Evidence map›Paper›PMID 31548386›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Discovering long noncoding RNA predictors of anticancer drug sensitivity beyond protein-coding genes.

Aritro Nath, Eunice Y T Lau, Adam M Lee, Paul Geeleher, William C S Cho, R Stephanie Huang

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–field-weighted citation impact
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

33 citing papers in PubMed.

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  12. Methylation-Regulated Long Non-Coding RNA Expression in Ulcerative Colitis.International journal of molecular sciences · 2023
    Article
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  19. Long Non-Coding RNAInternational journal of molecular sciences · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Aritro NathDepartment of Experimental and Clinical Pharmacology, University of Minnesota Minneapolis, MN 55455.ORCID 0000-0002-3225-4203
Eunice Y T LauDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong SAR, China.
Adam M LeeDepartment of Experimental and Clinical Pharmacology, University of Minnesota Minneapolis, MN 55455.
Paul GeeleherDepartment of Computational Biology, St. Jude Children's Research Hospital Memphis, TN 38105.
William C S ChoDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong SAR, China.
R Stephanie HuangDepartment of Experimental and Clinical Pharmacology, University of Minnesota Minneapolis, MN 55455; rshuang@umn.edu.

Funding

Drug repurposing in breast cancerR01CA204856 · NCI · UNIVERSITY OF MINNESOTA · PI HUANG, RONG STEPHANIE · 2018 to 2022
$2.2M
NCI NIH HHS R01 CA204856
6 · The paper itself

Abstract

Large-scale cancer cell line screens have identified thousands of protein-coding genes (PCGs) as biomarkers of anticancer drug response. However, systematic evaluation of long noncoding RNAs (lncRNAs) as pharmacogenomic biomarkers has so far proven challenging. Here, we study the contribution of lncRNAs as drug response predictors beyond spurious associations driven by correlations with proximal PCGs, tissue lineage, or established biomarkers. We show that, as a whole, the lncRNA transcriptome is equally potent as the PCG transcriptome at predicting response to hundreds of anticancer drugs. Analysis of individual lncRNAs transcripts associated with drug response reveals nearly half of the significant associations are in fact attributable to proximal

Indexed as

Antineoplastic AgentsCell Line, TumorDrug Screening Assays, AntitumorErlotinib HydrochlorideGene Expression Regulation, NeoplasticGenome, HumanHumansLung NeoplasmsMutationRNA, Long NoncodingSurvival AnalysisTranscriptomeAntineoplastic AgentsErlotinib HydrochlorideRNA, Long Noncodingdrug response predictionlong noncoding RNAmachine learningpharmacogenomics

Identifiers

PMID31548386
PMCPMC6825320

What OpenQuestion holds

Textmetadata
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.