Dataset Information

CSF1R and HCST: Novel Candidate Biomarkers Predicting the Response to Immunotherapy in Non-Small Cell Lung Cancer.

ABSTRACT: OBJECTIVE:Precision immunotherapy in non-small cell lung cancer (NSCLC) have been the focus of tumor immunity research. The aim of this study is to identify?novel candidate biomarkers predicting the response to immunotherapy in NSCLC. METHODS:GSE126044 was obtained from Gene Expression Omnibus (GEO). According to the response to anti-PD-1 antibody, 2 groups were divided: response group and non-response group. Differentially expressed genes (DEGs) were screened using R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. ROC curves and possible pathways of the seed genes were further analyzed. RESULTS:In total, 588 DEGs (487 upregulated DEGs and 101 downregulated) were identified. GO and KEGG analyses showed that upregulated DEGs were mainly enriched in immune response and cell adhesion pathways, while VEGF signaling pathway and metabolic pathways were mainly enriched in downregulated DEGs. In addition, CSF1 R and HCST showed more powerful predictive ability than PDL1. More importantly, these candidate genes were not only positively correlated with the expression of PDL1 and the infiltration of CD8+ T cells in the immune microenvironment, but also might improve the prognosis in lung squamous cell carcinoma. CONCLUSIONS:CSF1 R and HCST might be novel predictive markers for immunotherapy in NSCLC.

SUBMITTER: Qi X

PROVIDER: S-EPMC7658512 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature

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CSF1R and HCST: Novel Candidate Biomarkers Predicting the Response to Immunotherapy in Non-Small Cell Lung Cancer.

Qi Xiaoguang X Qi Chunyan C Wu Tao T Hu Yi Y

Technology in cancer research & treatment 20200101

<h4>Objective</h4>Precision immunotherapy in non-small cell lung cancer (NSCLC) have been the focus of tumor immunity research. The aim of this study is to identify novel candidate biomarkers predicting the response to immunotherapy in NSCLC.<h4>Methods</h4>GSE126044 was obtained from Gene Expression Omnibus (GEO). According to the response to anti-PD-1 antibody, 2 groups were divided: response group and non-response group. Differentially expressed genes (DEGs) were screened using R. Gene Ontolo ...[more]

PMID: 33153411

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Project description:Background: Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC. Methods: The microarray datasets of GSE18842, GSE30219, GSE31210, GSE32863 and GSE40791 from Gene Expression Omnibus database were downloaded. The differential expressed genes (DEGs) between NSCLC and normal samples were identified by limma package. The construction of protein-protein interaction (PPI) network, module analysis and enrichment analysis were performed using bioinformatics tools. The expression and prognostic values of hub genes were validated by GEPIA database and real-time quantitative PCR. Based on these DEGs, the candidate small molecules for NSCLC were identified by the CMap database. Results: A total of 408 overlapping DEGs including 109 up-regulated and 296 down-regulated genes were identified; 300 nodes and 1283 interactions were obtained from the PPI network. The most significant biological process and pathway enrichment of DEGs were response to wounding and cell adhesion molecules, respectively. Six DEGs (PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5) which significantly up-regulated in NSCLC tissues, were selected as hub genes according to the results of module analysis. The GEPIA database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. Additionally, CMap predicted the 20 most significant small molecules as potential therapeutic drugs for NSCLC. DL-thiorphan was the most promising small molecule to reverse the NSCLC gene expression. Conclusions: Based on the gene expression profiles of 696 NSCLC samples and 237 normal samples, we first revealed that PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5 could act as the promising novel diagnostic and therapeutic targets for NSCLC. Our work will contribute to clarifying the molecular mechanisms of NSCLC initiation and progression.

Dataset Information

CSF1R and HCST: Novel Candidate Biomarkers Predicting the Response to Immunotherapy in Non-Small Cell Lung Cancer.

Publications

CSF1R and HCST: Novel Candidate Biomarkers Predicting the Response to Immunotherapy in Non-Small Cell Lung Cancer.

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