Page 239 - Haematologica Vol. 107 - September 2022

LETTER TO THE EDITOR
The gut microbiome in patients with chronic lymphocytic leukemia
The gut microbiome, an ecosystem formed by commen- sal, symbiotic, and pathogenic microorganisms colonizing the gastrointestinal tract, may impact both immune func- tion and carcinogenesis. The host immune system plays a vital role in the maintenance of gut microbiome homeo- stasis by establishing a balance between eliminating in- vading pathogens and promoting the growth of beneficial microbes. When this balance is disturbed, a state of dys- biosis arises in the microbial ecosystem. Conditions found to be associated with gut dysbiosis include, but are not limited to, inflammatory disorders including inflammatory bowel diseases (IBD),1 diabetes,2 as well as obesity,3 and asthma.4 The gut microbiome also seems to influence cancer susceptibility, and to correlate with tumorigenesis and progression.5 Within the area of hematological malig- nancies, studies focusing on acute leukemias, lymphopro- liferative disorders, and multiple myeloma, have found microbiome dysbiosis and decreased microbiome diver- sity to be related to microenvironmental alterations in- duced by the disease itself, chemotherapy, and/or antibiotics.6
To our knowledge, no previous studies have investigated the gut microbiome in patients with chronic lymphocytic leukemia (CLL). As CLL represents an antigen-driven ma- lignancy with immune dysfunction,7 the gut microbiome could both be implicated in the pathogenesis of CLL through antigenic drive, and contribute to the distortion of the immune system. However, the CLL microbiome itself may also be impacted by the immune dysfunction as well as reflect the increased prescription of antimicro- bials for this patient group. Thus, our study focusing on the fecal microbiome in patients with CLL aimed to de- scribe perturbations in the gut microbial composition, and to characterize potential signature for CLL-related gut dysbiosis.
We included fecal samples from ten patients enrolled during regular out-patient visits. Control cohorts were se- lected from an array of previously published cohorts8,9 and matched to the CLL cohort on criteria including mean age, residency, year of sampling, and sampling methods. Using shotgun metagenomic sequencing and taxonomical pro- filing, we assessed fecal microbiome composition, diver- sity, and dynamics. Bioinformatic analyses were performed following the state-of-the-art methods as well as using innovative tailor-made approaches.
Ten patients diagnosed with CLL delivered 12 stool samples between January 2016 and October 2018. Samp- ling was prior to treatment for eight patients and after
treatment for four patients, thus, two patients, were sampled both before and after treatment. No patients re- ceived antibiotics within 4 months prior to sample col- lection. For an overview of patient and control baseline characteristics, and patient treatment see the Online Sup- plementary Figure S1A to C. Changes in relative abundance of ten major bacterial genera in patients sampled both before and after treatment are demonstrated in the Online Supplementary Figure S1D.
We observed high intra-variability among the CLL micro- biomes (Figure 1A). At the genus level, Bacteroides was the most abundant genus in six of the 12 CLL samples. Addi- tionally, there was a trend of Bacteroides acquiring bac- terial dominance (>30% relative abundance) in five of 12 samples. Several other bacterial genera such as Parabac- teroides, Prevotella, and Acinetobacter also acquired bac- terial dominance among CLL patients. We next assessed microbiome diversity in CLL patients and healthy controls. Richness (the observed number of species) was lowest for patients with CLL and was significantly different com- pared to each of the two control cohorts (Observed: CLL vs. C1: median, 53 vs. 69; P=0.00057; CLL vs. C2: median, 53 vs. 73; P=6.8e−05; Figure 1B). Patients with CLL also showed lower a diversity compared to the control groups when assessed by Shannon index (CLL vs. C1: median, 1.90 vs. 2.90; P=2.1e−05; CLL vs. C2: median, 1.90 vs. 2.75; P=0.00057) and InvSimpson index (CLL vs. C1: median, 4.18 vs. 11.94; P=4.3e−05; CLL vs. C2: median, 4.18 vs. 10.05; P=0.00057; Figure 1B). The two control cohorts also dem- onstrated a significant difference in diversity between one another (C1 vs. C2: Shannon: median, 2.90 vs. 2.75; P=0.00057; InvSimpson: median, 11.94 vs. 10.05; P=0.017). In addition to reduced diversity, a difference in the spe- cific microbial composition between the CLL cohort and the two control cohorts was observed: at the phylum level, we focused on the differences in Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria as they comprised 95% of the total bacterial content in CLL pa- tients, on average. The distribution of these four phylo- types across each cohort highlights a significantly higher abundance of Bacteroidetes and Proteobacteria relative to the controls (Figure 1C). In contrast, both control groups showed greater proportions of Firmicutes and Actinobac- teria.
At the family level, Bacteroidaceae, Prevotellaceae, Clos- tidiaceae, Lachnospiraceae and Ruminococcaceae were the most abundant five families among both CLL patients and controls (Figure 2A). Bacteroidaceae were present in
Haematologica | 107 September 2022
2238