Evidence map›Paper›PMID 29900338›Full record

ArticleData in brief2018

Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

Shivangi Awasthi, Tapan Maity, Benjamin L Oyler, Xu Zhang, David R Goodlett, Udayan Guha

Open access · goldAbstract read
In one paragraph

Article in Data in brief, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Identification of active compounds inFrontiers in pharmacology · 2024
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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

6 authors at 2 institutions in 1 country.

Shivangi AwasthiThoracic & Gastrointestinal Oncology Branch, Center for Cancer Research, NCI, Bethesda, MD, United States.
Tapan MaityThoracic & Gastrointestinal Oncology Branch, Center for Cancer Research, NCI, Bethesda, MD, United States.
Benjamin L OylerSchool of Medicine, University of Maryland, Baltimore, MD, United States.
Xu ZhangThoracic & Gastrointestinal Oncology Branch, Center for Cancer Research, NCI, Bethesda, MD, United States.
David R GoodlettSchool of Pharmacy, University of Maryland, Baltimore, MD, United States.
Udayan GuhaThoracic & Gastrointestinal Oncology Branch, Center for Cancer Research, NCI, Bethesda, MD, United States.
Center for Cancer Research · USUniversity of Maryland, Baltimore · US

Funding

Protein phosphorylation downstream of mutant EGFR kinasesZIABC011410 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GUHA, UDAYAN · 2011 to 2020
$6.1M
Intramural NIH HHS ZIA BC011410
6 · The paper itself

Abstract

The data presented here describes the use of targeted proteomic assays to quantify potential biomarkers of Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) sensitivity in lung adenocarcinoma and is related to the research article: "Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma" [1]. This article describes the data associated with liquid chromatography coupled to multiple reaction monitoring (LC-MRM) method development which includes selection of an optimal transition list, retention time prediction and building of reverse calibration curves. Sample preparation and optimization which includes phosphotyrosine peptide enrichment via a combination of pan-phosphotyrosine antibodies is described. The dataset also consists of figures, tables and Excel files describing the quantitative results of testing these optimized methods in two lung adenocarcinoma cell lines with EGFR mutations.

Identifiers

PMID29900338
PMCPMC5997585
OpenAlexW2799631317

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.