Evidence map›Paper›PMID 25357240›Full record

ArticleNature methods2014

Onco-proteogenomics: cancer proteomics joins forces with genomics.

Javier A Alfaro, Ankit Sinha, Thomas Kislinger, Paul C Boutros

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Quantitative Proteomics Using Isobaric Labeling: A Practical Guide.Genomics, proteomics & bioinformatics · 2021
    Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Integrative Analysis of Incongruous Cancer Genomics and Proteomics Datasets.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  17. Review
  18. Identification of gene fusion events inNAR genomics and bioinformatics · 2020
    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

4 authors.

Javier A Alfaro1] Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. [2] Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada. [3] Informatics &Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Ankit Sinha1] Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. [2] Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada.
Thomas Kislinger1] Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. [2] Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada.
Paul C Boutros1] Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. [2] Informatics &Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. [3] Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada.ORCID 0000000305537520

Funding

Canadian Institutes of Health Research MOP-114896Canadian Institutes of Health Research MOP-93772
6 · The paper itself

Abstract

The complexities of tumor genomes are rapidly being uncovered, but how they are regulated into functional proteomes remains poorly understood. Standard proteomics workflows use databases of known proteins, but these databases do not capture the uniqueness of the cancer transcriptome, with its point mutations, unusual splice variants and gene fusions. Onco-proteogenomics integrates mass spectrometry-generated data with genomic information to identify tumor-specific peptides. Linking tumor-derived DNA, RNA and protein measurements into a central-dogma perspective has the potential to improve our understanding of cancer biology.

Indexed as

Databases, GeneticGenomicsHumansNeoplasmsProteomeProteomicsTranscriptomeProteome

Identifiers

PMID25357240

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.