Characterization of Mitoribosomal Small Subunit unit genes related immune and pharmacogenomic landscapes in renal cell carcinoma

Abstract

AbstractMitoribosomes are essential for the production of biological energy. The Human Mitoribosomal Small Subunit unit (MRPS) family, responsible for encoding mitochondrial ribosomal small subunits, is actively engaged in protein synthesis within the mitochondria. Intriguingly, MRPS family genes appear to play a role in cancer. A multistep process was employed to establish a risk model associated with MRPS genes, aiming to delineate the immune and pharmacogenomic landscapes in clear cell renal cell carcinoma (ccRCC). MRPScores were computed for individual patients to assess their responsiveness to various treatment modalities and their susceptibility to different therapeutic targets and drugs. While MRPS family genes have been implicated in various cancers as oncogenes, our findings reveal a contrasting tumor suppressor role for MRPS genes in ccRCC. Utilizing an MRPS‐related risk model, we observed its excellent prognostic capability in predicting survival outcomes for ccRCC patients. Remarkably, the subgroup with high MRPS‐related scores (MRPScore) displayed poorer prognosis but exhibited a more robust response to immunotherapy. Through in silico screening of 2183 drug targets and 1646 compounds, we identified two targets (RRM2 and OPRD1) and eight agents (AZ960, carmustine, lasalocid, SGI‐1776, AZD8055_1059, BPD.00008900_1998, MK.8776_2046, and XAV939_1268) with potential therapeutic implications for high‐MRPScore patients. Our study represents the pioneering effort in proposing that molecular classification, diagnosis, and treatment strategies can be formulated based on MRPScores. Indeed, a high MRPScore profile appears to elevate the risk of tumor progression and mortality, potentially through its influence on immune regulation. This suggests that the MRPS‐related risk model holds promise as a prognostic predictor and may offer novel insights into personalized therapeutic strategies.