Between January 2016 and April 2018, 30 patients who underwent allo-HSCT for hematologic malignancies and had oral mucosa samples collected were included in this study. The most common underlying diseases were acute myeloid leukemia and acute lymphoblastic leukemia (60%). Conditioning regimens and intensity, graft source, T-cell depletion, and other clinical characteristics are listed in Table 1. The median follow-up time for survivors was 41 (30–50) months.
Microbiota dynamics analyses
In total, 5,920,836 high-quality bacterial assigned sequencing reads were analyzed, representing 1723 unique ASVs. Out of the 90 samples sequenced, nine were excluded from diversity analyses owing to an insufficient number of high-quality reads (< 12,500 reads per sample, as determined using alpha diversity rarefaction curves) after the read-filtering steps employed in the pipeline. Therefore, adequate preconditioning samples were available for 27 of the 30 patients included in this study.
The intrasample bacterial diversity (Figure 1A) and richness (Figure S1) of OM samples decreased significantly during the clinical course. This drop in diversity is associated with changes in taxa relative abundance during the same period (Figure S2). Notably, all patients showed bacterial dominance by a single genus after preconditioning. In Figure 1B, we show three representative patients with major dominance (relative abundance > 80%) by a single genus (Stenotrophomonas, Rothia, and Veillonella, respectively) at engraftment.
For a broader assessment of the relative abundance changes from preconditioning to subsequent transplantation phases, we employed the ANCOM test at the genus level. We observed statistically significant variations in the abundance of both opportunistic pathogenic and commensal genera (Figure S3). From preconditioning to aplasia, there was a significant increase in the abundance of the potentially pathogenic genera Enterococcus and Lactobacillus, which were even more increased in the engraftment phase in terms of relative abundance fold change from preconditioning. Staphylococcus and Mycoplasma were other potentially pathogenic genera increased at engraftment. Contrarily, there was a significant decrease in the abundance of the commensal genera Haemophilus (at aplasia) and Gemella (at engraftment).
A global increase of potentially pathogenic genera occurs during allo-HSCT. However, evaluating each patient individually, we noticed irregular changes in the relative abundance of those same genera from preconditioning to engraftment. An increase in the relative abundance of Enterococcus, Lactobacillus, Staphylococcus, and Mycoplasma was observed in 32%, 40%, 56%, and 68% of patients (Figure S4). Patients who presented an increase in Enterococcus relative abundance had a higher incidence of cGVHD when compared with patients without the increase of relative abundance (P = 0.03). No other associations between the increase in the relative abundance of potentially pathogenic genera and allo-HSCT outcomes was observed (Table S1).
Impact of OM diversity on transplant outcomes
In order to elucidate the impact of OM bacterial diversity on allo-HSCT outcomes, we stratified patients into low or high diversity at each collection time (Table S2). A swimmer plot was used to illustrate these correlations at preconditioning (Figure 2A). When we compared those with high or low OM diversity at preconditioning, no differences were found in PFS (36% versus 32%, respectively; hazard ratio [HR] = 0.75, 95% CI: 0.28–2.00, P = 0.57), or in OS at 3 years (54% versus 57%, respectively; HR = 0.96, 95% CI: 0.33–2.89, P = 0.96). We also did not observe any differences in aGVHD at 100 days (43% versus 62%, respectively; HR = 1.77, 95% CI: 0.66–4.81, P = 0.26) or cGVHD at 3 years (30% versus 7%, respectively; HR = 4.79, 95% CI: 0.56–40.8, P = 0.15). However, high OM diversity at preconditioning was associated with a lower risk of relapse at 3 years when compared with low diversity (33% versus 68%, respectively; HR = 0.27, 95% CI: 0.07–0.97, P = 0.04; Figure 2B, Table S3).
Notably, 16 (59%) patients presented some type of bacterial dominance at preconditioning. Such events encompassed 4 different genera, all of which are oral commensal: Streptococcus (dominant in 9/16 patients) and Veillonella (dominant in 2/16 patients), both members of the Firmicutes phylum; Neisseria (dominant in 3/16 patients) and Rothia (dominant in 2/16 patients). Genus dominance was detected even among patients classified as having high diversity at preconditioning (Figure 2A). The presence of dominance by any genus at preconditioning was also associated with an increased risk of relapse at 3 years when compared with the absence of dominance (63% versus 36%, respectively; HR = 4.59, 95% CI: 1.11–19, P = 0.03; Figure 3A). When evaluating dominance by specific genera or types of genera at preconditioning, neither dominance by Streptococcus (56% versus 39%, respectively; HR = 1.64, 95% CI: 0.52-5.14, P = 0.4), nor dominance by facultative anaerobic genera (Streptococcus or Rothia; 56% versus 39%, respectively; HR = 2.05, 95% CI: 0.67-6.27, P = 0.21) were associated with an increased risk of relapse. Due to the very unequal group sizes, we could not evaluate the association between dominance by Rothia (2/27 patients), Veillonella (the only dominant anaerobe; 2/27 patients) or Neisseria (the only dominant aerobe; 3/27 patients) at preconditioning and the risk of relapse.
Additionally, the presence of dominance by any genus at preconditioning was associated with inferior PFS (19% versus 55%, respectively; HR = 4.75, 95% CI: 1.78–12.7, P = 0.01; Figure 3B) and OS (38% versus 81%, respectively; HR = 4.73, 95% CI: 1.59–14.08, P = 0.02; Figure 3C). No differences in aGVHD at 100 days (43% versus 63%, respectively; HR = 0.50, 95% CI: 0.18–1.37, P = 0.18), cGVHD at 3 years (19% versus 18%, respectively; HR = 1.07, 95% CI: 0.19–5.93, P = 0.94), or NRM at 3 years (20% versus 9%, respectively; HR = 2.35, 95% CI: 0.27–20.60, P = 0.44) were observed.
As expected, we also observed that patients with a high DRI had a significantly higher risk of relapse/progression, as compared with those with low-intermediate DRI at 3 years (62% versus 12%, respectively; HR = 10.2, 95% CI: 2.24–46.7, P < 0.01) and worse OS (77% versus 30%, respectively; HR = 4.07, 95% CI: 1.38–11.97, P = 0.01).
After adjusting analyses for the DRI, there was a trend toward a higher risk of relapse/progression in those with low OM diversity (HR = 0.30, 95% CI: 0.08–1.09, P = 0.07; Figure 2C), and bacterial dominance of any genus remained significantly associated with the risk of relapse (HR = 4.19, 95% CI: 1.25–14.1, P = 0.02; Figure 3D) and worse PFS (HR = 4.14, 95% CI: 1.15–14.89, P = 0.03; Figure 3E); there was a tendency for bacterial dominance of any genus to also be related to worse OS (HR = 4.12, 95% CI: 0.89–19.13, P = 0.07; Figure 3F).
Other relevant clinical parameters, such as conditioning intensity, underlying disease, and graft source, were not significantly associated with the risk of relapse (Figure S5, Table S4).
Genus presence and transplant outcomes
As the genus level represents the most specific taxonomic level that still provides reliable taxonomic classification for V3-V4 amplicons, to further evaluate the association between preconditioning OM and transplant outcomes, we analyzed whether any non-core genus (those present in 25-75% of samples) was associated with a higher risk of relapse. In this exploratory analysis (without adjustment for multiple comparisons), of the 18 genera that matched the selection criteria tested in a univariate analysis for relapse (Figure 4A, Figure S6), only Solobacterium was significantly associated with lower relapse risk (9% versus 56%, respectively; HR = 0.23, 95% CI: 0.05–0.94, P = 0.04; Figure 4B), and this association remained significant after adjusting for DRI (HR = 0.20, 95% CI: 0.06–0.67, P = 0.01; Figure 4C). However, after adjusting for multiple comparisons using the Bonferroni correction, because of the limited statistical power of this study, the univariate association between Solobacterium presence and lower relapse risk loses significance (P = 0.72). The relative abundance of Solobacterium at preconditioning per patient is depicted in Figure S7. No differences in the presence of Solobacterium were found in other outcomes (aGVHD at 100 days: 64% versus 44%, respectively [HR = 1.84, 95% CI: 0.68–4.95, P = 0.23]; cGVHD: 27% versus 13%, respectively [HR = 2.41, 95% CI: 0.43–13.4, P = 0.31]; PFS: 55% versus 37%, respectively [HR = 0.83, 95% CI: 0.31–0.83, P = 0.71]; and OS at 3 years: 55% versus 28%, respectively [HR = 0.99, 95% CI: 0.32–3.08, P = 0.99]).
From 1 week before the start of the conditioning regimen to engraftment, 28 (93%) patients used antibiotics to treat febrile neutropenia; 20 (67%) used cefepime, 16 (53%) used meropenem, and four (13%) used piperacillin-tazobactam. None of these antibiotics were associated with the risk of relapse (Figure S5).
We could not analyze the association between the use of antibiotics before transplant (30 days before starting the conditioning regimen) and OM bacterial diversity because of the small number of patients who used antibiotics at that time point.