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Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis

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 bre...

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Detalles Bibliográficos
Autores principales: Wang, Li, Wrobel, John A., Xie, Ling, Chen, Xian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887646/
https://www.ncbi.nlm.nih.gov/pubmed/33644773
http://dx.doi.org/10.1016/j.xpro.2021.100338
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author Wang, Li
Wrobel, John A.
Xie, Ling
Chen, Xian
author_facet Wang, Li
Wrobel, John A.
Xie, Ling
Chen, Xian
author_sort Wang, Li
collection PubMed
description 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 Wang et al. (2018).
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spelling pubmed-78876462021-02-26 Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis Wang, Li Wrobel, John A. Xie, Ling Chen, Xian STAR Protoc Protocol 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 Wang et al. (2018). Elsevier 2021-02-11 /pmc/articles/PMC7887646/ /pubmed/33644773 http://dx.doi.org/10.1016/j.xpro.2021.100338 Text en © 2021 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Wang, Li
Wrobel, John A.
Xie, Ling
Chen, Xian
Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
title Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
title_full Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
title_fullStr Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
title_full_unstemmed Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
title_short Protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
title_sort protocol for proteogenomic dissection of intronic splicing enhancer interactome for prediction of individualized cancer prognosis
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7887646/
https://www.ncbi.nlm.nih.gov/pubmed/33644773
http://dx.doi.org/10.1016/j.xpro.2021.100338
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