Evidence map›Paper›PMID 39225545›Full record

ArticleCancer research communications2024

NCI's Proteomic Data Commons: A Cloud-Based Proteomics Repository Empowering Comprehensive Cancer Analysis through Cross-Referencing with Genomic and Imaging Data.

Ratna R Thangudu, Michael Holck, Deepak Singhal, Alexander Pilozzi, Nathan Edwards, Paul A Rudnick, Marcin J Domagalski, Padmini Chilappagari, Lei Ma, Yi Xin and 17 more

Abstract read
In one paragraph

Article in Cancer research communications, 2024. 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. Article
  2. Review
  3. Review
  4. Article
  5. HISTAI: a valuable dataset with a valuable lesson.The journal of pathology. Clinical research · 2026
    Article
  6. Article
  7. Article
  8. Beyond olfaction: New insights into human odorant binding proteins.Protein science : a publication of the Protein Society · 2026
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. PepCentric Enables Fast Repository-Scale Proteogenomics Searches.bioRxiv : the preprint server for biology · 2025
    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

27 authors.

Ratna R ThanguduICF, Rockville, Maryland.ORCID 0000-0001-6765-0401
Michael HolckICF, Rockville, Maryland.ORCID 0009-0007-9824-8491
Deepak SinghalICF, Rockville, Maryland.ORCID 0009-0007-0677-505X
Alexander PilozziICF, Rockville, Maryland.ORCID 0009-0001-8521-6470
Nathan EdwardsGeorgetown University, Washington, District of Columbia.ORCID 0000-0001-5168-3196
Paul A RudnickSpectragen Informatics LLC, Bainbridge Island, Washington.ORCID 0000-0003-1403-6445
Marcin J DomagalskiICF, Rockville, Maryland.ORCID 0000-0002-2579-9133
Padmini ChilappagariICF, Rockville, Maryland.ORCID 0009-0009-9452-6639
Lei MaICF, Rockville, Maryland.ORCID 0009-0000-1240-0691
Yi XinICF, Rockville, Maryland.ORCID 0009-0000-3983-7746
Toan LeICF, Rockville, Maryland.ORCID 0009-0002-9431-2170
Kristen NyceICF, Rockville, Maryland.ORCID 0009-0005-7388-5756
Rekha ChaudharyICF, Rockville, Maryland.ORCID 0009-0008-1564-8842
Karen A KetchumICF, Rockville, Maryland.ORCID 0009-0003-8317-2042
Aaron MauraisUniversity of Washington, Seattle, Washington.ORCID 0000-0003-3489-9117
Brian ConnollyUniversity of Washington, Seattle, Washington.ORCID 0009-0008-6137-2197
Michael RiffleUniversity of Washington, Seattle, Washington.ORCID 0000-0003-1633-8607
Matthew C ChambersUniversity of Washington, Seattle, Washington.ORCID 0000-0002-7299-4783
Brendan MacLeanUniversity of Washington, Seattle, Washington.ORCID 0000-0002-9575-0255
Michael J MacCossUniversity of Washington, Seattle, Washington.ORCID 0000-0003-1853-0256
Peter B McGarveyGeorgetown University, Washington, District of Columbia.ORCID 0000-0002-8312-6017
Anand BasuICF, Rockville, Maryland.ORCID 0000-0002-9908-9097
John OtridgeLeidos Biomedical, Inc., Rockville, Maryland.ORCID 0009-0007-7018-916X
Esmeralda Casas-SilvaCenter for Biomedical Informatics & Information Technology, National Cancer Institute, Rockville, Maryland.ORCID 0000-0002-9704-0812
Sudha VenkatachariLeidos Biomedical, Inc., Rockville, Maryland.ORCID 0009-0001-4553-8141
Henry RodriguezOffice of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, Maryland.ORCID 0000-0002-4593-4232
Xu ZhangOffice of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, Maryland.ORCID 0000-0001-7784-1439

Funding

Seattle Quant: A Resource for the Skyline Software EcosystemR24GM141156 · NIGMS · UNIVERSITY OF WASHINGTON · PI Michael MacCoss · 2021 to 2026
$6.7M
NCI NIH HHS HHSN261201500003CNCI NIH HHS HHSN261201500003INIGMS NIH HHS R24 GM141156
6 · The paper itself

Abstract

Proteomics has emerged as a powerful tool for studying cancer biology, developing diagnostics, and therapies. With the continuous improvement and widespread availability of high-throughput proteomic technologies, the generation of large-scale proteomic data has become more common in cancer research, and there is a growing need for resources that support the sharing and integration of multi-omics datasets. Such datasets require extensive metadata including clinical, biospecimen, and experimental and workflow annotations that are crucial for data interpretation and reanalysis. The need to integrate, analyze, and share these data has led to the development of NCI's Proteomic Data Commons (PDC), accessible at https://pdc.cancer.gov. As a specialized repository within the NCI Cancer Research Data Commons (CRDC), PDC enables researchers to locate and analyze proteomic data from various cancer types and connect with genomic and imaging data available for the same samples in other CRDC nodes. Presently, PDC houses annotated data from more than 160 datasets across 19 cancer types, generated by several large-scale cancer research programs with cohort sizes exceeding 100 samples (tumor and associated normal when available). In this article, we review the current state of PDC in cancer research, discuss the opportunities and challenges associated with data sharing in proteomics, and propose future directions for the resource. SIGNIFICANCE: The Proteomic Data Commons (PDC) plays a crucial role in advancing cancer research by providing a centralized repository of high-quality cancer proteomic data, enriched with extensive clinical annotations. By integrating and cross-referencing with complementary genomic and imaging data, the PDC facilitates multi-omics analyses, driving comprehensive insights, and accelerating discoveries across various cancer types.

Indexed as

Cloud ComputingGenomicsNational Cancer Institute (U.S.)NeoplasmsProteomicsHumansUnited States

Identifiers

PMID39225545
PMCPMC11413857

What OpenQuestion holds

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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.