Search Results (116)

Dynamic transcriptomic remodeling of epithelial cells represents a critical hallmark of lung adenocarcinoma (LUAD) progression, yet epithelial-cell progression signatures (ECPSs) linked to this process remain incompletely characterized, impeding our understanding of malignant LUAD transformation. Here, we performed a multi-resolution multi-omics study and identified two functionally opposing ECPSs: a Cancer-Promoting Signature (CPS) and a Cancer-Suppressing Signature (CSS). The CPS was progressively upregulated from normal to early- and advanced-stage lesions, while the CSS was gradually downregulated, and both were validated by multi-resolution transcriptomic data. Both the CPS and CSS demonstrated robust diagnostic value for LUAD, particularly in early-stage detection (median AUC > 0.95). In seven independent validation cohorts, the CPS and CSS served as robust prognostic risk and protective factors, respectively. Their combination could better stratify LUAD patients into distinct prognostic subgroups, with the CPS_high–CSS_low subgroup showing the worst prognosis, accompanied by high genomic instability, an immunosuppressive tumor microenvironment, and resistance to chemotherapy. Notably, the CPS and CSS exhibited broad translational value in other epithelium-derived cancers. HMGA1, a key CPS gene, showed epithelium- and advanced-stage-specific high expression, which was significantly associated with poor prognosis, genomic instability, and immune escape. Collectively, our study identifies the CPS and CSS as clinically reliable ECPSs, providing valuable biomarkers for clinical application to LUAD. Full article

The progression and immune escape of HCC are closely regulated by endoplasmic reticulum stress (ERS). However, the associated ceRNA regulatory networks and their prognostic value remain to be systematically elucidated. Here, we sought to establish a prognostic signature derived from an ERS-associated ceRNA network and to investigate its relationship with the tumor immune microenvironment. We integrated TCGA-LIHC transcriptomic data with the MSigDB ERS gene set to identify ERS-associated differentially expressed genes and construct a ceRNA regulatory network. Using a forward search strategy with 10-fold cross-validation, we screened candidate genes to select the optimal prognostic combination and constructed a multigene Cox regression signature. External validation was performed in the independent microarray cohort GSE14520. By integrating single-cell transcriptomics, CIBERSORT, ESTIMATE, TIDE, and drug sensitivity analyses, we revealed immune microenvironment characteristics associated with this signature. Based on the ceRNA network’s eight core ERS mRNAs, an optimal three-gene signature comprising STC2, CKS1B, and PSAT1 was selected via forward search. The signature demonstrated robust prognostic discrimination in the TCGA training cohort (C-index = 0.653) and was independently corroborated in the external GSE14520 dataset (C-index = 0.584, log-rank p = 0.008). The signature was confirmed as an independent prognostic indicator by multivariable Cox regression. Functional enrichment analysis demonstrated a marked accumulation of cell-cycle-related pathways in the high-risk group, notably DNA replication and the spindle assembly checkpoint. Single-cell transcriptomic profiling showed that STC2 and CKS1B were predominantly expressed by tumor epithelial cells, whereas CCL2 and ATF3 were mainly detected in macrophages and fibroblasts. Drug sensitivity analysis indicated that the high-risk group was more sensitive to drugs such as docetaxel and AZD5582, consistent with the upregulation of proliferation pathways in this group; in the low-risk group, VE-822 exhibited selective sensitivity. This study established a three-gene prognostic signature based on the ERS-associated ceRNA network. The signature demonstrated robust prognostic stratification capabilities in cross-platform validation and revealed molecular characteristics centered on uncontrolled cell-cycle progression, as well as an immunosuppressive microenvironment, in the high-risk group, providing an exploratory tool for prognostic assessment and treatment strategy selection in hepatocellular carcinoma (HCC). Full article

Background: Lung adenocarcinoma (LUAD) develops through a stepwise pathological status from atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IA). Although malignant epithelial evolution during this process has been increasingly characterized, the dynamic remodeling of cancer-associated fibroblasts (CAFs) and their contribution to the immunosuppressive tumor microenvironment (TME) remain incompletely explored. Methods: Single-cell RNA sequencing data from treatment-naïve LUAD lesions, including AAH, AIS, MIA, and IA, were analyzed together with external bulk transcriptomic cohorts. CAF subsets were characterized according to their transcriptional features, inferred developmental states, transcription factor activity, functional programs, and predicted cell–cell interactions. Ligand–receptor analysis was used to examine MIF-related communication between epithelial cells and CAFs. MIF-related genes were then used to develop a machine learning-based prognostic signature in the TCGA-LUAD cohort, followed by validation in independent GEO cohorts. Results: Single-cell transcriptomic analysis of 131,639 cells from 25 treatment-naïve LUAD lesions identified six CAF subtypes, including alveolar CAFs, antigen-presenting CAFs, extracellular matrix CAFs, EndMT-like CAFs, inflammatory CAFs, and myofibroblastic CAFs. CAF composition differed across pathological stages, with MIA lesions showing a distinct enrichment of eCAFs and reduced proportions of inflammatory and myofibroblastic CAF populations. Compared with pre-invasive lesions, IA lesions exhibited increased proportions of exhausted CD4+ and CD8+ T cells together with reduced cytotoxic features. Cell–cell communication analysis identified enhanced epithelial–CAF interactions in IA, including enrichment of MIF-CD74/CD44 signaling. Based on MIF-related genes, a machine learning prognostic signature was developed and validated in independent cohorts, consistently stratifying patients into distinct risk groups with significantly different survival outcomes. Conclusions: These findings suggest that CAF-related stromal remodeling is associated with immune suppression during LUAD progression. MIF-mediated epithelial–CAF communication may be involved in the formation of an immunosuppressive microenvironment and is associated with poor prognosis. The MIF-related signature may provide a useful approach for prognostic stratification in LUAD. Full article

Ovarian cancer, particularly high-grade serous ovarian cancer (HGSOC), remains one of the most lethal gynecological malignancies due to late diagnosis and the development of chemoresistance. The tumor microenvironment (TME) plays an important role in disease progression, with chemokines influencing cell recruitment, angiogenesis, metastasis, and immune modification. This review synthesizes current evidence on key chemokine axes in ovarian cancer, highlighting their dual roles as prognostic biomarkers and therapeutic targets. The most important axes include CXCL12/CXCR4 (which drives tumor proliferation, angiogenesis and chemoresistance via epithelial–mesenchymal transition), CCL2/CCR2 (promoting immunosuppressive tumor-associated macrophages and resistance), and CCL5/CCR5 (enhancing pro-oncogenic signaling and Treg/MDSC infiltration). Pro-angiogenic ELR+CXC chemokines like CXCL8 induce vascularization and inflammation. On the contrary, effector chemokines (CXCL9/10/11/13) correlate with “hot” immune subtypes and improved survival in several studies. High expression of immunosuppressive chemokines predicts poorer prognosis and therapy resistance, while immune-attracting profiles associate with better outcomes and chemotherapy responsiveness. Therapeutically, inhibitors like plerixafor (CXCR4), PF-04136309 (CCR2), and maraviroc (CCR5) show preclinical promise, synergizing with chemotherapy, anti-VEGF, and checkpoint inhibitors. Chemokines also represent actionable molecular targets to overcome ovarian cancer’s “cold” immune phenotype. Future research should validate multi-chemokine signatures for patient stratification and advanced clinical trials toward personalized therapies. Full article

Persistent high-risk human papillomavirus infection is a critical prerequisite for cervical intraepithelial neoplasia and cervical cancer, yet viral factors alone do not fully explain why most infections clear while a subset persists and progresses. Emerging longitudinal, multi-omics, and mechanistic evidence supports a plausible model in which the cervicovaginal microbiota is not a passive bystander but a functional determinant of mucosal immunity, epithelial barrier integrity, and local metabolic tone. Lactobacillus-dominant community states, particularly those enriched in Lactobacillus crispatus, are generally associated with lower pH, regulated inflammatory signaling, stronger barrier function, and a higher likelihood of HPV clearance. In contrast, anaerobe-enriched dysbiosis is linked to elevated pro-inflammatory cytokines, altered antigen presentation, immune checkpoint signatures consistent with T-cell dysfunction, and metabolic shifts involving lactate depletion and accumulation of short-chain fatty acids and other metabolites that can influence epithelial and immune-cell programs. Importantly, the interaction is bidirectional: hrHPV can remodel the microenvironment by suppressing host defense peptides and perturbing mucosal barriers, thereby reducing Lactobacillus fitness and reinforcing dysbiosis in a feed-forward loop that favors persistence and oncogenic progression. This review integrates functional ecology, longitudinal clinical evidence, immunological and metabolic mechanisms, and translational implications, highlighting opportunities for microbiome-informed risk stratification and adjunctive interventions, as well as key gaps requiring standardized longitudinal multi-omics and rigorously designed clinical trials. Full article

Background: Brain metastasis is associated with poor prognosis in lung adenocarcinoma (LUAD). Anoikis resistance may contribute to tumor cell survival during metastatic dissemination and brain colonization; however, robust biomarkers for prognostic stratification and brain metastasis-associated classification remain limited. This study aimed to investigate anoikis-related molecular features in LUAD brain metastasis and develop a machine learning-based signature for prognostic assessment and exploratory classification of primary and brain-metastatic LUAD samples. Methods: We integrated single-cell and multi-cohort bulk transcriptomic data. Single-cell analysis was performed to characterize anoikis-related cellular states and intercellular communication in primary and brain-metastatic LUAD samples. In the bulk transcriptomic analysis, TCGA-LUAD was used for prognostic feature selection and risk-model construction, and GSE26939 was used for external prognostic validation. The classification performance of the fixed signature for distinguishing primary LUAD from brain-metastatic LUAD samples was further evaluated in GSE161116 and GSE271259. Immune microenvironment features were assessed, and an LLM-assisted exploratory drug-screening strategy combined with molecular docking was used to prioritize candidate compounds. Results: Single-cell analysis suggested that metastatic epithelial cells exhibited enhanced anoikis-related activity, accompanied by macrophage-associated SPP1-CD44 and MIF-(CD74+CXCR4) communication patterns. Machine learning-based feature selection identified an eight-gene signature consisting of BIRC3, CCL20, CLEC7A, CTSL, GOLM1, ICAM3, MTUS1, and SERPINH1. The signature showed prognostic value in TCGA-LUAD and GSE26939 and demonstrated exploratory classification performance in distinguishing primary LUAD from brain-metastatic LUAD samples. High-risk patients exhibited immune microenvironment alterations and enrichment of tumor progression-related pathways. LLM-assisted compound prioritization and molecular docking highlighted resveratrol and SB431542 as hypothesis-generating candidates with predicted interactions with core targets. Conclusions: This study identified an anoikis-related eight-gene signature for LUAD prognostic stratification and exploratory brain metastasis-associated classification. The findings suggest the potential involvement of anoikis-related tumor–microenvironment interactions in LUAD brain metastasis and provide candidate genes and compounds for further experimental validation. Full article

Gastric adenocarcinoma (STAD) exhibits extensive intratumoral heterogeneity that contributes to tumor progression and therapeutic resistance. In this study, we integrated single-cell RNA sequencing and bulk transcriptomic analyses to characterize malignant epithelial subtypes in STAD. Among seven identified tumor subtypes, the OLFM4-associated C3 subtype exhibited enriched palmitoylation-related signatures and altered metabolic activities, particularly glycolysis-related pathways. Functional enrichment analyses further supported the enrichment of multiple energy metabolism pathways. To evaluate the association between OLFM4 and metabolic regulation, recombinant OLFM4 treatment and siRNA-mediated OLFM4 knockdown were performed in gastric cancer cell lines. OLFM4 upregulation increased the expression of ZDHHC2 and GLUT1, accompanied by enhanced glucose uptake and elevated ATP production, whereas OLFM4 silencing reduced ZDHHC2 and GLUT1 expression. In addition, a prognostic risk model derived from C3 subtype-associated genes (MUC16, RALA, and PCBD1) effectively stratified STAD patients and was associated with immune checkpoint expression and immune infiltration. Collectively, our findings identify an OLFM4-associated gastric cancer cell state with palmitoylation-related signatures and altered metabolic activities, highlighting its potential relevance to metabolic heterogeneity in gastric adenocarcinoma. Full article

Background/Objectives: The tumour immune microenvironment (TIME) critically influences colorectal cancer (CRC) progression and therapeutic response, yet mechanisms shaping immune phenotypes remain unclear. Mucin-type O-glycosylation regulates tumour–immune interactions at the cell surface. Methods: We analysed O-glycosylation activity in 988 colorectal cancer (CRC) tumours derived from three independent cohorts: The Cancer Genome Atlas (TCGA-CRC, n = 534), the Clinical Proteomic Tumour Analysis Consortium (CPTAC2-CRC, n = 106), and the Sidra–Leiden University Medical Center (Sidra-LUMC, n = 348). O-glycosylation activity was quantified using a transcriptomic gene signature and single-sample gene set enrichment analysis (ssGSEA). Tumours were stratified into high and low O-glycosylation groups based on the median score, and associations with immune phenotypes, genomic alterations, and tumour functional states were assessed. Results: High O-glycosylation tumours exhibited an immune-desert phenotype with reduced immune-inflamed (p = 3.65 × 10⁻¹⁰) and immune-excluded (p = 0.0070) signatures alongside increased immune-desert scores (p = 0.0049) and reduced Siglec signalling (p = 8.14 × 10⁻⁵). O-glycosylation was associated with genomic stability, including lower TP53 mutation frequency (p = 0.0056), reduced aneuploidy (p = 0.0116), and decreased fraction of genome altered (p = 0.0309). High O-glycosylation tumours also showed upregulation of multidrug resistance programmes and reduced epithelial–mesenchymal transition (p = 0.0141) and proliferation (p = 0.0294). Conclusions: O-glycosylation defines a CRC subtype characterised by immune exclusion, genomic stability, and multidrug resistance, highlighting its potential as a biomarker and therapeutic target. Full article

Background: Colorectal cancer (CRC) progression is associated with tumor metabolic reprogramming and an immunosuppressive tumor microenvironment, yet coordinated metabolic interactions between malignant epithelial and immune cells remain unclear. This study aimed to characterize metabolic crosstalk in CRC, validate spatial organization, and develop a metabolism-based prognostic model. Methods: Six CRC single-cell RNA sequencing datasets were integrated to identify cell populations, evaluate metabolic pathway activity, and infer cell–cell communication. Spatial transcriptomics was used to assess regional co-enrichment of key cell-subset signatures and metabolic activities. Bulk transcriptomic cohorts and targeted metabolomics data were analyzed for pathway-level support. Patients were stratified using metabolic features of selected subsets, followed by protein–protein interaction analysis and elastic net modeling. Results: Across six scRNA-seq datasets comprising 431,217 cells from 173 samples (107 tumor, 60 normal, and 6 border), we identified a metabolically reprogrammed malignant epithelial subset (SLC6A20+ epithelial cells) and an immunosuppressive SPP1+ tumor-associated macrophage (TAM) subset. Both exhibited elevated glycolysis, vitamin B6 metabolism, and aromatic amino acid metabolism. Spatial transcriptomics supported regional co-enrichment of their signatures and shared metabolic activities within the same tumor regions. Independent bulk transcriptomic cohorts and targeted metabolomics further supported these pathway alterations. Cell–cell communication analysis revealed extensive bidirectional ligand-receptor interactions. Based on metabolic features of these subsets, patients were stratified into two prognostic groups. A 14-gene elastic net signature predicted the high-risk subtype with consistent performance across independent cohorts. Conclusions: SLC6A20+ epithelial cells and SPP1+ TAMs showed coordinated, transcriptome-inferred metabolic programs and predicted bidirectional communication in CRC. These features provide candidate biologically interpretable biomarkers and a metabolism-based prognostic model for patient stratification. Full article

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cancer, characterized by frequent metastasis and poor prognosis. Epithelial–mesenchymal transition (EMT) plays a pivotal role in tumor progression. Protocadherin 9 (PCDH9) has emerged as a potential tumor suppressor, but its relationship with EMT markers in ccRCC remains unclear. This study aimed to investigate the expression patterns and prognostic significance of PCDH9, β-catenin (CTNNB1), Snail (SNAI1), and Vimentin (VIM) in ccRCC. Methods: Immunofluorescence analysis was performed on formalin-fixed paraffin-embedded tissue sections from 48 ccRCC patients (31 low-grade, 17 high-grade) and adjacent normal renal cortex. Findings were validated using The Cancer Genome Atlas (TCGA-KIRC) dataset via GEPIA2/GEPIA3 platforms, including differential expression, correlation, and survival analyses. Results:PCDH9 mRNA was significantly downregulated in ccRCC tumors (TCGA-KIRC), while VIM was upregulated at the transcriptomic level. Tissue-level immunofluorescence quantification revealed discordant patterns, highlighting the influence of cellular heterogeneity on bulk protein assessment. The strong positive correlation between PCDH9 and CDH1 observed in normal kidney was completely lost in tumor tissue. Unexpectedly, PCDH9 showed positive correlations with EMT transcription factors (ZEB1, SNAI1) in tumors. In univariate survival analysis, high PCDH9 and CTNNB1 expression were associated with improved overall survival. Multivariate Cox regression revealed endpoint-specific prognostic signatures: VIM independently predicted disease progression, while SNAI1 predicted overall mortality. CTNNB1 was consistently protective across both endpoints. Conclusions: Our findings support a tumor-suppressive role for PCDH9 in ccRCC and reveal disruption of epithelial adhesion molecule co-regulation during tumorigenesis. The identification of endpoint-specific prognostic signatures has implications for patient stratification and suggests that ccRCC exhibits a partial EMT phenotype rather than classical EMT. Full article

The phenotypic plasticity of epithelial cells along the epithelial–mesenchymal (E-M) axis, or epithelial–mesenchymal transition (EMT), is a critical aspect of tumour progression and therapeutic resistance. During EMT, epithelial cells gradually acquire mesenchymal traits, facilitating vital functions in embryogenesis, wound healing, fibrosis, and tumour metastasis. This review article investigates the potential interplay between hyperglycaemia-induced metabolic stress and EMT in the context of therapeutic resistance. The study examines a complex, multifaceted network of molecular mechanisms regulating EMT, including specialised transcription factors and signalling pathways as well as growth factors, integrins, and matrix metalloproteinases in various epithelial carcinomas. Emerging findings have demonstrated the existence of EMT hybrid states along the continuum, possessing heightened metastatic potential and distinctive metabolic signatures that play critical roles in the development of therapeutic resistance in cancer cells. Hyperglycaemia has been particularly highlighted for its potential to promote EMT-driven therapeutic resistance through various interconnected mechanisms. Elevated glucose levels induce the increased production of reactive oxygen species (ROS), activation of EMT-promoting transcription factors, and a metabolic shift towards glycolysis. This hyperglycaemic stress involves upregulation of glucose transporters and glycolytic enzymes, creating feed-forward loops that support drug efflux mechanisms and help maintain the mesenchymal phenotype. Clinical data also indicate that hyperglycaemia in OSCC patients is associated with more advanced tumour stages, more extended hospital stays, less effective treatments, and higher rates of local recurrence and distant metastasis. Overall, these insights reveal a deleterious feed-forward loop in which hyperglycaemia promotes EMT-driven therapeutic resistance, with the strongest clinical evidence in oral squamous cell carcinoma (OSCC) and supportive data from pancreatic and breast cancers. Although glycaemic control represents a promising low-risk adjunctive approach, its clinical benefit remains to be validated in prospective interventional studies. Full article

Background/Objectives: Oral squamous cell carcinoma (OSCC) commonly arises from oral potentially malignant disorders (OPMDs), yet reliable molecular biomarkers that predict malignant transformation remain scarce. Because epithelial carcinogenesis follows similar multistep trajectories across multiple organs, pan-cancer transcriptional analyses may reveal conserved pathways relevant to early oral tumorigenesis. This study aimed to identify shared transcriptional signatures across carcinomas and evaluate their applicability to precancerous-to-carcinoma progression. Methods: Bulk RNA-seq data from five carcinomas (lung, colon, breast, prostate, and head and neck squamous cell carcinoma, HNSCC) were obtained from TCGA to identify shared differentially expressed genes (DEGs) (|log₂FC| ≥ 2; FDR < 0.05). Functional enrichment, clustering, and gene–pathway network analyses characterized conserved biological processes. Independent GEO datasets containing premalignant and malignant samples, including OPMD and OSCC cohorts, were examined to assess early-stage relevance. Results: A conserved 45-gene signature was identified, enriched for transcriptional regulation, chromatin organization, and RNA polymerase II-mediated processes. Regulatory hubs, including ZIC5, MYBL2, ONECUT2, POU4F1, and PDX1, and strong upregulation of cancer-testis antigens (MAGEA3, MAGEA6, MAGEC2) were notable. Integration with premalignant datasets revealed 13 genes consistently dysregulated across early lesions, involving pathways such as cell differentiation, apoptosis, and lipid transport. Several genes remained altered from normal tissue through OPMD to OSCC, supporting their potential as stable biomarkers. Conclusions: This study identifies conserved transcriptional programs shared across epithelial cancers and detectable in OPMDs. These findings highlight promising biomarker and regulatory candidates for improving early detection and risk stratification of oral precancer, addressing a critical unmet need in OSCC prevention and clinical management. Full article

Undifferentiated sarcomas (USs), including undifferentiated pleomorphic sarcoma (UPS), are aggressive mesenchymal malignancies with limited molecular biomarkers for prognostic assessment and therapeutic stratification. Expression-based markers may provide insight into tumor aggressiveness and clinical outcomes. Here, we performed integrative transcriptomic and spatial analyses to identify differentially expressed genes (DEGs). By comparing normal tissues with sarcoma tumors and sarcoma tumors with cell lines. Intersection and clustering analyses were conducted to define shared expression programs, which revealed a subset of DEGs enriched in epithelial-mesenchymal transition (EMT)-related pathways. CosMx spatial transcriptomics was applied to xenograft tumors derived from two UPS cell lines to resolve tumor-intrinsic signatures. The National Cancer Center Cohort samples were used for validation, and immunohistochemistry confirmed the expression in thirty US tissues. Spatial transcriptomic profiling identified mesenchymal tissue–driven gene expression programs in UPS xenografts. Across bulk RNA-seq and spatial data, epithelial membrane protein 3 (EMP3) consistently emerged as highly expressed in US tissues and cell lines. EMP3 is a robust mesenchymal-associated biomarker linked to EMT, tumor progression, and clinical outcomes in USs, supporting its potential utility as a prognostic indicator and therapeutic target. Full article

Background: The optimal timing of adjuvant chemotherapy after cytoreductive surgery in epithelial ovarian cancer remains uncertain, and perioperative wound-healing responses may transiently create a pro-tumorigenic and drug-resistant microenvironment. This study aimed to characterize time-dependent wound-induced transcriptomic alterations and to identify pharmacologic agents capable of reversing these responses. Methods: An ID8 murine ovarian cancer model was used to compare no treatment, anesthesia alone, and anesthesia plus surgical wounding mimicking futile laparotomy. Tumors were collected at baseline, 1 day (T1), 1 week (T2), and 2 weeks (T3) after intervention. RNA sequencing was performed, and wound-specific differentially expressed genes (WsDEGs) were defined by excluding anesthesia- and progression-related signatures. Functional enrichment analyses were conducted, followed by transcriptome-based drug repurposing using the REMEDY platform to identify compounds predicted to reverse wound-induced gene expression profiles. Results: Surgical wounding significantly increased tumor burden at T1. Transcriptomic analyses revealed distinct, time-dependent wound-associated programs. At T1, WsDEGs were enriched in inflammatory signaling, coagulation, angiogenesis, and immune cell migration, with Vorinostat and Homoharringtonine identified as top candidates to counteract these signatures. At T2, pathways related to cell survival, adhesion, and morphogenesis predominated, with LY-2090314, Artesunate, and Birinapant emerging as potential modulators. At T3, cell-cycle regulation and lipid metabolic pathways were dominant, and Fulvestrant, Atorvastatin, Imatinib, and ABT-737 were predicted to inhibit these processes. Conclusions: Perioperative surgical wounding induces dynamic, stage-specific transcriptomic programs that may promote ovarian cancer progression and alter drug responsiveness. These findings support time-adapted perioperative pharmacologic strategies to optimize postoperative cancer therapy. Full article

Cytokines are central regulators of inflammation and immune responses within the tumor microenvironment and have been implicated in cancer progression and prognosis. However, the prognostic value of coordinated cytokine-related transcriptional programs across cancer types has not been systematically explored. Pan-cancer transcriptomic and clinical data were analyzed to construct a cytokine-related prognostic signature using least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were stratified into high-risk and low-risk groups based on the derived risk score. Prognostic performance was evaluated in training and test cohorts, and biological relevance was assessed through survival analyses and pathway-level investigations. A 16-gene cytokine-related signature was established that consistently stratified patients into distinct prognostic groups across multiple cancer types. High cytokine-related risk scores were significantly associated with unfavorable survival outcomes and were linked to enhanced cell cycle activity, epithelial-mesenchymal transition, and extracellular matrix remodeling. Integration of the risk score with clinical variables improved individualized survival prediction. Immunohistochemical analyses further confirmed increased protein expression of representative risk-associated genes, including pannexin 1 (PANX1) and FERM domain containing 8 (FRMD8), in multiple tumor tissues compared with corresponding normal tissues. The cytokine-related prognostic signature captures key inflammatory and immune-related programs underlying tumor aggressiveness and provides a robust tool for pan-cancer risk stratification with potential clinical utility. Full article