Identifying ADME-related gene signature for immune landscape and prognosis in KIRC by single-cell and spatial transcriptome analysis

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 8, 2025

Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of kidney cancer. Although multiple therapeutic agents have been proven effective in KIRC, their clinical application has hindered by a lack reliable biomarkers. This study focused on prognostic value and function drug absorption, distribution, metabolism, excretion- (ADME-) related genes (ARGs) KIRC to enhance personalized therapy. The critical role ARGs microenvironment was confirmed single RNA-seq analysis spatial transcriptome sequencing for first time. Then, an ADME-related signature (ARPS) developed bulk analysis. ARPS, created through Cox regression, LASSO, stepAIC analyses, identified eight that stratified patients into high-risk low-risk groups. High-risk had significantly poorer overall survival. Multivariate independent predictive ability ARPS-based nomogram constructed application. Gene ontology KEGG pathway analyses revealed immune-related functions pathways enriched these groups, with showing better responses immunotherapy. Finally, expression validated qRT-PCR Western blotting experiments. These findings underscore significance ARPS its potential guiding treatment strategies.

Language: Английский

---

A novel identified epithelial ligand-receptor-associated gene signature highlights POPDC3 as a potential therapy target for non-small cell lung cancer

Cell Death and Disease, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 19, 2025

Abstract The tumor microenvironment (TME) is pivotal in non-small cell lung cancer (NSCLC) progression, influencing drug resistance and immune behavior through complex ligand-receptor (LR) interactions. This study developed an epithelial LR-related prognostic risk score (LRrisk) to identify biomarkers targets NSCLC. We identified twenty LRs with significant implications delineated three molecular NSCLC subtypes distinct outcomes, pathological characteristics, biological pathways, profiles. LRrisk model was constructed using twelve differentially expressed interaction-related genes (LRGs), a focus on POPDC3 (popeye domain-containing protein 3), which overexpressed cells. Functional assays revealed that knockdown reduced proliferation, migration, invasion, epithelial-mesenchymal transition (EMT), while its overexpression promoted cancerous activities. In vivo, silencing hindered, accelerated the growth of xenografts nude mice. Additionally, high expression levels tissues were associated enhanced CD4 + T infiltration increased PD-1 within TME. Moreover, ectopic C57BL/6 J mouse Lewis carcinoma (LLC) research establishes robust signature, highlighting as critical facilitator progression potential therapeutic target.

Language: Английский

---

A nicotinamide metabolism-related gene signature for predicting immunotherapy response and prognosis in lung adenocarcinoma patients

PeerJ, Journal Year: 2025, Volume and Issue: 13, P. e18991 - e18991

Published: Feb. 27, 2025

Background Nicotinamide (NAM) metabolism fulfills crucial functions in tumor progression. The present study aims to establish a NAM metabolism-correlated gene (NMRG) signature assess the immunotherapy response and prognosis of lung adenocarcinoma (LUAD). Methods training set validation (the GSE31210 dataset) were collected Cancer Genome Atlas (TCGA) Gene Expression Omnibus (GEO), respectively. Molecular subtypes LUAD classified by consensus clustering. Mutation landscape top 20 somatic genes was visualized maftools package. Subsequently, differential expression analysis conducted using limma package, univariate, multivariate LASSO regression analyses performed on screened construct risk model for LUAD. Next, MCP-counter, TIMER ESTIMATE algorithms utilized comprehensively immune microenvironmental profile patients different groups. efficacy chemotherapy drugs evaluated TIDE score pRRophetic A nomogram created integrating RiskScore clinical features. mRNA expressions independent prognostic NMRGs migration invasion cells measured carrying out cellular assays. Results Two (C1 C2) classified, with C1 subtype showing worse than C2. three high mutation frequency C2 TTN (45.25%), FLG (25.25%), ZNF536 (19.8%). Four ( GJB3 , CPA3 DKK1 KRT6A ) used model, which exhibited strong predictive performance. High-risk group showed low cell infiltration, score, prognosis, this drug sensitivity Cisplatin, Erlotinib, Paclitaxel, Saracatini, CGP_082996. established an accurate diagnostic all high- expressed cells, silencing inhibited cells. Conclusion novel NMRG developed, contributing evaluation personalized treatment patients.

Language: Английский

---

Prognostic value of disulfidptosis-associated genes in gastric cancer: a comprehensive analysis

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 4, 2025

Objective Disulfidptosis is a newly identified type of nonapoptotic programmed cell death related to mechanisms such as ferroptosis, cuproptosis, pyroptosis, and necrotic apoptosis. This study explores the role disulfidptosis-related long non-coding RNAs (DRLs) in gastric cancer their potential prognostic biomarkers. Method We developed model using DRL scores classify patients based on disulfidptosis activity. evaluated these for correlations with drug sensitivity, tumor microenvironment (TME) features, mutational burden (TMB), prognosis. Potential signaling pathways were screened, identifying FRMD6-AS promising therapeutic target. expression was further validated real-time fluorescent quantitative PCR (qRT-PCR). Results The DRL-based model, established through univariate multivariate Cox regression LASSO analyses, outperformed traditional models predicting divided samples into high-risk low-risk groups scores, finding that group had significantly higher survival rate (P < 0.05). A high-precision prediction incorporating age, sex, grade, stage showed strong predictive value consistency actual outcomes. High correlated TME lower TMB. Key axes AC129507.1/(FLNA, TLN1)/FOCAL ADHESION AC107021.2/MYH10/(TIGHT JUNCTION, VIRAL MYOCARDITIS, REGULATION OF ACTIN CYTOSKELETON). Potentially effective drugs, including BMS-754807, dabrafenib, JQ1, identified. emerged target treatment. Conclusions novel DRLs, two key JQ1 may be an treatment, could

Language: Английский

---

Integrative Analysis of scRNA-Seq and Bulk RNA-Seq Identifies Plasma Cell Related Genes and Constructs a Prognostic Model for Hepatocellular Carcinoma

Journal of Hepatocellular Carcinoma, Journal Year: 2025, Volume and Issue: Volume 12, P. 427 - 444

Published: Feb. 1, 2025

The complexity and heterogeneity of the tumor immune microenvironment (TIME) are linked to development poor prognosis hepatocellular carcinoma (HCC). However, cell type within TIME that is most closely associated with HCC remains unclear. Herein, we aimed identify clusters significantly contribute their underlying mechanisms. Using single-cell RNA sequencing (scRNA-seq), analyzed changes in normal tissues, identifying plasma cells as key cluster development. Based on cell-related genes (PCRGs), constructed validated an eight-gene prognostic model (ST6GALNAC4, SEC61A1, SSR3, RPN2, PRDX4, TRAM1, SPCS2, CD79A) using internal external datasets a nomogram. Functional enrichment, miRNA network construction, transcriptional regulation analyses were performed explore TIDE scores GDSC database used predict immunotherapy chemotherapy sensitivity different risk groups. Finally, SSR3's biological function was vitro lines. Plasma A based PCRGs can accurately patients guide clinical treatment.

Language: Английский

---

A patient stratification signature mirrors the immunogenic potential of high grade serous ovarian cancers

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Nov. 20, 2024

Abstract Background While high-grade serous ovarian cancer (HGSC) has proven largely resistant to immunotherapy, sporadic incidents of partial and complete response have been observed in clinical trials case reports. These observations suggest that a molecular basis for effective immunity may exist within subpopulation HGSC. Herein, we developed an algorithm, CONSTRU (Computing Prognostic Marker Dependencies by Successive Testing Gene-Stratified Subgroups), facilitate the discovery characterization backgrounds HGSC confer resistance or susceptibility protective anti-tumor immunity. Methods We used identify genes from tumor expression profiles influence prognostic power established immune cytolytic activity signature (CYTscore). From identified genes, stratification (STRATsig) partitioned patient populations into tertiles varied markedly CYTscore power. The tertile groups were then analyzed distinguishing biological, immunological properties using integrative bioinformatics approaches. Results Patient survival measures suppression, evasion dysfunction significantly across STRATsig validation cohorts. Tumors comprising 1 (S-T1) showed no immune-survival benefit displayed hyper-immune suppressed state marked activation TGF-β, Wnt/β-catenin adenosine-mediated immunosuppressive pathways, with concurrent T cell dysfunction, reduced potential antigen presentation, enrichment cancer-associated fibroblasts. By contrast, S-T3 tumors exhibited diminished signaling, heightened presentation machinery, lowered significant CYTscore-survival correlated mutational burden manner consistent immunoediting. also elevated DNA damage/repair, cycle/proliferation oxidative phosphorylation, greater proportions Th1 CD4 + cells. In these patients, but not those S-T1 S-T2, validated predictors immunotherapy longer survival. Further analyses explained known subtypes singular mechanisms. Conclusions is composite parallel immunoregulatory pathways mirrors immunogenic potential. Approximately one-third cases classify as display hypo-immunosuppressed antigenic composition favors immunologic control. patients show responsiveness current immunotherapies.

Language: Английский

---

A Novel Liquid–Liquid Phase Separation Characteristic Model Associated with Prognosis and Immune Landscape of Gastric Cancer Patients

Published: July 15, 2024

Background Liquid-liquid phase separation (LLPS) refers to a phenomenon in which unique liquid condensates are formed due weak interactions among biomolecules, including proteins and nucleic acids. In cellular environments, abnormal LLPS can induce aggregation of membrane-less organelles, disrupt intracellular signaling, alter chromatin structures, cause aberrant gene expression. The significance gastric cancer (GC) cells is still poorly understood. This study aims integrate multiple omics analysis machine learning algorithms identify characteristic genes (LCGs) be used develop prognostic model. Methods Transcriptomic single-cell data for GC patients were retrieved from the GEO TCGA databases. set was extracted PhaSepDB database. Initial localization set-expressing performed using GSE167297. Subsequently, we analyzed 797 samples TCGA-STAD GSE84437 merged cohort ConsensusClusterPlus method, then subdivided into two clusters based on expression further immune analyses. Characteristic identified by best combination four correlating with patient survival status time, validated across three independent cohorts. differential LCGs model HPA UALCAN databases, as well western blotting. Additionally, nomogram developed improve effectiveness clinical application. Furthermore, differences tumor microenvironment (TME), immunotherapy response, drug sensitivity between different risk groups studied through variety algorithms. Mutational ten conducted mutation cohort. Results A established, identifying high predictive value prognosis, TME, responses, chemotherapy patients. specific developed, incorporating features enhance score, AUC values 0.722, 0.715, 0.707 at 1, 3, 5 years, respectively. demonstrated good age groups, T stages, N stages Risk scores calculated showed linear correlations stromal scores, TME Tumor Immune Dysfunction Exclusion (TIDE) epithelial-mesenchymal transition (EMT) angiogenesis purity scores. mutations found impact Conclusions provides new perspective assessing prognosis patients, their responses immunotherapy, usage.

Language: Английский

---

Identification of a distinctive immunogenomic gene signature in stage-matched colorectal cancer

Journal of Cancer Research and Clinical Oncology, Journal Year: 2024, Volume and Issue: 151(1)

Published: Dec. 14, 2024

Colorectal cancer (CRC) remains one of the leading causes cancer-related mortality worldwide. Despite advances in diagnosis and treatment, including surgery, chemotherapy, immunotherapy, accurate clinical markers are still lacking. The development prognostic predictive indicators, particularly context personalized medicine, could significantly improve CRC patient management. In this retrospective study, we used FFPE blocks tissue samples from patients at Augusta University (AU) to quantify a custom 15-gene panel. To differentiate tumor adjacent normal regions (NAT), H&E staining was utilized. For quantification transcripts, NanoString nCounter platform. Kaplan–Meier Log-rank tests were perform survival analyses. Several independent datasets explored validate gene signature. Orthogonal analyses included single-cell profiling, differential expression, immune cell deconvolution, neoantigen prediction, biological pathway assessment. A 3-gene signature (GTF3A, PKM, VEGFA) found be associated with overall AU cohort (HR = 2.26, 95% CI 1.05–4.84, p 0.02, 93 patients), TCGA 1.57, 1.05–2.35, < 435 patients) four other GEO datasets. Independent analysis identified relatively higher expression region. Differential revealed dysregulated inflammation, dysfunction, load cycle processes among high-risk compared low-risk patients. We developed potential for assessment This gene-based stratification offers cost-effective approach Further research using similar methods identify therapy-specific signatures strengthen medicine

Language: Английский

---

UNC5B Knockdown Enhances Chemotherapy Sensitivity and Immunogenic Cell Death in Sarcoma: A Comprehensive Prognostic Analysis based on PANoptosis and Macrophage

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 3, 2024

Purpose Sarcomas represent a heterogeneous collection of malignancies originating from mesodermal tissues, posing significant challenges in diagnosis and treatment. Emerging research has spotlighted PANoptosis—a synergistic process pyroptosis, apoptosis, necroptosis—as novel therapeutic target. This study seeks to construct prognostic model leveraging PANoptosis macrophage-related genes advance the understanding treatment sarcoma. Methods Utilizing data TCGA-SARC, TARGET-OS cohorts, GSE159847, we identified associated with macrophages PANoptosis. A was formulated through multivariate LASSO regression analyses, its efficacy evaluated via Kaplan-Meier survival analysis, ROC curves, validation an independent cohort. Comprehensive analyses included functional enrichment, immune microenvironment assessment, drug response prediction. Additionally, assays were performed on 143B cells elucidate pivotal gene’s roles. Results The model, incorporating four (CD2, STAT6, TXNIP, UNC5B), effectively categorized samples into high low risk cohorts notable disparities. Samples high-risk group exhibited greater genomic instability immunosuppressive microenvironments. Functional revealed that knockdown UNC5B reduced cell proliferation increased sensitivity paclitaxel, indicating potential targets. Conclusion highlights critical role macrophage polarization sarcoma microenvironment. devised provides reliable instrument for predicting patient outcomes tailoring personalized strategies, thereby offering innovative pathways management.

Language: Английский

---