Integrative statistical models for TNBC biomarker discovery

TNBC 生物标志物发现的综合统计模型

• 批准号: 9314546
• 负责人: Xi Steven Chen
• 金额: $ 35.31万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-12 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9314546
• 关键词: Address; Algorithms; Alkylating Agents; Androgen Receptor; Anthracyclines; Biological Markers; Biology; Cancer Patient; Cancer cell line; Categories; Cell Line; Chemotherapy-Oncologic Procedure; Clinical; Cluster Analysis; Collection; Computer software; Data; Data Analyses; Data Set; Decision Trees; Disease; Distant; ERBB2 gene; Estrogen Receptors; Estrogen receptor positive; FDA approved; Frequencies; Gene Chips; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genomic approach; Goals; Heterogeneity; In complete remission; Lead; Mesenchymal; Meta-Analysis; Modeling; Molecular; Molecular Profiling; Mutation; Neoadjuvant Therapy; Oncogenic; Ontology; Operative Surgical Procedures; Pathologic; Patients; Pharmaceutical Preparations; Probability; Progesterone Receptors; Recurrence; Regimen; Reproducibility; Residual Tumors; Residual state; Resistance; Salts; Sampling; Statistical Models; Time; Translating; Woman; actionable mutation; base; biomarker discovery; cancer subtypes; chemotherapy; experience; falls; forest; genetic signature; genomic data; immunoregulation; innovation; mRNA Differential Displays; malignant breast neoplasm; new therapeutic target; novel; novel marker; outcome forecast; personalized medicine; pre-clinical; response; specific biomarkers; stem; targeted biomarker; targeted treatment; taxane; tool; transcriptome sequencing; triple-negative invasive breast carcinoma; tumor

PROJECT SUMMARY/ABSTRACT The “triple negative breast cancer” (TNBC), refers to a heterogeneous collection of the tumors that lack expression of the estrogen receptor (ER), progesterone receptor (PR), and HER2 amplification. Unlike, ER- positive and HER2-amplified breast cancers; the lack of high frequency oncogenic driver mutations in TNBC has limited treatment options for women with the disease. However, TNBCs have higher rates of clinical response to pre-surgical (neo-adjuvant) chemotherapy, despite the lack of targeted therapy. Despite better responses to chemotherapy, TNBC patients still have a higher rate of distant recurrence and a poorer prognosis than women with other breast cancer subtypes. TNBC patients who experience a pathologic complete response (pCR) to neoadjuvant chemotherapy have significant improvements in both disease-free and overall survival compared with patients with residual invasive disease. In contrast, those patients with residual disease have a much poorer prognosis and are 6 times more likely to have recurrence and 12 times more likely to die. While 30% of patients with TNBC benefit from neoadjuvant chemotherapy, currently there is no effective way to identify those TNBC patients that would benefit most. TNBC's heterogeneous response to chemotherapy suggests that different TNBC subtypes may exist and are associated drug responses. We recently developed a novel gene expression signature with 2188 genes based on a new algorithm to classify TNBCs into six subtypes and implemented the algorithm in the software “TNBCtype”. Our study showed that each TNBC subtype displays a unique biology. Furthermore, we identified representative TNBC cell line models for these subtypes that display differential sensitivity to targeted and chemotherapy. Therefore, to translate our pre-clinical results, there is a critical need to develop new strategies to develop a refined, reproducible, robust and clinically useful subtyping tool to identify TNBC patients most likely to benefit from neoadjuvant chemotherapy, and discover the new biomarkers for targeted treatments in patients that are resistant to chemotherapy. We propose the following specific aims to address these challenges: (1) develop and validate a robust TNBC subtyping model; (2) identify TNBC subtype specific chemotherapy response gene signatures; (3) discover TNBC chemotherapy resistant biomarkers by integrative genomic approach.

项目总结/摘要 “三阴性乳腺癌”（TNBC）是指缺乏免疫原性的肿瘤的异质性集合。 雌激素受体（ER）、孕激素受体（PR）的表达和HER 2扩增。不像，呃- 阳性和HER 2扩增乳腺癌; TNBC中缺乏高频致癌驱动突变 对患有这种疾病的妇女来说，治疗选择有限。然而，TNBC具有更高的临床 对术前（新辅助）化疗的反应，尽管缺乏靶向治疗。尽管更好 尽管TNBC患者对化疗有反应，但其远处复发率仍较高， 与其他乳腺癌亚型相比， 对新辅助化疗有病理完全缓解（pCR）的TNBC患者， 与有残留癌细胞的患者相比， 侵袭性疾病相反，那些有残留病变的患者预后差得多， 复发的可能性是正常人的1倍，死亡的可能性是正常人的12倍。虽然30%的TNBC患者受益 从新辅助化疗，目前还没有有效的方法来确定那些TNBC患者， 受益最多。 TNBC对化疗的异质性反应表明可能存在不同的TNBC亚型， 与药物反应有关。我们最近开发了一种新的基因表达标签， 基于一种新的算法将TNBC分为六种亚型，并在软件中实现了该算法 “TNBC类型”。我们的研究表明，每个TNBC亚型都显示出独特的生物学。此外，我们发现 这些亚型的代表性TNBC细胞系模型显示出对靶向的和靶向的TNBC细胞系的不同敏感性， 化疗 因此，为了转化我们的临床前结果，迫切需要开发新的策略来开发 一种精细、可重复、稳健且临床上有用的亚型分型工具，用于识别最有可能受益的TNBC患者 从新辅助化疗，并发现新的生物标志物的靶向治疗的患者， 对化疗有抵抗力我们提出以下具体目标来应对这些挑战：（1）发展 并验证稳健的TNBC亚型分型模型;（2）鉴定TNBC亚型特异性化疗反应基因 （3）通过整合基因组方法发现TNBC化疗抗性生物标志物。