Evidence map›Paper›PMID 39702552›Full record

ArticleNPJ breast cancer2024

The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer.

Zheqi Li, Fangyuan Chen, Li Chen, Jiebin Liu, Danielle Tseng, Fazal Hadi, Soleilmane Omarjee, Kamal Kishore, Joshua Kent, Joanna Kirkpatrick and 9 more

Abstract read
In one paragraph

Article in NPJ breast cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

19 authors.

Zheqi Li *Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.ORCID http://orcid.org/0000-0003-1213-640X
Fangyuan Chen *School of Medicine, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-9891-4753
Li Chen *Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA.
Jiebin LiuWomen's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.
Danielle TsengWomen's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.
Fazal HadiAstraZeneca, The Discovery Centre, Biomedical Campus, Cambridge, UK.
Soleilmane OmarjeeCancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.
Kamal KishoreCancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.
Joshua KentCancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.
Joanna KirkpatrickCancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.
Clive D'SantosCancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.
Mandy LawsonAstraZeneca, The Discovery Centre, Biomedical Campus, Cambridge, UK.
Jason GertzDepartment of Oncological Sciences, University of Utah, Salt Lake City, UT, USA.
Matthew J SikoraDepartment of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID http://orcid.org/0000-0003-2915-7442
Donald P McDonnellDepartment of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC, USA.
Jason S CarrollCancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-3643-0080
Kornelia PolyakDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.ORCID http://orcid.org/0000-0002-5964-0382
Steffi OesterreichWomen's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-2537-6923
Adrian V LeeWomen's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA, USA. leeav@upmc.edu.ORCID http://orcid.org/0000-0001-9917-514X

Funding

VECTOR CORE FACILITYP30CA047904 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Dan Paul Zandberg · 1988 to 2026
$158.0M
Estrogen receptor fusions genes as drivers of endocrine resistance in breast cancerR01CA256161 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V, OESTERREICH, STEFFI · 2021 to 2025
$2.8M
Manipulating normal estrogen physiology as a therapeutic approach in cancerR01CA276089 · NCI · DUKE UNIVERSITY · PI Donald P McDonnell · 2023 to 2026
$2.2M
Mechanism-based strategies to target ER-mutant endocrine resistant breast cancerR01CA221303 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI OESTERREICH, STEFFI · 2018 to 2022
$2.0M
MDC1: central regulator of estrogen receptor function and therapy response in lobular carcinomaR01CA251621 · NCI · UNIVERSITY OF COLORADO DENVER · PI SIKORA, MATTHEW J · 2022 to 2025
$1.8M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
Cancer Research UK 20411Cancer Research UK (CRUK) DRCPGM\100088NCI NIH HHS P30 CA047904NCI NIH HHS R01 CA221303NCI NIH HHS R01 CA251621NCI NIH HHS R01 CA256161NCI NIH HHS R01 CA276089NIH HHS S10 OD028483Susan G. Komen (Susan G. Komen Breast Cancer Foundation) SAC110021Susan G. Komen (Susan G. Komen Breast Cancer Foundation) SAC160073Susan G. Komen (Susan G. Komen Breast Cancer Foundation) SAC180085University of Cambridge A20411, A31344, A29580U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01256161U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01CA221303U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) R01CA251621
6 · The paper itself

Abstract

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities ( https://estrogeneii.web.app/ ). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed transcriptomic landscape and substantial diversity in response to different classes of ER modulators. Endocrine-resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signalings, which is recapitulated clinically. Dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of cell model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer's response to endocrine therapies and explore resistance mechanisms.

Identifiers

PMID39702552
PMCPMC11659402

What Socratic holds

Textmetadata
LicenceCC BY
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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.