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Principal Investigator: Rosalie Griffin
Organization: MAYO CLINIC ROCHESTER
Fiscal Year: 2024
Award: $245,120
Funding agency: National Cancer Institute
ABSTRACT
Monoclonal B-cell lymphocytosis (MBL) is a precancerous state affecting 8-10 million adults with no
existing cancer control strategies. As a precursor to chronic lymphocytic leukemia (CLL), MBL is characterized
by the presence of monoclonal B-cell clones in the peripheral blood of otherwise healthy individuals. Early
evidence supports that MBL increases risk of adverse clinical outcomes, including progression to CLL requiring
therapy, development of other hematological and solid cancers, hospitalizations due to serious infections, and
reduced humoral immune response to vaccinations. However, the scale and diversity of MBL studies is
currently limited by the need for flow cytometric analysis of peripheral blood mononuclear cells to diagnose
MBL. These biospecimens are rarely available in large biobanking or cohort studies that could otherwise allow
more comprehensive and well-powered investigation of the causes and consequences of MBL, especially in
populations of diverse ancestries. We propose to overcome these limitations by developing and validating a
strategy to predict MBL status (Aim 1). In brief, we propose using existing genotyping array data, that is readily
available in many biobanks, to identify mosaic chromosomal alterations (mCAs), which affect large segments
of DNA and include gains, losses, and copy number-neutral loss of heterozygosity events. Recent work in
biobank studies has established mCAs as a potent risk factor for lymphoid malignancies but MBL is also a
major risk factor of lymphoid malignancies, and thus the question of how mCAs relate to MBL is unknown. We
have collected the largest cohort of individuals with MBL and genetic data, and in our preliminary analyses, we
found that autosomal mCAs are associated with risk of MBL with an odds ratio of 50.5 (95% confidence
interval 36.5-70.6, P = 1.34x10-152) with high discrimination. Aim 1 will validate these results, develop a
predictive model with other known risk factors for MBL, and then examine generalizability of the model to
individuals with strong family history of lymphoid malignancy and to individuals of African ancestry. We further
hypothesize that mCAs are drivers of B-cell clone growth. In Aim 2 we will be the first to quantify the incidence
of mCAs and the change in cell fraction of mCAs over time from serial peripheral blood samples that have also
been screened for MBL. We will then evaluate the relationship between mCAs and growth trajectories of B-cell
clones in individuals with MBL. Successful completion of these aims will unlock the ability to study MBL in the
largest cohorts in the world, enabling future studies of MBL at an unprecedented scale. As we continue to
improve understanding of the consequences of MBL, risk stratification of individuals with MBL will be essential.
This proposal will also begin to enable such stratification by characterizing MBL clonal trajectories. Together,
these aims will catalyze future studies of MBL to improve understanding of to inform etiologic factors and risk
stratification of this prevalent precancer for eventual cancer control.
Terms: <21+ years old><Aberrant Chromosome><Adult><Adult Human><Affect><African American><African ancestry><African descent><Afro American><Afroamerican><Age><Allelic Loss><B blood cells><B cell><B cells><B-Cell CLL><B-Cell Chronic Lymphocytic Leukemia><B-Cell Chronic Lymphogenous Leukemia><B-Cell Chronic Lymphoid Leukemia><B-Cell Lymphocytic Leukemia><B-Cells><B-Lymphocytes><B-Lymphocytic Leukemia><B-cell><Blood><Blood Reticuloendothelial System><Blood Sample><Blood specimen><Cancer Control><Cancer Control Science><Cancers><Causality><Cell Count><Cell Fraction><Cell Number><Chromosomal Aberrations><Chromosomal Abnormalities><Chromosomal Alterations><Chromosome Aberrations><Chromosome Alterations><Chromosome Anomalies><Chromosome abnormality><Chronic B-Lymphocytic Leukemia><Chronic Lymphatic Leukemia><Chronic Lymphoblastic Leukemia><Chronic Lymphocytic Leukemia><Chronic Lymphogenous Leukemia><Classification><Clinical><Clone Cells><Cognitive Discrimination><Cohort Studies><Concurrent Studies><Confidence Intervals><Copy Number Polymorphism><Cross-Product Ratio><Cytogenetic Aberrations><Cytogenetic Abnormalities><DNA><Data><Data Set><Deoxyribonucleic Acid><Development><Diagnosis><Discrimination><Etiology><European ancestry><Event><Family Medical History><Family Medical History Epidemiology><Family history of><Flow Cytofluorometries><Flow Cytofluorometry><Flow Cytometry><Flow Microfluorimetry><Flow Microfluorometry><Future><General Population><General Public><Generalized Growth><Genetic><Genome><Genotype><Goals><Growth><Hematology><Hematopoiesis><Hematopoietic Cellular Control Mechanisms><Hospital Admission><Hospitalization><Incidence><Individual><Infection><Investigation><Knowledge><Location><Loss of Heterozygosity><Lymphocytosis><Malignant Neoplasms><Malignant Tumor><Malignant lymphoid neoplasm><Modeling><Monitor><Odds Ratio><Outcome><PBMC><Pattern><Peripheral Blood Mononuclear Cell><Population Heterogeneity><Precancerous Conditions><Premalignant Condition><Premalignant State><Prevention><Public Health><Relative Odds><Risk><Risk Factors><Risk Marker><Risk Ratio><SNP array><SNP chip><Sampling><Solid><Stratification><Systematics><Time><Tissue Growth><Work><adulthood><adverse consequence><adverse outcome><ages><autosome><biobank><biorepository><blood cell formation><cancer risk><causation><chromosomal defect><chromosome defect><chronic lymphoid leukemia><cohort><computer based prediction><copy number variant><copy number variation><cost><developmental><disease causation><diverse populations><empowerment><flow cytophotometry><heterogeneous population><immune response to vaccination><immune response to vaccines><improved><lymphoid cancers><lymphoid malignancy><malignancy><model generalizability><mosaic><neoplasm/cancer><ontogeny><peripheral blood><phenome><population diversity><precancer><precancerous><precancerous state><predictive modeling><premalignant><risk predictor><risk predictors><risk stratification><screening><screenings><sex><single nucleotide polymorphism array><single nucleotide polymorphism chip><stratify risk><study population><vaccine associated immune response><vaccine immune response><vaccine immunogenicity><vaccine induced immune response>