Network Analysis of Gut Microbiome and Metabolome to Discover Microbiota-Linked Biomarkers in Patients Affected by Non-Small Cell Lung Cancer
Creators
- 1. Area of Genetics and Rare Diseases, Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, 00146 Rome, Italy
- 2. IMT School for Advanced Studies Lucca, Networks Unit, 55100 Lucca, Italy
- 3. Institute for Systems Analysis and Computer Science "Antonio Ruberti", National Research Council, 00185 Rome, Italy
- 4. Department of Chemistry and NMR-Based Metabolomics Laboratory, Sapienza University of Rome, 00185 Rome, Italy
- 5. Department of Environmental Biology and NMR-Based Metabolomics Laboratory, Sapienza University of Rome, 00185 Rome, Italy
- 6. Department of Clinical and Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy and AOU Policlinico Umberto I, 00161 Rome, Italy
- 7. Department of Computer, Control and Management Engineering, Sapienza University of Rome, 00185 Rome, Italy
- 8. Department of Molecular Sciences and Nanosystems, Ca' Foscari, University of Venice, and European Centre for Living Technologies, 30172 Venice, Italy, and Institute of Complex Systems (CNR), Department of Physics, University of Rome "Sapienza", 00185 Rome, Italy
- 9. Department of Experimental Medicine, University Sapienza of Rome, 00185 Rome, Italy
- 10. Department of Clinical and Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy, AOU Policlinico Umberto I, 00161 Rome, Italy, and AOU Sant' Andrea Hospital, 00189 Rome, Italy
- 11. Department of Diagnostic and Laboratory Medicine, Unit of Parasitology and Area of Genetics and Rare Diseases, Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, 00165 Rome, Italy
Description
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.
Files
ijms-21-08730-v2.pdf
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(1.8 MB)
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