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Le, Z.

Publications and source records attributed to Le, Z..

2 recordsLinked to original sources

An Oxidative Stress-Associated Seven-Gene Prognostic Signature in Lung Adenocarcinoma: Integrative Transcriptomic Analysis Across Public Cohorts

Lung adenocarcinoma is molecularly heterogeneous, and oxidative-stress programs can support either tumor restraint or tumor adaptation depending on cellular context. This study integrated public lung adenocarcinoma transcriptomic cohorts to identify oxidative-stress-associated expression features and evaluate their prognostic relevance. Expression profiles from The Cancer Genome Atlas, Genotype-Tissue Expression project, and GEO series GSE31210, GSE40791, and GSE30219 were analyzed. Differential expression, weighted gene co-expression network analysis, functional enrichment, univariable Cox regression, and least absolute shrinkage and selection operator Cox modeling were combined to derive a risk signature. Immune-cell enrichment, gene set enrichment analysis, gene set variation analysis, and pan-cancer analyses were used for biological characterization. A total of 1,305 genes differed between tumor and control samples, including 498 upregulated and 807 downregulated genes. Intersection of differentially expressed genes, the oxidative-stress-associated co-expression module, and the oxidative-stress gene set yielded 44 genes enriched in responses to reactive oxygen species and hydrogen peroxide, antioxidant and peroxidase activities, focal adhesion, Rap1 signaling, and PI3K-Akt signaling. A seven-gene signature comprising FBLN5, HBB, FYN, HGF, TFAP2A, PLIN5, and F2RL1 stratified the 523-sample training cohort and the 207-sample internal validation cohort into groups with different overall survival. Time-dependent areas under the receiver operating characteristic curve at 1, 3, and 5 years were 0.677, 0.622, and 0.649 in training and 0.613, 0.691, and 0.706 in internal validation. In the 85-case GSE30219 external cohort, corresponding values were 0.588, 0.661, and 0.631; survival separation followed the expected direction but did not reach statistical significance (log-rank P = 0.100). Seventeen immune-cell signatures differed between risk groups, while high-risk tumors were enriched for cell-cycle, DNA-replication, mismatch-repair, glycolytic, E2F, G2M-checkpoint, MYC-target, and mTORC1-related programs. The signature therefore captures reproducible oxidative-stress-associated transcriptional variation with moderate prognostic discrimination. Its clinical utility requires prospective evaluation, complete clinical adjustment, and experimental validation.

cancer biology↗

An inflammation-associated five-gene expression signature stratifies survival and immune states in lung adenocarcinoma: an integrative public-cohort analysis

Background: Inflammation and the tumor immune microenvironment contribute to lung adenocarcinoma (LUAD) progression, but the relationship among inflammation-linked transcriptional heterogeneity, patient survival, and immune-state variation remains incompletely defined. Objective: We aimed to identify inflammation-associated LUAD subtypes, derive a parsimonious survival-stratification signature, and characterize its immune and pathway context across public transcriptomic cohorts. Methods: Expression profiles and clinical data were obtained from TCGA-LUAD, GTEx normal lung, and GEO datasets GSE11969, GSE30219, GSE31210, and GSE40791. A curated set of 596 inflammation-related genes was used for consensus clustering. Differential-expression analysis, functional enrichment, univariate Cox regression, and LASSO-Cox modeling were integrated to construct a gene-expression risk score. The prognostic dataset comprised 730 cases and was randomly divided into training (n=502) and internal-validation (n=228) sets; 85 GSE30219 cases formed an external-validation cohort. Immune-cell enrichment, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and pan-cancer analyses were used for biological contextualization. Results: The LUAD-versus-control comparison identified 1,305 differentially expressed genes, including 498 upregulated and 807 downregulated genes. Consensus clustering resolved two inflammation-associated subtypes and 67 subtype-associated genes, of which 64 were higher and 3 were lower in Cluster 1 relative to Cluster 2. Thirty-three genes overlapped between the tumor-control and subtype contrasts. LASSO-Cox regression selected CHRDL1, FDCSP, CXCL13, CYP4B1, and S100P. The 1-, 3-, and 5-year areas under the time-dependent receiver operating characteristic curve were 0.6625, 0.6581, and 0.6658 in the training set; 0.7422, 0.6537, and 0.6761 in internal validation; and 0.6560, 0.6387, and 0.6753 in external validation. Risk groups differed across multiple T-cell, B-cell, natural-killer-cell, myeloid, dendritic-cell, macrophage, and granulocyte signatures. Positive GSEA signals included cell cycle (normalized enrichment score [NES]=2.67; adjusted P=1.42 x 10-), DNA replication (NES=2.52; adjusted P=2.52 x 10-), and mismatch repair (NES=2.20; adjusted P=1.77 x 10-). Conclusions: The five-gene expression score separated LUAD survival groups and captured coordinated proliferative and immune transcriptional states. Its moderate discrimination supports further biological and clinical validation rather than immediate clinical application.

bioinformatics↗