Evidence map›Paper›PMID 24755198›Full record

SynthesisMolecular cancer therapeutics2014

A meta-analysis of somatic mutations from next generation sequencing of 241 melanomas: a road map for the study of genes with potential clinical relevance.

Junfeng Xia, Peilin Jia, Katherine E Hutchinson, Kimberly B Dahlman, Douglas Johnson, Jeffrey Sosman, William Pao, Zhongming Zhao

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Molecular cancer therapeutics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 1 pooled it
7.0field-weighted citation impact, top 2% 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

53 citing papers in PubMed, 1 synthesis or guideline pooled it, 94 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Inhibition of mTOR Signaling and Clinical Activity of Rapamycin in Head and Neck Cancer in a Window of Opportunity Trial.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
    Trial
  4. Article
  5. Review
  6. Melanoma genomics - will we go beyond BRAF in clinics?Journal of cancer research and clinical oncology · 2024
    Review
  7. Pathology and Molecular Biology of Melanoma.Current issues in molecular biology · 2023
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Journal for immunotherapy of cancer · 2020
    Article
  18. The miRNAs Role in Melanoma and in Its Resistance to Therapy.International journal of molecular sciences · 2020
    Review
  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

8 authors at 5 institutions in 2 countries.

Junfeng XiaAuthors' Affiliations: Department of Biomedical Informatics;
Peilin JiaAuthors' Affiliations: Department of Biomedical Informatics; Center for Quantitative Sciences;
Katherine E HutchinsonDepartment of Cancer Biology;
Kimberly B DahlmanDepartment of Cancer Biology; Vanderbilt-Ingram Cancer Center; and.
Douglas JohnsonDepartment of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee.
Jeffrey SosmanVanderbilt-Ingram Cancer Center; and Department of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee.
William PaoVanderbilt-Ingram Cancer Center; and Department of Medicine/Division of Hematology-Oncology, Vanderbilt University School of Medicine, Nashville, Tennessee zhongming.zhao@vanderbilt.edu william.pao@vanderbilt.edu.
Zhongming ZhaoAuthors' Affiliations: Department of Biomedical Informatics; Center for Quantitative Sciences; Department of Cancer Biology; Vanderbilt-Ingram Cancer Center; and zhongming.zhao@vanderbilt.edu william.pao@vanderbilt.edu.
Vanderbilt-Ingram Cancer CenterVanderbilt University · USBreast Cancer Research Foundation · USCentre for Cancer Biology · AUQuantitative BioSciences · US

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI STACIE B DUSETZINA · 1995 to 2026
$172.8M
Vanderbilt Clinical Oncology Research Career Development ProgramK12CA090625 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Debra L. Friedman, Paula Jill Hurley · 2001 to 2026
$16.9M
Clinical Investigation in Tumor ImmunotherapyK24CA097588 · NCI · VANDERBILT UNIVERSITY · PI SOSMAN, JEFFREY A · 2002 to 2012
$1.5M
Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI ZHAO, ZHONGMING · 2012 to 2014
$1.0M
Investigating MicroRNAs and Their Regulatory Networks in GlioblastomaR03CA167695 · NCI · VANDERBILT UNIVERSITY · PI ZHAO, ZHONGMING · 2013 to 2014
$154k
NCI NIH HHS K12 CA090625NCI NIH HHS K12CA0906525NCI NIH HHS K24 CA097588NCI NIH HHS K24CA097588NCI NIH HHS P30 CA068485NCI NIH HHS P30CA068485NCI NIH HHS R03 CA167695NCI NIH HHS R03CA167695NLM NIH HHS R01 LM011177NLM NIH HHS R01LM011177
6 · The paper itself

Abstract

Next generation sequencing (NGS) has been used to characterize the overall genomic landscape of melanomas. Here, we systematically examined mutations from recently published melanoma NGS data involving 241 paired tumor-normal samples to identify potentially clinically relevant mutations. Melanomas were characterized according to an in-house clinical assay that identifies well-known specific recurrent mutations in five driver genes: BRAF (affecting V600), NRAS (G12, G13, and Q61), KIT (W557, V559, L576, K642, and D816), GNAQ (Q209), and GNA11 (Q209). Tumors with none of these mutations are termed "pan negative." We then mined the driver mutation-positive and pan-negative melanoma NGS data for mutations in 632 cancer genes that could influence existing or emerging targeted therapies. First, we uncovered several genes whose mutations were more likely associated with BRAF- or NRAS-driven melanomas, including TP53 and COL1A1 with BRAF, and PPP6C, KALRN, PIK3R4, TRPM6, GUCY2C, and PRKAA2 with NRAS. Second, we found that the 69 "pan-negative" melanoma genomes harbored alternate infrequent mutations in the five known driver genes along with many mutations in genes encoding guanine nucleotide binding protein α-subunits. Third, we identified 12 significantly mutated genes in "pan-negative" samples (ALK, STK31, DGKI, RAC1, EPHA4, ADAMTS18, EPHA7, ERBB4, TAF1L, NF1, SYK, and KDR), including five genes (RAC1, ADAMTS18, EPHA7, TAF1L, and NF1) with a recurrent mutation in at least two "pan-negative" tumor samples. This meta-analysis provides a road map for the study of additional potentially actionable genes in both driver mutation-positive and pan-negative melanomas.

Indexed as

MutationHigh-Throughput Nucleotide SequencingHumansMelanomaSkin Neoplasms

Identifiers

PMID24755198
PMCPMC4090262
OpenAlexW2066104717

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.