{"doi":"10.3390/ijms25115901","title":"An Optimized Method for LC–MS-Based Quantification of Endogenous Organic Acids: Metabolic Perturbations in Pancreatic Cancer","abstract":"Accurate and reliable quantification of organic acids with carboxylic acid functional groups in complex biological samples remains a major analytical challenge in clinical chemistry. Issues such as spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column hinder sensitivity, specificity, and reproducibility in multiple-reaction monitoring (MRM)-based LC-MS assays. We report a targeted metabolomics method using phenylenediamine derivatization for quantifying carboxylic acid-containing metabolites (CCMs). This method achieves accurate and sensitive quantification in various biological matrices, with recovery rates from 90% to 105% and CVs ≤ 10%. It shows linearity from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 and LODs as low as 0.01 ng/mL. The library included a wide variety of structurally variant CCMs such as amino acids/conjugates, short- to medium-chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids, and some ring-containing CCMs. Comparing CCM profiles of pancreatic cancer cells to normal pancreatic cells identified potential biomarkers and their correlation with key metabolic pathways. This method enables sensitive, specific, and high-throughput quantification of CCMs from small samples, supporting a wide range of applications in basic, clinical, and translational research.","journal":"International Journal of Molecular Sciences","year":2024,"id":462041,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9468,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":369550,"name":"Shivani Bansal","orcid":"0000-0002-5095-5687","position":1,"is_corresponding":false},{"id":730985,"name":"Sunil Bansal","orcid":"0000-0001-6066-7841","position":2,"is_corresponding":false},{"id":731775,"name":"Baldev Singh","orcid":null,"position":3,"is_corresponding":false},{"id":1272685,"name":"William Klotzbier","orcid":null,"position":4,"is_corresponding":false},{"id":1291494,"name":"Khyati Y. Mehta","orcid":"0000-0002-2613-1362","position":5,"is_corresponding":false},{"id":87920,"name":"Amrita K. Cheema","orcid":"0000-0003-4877-7583","position":6,"is_corresponding":false},{"id":730982,"name":"Shreyans K. Jain","orcid":"0000-0001-6160-8755","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:04:20.631898Z","pmid":"38892088","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}