Evidence map›Paper›PMID 36765683›Full record

ReviewCancers2023

Cancer-Associated Adipocytes and Breast Cancer: Intertwining in the Tumor Microenvironment and Challenges for Cancer Therapy.

Chenghui Wu, Shuwen Dong, Renhong Huang, Xiaosong Chen

Abstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

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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.

Chenghui WuDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Shuwen DongDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Renhong HuangDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Xiaosong ChenDepartment of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.

Funding

Innovative Research Team of High-Level Local Universities in Shanghai SHSMU-ZDCX20212200National Natural Science Foundation of China 81772797National Natural Science Foundation of China 82072897Science and Technology Commission of Shanghai Municipality Shanghai Sailing Program 21YF1427400Scientific research project of Shanghai Municipal Health Commission 20194Y0419
6 · The paper itself

Abstract

Adipocytes are the main components in breast tissue, and cancer-associated adipocytes (CAAs) are one of the most important components in the tumor microenvironment of breast cancer (BC). Bidirectional regulation was found between CAAs and BC cells. BC facilitates the dedifferentiation of adjacent adipocytes to form CAAs with morphological and biological changes. CAAs increase the secretion of multiple cytokines and adipokines to promote the tumorigenesis, progression, and metastasis of BC by remodeling the extracellular matrix, changing aromatase expression, and metabolic reprogramming, and shaping the tumor immune microenvironment. CAAs are also associated with the therapeutic response of BC and provide potential targets in BC therapy. The present review provides a comprehensive description of the crosstalk between CAAs and BC and discusses the potential strategies to target CAAs to overcome BC treatment resistance.

Indexed as

adipokinesbreast cancercancer-associated adipocytescytokinestreatment resistancetumor microenvironment

Identifiers

PMID36765683
PMCPMC9913307

What OpenQuestion holds

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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 OpenQuestion graph.