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: 10252892
• 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/10252892
• 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/antagonist; 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.

项目概要/摘要 这是向 Jennifer Caswell-Jin 博士申请 K08 奖的申请，她是一名讲师兼乳腺肿瘤学家 斯坦福大学致力于转化乳腺癌基因组研究。该奖项将 通过提供临床试验、生物标志物开发和 在 Christina Curtis 博士的专家指导下对多组学数据进行生物信息分析，计算和 癌症系统生物学家，以及乳腺癌临床试验师和转化研究员 George Sledge 博士。 拟议的研究重点关注转移性乳腺癌的主要公共卫生问题，估计 在美国，每年影响超过 150,000 名妇女并导致超过 40,000 人死亡。激素 受体阳性（HR+）乳腺癌是最常见的亚型。 HR+ 乳房的八种“综合”亚型 癌症已根据全基因组拷贝数和表达信息的整合来识别 在早期乳腺肿瘤中。四种综合亚型，合计占所有 HR+ 早期阶段的四分之一 乳腺癌，表现出极高的远处转移风险；这些亚型中的每一个都有一个特点 基因组的独特区域，表现出伴随的拷贝数增加和过度表达。研究在 该提案将首次研究整合亚型在转移后的表现，以及驱动因素 假设他们可以从个性化治疗方法中受益。目标 1 是调查 转移性 HR+ 乳腺癌中整合亚型的生物学和影响。我们将开发新方法 评估综合亚型，并了解它们是否在转移过程中发生变化，是否 与转移时间相关，以及它们对标准的反应长度是否不同 疗法。目标 2 是评估两种综合靶向治疗的新型组合的效果 转移性乳腺癌的亚型。我们将进行一项临床试验来测试靶向治疗方法 肿瘤被分类为四种高风险综合亚型中的两种之一。因为这两个亚型是 由涉及成纤维细胞生长因子受体配体（FGF3；FGF3）的基因组改变的焦点区域定义。 整合亚型 2) 或成纤维细胞生长因子受体 (FGFR1;整合亚型 6)，我们假设 这些肿瘤可能受益于 FGFR 抑制。该试验的参与者将接受标准内分泌 与 CDK4/6 抑制以及抑制成纤维细胞的研究药物相结合的疗法 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以评估 了解这种联合靶向治疗方法所发生的变化。圆满完成了 拟议的研究将为继续努力开发精准肿瘤学方法奠定基础 转移性 HR+ 乳腺癌，后续步骤将在 R01 拨款申请结束前提出 K08奖。