Evidence map›Paper›PMID 31508508›Full record

ArticleCommunications biology2019

pathCHEMO, a generalizable computational framework uncovers molecular pathways of chemoresistance in lung adenocarcinoma.

Nusrat J Epsi, Sukanya Panja, Sharon R Pine, Antonina Mitrofanova

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2019. 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
1.4field-weighted citation impact, top 17% 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, 13 citations in OpenAlex.

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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

4 authors at 1 institution in 2 countries.

Nusrat J Epsi1Department of Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ 07107 USA.ORCID 0000-0001-5363-075X
Sukanya Panja1Department of Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ 07107 USA.
Sharon R Pine2Departments of Pharmacology and Medicine, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ 08901 USA.ORCID 0000-0001-5318-0277
Antonina Mitrofanova1Department of Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ 07107 USA.ORCID 0000-0003-0671-6512
Rutgers, The State University of New Jersey · US

Funding

Sox9 signaling in lung adenocarcinomaR01CA190578 · NCI · RBHS -CANCER INSTITUTE OF NEW JERSEY · PI PINE, SHARON R. · 2014 to 2018
$1.7M
NCI NIH HHS R01 CA190578
6 · The paper itself

Abstract

Despite recent advances in discovering a wide array of novel chemotherapy agents, identification of patients with poor and favorable chemotherapy response prior to treatment administration remains a major challenge in clinical oncology. To tackle this challenge, we present a generalizable genome-wide computational framework pathCHEMO that uncovers interplay between transcriptomic and epigenomic mechanisms altered in biological pathways that govern chemotherapy response in cancer patients. Our approach is tested on patients with lung adenocarcinoma who received adjuvant standard-of-care doublet chemotherapy (i.e., carboplatin-paclitaxel), identifying seven molecular pathway markers of primary treatment response and demonstrating their ability to predict patients at risk of carboplatin-paclitaxel resistance in an independent patient cohort (log-rank

Indexed as

Computational BiologyDrug Resistance, NeoplasmSignal TransductionSoftwareAdenocarcinoma of LungAntineoplastic AgentsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansModels, BiologicalReproducibility of ResultsROC CurveAntineoplastic AgentsComputational modelsLung cancerPredictive medicine

Identifiers

PMID31508508
PMCPMC6731276
OpenAlexW2972287571

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.