Grant Details
Grant Number: |
5R01CA269617-03 Interpret this number |
Primary Investigator: |
Diefenbach, Catherine |
Organization: |
New York University School Of Medicine |
Project Title: |
A Prospective Evaluation of the Gut Microbiome as a Mediator of Lymphoma Treatment Outcome and Systemic Immunity |
Fiscal Year: |
2024 |
Abstract
ABSTRACT/SUMMARY
Diffuse large B-cell lymphoma (DLBCL), the most common lymphoma, is a significant clinical problem, with only
60% of patients cured. Mechanisms for how DLBCL, an immune cancer, evades host defenses are poorly
understood. Growing evidence suggests that the human gut microbiota (GMB) plays important roles in regulating
innate and adaptive immunity, and is associated with therapeutic outcome in multiple solid tumor types. Based
on this connection, we hypothesize that the GMB influences lymphoma behavior by altering the anti-tumor
immune response. Our preliminary data provide compelling evidence that DLBCL patients: a) have distinct
GMB compositions in which many commensal families are lost; and b) show chronic activation in central and
effector memory T cells. However, the connections between GMB and lymphoma remain poorly understood,
limiting the development of targeted therapies. The overall goal of the proposed research is to investigate
longitudinally the impact of GMB signatures on clinical response and systemic immunity in DLBCL.
Thus, our specific aims are: Aim 1: To investigate in untreated DLBCL the association between the GMB and
treatment response using 16S and full metagenomic shotgun sequencing of stool samples from 300 patients
pre-treatment, during treatment, and at 12 months, a validated endpoint for clinical outcome; Aim 2: To evaluate
the potential bi-directional associations between GMB and DLBCL by tracking concurrent stool and weekly blood
samples which we will analyze with novel Bayesian timeseries methods for a subset of 50 DLBCL patients daily
during the first 14 days of treatment, and then in follow-up as in Aim 1; Aim 3: To investigate functional
relationships between immune activation and microbial diversity, including translocation of microbial products
from the gut into the blood and expansion of antigen-specific T cells directed against poor outcome microbes.
The scientific premise is supported by extensive pilot data and rigorous application of established methods.
The proposed study is highly innovative, as it will be the first large scale longitudinal and prospective
investigation of the GMB in lymphoma, using state of the art methodologies such as, full metagenomic shotgun
sequencing, AbSeq, and Bayesian time series analysis. This research has the potential to significantly advance
lymphoma research by identifying the GMB and systemic immune pathways that impact treatment failure in
DLBCL, and it may provide the biologic insights for new personalized therapeutics. We will build on our findings
to develop personalized microbial-based therapies, which could range from dietary changes that would favor
growth of organisms we demonstrate to be beneficial, to targeted probiotic therapy and/or fecal transplantation to
reduce microbes we show are deleterious. Because gut bacteria are modifiable, our findings could lead in the
future to the implementation of tailored microbial-based therapies, a new and minimally toxic treatment paradigm
for DLBCL patients, a significant unmet medical need.
Publications
The MTIST platform: a microbiome time series inference standardized test.
Authors: Schluter J.
, Hussey G.
, Valeriano J.
, Zhang C.
, Sullivan A.
, Fenyƶ D.
.
Source: Research Square, 2024-05-08 00:00:00.0; , .
EPub date: 2024-05-08 00:00:00.0.
PMID: 38766187
Related Citations
Gut microbiome dysbiosis in antibiotic-treated COVID-19 patients is associated with microbial translocation and bacteremia.
Authors: Bernard-Raichon L.
, Venzon M.
, Klein J.
, Axelrad J.E.
, Zhang C.
, Sullivan A.P.
, Hussey G.A.
, Casanovas-Massana A.
, Noval M.G.
, Valero-Jimenez A.M.
, et al.
.
Source: Nature Communications, 2022-11-01 00:00:00.0; 13(1), p. 5926.
EPub date: 2022-11-01 00:00:00.0.
PMID: 36319618
Related Citations