Proteomic Characterization of Genomically Complex Sarcomas

基因组复杂肉瘤的蛋白质组学表征

• 批准号: 10039807
• 负责人: Michael H. A. Roehrl
• 金额: $ 38.11万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10039807
• 关键词: Area; Behavior; Biology; Carcinoma; Caring; Characteristics; Classification; Clinical; Complex; Diagnosis; Diagnostic; Differentiation Antigens; Disease; Disease Outcome; Event; Evolution; Exhibits; Future; Genetic; Genome; Genomics; Goals; Grant; Histology; Immunohistochemistry; Knowledge; Length; Malignant Fibrous Histiocytoma; Malignant Neoplasms; Medical; Memorial Sloan-Kettering Cancer Center; Metastatic to; Methods; Modeling; Molecular; Monitor; Neoplasm Metastasis; Nonmetastatic; Operative Surgical Procedures; Outcome; Pathway interactions; Patients; Primary Lesion; Proteins; Proteome; Proteomics; Recurrence; Resistance; Risk; Risk stratification; Scientist; Therapeutic; Tissues; Treatment outcome; Validation; Work; base; biomarker panel; biomedical referral center; cancer care; cancer diagnosis; cancer subtypes; clinically relevant; cohort; differential expression; drug development; experimental study; high risk; high risk population; innovation; leiomyosarcoma; metastatic process; novel; personalized medicine; predictive modeling; protein biomarkers; sarcoma; soft tissue; success; therapeutic target; therapy development; transcriptomics; treatment response; tumor

Roehrl (PI): Proteomic Characterization of Genomically Complex Sarcomas Project Summary/Abstract Patients with seemingly identical sarcomas often differ in their clinical outcomes (emergence of metastases, treatment response, survival, etc.), suggesting that these malignancies may in fact be of different subtypes that are currently unknown and indistinguishable by standard diagnostics (e.g., histology or genomics). Especially so-called genomically complex sarcomas (GCS), such as high-grade soft tissue leiomyosarcoma (LMS) and undifferentiated pleomorphic sarcoma (UPS), have been difficult to further classify by traditional genomic or transcriptomic methods alone due to absence of recurrent genomic events and targetable alterations. We hypothesize that GCS can be better classified according to proteome signatures. We propose to uncover new proteome-based subtypes by deep proteomic analysis that better define these tumors. In preliminary studies, we have shown that proteomic profiling can distinguish and sub-classify various tumors and identify protein signatures characteristic of primary or metastatic lesions. In this proposal, we will first elucidate the deep proteomes of two types of GCS, high-grade LMS and UPS. We will study tissues from two clinical outcome cohorts for each disease, a “low risk” group (tumors did not show metastases for at least 3 years after surgery) and a “high risk” group (tumors developed subsequent metastases, but are otherwise indistinguishable by current diagnostic means). By examining both primary and metastatic lesions, we will identify protein markers that differentiate these two GCS and signatures that distinguish primary from metastatic lesions. We will then validate marker panels in independent cohorts by immunohistochemistry and correlate with clinical outcomes. Based on the protein-panel signatures, we will be able to develop risk stratification models that predict metastatic propensity of LMS and UPS. Our study will have significant impact on understanding sarcomas. The likelihood of success of this proposal is high, as we have already discovered new cancer subtypes in our preliminary studies. Our interdisciplinary team includes both basic scientists and clinicians who have successfully collaborated in the past. MSKCC is a high-volume referral center for rare sarcomas, providing us with a unique opportunity to study GCS. Our envisioned proteome-based risk stratification may explain the clinical conundrum of why patients with currently seemingly similar GCS exhibit strikingly different metastatic propensity, treatment response, and length of survival. New proteomic subtyping may inform future therapy development by providing subtype-specific and metastasis-specific protein targets.

Roehrl(PI)：基因组复杂肉瘤的蛋白质组学特征 项目摘要/摘要 看似相同的肉瘤患者的临床结果往往不同(出现 转移、治疗反应、存活率等)，提示这些恶性肿瘤实际上可能是 当前未知且无法通过标准诊断区分的不同的子类型(例如， 组织学或基因组学)。尤其是所谓的基因复杂肉瘤(GCS)，如高级别 软组织平滑肌肉瘤(LMS)和未分化多形性肉瘤(UPS)一直很难治疗 由于没有复发，通过传统的基因组或转录本方法进行进一步分类 基因组事件和有针对性的改变。我们假设GCS可以更好地按照 蛋白质组签名。我们建议通过深入的蛋白质组学分析来发现新的基于蛋白质组的亚型 更好地定义了这些肿瘤。 在初步研究中，我们已经表明，蛋白质组图谱可以区分和细分不同的 并识别原发灶或转移灶的蛋白质特征。在这项提案中，我们 将首先阐明两种类型的GCS，高级别LMS和UPS的深层蛋白质组。我们会研究 每种疾病的两个临床结果队列的组织，一个低风险组(肿瘤未显示 手术后转移至少3年)和“高危”组(肿瘤随后发展 转移，但在其他方面无法通过目前的诊断手段区分)。通过检查两个主要的 和转移性病变，我们将识别区分这两个GC和信号的蛋白质标志物 来区分原发灶和转移灶。然后我们将在独立的标记面板中验证 通过免疫组织化学方法进行队列分析，并与临床结果相关。基于蛋白质组 签名，我们将能够开发预测LMS转移倾向的风险分层模型 和UPS。 我们的研究将对理解肉瘤产生重大影响。这件事成功的可能性 建议很高，因为我们已经在初步研究中发现了新的癌症亚型。我们的 跨学科团队包括基础科学家和临床医生，他们成功地在 过去的事。MSKCC是一家针对罕见肉瘤的高容量转诊中心，为我们提供了独特的 学习GCS的机会。我们设想的基于蛋白质组的风险分层可以解释临床 为什么目前看似相似的GCS患者表现出显著不同的转移 倾向、治疗反应和生存时间。新的蛋白质组亚型可能为未来提供信息 通过提供亚型特异性和转移特异性蛋白质靶点的治疗进展。