Background: The human gut microbiome plays a pivotal role in health and disease, influencing immunity, metabolism, and disease susceptibility. Though dysbiosis in the gut microbiome has been postulated in hematologic cancers, most studies are confounded by chemotherapy, immunosuppression, and antibiotic exposure (Guevara-Ramírez P et al. Int J Mol Sci. 2024). In immunocompromised populations, such as those with hematologic malignancies, alterations in microbial communities may have critical implications. It remains unclear whether microbial compositional and functional alterations precede diagnosis or arise secondarily to treatment.

Objectives: To profile the gut microbiome diversity and to identify differential abundance and indicator species in patients with hematologic malignancies compared to healthy controls.

Methods: In this proof of concept study, we included fecal samples from 11 newly diagnosed acute leukemia (AL) and 6 multiple myeloma (MM) patients enrolled during regular hospital visits. All cases were sampled both before and after intiating chemotherapy treatment. Healthy control samples were collected from the same geographical location. Gut microbiome analysis was performed by 16S rRNA gene amplicon sequencing followed by bioinformatics analysis in R packages.

Results: Among AL cases with recorded age/sex, the median age was 59 years (IQR 42–75; range 39–80) with 3(27.3%) females. Among MM cases with recorded age/sex, the median age was 53 years (IQR 48–61; range 48–70) and all were male. At the phylum level, Firmicutes dominated across all groups, with a notable increase in Proteobacteria and decrease in bacteroidetes in AL and MM cases compared to controls. Minor shifts was observed at phylum and species level after chemotherapy. Control samples were enriched in Faecalibacterium prausnitzii, Lactobacillus ruminis, Prevotella copri, and Roseburia faecis whereas AL and MM groups showed increased abundance of opportunistic taxa such as Streptococcus spp. Leuconostoc spp. and Enterococcus spp. Alpha diversity for microbial composition was significantly reduced in controls compared to the cases (p=0.005). MM (p=0.022) and AL (p=0.008) groups showed significantly increased richness compared to control with Shannon indices showing moderate shifts (p=0.08)) in species diversity in MM. In beta diversity, PCoA plots has shown significant difference between control and case groups (p<0.001), highlighting distinct microbial diversity. No significant difference in both alpha and beta diversity was observed in post- versus pre-treatment. Differential abundance analysis showed significant reduction of health-associated putative beneficial taxa such as [Eubacterium] biforme, Faecalibacterium prausnitzii, Prevotella copri, Lactobacillus ruminis and Bacteroides spp. in the disease groups, further supporting a dysbiosis signature. Indicator species analysis identified disease-specific microbial biomarkers compared to the controls. Proteobacteria such as Salmonella enterica and Klebsiella oxytoca formed the influencer species in AL cases and MM cases showed unique indicators such as Eggerthella lenta and Streptococcus luteicae.

Conclusion: Our data suggest that newly diagnosed, treatment-naïve AL and MM harbor distinct, disease-specific gut microbiome signatures compared with healthy controls. Although microbial diversity was higher in the disease groups, it was characterized by increased opportunistic and pathogenic taxa, indicating a loss of ecological balance rather than a healthy expansion. Acute leukemia (AL) showed a stronger accumulation of Enterobacteriaceae/pathobionts, potentially relevant to bloodstream infection risk during induction, while multiple myeloma (MM) showed a more pronounced loss of short-chain fatty acid (SCFA)–producing keystone taxa that may affect mucosal integrity and immune regulation. The identification of disease-specific indicator species offers potential biomarkers for diagnostic or therapeutic microbiome-based interventions. Further longitudinal and functional studies are warranted to clarify causal relationships and to test microbiota-directed strategies.

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