Evidence map›Paper›PMID 27338857›Full record

ReviewSeminars in cell & developmental biology2016

The value of genomics in dissecting the RAS-network and in guiding therapeutics for RAS-driven cancers.

Gajendra Shrestha, Shelley M MacNeil, Jasmine A McQuerry, David F Jenkins, Sunil Sharma, Andrea H Bild

Open access · hybridAbstract readReview
In one paragraph

Review in Seminars in cell & developmental biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Mutational analysis ofWorld journal of clinical oncology · 2020
    Article
  2. Review
  3. MAPK/ERK Signaling in Regulation of Renal Differentiation.International journal of molecular sciences · 2019
    Review
  4. Article
  5. Article
  6. Article
  7. Review
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

6 authors at 3 institutions in 1 country.

Gajendra ShresthaDepartment of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA.
Shelley M MacNeilDepartment of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA.
Jasmine A McQuerryDepartment of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA.
David F JenkinsDivision of Computational Biomedicine, Boston University School of Medicine, Boston, MA, USA.
Sunil SharmaDepartment of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; Center for Investigational Therapeutics, Huntsman Cancer Institute, Salt Lake City, UT, USA.
Andrea H BildDepartment of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA; Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA. Electronic address: andreab@genetics.utah.edu.
University of Utah · USBoston University · USHuntsman Cancer Institute · US

Funding

Integrative signaling models to decipher complex cancer phenotypesU01CA164720 · NCI · UNIVERSITY OF UTAH · PI BILD, ANDREA HOPE, GRAY, JOE W. · 2012 to 2016
$2.9M
NCI NIH HHS U01 CA164720
6 · The paper itself

Abstract

The rise in genomic knowledge over the past decade has revealed the molecular etiology of many diseases, and has identified intricate signaling network activity in human cancers. Genomics provides the opportunity to determine genome structure and capture the activity of thousands of molecular events concurrently, which is important for deciphering highly complex genetic diseases such as cancer. In this review, we focus on genomic efforts directed towards one of cancer's most frequently mutated networks, the RAS pathway. Genomic tools such as gene expression signatures and assessment of mutations across the RAS network enable the capture of RAS signaling complexity. Due to this high level of interaction and cross-talk within the network, efforts to target RAS signaling in the clinic have generally failed, and we currently lack the ability to directly inhibit the RAS protein with high efficacy. We propose that the use of gene expression data can identify effective treatments that broadly inhibit the RAS network as this approach measures pathway activity independent of mutation status or any single mechanism of activation. Here, we review the genomic studies that map the complexity of the RAS network in cancer, and that show how genomic measurements of RAS pathway activation can identify effective RAS inhibition strategies. We also address the challenges and future directions for treating RAS-driven tumors. In summary, genomic assessment of RAS signaling provides a level of complexity necessary to accurately map the network that matches the intricacy of RAS pathway interactions in cancer.

Indexed as

GenomicsMolecular Targeted TherapyAnimalsHumansModels, BiologicalNeoplasmsras ProteinsSignal Transductionras ProteinsCancerGene expression signatureGenomicsRASTargeted therapy

Identifiers

PMID27338857
PMCPMC5951171
OpenAlexW2473654300

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.