Integrated single-cell and bulk RNA-seq analysis identifies a prognostic T-cell signature in colorectal cancer DOI Creative Commons
Peng Cui, Haibo Wang, Zhigang Bai

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 30, 2024

Colorectal cancer (CRC) is a major contributor to global morbidity and mortality, necessitating more effective therapeutic approaches. T cells, prominent in the tumor microenvironment, exert crucial role modulating immunotherapeutic responses clinical outcomes CRC. This study introduces pioneering method for characterizing CRC immune microenvironment using single-cell sequencing data. Unlike previous approaches, which focused on individual T-cell signature genes, we utilized overall infiltration levels of colorectal T-cells. Through weighted gene co-expression network analysis, Lasso regression, StepCox developed prognostic risk model, TRGS (T-cell related genes signatures), based six cell-related genes. Multivariate Cox analysis identified as an independent factor CRC, showcasing its superior predictive efficacy compared existing immune-related models. Immunoreactivity revealed higher Immunophenoscore lower Tumor Immune Dysfunction Exclusion scores low-risk group, indicating potential responsiveness checkpoint inhibitor therapy. Additionally, patients group demonstrated heightened sensitivity 5-fluorouracil-based chemotherapy regimens. In summary, emerges standalone biomarker offering insights optimize patient immunotherapy chemotherapy, thereby laying groundwork personalized management strategies.

Language: Английский

Do forensic genetic markers disclose more information about us than they should? (A review) DOI

Carlota Manglano de la Fuente,

Sara Palomo‐Díez

International Journal of Legal Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Language: Английский

Citations

0
A nicotinamide metabolism-related gene signature for predicting immunotherapy response and prognosis in lung adenocarcinoma patients DOI Creative Commons
Meng Wang, Li Wei, Fang Zhou

et al.

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

Citations

0
Bulk and single-cell RNA sequencing identify prognostic signatures related to FGFBP2+ NK cell in hepatocellular carcinoma DOI Creative Commons
Yinbing Wu, Huizhi Peng,

G.-X. Chen

et al.

PeerJ, Journal Year: 2025, Volume and Issue: 13, P. e19337 - e19337

Published: May 20, 2025

Background Hepatocellular carcinoma (HCC) is a highly aggressive malignancy. As specific immune cell subpopulation, FGFBP2 + NK cells play crucial part in surveillance of HCC progression. This study set out to identify prognostic signature related HCC. Methods Bulk and scRNA-seq data were derived from the public databases. The single atlas heterogeneity natural killer (NK) delineated by “Seurat” package. Pseudo-time trajectory was constructed “Monocle2” Cell-cell interactions analyzed “CellChat” Prognostic screened develop RiskScore model, prediction robustness verified. Immune infiltration immunotherapy response assessed between different risk groups. Drug sensitivity predicted “oncoPredict” expressions prognosis gene detected vitro test utilizing cells. effects key genes on proliferative, migratory invasive capacity EdU assay, wound healing Transwell assay. Results proportion samples markedly decreased than that healthy samples. further divided into three subpopulations, associated with patients. analysis revealed two differential expression clusters. exhibited extensive intercellular communication Further, eight signatures identified, including six “risk” ( UBE2F , AHSA1 PTP4A2 CDKN2D FTL RGS2 ) “protective” KLF2 GZMH ). model established good performance. In comparison low-risk group, high-risk group had poorer prognosis, lower infiltration, higher TIDE score. Moreover, 16 drugs showed significant correlation RiskScore. Additionally, downregulated while up-regulated silencing could suppress proliferation, migration invasion abilities Conclusion identified HCC, which may serve as potential therapeutic targets for

Language: Английский

Citations

0
Integrated single-cell and bulk RNA-seq analysis reveals a novel T-cell signature for prognosis and treatment response in colorectal cancer DOI Creative Commons
Peng Cui, Haibo Wang, Zhigang Bai

et al.

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

Published: April 5, 2024

Abstract Colorectal cancer (CRC) is a major contributor to global morbidity and mortality, necessitating more effective therapeutic approaches. T cells, prominent in the tumor microenvironment, exert crucial role modulating immunotherapeutic responses clinical outcomes CRC. This study introduces pioneering method for characterizing CRC immune microenvironment using single-cell sequencing data. Unlike previous approaches, which focused on individual T-cell signature genes, we utilized overall infiltration levels of colorectal T-cells. Through weighted gene co-expression network analysis (WGCNA), Lasso regression, StepCox analysis, developed prognostic risk model, TRGS, based six cell-related genes. Multivariate Cox identified TRGS as an independent factor CRC, showcasing its superior predictive efficacy compared existing immune-related models. Immunoreactivity revealed higher Immune Prognostic Score (IPS) lower Tumor Dysfunction Exclusion (TIDE) scores low-risk group, indicating potential responsiveness checkpoint inhibitor (ICI) therapy. Additionally, patients group demonstrated heightened sensitivity 5-Fu-based chemotherapy regimens. In summary, emerges standalone biomarker offering insights optimize patient immunotherapy chemotherapy, thereby laying groundwork personalized management strategies.

Language: Английский

Citations

0
Integrated single-cell and bulk RNA-seq analysis identifies a prognostic T-cell signature in colorectal cancer DOI Creative Commons
Peng Cui, Haibo Wang, Zhigang Bai

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 30, 2024

Colorectal cancer (CRC) is a major contributor to global morbidity and mortality, necessitating more effective therapeutic approaches. T cells, prominent in the tumor microenvironment, exert crucial role modulating immunotherapeutic responses clinical outcomes CRC. This study introduces pioneering method for characterizing CRC immune microenvironment using single-cell sequencing data. Unlike previous approaches, which focused on individual T-cell signature genes, we utilized overall infiltration levels of colorectal T-cells. Through weighted gene co-expression network analysis, Lasso regression, StepCox developed prognostic risk model, TRGS (T-cell related genes signatures), based six cell-related genes. Multivariate Cox analysis identified as an independent factor CRC, showcasing its superior predictive efficacy compared existing immune-related models. Immunoreactivity revealed higher Immunophenoscore lower Tumor Immune Dysfunction Exclusion scores low-risk group, indicating potential responsiveness checkpoint inhibitor therapy. Additionally, patients group demonstrated heightened sensitivity 5-fluorouracil-based chemotherapy regimens. In summary, emerges standalone biomarker offering insights optimize patient immunotherapy chemotherapy, thereby laying groundwork personalized management strategies.

Language: Английский

Citations

0