Evidence map›Paper›PMID 26202522›Full record

ArticleJournal of proteome research2015

Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry.

Reta Birhanu Kitata, Baby Rorielyn T Dimayacyac-Esleta, Wai-Kok Choong, Chia-Feng Tsai, Tai-Du Lin, Chih-Chiang Tsou, Shao-Hsing Weng, Yi-Ju Chen, Pan-Chyr Yang, Susan D Arco and 3 more

Abstract read
In one paragraph

Article in Journal of proteome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. StageTip: a little giant unveiling the potential of mass spectrometry-based proteomics.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Proteomic Analysis of Embryonic and Young Human Vitreous.Investigative ophthalmology & visual science · 2015
    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

13 authors.

Reta Birhanu KitataInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.
Baby Rorielyn T Dimayacyac-EsletaInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.
Wai-Kok ChoongInstitute of Information Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan.
Chia-Feng TsaiInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.
Tai-Du LinInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.
Chih-Chiang TsouDepartment of Computational Medicine and Bioinformatics and Department of Pathology, University of Michigan Medical School , 1301 Catherine, Ann Arbor, Michigan 48109, United States.
Shao-Hsing WengInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.
Yi-Ju ChenInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.
Pan-Chyr YangDepartment of Internal Medicine, National Taiwan University Hospital , 1 Jen-Ai Road, Section 1, Taipei 10051, Taiwan.
Susan D ArcoInstitute of Chemistry, University of the Philippines , Diliman Quezon City, Philippines.
Alexey I NesvizhskiiDepartment of Computational Medicine and Bioinformatics and Department of Pathology, University of Michigan Medical School , 1301 Catherine, Ann Arbor, Michigan 48109, United States.
Ting-Yi SungInstitute of Information Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan.
Yu-Ju ChenInstitute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.

Funding

COMPUTATIONAL TOOLS FOR MASS SPECTROMETRY-BASED INTERACTOME DATAR01GM094231 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 2010 to 2026
$5.4M
NIGMS NIH HHS 5R01GM94231NIGMS NIH HHS R01 GM094231
6 · The paper itself

Abstract

Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.

Indexed as

Amino Acid SequenceCell Line, TumorChromatography, LiquidHumansHydrogen-Ion ConcentrationMembrane ProteinsMolecular Sequence DataProteomeTandem Mass SpectrometryMembrane ProteinsProteomeHp-RP StageTiplung cancermembrane proteinsmissing proteinsMRM

Identifiers

PMID26202522
PMCPMC4761227

What OpenQuestion holds

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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.