Prognostic significance of HER2 heterogeneity in early-stage and locally advanced HER2-positive breast cancer.
Abstract
e12595 Background: Breast cancer tumors often have intratumoral heterogeneity (ITH), which has been associated with therapeutic resistance. Tumors with high ITH show human epidermal growth factor receptor 2 (HER2) heterogeneity, impacting the effectiveness of HER2-targeted therapies. Our recent study identified HER2 ITH as an independent prognostic factor for poor outcomes in HER2-positive breast cancer. In this study, we investigated the association between HER2 ITH and resistance to Anti-HER2 Neoadjuvant Chemotherapy (NAC). Methods: The study included 97 patients of primary HER2-positive breast cancer treated with Anti-HER2 NAC. Breast tumor samples were obtained from vacuum-assisted breast biopsy before NAC. HER2 gene amplification was assessed by fluorescence in situ hybridization (FISH), and histograms of HER2 gene copy numbers were generated. Using Gaussian mixture model, the histogram data were analyzed and classified into two groups, high HER2 heterogeneity (HH) and low HER2 heterogeneity (LH). The relationship between HER2 ITH and treatment response was evaluated with the pathological complete response (pCR) rate. Results: Of 97 patients,18 (18.6%) were classified into the HH group, and 79 (81.4%) into the LH group. The pCR rate in the HH group was significantly lower at 33% (6/18) compared to 65% (51/79) in the LH group ( P = 0.01). Multivariate analysis of pathological parameters revealed that HER2 ITH was the second most significant predictor of pCR rate ( P = 0.07), following estrogen receptor status. Conclusions: The assessment of HER2 ITH may be valuable in predicting therapeutic outcomes in HER2-positive breast cancer. Our novel approach of HER2 ITH method using FISH histograms could potentially serve as a useful tool in predicting resistance to anti-HER2 NAC.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (14)
Takaaki Hatano
Department of Breast and Endocrine Surgery Graduate School of Medicine The University of Osaka 2‐2‐E10 Yamadaoka Suita Osaka 565–0871 Japan
Tomonori Tanei
Department of Breast and Endocrine Surgery Graduate School of Medicine The University of Osaka 2‐2‐E10 Yamadaoka Suita Osaka 565–0871 Japan
Shigeto Seno
Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, The University of Osaka
Yoshiaki Sota
Osaka University Graduate School of Medicine, Suita, Japan
Yuri Kitahara
Osaka University Graduate School of Medicine, Suita, Japan
Kaori Abe
Nanae Masunaga
Osaka University Graduate School of Medicine, Suita, Japan
Chieko Mishima
Osaka University Graduate School of Medicine, Suita, Japan
Masami Tsukabe
Osaka University Graduate School of Medicine, Suita, Japan
Tetsuhiro Yoshinami
Graduate School of Medicine, Osaka University, Osaka, Japan
Tomohiro Miyake
Osaka University Graduate School of Medicine, Suita, Japan
Masafumi Shimoda
Hideo Matsuda
Kenzo Shimazu
Department of Breast and Endocrine Surgery Graduate School of Medicine The University of Osaka 2‐2‐E10 Yamadaoka Suita Osaka 565–0871 Japan