Abstract PO3-14-05: Integration of metabolomics and transcriptomics to Reveal Potential Biomarkers Associated with Treatment Response of Neoadjuvant Therapy in HER2+ Breast Cancer

Abstract Background: Neoadjuvant therapy (NAT) has become the standard treatment for early human epidermal growth factor receptor 2 positive (HER2+) breast cancer. For patients with HER2+ breast cancer, achieving a pathologic complete response (pCR) is highly indicative of their prognosis. However, not all HER2+ breast cancer patients could benefit from the NAT, about 40%-50% patients could not achieve pCR at surgery, even if they used the present standard neoadjuvant regime of TCbHP (taxane, carboplatin, trastuzumab and pertuzumab). This study was conducted to explore potential indicators associated with neoadjuvant efficacy of TCbHP in HER2+ breast cancer. Methods: Consecutive HER2+ breast cancer patients, who received and completed NAT with TCbHP regime and subsequent surgery at Chongqing University Cancer Hospital were prospectively enrolled. LC-MS and GC-MS platform-based untargeted metabolomics were performed to determine the metabolic profiles of plasma samples from these patients at different time points during treatment period. Random forest (RF) was used to establish predictive models based on pre-therapeutic metabolic traits. The potential monitors for the treatment response were obtained by time series analysis. Transcriptome analysis was performed in available samples to identify differentially expressed genes (DEGs) before treatment. qRT-pCR was used to detect DEGs in tastuzumab-sensitive and -resistant cell lines. Metabolic and transcriptomic data were integrated to explore substantially altered pathways that might be responsible for drug resistance. Results: From July 20, 2020 to May 28, 2021, a total of 40 HER2+ breast cancer patients with 120 plasma samples were eligible and recruited for this study. Of whom 21 (52.5%) patients achieved pCR and 19 (47.5%) achieved non-pCR, there are no significant difference in baseline clinicopathological features between pCR and non-pCR patients. There were significant differences in plasma metabolic profiles between non-pCR and pCR groups before and during treatment. A total of 100 differential metabolites were identified between pCR and non-pCR patients at pre-therapeutic period, which were markedly enriched in 40 metabolic pathways. Four key metabolites sophorose, N-(2-acetamido)iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid were selected by RF analysis. The AUC value to discriminate pCR and non-PCR group to NAT of the single potential metabolite or combined panel of these metabolites were more than 0.910. 18 metabolites exhibit a potential for monitoring efficacy. Among 163 DEGs identified by RNA-seq, some genes might associate with trastuzumab resistance detected by qRT-PCR in cell lines. 39 altered pathways were found abnormally expressed at both the transcriptional and metabolic levels, including ABC transporters, protein digestion and absorption, mineral absorption, et al. Conclusion: By metabolomics analysis, we have both offered a road map of the molecular alterations underlying NAT of TCbHP regime in HER2+ breast cancer and a preliminary analysis of a unique metabolic signature that might be used to distinguish non-pCR from pCR patients. Metabolomics integrated with transcriptomics analysis could assist for gaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients. Citation Format: Ningning Zhang, Yuxin Huang, Guanwen Wang, Yimei Xiang, Zhouhong Jing, Junjie Zeng, Feng Yu, Xianjun Pan, Wenqi Zhou, Xiaohua Zeng. Integration of metabolomics and transcriptomics to Reveal Potential Biomarkers Associated with Treatment Response of Neoadjuvant Therapy in HER2+ Breast Cancer abstract. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-14-05.