# Prognostic analysis and progression modeling of basal-like breast cancer using multi-region sequencing

> **NIH NIH R01** · STATE UNIVERSITY OF NEW YORK AT BUFFALO · 2024 · $595,029

## Abstract

Project Summary/Abstract
Breast cancer is the most common cancer in women worldwide, and the fifth most common cause of death
from cancer overall. As with many other cancers, breast cancer presents in a variety of forms and can be
broadly divided into four molecular subtypes, including luminal A, luminal B, HER2+ and basal. Among them,
basal cancer represents ~20% of primary breast tumors and is one of the most aggressive and deadly
subtypes. While significant efforts have been made, the biological process of how basal cancer progresses to a
malignant, life-threatening disease is not well understood, and the prognostication and treatment of basal
cancer remain major challenges. Specifically, there are currently no prognostic tests available that can assist
clinical management, and nearly all basal cancer patients are classified as having a high risk of recurrence.
Moreover, as the majority of basal tumors lack expression of estrogen receptor (ER), progesterone receptor
(PR) and HER2, there are presently no effective targeted treatment regimens available, and harsh,
indiscriminate chemotherapy is the only treatment option. Consequently, a significant number of basal cancer
patients are under- or over-treated. Built logically on our previous work, we propose a large-scale
interdisciplinary research plan, in which we will use multi-region sequencing and advanced computational
techniques to address some pressing issues and the aforementioned unmet clinical needs of basal breast
cancer. Specifically, we will perform molecular profiling of 300 primary basal tumors and 50 matched
metastatic tumors that we have identified from Mayo Clinic tissue banks. By using the obtained multi-region
sequencing tumor tissue data, we will derive a prognostic evaluation system for basal cancer through multiple
instance learning, and construct and validate a high-resolution progression model of basal cancer. We will also
perform a large-scale analysis on a range of molecular data to systematically search for genetic determinants
of basal cancer progression at both gene and pathway levels, which will provide a wealth of insights into
molecular mechanisms of tumorigenesis and enable us to identify potential therapeutic targets for basal
cancer. If successfully implemented, this work will significantly advance the basal cancer research, and pave
the way for applying similar strategies to study other deadly cancers.

## Key facts

- **NIH application ID:** 10864066
- **Project number:** 5R01CA269075-02
- **Recipient organization:** STATE UNIVERSITY OF NEW YORK AT BUFFALO
- **Principal Investigator:** Steve Goodison
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $595,029
- **Award type:** 5
- **Project period:** 2023-06-09 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10864066

## Citation

> US National Institutes of Health, RePORTER application 10864066, Prognostic analysis and progression modeling of basal-like breast cancer using multi-region sequencing (5R01CA269075-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10864066. Licensed CC0.

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