Fecal Microbiota Taxonomic Shifts in Chinese Multiple Myeloma Patients Analyzed by Quantitative Polimerase Chain Reaction (QPCR) and 16S rRNA High-Throughput Sequencing

Abstract

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.

Figure 1

Beta diversity of the gut microbiota in each group using PCoA analysis.

Figure 2

(A) Histogram of species distribution for each sample at the phylum level. The sample with the beginning of A indicates the MM group; the sample with the beginning of B indicates the control group. (B) Comparison of IM between the MM group and healthy control at the phylum level.

Figure 3

Taxonomic differences were detected based on OTUs between MM group and healthy controls. (A) Linear discriminative analysis (LDA) effect size (LEfSe) analysis between healthy controls and MM patients. (B) Cladogram showing differentially abundant taxonomic clades with an LDA score >2.0 among patients and controls.

Figure 4

(A, B) Correlation analysis between the level of Clostridium leptum with ISS stage and creatinine levels.

Figure 5

(A, B) Differential analysis of KEGG metabolic pathway between MM and healthy controls.