Evidence map›Paper›PMID 25036042›Full record

SynthesisPloS one2014

A meta-analysis approach for characterizing pan-cancer mechanisms of drug sensitivity in cell lines.

Kendric Wang, Raunak Shrestha, Alexander W Wyatt, Anupama Reddy, Joseph Lehár, Yuzhou Wang, Anna Lapuk, Colin C Collins

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Medulloblastoma: Molecular Classification-Based Personal Therapeutics.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2017
    Review
  6. A Robust Model-Free Feature Screening Method for Ultrahigh-Dimensional Data.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2017
    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 2 institutions in 2 countries.

Kendric WangVancouver Prostate Centre, Vancouver General Hospital, Vancouver, Canada.
Raunak ShresthaVancouver Prostate Centre, Vancouver General Hospital, Vancouver, Canada; CIHR/MSHFR Bioinformatics Training Program, University of British Columbia, Vancouver, Canada.
Alexander W WyattVancouver Prostate Centre, Vancouver General Hospital, Vancouver, Canada.
Anupama ReddyNovartis Pharmaceuticals, Oncology Division, Basal, Switzerland.
Joseph LehárNovartis Pharmaceuticals, Oncology Division, Basal, Switzerland.
Yuzhou WangVancouver Prostate Centre, Vancouver General Hospital, Vancouver, Canada; Department of Urologic Sciences, the University of British Columbia, Vancouver, Canada.
Anna LapukVancouver Prostate Centre, Vancouver General Hospital, Vancouver, Canada.
Colin C CollinsVancouver Prostate Centre, Vancouver General Hospital, Vancouver, Canada; Department of Urologic Sciences, the University of British Columbia, Vancouver, Canada.
Vancouver General Hospital · CANovartis (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the heterogeneous drug response of cancer patients is essential to precision oncology. Pioneering genomic analyses of individual cancer subtypes have begun to identify key determinants of resistance, including up-regulation of multi-drug resistance (MDR) genes and mutational alterations of drug targets. However, these alterations are sufficient to explain only a minority of the population, and additional mechanisms of drug resistance or sensitivity are required to explain the remaining spectrum of patient responses to ultimately achieve the goal of precision oncology. We hypothesized that a pan-cancer analysis of in vitro drug sensitivities across numerous cancer lineages will improve the detection of statistical associations and yield more robust and, importantly, recurrent determinants of response. In this study, we developed a statistical framework based on the meta-analysis of expression profiles to identify pan-cancer markers and mechanisms of drug response. Using the Cancer Cell Line Encyclopaedia (CCLE), a large panel of several hundred cancer cell lines from numerous distinct lineages, we characterized both known and novel mechanisms of response to cytotoxic drugs including inhibitors of Topoisomerase 1 (TOP1; Topotecan, Irinotecan) and targeted therapies including inhibitors of histone deacetylases (HDAC; Panobinostat) and MAP/ERK kinases (MEK; PD-0325901, AZD6244). Notably, our analysis implicated reduced replication and transcriptional rates, as well as deficiency in DNA damage repair genes in resistance to TOP1 inhibitors. The constitutive activation of several signaling pathways including the interferon/STAT-1 pathway was implicated in resistance to the pan-HDAC inhibitor. Finally, a number of dysregulations upstream of MEK were identified as compensatory mechanisms of resistance to the MEK inhibitors. In comparison to alternative pan-cancer analysis strategies, our approach can better elucidate relevant drug response mechanisms. Moreover, the compendium of putative markers and mechanisms identified through our analysis can serve as a foundation for future studies into these drugs.

Indexed as

Antineoplastic AgentsBiomarkers, TumorCell Line, TumorDNA RepairDrug Resistance, MultipleDrug Resistance, NeoplasmHistone Deacetylase InhibitorsHumansInterferonsMitogen-Activated Protein Kinase KinasesNeoplasmsSignal TransductionSTAT1 Transcription FactorTopoisomerase I InhibitorsTranscriptomeUp-RegulationAntineoplastic AgentsBiomarkers, TumorHistone Deacetylase InhibitorsInterferonsMitogen-Activated Protein Kinase KinasesSTAT1 Transcription FactorTopoisomerase I Inhibitors

Identifiers

PMID25036042
PMCPMC4103868
OpenAlexW2078074992

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.