bioRxivCancer BiologyPreprint
LINC00261 expression reduces mutation accumulation while conferring resistance to cisplatin and altering the tumor-immune microenvironment in lung adenocarcinoma
J. Castillo, T. Xue, S. Joseph, M. Norwood, D. J. Mullen, S. Berrellez, S. James, A. L. Epstein, T. McEachron, C. N. Marconett
Abstract
Immunotherapy has emerged as a major breakthrough that has the ability to improve survival outcomes for multiple solid tumor types, however effective response requires the combination of blocking inhibitory signals on the tumor surface and antigen presentation to the tumor surface for proper immune recognition. Several commercially available and robust methods exist for identification of tumors displaying immune-inhibitory surface receptors, including PD-L1 and CTLA-4, however it is currently difficult to predict effectiveness of antigen presentation on the cell surface. To address this, we utilized clinical and next-generation sequencing data generated by The Cancer Genome Atlas (TCGA) to identify gene signatures that are correlated to tumor mutational burden (TMB) within cancers of epithelial origins as a surrogate for neoantigen signatures. We identified LINC00261 as a top gene correlated to mutational burden (TMB), whose expression activates DNA damage response pathways in vitro along with resistance to cisplatin. LINC00261 expression was also significantly correlated to MHC Class II genes involved in endogenous neoantigen presentation expression within the TCGA-LUAD cohort. This relationship was confirmed in vitro through ectopic reintroduction of LINC00261 for key MHC Class II presentation genes. Interferon gamma-induced MHC gene activation in vitro was also able to induce endogenous expression of LINC00261. Our results suggest there is a mechanistic relationship between LINC00261 expression and functional MHC Class II neoantigen presentation in LUAD. The silencing of LINC00261 in LUAD results in compromised DNA repair, accumulation of mutations, and reduced antitumor immune response.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
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