Integrative subtyping to improve therapeutic options for metastatic hormone receptor-positive breast cancer

综合亚型分型可改善转移性激素受体阳性乳腺癌的治疗选择

• 批准号: 10472731
• 负责人: Jennifer Caswell-Jin
• 金额: $ 22.55万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-03 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10472731
• 关键词: Affect; Applications Grants; Area; Automobile Driving; Award; Bioinformatics; Biological Assay; Biology; Biopsy; Breast; CCND1 gene; CDK4 gene; Cancer Etiology; Categories; Cessation of life; Characteristics; Clinical; Clinical Trials; DNA Sequence Alteration; Data; Data Set; Development; Diagnosis; Disease; Distant Metastasis; ERBB2 gene; Exhibits; FGF19 gene; FGF3 gene; FGFR1 gene; Fibroblast Growth Factor Receptors; Fluorescent in Situ Hybridization; Frequencies; Genes; Genome; Genomic approach; Genomics; Goals; Health; In Situ; Institution; Intelligence; Investigation; Knowledge; Lead; Learning; Length; Life; Ligands; Malignant Neoplasms; Mammary Neoplasms; Mentorship; Metastatic breast cancer; Methods; Molecular; Multiomic Data; Neoplasm Metastasis; Oncologist; Participant; Pathway interactions; Patients; Phase Ib Clinical Trial; Plasma; Proteomics; Public Health; Receptor Inhibition; Recurrence; Research; Resistance; Role; Safety; Sampling; Signal Pathway; Specimen; System; Testing; The Cancer Genome Atlas; Therapeutic; Time; Tissue Sample; Training; Tumor Markers; Tumor Tissue; Tumor stage; United States; Universities; Woman; base; biomarker development; breast cancer genomics; cancer subtypes; career; career development; cohort; design; effective therapy; genetic variant; genome-wide; high risk; hormone receptor-positive; hormone therapy; improved; improved outcome; inhibitor; insight; instructor; machine learning algorithm; machine learning method; malignant breast neoplasm; novel; novel strategies; novel therapeutic intervention; overexpression; patient subsets; personalized approach; personalized therapeutic; precision oncology; resistance mechanism; response; targeted treatment; transcriptome sequencing; translational scientist; treatment response; tumor; tumor-immune system interactions; whole genome

Project Summary/Abstract This is an application for a K08 Award to Dr Jennifer Caswell-Jin, an Instructor and breast oncologist at Stanford University establishing a career in translational breast cancer genomic research. The Award will support her career development by providing training in clinical trials, biomarker development, and bioinformatic analysis of multi-omic data under the expert mentorship of Dr Christina Curtis, computational and cancer systems biologist, and Dr George Sledge, breast cancer clinical trialist and translational researcher. The proposed research focuses on the major public health problem of metastatic breast cancer, estimated to affect over 150,000 women and to cause over 40,000 deaths each year in the United States. Hormone receptor-positive (HR+) breast cancer is the most common subtype. Eight “integrative” subtypes of HR+ breast cancer have been identified based on the integration of genome-wide copy number and expression information in early-stage breast tumors. Four integrative subtypes, together comprising one-quarter of all HR+ early-stage breast cancers, exhibit a very high risk of distant metastasis; each of these subtypes is characterized by a distinct area of the genome that exhibits concomitant copy number gain and overexpression. The studies in this proposal will examine for the first time how integrative subtypes behave after metastasis, with the driving hypothesis that they may derive benefit from personalized therapeutic approaches. Aim 1 is to investigate the biology and impact of integrative subtypes in metastatic HR+ breast cancer. We will develop novel approaches to assess integrative subtypes and will learn whether they change across metastasis, whether they are associated with timing of metastasis, and whether they have differential lengths of response to standard therapies. Aim 2 is to evaluate the effects of a novel combination of targeted therapy in two integrative subtypes of metastatic breast cancer. We will perform a clinical trial that tests a targeted therapeutic approach in tumors classifying as one of two of the four high-risk integrative subtypes. Because these two subtypes are defined by focal areas of genomic alteration involving either the fibroblast growth factor receptor ligand (FGF3; integrative subtype 2) or the fibroblast growth factor receptor (FGFR1; integrative subtype 6), we hypothesize that these tumors may benefit from FGFR inhibition. Participants in this trial will receive standard endocrine therapy in combination with CDK4/6 inhibition, as well as an investigational agent that inhibits the fibroblast growth factor receptor pathway. We will also perform tumor biopsies before and during treatment to evaluate for changes that occur with this combination targeted therapy approach. Successful completion of the proposed studies will lay the groundwork for continued efforts to develop a precision oncology approach for metastatic HR+ breast cancer, with next steps to be proposed in an R01 grant application before the end of the K08 Award.

项目总结/摘要 这是K 08奖的申请，Jennifer Caswell-Jin博士是一名讲师和乳腺肿瘤学家， 斯坦福大学建立了转化乳腺癌基因组研究的职业生涯。该奖项将 通过提供临床试验、生物标志物开发方面的培训， 在Christina Curtis博士的专家指导下，对多组学数据进行生物信息学分析， 癌症系统生物学家和乔治斯莱奇博士，乳腺癌临床试验和转化研究员。 拟议的研究集中在转移性乳腺癌的主要公共卫生问题上，估计 在美国，每年有超过150，000名妇女受到影响，并导致超过40，000人死亡。激素 受体阳性（HR+）乳腺癌是最常见的亚型。HR+乳腺癌的八种“综合”亚型 已经基于全基因组拷贝数和表达信息的整合来鉴定癌症 在早期乳腺肿瘤中。四种整合亚型，共占所有HR+早期 乳腺癌表现出非常高的远处转移风险;这些亚型中的每一种的特征都是 基因组的不同区域，表现出伴随的拷贝数增加和过表达。中的研究 这项提案将首次研究整合亚型在转移后的行为， 假设他们可能从个性化治疗方法中获益。目的1是研究 转移性HR+乳腺癌中整合亚型的生物学和影响。我们将开发新的方法 评估整合亚型，并将了解它们是否在转移过程中发生变化， 与转移的时间有关，以及它们是否对标准的 治疗目的2是评价一种新的靶向治疗组合在两种综合性肿瘤中的作用， 转移性乳腺癌的亚型。我们将进行一项临床试验， 在肿瘤分类为四个高风险综合亚型中的两个之一。因为这两种亚型 由涉及成纤维细胞生长因子受体配体（FGF 3; 整合亚型2）或成纤维细胞生长因子受体（FGFR 1;整合亚型6），我们假设 这些肿瘤可能受益于FGFR抑制。这项试验的参与者将接受标准的内分泌治疗， 联合CDK 4/6抑制治疗，以及抑制成纤维细胞的研究药物 生长因子受体途径我们还将在治疗前和治疗期间进行肿瘤活检， 了解这种联合靶向治疗方法发生的变化。成功完成 拟议的研究将为继续努力开发精确的肿瘤学方法奠定基础， 转移性HR+乳腺癌，在R 01补助金申请结束前提出下一步措施。 K 08奖。