The Gut Microbiome Strains: Non-Small Cell Lung Cancer Treatment: Deciphering the Connection

Abstract

Non-small cell lung cancer (NSCLC) is the second most frequently diagnosed cancer worldwide and the leading cause of cancer-related mortality, with approximately 1.8 million reported deaths in 2020. NSCLC treatment includes surgery, chemotherapy, radiation, and immunotherapy, with Immune Checkpoint Inhibitors (ICIs) such as PD1/PD-L1 inhibitors revolutionizing patient outcomes. However, treatment response varies significantly among patients, presenting a substantial challenge. Emerging evidence suggests that the gut microbiome profoundly influences the efficacy of cancer therapies, including ICIs. This research investigates the role of gut microbial species, strains, and genetic variants in modulating NSCLC treatment response. Utilizing metagenomic analysis, taxonomic profiling was conducted to identify microbial species such as B. uniformis, F. prausnitzii, and A. muciniphila present in NSCLC patients' gut microbiomes at various time points and response categories. Strain diversity profiling revealed specific strains consistently present across all time points, including strains of B. uniformis and F. prausnitzii, while others, such as L. eligens and E. coli, were unique to patient responses. Variant calling identified 35,615 genetic variations in responders and 47,969 in nonresponders, including SNPs, indels, and complex mutations. Notably, NR exhibited a higher number of genetic variations, highlighting potential microbial markers for treatment efficacy. Specific genes, including ftsA, lpdA, and sufD, were associated with treatment response, providing insights into the functional attributes of these variations. Further, gene ontology analysis categorized these genetic variants into biological processes, cellular components, and molecular functions, underscoring the role of microbial genes in XVII influencing treatment outcomes. Machine learning models showed an AUC of 85%, indicating the predictive capabilities for treatment response based on gut microbiome composition. Our findings emphasize the potential of integrating gut microbiome analysis with NSCLC treatment strategies to enhance the efficacy of immunotherapy. By deciphering the connection between gut microbiome and NSCLC treatment responses, this study may highlight the need for developing microbiome-based interventions to optimize cancer therapy outcomes.