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Dissecting the Melanoma Genome

Dissecting the Melanoma Genome
剖析黑色素瘤基因组
批准号:
8667551
负责人:
Julide T. Celebi
金额:
$7.97万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-02-29 至 2015-01-31

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DESCRIPTION (provided by applicant): Metastatic melanoma is an aggressive malignancy lacking molecular markers predictive of patient outcome as well as effective therapies. The molecular genetics of melanoma has not been fully characterized. Recent advances in high-resolution genomic hybridization and high throughput sequencing methods provide opportunities for further characterization of the cancer genome. In our previous studies, we identified recurrent narrow amplifications and deletions by genome-wide BAC array comparative genomic hybridization analysis of metastatic melanoma samples. Our copy number data suggested the presence of chromosomal regions with previously undefined genetic events. Notably, we recently described GAB2 amplifications in a subset of acral melanomas as a novel genetic event, and demonstrated its critical role in melanoma metastasis via activation of the PI3K-AKT signaling. Based on our previous work, we will now pursue studies to characterize novel oncogenes and tumor suppressor genes critical for melanoma metastasis. We will pursue two linked specific aims, using a combination of genetic, biologic, and clinical approaches. (1) Defining and validating candidate genes mutated in metastatic melanoma by whole exome sequencing approach, mapping the mutated genes within amplifications and deletions, and selecting candidates. (2) Mutational profiling and functional assays will characterize the candidate gene and explore oncogenic and tumor suppressive function in melanoma. The studies in this proposal expand our knowledge on molecular genetics of melanoma by utilizing state-of- the-art technology including high throughput next generation sequencing, aim to identify novel oncogenes or tumor suppressor genes of potential high clinical significance, and include present and future studies for molecular diagnosis and outcome prediction. The studies in this proposal aim to translate knowledge gained from molecular genetics into tools that can be used in clinical decision-making.
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