Gut Microbiome Is Associated With the Response to Chemoradiotherapy in Patients With Non-small Cell Lung Cancer.

Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat‑sen University Cancer Center, Guangzhou, China. Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou. China. Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China. Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat‑sen University Cancer Center, Guangzhou, China. Electronic address: liuhuisysucc@126.com.

International journal of radiation oncology, biology, physics. 2023;(2):407-418
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Abstract

PURPOSE To explore the dynamic change of gut microbiota and its predictive role in progression-free survival (PFS) in non-small cell lung cancer (NSCLC) after concurrent chemoradiotherapy (CCRT). METHODS AND MATERIALS Forty-one patients with NSCLC in 2 phase 2 trials (NCT02573506 and NCT03006575) were analyzed. A total of 102 fecal samples were collected at 3 time points (T0, before CCRT; T1, 2 weeks after the initiation of CCRT; and T2, the end of CCRT). Gut microbiota composition and functionality were analyzed by 16S rRNA gene sequencing and shotgun metagenomics, respectively. Alpha diversity, taxonomic composition, and KEGG functional pathways were compared between patients in the long-PFS group (PFS ≥11.0 months) and short-PFS group (PFS <11.0 months). A random forest classifier was constructed to identify microbial signature related to PFS. Clinical and microbial factors potentially predictive of PFS were assessed in the univariate and multivariate Cox regression analysis. RESULTS The abundance of Bacteroidota and Proteobacteria increased, while the abundance of Firmicutes decreased after CCRT. Shannon index (P = .006) and PD index (P = .022) were significantly higher in the long-PFS group than for those in the short-PFS group at T1. The PFS-prediction microbial signature at T1 included unclassified members of the Lanchospiraceae spp., such as NK4A136 and UCG-003 groups, Dorea sp., various strains from within the Eubacterium hallii and E. siraeum groups, and an unclassified member of the Muribaculaceae, which yielded an area under the ROC curve of 0.87. These discriminatory genera mostly belong to phylum Firmicutes/family Clostridia. Multivariate analysis indicated PD index (HR = 8.036, P = .016) and the abundance of Dorea sp. at T1 (HR = 4.186, P = .043) were independent predictors of PFS. The KEGG pathways at T1 overrepresented in the long-PFS group included fatty acid metabolism, fatty acid biosynthesis, and arginine biosynthesis. Those overrepresented in the short-PFS group included lipopolysaccharide biosynthesis, ascorbate and aldarate metabolism, and biosynthesis of vancomycin group antibiotics. CONCLUSIONS Gut microbiota composition and functionality at 2 weeks after the initiation of CCRT were associated with PFS in NSCLC. Further research is needed to confirm these results.

Methodological quality

Publication Type : Clinical Trial

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