Evidence map›Paper›PMID 33099086›Full record

ArticleEBioMedicine2020

Genome-wide analysis of therapeutic response uncovers molecular pathways governing tamoxifen resistance in ER+ breast cancer.

Sarra M Rahem, Nusrat J Epsi, Frederick D Coffman, Antonina Mitrofanova

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

Article in EBioMedicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

8 citing papers in PubMed, 42 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.

Sarra M RahemDepartment of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA.
Nusrat J EpsiDepartment of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA.
Frederick D CoffmanDepartment of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA; Department of Physician Assistant Studies and Practice, USA; Department of Pathology & Laboratory Medicine, New Jersey Medical School, Newark, New Jersey 07107, USA.
Antonina MitrofanovaDepartment of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, New Jersey 08901, USA. Electronic address: amitrofa@shp.rutgers.edu.
Rutgers, The State University of New Jersey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrioritization of breast cancer patients based on the risk of resistance to tamoxifen plays a significant role in personalized therapeutic planning and improving disease course and outcomes.

methodsIn this work, we demonstrate that a genome-wide pathway-centric computational framework elucidates molecular pathways as markers of tamoxifen resistance in ER+ breast cancer patients. In particular, we associated activity levels of molecular pathways with a wide spectrum of response to tamoxifen, which defined markers of tamoxifen resistance in patients with ER+ breast cancer.

findingsWe identified five biological pathways as markers of tamoxifen failure and demonstrated their ability to predict the risk of tamoxifen resistance in two independent patient cohorts (Test cohort1: log-rank p-value = 0.02, adjusted HR = 3.11; Test cohort2: log-rank p-value = 0.01, adjusted HR = 4.24). We have shown that these pathways are not markers of aggressiveness and outperform known markers of tamoxifen response. Furthermore, for adoption into clinic, we derived a list of pathway read-out genes and their associated scoring system, which assigns a risk of tamoxifen resistance for new incoming patients.

interpretationWe propose that the identified pathways and their read-out genes can be utilized to prioritize patients who would benefit from tamoxifen treatment and patients at risk of tamoxifen resistance that should be offered alternative regimens.

fundingThis work was supported by the Rutgers SHP Dean's research grant, Rutgers start-up funds, Libyan Ministry of Higher Education and Scientific Research, and Katrina Kehlet Graduate Award from The NJ Chapter of the Healthcare Information Management Systems Society.

Indexed as

Biomarkers, TumorSignal TransductionAntineoplastic Agents, HormonalBreast NeoplasmsDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticGenome-Wide Association StudyHumansReceptors, EstrogenROC CurveTamoxifenAntineoplastic Agents, HormonalBiomarkers, TumorReceptors, EstrogenTamoxifenBreast cancerPathway markersTamoxifenTherapeutic resistance

Identifiers

PMID33099086
PMCPMC7585053
OpenAlexW3094190349

What Socratic holds

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LicenceCC BY-NC-ND
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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.