Evidence map›Paper›PMID 27551012›Full record

ArticleThe oncologist2016

Metastatic Breast Cancer With ESR1 Mutation: Clinical Management Considerations From the Molecular and Precision Medicine (MAP) Tumor Board at Massachusetts General Hospital.

Aditya Bardia, John A Iafrate, Tilak Sundaresan, Jerry Younger, Valentina Nardi

Open access · bronzeAbstract readCase Reports
In one paragraph

Article in The oncologist, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 21% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Genomic Landscape of Uterine Sarcomas Defined Through Prospective Clinical Sequencing.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020
    Observational
  7. Article
  8. Article
  9. Review
  10. Precision Oncology Decision Support: Current Approaches and Strategies for the Future.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018
    Review
  11. Article
  12. Review
  13. 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

5 authors at 2 institutions in 1 country.

Aditya BardiaMassachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts, USA bardia.aditya@mgh.harvard.edu.
John A IafrateMassachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts, USA.
Tilak SundaresanMassachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts, USA.
Jerry YoungerMassachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts, USA.
Valentina NardiMassachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts, USA.
Massachusetts General Hospital · USHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelled: The last decade in oncology has witnessed impressive response rates with targeted therapies, largely because of collaborative efforts at understanding tumor biology and careful patient selection based on molecular fingerprinting of the tumor. Consequently, there has been a push toward routine molecular genotyping of tumors, and large precision medicine-based clinical trials have been launched to match therapy to the molecular alteration seen in a tumor. However, selecting the "right drug" for an individual patient in clinic is a complex decision-making process, including analytical interpretation of the report, consideration of the importance of the molecular alteration in driving growth of the tumor, tumor heterogeneity, the availability of a matched targeted therapy, efficacy and toxicity considerations of the targeted therapy (compared with standard therapy), and reimbursement issues. In this article, we review the key considerations involved in clinical decision making while reviewing a molecular genotyping report. We present the case of a 67-year-old postmenopausal female with metastatic estrogen receptor-positive (ER+) breast cancer, whose tumor progressed on multiple endocrine therapies. Molecular genotyping of the metastatic lesion revealed the presence of an ESR1 mutation (encoding p.Tyr537Asn), which was absent in the primary tumor. The same ESR1 mutation was also detected in circulating tumor DNA (ctDNA) extracted from her blood. The general approach for interpretation of genotyping results, the clinical significance of the specific mutation in the particular cancer, potential strategies to target the pathway, and implications for clinical practice are reviewed in this article. KEY POINTS: ER+ breast tumors are known to undergo genomic evolution during treatment with the acquisition of new mutations that confer resistance to treatment.ESR1 mutations in the ligand-binding domain of ER can lead to a ligand-independent, constitutively active form of ER and mediate resistance to aromatase inhibitors.ESR1 mutations may be detected by genomic sequencing of tissue biopsies of the metastatic tumor or by sequencing the circulating tumor cells or tumor DNA (ctDNA).Sequencing results may lead to a therapeutic "match" with an existing FDA-approved drug or match with an experimental agent that fits the clinical setting.

Indexed as

AgedAromatase InhibitorsBreast NeoplasmsDrug Resistance, NeoplasmEstrogen Receptor alphaFemaleGenotypeHospitals, GeneralHumansMutationNeoplasm MetastasisNeoplastic Cells, CirculatingPrecision MedicineAromatase InhibitorsESR1 protein, humanEstrogen Receptor alpha

Identifiers

PMID27551012
PMCPMC5016066
OpenAlexW2513858874

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.