Abstract

HER2 amplification is a well-established driver of breast cancer and serves as the primary basis for clinical classification and treatment selection. However, this framework assumes that HER2-driven tumor biology is defined solely by ERBB2 amplification or overexpression. The goal of this study was to evaluate whether HER2-associated signaling is represented as a pathway-level activation state and whether this framework could help identify tumors with clinically relevant HER2 activity beyond current routine classification methods. HER2-associated transcriptional programs were identified across three independent breast cancer cohorts, resulting in conserved gene sets (P76 and P25). Amplification-independent HER2 activation was assessed using the HER2 Activation Response Predictive Signature (HARPS), derived from the I-SPY2 clinical trial, and evaluated across proteomic datasets and extended to gynecologic cancers. HER2- positive tumors showed consistent transcriptional differences, including many non-amplicon features. A subset of HER2 low or HER2 negative tumors demonstrated similar transcriptional patterns, indicating activation without amplification. These signals were partially preserved at the protein level and were largely independent of tumor microenvironment effects. Pathway enrichment analysis revealed that amplification-dependent and amplification-independent HER2 signaling converge on shared downstream biological programs enriched for immune signaling and cellular migration. Extension to gynecologic cancers showed limited and context-dependent preservation with stronger evidence in endometrial carcinoma compared to ovarian. Overall, these findings suggest that HER2-associated tumor biology extends beyond ERBB2 amplification and can be captured as a pathway-level state. This framework may improve the identification of tumors with clinically relevant HER2 signaling that are not currently recognized and could support future efforts to expand HER2-targeted therapeutic strategies.

Library of Congress Subject Headings

Breast--Cancer--Diagnosis; Ovaries--Cancer--Diagnosis; HER-2 protein; Proteomics; Genomics

Publication Date

4-2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Bioinformatics (MS)

Department, Program, or Center

Thomas H. Gosnell School of Life Sciences

College

College of Science

Advisor

Nicholas Bateman

Advisor/Committee Member

Feng Cui

Advisor/Committee Member

Girish Kumar

Campus

RIT – Main Campus

Plan Codes

BIOINFO-MS

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