Proteomic Characterization of Genomically Complex Sarcomas
Proteomic Characterization of Genomically Complex Sarcomas
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
关键词:
AreaBehaviorBiologyCarcinomaCaringCharacteristicsClassificationClinicalComplexDiagnosisDiagnosticDifferentiation AntigensDiseaseDisease OutcomeEventEvolutionExhibitsFutureGeneticGenomeGenomicsGoalsGrantHistologyImmunohistochemistryKnowledgeLengthMalignant Fibrous HistiocytomaMalignant NeoplasmsMedicalMemorial Sloan-Kettering Cancer CenterMetastatic toMethodsModelingMolecularMonitorNeoplasm MetastasisNonmetastaticOperative Surgical ProceduresOutcomePathway interactionsPatientsPrimary LesionProteinsProteomeProteomicsRecurrenceResistanceRiskRisk stratificationScientistTherapeuticTissuesTreatment outcomeValidationWorkbasebiomarker panelbiomedical referral centercancer carecancer diagnosiscancer subtypesclinically relevantcohortdifferential expressiondrug developmentexperimental studyhigh riskhigh risk populationinnovationleiomyosarcomametastatic processnovelpersonalized medicinepredictive modelingprotein biomarkerssarcomasoft tissuesuccesstherapeutic targettherapy developmenttranscriptomicstreatment responsetumor
中文摘要
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英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Evaluation of Patient Factors and Sample Pre-Analytics on Predictive Multiplex Immunohistochemical Assays in Immuno-Oncology Patients
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批准号:10907058
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项目类别:
-
资助金额:$20.11万
-
财政年份:2023
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负责人:Michael H. A. Roehrl
-
依托单位:
Evaluation of Patient Factors and Sample Pre-Analytics on Predictive Multiplex Immunohistochemical Assays in Immuno-Oncology Patients
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批准号:10451186
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项目类别:
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资助金额:$20.13万
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财政年份:2022
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负责人:Michael H. A. Roehrl
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依托单位:
Proteomic Characterization of Pancreatic Neuroendocrine Tumors and Metastatic Progression
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批准号:10472649
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项目类别:
-
资助金额:$2.45万
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财政年份:2021
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负责人:Michael H. A. Roehrl
-
依托单位:
Proteomic Characterization of Pancreatic Neuroendocrine Tumors and Metastatic Progression
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批准号:10290014
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项目类别:
-
资助金额:$20.69万
-
财政年份:2021
-
负责人:Michael H. A. Roehrl
-
依托单位:
Pathology
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批准号:10084822
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项目类别:
-
资助金额:$76.36万
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财政年份:1997
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负责人:Michael H. A. Roehrl
-
依托单位:
Pathology
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批准号:10571810
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项目类别:
-
资助金额:$76.36万
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财政年份:1997
-
负责人:Michael H. A. Roehrl
-
依托单位:
Pathology
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批准号:10319505
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项目类别:
-
资助金额:$76.36万
-
财政年份:1997
-
负责人:Michael H. A. Roehrl
-
依托单位:
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