Evidence map›Paper›PMID 31990579›Full record

ArticleJCO clinical cancer informatics2020

Evidence-Based Network Approach to Recommending Targeted Cancer Therapies.

Jayaram Kancherla, Shruti Rao, Krithika Bhuvaneshwar, Rebecca B Riggins, Robert A Beckman, Subha Madhavan, Héctor Corrada Bravo, Simina M Boca

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JCO clinical cancer informatics, 2020. 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
–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

7 citing papers in PubMed.

  1. Article
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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

8 authors.

Jayaram KancherlaUniversity of Maryland, College Park, MD.
Shruti RaoGeorgetown University, Washington, DC.
Krithika BhuvaneshwarGeorgetown University, Washington, DC.
Rebecca B RigginsGeorgetown University, Washington, DC.
Robert A BeckmanGeorgetown University, Washington, DC.
Subha MadhavanGeorgetown University, Washington, DC.
Héctor Corrada BravoUniversity of Maryland, College Park, MD.
Simina M BocaUniversity of Maryland, College Park, MD.

Funding

Tissue Culture Shared ResourceP30CA051008 · NCI · GEORGETOWN UNIVERSITY · PI Louis M Weiner · 1990 to 2026
$71.5M
The Clinical Genome Resource - Expert Curation and EHR IntegrationU41HG009650 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERG, JONATHAN S · 2017 to 2020
$13.3M
A Knowledge Base for Clinically Relevant Genes and VariantsU01HG007437 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERG, JONATHAN S, EVANS, JAMES PHILIP · 2013 to 2016
$9.0M
Standardized and Genome-Wide Clinical Interpretation of Complex Genotypes for Cancer Precision MedicineU24CA237719 · NCI · WASHINGTON UNIVERSITY · PI GRIFFITH, OBI L. · 2019 to 2023
$3.8M
Illuminating Neurodevelopment through Integrated Analysis and Vizualization of Multi-Omic DataR24MH114815 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI HERTZANO, RONNA, WHITE, OWEN R · 2018 to 2020
$2.3M
Integrative Visual and Computational Exploratory Analysis of Genomics DataR01GM114267 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI CORRADA BRAVO, HECTOR · 2015 to 2018
$1.8M
Integration of 3D primary tumor drug-profiling with patient-specific drug gene networks for recommending targeted cancer therapies (2 of 2).R21CA220398 · NCI · GEORGETOWN UNIVERSITY · PI BOCA, SIMINA MARIA · 2017 to 2019
$497k
NCI NIH HHS P30 CA051008NCI NIH HHS R21 CA220398NCI NIH HHS U24 CA237719NHGRI NIH HHS U01 HG007437NHGRI NIH HHS U41 HG009650NIGMS NIH HHS R01 GM114267NIMH NIH HHS R24 MH114815
6 · The paper itself

Abstract

purposeIn this work, we introduce CDGnet (Cancer-Drug-Gene Network), an evidence-based network approach for recommending targeted cancer therapies. CDGnet represents a user-friendly informatics tool that expands the range of targeted therapy options for patients with cancer who undergo molecular profiling by including the biologic context via pathway information.

methodsCDGnet considers biologic pathway information specifically by looking at targets or biomarkers downstream of oncogenes and is personalized for individual patients via user-inputted molecular alterations and cancer type. It integrates a number of different sources of knowledge: patient-specific inputs (molecular alterations and cancer type), US Food and Drug Administration-approved therapies and biomarkers (curated from DailyMed), pathways for specific cancer types (from Kyoto Encyclopedia of Genes and Genomes [KEGG]), gene-drug connections (from DrugBank), and oncogene information (from KEGG). We consider 4 different evidence-based categories for therapy recommendations. Our tool is delivered via an R/Shiny Web application. For the 2 categories that use pathway information, we include an interactive Sankey visualization built on top of d3.js that also provides links to PubChem.

resultsWe present a scenario for a patient who has estrogen receptor (ER)-positive breast cancer with

conclusionCDGnet provides results in a number of easily accessible and usable forms, separating targeted cancer therapies into categories in an evidence-based manner that incorporates biologic pathway information.

Indexed as

Evidence-Based MedicineGene Regulatory NetworksMolecular Targeted TherapyPrecision MedicineAntineoplastic AgentsBiomarkers, TumorHumansNeoplasmsPatient SelectionAntineoplastic AgentsBiomarkers, Tumor

Identifiers

PMID31990579
PMCPMC6995264

What OpenQuestion holds

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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.