Evidence map›Paper›PMID 22554165›Full record

ArticleClinical proteomics2012

Selected Reaction Monitoring (SRM) Analysis of Epidermal Growth Factor Receptor (EGFR) in Formalin Fixed Tumor Tissue.

Todd Hembrough, Sheeno Thyparambil, Wei-Li Liao, Marlene M Darfler, Joseph Abdo, Kathleen M Bengali, Paul Taylor, Jiefei Tong, Humberto Lara-Guerra, Thomas K Waddell and 4 more

Open access · goldAbstract read
In one paragraph

Article in Clinical proteomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

34 citing papers in PubMed, 67 citations in OpenAlex.

  1. Trial
  2. Cancer discovery · 2019
    Trial
  3. Article
  4. Article
  5. Review
  6. Clinical Proteomics for Solid Organ Tissues.Molecular & cellular proteomics : MCP · 2023
    Article
  7. Article
  8. Article
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  19. Proof of the quantitative potential of immunofluorescence by mass spectrometry.Laboratory investigation; a journal of technical methods and pathology · 2017
    Article
  20. Quantitative proteomic analysis of HER2 expression in the selection of gastric cancer patients for trastuzumab treatment.Annals of oncology : official journal of the European Society for Medical Oncology · 2017
    Article
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

14 authors at 4 institutions in 2 countries.

Todd HembroughOnco Plex Diagnostics Inc, 9620 Medical Center Drive, Rockville, Maryland, 20850, USA. d.krizman@expressionpathology.com.
Sheeno Thyparambil
Wei-Li Liao
Marlene M Darfler
Joseph Abdo
Kathleen M Bengali
Paul Taylor
Jiefei Tong
Humberto Lara-Guerra
Thomas K Waddell
Michael F Moran
Ming-Sound Tsao
David B Krizman
Jon Burrows
OncoPlex Diagnostics (United States) · USHospital for Sick Children · CAPrincess Margaret Cancer Centre · CAUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnalysis of key therapeutic targets such as epidermal growth factor receptor (EGFR) in clinical tissue samples is typically done by immunohistochemistry (IHC) and is only subjectively quantitative through a narrow dynamic range. The development of a standardized, highly-sensitive, linear, and quantitative assay for EGFR for use in patient tumor tissue carries high potential for identifying those patients most likely to benefit from EGFR-targeted therapies.

methodsA mass spectrometry-based Selected Reaction Monitoring (SRM) assay for the EGFR protein (EGFR-SRM) was developed utilizing the Liquid Tissue®-SRM technology platform. Tissue culture cells (n = 4) were analyzed by enzyme-linked immunosorbent assay (ELISA) to establish quantitative EGFR levels. Matching formalin fixed cultures were analyzed by the EGFR-SRM assay and benchmarked against immunoassay of the non-fixed cultured cells. Xenograft human tumor tissue (n = 10) of non-small cell lung cancer (NSCLC) origin and NSCLC patient tumor tissue samples (n = 23) were microdissected and the EGFR-SRM assay performed on Liquid Tissue lysates prepared from microdissected tissue. Quantitative curves and linear regression curves for correlation between immunoassay and SRM methodology were developed in Excel.

resultsThe assay was developed for quantitation of a single EGFR tryptic peptide for use in FFPE patient tissue with absolute specificity to uniquely distinguish EGFR from all other proteins including the receptor tyrosine kinases, IGF-1R, cMet, Her2, Her3, and Her4. The assay was analytically validated against a collection of tissue culture cell lines where SRM analysis of the formalin fixed cells accurately reflects EGFR protein levels in matching non-formalin fixed cultures as established by ELISA sandwich immunoassay (R2 = 0.9991). The SRM assay was applied to a collection of FFPE NSCLC xenograft tumors where SRM data range from 305amol/μg to 12,860amol/μg and are consistent with EGFR protein levels in these tumors as previously-reported by western blot and SRM analysis of the matched frozen tissue. In addition, the SRM assay was applied to a collection of histologically-characterized FFPE NSCLC patient tumor tissue where EGFR levels were quantitated from not detected (ND) to 670amol/μg.

conclusionsThis report describes and evaluates the performance of a robust and reproducible SRM assay designed for measuring EGFR directly in FFPE patient tumor tissue with accuracy at extremely low (attomolar) levels. This assay can be used as part of a complementary or companion diagnostic strategy to support novel therapies currently under development and demonstrates the potential to identify candidates for EGFR-inhibitor therapy, predict treatment outcome, and reveal mechanisms of therapeutic resistance.

Identifiers

PMID22554165
PMCPMC3464929
OpenAlexW2168110569

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Registered trials

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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.