<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Kitata RB</submitter><funding>Ministry of Science and Technology, Taiwan</funding><funding>NCI NIH HHS</funding><funding>NIGMS NIH HHS</funding><pagination>2539</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8099862</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12(1)</volume><pubmed_abstract>Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (&lt;0.1 ng), accurate site localization and reproducible quantification (~5% median coefficient of variation). As a proof-of-concept, we use lung cancer cell lines and patient-derived tissue to construct a hybrid phosphoproteome spectral library covering 159,524 phosphopeptides (88,107 phosphosites). Based on this library, our single-shot streamlined DIA workflow quantifies 36,350 phosphosites (19,755 class 1) in cell line samples within two hours. Application to drug-resistant cells and patient-derived lung cancer tissues delineates site-specific phosphorylation events associated with resistance and tumor progression, showing that our workflow enables the characterization of phosphorylation signaling with deep coverage, high sensitivity and low between-run missing values.</pubmed_abstract><journal>Nature communications</journal><pubmed_title>A data-independent acquisition-based global phosphoproteomics system enables deep profiling.</pubmed_title><pmcid>PMC8099862</pmcid><funding_grant_id>R01 GM094231</funding_grant_id><funding_grant_id>U24 CA210967</funding_grant_id><funding_grant_id>MOST 107-2113-M-001-023-MY3</funding_grant_id><pubmed_authors>Lin PY</pubmed_authors><pubmed_authors>Tsai CF</pubmed_authors><pubmed_authors>Sung TY</pubmed_authors><pubmed_authors>Kitata RB</pubmed_authors><pubmed_authors>Choong WK</pubmed_authors><pubmed_authors>Chen BS</pubmed_authors><pubmed_authors>Chen YJ</pubmed_authors><pubmed_authors>Nesvizhskii AI</pubmed_authors><pubmed_authors>Chang YC</pubmed_authors></additional><is_claimable>false</is_claimable><name>A data-independent acquisition-based global phosphoproteomics system enables deep profiling.</name><description>Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (&lt;0.1 ng), accurate site localization and reproducible quantification (~5% median coefficient of variation). As a proof-of-concept, we use lung cancer cell lines and patient-derived tissue to construct a hybrid phosphoproteome spectral library covering 159,524 phosphopeptides (88,107 phosphosites). Based on this library, our single-shot streamlined DIA workflow quantifies 36,350 phosphosites (19,755 class 1) in cell line samples within two hours. Application to drug-resistant cells and patient-derived lung cancer tissues delineates site-specific phosphorylation events associated with resistance and tumor progression, showing that our workflow enables the characterization of phosphorylation signaling with deep coverage, high sensitivity and low between-run missing values.</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 May</publication><modification>2025-04-26T07:25:12.309Z</modification><creation>2025-04-06T12:16:30.875Z</creation></dates><accession>S-EPMC8099862</accession><cross_references><pubmed>33953186</pubmed><doi>10.1038/s41467-021-22759-z</doi></cross_references></HashMap>