Evidence map›Paper›PMID 32407979›Full record

ArticleMolecular and cellular endocrinology2020

Reciprocal fine-tuning of progesterone and prolactin-regulated gene expression in breast cancer cells.

Sean M Holloran, Bakhtiyor Nosirov, Katherine R Walter, Gloria M Trinca, Zhao Lai, Victor X Jin, Christy R Hagan

Open access · greenAbstract read
In one paragraph

Article in Molecular and cellular endocrinology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 37% 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, 17 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

7 authors at 3 institutions in 1 country.

Sean M HolloranDepartment of Biochemistry and Molecular Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA; Department of Cancer Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Bakhtiyor NosirovDepartment of Molecular Medicine, University of Texas Health San Antonio (UTHSA), San Antonio, TX, 78229, USA.
Katherine R WalterDepartment of Biochemistry and Molecular Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA; Department of Cancer Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Gloria M TrincaDepartment of Biochemistry and Molecular Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA; Department of Cancer Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Zhao LaiDepartment of Molecular Medicine, University of Texas Health San Antonio (UTHSA), San Antonio, TX, 78229, USA; Greehey Children's Cancer Research Institute, University of Texas Health San Antonio (UTHSA), San Antonio, TX, 78229, USA.
Victor X JinDepartment of Molecular Medicine, University of Texas Health San Antonio (UTHSA), San Antonio, TX, 78229, USA.
Christy R HaganDepartment of Biochemistry and Molecular Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA; Department of Cancer Biology, University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA. Electronic address: chagan@kumc.edu.
The University of Texas Health Science Center at San Antonio · USThe University of Kansas Cancer Center · USUniversity of Kansas Medical Center · US

Funding

Mentoring CoreP20GM103418 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Douglas E Wright · 2012 to 2026
$63.0M
Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
Systems Analysis of Epigenomic Architecture in Cancer ProgressionU54CA217297 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI KIRMA, NAMEER · 2017 to 2021
$9.3M
Omics analysis of three-dimensional transcriptional regulationR01GM114142 · NIGMS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI JIN, VICTOR, LIN, SHILI · 2015 to 2024
$2.7M
CK2-dependent phosphorylation of Progesterone Receptors mediates proliferative signaling in breast cancerR00CA166643 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI HAGAN, CHRISTY · 2015 to 2017
$747k
High Throughput DNA Sequencer: Illumina HiSeq 3000 SequencerS10OD021805 · OD · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI LAI, ZHAO · 2016 to 2016
$600k
Department of Defense BCRP W81XWH-16-1-0320NCI NIH HHS P30 CA168524NCI NIH HHS R00 CA166643NCI NIH HHS U54 CA217297NIGMS NIH HHS P20 GM103418NIGMS NIH HHS R01 GM114142NIH HHS 1S10OD021805-01NIH HHS S10 OD021805
6 · The paper itself

Abstract

Progesterone and prolactin are two key hormones involved in development and remodeling of the mammary gland. As such, both hormones have been linked to breast cancer. Despite the overlap between biological processes ascribed to these two hormones, little is known about how co-expression of both hormones affects their individual actions. Progesterone and prolactin exert many of their effects on the mammary gland through activation of gene expression, either directly (progesterone, binding to the progesterone receptor [PR]) or indirectly (multiple transcription factors being activated downstream of prolactin, most notably STAT5). Using RNA-seq in T47D breast cancer cells, we characterized the gene expression programs regulated by progestin and prolactin, either alone or in combination. We found significant crosstalk and fine-tuning between the transcriptional programs executed by each hormone independently and in combination. We divided and characterized the transcriptional programs into four broad categories. All crosstalk/fine-tuning shown to be modulated by progesterone was dependent upon the expression of PR. Moreover, PR was recruited to enhancer regions of all regulated genes. Interestingly, despite the canonical role for STAT5 in transducing prolactin-signaling in the normal and lactating mammary gland, very few of the prolactin-regulated transcriptional programs fine-tuned by progesterone in this breast cancer cell line model system were in fact dependent upon STAT5. Cumulatively, these data suggest that the interplay of progesterone and prolactin in breast cancer impacts gene expression in a more complex and nuanced manner than previously thought, and likely through different transcriptional regulators than those observed in the normal mammary gland. Studying gene regulation when both hormones are present is most clinically relevant, particularly in the context of breast cancer.

Indexed as

Gene Expression Regulation, NeoplasticBreast NeoplasmsCell Line, TumorFemaleGene OntologyHumansProgesteroneProlactinReceptors, ProgesteroneSTAT5 Transcription FactorTranscription, GeneticProgesteroneProlactinReceptors, ProgesteroneSTAT5 Transcription FactorBreast cancerGene expressionProgesterone receptorProlactin

Identifiers

PMID32407979
PMCPMC8941988
OpenAlexW3024487183

What OpenQuestion holds

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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 OpenQuestion graph.