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Proteomic Characterization of Genomically Complex Sarcomas

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
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-01 至 2023-06-30

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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.
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