Molecular Atlas Offers New Framework for Breast Cancer Risk and Treatment Research

Transcriptomic profiling can reveal gene-expression patterns that standard pathology may not fully capture, creating a need for molecular tools that better stratify tumors for precision oncology. Building on this approach, new findings show that a large transcriptomic atlas can uncover previously unrecognized breast cancer subtypes with distinct outcomes and treatment sensitivities.

Vanderbilt-Ingram Cancer Center generated a molecular map of breast cancer by integrating transcriptomic data from more than 7,600 tumors across 22 independent studies. The atlas is based on the tumor transcriptome, the complete set of RNA molecules produced by a tumor. It groups breast cancers into interconnected clusters that share molecular features, treatment responses, and clinical outcomes.

The researchers adapted computational approaches originally developed for single-cell genomics to address differences among datasets generated across studies, sequencing platforms, and analytical methods. The resulting map resembles an archipelago, with related tumor populations forming distinct molecular “islands.” The team also created a tool that can assign tumors to subtypes using standard bulk RNA sequencing data for future research studies and clinical trials.

The study, published Nov. 3 in Cell Reports Medicine, found substantial biological diversity within traditional breast cancer categories. Estrogen receptor-low tumors behaved more like estrogen receptor-negative disease, while subsets of human epidermal growth factor receptor 2 (HER2)-positive tumors appeared most dependent on HER2 signaling. The atlas also identified a hidden neuroendocrine form associated with worse outcomes after standard chemo-endocrine therapy, as well as an aggressive basal-luminal progenitor subtype of triple-negative breast cancer with potential therapeutic vulnerabilities.

The work involved Vanderbilt-Ingram Cancer Center, Vanderbilt Health, and the Department of Medicine at Vanderbilt Health. The researchers stated that prospective testing is needed to determine whether treatment decisions guided by transcriptional subtypes improve patient outcomes. They also indicated that the computational approach could be applied to transcriptomic, proteomic, and other large-scale molecular datasets across a wide range of diseases.

“The breast cancer atlas provides an unprecedented view of the disease’s molecular diversity and reveals distinct tumor populations associated with different clinical outcomes, biological characteristics and therapeutic vulnerabilities. By analyzing thousands of tumors together, we uncovered previously hidden forms of breast cancer that differ in prognosis, biology and treatment sensitivity,” said Brian Lehmann, PhD, Research Associate Professor of Medicine at Vanderbilt Health.

“The next critical step is prospective testing to determine whether treatment decisions guided by these transcriptional subtypes improve patient outcomes. Our goal is to match patients to therapies based on the biology of their tumors. This atlas provides both a road map and a practical framework for achieving that vision,” added Lehmann.

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Vanderbilt-Ingram Cancer Center