Identifying responders to chemotherapy in invasive lobular carcinoma of the breast: development of a multivariable clinical prediction tool

点击翻译按钮获取中文摘要

Project Summary/Abstract Invasive lobular carcinoma (ILC) is the second most prevalent breast cancer, which is the most common malignancy affecting women in the United States. Although ILC has unique molecular and clinical features, it is not well-studied, and no specific therapeutic strategies exist for it. One of the major challenges in the treatment of women with ILC is determining whether cytotoxic chemotherapy should be utilized or not. Currently available gene expression assays (e.g. Oncotype and Mammaprint tests) classify the majority of ILC tumors as molecularly “low risk,” which suggests that cytotoxic chemotherapy will be ineffective. However, ILC is more likely than other types of breast cancer to present at advanced stages with lymph node involvement, making these patients clinically “high risk.” This “clinical high risk” status drives chemotherapy use in patients with ILC, despite discordant results from molecular assays. Indeed, the majority of node-positive ILC patients receive chemotherapy, despite the absence of data suggesting benefit for any individual patient. There is a huge need to improve patient selection, so that chemotherapy can be utilized only in patients who will benefit from it, while others can be spared its toxic side effects. In parallel, for patients with predicted poor response to standard chemotherapy, we need personalized approaches that target the unique molecular pathways involved in ILC. There have been recent advances in our understanding of ILC, and several groups have now identified ILC specific gene signatures that show significant heterogeneity within this group of tumors. Given this newly available data, we can now start incorporating ILC specific tools into clinical practice and develop tailored treatment strategies for women with ILC. In this proposal, I will address this via the following three approaches. First, I will evaluate a novel early indicator of chemotherapy responsiveness in ILC, improving our ability to determine whether a tumor has responded or not. Given the relatively small numbers of ILC patients in clinical trials, I will conduct a pooled analysis using 12 combined datasets from breast cancer patients treated with pre-operative (neoadjuvant) chemotherapy. Second, I will leverage the recent discovery of ILC- specific gene expression signatures and the data available in the I-SPY2 Trial to develop a predictive tool to identify chemotherapy responders (Chemotherapy in Lobular breast cancer Effectiveness and Response [CLEAR] score). Finally, I will conduct a pilot study testing a novel, targeted agent in combination with endocrine therapy in the I-SPY2 Trial, through a new arm termed the Endocrine Optimization Pathway. This project addresses an important, relevant clinical issue, utilizes new datasets and molecular signatures not previously available, and importantly, will allow me to develop skills and knowledge in a mentored setting that will facilitate my ability to design and conduct prospective clinical trials for women with ILC.