Douglas Walker

PhD

Emory University

Associate Professor

PLCO (Learn more about this study)

2023-0062

Jun 12, 2023

Environmental and Metabolic Phenotyping of the Blood Cancer Exposome

Non-Hodgkin's lymphoma (NHL) and acute myeloid leukemia (AML) are two of the most common hematologic cancers in the world. It has been estimated that approximately 20% of cases are collectively attributed to known risk factors, suggesting that the etiological factors largely remain unexplained and that agnostic investigations that utilize emerging molecular epidemiologic platforms may be informative. Our research team has developed an analytical platform for high-throughput and comprehensive characterization of the human blood metabolome, greatly advancing the ability to establish metabolic phenotypes underlying carcinogenesis. Our approach leverages the latest advances in Orbitrap-based ultra-high resolution mass spectrometers (HRMS) for detection of both low- and high-concentration compounds in a single analysis, making possible measurement of over 100,000 chemical signals using 150 µL of serum. These measurements integrate biomarkers of exogenous chemicals from environmental and dietary sources with alterations in endogenous metabolic pathways, linking exposure to biological response and disease pathobiology. Thus, this approach is a critical advance over traditional metabolomic approaches focused on alterations in primary metabolism only.
To characterize exposures and biological response driving NHL and AML risk, our team will leverage untargeted, HRMS to profile small molecule signatures in serum to develop prognostic metabolomic risk scores underlying the primary hematologic cancers, including B-cell malignancies and AML. We propose to conduct a nested case-control study leveraging the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). As of the latest follow-up, there are 525 NHL eligible cases, including 205, 201 and 119 incident cases of DBCL, CLL and FL respectively, and 125 AML eligible cases. Our research team was recently funded (R01ES032831) to analyze prospectively collected serum samples from the European Prospective Investigation of Cancer (EPIC), including 2,170 individuals later diagnosed with NHL and 1,085 matched controls, and provides an independent validation of findings detected using PLCO. We are also planning to conduct parallel analyses of AML from several additional cohorts including EPIC and CLUE to provide an independent validation.
By using blood samples collected >2 years before disease manifestation, the proposed study will provide a comprehensive metabolome characterization of NHL and AML without early disease bias. We utilize an efficient study design that integrates B-cell and myeloid malignancies to maximize usage of PLCO resources. Our approach will be a critical first step needed to leverage our novel metabolomics platform to identify environmental determinants and biological processes underlying non-genetic risk factors of hematologic cancers. We are also requesting samples from a subset of participants with repeat blood collection (15 cases for each NHL subtype, all cases available for AML, and 120 shared controls) to investigate intraindividual variation over time, which is critical to evaluate given that exogenous exposure patterns and endogenous metabolic phenotypes can vary. This will be especially informative for AML, given that its etiological window is relatively proximate to diagnosis (i.e., 5-10 years) compared to many solid tumors, based on several models of AML including occupational benzene exposure (Linet et al, 2019, PMID30520970) and ionizing radiation and chemotherapy (McNerney et al, 2017, PMID28835720).

Aim 1: Perform comprehensive untargeted chemical analysis to characterize the blood metabolome and uncover pre-diagnostic environmental and metabolomic phenotypes of NHL and AML
Measures of the metabolome will be generated using pre-diagnostic blood samples collected from 650 cases and about 900 matched controls (controls will be shared across subtypes to the extent possible based on overlap in matching variables and selected so that there are 3 controls for the subtype with the largest number of cases) who remain cancer free and include:
a) High-resolution exposomics to profile exogenous compounds and their metabolites. Our team has pioneered the use of ultra-high-resolution Orbitrap mass spectrometry to detect over 1000 exogenous confirmed chemicals along with over 100,000 chemical signals that will be annotated by comparison to databases of exposure-related chemicals for untargeted screening of the exposome.
b) High-resolution metabolomics will be used to profile biological responses to exposures and disease by measuring endogenous molecules corresponding to most human metabolic pathways. This will include mapping to our library of over 1,500 compounds, and untargeted metabolomics to detect over 20,000 chemical signals from intermediate metabolism.

Aim 2: Identify metabolomic risk scores of primary NHL subtypes, AML, and time to diagnosis.
We will leverage advanced biostatistic and cross-omic methods developed for high-dimensional data analysis to establish metabolomic risk scores and disease metabolome trajectories for AML and NHL.
a) Identify and establish weights for key environmental and biological response measures defining relative disease risk for CLL, FL, DLBCL and AML.
b) Using time-to-diagnoses, evaluate influence of exposure and biological response timing for NHL and AML.

Aim 3: Perform integrated analysis of GWAS and the metabolome for G x M analysis of NHL.
a) We will use the top findings from the InterLymph GWAS of NHL (which includes both the PLCO Trial, CLUE,
and the EPIC cohort) for each NHL subtype to evaluate potential interactions with the top metabolomic and
environmental associations in the proposed project and the EPIC cohort.
b) We will perform an exploratory agnostic genome-wide by metabolome-wide search to identify interactive
effects between gene variants and metabolic alterations that influence NHL risk using data from the proposed
project and the EPIC cohort.