Binding blockade between TLN1 and integrin β1 represses triple-negative breast cancer

  1. Yixiao Zhang
  2. Lisha Sun  Is a corresponding author
  3. Haonan Li
  4. Liping Ai
  5. Qingtian Ma
  6. Xinbo Qiao
  7. Jie Yang
  8. Hao Zhang
  9. Xunyan Ou
  10. Yining Wang
  11. Guanglei Chen
  12. Jinqi Xue
  13. Xudong Zhu
  14. Yu Zhao
  15. Yongliang Yang  Is a corresponding author
  16. Caigang Liu  Is a corresponding author
  1. Shengjing Hospital of China Medical University, China
  2. Dalian University of Technology, China
  3. Mayo Clinic, United States

Abstract

Background: Integrin family are known as key gears in focal adhesion for triple-negative breast cancer (TNBC) metastasis. However, the integrin independent factor TLN1 remains vague in TNBC.

Methods: Bioinformatics analysis was performed based on TCGA database and Shengjing Hospital cohort. Western blot and RT-PCR were used to detect the expression of TLN1 and integrin pathway in cells. A small-molecule C67399 was screened for blocking TLN1 and integrin β1 through a novel computational screening approach by targeting the protein-protein binding interface. Drug pharmacodynamics were determined through xenograft assay.

Results: Upregulation of TLN1 in TNBC samples correlates with metastasis and worse prognosis. Silencing TLN1 in TNBC cells significantly attenuated the migration of tumour cells through interfering the dynamic formation of focal adhesion with integrin β1, thus regulating FAK-AKT signal pathway and epithelial-mesenchymal transformation. Targeting the binding between TLN1 and integrin β1 by C67399 could repress metastasis of TNBC.

Conclusions: TLN1 overexpression contributes to TNBC metastasis and C67399 targeting TLN1 may hold promise for TNBC treatment.

Funding: This study was supported by grants from the National Natural Science Foundation of China (No. 81872159, 81902607, 81874301), Liaoning Colleges Innovative Talent Support Program (Name: Cancer Stem Cell Origin and Biological Behaviour), Outstanding Scientific Fund of Shengjing Hospital (201803) and Outstanding Young Scholars of Liaoning Province (2019-YQ-10).

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Yixiao Zhang

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  2. Lisha Sun

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    For correspondence
    sunlisha1224@126.com
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4095-5026
  3. Haonan Li

    School of Bioengineering, Dalian University of Technology, Dalian, China
    Competing interests
    No competing interests declared.
  4. Liping Ai

    Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  5. Qingtian Ma

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  6. Xinbo Qiao

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6759-921X
  7. Jie Yang

    Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  8. Hao Zhang

    Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  9. Xunyan Ou

    Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  10. Yining Wang

    Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  11. Guanglei Chen

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  12. Jinqi Xue

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  13. Xudong Zhu

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    Competing interests
    No competing interests declared.
  14. Yu Zhao

    Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, United States
    Competing interests
    No competing interests declared.
  15. Yongliang Yang

    School of Bioengineering, Dalian University of Technology, Dalian, China
    For correspondence
    everbright99@foxmail.com
    Competing interests
    No competing interests declared.
  16. Caigang Liu

    Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    For correspondence
    angel-s205@163.com
    Competing interests
    Caigang Liu, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3729-2839

Funding

National Natural Science Foundation of China (81872159)

  • Caigang Liu

Liaoning Colleges Innovative Talent Support Program (Cancer Stem Cell Origin and Biological Behavior)

  • Caigang Liu

Outstanding Scientific Fund of Shengjing Hospital (201803)

  • Caigang Liu

Outstanding Young Scholars of Liaoning Province (2019-YQ-10)

  • Caigang Liu

National Natural Science Foundation of China (81902607)

  • Yixiao Zhang

National Natural Science Foundation of China (81874301)

  • Yongliang Yang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: The current study was approved by the institutional research ethics committee of Shengjing Hospital of China Medical University (Project identification code: 2018PS304K, date on 03/05/2018), and each participant signed an informed consent before being included in the study. Meanwhile, this study was performed in very strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All surgery was performed under sodium pentobarbital anesthesia, and every effort was made to minimize suffering of the animals, and all the animals were handled according to approved Animal Ethics and Experimentation Committee protocols of Shengjing Hospital of China Medical University (Project identification code: 2018PS312K, date on 03/05/2018).

Human subjects: Written informed consent was obtained from all the patients, and this study was approved by the institutional research ethics committee of China Medical University

Copyright

© 2022, Zhang et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,408
    views
  • 233
    downloads
  • 13
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Yixiao Zhang
  2. Lisha Sun
  3. Haonan Li
  4. Liping Ai
  5. Qingtian Ma
  6. Xinbo Qiao
  7. Jie Yang
  8. Hao Zhang
  9. Xunyan Ou
  10. Yining Wang
  11. Guanglei Chen
  12. Jinqi Xue
  13. Xudong Zhu
  14. Yu Zhao
  15. Yongliang Yang
  16. Caigang Liu
(2022)
Binding blockade between TLN1 and integrin β1 represses triple-negative breast cancer
eLife 11:e68481.
https://doi.org/10.7554/eLife.68481

Share this article

https://doi.org/10.7554/eLife.68481

Further reading

    1. Medicine
    Mitsuru Sugimoto, Tadayuki Takagi ... Hiromasa Ohira
    Research Article

    Background:

    Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a severe and deadly adverse event following ERCP. The ideal method for predicting PEP risk before ERCP has yet to be identified. We aimed to establish a simple PEP risk score model (SuPER model: Support for PEP Reduction) that can be applied before ERCP.

    Methods:

    This multicenter study enrolled 2074 patients who underwent ERCP. Among them, 1037 patients each were randomly assigned to the development and validation cohorts. In the development cohort, the risk score model for predicting PEP was established via logistic regression analysis. In the validation cohort, the performance of the model was assessed.

    Results:

    In the development cohort, five PEP risk factors that could be identified before ERCP were extracted and assigned weights according to their respective regression coefficients: –2 points for pancreatic calcification, 1 point for female sex, and 2 points for intraductal papillary mucinous neoplasm, a native papilla of Vater, or the pancreatic duct procedures (treated as ‘planned pancreatic duct procedures’ for calculating the score before ERCP). The PEP occurrence rate was 0% among low-risk patients (≤0 points), 5.5% among moderate-risk patients (1–3 points), and 20.2% among high-risk patients (4–7 points). In the validation cohort, the C statistic of the risk score model was 0.71 (95% CI 0.64–0.78), which was considered acceptable. The PEP risk classification (low, moderate, and high) was a significant predictive factor for PEP that was independent of intraprocedural PEP risk factors (precut sphincterotomy and inadvertent pancreatic duct cannulation) (OR 4.2, 95% CI 2.8–6.3; p<0.01).

    Conclusions:

    The PEP risk score allows an estimation of the risk of PEP prior to ERCP, regardless of whether the patient has undergone pancreatic duct procedures. This simple risk model, consisting of only five items, may aid in predicting and explaining the risk of PEP before ERCP and in preventing PEP by allowing selection of the appropriate expert endoscopist and useful PEP prophylaxes.

    Funding:

    No external funding was received for this work.

    1. Medicine
    Yao Li, Hui Xin ... Wei Zhang
    Research Article

    Estrogen significantly impacts women’s health, and postmenopausal hypertension is a common issue characterized by blood pressure fluctuations. Current control strategies for this condition are limited in efficacy, necessitating further research into the underlying mechanisms. Although metabolomics has been applied to study various diseases, its use in understanding postmenopausal hypertension is scarce. Therefore, an ovariectomized rat model was used to simulate postmenopausal conditions. Estrogen levels, blood pressure, and aortic tissue metabolomics were analyzed. Animal models were divided into Sham, OVX, and OVX +E groups. Serum estrogen levels, blood pressure measurements, and aortic tissue metabolomics analyses were performed using radioimmunoassay, UHPLC-Q-TOF, and bioinformatics techniques. Based on the above research content, we successfully established a correlation between low estrogen levels and postmenopausal hypertension in rats. Notable differences in blood pressure parameters and aortic tissue metabolites were observed across the experimental groups. Specifically, metabolites that were differentially expressed, particularly L-alpha-aminobutyric acid (L-AABA), showed potential as a biomarker for postmenopausal hypertension, potentially exerting a protective function through macrophage activation and vascular remodeling. Enrichment analysis revealed alterations in sugar metabolism pathways, such as the Warburg effect and glycolysis, indicating their involvement in postmenopausal hypertension. Overall, this current research provides insights into the metabolic changes associated with postmenopausal hypertension, highlighting the role of L-AABA and sugar metabolism reprogramming in aortic tissue. The findings suggest a potential link between low estrogen levels, macrophage function, and vascular remodeling in the pathogenesis of postmenopausal hypertension. Further investigations are needed to validate these findings and explore their clinical implications for postmenopausal women.