Evidence map›Paper›PMID 36686775›Full record

ArticleFrontiers in oncology2022

Separate and combined effects of advanced age and obesity on mammary adipose inflammation, immunosuppression and tumor progression in mouse models of triple negative breast cancer.

Laura A Smith, Dalton M Craven, Magdalena A Rainey, Alyssa J Cozzo, Meredith S Carson, Elaine M Glenny, Nishita Sheth, Shannon B McDonell, Erika T Rezeli, Stephanie A Montgomery and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. 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
1.6field-weighted citation impact, top 15% 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, 8 citations in OpenAlex.

  1. Review
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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

13 authors at 1 institution in 1 country.

Laura A SmithDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Dalton M CravenDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Magdalena A RaineyDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Alyssa J CozzoDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Meredith S CarsonDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Elaine M GlennyDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Nishita ShethDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Shannon B McDonellDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Erika T RezeliDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Stephanie A MontgomeryDepartment of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Laura W BowersDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Michael F ColemanDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Stephen D HurstingDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
University of North Carolina at Chapel Hill · US

Funding

GASTROENTEROLOGY RESEARCH TRAININGT32DK007737 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHEHZAD Z. SHEIKH · 1996 to 2026
$7.8M
Cancer Control Education ProgramT32CA057726 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa B Gilkey, Melissa A. Troester · 2017 to 2026
$3.7M
NCI NIH HHS T32 CA057726NIDDK NIH HHS T32 DK007737
6 · The paper itself

Abstract

Introduction: Advanced age and obesity are independent risk and progression factors for triple negative breast cancer (TNBC), which presents significant public health concerns for the aging population and its increasing burden of obesity. Due to parallels between advanced age- and obesityrelated biology, particularly adipose inflammation, we hypothesized that advanced age and obesity each accelerate mammary tumor growth through convergent, and likely interactive, mechanisms. Methods: To test this hypothesis, we orthotopically transplanted murine syngeneic TNBC cells into the mammary glands of young normoweight control (7 months), young diet-induced obese (DIO), aged normoweight control (17 months), and aged DIO female C57BL/6J mice. Results: Here we report accelerated tumor growth in aged control and young DIO mice, compared with young controls. Transcriptional analyses revealed, with a few exceptions, overlapping patterns of mammary tumor inflammation and tumor immunosuppression in aged control mice and young DIO mice, relative to young controls. Moreover, aged control and young DIO tumors, compared with young controls, had reduced abundance ofcytotoxic CD8 T cells. Finally, DIO in advanced age exacerbated mammary tumor growth, inflammation and tumor immunosuppression. Discussion: These findings demonstrate commonalities in the mechanisms driving TNBC in aged and obese mice, relative to young normoweight controls. Moreover, we found that advanced age and DIO interact to accelerate mammary tumor progression. Given the US population is getting older and more obese, age- and obesity-related biological differences will need to be considered when developing mechanism-based strategies for preventing or controlling breast cancer.

Indexed as

advanced agebreast cancerinflammationobesitytumor immunosuppression

Identifiers

PMID36686775
PMCPMC9846347
OpenAlexW4313584741

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.