The Pan-Tumor Landscape of Gene Amplifications and Copy Number Amplification Ratio for Established and Emerging Clinical Targets
Year: 2026
Type: article
Study design: Observational Study
Abstract: PURPOSE: Gene copy number (CN) amplifications and protein overexpression are common drug targets, and detection relies on various methodologies, including next-generation sequencing-based CN, immunohistochemistry (IHC), and in situ hybridization (ISH). We investigated the pan-tumor landscape of amplifications and developed AmpRatio, a novel method of CN quantitation. EXPERIMENTAL DESIGN: Pan-tumor tissue (N = 486,340) and liquid (N = 85,635) samples underwent hybrid capture-based comprehensive genomic profiling. A genome-wide CN model for each sample was generated to estimate the purity, ploidy, and segment-level CN. AmpRatio was calculated by dividing gene CN/sample ploidy. A US-based deidentified clinicogenomic database was utilized to assess the relationship between ERBB2 AmpRatio and HER2 IHC/FISH and outcomes on anti-HER2 therapies. RESULTS: Amplifications with varying degrees of gain were reported in 38.6% of pan-tumor tissue samples, most frequently MYC (5.6%), 11q13 (5.2%), ERBB2 (5.2%), and CCNE1 (3.2%). ERBB2 AmpRatio was associated with HER2 positivity by IHC/FISH in gastroesophageal [overall percent agreement (OPA) 90%] and breast (OPA 95%) cancers. Among patients treated with anti-HER2 therapies, ERBB2 AmpRatio significantly stratified outcomes within the ERBB2-amplified and IHC-defined HER2+ and HER2-low/ultralow populations. High concordance (sensitivity 88%) of amplification detection in liquid biopsy versus tissue was associated with higher AmpRatio and ctDNA tumor fraction ≥20%. CONCLUSIONS: CN amplifications are prevalent and diverse biomarkers, and AmpRatio is variable across genes and tumor types. ERBB2 AmpRatio is associated with outcomes to HER2-directed therapies and may have utility alongside IHC for clinical decision-making. With the increasing number of therapies targeting amplifications/overexpression, it will be important to define harmonized methods for CN quantification for optimal patient selection.
Source: Clinical Cancer Research
Authors: Jessica K. Lee, Julia C.F. Quintanilha, Kuei-Ting Chen, Bernard Fendler, Candice Francheska B. Tambaoan, Ryon Graf, Nicole Odzer, Lajos Pusztai, Maryam Lustberg, Harshabad Singh, Matthew Strickland, Tess A. O’Meara, Sara M. Tolaney, Timothy A. Yap, Jeffrey Ross, Amaya Gasco Hernandez, Brennan Decker, Richard S.P. Huang, Samuel J. Klempner, Ethan S. Sokol, Alexa B. Schrock
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: hybrid
Funder: Foundation Medicine
OpenAlex ID: W7140117746
