# Subtyping Bladder Cancer: A Multi-omic, Exposure-informed, Genealogical Approach (MErGE)

> **NIH NIH K07** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2021 · $85,561

## Abstract

This application is submitted in response to Notice of Special Interest (NOSI) NOT-CA-21-009 as an
Administrative Supplement to K07 CA230150-03. The goal of Dr. Heidi Hanson’s NCI K07 award is to launch
an independent cancer research program focused on improving precision strategies of cancer screening and
treatment by integrating genetic, genomic and environmental factors. Pertinent to this Supplement are
Research Aim 1: Methodological development of novel multi-omic methods, and Career Development Aim 3:
Develop hands-on training in genomic and epigenetic profiling of tumor samples. Currently, her K07 allows her
to develop a unique set of skills to improve modeling with transcriptomics in epidemiology. This Supplement
would afford her the opportunity to enhance those skills to include translation of the same methods toward
clinical interventions. Specifically, it will enhance her career development to include hands-on experience
translating her transcriptome methods to the field of pre-clinical models. Her new transcriptome SPECTRA
method will concurrently provide potential to advance patient derived xenograph organoid (PDxO) prediction
modeling and biomarker development. The project and experience gained will significantly expand the
research horizons offered by her NCI K07 and the results gained will be directly relevant to the goals of
PDXNet.
SPECTRA is novel transcriptome approach to characterize tissue expression using multiple, independent,
quantitative variables, or spectra. Dr. Hanson developed the strategy as part of her K07 hands-on training with
Dr. Camp. Spectra variables provide a deep dive into complex transcriptome data and show great promise in
epidemiology applications. As a novel omic approach, the strategy has excellent potential to enhance
incorporation of transcriptome data in other fields, too. In this Supplement, we will: 1) Establish transcriptome
spectra for breast tumors using TCGA RNA sequencing data; 2) Apply these quantitative variables to the
PDXNet tumors at the Welm lab; and 3) Utilize the spectra variables to build prediction models, classifiers and
biomarkers for drug response in PDxO and successful PDX engraftment (an indicator for tumor
aggressiveness). New prediction models will uncover drugs and biomarkers for confirmation in vivo in PDX
models. Biomarkers provide for patient identification for new clinical trials. Integration of the SPECTRA strategy
into preclinical modeling has the potential to provide a new bridge to translate successful drug response
findings into prospective clinical trials: a major unmet need and of great interest to PDXNet and NCI.

## Key facts

- **NIH application ID:** 10327452
- **Project number:** 3K07CA230150-04S1
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** HEIDI Anne HANSON
- **Activity code:** K07 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $85,561
- **Award type:** 3
- **Project period:** 2018-07-06 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10327452

## Citation

> US National Institutes of Health, RePORTER application 10327452, Subtyping Bladder Cancer: A Multi-omic, Exposure-informed, Genealogical Approach (MErGE) (3K07CA230150-04S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10327452. Licensed CC0.

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