Technology in Cancer Research & Treatment · 2020 · 20 citations · 17 references
MedicineImmunologyOncologyImmunotherapyMolecular OncologyTumor ImmunologyBiomarker-guided ImmunotherapyCancer BiomarkersCancer GenomicsCancer ImmunotherapyImmuno-oncology BiomarkersMolecular Classification Of TumorsImmune Biomarker ProfilingImmune Biomarkers In CancerImmune Gene Expression SignaturesNon-small Cell Lung Cancer ImmunotherapyNon-small Cell Lung Cancer TherapyNon-small Cell Lung Cancer TreatmentPredictive Tumor MarkersProgrammed Death-ligand 1 Biomarker
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.
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