Evidence map›Paper›PMID 25656898›Full record

ArticleCancer discovery2015

Database of genomic biomarkers for cancer drugs and clinical targetability in solid tumors.

Rodrigo Dienstmann, In Sock Jang, Brian Bot, Stephen Friend, Justin Guinney

Abstract read
In one paragraph

Article in Cancer discovery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 1 pooled it
7.1field-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

71 citing papers in PubMed, 1 synthesis or guideline pooled it, 142 citations in OpenAlex.

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11 more citing papers are in PubMed but not listed here.

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

5 authors at 3 institutions in 1 country.

Rodrigo DienstmannSage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, Washington. rodrigo.dienstmann@sagebase.org.
In Sock JangSage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Brian BotSage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Stephen FriendSage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Justin GuinneySage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Cancer Research Center · USSage Bionetworks · USFred Hutch Cancer Center · US

Funding

Training SubprojectU54HG007990 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI HAUSSLER, DAVID H, PATTERSON, DAVID · 2014 to 2018
$14.8M
Integrating cancer datasets for predictive model development and trainingU54CA149237 · NCI · SAGE BIONETWORKS · PI FRIEND, STEPHEN HENRY · 2010 to 2014
$8.9M
NCI NIH HHS U54 CA149237NHGRI NIH HHS U54 HG007990
6 · The paper itself

Abstract

summaryComprehensive genomic profiling is expected to revolutionize cancer therapy. In this Prospective, we present the prevalence of mutations and copy-number alterations with predictive associations across solid tumors at different levels of stringency for gene-drug targetability. More than 90% of The Cancer Genome Atlas samples have potentially targetable alterations, the majority with multiple events, illustrating the challenges for treatment prioritization given the complexity of the genomic landscape. Nearly 80% of the variants in rarely mutated oncogenes are of uncertain functional significance, reflecting the gap in our understanding of the relevance of many alterations potentially linked to therapeutic actions. Access to targeted agents in early clinical trials could affect treatment decision in 75% of patients with cancer. Prospective implementation of large-scale molecular profiling and standardized reports of predictive biomarkers are fundamental steps for making precision cancer medicine a reality.

Indexed as

Databases, GeneticAntineoplastic AgentsBiomarkers, TumorGenomicsHumansMolecular Targeted TherapyNeoplasmsAntineoplastic AgentsBiomarkers, Tumor

Identifiers

PMID25656898
PMCPMC4825796
OpenAlexW2167179525

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.