1. Network Analysis of Gut Microbiome and Metabolome to Discover Microbiota-Linked Biomarkers in Patients Affected by Non-Small Cell Lung Cancer
- Author
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Tommaso Gili, Paola Paci, Pamela Vernocchi, Federica Del Chierico, Giorgia Conta, Federica Conte, Guido Caldarelli, Alfredo Miccheli, Paolo Marchetti, Lorenza Putignani, Andrea Botticelli, and Marianna Nuti
- Subjects
Rikenellaceae ,Indoles ,Lung Neoplasms ,medicine.medical_treatment ,Programmed Cell Death 1 Receptor ,Anti-PD1 immune checkpoint inhibitor ,Betweenness centrality ,Clustering coefficient ,Communities ,Gut microbiome ,Metabolite ,Network analysis ,Non-small cell lung cancer (NSCLC) ,Operational taxonomic unit (OTU) ,Weighted gene co-expression network analysis (WGCNA) ,non-small cell lung cancer (NSCLC) ,gut microbiome ,lcsh:Chemistry ,0302 clinical medicine ,Antineoplastic Agents, Immunological ,Carcinoma, Non-Small-Cell Lung ,RNA, Ribosomal, 16S ,Databases, Genetic ,Bacteroides ,anti-PD1 immune checkpoint inhibitor ,Gene Regulatory Networks ,Precision Medicine ,lcsh:QH301-705.5 ,network analysis ,Spectroscopy ,0303 health sciences ,biology ,clustering coefficient ,General Medicine ,weighted gene co-expression network analysis (WGCNA) ,3. Good health ,Computer Science Applications ,Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici ,Gene Expression Regulation, Neoplastic ,communities ,030220 oncology & carcinogenesis ,Disease Progression ,Metabolome ,Immunotherapy ,Drug Monitoring ,Akkermansia muciniphila ,betweenness centrality ,Signal Transduction ,metabolite ,Clostridiaceae ,Computational biology ,Catalysis ,Article ,Inorganic Chemistry ,03 medical and health sciences ,Metabolomics ,medicine ,Humans ,operational taxonomic unit (OTU) ,clustering coeffcient ,Physical and Theoretical Chemistry ,Molecular Biology ,030304 developmental biology ,Aldehydes ,Peptostreptococcus ,Organic Chemistry ,Cancer ,Akkermansia ,biology.organism_classification ,medicine.disease ,Fatty Acids, Volatile ,Gastrointestinal Microbiome ,lcsh:Biology (General) ,lcsh:QD1-999 ,Metagenomics ,Alcohols - Abstract
Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients.
- Published
- 2020