Abstract 2502: Identification of poor responders to trastuzumab-deruxtecan with a multi-modal HER2-status predictor
Authors: Nadhamuni Kaveri , Ahmed Talal , Carty Mark , Terdich Ben , Hensing Whitney L. , Taxter Timothy , Chao Calvin , Pelossof Raphael 
Published: March 2024

Abstract
Trastuzumab deruxtecan (TDXD) is approved for HER2 low or positive metastatic breast cancer. HER2-status is assessed through HER IHC and ERBB2 FISH assays. HER2-status has been shown to be correlated to RNA expression. This study aimed to assess if the addition of DNA to an RNA-based model can improve HER2-status prediction performance. Furthermore, to investigate the relationship between model score and outcomes for TDXD patients according to their overall survival (OS).
Training and test sets of breast cancer samples were collected for HER2 status prediction (n = 1275, n = 397 respectively). HER2 status was reported positive: 11%, 12%, low: 61%, 60%, negative: 28%, 29% for each set respectively. HER2 testing and NGS were performed on samples with the same collection date. A TDXD discovery cohort of 284 patients included patients who received TDXD after RNA/DNA collection and had at least a 30-day follow-up. Metastatic disease was reported for 98% of the TDXD cohort. Receptor status was HR+/HER2- 39%, HR-/HER2- 17%, HR+/HER2+ 16%, HR-/HER2+ 9%, unknown 19%, and HER2-status was negative 11%, low 42%, and positive 27%, unknown 20%. OS was measured from medication start date.
We trained a 12-gene linear model based on RNA expression and DNA copy number to predict HER2-positivity. The genes were selected by stepwise-selection on RNA and DNA features when predicting HER2-positivity using a random forest model. A baseline model consisting only of ERBB2 RNA expression was compared. Setting a HER2-positivity score threshold and allowing for an indeterminate group of 15% of the validation cohort, the RNA-DNA model achieved 91% PPA and 91% PPV in validation, whereas the RNA-only model achieved 83% PPA and 85% PPA. This indicates that the addition of DNA data improved the RNA-only HER2 predictor.
The Concordance index of the RNA-DNA model score and OS for TDXD was 0.64. Characterizing this relationship, we partitioned the TDXD cohort to three equal sized sub-cohorts (33 1/3%) ordered by model score: low, intermediate, and high. Median OS in months for groups was: low 13.6, intermediate 18.5, and high 20.4. High-group patients had significantly better OS on TDXD compared to the low-group (HR = 0.39, log-rank p-value &lt; 0.002). For patients with reported status, HER2-positivity rate in each group respectively was 6%, 16%, 85% (n=78), and HR-positivity in each group was 70%, 68%, 67% (n=156).
Together, these findings indicate that HER2 status prediction improved by adding DNA to an RNA base predictor, and the predicted score was positively correlated with OS for TDXD.
Citation Format: Kaveri Nadhamuni, Talal Ahmed, Mark Carty, Ben Terdich, Whitney L. Hensing, Timothy Taxter, Calvin Chao, Raphael Pelossof. Identification of poor responders to trastuzumab-deruxtecan with a multi-modal HER2-status predictor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2502.