Evidence map›Paper›PMID 26635363›Full record

ArticleMolecular & cellular proteomics : MCP2016

Quantitative Profiling of Post-translational Modifications by Immunoaffinity Enrichment and LC-MS/MS in Cancer Serum without Immunodepletion.

Hongbo Gu, Jian Min Ren, Xiaoying Jia, Tyler Levy, Klarisa Rikova, Vicky Yang, Kimberly A Lee, Matthew P Stokes, Jeffrey C Silva

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Plasma/Serum Proteomics based on Mass Spectrometry.Protein and peptide letters · 2024
    Review
  6. Article
  7. Article
  8. Observational
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. The plasma peptides of ovarian cancer.Clinical proteomics · 2018
    Article
  17. Article
  18. Article
  19. Review
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

9 authors.

Hongbo GuFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923 hongbo.gu@cellsignal.com.
Jian Min RenFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Xiaoying JiaFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Tyler LevyFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Klarisa RikovaFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Vicky YangFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Kimberly A LeeFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Matthew P StokesFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.
Jeffrey C SilvaFrom the § Cell Signaling Technology, 3 Trask Lane, Danvers, MA 01923.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A robust method was developed and optimized for enrichment and quantitative analysis of posttranslational modifications (PTMs) in serum/plasma samples by combining immunoaffinity purification and LC-MS/MS without depletion of abundant proteins. The method was used to survey serum samples of patients with acute myeloid leukemia (AML), breast cancer (BC), and nonsmall cell lung cancer (NSCLC). Peptides were identified from serum samples containing phosphorylation, acetylation, lysine methylation, and arginine methylation. Of the PTMs identified, lysine acetylation (AcK) and arginine mono-methylation (Rme) were more prevalent than other PTMs. Label-free quantitative analysis of AcK and Rme peptides was performed for sera from AML, BC, and NSCLC patients. Several AcK and Rme sites showed distinct abundance distribution patterns across the three cancer types. The identification and quantification of posttranslationally modified peptides in serum samples reported here can be used for patient profiling and biomarker discovery research.

Indexed as

AcetylationBreast NeoplasmsCarcinoma, Non-Small-Cell LungCell Line, TumorChromatography, LiquidFemaleHumansLeukemia, Myeloid, AcuteMethylationNeoplasm ProteinsProtein Processing, Post-TranslationalProteomicsTandem Mass SpectrometryNeoplasm Proteins

Identifiers

PMID26635363
PMCPMC4739682

What OpenQuestion holds

Textmetadata
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.