Evidence map›Paper›PMID 28364002›Full record

ArticleCancer research2017

Tissue-Specific Signaling Networks Rewired by Major Somatic Mutations in Human Cancer Revealed by Proteome-Wide Discovery.

Junfei Zhao, Feixiong Cheng, Zhongming Zhao

Open access · bronzeAbstract read
In one paragraph

Article in Cancer research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

18 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Exome sequencing link mutation inFrontiers in oncology · 2022
    Article
  4. Review
  5. Analyzing signaling activity and function in hematopoietic cells.The Journal of experimental medicine · 2021
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. HCCDB: A Database of Hepatocellular Carcinoma Expression Atlas.Genomics, proteomics & bioinformatics · 2018
    Article
  17. Article
  18. 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

3 authors at 2 institutions in 1 country.

Junfei ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas.
Feixiong ChengCenter for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas. zhongming.zhao@uth.tmc.edu.
The University of Texas Health Science Center · USNortheastern University · US

Funding

Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI WANG, LILY, ZHAO, ZHONGMING · 2012 to 2014
$1.0M
NLM NIH HHS R01 LM011177
6 · The paper itself

Abstract

Massive somatic mutations discovered by large cancer genome sequencing projects provide unprecedented opportunities in the development of precision oncology. However, deep understanding of functional consequences of somatic mutations and identifying actionable mutations and the related drug responses currently remain formidable challenges. Dysfunction of protein posttranslational modification plays critical roles in tumorigenesis and drug responses. In this study, we proposed a novel computational oncoproteomics approach, named kinome-wide network module for cancer pharmacogenomics (KNMPx), for identifying actionable mutations that rewired signaling networks and further characterized tumorigenesis and anticancer drug responses. Specifically, we integrated 746,631 missense mutations in 4,997 tumor samples across 16 major cancer types/subtypes from The Cancer Genome Atlas into over 170,000 carefully curated nonredundant phosphorylation sites covering 18,610 proteins. We found 47 mutated proteins (e.g., ERBB2, TP53, and CTNNB1) that had enriched missense mutations at their phosphorylation sites in pan-cancer analysis. In addition, tissue-specific kinase-substrate interaction modules altered by somatic mutations identified by KNMPx were significantly associated with patient survival. We further reported a kinome-wide landscape of pharmacogenomic interactions by incorporating somatic mutation-rewired signaling networks in 1,001 cancer cell lines via KNMPx. Interestingly, we found that cell lines could highly reproduce oncogenic phosphorylation site mutations identified in primary tumors, supporting the confidence in their associations with sensitivity/resistance of inhibitors targeting EGF, MAPK, PI3K, mTOR, and Wnt signaling pathways. In summary, our KNMPx approach is powerful for identifying oncogenic alterations via rewiring phosphorylation-related signaling networks and drug sensitivity/resistance in the era of precision oncology.

Indexed as

CarcinogenesisHumansMutationNeoplasmsPhosphorylationProteomeSignal TransductionProteome

Identifiers

PMID28364002
PMCPMC5476506
OpenAlexW2602965346

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.