03 November 2019 : Clinical Research
Fecal Microbiota Taxonomic Shifts in Chinese Multiple Myeloma Patients Analyzed by Quantitative Polimerase Chain Reaction (QPCR) and 16S rRNA High-Throughput SequencingBingqing Zhang1BC*, Jingli Gu1D, Junru Liu1E, Beihui Huang1AF, Juan Li1AEG
Med Sci Monit 2019; 25:8269-8280
BACKGROUND: Increasing evidence has suggested that gut flora play an important role in tumor progression and prognosis. However, the relationship between fecal microbiota and hematologic malignancy requires further investigation. This study aimed to characterize the relationship of the fecal microbial community in multiple myeloma (MM) patients.
MATERIAL AND METHODS: A total of 40 MM patients and healthy controls (n=17) were retrospectively collected from the First Affiliated Hospital of Sun Yat-sen University between October 2018 and May 2019. The fecal samples were collected for 16S rRNA high-throughput sequencing for the fecal microbial community, as well as diversity and correlation analysis. Furthermore, 21 MM patients and their family members were selected for the matched pair analysis to confirm the fecal microbiota taxonomic changes by qRT-PCR assay.
RESULTS: Diversity analysis showed that diversity measured by Shannon index was lower in MM patients compared with healthy controls. At the phylum level, higher abundances of Proteobacteria but lower abundances of Actinobacteria were identified in the MM group in comparison with the healthy control group. At the genus level, the proportion of Bacteroides, Faecalibacterium, and Roseburia was significantly higher in the MM group. The matched pair analysis showed that Pseudomonas aeruginosa and Faecalibacterium were significantly more abundant in the MM group. Further analysis on prognostic risk factors revealed that the Faecalibacterium prausnitzii level was significantly correlated with ISS stage.
CONCLUSIONS: Our study highlights the imbalanced composition and diversity of the gastrointestinal microbiome in MM patients, which could be further used as a potential biomarker for MM risk screening, therapeutic strategies, and prognostic prediction.
Keywords: High-Throughput Nucleotide Sequencing, microbiota, Multiple Myeloma, Prognosis
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