Genomic Features Predictive of Response to Trastuzumab-Containing Therapy

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Genomic Features Predictive of Response to Trastuzumab-Containing Therapy
Genomic Features Predictive of Response to Trastuzumab-Containing Therapy

SAN ANTONIO –  Tumor genetics, tumor RNA subtype, and the tumor microenvironment were independently associated with response to trastuzumab-containing therapies in patients with HER2-positive breast cancer, a study presented at the 2016 San Antonio Breast Cancer Symposium (SABCS) has shown.1

CALGB 40601 (ClinicalTrials.gov Identifier: NCT00770809) showed that neoadjuvant treatment with paclitaxel, trastuzumab, and lapatinib was associated with a nonsignificant increase in pathologic complete rates compared with standard weekly paclitaxel plus trastuzumab in women with HER2-positive breast cancer.

“RNA profiling and mutational analyses in CALGB 40601 found significant impact on pathologic complete response rates from tumor and microenvironmental features,” said Maki Tanioka, MD, PhD, Lineberger Comprehensive Cancer Center, Chapel Hill, North Carolina. “Therefore, integrated analysis across platforms is needed to better understand the roles of these different factors with respect to response to HER2-targeted therapies.”

For the study, researchers performed comprehensive genomic analyses on pathologic complete response rate by integrating clinicopathologic information with somatic mutation status, 422 segment-level DNA Copy Number Alterations (CNAs), and 510 gene expression signatures using mRNAseq and DNA exome sequencing from 213 pretreatment tumors.

After excluding 48 samples from the trastuzumab plus lapatinib arm, which was closed early, and 4 normal-like tumors, results showed that clinical estrogen/progesterone receptor status and the PAM50 intrinsic subtype were significantly associated with pathologic complete response; however, treatment arm and disease stage were not.

In an Elastic Net analysis, researchers found that tumor type (HER2-enriched vs luminal), tumor genetics (mutation, amplification, deletion), and the microenvironment (immune cells) were each independent predictors of response.

“Integrated Elastic Net models could be used to develop valuable biomarkers,” said Dr Tanioka. “To accomplish this goal, we could use all 161 samples as a training set, and then apply this model onto the test data set(s). The test sets will require both DNA exome and RNA sequencing data, and we are actively looking for such tests.”

Results further identified chromosome 6p gain (MAPK14) as a predictor of sensitivity, and 11q (CBL) and 22q loss as predictors of resistance to trastuzumab-paclitaxel regimens, but experimental validation is needed to confirm these findings.

Reference

1. Tanioka M, Fan C, Carey LA, et al. Integrated analysis of multidimensional genomic data on CALGB 40601 (Alliance), a randomized neoadjuvant phase III trial of weekly paclitaxel (T) and trastuzumab (H) with or without lapatinib (L) for HER2-positive breast cancer. Paper presented at: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, TX.

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