Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis.
Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis.
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DOI:
10.1016/j.xpro.2021.100338
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发表时间:
2021-03-19
期刊:
影响因子:
--
通讯作者:
Chen X
中科院分区:
文献类型:
--
作者:
Wang L;Wrobel JA;Xie L;Chen X
Inter- or intra-patient tumor heterogeneity hinders the discovery of biomarkers for predicting individualized prognosis. Here, we present a protocol for an alternative splicing activity-based proteogenomic approach for identification of candidate prognostic markers in cancer cell lines and human breast cancer specimens. The pull-down of protein complexes with intronic splicing enhancer (ISE) probes is followed by tandem mass spectrometry (MS/MS) peptide sequencing. The proteogenomic analysis of data from these ISE-MS/MS assays identifies new prognostic markers that can be utilized to stratify patients with poor prognosis. For complete details on the use and execution of this protocol, please refer to. Protocol for LC-MS/MS analysis of ISE interactomes from cancer cell lines or tissues Protocol for proteogenomic identification of ISE interactors of prognostic significance Protocol for protein extraction, ISE pull-downs, MS/MS, and proteogenomic analysis Protocols applicable to cancer cell lines and clinical specimens Inter- or intra-patient tumor heterogeneity hinders the discovery of biomarkers for predicting individualized prognosis. Here, we present a protocol for an alternative splicing activity-based proteogenomic approach for identification of candidate prognostic markers in cancer cell lines and human breast cancer specimens. The pull-down of protein complexes with intronic splicing enhancer (ISE) probes is followed by tandem mass spectrometry (MS/MS) peptide sequencing. The proteogenomic analysis of data from these ISE-MS/MS assays identifies new prognostic markers that can be utilized to stratify patients with poor prognosis.
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影响因子:
7.3
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影响因子:
5.8
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Wrobel, John A.;Xie, Ling;Chen, Xian
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64.5
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通讯作者:
Perou CM