ArticleJournal of applied genetics2025
Genomic Profiling Reveals Immune-Related Gene Differences in Lung Cancer Patients Stratified by PD1/PDL1 Expression: Implications for Immunotherapy Efficacy.
Article in Journal of applied genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors at 2 institutions in 1 country.
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Abstract
Lung cancer remains a leading cause of global cancer-related mortality, and the exploration of innovative therapeutic approaches, such as PD1/PDL1 immunotherapy, is critical. This study leverages comprehensive data from the Cancer Genome Atlas (TCGA) to investigate the differential expression of PD1/PDL1 in lung cancer patients and explores its implications. Clinical data, RNA expression, somatic mutations, and copy number variations of 1017 lung cancer patients were obtained from TCGA. Patients were categorized into high (HE) and low (LE) PD1/PDL1 expression groups based on mRNA levels. Analyses included differential gene expression, functional enrichment, protein-protein interaction networks, and mutational landscape exploration. The study identified 391 differentially expressed genes, with CD4 and PTPRC among the upregulated genes in the HE group. Although overall survival did not significantly differ between HE and LE groups, enrichment analysis revealed a strong association with immunoregulatory signaling pathways, emphasizing the relevance of PD1/PDL1 in immune response modulation. Notably, TP53 mutations were significantly correlated with high PD1/PDL1 expression. This study provides a comprehensive analysis of PD1/PDL1 expression in lung cancer, uncovering potential biomarkers and highlighting the intricate interplay between PD1/PDL1 and the immune response. The identified upregulated genes, including CD4 and PTPRC, warrant further investigation for their roles in the context of lung cancer and immunotherapy. The study underscores the importance of considering molecular heterogeneity in shaping personalized treatment strategies for lung cancer patients. Limitations, such as the retrospective nature of TCGA data, should be acknowledged.
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