# Heterogeneity of tumor transcriptomics in underrepresented populations

> **NIH NIH P30** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $100,000

## Abstract

ABSTRACT
This application is being submitted in response to Notice of Special Interest (NOSI) NOT-CA-24-032.
Certain populations have been traditionally underrepresented in cancer research and therefore the benefits of
cancer discoveries are more limited for these populations. Understanding informative variability (heterogeneity)
across individuals is the key to prediction, and therefore to address underrepresentation it is critical to better
understand heterogeneity within underrepresented groups. Cancers occur due to dysfunctional biological
processes. We hypothesize that many important sources of within-group heterogeneity will influence gene
function and biology and will be observed in patterns of gene expression (the transcriptome). Transcriptomes
sum the biological effects of lifestyle, genetics and environmental exposures on gene expression and provide a
molecular platform well-suited to explore tumor heterogeneities that may originate from many different factors.
Further, tumor expression has been shown to have utility for predicting clinical risk and outcomes. Hence,
transcriptomes provide an attractive way to understand both the origins and consequences of tumor
heterogeneity. We will perform characterization of tumor transcriptomes to understand heterogeneity
within three underrepresented populations: cancer patients living in rural areas, those of lower socio-
economic status, and those of Hispanic ethnicity. Deep multi-dimensional characterization will be determined
using the novel SPECTRA method developed by the Camp lab. Multiple independent quantitative
transcriptome variables will be derived that describe gene expression variability within each group. A common
limitation of molecular tumor studies is a paucity of companion epidemiologic data, necessary to identify
potential avenues for intervention and modification of risk. In addition to data collected in the parent study, we
will use record-linkage to the unique and powerful Utah Population Database (UPDB) to add individual- and
area-level epidemiologic variables. For each of the three focus groups, we will construct rich datasets that will
include demographic and lifestyle characteristics, clinical and prognostic variables, sociodemographic metrics,
measures of comorbidity, healthcare access and environmental exposures. We will identify associations
between state-of-the-art transcriptome variables and these elements to determine possible causes and
consequences of tumor heterogeneities observed within each group. Findings from this project will narrow the
knowledge gap by increasing our understanding of within-group tumor heterogeneities and has the potential to
provide new avenues and opportunities to advance equity in cancer prevention, control and outcomes in these
underrepresented populations.

## Key facts

- **NIH application ID:** 11081244
- **Project number:** 3P30CA042014-35S5
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** CORNELIA M ULRICH
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $100,000
- **Award type:** 3
- **Project period:** 1997-05-09 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11081244

## Citation

> US National Institutes of Health, RePORTER application 11081244, Heterogeneity of tumor transcriptomics in underrepresented populations (3P30CA042014-35S5). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11081244. Licensed CC0.

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