Evidence map›Paper›PMID 26139413›Full record

ArticleJournal of proteome research2015

Advanced Proteogenomic Analysis Reveals Multiple Peptide Mutations and Complex Immunoglobulin Peptides in Colon Cancer.

Sunghee Woo, Seong Won Cha, Stefano Bonissone, Seungjin Na, David L Tabb, Pavel A Pevzner, Vineet Bafna

Open access · greenAbstract 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 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

20 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Multi-omic stratification of the missense variant cysteinome.bioRxiv : the preprint server for biology · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. The Antibody Repertoire of Colorectal Cancer.Molecular & cellular proteomics : MCP · 2017
    Article
  17. Methods, Tools and Current Perspectives in Proteogenomics.Molecular & cellular proteomics : MCP · 2017
    Review
  18. Article
  19. Article
  20. 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

7 authors at 1 institution in 1 country.

Sunghee Woo
Seong Won Cha
Stefano Bonissone
Seungjin Na
David L TabbDepartment of Biomedical Informatics, Vanderbilt University , Nashville, Tennessee 37203, United States.
Pavel A Pevzner
Vineet Bafna
Vanderbilt University · US

Funding

Vanderbilt Proteome Characterization CenterU24CA159988 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LIEBLER, DANIEL C · 2011 to 2016
$13.9M
TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
Computational methods for detecting patterns of complex genomic variationR01GM114362 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Vineet Bafna · 2016 to 2026
$3.1M
NCI NIH HHS U24 CA159988NIGMS NIH HHS 5 P41 GM103484-07NIGMS NIH HHS P41 GM103484NIGMS NIH HHS R01 GM114362
6 · The paper itself

Abstract

Aiming toward an improved understanding of the regulation of proteins in cancer, recent studies from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) have focused on analyzing cancer tissue using proteomic technologies and workflows. Although many proteogenomics approaches for the study of cancer samples have been proposed, serious methodological challenges remain, especially in the identification of multiple mutational variants or structural variations such as fusion gene events. In addition, although immune system genes play an important role in cancer, identification of IgG peptides remains challenging in proteomic data sets. Here, we describe an integrative proteogenomic method that extends the limit of proteogenomic searches to identify multiple variant peptides as well as immunoglobulin gene variations/rearrangements using customized mining of RNA-seq data. Our results also provide the first extensive characterization of tumor immune response and demonstrate the potential of this method to improve the molecular characterization of tumor subtypes.

Indexed as

GenomicsMutationProteomicsAlternative SplicingAmino Acid SequenceDatabases, ProteinHumansImmunoglobulinsMolecular Sequence DataPeptidesTandem Mass SpectrometryImmunoglobulinsPeptidescancercancer proteogenomicsCPTACProteogenomicsRNA-seqTCGA

Identifiers

PMID26139413
PMCPMC4868822
OpenAlexW2461798152

What OpenQuestion holds

Textmetadata
LicenceTDM
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.