Unraveling the relapse-associated landscape and individualized therapy in stage I lung adenocarcinoma based on immune and mitochondrial metabolism hallmarks via multi-omics analyses
Tao Zhan , Luyao Wang , Zewei Li , Huijing Deng , Liu Huang
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引用次数: 0
Abstract
Lung adenocarcinoma (LUAD) is characterized by significant molecular heterogeneity and high recurrence rate even among stage I patients. There is an urgent quest for reliable biomarkers to recognize early-stage patients at high risk and guide potential treatment. Considering the pivotal role of immune and mitochondrial metabolic hallmarks in tumor initiation and progression, we rigorously included four independent cohorts of stage I LUAD patients with or without relapse. A consensus immune and mitochondrial metabolism genes-related signature (IMMS) is then constructed via 101 machine-learning combinations. IMMS classified all patients into high- and low-risk groups and exhibited a leading predicting accuracy compared with 70 previously published signatures. Subsequently, comprehensive analysis of the multi-omics data discovered elevated genomic heterogeneity, cancer stemness, metabolic reprogramming, immune escape, and tolerance to immune therapy in the high-risk group, which promotes the survival and proliferation of tumor cells. After the analysis of multiple drug databases, mitoxantrone is considered a candidate drug for stage I high-risk LUAD patients. The research of single-cell data further supported the tight association between IMMS and tumor cell characteristics. Overall, our study developed a novel signature and emphasized the role of immune escape and metabolic reprogramming hallmarks in recurrence, offering valuable insights into clinical prognosis, molecular mechanism, and individualized therapy for stage I LUAD patients.
期刊介绍:
Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.