Evidence map›Paper›PMID 33072574›Full record

ArticleFrontiers in oncology2020

An Integrated Quantitative Proteomics Workflow for Cancer Biomarker Discovery and Validation in Plasma.

Vipin Kumar, Sandipan Ray, Saicharan Ghantasala, Sanjeeva Srivastava

Abstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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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

4 authors.

Vipin KumarDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.
Sandipan RayDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.
Saicharan GhantasalaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.
Sanjeeva SrivastavaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood plasma is one of the most widely used samples for cancer biomarker discovery research as well as clinical investigations for diagnostic and therapeutic purposes. However, the plasma proteome is extremely complex due to its wide dynamic range of protein concentrations and the presence of high-abundance proteins. Here we have described an optimized, integrated quantitative proteomics pipeline combining the label-free and multiplexed-labeling-based (iTRAQ and TMT) plasma proteome profiling methods for biomarker discovery, followed by the targeted approaches for validation of the identified potential marker proteins. In this workflow, the targeted quantitation of proteins is carried out by multiple-reaction monitoring (MRM) and parallel-reaction monitoring (PRM) mass spectrometry. Thus, our approach enables both unbiased screenings of biomarkers and their subsequent selective validation in human plasma. The overall procedure takes only ~2 days to complete, including the time for data acquisition (excluding database searching). This protocol is quick, flexible, and eliminates the need for a separate immunoassay-based validation workflow in blood cancer biomarker investigations. We anticipate that this plasma proteomics workflow will help to accelerate the cancer biomarker discovery program and provide a valuable resource to the cancer research community.

Indexed as

cancer biomarkerlabel-free quantitationmultiple reaction monitoringmultiplexed quantitative proteomicsparallel reaction monitoringtargeted proteomics

Identifiers

PMID33072574
PMCPMC7538778

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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.