Evidence map›Paper›PMID 30401717›Full record

ArticleMolecular cancer research : MCR2019

Molecular Correlates of Metastasis by Systematic Pan-Cancer Analysis Across The Cancer Genome Atlas.

Fengju Chen, Yiqun Zhang, Sooryanarayana Varambally, Chad J Creighton

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cancer research : MCR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
1.2field-weighted citation impact, top 24% 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

29 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
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  5. Review
  6. A deep profile of gene expression across 18 human cancers.bioRxiv : the preprint server for biology · 2024
    Article
  7. Article
  8. Article
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  10. Review
  11. Article
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  16. Tumor Purity in Preclinical Mouse Tumor Models.Cancer research communications · 2022
    Article
  17. Article
  18. Investigation of Transcript Variant 6 ofOxidative medicine and cellular longevity · 2022
    Article
  19. Review
  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 at 2 institutions in 1 country.

Fengju ChenDivision of Biostatistics, Dan L. Duncan Comprehensive Cancer Center Baylor College of Medicine, Houston, Texas.
Yiqun ZhangDivision of Biostatistics, Dan L. Duncan Comprehensive Cancer Center Baylor College of Medicine, Houston, Texas.
Sooryanarayana VaramballyComprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama.
Chad J CreightonDivision of Biostatistics, Dan L. Duncan Comprehensive Cancer Center Baylor College of Medicine, Houston, Texas. creighto@bcm.edu.
Baylor College of Medicine · USUniversity of Alabama at Birmingham · US

Funding

Tumor BiologyP30CA125123 · NCI · BAYLOR COLLEGE OF MEDICINE · PI DAVID R ROWLEY · 2007 to 2026
$73.9M
NCI NIH HHS P30 CA125123
6 · The paper itself

Abstract

Tumor metastasis is a major contributor to mortality of cancer patients, but the process remains poorly understood. Molecular comparisons between primary tumors and metastases can provide insights into the pathways and processes involved. Here, we systematically analyzed and cataloged molecular correlates of metastasis using The Cancer Genome Atlas (TCGA) datasets across 11 different cancer types, these data involving 4,473 primary tumor samples and 395 tumor metastasis samples (including 369 from melanoma). For each cancer type, widespread differences in gene transcription between primary and metastasis samples were observed. For several cancer types, metastasis-associated genes from TCGA comparisons were found to overlap extensively with external results from independent profiling datasets of metastatic tumors. Although some differential expression patterns associated with metastasis were found to be shared across multiple cancer types, by and large each cancer type showed a metastasis signature that was distinctive from those of the other cancer types. Functional categories of genes enriched in multiple cancer type-specific metastatic overexpression signatures included cellular response to stress, DNA repair, oxidation-reduction process, protein deubiquitination, and receptor activity. The TCGA-derived prostate cancer metastasis signature in particular could define a subset of aggressive primary prostate cancer. Transglutaminase 2 protein and mRNA were both elevated in metastases from breast and melanoma cancers. Alterations in miRNAs and in DNA methylation were also identified. IMPLICATIONS: Our findings suggest that there are different molecular pathways to metastasis involved in different cancers. Our catalog of alterations provides a resource for future studies investigating the role of specific genes in metastasis.

Indexed as

Genes, NeoplasmFemaleGene Expression ProfilingHumansMaleNeoplasm MetastasisNeoplasms

Identifiers

PMID30401717
PMCPMC6359982
OpenAlexW2899687476

What OpenQuestion holds

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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.