Dataset Information

Transcriptomic Profiling for Prognostic Biomarkers in Early-stage Squamous Cell Lung Cancer (SqCLC)

ABSTRACT: Squamous cell lung cancer (LUSC) is a frequently diagnosed histological subtype of lung malignancy associated with high mortality due to limited number of treatment options. Identification of potential targets suitable for drug development using high-throughput methods is still lacking. Therefore, the purpose of this research is to analyze expression profiles of mRNA and miRNA in LUSC, aiming to identify the key molecules associated with tumorigenesis and prognosis (overall survival; OS). We performed differential gene expression analysis, pathway enrichment analysis and gene ontology analysis on RNA-seq data obtained from 23 FFPE tumor samples and 3 FFPE healthy individuals. TCGA LUSC and GTEx healthy donors’ cohorts were used for validation. We identified 1133 up-regulated and 644 down-regulated genes, common for both cohorts. The most significant up-regulated genes were involved in cell-cycle regulation pathways, while down-regulated genes predominately belonged to immune-related pathways. Survival analysis performed on selected genes, commonly dysregulated in both cohorts and performed only on non-metastatic patients, identified novel prognostic biomarkers associated with OS in early-stage LUSC patients (HOXC4-worse OS, p=0.0001; LILRA5-better OS, p=0.0086). In total, 50 differentially expressed genes are correlated with patients’ OS. Aiming to get better insight into the profile of the tumor microenvironment, we estimated levels of immune-cells infiltration in LUSC and identified 4 subtypes based on immune-cell infiltration levels. Protein-protein interaction (PPI) network was built based on differentially expressed genes, and PPI modules and hub-genes were identified. Weighted gene co-expression network analysis was conducted to identify significant modules and hub-genes in correlation to clinical traits. Differential analysis on miRNA-Seq data, obtained from 16 tumor and 4 healthy tissue samples, was conducted as well. 75 up-regulated and 47 down-regulated miRNAs were identified. Further, targets of differentially expressed miRNA were identified, following gene ontology analysis and miRNA-mRNA networks construction.

ORGANISM(S): Homo sapiens

PROVIDER: GSE229509 | GEO | 2024/02/28

REPOSITORIES: GEO

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Project description:Squamous cell lung cancer (LUSC) is a frequently diagnosed histological subtype of lung malignancy associated with high mortality due to limited number of treatment options. Identification of potential targets suitable for drug development using high-throughput methods is still lacking. Therefore, the purpose of this research is to analyze expression profiles of mRNA and miRNA in LUSC, aiming to identify the key molecules associated with tumorigenesis and prognosis (overall survival; OS). We performed differential gene expression analysis, pathway enrichment analysis and gene ontology analysis on RNA-seq data obtained from 23 FFPE tumor samples and 3 FFPE healthy individuals. TCGA LUSC and GTEx healthy donors’ cohorts were used for validation. We identified 1133 up-regulated and 644 down-regulated genes, common for both cohorts. The most significant up-regulated genes were involved in cell-cycle regulation pathways, while down-regulated genes predominately belonged to immune-related pathways. Survival analysis performed on selected genes, commonly dysregulated in both cohorts and performed only on non-metastatic patients, identified novel prognostic biomarkers associated with OS in early-stage LUSC patients (HOXC4-worse OS, p=0.0001; LILRA5-better OS, p=0.0086). In total, 50 differentially expressed genes are correlated with patients’ OS. Aiming to get better insight into the profile of the tumor microenvironment, we estimated levels of immune-cells infiltration in LUSC and identified 4 subtypes based on immune-cell infiltration levels. Protein-protein interaction (PPI) network was built based on differentially expressed genes, and PPI modules and hub-genes were identified. Weighted gene co-expression network analysis was conducted to identify significant modules and hub-genes in correlation to clinical traits. Differential analysis on miRNA-Seq data, obtained from 16 tumor and 4 healthy tissue samples, was conducted as well. 75 up-regulated and 47 down-regulated miRNAs were identified. Further, targets of differentially expressed miRNA were identified, following gene ontology analysis and miRNA-mRNA networks construction.

Project description:Background: Only a subset of radically-resected pancreatic ductal adenocarcinoma (PDAC) patients benefit from chemotherapy, and identification of novel prognostic factors is warranted. Recently miRNAs emerged as diagnostic biomarkers and innovative therapeutic targets, while high-throughput arrays are opening new opportunities to evaluate whether they can also predict clinical outcome. The present study evaluated whether comprehensive miRNA expression profiling correlated with overall survival (OS) in resected PDAC patients. Methodology/Principal Findings: High-resolution miRNA profiles were obtained with the Toray’s 3D-GeneTM miRNA chip, detecting more than 1200 types of human miRNA. RNA was isolated from paraffin-embedded primary tumors of 26 radically resected stage-pT3N1 homogeneously treated patients (adjuvant gemcitabine 1000mg/m2/day, days-1/8/15, every 28days), carefully selected according to their outcome (OS<12 vs. OS>30 months, i.e. short/long-OS). Highly stringent statistics included t-test, distance matrix with Spearman-ranked correlation, and iterative approaches. Unsupervised hierarchical analysis revealed that PDAC specimens clustered according to their short/long-OS classification, while the feature selection algorithm RELIEF identified the top-4 discriminating miRNAs between the two groups. These miRNAs target more than 1500 transcripts, including 169 targeted by two or more of these miRNAs. MiR-211 emerged as the best discriminating miRNA, with significantly higher expression in long- vs. short-OS patients. The expression of this miRNA was subsequently assessed by quantitative-PCR in an independent cohort of laser microdissected tumors from 60 resected stage-pT3N1 PDAC patients treated with the same gemcitabine regimen. Patients with low miR-211 expression according to median value had a significantly shorter median OS (14.8, 95%CI=13.1-16.5, vs. 25.7 months, 95%CI=16.2-35.1, log-rank P=0.004). Multivariate analysis demonstrated that low miR-211 expression was an independent factor of poor prognosis (hazard ratio 2.3, P=0.03) after adjusting for all the factors influencing outcome.

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Transcriptomic Profiling for Prognostic Biomarkers in Early-stage Squamous Cell Lung Cancer (SqCLC)

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