Evidence map›Paper›PMID 38892088›Full record

ArticleInternational journal of molecular sciences2024

An Optimized Method for LC-MS-Based Quantification of Endogenous Organic Acids: Metabolic Perturbations in Pancreatic Cancer.

Shreyans K Jain, Shivani Bansal, Sunil Bansal, Baldev Singh, William Klotzbier, Khyati Y Mehta, Amrita K Cheema

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shreyans K JainDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.ORCID 0000-0001-6160-8755
Shivani BansalDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.ORCID 0000-0002-5095-5687
Sunil BansalDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.
Baldev SinghDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.
William KlotzbierDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.
Khyati Y MehtaDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.ORCID 0000-0002-2613-1362
Amrita K CheemaDepartment of Oncology, Lombardi Comprehensive Cancer Centre, Georgetown University Medical Center, E-415, New Research Building, 3900 Reservoir Road NW, Washington, DC 20057, USA.ORCID 0000-0003-4877-7583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Carboxylic AcidsMetabolomicsPancreatic NeoplasmsCell Line, TumorChromatography, LiquidHumansLiquid Chromatography-Mass SpectrometryMass SpectrometryReproducibility of ResultsTandem Mass SpectrometryCarboxylic Acids4-Chloro-o-phenylenediamineCCMsLC–MRMpancreatic cancerquantification

Identifiers

PMID38892088
PMCPMC11172734

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.