Evidence map›Paper›PMID 31655920›Full record

ArticleBreast cancer research and treatment2020

Molecular determinants of drug response in TNBC cell lines.

Nathan M Merrill, Eric J Lachacz, Nathalie M Vandecan, Peter J Ulintz, Liwei Bao, John P Lloyd, Joel A Yates, Aki Morikawa, Sofia D Merajver, Matthew B Soellner

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Breast cancer research and treatment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 18% 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, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. 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

10 authors at 1 institution in 1 country.

Nathan M MerrillDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Eric J LachaczDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Nathalie M VandecanDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Peter J UlintzDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Liwei BaoDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
John P LloydDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Joel A YatesDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Aki MorikawaDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA.
Sofia D MerajverDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA. smerajve@med.umich.edu.
Matthew B SoellnerDepartment of Internal Medicine, University of Michigan, 1500 Medical Center Dr, Ann Arbor, MI, 48109, USA. soellner@med.umich.edu.ORCID http://orcid.org/0000-0003-1394-8645
University of Michigan · US

Funding

Conformational Control of Protein KinasesR01GM125881 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MATTHEW B SOELLNER · 2017 to 2026
$2.5M
Artificial Intelligence driven prediction of brain metastasis from primary tumor sites at diagnosisR21CA245597 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MERAJVER, SOFIA DIANA · 2020 to 2021
$401k
Integrative signaling to increase efficacy of targeted therapies for triple negative breast cancerR21CA218498 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MERAJVER, SOFIA DIANA, SOELLNER, MATTHEW B · 2017 to 2018
$373k
NCI NIH HHS R21 CA218498NCI NIH HHS R21CA218498NCI NIH HHS R21 CA245597NIGMS NIH HHS R01 GM125881
6 · The paper itself

Abstract

purposeThere is a need for biomarkers of drug efficacy for targeted therapies in triple-negative breast cancer (TNBC). As a step toward this, we identify multi-omic molecular determinants of anti-TNBC efficacy in cell lines for a panel of oncology drugs.

methodsUsing 23 TNBC cell lines, drug sensitivity scores (DSS

resultsSix molecular determinant panels were obtained from 12 drugs we prioritized based on their efficacy. Determinant panels were largely devoid of DNA mutations of the targeted pathway. Molecular determinants were obtained by correlating DSS

conclusionsThese findings demonstrate an integrated method to identify biomarkers of drug efficacy in TNBC where DNA predictions correlate poorly with drug response. Our work outlines a framework for the identification of novel molecular determinants and optimal companion drugs for combination therapy based on these correlates.

Indexed as

Drug Resistance, NeoplasmAntineoplastic AgentsAntineoplastic Combined Chemotherapy ProtocolsCell Line, TumorComputational BiologyDose-Response Relationship, DrugDrug Screening Assays, AntitumorFemaleGene Expression ProfilingHumansMutationProteomicsTreatment OutcomeTriple Negative Breast NeoplasmsAntineoplastic AgentsCombination therapyFunctional proteomicsMolecular determinantsSequencingTriple-negative breast cancer

Identifiers

PMID31655920
PMCPMC7323911
OpenAlexW2981431511

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.