Your browser doesn't support javascript.
loading
Peptide set test: a peptide-centric strategy to infer differentially expressed proteins.
Wang, Junmin; Novick, Steven.
Afiliación
  • Wang J; Data Sciences and Quantitative Biology, Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gaithersburg, MD 20878, United States.
  • Novick S; Global Statistical Sciences, Eli Lilly, Indianapolis, IN 46285, United States.
Bioinformatics ; 40(5)2024 May 02.
Article en En | MEDLINE | ID: mdl-38632081
ABSTRACT
MOTIVATION The clinical translation of mass spectrometry-based proteomics has been challenging due to limited statistical power caused by large technical variability and inter-patient heterogeneity. Bottom-up proteomics provides an indirect measurement of proteins through digested peptides. This raises the question whether peptide measurements can be used directly to better distinguish differentially expressed proteins.

RESULTS:

We present a novel method called the peptide set test, which detects coordinated changes in the expression of peptides originating from the same protein and compares them to the rest of the peptidome. Applying our method to data from a published spike-in experiment and simulations demonstrates improved sensitivity without compromising precision, compared to aggregation-based approaches. Additionally, applying the peptide set test to compare the tumor proteomes of tamoxifen-sensitive and tamoxifen-resistant breast cancer patients reveals significant alterations in peptide levels of collagen XII, suggesting an association between collagen XII-mediated matrix reassembly and tamoxifen resistance. Our study establishes the peptide set test as a powerful peptide-centric strategy to infer differential expression in proteomics studies. AVAILABILITY AND IMPLEMENTATION Peptide set test (PepSetTest) is publicly available at https//github.com/JmWangBio/PepSetTest.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Péptidos / Neoplasias de la Mama / Proteómica Límite: Female / Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Péptidos / Neoplasias de la Mama / Proteómica Límite: Female / Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos