Peptide Set Test: a Peptide-centric Strategy to Infer Differentially Expressed Proteins

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2024 Apr 17

PMID 38632081

Authors

Junmin Wang

Steven Novick

Affiliations

Soon will be listed here.

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.

References

Wu D, Lim E, Vaillant F, Asselin-Labat M, Visvader J, Smyth G . ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics. 2010; 26(17):2176-82. PMC: 2922896. DOI: 10.1093/bioinformatics/btq401. View

Nuber S, Nam A, Rajsombath M, Cirka H, Hronowski X, Wang J . A Stearoyl-Coenzyme A Desaturase Inhibitor Prevents Multiple Parkinson Disease Phenotypes in α-Synuclein Mice. Ann Neurol. 2020; 89(1):74-90. PMC: 7756464. DOI: 10.1002/ana.25920. View

De Marchi T, Liu N, Stingl C, Timmermans M, Smid M, Look M . 4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer. Mol Oncol. 2015; 10(1):24-39. PMC: 5528925. DOI: 10.1016/j.molonc.2015.07.004. View

Woo Y, Shin Y, Lee E, Lee S, Jeong S, Kong H . Inhibition of Aerobic Glycolysis Represses Akt/mTOR/HIF-1α Axis and Restores Tamoxifen Sensitivity in Antiestrogen-Resistant Breast Cancer Cells. PLoS One. 2015; 10(7):e0132285. PMC: 4497721. DOI: 10.1371/journal.pone.0132285. View

Papanicolaou M, Parker A, Yam M, Filipe E, Wu S, Chitty J . Temporal profiling of the breast tumour microenvironment reveals collagen XII as a driver of metastasis. Nat Commun. 2022; 13(1):4587. PMC: 9357007. DOI: 10.1038/s41467-022-32255-7. View

Sticker A, Goeminne L, Martens L, Clement L . Robust Summarization and Inference in Proteome-wide Label-free Quantification. Mol Cell Proteomics. 2020; 19(7):1209-1219. PMC: 7338080. DOI: 10.1074/mcp.RA119.001624. View

Reyes-Ramos A, Alvarez-Garcia Y, Solodin N, Almodovar J, Alarid E, Torres-Garcia W . Collagen I Fibrous Substrates Modulate the Proliferation and Secretome of Estrogen Receptor-Positive Breast Tumor Cells in a Hormone-Restricted Microenvironment. ACS Biomater Sci Eng. 2021; 7(6):2430-2443. PMC: 8877809. DOI: 10.1021/acsbiomaterials.0c01803. View

Yang J, Zhao X, Lu X, Lin X, Xu G . A data preprocessing strategy for metabolomics to reduce the mask effect in data analysis. Front Mol Biosci. 2015; 2:4. PMC: 4428451. DOI: 10.3389/fmolb.2015.00004. View

Suh M, Tovchigrechko A, Thovarai V, Rolfe M, Torralba M, Wang J . Quantitative Differences in the Urinary Proteome of Siblings Discordant for Type 1 Diabetes Include Lysosomal Enzymes. J Proteome Res. 2015; 14(8):3123-35. DOI: 10.1021/acs.jproteome.5b00052. View

10.

Piehowski P, Petyuk V, Orton D, Xie F, Moore R, Ramirez-Restrepo M . Sources of technical variability in quantitative LC-MS proteomics: human brain tissue sample analysis. J Proteome Res. 2013; 12(5):2128-37. PMC: 3695475. DOI: 10.1021/pr301146m. View

11.

Shu T, Ning W, Wu D, Xu J, Han Q, Huang M . Plasma Proteomics Identify Biomarkers and Pathogenesis of COVID-19. Immunity. 2020; 53(5):1108-1122.e5. PMC: 7574896. DOI: 10.1016/j.immuni.2020.10.008. View

12.

Chandramouli K, Qian P . Proteomics: challenges, techniques and possibilities to overcome biological sample complexity. Hum Genomics Proteomics. 2010; 2009. PMC: 2950283. DOI: 10.4061/2009/239204. View

13.

Wu D, Smyth G . Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Res. 2012; 40(17):e133. PMC: 3458527. DOI: 10.1093/nar/gks461. View

14.

Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z . clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation (Camb). 2021; 2(3):100141. PMC: 8454663. DOI: 10.1016/j.xinn.2021.100141. View

15.

Vizcaino J, Cote R, Csordas A, Dianes J, Fabregat A, Foster J . The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Res. 2012; 41(Database issue):D1063-9. PMC: 3531176. DOI: 10.1093/nar/gks1262. View

16.

Dahan H, Shir Y, Velly A, Allison P . Specific and number of comorbidities are associated with increased levels of temporomandibular pain intensity and duration. J Headache Pain. 2015; 16:528. PMC: 4441879. DOI: 10.1186/s10194-015-0528-2. View

17.

Paulovich A, Billheimer D, Ham A, Vega-Montoto L, Rudnick P, Tabb D . Interlaboratory study characterizing a yeast performance standard for benchmarking LC-MS platform performance. Mol Cell Proteomics. 2009; 9(2):242-54. PMC: 2830837. DOI: 10.1074/mcp.M900222-MCP200. View

18.

Lileikyte G, Bakochi A, Ali A, Moseby-Knappe M, Cronberg T, Friberg H . Serum proteome profiles in patients treated with targeted temperature management after out-of-hospital cardiac arrest. Intensive Care Med Exp. 2023; 11(1):43. PMC: 10350448. DOI: 10.1186/s40635-023-00528-0. View

19.

Choi M, Chang C, Clough T, Broudy D, Killeen T, MacLean B . MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics. 2014; 30(17):2524-6. DOI: 10.1093/bioinformatics/btu305. View

20.

Yu G, Wang L, Han Y, He Q . clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012; 16(5):284-7. PMC: 3339379. DOI: 10.1089/omi.2011.0118. View