Dataset Information

Multiple reaction monitoring assay for differentiating gastric cancer from acid peptic diseases

ABSTRACT: Gastric cancers (GCs) are often diagnosed in advanced stages, owing to non-specific clinical symptoms at early stages that resemble Acid Peptic Diseases (APDs). Despite recent efforts, a simple, liquid biopsy-based, multi-protein panel pre-diagnostic assay that can differentiate GCs from APDs is lacking. Parallelly, Mass Spectrometry (MS)-based targeted proteomics methods including Multiple Reaction Monitoring (MRM) are being progressively utilised as method-of-choice to build Laboratory Developed Tests (LDTs). An MS-MRM LDT that can quantify a panel of serum proteins was developed and tested in 135 serum samples from treatment-naïve cases of GCs, APDs, and healthy individuals.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

SUBMITTER: Keshava Prasad T. S.

LAB HEAD: Keshava Prasad

PROVIDER: PXD064371 | Pride | 2025-09-18

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 1008

Publications

Differentiating Gastric Cancers from Acid Peptic Diseases through Integrative Targeted Proteomics and Machine Learning Approaches.

Ramesh Poornima P Upadhyay Shubham Sukerndeo SS Thomas Sonet Daniel SD Sorake Chandrashekar Jeevaraj CJ M K Ganesh G Shetty Vijith Vittal VV Modi Prashant Kumar PK Shetty Rohan R Vijayakumar Manavalan M Codi Jalaluddin Akbar Kandel JAK Prasad Thottethodi Subrahmanya Keshava TSK

Journal of proteome research 20250917 10

Gastric cancers (GCs) are often diagnosed in advanced stages owing to nonspecific early symptoms resembling Acid Peptic Diseases (APDs). Despite recent efforts, a simple, liquid biopsy-based multiprotein panel prediagnostic assay capable of differentiating GCs from APDs is lacking. Mass spectrometry (MS)-based targeted proteomics methods, including Multiple Reaction Monitoring (MRM), are utilized as the method of choice to develop Laboratory Developed Tests (LDTs) that revolutionize GC early dia ...[more]

PMID: 40958687

Similar Datasets

Project description:The current state of proteomics requires a choice between targeted and discovery methods. The former provides exceptional quantitation and data completeness, but only with few analytes. Discovery proteomics can identify hundreds and thousands of proteins in a sample, but with poor quantitation and data completeness. We have established and optimized a method that combines targeted and data-independent acquisition for absolute quantitation of all plasma proteins in a single sequential window acquisition of all theoretical fragment ions (SWATH) acquisition run using a panel of spike-in standards (SIS). We compared the absolute quantitation (AQ) of SWATH and high-resolution multiple-reaction monitoring (MRM-HR) acquisition methods using the 100 protein PlasmaDive SIS panel spiked into human plasma. SWATH provided equivalent quantitation and differentially abundant protein profiles as MRM-HR. Absolute quantities of the SIS peptides from the SWATH data were used to estimate the absolute quantities (eAQ) for all the proteins in the run. The eAQ values provided similar quantitation and differentially abundant protein profiles as AQ and protein group (PG) values, and the eAQ method was the only scheme where all selected proteins were verified by MRM-HR. We applied the eAQ method to a cohort of 16 non-small cell lung cancer (NSCLC) patients receiving immunotherapeutics and found that fibronectin (FN1) and proteoglycan 4 (PRG4) were useful markers for predicting patients who would stay on these agents for at least 6 months (area under the curve of 0.8438 and 0.6735, respectively). Thirteen additional plasma samples confirmed that FN1 and PRG4 are putative biomarkers (positive predictive value is 100% and 85.7%, respectively) for a prolonged (>6 months) response to immunotherapeutic agents. In conclusion, we describe an optimized method for absolute quantification of all proteins in a SWATH run, and this approach is amenable for the identification of plasma biomarkers.

			Action	DRS
	CO_H1-R1.wiff	Wiff
	CO_H1-R1.wiff.scan	Wiff
	CO_H1-R2.wiff	Wiff
	CO_H1-R2.wiff.scan	Wiff
	CO_H1-R3.wiff	Wiff