Evidence map›Paper›PMID 41164943›Full record

ArticleCell proliferation2026

Decoding the Role of Caveolin-1 in Morphological Diversity and Self-Renewal of Breast Cancer Cells.

Shun Li, Hongyun Duan, Lu Yang, Lingyi Jiang, Haocheng Bian, Yuqin Jiang, Yixi Zhang, Wei Yan, Qin Yang, Tingting Li and 5 more

Abstract read
In one paragraph

Article in Cell proliferation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

15 authors.

Shun LiDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Hongyun DuanMOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Lu YangDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Lingyi JiangDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Haocheng BianDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yuqin JiangDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yixi ZhangDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Wei YanDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Qin YangDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Tingting LiDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Xiang QinDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Zong-Yuan LiuDepartment of Engineering Mechanics, Institute of Biomechanics and Medical Engineering, Tsinghua University, Beijing, China.
Ningwei SunDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Kai-Fu YangMOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yiyao LiuDepartment of Oncology & Cancer Institute, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, and School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.ORCID https://orcid.org/0000-0002-7786-7361

Funding

Fundamental Research Funds for the Central Universities ZYGX2022J025National Natural Science Foundation of China 12132004National Natural Science Foundation of China 12272086National Natural Science Foundation of China 12472318National Natural Science Foundation of China 32171309National Natural Science Foundation of China 32471364National Natural Science Foundation of China 32471367Natural Science Foundation of Sichuan Province 2024NSFSC0601Program for Innovative Fundamental Research Incubation of UESTC Y03023206100226
6 · The paper itself

Abstract

Cellular geometry is tightly associated with the function of a cell. During tumour progression, cancer cells undergo changes in phenotypes and biological behaviour with deformations in cellular morphology. However, whether the morphological diversity of cancer cells correlates with the cellular phenotype, and the underlying mechanism of morphology-related function in cancer cells is still unclear. Here, we simplified the cellular morphology by clustering cancer cells into three categories based on two-dimensional cellular morphological features. The silence of caveolin-1 (Cav-1), the primary constituent of membrane caveolae, reproduced the morphological evolutionary behaviour of cancer cells, which is similar to the epithelial-mesenchymal transition process. The attenuation of dorsal stress fibres, the assembly of focal adhesions and the disorder of transverse arc fibres and their regulatory signals are demonstrated as the main morphological evolutionary tools of cancer cells. Moreover, a modified vertex model theoretically reconfirmed the evolutionary process of cellular morphology. Small GTPases and focal adhesion kinase signalling were implicated in Cav-1 knockdown-induced cytoskeletal remodelling and focal adhesion assembly. Both in vitro and in vivo studies have demonstrated that Cav-1-dependent morphological changes are closely associated with the self-renewal capacity of breast cancer cells. Overall, our work highlights new insight into the morphological diversity and the correlation between cellular shape and phenotype of cancer cells, and provides evidence that Cav-1 could affect cancer cell properties such as self-renewal capacity through maintaining the morphological stability.

Indexed as

Breast NeoplasmsCaveolin 1Cell Self RenewalAnimalsCell Line, TumorCell ProliferationCell ShapeEpithelial-Mesenchymal TransitionFemaleFocal AdhesionsHumansMiceSignal TransductionCAV1 protein, humanCaveolin 1cancer cell morphologycaveolin‐1cytoskeleton rebuildingfocal adhesionsself‐renewal ability

Identifiers

PMID41164943
PMCPMC13114796

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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.