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PubMed2026

Integrative pan-cancer analysis of transferrin reveals context-dependent prognostic associations and links to immune and metabolic disease-related programs.

BACKGROUND: Iron metabolism is closely linked to tumor biology, yet the pan-cancer significance of transferrin (TF), the major circulating iron-transport protein, remains insufficiently defined. Although TF has been implicated in cancer-related processes, its prognostic relevance, immune associations, and broader disease-related transcriptional context have not been systematically characterized across tumor types. OBJECTIVE: This study aimed to perform an integrative pan-cancer analysis of TF to characterize its expression patterns, clinical associations, immune context, pathway features, and pharmacogenomic correlations, and to explore whether TF-related signals extend to selected metabolic and chronic organ injury settings. METHODS: We used multiple public databases, including The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE), to integrate transcriptomic, proteomic, and clinical data across 33 tumor types and selected non-malignant conditions. TF expression was evaluated across normal tissues, tumors, and cell lines, followed by survival analysis, immune infiltration analysis, TMB/MSI and methylation assessment, pathway enrichment, and drug-response correlation. Independent GEO cohorts of non-alcoholic steatohepatitis (NASH), heart failure (HF), and liver cirrhosis (LC) were used for cross-disease extension. Selected findings were further explored in OA/PA-treated hepatocytes, 786-O renal carcinoma cells, and AC16 cardiomyocytes. RESULTS: TF showed pronounced tissue specificity and cancer-type-dependent dysregulation. Across pan-cancer cohorts, the most consistent adverse survival associations were observed in kidney renal clear cell carcinoma (KIRC) and stomach adenocarcinoma (STAD), where TF remained associated with overall survival (OS) in multivariable analyses. TF expression was also correlated with cancer-type-specific immune infiltration patterns and selected drug-response profiles. Across independent NASH, HF, and LC datasets, TF expression was elevated and TF-associated pathways partially overlapped with those observed in cancer. In vitro experiments provided preliminary support that TF modulation is associated with proliferative phenotypes in KIRC cells and stress- and metabolism-related phenotypes in hepatocyte and cardiomyocyte models. CONCLUSION: These findings support TF as a context-dependent biomarker candidate in cancer, with the most consistent prognostic relevance observed in KIRC and STAD. Rather than establishing a unified mechanism across diseases, this study provides an integrative framework suggesting that TF is associated with malignant behavior, immune context, and selected metabolic stress-related programs, and warrants further mechanistic investigation.

Iron metabolism↗

PubMed2026

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans↗

PubMed2026

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and clarify the underlying roles and mechanisms in FL. Bioinformatics methods, including differential analysis, WGCNA, machine learning, and Mendelian randomization, were utilized to select the LMRGs in FL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the function of the key LMRG. Receiver operator characteristic (ROC) was used to evaluate the diagnostic value of the key gene CPOX. A pan-cancer analysis investigated CPOX's expression level and immune correlations. In vitro experiments using FL cell lines (WSU-FSCCL, DOHH2) validated CPOX expression, and CPOX knockdown in DOHH2 cells was used to assess its impact on viability, migration, invasion, and fatty acid metabolism. CPOX was confirmed to be a risk factor, significantly overexpressed in FL, and exhibited effective diagnostic ability in FL (AUC = 0.731). Functional analysis linked CPOX to mitochondrial function, oxidative phosphorylation, and heme metabolic process. Pan-cancer indicated the dysregulated CPOX across multiple cancers and closely correlation with immune characteristics. Experimentally, CPOX was higher in the more invasive DOHH2 cells; and CPOX knockdown suppressed FL progression and reduced lipid droplet formation, triglyceride, total cholesterol, and free fatty acid levels. In conclusion, this study fills the gap in understanding the significance of lipid metabolism-related molecules in FL, and innovatively proposes that CPOX is a risk factor for FL. Knockdown of CPOX inhibits the FL progression, which is regulated by fatty acid metabolism.

Lymphoma, Follicular↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

IL1RAP Is Associated With an Inflammation-Immunity-Related State in Skin Cutaneous Melanoma: Integrative Evidence From Pan-Cancer Data and Melanoma Immunotherapy Cohorts.

BACKGROUND: The crosstalk between inflammation and immunity plays a central role in tumor progression, immune evasion, and therapeutic response. Interleukin-1 receptor accessory protein (IL1RAP) is a key adaptor in inflammatory signaling, yet its immunological relevance and clinical implications in skin cutaneous melanoma (SKCM) remain largely unexplored. METHODS: We performed an integrative analysis combining pan-cancer and melanoma-focused datasets. Bulk transcriptomic, single-cell, spatial transcriptomic, genomic alteration, pharmacogenomic, and clinical survival data were obtained from TCGA, GTEx, GEO, ENA, and other public resources. IL1RAP expression was evaluated across cancer types in relation to diagnostic performance, immune subtypes, survival outcomes, functional pathway activity, immune-genomic states, somatic alterations, and drug-response metrics. Melanoma-focused analyses examined immune infiltration, methylation-derived tumor-infiltrating lymphocyte (MeTIL) scores, and exploratory survival associations in five treatment cohorts; the survival groups were defined using cohort-specific optimal cutoffs rather than median splits. RESULTS: IL1RAP expression differed between tumor and normal tissues in multiple cancers, although the direction and magnitude varied by cancer type. Pan-cancer survival associations were likewise context dependent. Single-cell and spatial transcriptomic resources indicated cell-type and spatial heterogeneity of IL1RAP expression within tumor microenvironments. Pathway, immune-genomic, and pharmacogenomic analyses identified exploratory associations with functional states, genomic features, and drug-response metrics. In SKCM, IL1RAP expression was associated with several immune-infiltration estimates and higher MeTIL scores. Across five melanoma immunotherapy cohorts, the direction and magnitude of the overall survival associations varied substantially. CONCLUSIONS: This retrospective integrative analysis suggests that IL1RAP may mark an inflammation-immunity-related state in SKCM. The heterogeneous associations across cancers and melanoma treatment cohorts support further validation but do not establish IL1RAP as a causal regulator, a treatment-response predictor, or a therapeutic target.

IL1RAP↗

PubMed2026

cfMethDB: A Comprehensive cfDNA Methylation Data Resource for Cancer Biomarkers.

Cancer is a major global health threat, and early detection is crucial for improving patient outcomes. DNA methylation in circulating cell-free DNA (cfDNA) has emerged as a promising biomarker for non-invasive cancer diagnosis. However, the integration and utilization of existing cfDNA methylation data have been limited, hindering comprehensive research efforts, particularly in the discovery of cfDNA methylation biomarkers. To address this challenge, we introduced cfMethDB, a comprehensive database dedicated to cfDNA methylation in cancer that encompasses 4828 publicly available datasets. Through standardized analysis, we identified 1,048,770 differentially methylated cytosines (DMCs) as candidate biomarkers across seven cancer types. With cfMethDB, we not only identified known cfDNA methylation biomarkers, but also discovered several genes, such as ZIC4, that could be novel biomarkers. Moreover, cfMethDB offers a suite of user-friendly tools, including biomarker evaluation, pan-cancer search, and end motif analysis. We hope that cfMethDB will serve as a valuable platform for the discovery of novel cancer cfDNA methylation biomarkers and facilitate cancer research and clinical applications. cfMethDB is publicly available at https://cfmethdb.hzau.edu.cn/home.

Humans↗

PubMed2026

SDC1+ CAFs secreting CTGF drive tumour metastasis via FGFR3 signalling in cancers.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are key stromal components of the tumour microenvironment (TME) that profoundly influence tumour progression. However, CAFs exhibit pronounced phenotypic and functional heterogeneity, and whether conserved CAF subtypes with shared functional hallmarks exist across different cancer types remains unclear. OBJECTIVE: We sought to uncover universal CAF subtypes that transcend tumour origins, defining their core molecular signatures and pro-tumorigenic functions within the TME. DESIGN: We constructed a pan-cancer CAF atlas through single-cell transcriptomic analysis of 554 specimens across 14 cancer types. To validate the findings, we performed further functional analyses, including in vitro migration and invasion assays, in vivo lymphatic metastasis models and mechanistic studies focusing on candidate signalling pathways. RESULTS: We identified a conserved syndecan 1 (SDC1) + CAF subset associated with advanced tumour stage and poor outcomes. These CAFs enhanced tumour cell migration and invasion in vitro and promoted lymphatic metastasis in vivo. This effect is mediated through connective tissue growth factor (CTGF) secretion, which activates fibroblast growth factor receptor 3 (FGFR3) signalling in tumour cells to induce epithelial-mesenchymal transition (EMT). Blocking CTGF or FGFR3 signalling abrogated these effects. We also found that kruppel like factor 6 (KLF6) directly regulates CTGF in SDC1+ CAFs, establishing a complete KLF6-CTGF-FGFR3 metastatic axis. CONCLUSIONS: Our study establishes SDC1+ CAFs as a universal, metastasis-promoting CAF subset across multiple cancer types and uncovers a novel KLF6-CTGF-FGFR3 axis that drives EMT and tumour dissemination. These findings provide mechanistic insight into CAF-tumour cell crosstalk and highlight actionable stromal targets for anti-metastatic therapies across diverse malignancies.

Humans↗

PubMed2026

Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.

Subcellular spatial transcriptomics can resolve tissue architecture at cellular scale, but sparse gene panels and limited detection sensitivity constrain downstream analysis. Existing enhancement methods often require tissue-matched single-cell RNA sequencing (scRNA-seq) references and dataset-specific retraining. Here we show that stPainter, a conditional generative model pretrained on a pan-cancer scRNA-seq atlas, can enhance spatial transcriptomics data without matched references or retraining. Using a latent diffusion architecture guided by Stochastic Differential Equations (SDE), stPainter reconstructs expanded expression profiles from sparse measurements and produces latent representations for clustering and cell-state analysis. When we apply stPainter upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers downstream biological analyses, including fine-grained subpopulation clustering and pathway enrichment. Comparison with spatially resolved proteomics (CODEX) provided independent support for regional agreement between imputed cellular compositions and protein-level tissue organization. These results establish stPainter as a scalable approach for analyzing tumor microenvironments without auxiliary sequencing data.

Spatial Transcriptomics↗

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

Cross-Platform Concordance in DNA Methylation Based Classification of CNS Tumors.

DNA methylation profiling enables precise classification of pediatric central nervous system (CNS) tumors. Oxford Nanopore Technologies (ONT) offers same-day, single-sample methylation readouts, but its concordance with Illumina EPIC arrays in routine diagnostic tasks remains incompletely defined. We profiled 23 pediatric tumors (18 CNS, 5 non-CNS) by EPIC arrays and ONT. Methylation profiles from both platforms were classified with crossNN (brain model or pan-cancer model); ONT data were additionally classified with Rapid-CNS2 and Sturgeon. We compared (i) classifier agreement with integrated histology (w/o NGS) at family/class levels, (ii) pass-rate above platform-specific score cutoffs, (iii) cross-platform concordance of copy-number variation (CNV), and MGMT promoter methylation status. In CNS cases, ONT and EPIC methylation profiles demonstrated strong correlation, except for a single outlier (P2), which was excluded from further analysis. Comparative assessment of the two platforms showed that: (a) Molecular classification of CNS tumors using the crossNN classifier was consistent with histology (w/o NGS) at the family level in all cases. (b) Copy-number profiles showed high concordance between platforms. (c) MGMT promoter methylation status matched in 94% of cases (16/17). When comparing ONT-specific analysis pipelines using the ONT data, the Rapid-CNS2 pipeline yielded the most reliable class level assignments with 94% (16/17) concordance with the histopathological diagnosis, which marginally exceeded the crossNN and sturgeon classifiers. In non-CNS tumors, the pan-cancer model produced low-confidence outputs with poor agreement with histology (w/o NGS) (only 1/5 concordant), indicating limited readiness for these entities. In conclusion, ONT enables same-day, clinically reliable family-level CNS tumor classification with high concordance to arrays, while EPIC retains a modest class-level edge. A key limitation of ONT is its reliance on fresh-frozen DNA and on classifiers originally built around array-derived CpG sites, rather than on models developed natively from ONT data.

DNA methylation↗

PubMed2026

Pan-Cancer Quantification of Driver Alteration Transmission Across Molecular Layers Reveals Limited Propagation to Protein Abundance.

Precision oncology relies primarily on DNA-level alterations for therapeutic decisions, but the extent to which driver mutations propagate to protein abundance has not been systematically evaluated. Here, I developed a regression-based transmission score (TS_R 2) to quantify driver alteration signal propagation across DNA, mRNA, and protein layers. Applying this framework to matched genomic, transcriptomic, proteomic, and phosphoproteomic data from 754 Clinical Proteomic Tumor Analysis Consortium (CPTAC) tumors across seven cancer types, I analyzed 86 driver gene-cancer type pairs, of which 83 were evaluable for the full two-layer transmission score. I employed covariate-adjusted regression for each molecular transition, assessing significance via permutation testing (n = 1000). Mixed-effects modeling then partitioned gene-intrinsic from cancer-type-dependent effects. Only 5 of 83 evaluable pairs (6%) demonstrated high transmission (TS_R 2 > 0.05), with receptor tyrosine kinases (EGFR, FGFR2) exemplifying this class. The primary bottleneck occurred at the mutation-mRNA transition, not mRNA-protein translation. Gene identity accounted for 49% of transmission efficiency variance, nearly double the contribution of cancer type (29%). Copy number alterations transmitted signals 13.8-fold more efficiently than point mutations, and truncating mutations showed higher transmission than missense variants (Wilcoxon p = 0.005). Microsatellite instability attenuated mRNA-protein transmission in UCEC and COAD. These findings demonstrate that many driver alterations show limited propagation to protein abundance. This challenges DNA-only interpretations in precision oncology and provides a framework for integrated functional driver prioritization.

Humans↗

PubMed2026

Age-stratified mutation patterns in early-onset colorectal cancer reveal distinct molecular features and therapeutic implications.

BACKGROUND: Colorectal cancer (CRC) is increasingly diagnosed in younger adults, with evidence that early-onset cases (age <50 years) differ in the spectrum of prevalent gene mutations compared with older individuals. To evaluate how these age-related differences may inform testing guidelines and therapeutic development, we examined mutation rates of the most prevalent gene mutations across four age-stratified cohorts. PATIENTS AND METHODS: Clinicogenomic data were obtained from Memorial Sloan Kettering Center for Harmonized Onco-genomic Research Dataset and China Pan-Cancer cohorts available in cBioPortal. A total of 6762 samples were analyzed. Mutation frequencies for a comprehensive panel of the 100 most prevalent CRC genes were compared across four age groups: 18-29 (n = 79), 30-39 (n = 402), 40-49 (n = 1064), and ≥50 (n = 5217) using chi-square analysis. False discovery rate (FDR) correction for multiple comparisons was carried out using Benjamini-Hochberg procedure. RESULTS: Statistically significant variation in mutation frequency across age groups was seen in 22 key genes. APC mutations increased with age and were seen in 49.4% of patients in the 18-29 group, 69.7% in 30-39, 73.3% in 40-49, and 75.25% of patients ≥50 (P < 0.001, FDR < 0.001). The oldest cohort was more than three times more likely to have an APC mutation than the youngest [odds ratio (OR) = 3.74, 95% confidence interval (CI) 2.44-5.74, P < 0.001]. In contrast, SMAD4 mutations were twice as common in the youngest age group at 31.6% compared with those over 40, with a prevalence of 17.29% in patients 40-49, and 18.84% in patients over 50 (OR = 2.03, 95% CI 1.26-3.27, P < 0.001, FDR < 0.001). POLE mutations peaked in the 30-39 age group with a prevalence of 10.7% compared with 6.3% in patients aged 18-29, 4.9% in patients aged 40-49, and 5.9% in patients aged ≥50 (P < 0.001, FDR < 0.001). Individuals in the 30-39 group were nearly twice as likely to carry a POLE mutation compared with those over 40 (OR = 1.96, 95% CI 1.41-2.74, P < 0.001). CONCLUSIONS: Differences in mutations of key genes including a lower prevalence of APC mutations and increased SMAD4 mutations in younger individuals provides further supporting evidence that early-onset CRC may represent a distinct biological subtype of CRC. Enrichment of POLE mutations in younger patients highlights the importance of expanded molecular profiling in early-onset CRC, which could help identify patients most likely to benefit from immunotherapy and advance personalized treatment strategies in CRC. Together, these findings reinforce the need to approach early-onset CRC as a distinct biological entity and ensure that appropriate molecular assays are incorporated to guide care.

APC↗

PubMed2026

Multi-level Transcriptomic and Machine-learning Analyses Identify MZT1 as a Proliferation-associated Prognostic Marker in Lung Adenocarcinoma.

BACKGROUND/AIM: Lung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biomarkers that reflect core tumor biological processes. Centrosome-associated proteins regulate mitotic fidelity and genome stability, yet their roles in LUAD remain incompletely defined. In this study, we systematically characterized mitotic spindle organizing protein 1 (MOZART1; MZT1) and related family members in LUAD. MATERIALS AND METHODS: We performed integrated analyses combining bulk transcriptomic datasets, survival modeling, gene set enrichment, immune deconvolution, machine-learning based prognostic modeling, and single-cell RNA sequencing. Expression patterns and clinical associations of MZT family genes were evaluated across pan-cancer and LUAD cohorts. RESULTS: MZT family genes were consistently upregulated in tumor tissues, with MZT1 showing the most robust expression pattern. Elevated MZT1 expression was significantly associated with reduced overall survival. Functional analyses revealed coordinated activation of proliferative and genome maintenance pathways, including G2/M checkpoint regulation, E2F and MYC signaling, and DNA repair. A multivariable analysis indicated that the prognostic association of MZT1 was reduced after adjusting for canonical proliferation markers, suggesting partial overlap with established proliferation signals. The LASSO-based Cox model demonstrated stable time-dependent predictive performance at 1-, 3-, and 5-year survival. Immune analyses indicated associations between MZT1 expression and tumor microenvironmental features. Single-cell analysis showed that MZT1 expression was predominantly enriched in malignant epithelial cells and associated with proliferative cellular states. Protein-level validation supported concordance with transcriptomic findings. CONCLUSION: MZT1 is a proliferation-associated marker that integrates clinical risk, transcriptional programs, cellular heterogeneity, and predictive modeling in LUAD, providing a potential framework for biomarker development and risk stratification.

Humans↗

PubMed2026

Immune-Like Malignant Epithelial Programs Shape Tumor-Immune Interactions and Inform Prognostic Stratification in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is characterized by marked cellular heterogeneity, yet how malignant epithelial states contribute to immune regulation and clinical outcomes remains incompletely defined. We integrated single-cell RNA-sequencing data to map the cellular landscape of LUAD and identify malignant epithelial cells based on inferred copy-number alterations. Epithelial states were further examined through trajectory inference, transcription factor analysis, and cell-cell communication profiling. Single-cell-derived genes were subsequently integrated with TCGA and independent GEO cohorts to construct and validate a machine learning-based prognostic signature. Malignant epithelial cells displayed distinct functional programs, including an immune-like state associated with genomic instability, immune-related transcriptional activity, tumor-immune communication, and patient outcomes. The resulting immune-like malignant epithelial cell signature (IMEC-Sig) consistently stratified survival across multiple cohorts. Low IMEC-Sig scores were accompanied by greater immune infiltration, higher immune checkpoint expression, and increased immunophenoscore, whereas high scores were linked to a comparatively immunosuppressive phenotype. Pan-cancer analyses further identified KRT8 as a gene associated with unfavorable prognosis, and functional experiments showed that KRT8 silencing suppressed proliferation, migration, invasion, and colony formation in LUAD cells. Together, these findings connect malignant epithelial heterogeneity with the immune context and clinical outcomes, support IMEC-Sig as a biologically informed prognostic tool, and nominate KRT8 as a potential therapeutic target in LUAD.

Humans↗

PubMed2026

Prognostic significance of NLRP-3 expression in solid cancers: a systematic review and meta-analysis.

BACKGROUND: The inflammasome is a critical immunological sensor comprised of NLRP-3, ASC, and CASPASE-1. Mutations in NLRP-3 are prevalent in inflammatory diseases. However, the role of NLRP-3 in cancer is controversial. This study investigates whether NLRP-3 expression is associated with clinical outcomes in patients with solid cancers. METHODS: PubMed (MEDLINE), Embase, Cochrane, and Google Scholar were searched for articles reporting NLRP-3 expression and disease outcome data in cancer patients. RevMan Review Manager was used to calculate pooled hazard ratios and Mantel-Haenszel pooled odds ratios. RNA sequencing datasets from the TCGA Pan-Cancer (PANCAN) were used for external validation. RESULTS: Patients with higher NLRP-3 expression showed a significant association with larger tumor size, advanced tumor grade, TNM stage, and presence of metastasis. High NLRP-3 expression has a significant association with poor OS (HR:2.12, 95% CI = 1.49-3.03), p < 0.0001) and DFS (HR:1.86, 95% CI = 1.30- 2.65, p = 0.0007). Subgroup analysis showed that higher NLRP-3 expression is associated with worse OS in head and neck cancer (HR: 2.77, 95% CI = 1.88-4.09, p < 0.00001), colorectal cancers (HR:2.14, 95% CI= 1.59- 2.87, p < 0.00001), and pancreatic cancer patients (HR: 3.19, 95% CI = 1.73-5.91, p = 0.0002). CONCLUSION: High NLRP-3 expression is associated with advanced disease and poor outcomes in many solid tumours.

Humans↗

PubMed2026

Comprehensive characterization of MET exon 14 skipping mutations in non-small cell lung cancer.

BACKGROUND: MET exon 14 skipping mutation (METΔex14) is a key driver event in non-small cell lung cancer (NSCLC) and can emerge as an acquired drug resistance mechanism to MET, EGFR or ALK inhibitors. The clinical and genomic features of METΔex14 in NSCLC require further characterization. METHODS: Our study included a total of 585 patients with METΔex14 + NSCLC, comprising 556 baseline samples, 53 samples from patients exhibiting resistance to MET inhibitors, and 16 samples from patients resistant to EGFR/ALK inhibitors. Genomic data from targeted next-generation sequencing (NGS) of tissue and/or plasma samples using GeneseeqPrime™ (a 425 pan-cancer gene panel) were analyzed. RESULTS: Overall, METΔex14 exhibited a prevalence of 1.02% (n = 585) in the screened NSCLC population, with a higher incidence in patients with a sarcomatoid histology. METΔex14 was predominantly detected at the splice donor site, though the non-coding region adjacent to the splice acceptor site contributed considerably to the complexity of METΔex14. Common concurrent alterations identified at baseline included those in TP53 (40.8%), CDK4 (16%) and EGFR (12.4%). Concurrent MET amplification and cell cycle pathway mutations were both associated with worse outcomes in patients treated with crizotinib, with significant co-occurrences observed also among these concurrent genomic variations. In addition, increased chromosomal instability and intra-tumoral heterogeneity correlated with a poorer response to crizotinib. Mechanisms of acquired resistance to MET inhibitors were primarily attributed to on-target MET D1228X/Y1230X mutations or off-target alterations within genes in the RTK/RAS/MAPK and PI3K/AKT/mTOR pathways. Intriguingly, our exploratory analysis also identified the FGFR3::TACC3 fusion as a potential resistance mechanism to savolitinib. Moreover, METΔex14 was identified in 16 patients following progression on EGFR and ALK inhibitors, highlighting the need for developing tailored therapeutic strategies to overcome resistance. CONCLUSIONS: This study provides a comprehensive characterization of METΔex14 in NSCLC, revealing its dual role as a primary driver of oncogenesis and a potential resistance mechanism to EGFR/ALK inhibitors. The identification of concurrent genetic alterations and potential resistance mechanisms enhances our molecular understanding of treatment responses. These findings highlight the need for further investigation into targeted therapies that consider the genomic complexity of METΔex14 to improve treatment efficacy and patient outcomes.

Humans↗

PubMed2026

Cancer stemness-modulating (CSM) proteins in pan-cancer chemoresistance: regulatory roles and mechanisms.

Cancer stemness is a property of cancer cells that plays critical roles in tumorigenesis and therapeutic resistance. We previously identified and categorized, based on literature evidence, a group of fourteen cancer stemness-modulating (CSM) circular RNAs (circRNAs) in colorectal cancer (CRC), which we termed CSM-circRNAs. In the present work, we show that the proteins regulated by these CRC CSM-circRNAs, with one exception for which information is currently unavailable, are bona fide modulators of cancer stemness across a wide range of cancer types. We, therefore, designate these proteins as CSM-proteins. As chemoresistance is a major trait of cancer stemness, we further investigated the molecular mechanisms through which CSM-proteins contribute to chemoresistance. Our analysis reveals that twelve CRC CSM-proteins are implicated in chemoresistance across fourteen cancer types and resistance to ten therapeutic agents. Nine distinct chemoresistance mechanisms are identified and organized into five broader functional axes: survival, drug processing, genome maintenance, plasticity and adaptation, leading us to propose an integrated mechanistic framework for CSM-protein-mediated chemoresistance. Most CSM-proteins operate across multiple functional axes in different cancer contexts, with survival-associated mechanisms, particularly apoptosis evasion, and epithelial-mesenchymal transition-associated plasticity emerging as the predominant modes of chemoresistance. Furthermore, transcriptional regulatory CSM-proteins exhibit broader mechanistic profiles than other molecular categories, although the strength and extent of evidence vary across proteins and cancer types. Taken together, the proposed CSM-protein pan-cancer chemoresistance framework offers a biologically and therapeutically relevant regulatory network for understanding the mechanisms underlying cancer chemoresistance based predominantly on preclinical evidence. Our findings may provide a preclinical conceptual foundation for the development of combinatorial therapeutic strategies targeting cancer stemness and chemoresistance through the CSM-circRNA-CSM-protein regulatory axis.

Cancer stemness↗

PubMed2026

CDC20B Dysregulation: Links to Tumor Prognosis and Immunity.

OBJECTIVE: This study aimed to clarify the pan-cancer expression pattern, upstream regulatory mechanisms, prognostic relevance, and immune associations of CDC20B. METHOD: Using public databases (GTEx, GEO, and TCGA), we examined CDC20B expression and its associations with prognosis and tumor immunity across multiple cancers. Immunohistochemistry (IHC) on an independent clinical cohort was performed to validate CDC20B upregulation in tumor tissues. Promoter methylation, genetic alterations, and immune infiltration were analyzed using bioinformatics tools (cBioPortal, UALCAN, TIMER2.0, ESTIMATE). Functional enrichment was assessed by GSEA and single-cell state analysis (CancerSEA). RESULTS: CDC20B was markedly upregulated in most tumor types (p < 0.001), with strong diagnostic efficiency (AUC > 0.7 in 15 cancers) and potential regulation by promoter hypomethylation. IHC confirmed its overexpression in clinical tumor tissues. However, the prognostic impact of CDC20B was cancer-type-specific: high expression correlated with poor overall survival in UCS, LGG, KIRC, and OV, but with favorable survival in BRCA, LUAD, and PAAD. CDC20B expression was associated with immune infiltration patterns, showing negative correlations with ImmuneScore in most cancers but positive correlations with CD8+ T cells in PAAD. Functional analyses indicated involvement in EMT, KRAS/NF-κB signaling, and DNA damage response pathways. DISCUSSION: The dual prognostic role of CDC20B suggests context-dependent functions, likely influenced by tumor microenvironment composition and underlying oncogenic programs. Promoter hypomethylation emerges as a potential epigenetic driver of overexpression. The associations with immune modulation and genomic instability suggest that CDC20B is a candidate biomarker, though causal relationships require experimental validation. CONCLUSION: CDC20B may contribute to tumor progression in a context-dependent manner, with its prognostic impact varying across cancer types. Its role in tumor immunity and oncogenic pathways warrants further investigation, particularly in stratified patient populations.

CDC20B↗