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.

项目总结/摘要 浸润性小叶癌（ILC）是第二大最常见的乳腺癌，是最常见的乳腺癌。 在美国影响妇女的常见恶性肿瘤。虽然ILC具有独特的分子和临床特征， 但是，由于它的特点，它没有得到很好的研究，也没有具体的治疗策略。 对患有ILC的妇女的治疗是确定是否应该使用细胞毒性化疗。 目前可用的基因表达测定（例如Oncotype和Mammaprint测试）对大多数ILC进行分类， 肿瘤的分子“低风险”，这表明细胞毒性化疗将是无效的。然而，国际法委员会 与其他类型的乳腺癌相比，更有可能出现淋巴结受累的晚期， 使这些患者在临床上具有“高风险”。这种“临床高风险”状态促使患者使用化疗 与ILC，尽管不一致的结果，从分子测定。事实上，大多数淋巴结阳性的ILC患者 接受化疗，尽管没有数据表明对任何个体患者有益。有一个 需要改善患者选择，以便化疗仅用于将受益的患者 而其他人则可以免受其毒副作用的影响。与此同时，对于预测对以下药物反应不良的患者， 标准的化疗，我们需要个性化的方法，目标是独特的分子途径参与 在ILC。最近我们对ILC的理解有了一些进展，现在有几个小组已经确定了 ILC特异性基因特征在该组肿瘤中显示出显著的异质性。鉴于这一新 根据现有数据，我们现在可以开始将ILC特定工具纳入临床实践， ILC妇女的治疗策略。在本提案中，我将通过以下三个方面解决这一问题 接近。首先，我将评估一种新的ILC化疗反应性早期指标， 确定肿瘤是否有反应的能力。由于ILC患者数量相对较少， 在临床试验中，我将使用来自乳腺癌患者的12个组合数据集进行汇总分析 术前（新辅助）化疗。其次，我将利用最近发现的ILC- 特异性基因表达特征和I-SPY 2试验中可用的数据，以开发预测工具， 确定化疗反应者（小叶乳腺癌化疗的有效性和反应 [CLEAR] score）。最后，我将进行一项试点研究，测试一种新的靶向药物， I-SPY 2试验中的内分泌治疗，通过称为内分泌优化途径的新分支。这 该项目解决了一个重要的，相关的临床问题，利用新的数据集和分子特征， 以前可用的，重要的是，将使我能够在指导环境中发展技能和知识， 这将有助于我设计和进行针对ILC女性的前瞻性临床试验。