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Multi-Omics Immune Interaction Networks in Lung Cancer Tumorigenesis, Proliferation, and Survival

Authors :
Qing Ye
Justin Hickey
Kathleen Summers
Brianne Falatovich
Marieta Gencheva
Timothy D. Eubank
Alexey V. Ivanov
Nancy Lan Guo
Source :
International Journal of Molecular Sciences; Volume 23; Issue 23; Pages: 14978
Publication Year :
2022

Abstract

There are currently no effective biomarkers for prognosis and optimal treatment selection to improve non-small cell lung cancer (NSCLC) survival outcomes. This study further validated a seven-gene panel for diagnosis and prognosis of NSCLC using RNA sequencing and proteomic profiles of patient tumors. Within the seven-gene panel, ZNF71 expression combined with dendritic cell activities defined NSCLC patient subgroups (n = 966) with distinct survival outcomes (p = 0.04, Kaplan–Meier analysis). ZNF71 expression was significantly associated with the activities of natural killer cells (p = 0.014) and natural killer T cells (p = 0.003) in NSCLC patient tumors (n = 1016) using Chi-squared tests. Overexpression of ZNF71 resulted in decreased expression of multiple components of the intracellular intrinsic and innate immune systems, including dsRNA and dsDNA sensors. Multi-omics networks of ZNF71 and the intracellular intrinsic and innate immune systems were computed as relevant to NSCLC tumorigenesis, proliferation, and survival using patient clinical information and in-vitro CRISPR-Cas9/RNAi screening data. From these networks, pan-sensitive and pan-resistant genes to 21 NCCN-recommended drugs for treating NSCLC were selected. Based on the gene associations with patient survival and in-vitro CRISPR-Cas9, RNAi, and drug screening data, MEK1/2 inhibitors PD-198306 and U-0126, VEGFR inhibitor ZM-306416, and IGF-1R inhibitor PQ-401 were discovered as potential targeted therapy that may also induce an immune response for treating NSCLC.

Details

ISSN :
14220067
Volume :
23
Issue :
23
Database :
OpenAIRE
Journal :
International journal of molecular sciences
Accession number :
edsair.doi.dedup.....0154a0227497f27eb0af34f9fe5a61fb