Evidence map›Paper›PMID 31136571›Full record

ArticlePLoS computational biology2019

Sparse discriminative latent characteristics for predicting cancer drug sensitivity from genomic features.

David A Knowles, Gina Bouchard, Sylvia Plevritis

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

David A KnowlesDepartment of Radiology, Stanford University School of Medicine, Stanford, California, USA.ORCID 0000-0002-7408-146X
Gina BouchardDepartment of Radiology, Stanford University School of Medicine, Stanford, California, USA.
Sylvia PlevritisDepartment of Radiology, Stanford University School of Medicine, Stanford, California, USA.
Stanford University · US

Funding

MODELING THE ROLE OF PROGRESSION IN FOLLICULAR LYMPHOMAU54CA149145 · NCI · STANFORD UNIVERSITY · PI FELSHER, DEAN W · 2010 to 2014
$12.1M
Spatial-Genomic Integrative Multi-Species Analysis of Lymph Node MetastasisU54CA209971 · NCI · STANFORD UNIVERSITY · PI NOLAN, GARRY P, PLEVRITIS, SYLVIA KATINA · 2016 to 2021
$11.0M
Cancer Systems Biology Scholars ProgramR25CA180993 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2014 to 2018
$2.2M
NCI NIH HHS R25 CA180993NCI NIH HHS U54 CA149145NCI NIH HHS U54 CA209971
6 · The paper itself

Abstract

Drug screening studies typically involve assaying the sensitivity of a range of cancer cell lines across an array of anti-cancer therapeutics. Alongside these sensitivity measurements high dimensional molecular characterizations of the cell lines are typically available, including gene expression, copy number variation and genomic mutations. We propose a sparse multitask regression model which learns discriminative latent characteristics that predict drug sensitivity and are associated with specific molecular features. We use ideas from Bayesian nonparametrics to automatically infer the appropriate number of these latent characteristics. The resulting analysis couples high predictive performance with interpretability since each latent characteristic involves a typically small set of drugs, cell lines and genomic features. Our model uncovers a number of drug-gene sensitivity associations missed by single gene analyses. We functionally validate one such novel association: that increased expression of the cell-cycle regulator C/EBPδ decreases sensitivity to the histone deacetylase (HDAC) inhibitor panobinostat.

Indexed as

Antineoplastic AgentsBayes TheoremBiomarkers, PharmacologicalCCAAT-Enhancer-Binding Protein-deltaCell Line, TumorDNA Copy Number VariationsForecastingGenomeGenomicsHistone Deacetylase InhibitorsHumansNeoplasmsPanobinostatRegression AnalysisStatistics, NonparametricAntineoplastic AgentsBiomarkers, PharmacologicalCCAAT-Enhancer-Binding Protein-deltaCEBPD protein, humanHistone Deacetylase InhibitorsPanobinostat

Identifiers

PMID31136571
PMCPMC6555538
OpenAlexW2947230856

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.