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

Int J Mol Sci. 2022 Nov 29;23(23):14978. doi: 10.3390/ijms232314978.


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.

Keywords: CRISPR-Cas9/RNAi; diagnosis; drug screening; non-small cell lung cancer; prognosis; targeted therapy.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Carcinogenesis
  • Carcinoma, Non-Small-Cell Lung* / pathology
  • Cell Proliferation / genetics
  • Humans
  • Lung Neoplasms* / pathology
  • Multiomics
  • Proteomics


  • Biomarkers, Tumor