Evidence map›Paper›PMID 35148768›Full record

ArticleJournal of translational medicine2022

Pan-cancer quantitation of epithelial-mesenchymal transition dynamics using parallel reaction monitoring-based targeted proteomics approach.

Ankit P Jain, Janani Sambath, Gajanan Sathe, Irene A George, Akhilesh Pandey, Erik W Thompson, Prashant Kumar

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 40% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Pan-cancer and multiomics: advanced strategies for diagnosis, prognosis, and therapy in the complex genetic and molecular universe of cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
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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 at 4 institutions in 3 countries.

Ankit P Jain *Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.
Janani Sambath *Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.
Gajanan Sathe *Institute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.
Irene A GeorgeInstitute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.
Akhilesh PandeyInstitute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India.
Erik W ThompsonInstitute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, 4059, Australia. e2.thompson@qut.edu.au.
Prashant KumarInstitute of Bioinformatics, International Technology Park, Bangalore, 560066, Karnataka, India. prashant@ibioinformatics.org.ORCID 0000-0001-8975-5108
Manipal Academy of Higher Education · INInstitute of Bioinformatics · INMayo Clinic · USTranslational Research Institute · AU

Funding

DBT/Wellcome Trust India Alliance IA/M/15/1/502023
6 · The paper itself

Abstract

Epithelial-mesenchymal transition (EMT) is a dynamic and complex cellular process that is known to be hijacked by cancer cells to facilitate invasion, metastasis and therapeutic resistance. Several quantitative measures to assess the interplay between EMT and cancer progression are available, based on large scale genome and transcriptome data. However, these large scale multi-omics studies have repeatedly illustrated a lack of correlation in mRNA and protein abundances that may be influenced by diverse post-translational regulation. Hence, it is imperative to understand how changes in the EMT proteome are associated with the process of oncogenic transformation. To this effect, we developed a parallel reaction monitoring-based targeted proteomics method for quantifying abundances of EMT-associated proteins across cancer cell lines. Our study revealed that quantitative measurement of EMT proteome which enabled a more accurate assessment than transcriptomics data and revealed specific discrepancies against a backdrop of generally strong concordance between proteomic and transcriptomic data. We further demonstrated that changes in our EMT proteome panel might play a role in tumor transformation across cancer types. In future, this EMT panel assay has the potential to be used for clinical samples to guide treatment choices and to congregate functional information for the development and advancing novel therapeutics.

Indexed as

Epithelial-Mesenchymal TransitionNeoplasmsCell Line, TumorHumansProteomeProteomicsTranscriptomeProteomeEpithelial-mesenchymal transitionMass spectrometryPan-cancer targeted proteomicsParallel reaction monitoring

Identifiers

PMID35148768
PMCPMC8832824
OpenAlexW4211119316

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.