors, DNA repair and replication fidelity genes, and occasionally oncogenes. In most hereditary cancer syndromes, Knudson's two-hit hypothesis applies, where a second somatic event inactivates the remaining allele of a tumor suppressor or DNA repair gene, leading to tumorigenesis. Advancements in genome-wide sequencing have significantly enhanced our understanding of the mutational processes involved in hereditary cancers. In particular, the assessment of microsatellite instability (MSI), tumor mutational burden (TMB), and mutational signatures has emerged as a powerful tool for the identification of hereditary tumors. Tumors with high or ultra-high TMB often reflect underlying DNA repair deficiencies, while specific mutational signatures can pinpoint the defective pathway. These tumor mutational features are especially informative in syndromes involving mismatch repair (MMR), homologous recombination (HR), base excision repair (BER), nucleotide excision repair (NER), and polymerase proofreading. Moreover, tumor sequencing aids in the interpretation of germline variants, identifies somatic mosaicism, and helps differentiate hereditary from sporadic cancers. Additionally, tumor molecular features associated with DNA repair deficiencies offer insights into personalized therapies, such as the use of PARP inhibitors for BRCA1/2-deficient tumors and immune checkpoint inhibitors for MMR- and polymerase proofreading-deficient cancers. Tumor profiling also uncovers actionable mutations in oncogenes like RET and VHL, which can be targeted with specific therapies. This review explores the integration of tumor molecular features with germline genetic data to refine diagnosis, risk assessment, and therapeutic strategies in hereditary cancer.

Humans↗

PubMed2026

The clinical landscape of POLE-mutant colorectal cancer: a retrospective analysis of real-world outcome.

BACKGROUND: Pathogenic mutations in the POLE gene disrupt its proofreading function during DNA replication, causing an accumulation of erroneous nucleotide incorporations. This defect leads to a significantly elevated tumor mutation burden (TMB) and increased generation of tumor neoantigens. These molecular characteristics suggest a potential association between POLE-mutant tumors and distinct prognostic outcomes in colorectal cancer (CRC); however, clinical evidence supporting this correlation remains limited. METHODS: We retrospectively collected a cohort of CRC patients harboring pathogenic POLE mutations. Comparative analyses were performed between POLE-mutant and POLE wild-type CRCs regarding their clinical characteristics, prognostic outcomes, and genomic profiles. Additionally, we evaluated the response to immunotherapy in metastatic POLE-mutant CRC cases. RESULTS: Among 35,108 CRC patients, pathogenic POLE mutations were identified in 261 individuals, accounting for 0.74% of the cohort. The median age at diagnosis for POLE-mutant patients was 48 years, with a male predominance (74.4%) and a substantial proportion (50.4%) of tumors localized in the right-sided colon. All patients with pathogenic POLE mutations exhibited hypermutated phenotypes, characterized by a median TMB of 235.26 mutations per megabase (range: 71.20-719.00 mutations/Mb). In stage II CRC, POLE mutations were significantly associated with a reduced risk of recurrence (hazard ratio [HR] 0.344, 95% confidence interval [CI] 0.157-0.754, p = 0.008) when compared to POLE wild-type, microsatellite stable CRC patients. However, this association was not evident in stage III patients (HR 1.004, 95% CI 0.490-2.057, p = 0.992). Importantly, the incorporation of immune checkpoint inhibitors in first-line treatment regimens significantly improved progression-free survival (HR = 0.247, 95% CI 0.117-0.552, p = 0.0002) and overall survival (HR = 0.317, 95% CI 0.103-1.143, p = 0.0832) in metastatic CRC patients with pathogenic POLE mutations. CONCLUSIONS: Pathogenic POLE-mutant CRC constitutes a relatively rare, yet clinically important, subtype. These cancers exhibit distinct clinicopathological and genomic features. Our results indicate that mutations in the POLE gene may serve as a valuable prognostic marker and a potential indicator of benefit to immunotherapy in CRC, offering promising avenues for personalized treatment strategies.

Humans↗

PubMed2026

Clinicopathologic Features, Treatment Patterns, and Outcomes of Microsatellite Instability-High Gastric and Gastroesophageal Junction Adenocarcinoma: A Single-Institution Retrospective Analysis.

PURPOSE: Microsatellite instability-high (MSI-H) and deficient mismatch repair (dMMR) gastric or gastroesophageal junction (GEJ) adenocarcinomas are biologically distinct tumors with established sensitivity to immune checkpoint inhibitors (ICIs). However, real-world treatment patterns, response heterogeneity, and predictors of durable benefit remain poorly defined. METHODS: We retrospectively analyzed patients with biopsy-confirmed MSI-H/dMMR gastric/GEJ adenocarcinoma treated at a single center. Clinicopathologic, genomic, treatment, and outcome data were collected. Molecular profiling included ARID1A, RNF43, TP53, PIK3CA, KRAS, TGFBR2, and human epidermal growth factor 2 (HER2). ICIs-treated patients were classified as achieving clinical benefit (complete response, partial response, or durable stable disease ≥16 weeks) or no clinical benefit using iRECIST v1.1 and clinical assessment. Overall survival (OS) was estimated by using the Kaplan-Meier method. RESULTS: Thirty-four patients were identified (median age, 66 years; 53% male), including 21 with stage IV disease. Tumors were predominantly poorly differentiated (65%) and HER2-negative (94%), and 18% of patients had Lynch syndrome. Among 22 ICI-treated patients, 55% achieved clinical benefit, which was strongly associated with prolonged OS (P < .01). Most responses occurred at the first radiographic assessment (approximately 12 weeks). Elevated tumor mutational burden (TMB; ≥20 mutations/Mb) was present in 56% of patients but was not associated with clinical benefit (P = .40), and no individual genomic alteration significantly correlated with treatment outcome. Exploratory analyses suggested longer OS among patients with liver versus peritoneal metastases. Treatment was well tolerated, with predominantly low-grade immune-related adverse events. Baseline Eastern Cooperative Oncology Group performance status (0-1 v ≥ 2) was associated with clinical benefit (P = .049). CONCLUSION: Approximately half of the patients with MSI-H/dMMR gastric/GEJ adenocarcinoma cancers derived durable clinical benefit from ICIs, and treatment response was strongly associated with survival. Conventional genomic features, including TMB, did not predict clinical benefit, highlighting the need for additional biomarkers.

Humans↗

PubMed2024

A comprehensive analysis of ribonucleotide reductase subunit M2 for carcinogenesis in pan-cancer.

BACKGROUND: Although there is evidence that ribonucleotide reductase subunit M2 (RRM2) is associated with numerous cancers, pan-cancer analysis has seldom been conducted. This study aimed to explore the potential carcinogenesis of RRM2 in pan-cancer using datasets from The Cancer Genome Atlas (TCGA). METHODS: Data from the UCSC Xena database were analyzed to investigate the differential expression of RRM2 across multiple cancer types. Clinical data such as age, race, sex, tumor stage, and status were acquired to analyze the influence of RRM2 on the clinical characteristics of the patients. The role of RRM2 in the onset and progression of multiple cancers has been examined in terms of genetic changes at the molecular level, including tumor mutational burden (TMB), microsatellite instability (MSI), biological pathway changes, and the immune microenvironment. RESULTS: RRM2 was highly expressed in most cancers, and there was an obvious correlation between RRM2 expression and patient prognosis. RRM2 expression is associated with the infiltration of diverse immune and endothelial cells, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). Moreover, the cell cycle is involved in the functional mechanisms of RRM2. CONCLUSIONS: Our pan-cancer study provides a comprehensive understanding of the carcinogenesis of RRM2 in various tumors.

Humans↗

PubMed2026

Associations of TILs and genomic alterations in HER2+ early breast cancer.

This study investigated the associations between tumor-infiltrating lymphocytes (TILs), genomic features, and prognosis in HER2+ early breast cancer (EBC) patients receiving adjuvant trastuzumab. We retrospectively analyzed 864 HER2+ EBC patients from Shanghai Ruijin Hospital (2009-2017). The optimal threshold of TILs for predicting disease-free survival (DFS) and overall survival (OS) was explored. Whole-exome sequencing (WES) on 261 tumors assessed the mutational profiles, tumor mutational burden (TMB), and copy number alteration (CNA). Associations between these genomic features, TIL levels, and prognosis were further evaluated. TILs showed a right-skewed distribution (median: 15%, IQR: 1-30%), and higher TIL levels were significantly associated with hormone receptor negativity and high histologic grade (P < 0.001). A 15% TIL threshold optimally predicted prognosis, with low-TIL (≤15%, 63.0%) patients showing inferior DFS (HR: 1.63, P = 0.009) and OS (HR: 2.12, P = 0.037). WES identified frequent mutations in TP53 (62.8%), PIK3CA (34.5%), and BRCA2 (9.6%). A higher TIL density was observed in TP53-wild-type, low-TMB or low-CNA tumors (P < 0.05). PIK3CA mutations conferred a significant DFS advantage. Integrating TIL level with PIK3CA or BRCA2 mutational status yielded distinct DFS trajectories (log-rank P = 0.023 and 0.040, respectively); patients with both high TIL levels and either PIK3CA or BRCA2 mutations had the most favorable outcomes. Stromal TILs at a 15% cutoff provide robust prognostic information in trastuzumab-treated HER2+ EBC. Integrating TIL levels with PIK3CA or BRCA2 mutational status enables refined risk stratification, offering a practical framework for personalized treatment decisions.

Humans↗

PubMed2026

Pathomics-based machine learning models for predicting METTL5 expression and prognosis in lung adenocarcinoma.

BACKGROUND: METTL5, an N6-methyladenosine (m6A) RNA methyltransferase, has been implicated in tumor progression, but its prognostic value and non-invasive prediction in lung adenocarcinoma (LUAD) remain unclear. This study aimed to develop a pathomics-based machine learning model to predict METTL5 expression from histopathological images and evaluate its prognostic significance in LUAD. METHODS: A total of 327 LUAD patients from The Cancer Genome Atlas (TCGA) with matched hematoxylin and eosin (H&E) slides, transcriptomic, and clinical data were included and randomly divided into training and validation sets (7:3). Quantitative histopathological features were extracted using PyRadiomics. Feature selection was performed via maximum relevance minimum redundancy (mRMR) and recursive feature elimination (RFE), followed by construction of a Gradient Boosting Machine (GBM) model. A pathomics score (PS) was generated to assess prognostic relevance. Survival analyses, gene set variation analysis (GSVA), tumor mutational burden (TMB), immune infiltration analysis, and in vitro functional assays were conducted. RESULTS: METTL5 overexpression was independently associated with poor overall survival [hazard ratio (HR) =1.637, P=0.007]. The model achieved good predictive performance [area under the curve (AUC) =0.847 in the training set and 0.752 in the validation set]. High PS was significantly associated with worse survival and remained an independent prognostic factor (HR =1.563, P=0.03). Elevated PS correlated with altered metabolic pathways, increased TMB, and immune microenvironment changes. METTL5 knockdown reduced proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in A549 cells. CONCLUSIONS: The pathomics-based model accurately predicts METTL5 expression and provides prognostic stratification in LUAD, supporting its potential as a practical imaging-derived biomarker.

Methyltransferase-like 5↗

PubMed2026

Systematic characterization of neurotransmitter receptor dysregulation identifies a neural-related prognostic signature associated with biochemical recurrence in prostate cancer.

BACKGROUND: The nervous system is increasingly recognized to play a critical role in tumor initiation and progression. Central to this complex relationship are the interactions between neurotransmitters secreted by neurons and their receptors (neurotransmitter receptors, NTRs) expressed on cancer cells, which activate multiple intracellular signaling pathways. However, the spectrum of NTR dysregulation and its association with biochemical recurrence (BCR) in prostate cancer (PCa) has not been explored. Therefore, the aim of this study was to fill this gap. METHODS: We systematically characterized the expression profiles of 130 NTR genes by integrating bulk and single-cell transcriptomic data. Consistently dysregulated NTR (cdNTR) genes were identified and used to construct a PCa signature (PCaSig) using elastic-net regression. The robustness of PCaSig was evaluated across three independent cohorts. In addition, the associations of PCaSig with clinicopathological characteristics, genomic alterations, tumor immune-related characteristics, and biological pathways were comprehensively investigated. RESULTS: Thirteen cdNTR genes with strong cell-type specificity, particularly in luminal epithelial cells, were identified. PCaSig robustly stratified patients into distinct BCR risk groups across multiple independent cohorts and remained an independent predictor after adjustment for clinicopathological factors. High PCaSig scores were associated with aggressive clinicopathological features, elevated tumor mutation burden (TMB), suppression of neurotransmitter-related signaling, and activation of cell-cycle and immune-related pathways. Notably, PCaSig refined prognostic stratification regardless of TMB status and was associated with distinct immune-related characteristics, including immune checkpoint expression and immune cell infiltration. Incorporation of PCaSig into a clinical nomogram significantly improved prognostic accuracy and clinical net benefit. CONCLUSIONS: These findings establish NTR dysregulation as a previously underappreciated dimension of PCa and support PCaSig as a clinically relevant tool for personalized management.

Neurotransmitter receptor (NTR)↗

PubMed2026

Integrated bioinformatics analyses for GSDMB in carcinogenesis and progression of bladder cancer.

BACKGROUND: Emerging evidence suggests that pyroptosis influences the development of various diseases. Gasdermin B (GSDMB), an intracellular protein that executes pyroptosis, has recently attracted attention for its potential role in tumor biology. However, its specific function in bladder cancer (BLCA) remains unclear. Therefore, this study aimed to investigate the potential role of GSDMB in the carcinogenesis and prognosis of BLCA patients. METHODS: Mendelian randomization (MR) studies were conducted to examine relationships between the expression of GSDMB and BLCA with expression quantitative trait loci (eQTL) data. Then, GSDMB mRNA expression data and clinical characteristics of BLCA patients were retrieved from The Cancer Genome Atlas (TCGA) database. Cox regression was used to explore the relationship between GSDMB mRNA expression and patients' survival. Additionally, the correlation between GSDMB and the immune microenvironment, tumor mutational burden (TMB), tumor microenvironment (TME), and drug sensitivity in BLCA was examined. RESULTS: According to MR analysis based on eQTLs, GSDMB mRNA expression has positive causal effects on bladder carcinogenesis and the need for bladder surgery (P<0.05). The analyses of TCGA demonstrated an increased expression of GSDMB in BLCA tissues, correlating with improved patient survival. Additionally, elevated GSDMB mRNA expression was identified as an independent protective prognostic factor for BLCA, and it was associated with immune cell infiltration, TMB, TME score, and drug sensitivity. CONCLUSIONS: Elevated mRNA expression of GSDMB has a causal link to a higher risk of BLCA and the likelihood of bladder surgery, but also indicates a better prognosis. Thus, GSDMB exhibits dual effects and might serve as a potential biomarker for predicting onset and progression of BLCA. Nevertheless, further investigation of pathogenesis and mechanisms underlying GSDMB is warranted.

Bladder cancer (BLCA)↗

PubMed2026

A cuproptosis-related lncRNAs-based risk signature for predicting prognosis and immune status in glioma.

BACKGROUND: Glioma is one of the most prevalent primary malignant brain tumors, characterized by poor prognosis and limited treatment options. Recent studies have identified cuproptosis, a novel copper-dependent form of regulated cell death, as a critical mechanism involved in tumor progression. However, the role of cuproptosis-related long non-coding RNAs (lncRNAs) in glioma remains not fully clarified. This study aimed to develop and validate a prognostic model based on cuproptosis-associated lncRNAs to predict patient outcomes and guide individualizing therapeutic strategies. METHODS: Transcriptomic profiles and clinical data were obtained from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), and the Chinese Glioma Genome Atlas (CGGA) databases. Cuproptosis -related prognostic lncRNAs were filtered via univariate and multivariate Cox and Least absolute shrinkage and selection operator (LASSO) regression analyses, which were selected to establish a prognostic model for glioma. Samples were divided into high- and low-risk groups, and the predictive performance of the prognostic model was evaluated based on receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) survival curves, and a nomogram. In addition, immune cell infiltration, tumor mutational burden (TMB), immunophenoscore (IPS), Tumor Immune Dysfunction and Exclusion (TIDE) and drug sensitivity were analyzed. Expression levels of selected lncRNAs and proteins were validated using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting. RESULTS: An 11-lncRNA signature associated with cuproptosis was established, and the risk score derived from this model was identified as an independent prognostic factor for glioma. The model exhibited excellent predictive ability, with area under the curve (AUC) values of 0.880, 0.913, and 0.866 for 1-, 3-, and 5-year survival, respectively. Higher TMB, immune checkpoint expression, and IPS were observed in the high-risk group and no significant difference was observed in TIDE between risk groups. Drug sensitivity analysis identified TPCA-1, KIN001-135, and ispinesib mesylate as potential therapeutic agents. Expression validation in glioma cells further supported the biological relevance of the selected lncRNAs. CONCLUSIONS: This cuproptosis-related lncRNA-based signature demonstrates strong prognostic value and may serve as a promising tool for glioma risk stratification and personalized treatment selection.

Glioma↗

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)↗