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

确定乳腺癌浸润性小叶癌化疗的反应者：开发多变量临床预测工具

• 批准号: 10468944
• 负责人: Rita Mukhtar
• 金额: $ 25.54万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10468944
• 关键词: Address; Affect; BCL2 gene; Biological Assay; Biological Markers; Breast Cancer Patient; Cancer Burden; Cessation of life; Characteristics; Clinical; Clinical Investigator; Clinical Research; Clinical Trials; Cytotoxic Chemotherapy; Data; Data Set; Detection; Development; Diagnosis; Disease; Disease-Free Survival; Drug Combinations; Duct (organ) structure; E-Cadherin; Effectiveness; Endocrine; Estrogen receptor positive; Evaluation Reports; Future; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Goals; Heterogeneity; Histopathology; Image; In complete remission; Indolent; Institution; Investigation; Knowledge; Lead; Learning; Lobular; Lobular Carcinoma; Lymph Node Involvement; Machine Learning; Malignant Neoplasms; Measures; Mentors; Mentorship; Methods; Molecular; Molecular Profiling; Morbidity - disease rate; Neoadjuvant Therapy; Operative Surgical Procedures; Outcome; Pathologic; Pathway interactions; Patient Care; Patient Selection; Patients; Pharmacologic Substance; Pilot Projects; Positive Lymph Node; Protocols documentation; Randomized; Recurrence; Research; Residual Cancers; Residual state; Risk; Running; Safety; Statistical Methods; Testing; Therapeutic; Time; Training; United States; Woman; Work; arm; base; biomarker development; cancer clinical trial; career; chemotherapy; clinical practice; clinically relevant; cohort; design; diagnostic strategy; experience; genetic signature; high risk; hormone receptor-positive; hormone therapy; imaging biomarker; improved; indexing; individual patient; individualized medicine; infiltrating duct carcinoma; inhibitor; malignant breast neoplasm; novel; oncotype; patient oriented; personalized approach; pilot trial; predicting response; predictive modeling; predictive tools; programs; prospective; protein expression; radiomics; randomized trial; responders and non-responders; response; side effect; skills; specific biomarkers; standard care; targeted agent; targeted treatment; tissue biomarkers; tool; treatment choice; treatment strategy; tumor

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.

项目摘要/摘要 浸润性小叶癌（ILC）是第二大流行的乳腺癌，是最普遍的乳腺癌 在美国影响妇女的常见恶性肿瘤。尽管ILC具有独特的分子和临床 特征，它不是很好的研究，也没有特定的治疗策略。主要挑战之一 ILC女性的治疗方法是确定是否应使用细胞毒性化疗。 当前可用的基因表达测定（例如Oncotype和Mammaprint测试）对大多数ILC进行了分类 肿瘤是分子“低风险”，这表明细胞毒性化疗将无效。但是，ILC 比其他类型的乳腺癌更有可能在淋巴结受累的晚期阶段出现， 使这些患者在临床上“高风险”。这种“临床高风险”状态可驱动患者化学疗法的使用 使用ILC，dospite不一致是由于分子测定而导致的。确实，大多数淋巴结阳性ILC患者 接受化学疗法，没有数据为任何患者提供建议。有一个 改善患者选择的巨大需求，以便将化学疗法仅用于受益的患者 从中，其他人可以免除其有毒的副作用。同时，对于预测反应不佳的患者 标准化疗，我们需要针对涉及独特分子途径的个性化方法 在ILC中。我们对ILC的理解最近已经取得了进步，现在已经确定了几个小组 ILC特异性基因标志，在这组肿瘤中显示出显着的异质性。给出了新的 可用数据，我们现在可以开始将ILC特定工具编码为临床实践，并开发量身定制的 ILC女性的治疗策略。在此提案中，我将通过以下三个 方法。首先，我将评估ILC中化学疗法反应能力的新型早期指标，从而改善我们的 确定肿瘤是否反应的能力。考虑到相对数量的ILC患者 在临床试验中，我将使用来自乳腺癌患者的12个合并数据集进行合并分析 用术前（新辅助）化学疗法治疗。其次，我将利用最近发现的ILC- 特定的基因表达特征和I-SPY2试验中可用的数据，以开发一种预测工具 鉴定化学疗法反应者（小叶乳腺癌有效性和反应的化学疗法 [清除]得分）。最后，我将进行一项试验研究，以测试一种新颖的有针对性药物，并结合使用 在I-SPY2试验中，内分泌疗法通过一个新手臂称为内分泌优化途径。这 项目解决了一个重要的相关临床问题，它利用了新的数据集和分子特征 以前可用的，重要的是，我可以在设定方面发展技能和知识 将有助于我为ILC女性设计和进行前瞻性临床试验的能力。