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. Department of Oncology, Shengjing Hospital of China Medical University, China
  2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, China
  3. Innovative Cancer Drug Research and Development Engineering Center of Liaoning Province, China
  4. School of Bioengineering, Dalian University of Technology, China
  5. Department of Biochemistry and Molecular Biology, 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).

Editor's evaluation

The paper is of interest to preclinical and translational scientists in the field of breast cancer. It details the identification, characterization and selection of a novel drug candidate, based on the biology of a select target gene, with the premise to rationalize a new therapy for triple-negative breast cancer. The data presented support the proposed hypotheses, and the conclusions are well supported by the results.

https://doi.org/10.7554/eLife.68481.sa0

Introduction

Triple-negative breast cancer (TNBC) is characterized by absence of hormone receptor and human epidermal growth factor receptor 2 (HER2) amplification, which constitutes 15–20% of breast cancers with the highest mortality among all breast cancer subtypes (Arroyo-Crespo et al., 2019; Kim et al., 2018). In contrast to hormone receptor positive breast cancer (luminal subtype), targeted therapy towards TNBC still lacks and conventional chemotherapy remains the standard care for TNBC patients (Wahba and El-Hadaad, 2015). TNBC targeted therapies have been actively developed and approved by FDA, including PARP inhibitors for BRCA-1 mutated breast cancer, perbrolizumab-based immunotherapy, and Sacituzumab for Trop-2 (Vagia et al., 2020), but new therapeutic strategies are urgently needed to tackle this aggressive tumour for TNBC patients.

Unfortunately, the pathogenesis underlying the aggressive behaviour of TNBC is poorly understood. Epithelial-mesenchymal transformation (EMT) induces epithelial cells to acquire mesenchymal phenotypes, resulting in tumour progression and metastasis (Sikandar et al., 2017). Previous studies have proven that progression of EMT is critical for aggression of TNBC (Xu et al., 2012; Zhao et al., 2014). Hence, understanding potential molecular mechanisms will be of great significance to uncover new therapeutic targets for the management of patients with TNBC.

It is well known that invasive cancer cells adhere to extracellular molecules and disrupt the extracellular matrix (ECM) to initiate the metastatic process (Ishaque et al., 2018). TLNs are cytoplasmic adapter proteins essential for integrin-mediated cell adhesion to the ECM. Moreover, TLNs are responsible for the activation of integrins via linking integrins to cytoskeletal actin and coordinating recruitment of microtubules to adhesion sites (Gough and Goult, 2018). Loss of TLNs can impair EMT and the acquisition of cell motility (Thapa et al., 2017). There are two isoforms of TLNs: TLN1 and TLN2 (Gough and Goult, 2018). TLN1 is expressed in almost all tissues, while TLN2 is usually expressed mainly in the heart, brain, testis, and muscle (Debrand et al., 2009; Manso et al., 2013). Most of attention on TLNs has focused on TLN1 due to its essential role in mediating cell adhesion. TLN1 is located in focal adhesion (FA), which regulates integrin signalling and promotes metastasis in different cancers (Desiniotis and Kyprianou, 2011; Hoshino et al., 2015; Klapholz and Brown, 2017; Seguin et al., 2015), including prostate cancer (Jin et al., 2015), colon cancer (Bostanci et al., 2014), and oral squamous cell carcinoma (Lai et al., 2011). However, the biological effect of TLN1 deletion on the malignancy of TNBC as well as the underlying molecular mechanism remains vague.

Recent studies have reported that the auto-inhibition of TLN1 controls cell-ECM (CEM) adhesion, migration, and wound healing in vivo (Haage et al., 2018), and disrupting this auto-inhibition leads to more mature and stable FAs (Haage et al., 2018). Other studies have also shown that the rapid transition between the active and inactive conformations of TLN1 regulates FA turnover, a critical process for cell adhesion and signal transduction (Dedden et al., 2019). Moreover, a previous study found higher TLN1 transcripts in TNBC than in other clinical breast cancer subtypes (Singel et al., 2013). Therefore, disruption of TLN1 might be a potential strategy for cancer therapy.

Herein, we first explored the role of TLN1 in the pathogenesis of TNBC. We investigated the expression of TLN1 in TNBC cells and studied the effects of silencing TLN1 on TNBC cell proliferation, adhesion, and migration in vitro and in vivo. In addition, for the first time, we identified a small-molecule compound through a novel computational screening approach by targeting protein-protein binding interface (CSTPPI) to block the interaction between TLN1 and integrin β1. Moreover, we assessed the interference of small-molecule inhibitors with FAs formation and migration in vitro, as well as the inhibition of tumour size and lung metastasis in vivo. Our findings suggest TLN1/integrin β1 binding as a potential therapeutic target for TNBC.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Cell line (Homo sapiens)MDA-MB-231ATCCATCC Cat# HTB-26, RRID:CVCL_0062
Cell line (Homo sapiens)MCF-7ATCCATCC Cat# CRL-3435, RRID:CVCL_A4AQ
Cell line (Homo sapiens)BT-549ATCCATCC Cat# HTB-122, RRID:CVCL_1092
Cell line (Homo sapiens)SK-BR-3ATCCATCC Cat# HTB-30, RRID:CVCL_0033
Transfected construct (human)TLN1 shRNA #1Sangon BiotechTransfected construct (human)
AntibodyAnti-Vinculin (Rabbit polyclonal)Proteintech, Rosemont, ILCat# 26520–1-AP, RRID:AB_2868558WB (1:1000), IF(1:200)
AntibodyAnti-E-cadherin (Rabbit monoclonal)Cell Signaling Technology, Danvers, MACat# 3195, RRID:AB_2291471WB (1:1000)
AntibodyAnti-N-cadherin (Rabbit polyclonal)Cell Signaling Technology, Danvers, MACat# 4061, RRID:AB_10694647WB (1:1000)
AntibodyAnti-Tubulin α (Rabbit monoclonal)Cell Signaling Technology, Danvers, MACat# 2125, RRID:AB_2619646WB (1:5000)
AntibodyAnti-CK18 (mouse monoclonal)Cell Signaling Technology, Danvers, MACat# 4546, RRID:AB_2134843WB (1:1000)
AntibodyAnti-FAK (Rabbit polyclonal)Cell Signaling Technology, Danvers, MACat# 3285, RRID:AB_2269034WB (1:1000)
AntibodyAnti-GAPDH (Rabbit polyclonal)Proteintech, Rosemont, ILCat# 10494–1-AP, RRID:AB_2263076WB (1:5000)
AntibodyAnti-AKT1 (Rabbit polyclonal)Proteintech, Rosemont, ILCat# 10176–2-AP, RRID:AB_2224574WB (1:1000)
AntibodyAnti-integrin β3 (Rabbit polyclonal)Proteintech, Rosemont, ILCat# 18309–1-AP, RRID:AB_2128759WB (1:1000)
AntibodyAnti-p-AKT1 (sc-81433) (mouse monoclonal)Santa Cruz Biotechnology, Dallas, TXCat# sc-81433, RRID:AB_1125472WB (1:1000)
AntibodyAnti-p-FAK (Tyr397) (Rabbit polyclonal)Immunoway, Plano, TXCat# YP0739, RRID:AB_2904589WB (1:1000)
AntibodyAnti-integrin β1 (Rabbit polyclonal)Sino Biological, ChinaCat# 100562-T46, RRID:AB_2895614WB (1:1000), IF (1:200)
AntibodyAnti-TLN1 (Rabbit monoclonal)Cell Signaling Technology, Danvers, MACat# 4021, RRID:AB_2204018WB (1:1000), IF (1:200), IHC(1:500)
AntibodyGoat Anti-Rabbit IgG H&L Alexa Fluor 488 (Goat polyclonal)Abcam, Waltham, MACat# ab150077, RRID:AB_2630356IF (1:400)
AntibodyGoat Anti-Mouse IgG H&L Alexa Fluor 647 (Goat polyclonal)Abcam, Waltham, MACat# ab150115, RRID:AB_2687948IF (1:400)
Commercial assay or kitCCK-8 kitDojindo, JapanCK04
Commercial assay or kitCell adhesion detection kitBest Bio, Nanjing, ChinaBB-48120
Commercial assay or kitAnnexin-V and propidium iodide (PI) kitBD, San Diego, CA559763
Commercial assay or kitEdU kitRibobio, ChinaC10327
Chemical compound, drugC67399Chemdiv Compond, San Diego, CA4903–2135C38H48O5, 584.79 Da
Software, algorithmSPSSSPSSRRID:SCR_002865
Software, algorithmGraphPad PrismGraphPad PrismRRID:SCR_002798
Software, algorithmImageJImageJRRID:SCR_003070
Software, algorithmPyMOLPyMOLRRID:SCR_000305
Software, algorithmFIPSDockFIPSDockPMID:22961860
OtherDAPI stainUE, ChinaD4054(5 µg/ml)
OtherRhodamine-labelled phalloidin stain (TRITC Phalloidin)Solarbio, ChinaCat# CA1610, RRID:AB_2904593(100 nM)
OtherProtein A/G agarose beadsSanta Cruz Biotechnology, Dallas, TXCat# sc-2003, RRID:AB_10201400(50 µl/sample)

Patients

A total of 171 patients with TNBC were recruited at Shengjing Hospital of China Medical University. Patients with breast cancer were diagnosed based on histological examinations. When the patients underwent radical mastectomy, breast tumour and para-tumour tissues and at least 10 lymph nodes were collected and pathologically examined. The inclusion criteria were as follows: patients had complete clinical data, did not receive chemotherapy or radiotherapy before surgery, no other types of malignant tumours, no severe organ dysfunction, and no bilateral breast cancer. Tissues were fixed in 10% formalin and paraffin-embedded for histological examination and immunohistochemistry. Some tissues were snap-frozen in liquid nitrogen for protein expression analyses. Written informed consent was obtained from all the patients, and this study was approved by the institutional research ethics committee of Shengjing Hospital of China Medical University (Project identification code: 2018PS304K, dated on 03/05/2018).

Immunohistochemistry

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The expression of TLN1 in breast tumour, para-tumour, and metastatic tissues was examined by immunohistochemistry. Briefly, the breast tumour and para-tumour tissue sections (4 μm) were fixed, paraffin-embedded, dewaxed, and rehydrated as mentioned on Histology. The tissue sections were repaired with citrate antigen repair buffer (pH = 6.0) and heating in a microwave for 10 min. After incubating in 3% hydrogen peroxide solution, the sections were blocked with 5% bovine serum albumin (BSA) at 37°C for 1 hr, followed by incubation overnight with primary antibodies against TLN1 (4021; Cell Signaling Technology, Danvers, MA) with final dilution of 1:100. After washing with PBS, the sections were incubated with horseradish peroxidase (HRP)-conjugated goat-anti-IgG at room temperature for 30 min, the binding of which was visualized with 3,3′-diaminobenzidine, and counterstained with haematoxylin before they were mounted and imaged under a light microscope (Olympus, Japan). The intensity and frequency of positively stained cells were evaluated in a blinded manner (Liu et al., 2018).

The immunohistochemical signals were assessed independently by two pathologists in a blinded manner as before (Gu et al., 2018). Briefly, a total of 200 tumour cells in two 400× microscope fields of each specimen were evaluated for the percentages of positively stained cells. The staining intensity was scored as: 0 (colourless), 1 (light yellow), 2 (brownish yellow), or 3 (brown). The percentages of stained cells were scored as: 0 (<5% positive cells), 1 (5–25% positive cells), 2 (26–50% positive cells), 3 (51–75% positive cells), or 4 (>75% positive cells). A final score (intensity × percentage) was calculated and classified as: negative (score of 0), weakly positive (score of 1–4), moderately positive (score of 5–8), or strongly positive expression (score of 9–12). All specimens were stratified as low expression of TLN1 (scores of 0–4) or high expression of TLN1 (scores of 5–12) (Gu et al., 2018).

TCGA analysis

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UALCAN, an interactive web-portal to perform to in-depth analyses of The Cancer Genome Atlas (TCGA) gene expression data (http://ualcan.path.uab.edu) (Chandrashekar et al., 2017) was used to analyse TLN2 mRNA expression in breast cancer and normal breast tissue, as well as survival between different breast cancer subtypes. The correlation of TLN1 with key regulators in EMT pathway was performed in GEPIA (gene expression profiling interactive analysis, http://gepia.cancer-pku.cn/). Correlation between TLN1 and the integrin family in different types of the TCGA-BRCA dataset was obtained in the TIMER database.

Cell culture

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MDA-MB-231, MCF-7, BT-549, and SK-BR-3 human breast cancer cells were obtained from the American Type Culture Collection (ATCC, Manassas, VA). MDA-MB-231 cells were cultured in Leibovitz’s L15 medium and BT-549 cells were cultured in RPMI 1640 medium, MCF-7 cells were cultured in DMEM, and SK-BR-3 cells were cultured in McCoy’s 5A medium (Thermo Fisher, Waltham, MA), supplemented with 10% foetal bovine serum (Cellmax, China), penicillin (100 units/ml), and streptomycin (100 µg/ml). All cells were incubated at 37°C in a humidified atmosphere of 5% CO2. None of the cell lines were contaminated with mycoplasma.

Transduction

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To establish MDA-MB-231/NC and MDA-MB-231/shRNA cells with stable knockdown of TLN1 expression, MDA-MB-231 cells were transduced with lentivirus (at a multiplicity of infection of 10) containing either control shRNA (NC) or TLN1-specific shRNA (Sangon Biotech, Shanghai, China) and cultured in the presence of 5 µg/ml puromycin (Thermo Fisher, Waltham, MA) for 4 days for selection. The knockdown efficiency was determined by western blotting (described in a subsequent section). The TLN1-specific shRNA sequence was 5′-GCAGTGAAAGATGTAGCCAAA-3′.

EdU assay

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The proliferation of cells was determined using an EdU kit (C10327, Ribobio, Guangzhou, China) according to the manufacturer’s instructions. Briefly, MDA-MB-231/NC and shTLN1 cells (4 × 103 cells/well) were cultured in serum-free medium for 12 hr in triplicate in 96-well plates before the medium was changed to complete medium. After culture for 24, 48, or 72 hr, the cells were labelled with 50 µM EdU during the last 2 hr of culture. Then, the cells were washed with PBS, fixed in 4% paraformaldehyde, permeabilized with 0.5% Triton X-100 at room temperature for 10 min, and treated with additive solution buffer for 30 min in the dark. After washing again, the cells were stained with the nuclear dye Hoechst 33342 at 1:2000 and imaged under a fluorescence microscope. The percentages of EdU+ cells among all Hoechst 33342+ cells were determined in a blinded manner and calculated using ImageJ software (NIH, Bethesda, MD).

Adhesion assay

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The effect of silencing TLN1 on the adhesion of MDA-MB-231 cells was determined using a cell adhesion detection kit (BB-48120, Best Bio, Nanjing, China) according to the manufacturer’s instructions. Briefly, MDA-MB-231/NC and shTLN1 cells (5 × 104 cells/well) were seeded in triplicate in fibronectin/laminin-precoated 96-well plates and cultured at room temperature for 1 hr. In some experiments, the cells were pre-treated with vehicle (DMSO) or 2.0 µM C67399 (AO-774/41465499, Specs, San Francisco, CA) for 24 hr prior to the adhesion assay. After the cells were extensively washed with PBS, they were cultured in the presence of 20 µl of CCK-8 solution for 2 hr, and the absorbance was measured at 450 nm using a microplate reader (Titertek Multiskan PLUS, MK II, Labsystems, Waltham, MA,USA). The computer program PRISM and ImageJ were used to create graphs, process images, and perform statistical analysis.

Immunofluorescence

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MDA-MB-231 cells (4 × 103 cells/well) were serum-starved overnight and then cultured in complete medium in 24-well plates for 18 hr. The cells were stained with anti-integrin β1 (00562-T46, SinoBio, China) and anti-TLN1 (26520–1-AP, Proteintech, Rosemont, IL) at final dilution of 1:200 overnight at 4°C, followed by Alexa Fluor 647 (ab150115, Abcam) and Alexa Fluor 488 (ab150077, Abcam) staining. Or stained with Alexa Fluor 488 (ab150077, Abcam)-labelled anti-vinculin (26520–1-AP, Proteintech, Rosemont, IL) with final dilution of 1:200 overnight at 4°C and washed with PBS. And stained with rhodamine-labelled phalloidin (CA1610, Solarbio, China) with final dilution of 1:200 for 1 hr at room temperature, followed by nuclear staining with DAPI (5 µg/ml, UE, D4054, China). The cells were imaged under a confocal microscope (Zeiss, LSM800). The cell length and numbers and sizes of FAs were measured for 20 randomly selected cells from each group in a blinded manner.

Flow cytometry

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The effect of TLN1 silencing on spontaneous apoptosis in TNBC cells was measured by flow cytometry using an Annexin-V and propidium iodide (PI) kit (559763, BD, San Diego, CA), following the protocol provided. Briefly, the different groups of cells (2 × 105/tube) were stained in duplicate with 5 µl of Annexin V-FITC and PI in the dark for 15 min. The cells were then analysed by flow cytometry (BD FACSverse, Piscataway, NJ ).

Transmission electron microscopy

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The ultrastructure of MDA-MB-231/NC and MDA-MB-231/shTLN1 cells was examined by transmission electron microscopy. Briefly, the different groups of cells were harvested, fixed in 2.5% glutaraldehyde, and embedded. Ultra-thin sections (70 nm) were prepared using a microtome and mounted on a copper grid. The sections were stained with 4% aqueous uranyl acetate (10 min) and then Reynolds lead citrate (2 min). The cells were photoimaged under a transmission electron microscope (JEM-2000EX, JEOL, Sagamihara, Japan).

Western blotting

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The protein levels of molecules of interest relative to those of GAPDH (the loading control) in different groups of cells were determined by western blotting (Liu et al., 2018). Briefly, 5 × 106 of MDA-MB-231/NC and shTLN1 cells were lysed in RIPA buffer for 30 min at 4°C. After determining protein concentrations using a BCA kit (Thermo Fisher, Waltham, MA), the cell lysates (40 µg/lane) were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis on 8–12% gels and transferred to polyvinylidene difluoride membranes (Millipore, Sigma, Burlington, MA). The membranes were blocked with 5% BSA in TBST for 1 hr at room temperature and incubated with primary antibodies at 4°C overnight. The primary antibodies were anti-TLN1 (4021), anti-vimentin (5741), anti-E-cadherin (3195), anti-N-cadherin (4061), anti-tubulin α (2125), anti-CK18 (4546), anti-FAK (3285) purchased from Cell Signaling Technology (Danvers, MA); anti-GAPDH (10494–1-AP), anti-AKT1 (10176–2-AP), anti-integrin β3 (18309–1-AP) obtained from Proteintech (Rosemount, IL); anti-p-AKT1 (Santa Cruz Biotechnology, sc-81433, Dallas, TX); anti-p-FAK (Tyr397, Immunoway, YP0739, Plano, TX); and anti-integrin β1 (Sino Biological, 100562-T46, China). The membranes were then treated with HRP-conjugated secondary antibodies (1:10,000 dilution; Jackson ImmunoResearch Laboratories, West Grove, PA), and the proteins were visualized using enhanced chemiluminescence reagents (Thermo Fisher, Waltham, MA). The levels of individual target proteins relative to those of GAPDH or tubulin α were determined based on densitometric analysis using ImageJ software.

Immunoprecipitation

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MDA-MB-231 cells (1 × 107) were lysed in cold RIPA lysis buffer containing proteinase inhibitors. Lysis is followed by a washing step to remove cell debris and the lysis buffer. The cell lysates (50 µg/tube) were then incubated with anti-TLN1, anti-integrin β1, anti-integrin β3, or control isotype IgG (2 µg) with gentle agitation at 4°C overnight. Subsequently, immunocomplexes were precipitated with 50 µl of protein A/G agarose beads (sc-2003, Santa Cruz Biotechnology, Dallas, TX) at 4°C for 4 hr. After centrifugation at 700 g and at 4°C for 5 min, the microbeads were washed with lysis, and the bound proteins were disentangled from antigen-antibody-beads complex by heating at 100°C for 5 min. The proteins were analysed by western blotting.

Structural simulation and targeted molecular screening of TLN1

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The TLN1 protein contains F0, F1, F2, and F3 domains in the atypical FERM (band 4.1, ezrin, radixin, and moesin) structure (PDB ID: 3IVF). Given that the S1 and S2 chains of the phosphotyrosine-binding (PTB) F3 domain are crucial for integrin binding and activation (Bouaouina et al., 2008; Tadokoro et al., 2003; Wegener et al., 2007), the F3 domain of TLN1 was targeted. The flexible loop domain was labelled in cartoon mode and surface mode using PyMOL software. The potential ligands interacting with the PTB F3 domain of TLN1 were virtually screened using the FIPSDock tool (Liu et al., 2013). The optimal scoring of each molecule and the corresponding docking conformation and pocket mode of action, where the scoring was related to the negative logarithm (−logKd) of the ligand-receptor dissociation equilibrium constant, were assessed. The binding mode of the complexes identified from docking was used as a baseline structure for 5 ns of molecular dynamic (MD) simulations using the academic free package Gromacs (Wang et al., 2018).

Transwell assays

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The effect of silencing TLN1 on the migration and invasion of MDA-MB-231 cells was determined with transwell migration and invasion assays (Gu et al., 2019). Briefly, MDA-MB-231/NC and shTLN1 cells (105 cells/well) were seeded in duplicate in serum-free medium in the top chamber of transwell plates (8 µm pore size, Corning) and cultured for 24 hr. The bottom chambers were filled with complete medium. For the invasion assays, the membranes were coated with Matrigel in the upper chambers. The cells on the membranes of the top chamber were fixed by methyl alcohol for 20 min and stained by 0.1% crystal violet for 20 min at room temperature. Initial cell status was visualized immediately using a light microscope (Olympus, Tokyo, Japan). Cells in five fields per membrane were randomly selected and counted in a blinded manner.

Mass spectrometry

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The effect of silencing TLN1 on differentially expressed proteins (DEPs) in MDA-MB-231 cells was determined by tandem mass tag (TMT, Thermo, Pierce Technology, Waltham, MA) and LC-MS/MS. Briefly, proteins from MDA-MB-231/NC and shTLN1 cells were extracted. Three biological replicates were generated for each group. After labelled with TMT reagents for 2 hr at room temperature and then pooled and desalted, the peptide samples were subjected to LC-MS/MS using a Q Exactive system (Thermo Fisher, Waltham, MA) with a C18 column. The protein profiles with p < 0.05 and the difference multiple more than 1.2 times or less than 0.83 times were selected as DEPs. Then DEPs were analysed by GO analysis using WebGestaltR (http://www.webgestalt.org/option.php).

Xenograft tumours in mice

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Xenografted TNBC tumours were established as previously described (Liu et al., 2018). Briefly, 106 MDA-MB-231/NC or shTLN1 cells were injected into the mammary fat pads of NOD/SCID mice (n = 8 per group). The growth of the implanted tumour diameter was monitored longitudinally for up to 21 days post-inoculation, at which point the mice were sacrificed. The tumours were dissected, measured, and weighed.

For lung metastases, 106 MDA-MB-231/NC or shTLN1 cells were injected via tail vein of NOD/SCID mice (n = 8 per group). After 8 weeks, lung tissue was removed to evaluate the numbers and sizes of lung metastatic nodules by analysis of lung sections.

For the evaluation of treatment with C67399, after inoculation with MDA-MB-231 cells, the mice were randomized and intravenously treated with vehicle (5% DMSO in PBS) or 1.75 mg/kg C67399 twice per week for 3 weeks. Tumour growth was monitored by diameter for up to 21 days post-inoculation, at which point the mice were sacrificed. The tumours were recovered, and their volume and weight were measured (n = 5 per group). In addition, the numbers and sizes of lung metastatic tumour nodules in the individual mice were examined by analysis of lung sections (n = 5 per group).

Histology

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Each xenograft tissue samples fixed in 10% formaldehyde solution (pH 7.0) and paraffin-embedded. Paraffin-embedded tissue sections (4 μm) were dewaxed in xylene (3 × 10 min), rehydrated through a series of graded alcohols (100%, 95%, 85%, and 75%) to water. For histology, samples were stained with haematoxylin and eosin (H&E, Servicebio, Wuhan, China). The sections were imaged under a light microscope (Olympus, Tokyo, Japan) and independently examined by two pathologists in a blinded manner.

Statistical analysis

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Data are expressed as the mean ± standard error of the mean (SEM). Differences among more than two groups were analysed by one-way ANOVA with a post hoc Newman-Keuls test, and differences between two groups were analysed by Student’s t test. Disease-free survival (DFS) in each group of patients was estimated by the Kaplan-Meier method and analysed by the log-rank test. All statistical analyses were performed using SPSS 23.0 (IBM, Armonk, NY). A p-value < 0.05 was considered statistically significant.

Results

TLN1 overexpression is associated with poor survival in TNBC patients

Cell-cell (CC) and CEM adhesion are major structural components of the tumour microenvironment and induce a network of signals in refractory cancers, such as TNBC (Arroyo-Crespo et al., 2019; Xu et al., 2012; Zhao et al., 2014). Integrin family members are known as key gears in CC and CEM for metastasis of multiple cancer types (Arroyo-Crespo et al., 2019; Xu et al., 2012; Zhao et al., 2014). However, we found no correlation between integrin family members and different breast cancer types using TCGA database (Figure 1A). Correlation between TLN1 and the integrin family in different types of the TCGA-BRCA dataset from TIMER database showed that TLN1 may play an important role in breast cancer, especially in TNBC (Figure 1—figure supplement 1A-B). Due to the lack of an effective target for TNBC, we switched our focus on TLN1, a partner of integrins in TNBC.

Figure 1 with 1 supplement see all
TLN1 upregulation is associated with poor disease-free survival (DFS) in triple-negative breast cancer (TNBC).

(A) The expression of ITGB1, ITGB3, and ITGA5 in breast cancer subclasses and normal breast tissue using The Cancer Genome Atlas (TCGA) samples (n = 114 of normal samples, n = 556, 37, and 116 of luminal, human epidermal growth factor receptor 2 [HER2] positive and TNBC samples, respectively; p-value is the result of comparison with normal samples, respectively). (B) Representative immunohistochemistry images of TLN1 expression in TNBC tissue, chest wall recurrence, lymphatic metastasis, and intestinal metastasis (scale bar, 100 µm). (C) Western blot analysis of TLN1 expression in fresh TNBC and para-cancerous tissues (n = 4, p = 0.009). (D) The DFS of 171 TNBC patients in the cohort was estimated by the Kaplan-Meier method, and the difference between groups with high and low TLN1 expression was compared within each set of patients listed and analysed by log-rank analysis (HR = 3.19, p < 0.001). (E) Chi-square analysis of high or low TLN1 expression with T-stage, N-stage, and Ki67 index. Data are either presented as representative images or expressed as the mean ± standard error of the mean (SEM) of each group. p < 0.01 was indicated by **.

Figure 1—source data 1

TLN1 upregulation is associated with poor DFS in TNBC.

https://cdn.elifesciences.org/articles/68481/elife-68481-fig1-data1-v2.zip

To evaluate the clinical significance of TLN1 in TNBC, breast cancer tissues and adjacent non-tumour breast tissues from 171 surgically resected TNBC patients were studied. Immunohistochemistry of TLN1 showed that TLN1 was ubiquitously expressed in the membrane and cytoplasm of paraneoplastic and tumour tissues (Figure 1B). Western blotting of freshly dissected TNBC tumours revealed that the relative protein levels of TLN1 in TNBC tumour tissues were significantly higher than those in para-cancerous breast tissues (Figure 1C). Statistical analysis shows that TLN1 was highly expressed in 43.9% of TNBCs, and the DFS of high and low expression of TLN1 shows higher expression of TLN1 was significantly associated with shorter DFS in TNBCs (HR = 3.19, p < 0.001, Figure 1D). Stratified analysis indicated that high level of TLN1 expression were significantly associated with T3-T4 stage (p = 0.03), positive lymph node metastasis (p < 0.001), and high Ki67 index (p < 0.001) in all 171 TNBCs (Figure 1E). Besides, high expression of TLN1 was detected in chest wall recurrence, lymphatic metastasis, and intestinal metastasis (Figure 1B). Hence, TLN1 upregulation was associated with poor prognosis in TNBC patients.

Considering that TLN2 shares 76% protein sequence identity with TLN1 (Gough and Goult, 2018), we analysed the expression of TLN2 in the breast cancer dataset from TCGA database. Results showed that TLN2 mRNA in breast cancer tissue were significantly lower than in normal breast tissues (p < 0.01), and there was no difference in levels between luminal and TNBC, HER2+ and TNBC subtypes, except for the comparison between luminal and HER2+ subtypes (p = 0.006) (Figure 1—figure supplement 1C). Also, there was no significant difference in survival between high and low expression of TLN2 within each subtype of breast cancer (Figure 1—figure supplement 1D). Therefore, our subsequent study mainly focused on TLN1 rather than TLN2.

Depletion of TLN1 inhibits the growth of TNBC cells in vitro and in vivo

To understand the role of TLN1 in different types of breast cancer, relative protein levels of different types of breast cancer cell lines were detected by western blot. The TNBC cell lines MDA-MB-231 and BT-549 showed much higher levels of TLN1 than luminal cell line MCF-7 and HER2+ cell line SK-BR-3 cells (Figure 2A). We then employed shRNA-based lentivirus technology to generate MDA-MB-231 cells with stable knockdown of TLN1 expression (MDA-MB-231/shTLN1 cells), in which TLN1 expression was obviously reduced compared to negative control cells, named as MDA-MB-231/NC (Figure 2B). Silencing TLN1 significantly inhibited the proliferation of MDA-MB-231 cells (Figure 2C) and increased the frequency of spontaneous apoptosis (Figure 2D) and the number of apoptosis-related vacuoles in MDA-MB-231 cells (Figure 2E). More importantly, silencing TLN1 was shown significant reduction of tumour size and weight in NOD/SCID mice implanted with 106 MDA-MB-231/NC or shTLN1 cells in the mammary fat pad (Figure 2F). Together, these data demonstrate that silencing TLN1 can inhibit the growth of TNBC cells in vitro and in vivo.

Silencing TLN1 promotes apoptosis and inhibits tumour growth of MDA-MB-231 cells.

(A) TLN1 expression in the indicated breast cancer cell lines, using western blotting. (B) The efficiency of TLN1 silencing with shRNA in MDA-MB-231 cells was evaluated by western blotting. (C) Silencing TLN1 inhibited the proliferation of MDA-MB-231 cells (scale bar, 20 µm, p < 0.05 at 48 hr and p < 0.01 at 72 hr). (D) Silencing TLN1 enhanced spontaneous apoptosis in MDA-MB-231 cells, which was detected by Flowcyto. (E) Silencing TLN1 increased apoptosis-related vacuoles (red arrows), which was detected by transmission electron microscopy (TEM). (F) Silencing TLN1 reduced the growth of xenografted triple-negative breast cancer (TNBC) tumours in NOD/SCID mice (n = 8 per group). Data are presented as representative images, flow cytometric plots, or the mean ± standard error of the mean (SEM) of each group from three separate experiments. *p < 0.05, **p < 0.01 vs. the NC group.

Figure 2—source data 1

Silencing TLN1 promotes apoptosis and inhibits tumour growth of MDA-MB-231 cells.

https://cdn.elifesciences.org/articles/68481/elife-68481-fig2-data1-v2.zip

Depletion of TLN1 inhibits the adhesion and metastasis of TNBC cells in vitro and in vivo

Since TLN1 is crucial for tumour cell adhesion and metastasis (Zhang et al., 2011), we tested the effect of silencing TLN1 on MDA-MB-231 cell adhesion, migration, and invasion in vitro. We found that silencing TLN1 significantly inhibited the cell adhesion, migration, and invasion of MDA-MB-231 cells (Figure 3A and B) and BT549 cells (Figure 3—figure supplement 1A-C). Additionally, silencing TLN1 significantly increased the expression of CK18 and E-cadherin but significantly decreased the expression of N-cadherin and vimentin in MDA-MB-231 cells, suggesting that silencing TLN1 inhibited EMT in TNBC cells (Figure 3C and D). More importantly, silencing TLN1 suppressed lung metastasis in vivo, as demonstrated by significant decreases in the number and size of lung metastatic nodules in mice injected with shTLN1 cells (Figure 3E). While overexpression of integrin β1 could rescue invasion, migration, and adhesion in shTLN1 cells (Figure 3F–H). Thus, silencing TLN1 may inhibit TNBC cell adhesion and metastasis by attenuating EMT.

Figure 3 with 2 supplements see all
Silencing TLN1 reduces triple-negative breast cancer (TNBC) cell motility by blocking epithelial-mesenchymal transformation (EMT).

(A) TLN1 silencing decreased the adhesion of MDA-MB-231 cells (n = 3, p < 0.01). (B) Transwell assay was used to evaluate the migration and invasion of MDA-MB-231/NC and shTLN1 cells (n = 3, p < 0.01; scale bar, 100 µm). (C and D) The relative expression level of CK18, E-cadherin, N-cadherin, and vimentin relative to those of GAPDH in MDA-MB-231/NC and shTLN1 cells, using western blotting (n = 3, p < 0.01, respectively). (E) Haematoxylin and eosin (H&E) staining of mitigated lung metastasis derived from MDA-MB-231/NC and shTLN1 tumours in NOD/SCID mice (n = 5–8 per group; scale bar, 50 µm). (F) Western blot of integrin β1 overexpression in MDA-MB-231/shTLN1 cells. (G) Transwell analysis of invasion and migration following integrin β1 overexpression. (H) Adhesion assay after integrin β1 overexpression. Data are representative images or expressed as the mean ± standard error of the mean (SEM) of each group from three separate experiments for in vitro and 5–8 per group for in vivo studies. *p < 0.05, **p < 0.01 vs. the control group.

Figure 3—source data 1

Silencing TLN1 reduces TNBC cell motility by blocking EMT.

https://cdn.elifesciences.org/articles/68481/elife-68481-fig3-data1-v2.zip

Silencing TLN1 inhibits FA formation and integrin β1 signalling in MDA-MB-231 cells

To understand the molecular mechanisms underlying the effects of silencing TLN1, we compared protein expression profiles between MDA-MB-231/NC and shTLN1 cells using TMT proteomics. There were 156 DEPs between these cells; 76 were upregulated, whereas 80 were downregulated (Figure 3—figure supplement 2A). The results of Gene Ontology (GO) functional enrichment analysis of DEPs indicated that these TLN1-related DEPs were involved in tissue development, positive regulation of cell migration, microtubule organization, cell differentiation, and protein-binding activity (Figure 3—figure supplement 2B, C, D).

Given that mutations within both integrins β1 (Bouaouina et al., 2008) and β3 (Tadokoro et al., 2003) may abolish TLN binding and decrease integrin affinity, TLN1 ablation universally leads to integrin adhesion defects (Chen et al., 2017; Jin et al., 2015). These experiments inspired us to verify whether TLN1 could bind integrin β1 or β3 in TNBC. Firstly, we validated the interactions between TLN1 and integrin β1 or β3 in MDA-MB-231 cells by immunoprecipitation and found that there was a significant interaction between TLN1 and integrin β1 but not between TLN1 and integrin β3, though a non-specific band was seen in the TLN1 pull-down of integrin β3, which was probably a trace left by electrophoresis (Figure 4A). Subsequently, immunofluorescence showed that TLN1 and integrin β1 were scattered in the cytoplasm while co-located in FAs at both poles of the cell (Figure 4B). As TLN1 is a critical component of FAs which can be observed by vinculin and actin-phalloidin staining (Bennett et al., 2018), we further observed the effect of TLN1 silencing on FAs formation by confocal fluorescence microscopy. Results showed that silencing TLN1 led to significantly shorter cells, fewer FAs, the predominant localization of FAs on the cell membrane, and significant thickening of the actin cortex (Figure 4C). Moreover, light microscopic imaging showed that the morphology of shTLN1 cells was no longer as fusiform as MDA-MB-231/NC cells (Figure 4D). Western blot analysis further indicated that silencing TLN1 in MDA-MB-231 cells reduced the relative levels of integrin β1, as well as the levels of phosphorylated AKT and FAK (Figure 4E). These data indicate that silencing TLN1 attenuates integrin β1 signalling in TNBC cells, which results in impaired dynamic formation and maturation of FAs.

Silencing TLN1 reduces focal adhesion (FA) dynamic formation and integrin β1-mediated signalling in MDA-MB-231 cells via loss of interactions with integrin β1.

(A) Immunoprecipitation analysis of the interaction of TLN1 with integrin β1 or integrin β3 in MDA-MB-231 cells. (B) Immunofluorescence images of TLN1 and integrin β1 in MDA-MB-231 cells (scale bar, 40 µm; 5 µm for enlarged image). (C) Immunofluorescence confocal microscopy analysis of FAs and the actin cortex in MDA-MB-231/NC and shTLN1 cells (scale bar, 40 µm; 10 µm for enlarged image). (D) Light microscopy images of MDA-MB-231/NC and shTLN1 cells (scale bar, 100 µm). (E) Western blot analysis of the relative levels of integrin β1, integrin β3, total AKT, total FAK, phosphorylated AKT (Ser473), and phosphorylated FAK (Tyr397) in MDA-MB-231/NC and shTLN1 cells. GAPDH used as the control to evaluate relative expression. Data are presented as representative images or the mean ± standard error of the mean (SEM) of each group from three separate experiments. **p < 0.01 vs. the NC group.

Figure 4—source data 1

Silencing TLN1 reduces FA dynamic formation and integrin β1-mediated signalling in MDA-MB-231 cells via loss of interactions with integrin β1.

https://cdn.elifesciences.org/articles/68481/elife-68481-fig4-data1-v2.zip

C67399 is found to block the integrin β1 binding site of TLN1 and reduces the malignant behaviours of TNBC in vitro

Since we showed that TLN1/integrin β1 signalling is crucial in malignant behaviours of TNBC cells, we next screened small molecules from Enamine database that could block the binding of TLN1 and integrin β1, based on a novel CSTPPI using our in-house developed FIPSDock software (Liu et al., 2013; Figure 5—figure supplement 1A). In brief, the conformational ensembles of TLN1 and integrin β1 were first generated via 20 ns molecule dynamics simulation. Subsequently, the dynamic binding pockets of TLN1 and integrin β1 were used for further computational screening. Structurally, the TLN1 ‘head’ is comprised largely of an FERM domain, which contains F0, F1, F2, and F3 domains (band 4.1, ezrin, radixin, and moesin) (PDB ID: 3IVF) (Goult et al., 2013). As the S1 and S2 chains of the PTB F3 domain are crucial for integrin binding and activation, the F3 domain of TLN1 was targeted (Figure 5A). Based on the scores of the corresponding docking conformation and the pocket mode of action, we firstly selected the top eight small molecular compounds (named C1-C8) with the highest affinity score to test the drug sensitivity in vitro (Figure 5—figure supplement 1B). Due to the poor solubility of C1, C3, C5, C7, and C8, we only verified the drug sensitivity of the remaining C2, C4, and C6 (C67399) compounds to MDA-MB-231 cells. The results showed that C67399 (C38H48O5, 584.79 Da, 4903–2135, Chemdiv Compond, San Diego, CA) could obviously inhibit the cell viability of MDA-MB-231 cells (Figure 5—figure supplement 1C). We also found that C67399 could stably bound TLN1 with a low dissociation equilibrium (Figure 5B). Further MD simulations revealed that C67399 interacts with Thr354, Ala389, Gln390, Ala393, Ile396, Asp397, and Ile398, in addition to Trp359, in the hydrophobic pocket of the F3 domain of TLN1 (Figure 5C). Moreover, the total interaction energy spectrum shows that the addition of C67399 reduces the energy expenditure between TLN1 and integrin β1 (Figure 5D). These findings indicated that small-molecule C67399 could block the combination of TLN1 and integrin β1 from the point of view of protein structure and in silico modelling.

Figure 5 with 1 supplement see all
C67399 blocks TLN1-integrin β1 binding and attenuates the malignant behaviours of MDA-MB-231 cells.

(A) Complete structure of the human TLN1 ‘head’ with the F0, F1, F2, and F3 domains, with the predicted interaction between the TLN1 F3 domain (PDB ID: 3IVF) and integrin β1 at far right. The targeting of the flexible ring region of the F3 domain of the TLN1 head structure was labelled in cartoon mode and the head structure was labelled in surface mode using PyMOL software. The yellow- and paon-labelled regions indicate the hydrophobic ring structure of the F3 domain of TLN1, with the yellow-labelled region representing the K324 residue. (B) Docking mode diagram of the chemical molecule C67399 and TLN1; the hydrophobic pocket formed by the flexible ring of C67399 and the F3 domain was screened by FIPSDock. (C) The main favourable contributions to the binding of C67399 came from hydrophobic contacts with Thr354, Ala389, Gln390, Ala393, Ile396, Asp397, and Ile398, using a closer analysis of the complex structure and energy term. (D) Molecular dynamic simulations of the electrostatic interactions between C67399 and Trp359. (E) The dose-response curve of C67399 in MDA-MB-231 cells using CCK-8 kit (IC50 = 2.0 µM). (F–H) C67399 treatment significantly reduced the viability(F), adhesion(G), and migration(H) of MDA-MB-231 cells. (I) Western blot analysis of the relative levels of integrin β1, integrin β3, total AKT, total FAK, phosphorylated AKT (Ser473), and phosphorylated FAK (Tyr397) in MDA-MB-231/NC and shTLN1 cells, as well as in MDA-MB-231/NC treated with C67399 (2 µM for 48 hr). GAPDH used as the control to evaluate relative expression. (J) Immunoprecipitation analysis of TLN1 and integrin β1 in the presence or absence of C67399 treatment (2 µM for 48 hr). Data are shown as representative images, charts, or the mean ± standard error of the mean (SEM) of each group from three separate experiments. #p < 0.05, ##p < 0.01, and **p < 0.01 vs. the NC group.

Figure 5—source data 1

C67399 blocks TLN1–integrin β1 binding and attenuates the malignant behaviours of MDA-MB-231 cells.

https://cdn.elifesciences.org/articles/68481/elife-68481-fig5-data1-v2.zip

Next, we analysed the effect of C67399 on TNBC cells. Dose-response curve for C67399 in MDA-MB-231 cells revealed that the half maximal inhibitory concentration (IC50) of C67399 was 2.0 µM (Figure 5E). Functionally, treatment with C67399 significantly decreased the viability, adhesion, migration, and invasion of MDA-MB-231 cells and BT549 cells (Figure 5F, G and H and Figure 5—figure supplement 1D-E). More importantly, 2.0 µM C67399 significantly reduced the expression of integrin β1, AKT, FAK, and phosphorylated FAK in MDA-MB-231 cells, while did not affect the expression of integrin β3 (Figure 5I). Additionally, immunoprecipitation results revealed that C67399 inhibited the binding of TLN1 to integrin β1 in MDA-MB-231 cells (Figure 5J). Our findings suggest that targeting TLN1 with C67399 suppresses TNBC cell malignancy in vitro.

C67399 inhibits the tumour growth and metastasis of MDA-MB-231 cells in mice

To better understand the therapeutic effect of C67399 on TNBC in vivo, MDA-MB-231 cells were injected into the fat pad or tail vein of NOD/SCID mice with or without C67399 treatment. Mice that received intravenous administration of 1.75 mg/kg C67399 twice per week showed significant reductions in the tumour volume (Figure 6A and B), the number, and size of lung metastatic nodules (Figure 6C, D and E), indicating decreased tumour growth and attenuated lung metastasis of implanted shTLN1 cells. Furthermore, a decreased proliferation index of Ki67 was observed in the C67399-treated xenograft tumours using immunohistochemistry, compared to the untreated MDA-MB-231 tumours (Figure 6F).

Figure 6 with 1 supplement see all
C67399 inhibits the growth and metastasis of implanted triple-negative breast cancer (TNBC) cells.

MDA-MB-231 cells were injected into fat pad or tail vein of NOD/SCID mice to establish tumour model. Mice were intravenously injected with 1.75 mg/kg C67399, twice a week for 3 weeks. (A and B) The tumour volume of xenografts derived from MDA-MB-231 cells treated with or without C67399 (n = 5–8 per group, p < 0.01). (C–E) The number and size of lung metastatic tumour nodules in mice of MDA-MB-231 cells with or without C67399 treatment (n = 5–8 per group, p < 0.01). (F) Immunohistochemical staining for Ki67 of xenografted tumours derived from MDA-MB-231 cells in the presence or absence of C67399 treatment. (G) Diagram illustrating the function of TLN1 in TNBC. TLN1 could bind and activate integrin β1 in TNBC cells. On the one hand, it can regulate the dynamic formation and maturation of focal adhesions (FAs), induce epithelial-mesenchymal transformation (EMT), and promote tumour metastasis; on the other hand, it can promote tumour proliferation by inhibiting apoptosis. A small-molecule C67399 was developed to inhibit the binding of TLN1 to integrin β1, as well as a series of integrin β1-related pathways, and ultimately inhibit the malignancy of TNBC.

Figure 6—source data 1

C67399 inhibits the growth and metastasis of implanted TNBC cells.

https://cdn.elifesciences.org/articles/68481/elife-68481-fig6-data1-v2.zip

We also performed H&E staining of other organs harvested from the mice treated with C67399, and no structural changes suggestive of toxicity were observed in the heart, liver, spleen, lungs, kidneys, or other organs (Figure 6—figure supplement 1A), as well as no significant differences in Alcian blue staining of intestine, alanine aminotransferase, and aspartate aminotransferase activities in mice serum and blood cell counts (Figure 6—figure supplement 1B-D). These results suggested that C67399 could inhibit the tumour growth and metastasis of MDA-MB-231 cells in vivo, without causing obvious structural toxic changes.

Collectively, our findings indicated that TLN1 can bind and activate integrin β1 in TNBC cells. On the one hand, it can regulate the dynamic formation and maturation of FAs, induce EMT to promote tumour metastasis; on the other hand, it facilitates tumour growth by inhibiting apoptosis. Fortunately, C67399 can inhibit the binding of TLN1 to integrin β1, as well as a series of integrin β1-related pathways, and ultimately inhibit the malignancy of TNBC (Figure 6G).

Discussion

TNBC is a highly aggressive subtype of breast cancer characterized by rapid proliferation, early invasion, recurrence, and metastasis (Mostert et al., 2015). TLN1 is an integrin-activated, tension-sensitive FA component that directly links integrins in the plasma membrane to myosin cytoskeleton (Haage et al., 2018; Jin et al., 2015). Beyond the FA component, TLN1 is also associated with chemosensitivity to cancer therapy. Loss of TLN1 function was reported to significantly enhance chemosensitivity in TNBC cell lines, but not in hormone positive cell lines (Singel et al., 2013). They concluded that TLN1 is a regulator of response to docetaxel and a potential therapeutic target for TNBC, but not in other types of breast cancer (Singel et al., 2013). In addition to its role in chemosensitivity, we found that TLN1 has a carcinogenic effect independent of chemosensitivity in TNBC, and TLN1 initiates the growth and migration of TNBC. Therefore, we developed a specific molecule that more effectively inhibits the oncogenic effect of TLN1, which may be developed as a promising clinical treatment for TNBC, while potentially increasing chemotherapy sensitivity.

In this study, we revealed that high expression of TLN1 in TNBC was associated with poor prognosis and malignant behaviour, including proliferation, cell adhesion, EMT, invasion, and migration. These data indicate that TLN1 promotes TNBC malignancy as an oncogenic gene, which is in accordance with previous observations in prostate cancer, colon cancer, and oral squamous cell carcinoma (Bostanci et al., 2014; Jin et al., 2015; Lai et al., 2011). Given that it is very challenging to predict survival for TNBC patients after surgical resection (Brockwell et al., 2019), our data indicated that higher TLN1 expression could be a prognostic factor for TNBC patients. However, further validation of these findings is needed.

Our findings also highlight that TLN1 is a potential therapeutic target for TNBC. Specifically, TLN1 expression in TNBC cells is much higher than in other subtypes of breast cancer cell lines, and silencing TLN1 significantly attenuated the malignancy of MDA-MB-231 cells, reducing TNBC tumour growth and lung metastasis. Mechanically, it is hypothesized to inhibit cancer metastasis through suppressing EMT. These data were consistent with previous observations (Thapa et al., 2017) and support the notion that TLN1-related signalling is crucial for TNBC malignancy.

It is well known that malignant TNBC cells can adhere to the ECM by activating integrins (Bays and DeMali, 2017; Bosch-Fortea and Martín-Belmonte, 2018; Hynes, 2002; Lock et al., 2008) and the activation of integrin-related signalling promotes EMT and metastasis in TNBC (Wen et al., 2019). Major insights into TLN1 demonstrated that its ‘head’ can bind the cytoplasmic tails of integrin β through its PTB domain, resulting in integrin β activation (Tadokoro et al., 2003). This activation links integrins to the cytoskeleton (Critchley and Gingras, 2008) by activating FAK and Src and further promotes downstream PI3K/AKT signal transduction to promote cancer malignancy (Jin et al., 2015; Klapholz and Brown, 2017; Sun et al., 2019). In our results, TLN1 interacts with integrin β1 and silencing TLN1 alters many proteins expression and significantly reduces FAs dynamic formation in MDA-MB-231 cells, which is similar to observations in fibroblasts and endothelial cells (Kopp et al., 2010; Nader et al., 2016). In addition, silencing TLN1 was found to significantly reduce integrin β1 levels as well as the levels of phosphorylated FAK. The reduction in integrin might be a result of TLN1 silencing-mediated integrin degradation (Chinthalapudi et al., 2018). These data suggest that TLN1 is crucial for FA dynamic formation, adhesion, and invasion in TNBC cells, as well as tumour growth and metastasis. Additionally, silencing TLN1 significantly attenuated AKT phosphorylation in MDA-MB-231 cells, demonstrating the mitigation of TLN1/integrin β1 signalling in TNBC cells.

The actin cortex is a thin layer of filamentous actin that lies beneath the plasma membrane (Litschko et al., 2019). During EMT, actin reorganizes from a mostly cortical arrangement into stress fibres and lamellipodia (Chalut and Paluch, 2016). To the best of our knowledge, this study provides the first evidence that silencing TLN1 induces thickening of the actin cortex in TNBC cells, which may initiate cell surface contractile tension and result in local contractions and drive cell deformations (Chugh et al., 2017). Our findings indicated that loss of TLN1 led to actin redistribution, resulting in changes in membrane dynamics, and this loss may interfere with the efficient assembly or turnover of FAs, which is required for directional migration (Garcin and Straube, 2019). Therefore, TLN1 may regulate the dynamic formation of FAs by reducing cortical actin, and then promote cell migration in TNBC cells.

In this study, for the first time, we identified a novel small-molecule compound, C67399, which blocks TLN1 binding to integrin β1, through a novel computational approach named as CSTPPI against the binding interface of TLN1 with integrin β1. The advantage of this CSTPPI is that conformational ensembles of TLN1-integrin β1 interfaces were used as targets for the computational screening via our in-housed developed docking tool. Therefore, the flexibility of protein-protein interface was given full consideration in our CSTPPI to improve the accuracy. This is the first study of identifying small-molecule compounds by targeting dynamic protein-protein binding interface and this may be extended to other PPI study. Remarkably, we found that C67399 could significantly ablate the invasiveness of MDA-MB-231 cells and suppress the lung metastasis in vivo. These novel findings suggest that TLN1 is a promising therapeutic target and C67399 is a valuable candidate compound for TNBC intervention. C67399 is the first small-molecule inhibitor of its kind that interfere in the binding interface of TLN1 with integrin β1.

In summary, our data suggest that TLN1 is significantly upregulated in TNBC cells and TLN1 interacts with integrin β1 to activate downstream signalling pathways including PI3K/AKT and FAK pathways. Furthermore, the interaction of TLN1 with integrin β1 facilitates the formation of FAs and cell adhesion, leading to the malignancy and metastasis of TNBC by enhancing EMT. Hence, TLN1 could be a valuable prognostic factor and a promising therapeutic target for TNBC. Moreover, we identified a small-molecule compound C67399 via computational screening and we demonstrated that genetically downregulating TLN1 expression or blocking the binding of TLN1 with integrin β1 by C67399 could inhibit the aggressiveness and metastasis of TNBC.

Data availability

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

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Decision letter

  1. Renata Pasqualini
    Reviewing Editor; Rutgers University, United States
  2. Mone Zaidi
    Senior Editor; Icahn School of Medicine at Mount Sinai, United States
  3. Bedrich Eckhardt
    Reviewer; Olivia Newton-John Cancer Research Institute, Australia

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

Thank you for submitting your article "Binding blockade between TLN1 and integrin β1 represses metastasis of triple-negative breast cancer" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Mone Zaidi as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Bedrich Eckhardt (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) Referees comments must be addressed in full.

2) New data are required before re-submission, and the manuscript will be returned to the referees if a revised version is submitted.

Reviewer #1:

The authors established TLN1 as a potential therapeutic target for triple-negative breast cancer, an aggressive subtype, with very few treatment options. The authors used IHC on patient samples and concluded that high TLN1, but not TLN2 and other integrins expression is an independent prognostic marker for BrCa. It is important to note that TLN2/integrin expression was studied in TCGA dataset and not on the same set of samples and the conclusions on TLN2/integrins should be re-considered. The authors presented strong data on effect of TLN downregulation on cell proliferation, migration, invasion, stemness, EMT and in vivo tumor growth and metastasis. Their data suggest all aspects of tumor progression are impacted by TLN1 downregulation. Mechanistically, TLN1 downregulation impacted LATS/YAP/TAZ pathway as well as EMT proteins. The authors concluded that TLN1 silencing reduced tumor growth through Hippo/Yap signaling, which is not justified as there was no data presented, where activation of YAP/TAZ rescued stemness/tumor growth in TLN1 ablated cells. Presented data is just correlational. Same is true regarding their conclusion on EMT and Metastasis. Next, the authors confirmed the effect of TLN1 alteration on focal adhesions formation as well as other integrin signaling pathways. In the last part of the manuscript, the authors described the development and characterization of small molecule, which can inhibit interaction between beta1 integrin and TLN1. This inhibitor, C67399, affected viability, adhesion, migration, tumor growth and metastasis. However, it is important to point that all these effect on malignancy can be explained by the viability. Since cells were less viable, it is likely that non-viable cells will not adhere, migrate, form tumor or mets. This is an interesting article, but text needs to be re-worded to justify conclusions based on the data presented.

Recommendations for the authors:

1. Figure 1: To invalidate the role of TLN2/integrins, the authors should either use same patient samples with IHC for TLN2 or use TCGA for TLN1 comparisons. Considering that beta1 integrin expression is not significantly different between various subtype, would it be possible to conclude that beta1 signaling is independent of TLN1 in the subsets, where TLN1 is not amplified.

2. TNBC samples with high TLN1: are they mesenchymal type? The authors should check the correlation between TLN1/EMT/Hippo pathways, this will strengthen their hypothesis.

3. Figure 2: the conclusion that TLN1 affect stemness, needs to be supported by tumor initiation data. Is there any difference in tumor onset in figure 2E? Also, CSC are slow growing, which is in contrast to the current data, which suggest TLN1 promoted cell proliferation.

4. Figure 2: To validate the role of YAP/TAZ, the authors need to perform rescue experiment using constitutively active YAP/TAZ.

5. Figure 3: Are the effects on EMT proteins mediated by YAP/TAZ patwhays or this is an independent signaling from beta1 integrin.

6. Figure 3: Effect on TNBC cell adhesion and metastasis can be a consequence of reduced cell proliferation; the conclusions needs re-wording.

7. Figure 4: Conclusions on cell adhesion and migration should take viability into considerations. If the cells are dead, they will not adhere or migrate.

8. Figure 4J: western blots are of very poor quality. Bands were cropped too close, should show full blots. Also, inhibitors impacted the expression of beta1 integrin (4I), it will be hard to conclude that reduced association is not due to reduced expression.

9. To further strengthens the conclusion, it is suggested to include cell lines from non-TNBC subtype or normal epithelial in some of their experiments as a control.

Reviewer #2:

The article started with bioinformatic and pathological analysis of TCGA and/or breast cancer tissues related to focal adhesion molecules and identified talin-1 (TLN-1) as a worse prognostic marker in breast cancer in particular TNBC. Talin is known to be a component within focal adhesion and binds to the intracellular tail of integrins. Using shRNA-based silencing of TLN-1, the group found that TLN-1 is important in promoting different properties of TNBC cells – including the cell cycle progression, migration/invasion, and cancer-stem cell properties – by reducing integrin-β-mediated intracellular signaling transduction. Most importantly the group found that silencing TLN-1 reduces both primary tumor growth and metastasis, supporting the critical role of TLN-1 in TNBC progression. Using computer-based screening/docking approach, the group further identified the interface blocker compound C67399 that can interfere with the interaction between TLN-1 and integrin and reduce tumor growth and metastasis. The article is well-formulated in general to articulate the critical and new roles of TLN-1 in TNBC and the small inhibitor has potential for further translational studies.

This is in general well-written article that may generate interest in developing TLN-1/integrin inhibitors for TNBC therapy. At the current stages, however, there are some major concerns related to the evidence that can fully support the claims.

1) The justification for TNBC is not supported by the data. Both TNBC and luminal cancer have > 40% positivity and overall DFS showed trend of poor prognosis. The Figure 1D for TNBC DFS should be removed. With such limited number (n=12 low 16 high), I don't think the statistics mean much and only one outlier will damage the statistics.

2) The claims about cancer stem cells are not necessary nor sufficiently supported. Cancer stem cells should be based on in vivo experiments rather than in vitro experiments to look at serial dilutions (cancer forming efficiency) in mouse and calculate tumor forming efficiency. Mammosphere is not accurate assay for cancer stem cell activity, nor CD24 and CD44 double staining. The spheroid structures are not mammospheres (real mammospheres should have compact morphology and nicely arranged ball like structures). Figure 2G looks like more of cell aggregate. The numbers are ranging from 4-7 and there is no description of any related methods anywhere in the article.

3) All the IP experiments are critical to show the interaction between TLN1 and integrin beta1, but most of these western blotting showed very fuzzy bands that could be just non-specific protein blotting, including Figure 4A; Figure 5J.

4) The quality of immune fluorescence in Figure 4 is in very poor quality and it doesn't seem like a co-focal image. There is no visible co-localization based Figure 4B.

5) Figure 4C looks like stress fiber formation after TLN1 is reduced. Rho family GTPases should be checked for activity.

6) shRNA to TLN1 did not show signs of cell death, and yet there is significant reduction in cell viability by the C67399. This raises the question of specificity. C67399 should be used to treat shRNA expressing cells for viability to confirm whether this is on target effect. The same goes to animal studies. This is the biggest issue of this paper to claim the effect of C67399 is through TLN1. The interruption of TLN1 and integrin-b1 is not significant in Figure 6J. There is no explanation why the inhibitor will reduce integrin-b1 expression. There is no biological experiments to show whether C67399 has any effect on TLN1-null or silenced cells.

7) There is no other critical control for the impact of C67399 on different integrins. There are quite several integrin inhibitors available. There are also antibodies that can detect activated integrins. To the least, the paper should address whether C67399 has direct impact on integrin activity and should be compared with other integrin inhibitors for different effect.

Reviewer #3:

The authors present here a manuscript detailing the effect of TLN1 gene silencing in breast cancer, and its effects on tumour biology and growth. The authors utilize a combination of in vitro assays and animal models of breast cancer (although limited in number). Further, they expand their efforts using an in-silico analysis of a large drug library to identify a lead compound that can impair TLN1 gene function (with integrin β 1) and provide preliminary evidence of its utility to affect TNBC cell and tumour growth.

The data are well presented, however the manuscript (in its current form) requires more detail to support their hypotheses and conclusions; specifically, in terms of expanded methodology, grammatical review, reanalysis of tumour growth rate, and an increased volume of cell line and patient data that can better delineate whether TLN1 is truly overrepresented in TNBC (compared to other molecular subtypes, or TNBC subtypes), and whether TLN1 biology is similar amongst these subtypes (which would increase the relevance of this paper), or if it is selective to TNBC (which would still be of importance as this is aggressive class of breast cancer with limited therapeutic options).

To bolster the strength of this manuscript, please consider the following:

Figure 1A Only 3 of 26 known integrin genes were involved in the analysis. This makes the current finding vague and low powered. Consider expanding the analysis to all 26 integrin genes, since the data should be available in publicly accessible gene expression data sets. Would be of interest to correlate gene expression with, not only molecular subclasses, but also survival metrics including relapse-free, distant metastasis and overall survival. Further, combining TLN1+/- expression with various segregation of integrin expression may yield supportive data.

Figure 1C Only 4 TNBC samples used for validation; no other breast cancer subtypes. Expand to be more inclusive of ER+ and HER2+ tumours.

Figure 1D Please show DFS in all molecular subclasses (ER+ and HER2+) of breast cancer. Provide insight into whether this is a TNBC-only phenomenon, or potentially similarly effective in all subclasses. Without this, it is not clear why the Authors would be selective only for TNBC.

Sup Figure 1A. Does TLN2 mRNA similarly stratify DFS in all breast cancer molecular subtypes, as TLN1 does? Again, without this data it is not clear why the Authors would be selective only for TLN1, and also TNBC.

Figure 2 Should incorporate a more extensive panel of breast cancer cell lines. Only 4 are shown which severely limits the correlation that TLN1 is overrepresented in TNBC. Expand panel to include at least 10 TNBC and minimum 5 ER+ and 5 HER2+ cell lines. Potentially also include mRNA gene expression within cell lines and their molecular subtypes (see Neve et al., 2006; accessible through http://co.bmc.lu.se/gobo/); which does seem to suggest TLN1 overexpression in TNBC in a panel of 50+ cell lines. A further point would be to stratify TLN1 expression across subtypes of TNBC according to Lehman et al., 2011; (https://www.jci.org/articles/view/45014). IS TLN1 predominantly expressed in TNBC subtypes that are more mesenchymal (and that inherently have a more "stem-like" phenotype). A better understanding of the background of where TLN1 is overexpressed will improve this manuscript, in terms of its relevance and importance.

Figure 2E a statistical evaluation of tumour growth rates should be performed using regression analysis, and not measured based on tumour volume size between groups at each time point. It is important to establish that the loss of TLN1 leads to a reduction in tumour growth rate, and not just tumour size at independent time points (as this could be affected by differences in tumour inoculation). What about spontaneous lung metastasis?

Figure 2. What are the effects of TLN1 silencing in other TLN1+ TNBC cell lines (or ER+ cell lines?) Are similar effects observed in cell-cycle, growth, and stem-like properties. As 231 cells are largely all "stem like", it would be important to assess this in other cell lines where "stem-like" phenotype is less extensive.

Figure 2. Does restoration of Hippo/Yap signalling pathway lead functionally restore TLN1-mediated growth inhibition in TNBC cell lines?

Figure 3 Effect on lung metastasis could just be due to reduced growth rate of modified 231 cell lines. Very little information is given in this manuscript about the experimental tail vein experiment shown in Figure 3E. How many cells were inoculated into the tail vein? How long did the experiment go for? Was routine bioluminescent imaging performed so that a true evaluation of metastatic growth rate could be determined? Do lung metastases form in animals inoculated with 231-shRNA-TLN1? If they didn't, can the experiment be extended until they do? A Kaplan-Meier analysis of survival of time to metastasis combined with bioluminescent imaging is the gold standard for experimental lung metastasis assays. Without it, no inference on metastasis can be made (and is also there is no data on metastasis shown from the orthotopically-implanted animal experiment in Figure 2). Please clarify.

Figure 4 Does TLN1 biology (interactions with beta1 integrin) similarly occur in ER+ breast cancer, or other TNBC cell lines? Does it lead to similar effects on cell localization and changes in phosphor AKT, FAK, etc? Or is it a specific TNBC effect?

Figure 5 Does C67399 similarly affect cell stemness by flowcytometry with CD24/CD44 or ALDH1+? Does it affect mammosphere formation? Does C67399 similarly affect YAP/TAZ/Oct4 signalling? Or is it just killing cancer cells, with no link to stemlike actions of TLN1? What are the effects of C67399 in vitro in TLN1 negative breast cancer cell lines?

Figure 6 Please separate out the results of the two animal experiments; it is unclear whether the lung metastasis is spontaneous (from the mammary gland injected cancer cells), or from the experimental metastasis tail vein assay. Again, the details for the experimental metastasis tail vein assay are lacking, please see my comments above. Since TLN1 is associated with chemosensitivity, would a combination of C67399 with standard of care chemotherapy drugs be more effective in the in vivo studies? Is C67399 similarly effective on TNBC xenografts (and/or other molecular subtypes of breast cancer) that do not express TLN1?

https://doi.org/10.7554/eLife.68481.sa1

Author response

Reviewer #1:

The authors established TLN1 as a potential therapeutic target for triple-negative breast cancer, an aggressive subtype, with very few treatment options. The authors used IHC on patient samples and concluded that high TLN1, but not TLN2 and other integrins expression is an independent prognostic marker for BrCa. It is important to note that TLN2/integrin expression was studied in TCGA dataset and not on the same set of samples and the conclusions on TLN2/integrins should be re-considered. The authors presented strong data on effect of TLN downregulation on cell proliferation, migration, invasion, stemness, EMT and in vivo tumor growth and metastasis. Their data suggest all aspects of tumor progression are impacted by TLN1 downregulation. Mechanistically, TLN1 downregulation impacted LATS/YAP/TAZ pathway as well as EMT proteins. The authors concluded that TLN1 silencing reduced tumor growth through Hippo/Yap signaling, which is not justified as there was no data presented, where activation of YAP/TAZ rescued stemness/tumor growth in TLN1 ablated cells. Presented data is just correlational. Same is true regarding their conclusion on EMT and Metastasis. Next, the authors confirmed the effect of TLN1 alteration on focal adhesions formation as well as other integrin signaling pathways. In the last part of the manuscript, the authors described the development and characterization of small molecule, which can inhibit interaction between beta1 integrin and TLN1. This inhibitor, C67399, affected viability, adhesion, migration, tumor growth and metastasis. However, it is important to point that all these effect on malignancy can be explained by the viability. Since cells were less viable, it is likely that non-viable cells will not adhere, migrate, form tumor or mets. This is an interesting article, but text needs to be re-worded to justify conclusions based on the data presented.

Many thanks for this critical and helpful comment! TLN1 is expressed in almost all tissues, while TLN2 is usually expressed mainly in the heart, brain, testis and muscle (23266827; 19220457). TLNs are located in a complex between adherent cells and their extracellular matrix (ECM) and regulate integrative and adhesive signaling. Previous analysis revealed that TLN1 wast the most highly expressed integrin cytoskeleton cross-linker that can trigger integrin activation (21547905). TLN1 overexpression promotes tumor invasion and metastasis via focal adhesion (20160039). A key event is binding to the integrin β cytoplasmic tail by TLN (14526080; 17627302; 18086863), a 270 kDa protein (capable of forming homodimers) with an N-terminal head domain (comprising F0, F1, F2, and F3 subdomains) and a C-terminal rod domain that binds to vinculin and actin (18434644). Binding of the F3 domain to integrin β tails is sufficient for integrin activation (11932255), although other head domains contribute to activation (18165225). Furthermore, TLN1 phosphorylation activates β1 integrins to promote prostate cancer bone metastasis (24793790).

Recommendations for the authors:

1. Figure 1: To invalidate the role of TLN2/integrins, the authors should either use same patient samples with IHC for TLN2 or use TCGA for TLN1 comparisons. Considering that beta1 integrin expression is not significantly different between various subtype, would it be possible to conclude that beta1 signaling is independent of TLN1 in the subsets, where TLN1 is not amplified.

We appreciate for this very critical comment from the referee. We would like to comment on this from two folds. (1). We first compare the AA sequence of F3 domain ring-region between TLN1 and TLN2. Please see the superimposition Author response image 1, (TLN1: aa 324-370; TLN2: aa 327-373).

Author response image 1

Moreover, please see a more detailed superimposition between TLN1 and TLN2 Author response image 2 (Sci Rep. 2017;7:41989),

Author response image 2

Therefore, we conclude that there is a rather significant difference between F3 domain ring-region of TLN1 and TLN2, where beta1 integrin interacts with TLN subtypes. We agree with the referee that it is possible that beta1 signaling is independent of TLN1 in the subsets, where TLN1 is not amplified. (2). Next, we compute and examine the binding affinities of C67399 small-molecule compound with TLN1 and TLN2, respectively. Our calculation results implicate that c67399 small-molecule compound binds more strongly with TLN1 F3 domain as compared to the binding with TLN2 F3 domain. Noteworthy, there is a nearly 1kal/mol energy difference (corresponding to more than 10-fold in terms of binding constant) and therefore c67399 small-molecule compound selectively binds with TLN1 F3 domain. Moreover, our results suggest that c67399 small-molecule might be a selective inhibitor which interrupts the interaction of TLN1 F3 domain with beta1 integrin.

Author response image 3

Furthermore, although the expression of integrin β1 is not significantly different between various subtype, the correlation between TLN1 and integrin β1 by GEPIA showed a significant positive correlation (p<0.01, R=0.34). Therefore, with the present results, we cannot conclude that integrin β1 signaling is independent of TLN1 in the isoforms in which TLN1 is not amplified.

Author response image 4

2. TNBC samples with high TLN1: are they mesenchymal type? The authors should check the correlation between TLN1/EMT/Hippo pathways, this will strengthen their hypothesis.

We appreciate for the comment from the referee. We are not sure if all TNBC samples used in IHC are of the mesenchymal types. However, it has been shown that the JAK/STAT3 signaling pathway is upregulated in TNBC mesenchymal types, that this subtype has higher expression of JAK1 and IL6, which are important drivers of JAK/STAT3 activation, and that activation or tyrosine phosphorylation of STAT3 (pSTAT3) gene signature scores (26234940) are higher in mesenchymal types than in other subtypes. Therefore, we analyzed the correlation of TLN1 with key regulators in the JAK/STAT3 pathway by GEPIA (gene expression profiling interactive analysis, http://gepia.cancer-pku.cn/) and found that TLN1 was positively correlated with JAK1, IL6 and STAT3 were positively correlated (p<0.01 for all, R=0.23 for JAK1 and STAT3, and R=0.1 for IL6), suggesting that TLN1 high expression is largely a TNBC mesenchymal type.

Author response image 5

In addition, we also analyzed the correlation between TLN1 and key regulators in the EMT/Hippo pathway with the help of GEPIA, and found that TLN1 was negatively correlated with CDH1 (p<0.01, R=-0.11), positively correlated with CDH2 (p=0.12, R=0.048), VIM (p<0.01, R=0.51), VCL(p<0.01, R=0.31) and SNAI1 (p<0.01, R=0.27). Moreover, TLN1 was positive correlation with YAP1 (p<0.01, R=0.28) and TAZ (p<0.01, R=0.17), thus indicating the positive correlation of TLN1 with EMT/Hippo pathway. Per the referees' comments, we decided to remove the data on CSC and YAP/TAZ pathway from this manuscript to avoid ambiguity.

Author response image 6

3. Figure 2: the conclusion that TLN1 affect stemness, needs to be supported by tumor initiation data. Is there any difference in tumor onset in figure 2E? Also, CSC are slow growing, which is in contrast to the current data, which suggest TLN1 promoted cell proliferation.

We want to thank the reviewer for this suggestion. There was no significant difference in tumor incidence between 231/NC and 231/shTLN1 in Figure 2E, but the overall decrease in tumor size in the 231/shTLN1 group suggests that TLN1 knockdown affects tumor growth. In addition, stem cells grow rapidly in specific stem cell medium, which is enriched with cytokines that maintain stem cell growth, and our current data show a significant downregulation of the proportion of CD44+CD24- CSCs after knockdown of TLN1 and a slowed proliferation and reduced sphere-forming ability in stem cell medium. Per the referees' comments, we decided to remove the data on CSC from this manuscript to avoid ambiguity.

4. Figure 2: To validate the role of YAP/TAZ, the authors need to perform rescue experiment using constitutively active YAP/TAZ.

We are thankful for this critical comment. Per the referees' comments, we decided to remove the data on CSC and YAP/TAZ from this manuscript to avoid ambiguity.

5. Figure 3: Are the effects on EMT proteins mediated by YAP/TAZ patwhays or this is an independent signaling from beta1 integrin.

We are thankful for this critical comment. The effects of EMT proteins have been reported in the literature to be regulated both by YAP1/TAZ patwhays (31927328, 33421513) and by integrin β1 (27836001). YAP1/TAZ proteins can then receive regulatory input from tight junctions and polar complexes, as well as proteins from adherens junctions (22075429). In this study, we focus on the fact that TLN1 binding to integrin β1 activates both focal adhesion to regulate cell-ECM adhesion and integrin downstream signaling pathways, as well as cell-cell contacts, ultimately leading to cell migration and tumor metastasis in concert. Per the referees' comments, we decided to remove the data on CSC and YAP/TAZ pathway from this manuscript to avoid ambiguity.

6. Figure 3: Effect on TNBC cell adhesion and metastasis can be a consequence of reduced cell proliferation; the conclusions needs re-wording.

We want to thank the reviewer for this very insightful comment. To exclude the possibility that the metastasis reduction following knockdown of TLN1 on TNBC cells was due to reduced cell proliferation, we performed tail vein injection of MDA-231 cells to form experimental lung metastases in Balb/c-nu mice (M Shen, 2021) and found a significant reduction in lung metastasis after TLN1 knockdown.

7. Figure 4: Conclusions on cell adhesion and migration should take viability into considerations. If the cells are dead, they will not adhere or migrate.

Many thanks for the critical comments. Based on the recommendations of the referee, we describe the above findings more critically, and the effect on TNBC cell adhesion and metastasis may also be influenced by reduced cell proliferation. To exclude this effect, we performed an in vivo test in a tail vein injection lung metastasis model, and the results showed that knockdown of TLN1 inhibited lung metastasis.

8. Figure 4J: western blots are of very poor quality. Bands were cropped too close, should show full blots. Also, inhibitors impacted the expression of beta1 integrin (4I), it will be hard to conclude that reduced association is not due to reduced expression.

We want to thank the reviewer for this comment. According to the referee’s recommendation, we add the display of the IP complete blots. In addition, combining the westernbot results and IP results of C67399 on integrin β1, it can be seen that C67399 affects both the partial expression of integrin β1 and the binding of TLN1 to integrin β1 (Figure 4-source data 1 and Figure 5-source data 1).

9. To further strengthens the conclusion, it is suggested to include cell lines from non-TNBC subtype or normal epithelial in some of their experiments as a control.

Thanks to the referee for the critical comments. From Figure 2A, we can see that TLN1 is low expressed in MCF7 and SK-BR-3 cells, thus we focus on the effect of TLN1 in TNBC cells rather than other types of breast cancer cell line.

We are truly grateful for your kind help and guidance. Again, we sincerely appreciate the time and effort you have spent on reviewing our manuscript.

Reviewer #2:

The article started with bioinformatic and pathological analysis of TCGA and/or breast cancer tissues related to focal adhesion molecules and identified talin-1 (TLN-1) as a worse prognostic marker in breast cancer in particular TNBC. Talin is known to be a component within focal adhesion and binds to the intracellular tail of integrins. Using shRNA-based silencing of TLN-1, the group found that TLN-1 is important in promoting different properties of TNBC cells – including the cell cycle progression, migration/invasion, and cancer-stem cell properties – by reducing integrin-β-mediated intracellular signaling transduction. Most importantly the group found that silencing TLN-1 reduces both primary tumor growth and metastasis, supporting the critical role of TLN-1 in TNBC progression. Using computer-based screening/docking approach, the group further identified the interface blocker compound C67399 that can interfere with the interaction between TLN-1 and integrin and reduce tumor growth and metastasis. The article is well-formulated in general to articulate the critical and new roles of TLN-1 in TNBC and the small inhibitor has potential for further translational studies.

This is in general well-written article that may generate interest in developing TLN-1/integrin inhibitors for TNBC therapy. At the current stages, however, there are some major concerns related to the evidence that can fully support the claims.

Major concerns:

1) The justification for TNBC is not supported by the data. Both TNBC and luminal cancer have > 40% positivity and overall DFS showed trend of poor prognosis. The Figure 1D for TNBC DFS should be removed. With such limited number (n=12 low 16 high), I don't think the statistics mean much and only one outlier will damage the statistics.

Thanks to the referee for the critical comments. Triple-negative breast cancer lacks effective targets, while hormone receptor-positive breast cancer has anti-endocrine therapeutic targets, so we prioritize the study of triple-negative breast cancer. To strengthen the credibility of the data, we expanded the cases of triple-negative breast cancer to 171 cases and statistically found that TLN1 in TNBC still showed a poor survival prognosis (Figure 1D).

2) The claims about cancer stem cells are not necessary nor sufficiently supported. Cancer stem cells should be based on in vivo experiments rather than in vitro experiments to look at serial dilutions (cancer forming efficiency) in mouse and calculate tumor forming efficiency. Mammosphere is not accurate assay for cancer stem cell activity, nor CD24 and CD44 double staining. The spheroid structures are not mammospheres (real mammospheres should have compact morphology and nicely arranged ball like structures). Figure 2G looks like more of cell aggregate. The numbers are ranging from 4-7 and there is no description of any related methods anywhere in the article.

Thanks to the referee for the critical comments. After taking into account the referee' s suggestions, we decided to remove the cancer stem cell content, including mammospheres and double staining for CD24 and CD44.

3) All the IP experiments are critical to show the interaction between TLN1 and integrin beta1, but most of these western blotting showed very fuzzy bands that could be just non-specific protein blotting, including Figure 4A; Figure 5J.

Thanks to the referee for the critical comments. Since IP is essential to show the interaction between TLN1 and integrin β1, we supplementally show the full membrane results of all IP experiments, including Figure 4A and Figure 5J (Figure 4-source data 1 and Figure 5-source data 1).

4) The quality of immune fluorescence in Figure 4 is in very poor quality and it doesn't seem like a co-focal image. There is no visible co-localization based Figure 4B.

Thanks to the referee for the critical comments. Per the referee’s comment, we re-conduncted the staining and showed new confocal results in Figure 4B.

5) Figure 4C looks like stress fiber formation after TLN1 is reduced. Rho family GTPases should be checked for activity.

Thanks to the referee for the critical comments. The reduction of stress fibers after TLN1 knockdown is consistent with previous literature descriptions (32273388, 27043085), but Rho family GTPases and stress fibers are not the argument of interest in this study, we are more concerned with the effect on focal adhesion after TLN1 knockdown.

6) shRNA to TLN1 did not show signs of cell death, and yet there is significant reduction in cell viability by the C67399. This raises the question of specificity. C67399 should be used to treat shRNA expressing cells for viability to confirm whether this is on target effect. The same goes to animal studies. This is the biggest issue of this paper to claim the effect of C67399 is through TLN1. The interruption of TLN1 and integrin-b1 is not significant in Figure 6J. There is no explanation why the inhibitor will reduce integrin-b1 expression. There is no biological experiments to show whether C67399 has any effect on TLN1-null or silenced cells.

Thanks to the referee for the critical comments. Figure 2C-F and shows that shTLN1 affects cell proliferation ability, apoptosis and tumor grouth, while C67399 causes a significant decrease in cell viability, indicating that C67399 is able to inhibit TLN1 expression exerting an inhibitory effect on cell proliferation. In Fig5J, C67399 was able to inhibit the expression of TLN1, while TLN1 was able to affect the expression of intergrin β1, so C67399 inhibited the expression of intergrin β1. For TNBC cells that do not express TLN1, C67399 did not have a significant inhibitory effect.

7) There is no other critical control for the impact of C67399 on different integrins. There are quite several integrin inhibitors available. There are also antibodies that can detect activated integrins. To the least, the paper should address whether C67399 has direct impact on integrin activity and should be compared with other integrin inhibitors for different effect.

We want to thank the referee for the critical comments. As added in the Discussion section, C67399, an inhibitor against TLN1-integrin β1 in this study, showed inhibition of TLN1 and thus tumor growth and metastasis, and it has been reported in the literature that TLN1 phosphorylation activates integrin β1 to promote bone metastasis in prostate cancer (24793790). However, the inhibition of TLN1 phosphorylation and activation of integrin b1 by C67399 is not known.

Reviewer #3:

The authors present here a manuscript detailing the effect of TLN1 gene silencing in breast cancer, and its effects on tumour biology and growth. The authors utilize a combination of in vitro assays and animal models of breast cancer (although limited in number). Further, they expand their efforts using an in-silico analysis of a large drug library to identify a lead compound that can impair TLN1 gene function (with integrin β 1) and provide preliminary evidence of its utility to affect TNBC cell and tumour growth.

The data are well presented, however the manuscript (in its current form) requires more detail to support their hypotheses and conclusions; specifically, in terms of expanded methodology, grammatical review, reanalysis of tumour growth rate, and an increased volume of cell line and patient data that can better delineate whether TLN1 is truly overrepresented in TNBC (compared to other molecular subtypes, or TNBC subtypes), and whether TLN1 biology is similar amongst these subtypes (which would increase the relevance of this paper), or if it is selective to TNBC (which would still be of importance as this is aggressive class of breast cancer with limited therapeutic options).

To bolster the strength of this manuscript, please consider the following:

Figure 1A Only 3 of 26 known integrin genes were involved in the analysis. This makes the current finding vague and low powered. Consider expanding the analysis to all 26 integrin genes, since the data should be available in publicly accessible gene expression data sets. Would be of interest to correlate gene expression with, not only molecular subclasses, but also survival metrics including relapse-free, distant metastasis and overall survival. Further, combining TLN1+/- expression with various segregation of integrin expression may yield supportive data.

We want to thank the reviewer for the helpful and critical comments. Per the comments, we have performed and expanding analysis to all integrins. We hope these could address the concerns.

Author response image 7
TLN1 with three integrins in the manuscript.
Author response image 8
TLN1 with 31 integrins.
Author response image 9
TLN1& ITGB1.
Author response image 10
Author response image 11

Figure 1C Only 4 TNBC samples used for validation; no other breast cancer subtypes. Expand to be more inclusive of ER+ and HER2+ tumours.

Thanks to the referee for the critical comments. As mentioned previously, this study found that TLN1 protein was specifically highly expressed in TNBC cells compared to other molecular types, suggesting a unique potential role of TLN1 for TNBC and therefore focusing on TNBC.

Figure 1D Please show DFS in all molecular subclasses (ER+ and HER2+) of breast cancer. Provide insight into whether this is a TNBC-only phenomenon, or potentially similarly effective in all subclasses. Without this, it is not clear why the Authors would be selective only for TNBC.

Thanks to the referee for the critical comments. As mentioned previously, this study found that TLN1 protein was specifically highly expressed in TNBC cells compared to other molecular subtypes, suggesting a unique potential role of TLN1 for TNBC, while limiting the expression of TLN2 in tissues, so this study focused on the intervention effect of TLN1 with TNBC and its compound C67399. To strengthen the credibility of the data, we expanded the cases of triple-negative breast cancer to 171 cases and statistically found that TLN1 in TNBC still showed a poor survival prognosis (Figure 1D).

Sup Figure 1A. Does TLN2 mRNA similarly stratify DFS in all breast cancer molecular subtypes, as TLN1 does? Again, without this data it is not clear why the Authors would be selective only for TLN1, and also TNBC.

Figure 2 Should incorporate a more extensive panel of breast cancer cell lines. Only 4 are shown which severely limits the correlation that TLN1 is overrepresented in TNBC. Expand panel to include at least 10 TNBC and minimum 5 ER+ and 5 HER2+ cell lines. Potentially also include mRNA gene expression within cell lines and their molecular subtypes (see Neve et al., 2006; accessible through http://co.bmc.lu.se/gobo/); which does seem to suggest TLN1 overexpression in TNBC in a panel of 50+ cell lines. A further point would be to stratify TLN1 expression across subtypes of TNBC according to Lehman et al., 2011; (https://www.jci.org/articles/view/45014). IS TLN1 predominantly expressed in TNBC subtypes that are more mesenchymal (and that inherently have a more "stem-like" phenotype). A better understanding of the background of where TLN1 is overexpressed will improve this manuscript, in terms of its relevance and importance.

Per the referee’s suggestion, we have incorporate a more extensive panel of breast cancer cell lines into the analysis as Author response image 12. We hope this could address the concerns.

Author response image 12

Figure 2E a statistical evaluation of tumour growth rates should be performed using regression analysis, and not measured based on tumour volume size between groups at each time point. It is important to establish that the loss of TLN1 leads to a reduction in tumour growth rate, and not just tumour size at independent time points (as this could be affected by differences in tumour inoculation). What about spontaneous lung metastasis?

We are thankful for this critical comment. No spontaneous pulmonary metastases were detected due to the rapid growth of the primary focus.

Figure 2. What are the effects of TLN1 silencing in other TLN1+ TNBC cell lines (or ER+ cell lines?) Are similar effects observed in cell-cycle, growth, and stem-like properties. As 231 cells are largely all "stem like", it would be important to assess this in other cell lines where "stem-like" phenotype is less extensive.

Thanks to the referee for the critical comments. In this study, TLN1 protein was found to be specifically highly expressed in TNBC cells compared to other molecular subtypes, suggesting a unique potential role of TLN1 for TNBC and therefore focusing on TNBC.

Figure 2. Does restoration of Hippo/Yap signalling pathway lead functionally restore TLN1-mediated growth inhibition in TNBC cell lines?

Thanks to the referee for the critical comments. Per the referees' comments, we decided to remove the data on CSC and YAP/TAZ pathway from this manuscript to avoid ambiguity.

Figure 3 Effect on lung metastasis could just be due to reduced growth rate of modified 231 cell lines. Very little information is given in this manuscript about the experimental tail vein experiment shown in Figure 3E. How many cells were inoculated into the tail vein? How long did the experiment go for? Was routine bioluminescent imaging performed so that a true evaluation of metastatic growth rate could be determined? Do lung metastases form in animals inoculated with 231-shRNA-TLN1? If they didn't, can the experiment be extended until they do? A Kaplan-Meier analysis of survival of time to metastasis combined with bioluminescent imaging is the gold standard for experimental lung metastasis assays. Without it, no inference on metastasis can be made (and is also there is no data on metastasis shown from the orthotopically-implanted animal experiment in Figure 2). Please clarify.

Thanks to the referee for the critical comments. To rule out that the effect on lung metastasis was only due to the reduced growth rate of the modified 231 cell line, in this manuscript we used tail vein alone experiments to see if knockdown of TLN1 affects lung metastasis, with specific methods added to the methodology. Bioluminescence imaging was not performed in this study, so that lung metastasis could only be determined after final execution of the sampling. Due to the rapid growth of submammary fat pad inoculated MDA-MB-231 cells, it was too late to observe spontaneous lung metastasis.

Figure 4 Does TLN1 biology (interactions with beta1 integrin) similarly occur in ER+ breast cancer, or other TNBC cell lines? Does it lead to similar effects on cell localization and changes in phosphor AKT, FAK, etc? Or is it a specific TNBC effect?

We are thankful for this critical comment. In this study, TLN1 protein was found to be specifically highly expressed in TNBC cells compared to other molecular subtypes, suggesting a unique potential role of TLN1 for TNBC and therefore focusing on TNBC, rather than other molecular subtypes.

Figure 5 Does C67399 similarly affect cell stemness by flowcytometry with CD24/CD44 or ALDH1+? Does it affect mammosphere formation? Does C67399 similarly affect YAP/TAZ/Oct4 signalling? Or is it just killing cancer cells, with no link to stemlike actions of TLN1? What are the effects of C67399 in vitro in TLN1 negative breast cancer cell lines?

We are thankful for this critical comment. Per the referees' comments, we decided to remove the data on CSC and YAP/TAZ pathway from this manuscript to avoid ambiguity.

Figure 6 Please separate out the results of the two animal experiments; it is unclear whether the lung metastasis is spontaneous (from the mammary gland injected cancer cells), or from the experimental metastasis tail vein assay. Again, the details for the experimental metastasis tail vein assay are lacking, please see my comments above. Since TLN1 is associated with chemosensitivity, would a combination of C67399 with standard of care chemotherapy drugs be more effective in the in vivo studies? Is C67399 similarly effective on TNBC xenografts (and/or other molecular subtypes of breast cancer) that do not express TLN1?

We want to thank the reviewer for this very insightful comment. We have added detailed information on experimental tail vein injection experiments in the method blood. In addition, this study focused on ths development of novel targeted agents for the TLN1-integrin β1 binding site and validation of their inhibitory effects on tumor growth and metastasis, and did not address chemosensitivity. For TNBC cells that do not express TLN1, C67399 did not have a significant inhibitory effect.

We are grateful for your insightful comments and guidance. Again, we sincerely appreciate the time and effort you have spent on reviewing our manuscript.

https://doi.org/10.7554/eLife.68481.sa2

Article and author information

Author details

  1. Yixiao Zhang

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Contribution
    Data curation, Formal analysis
    Contributed equally with
    Lisha Sun and Haonan Li
    Competing interests
    No competing interests declared
  2. Lisha Sun

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    3. Innovative Cancer Drug Research and Development Engineering Center of Liaoning Province, Shenyang, China
    Contribution
    Formal analysis, Methodology, Writing - review and editing
    Contributed equally with
    Yixiao Zhang and Haonan Li
    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
    Contribution
    Methodology, Software
    Contributed equally with
    Yixiao Zhang and Lisha Sun
    Competing interests
    No competing interests declared
  4. Liping Ai

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

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Contribution
    Methodology, Resources
    Competing interests
    No competing interests declared
  6. Xinbo Qiao

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Contribution
    Software
    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
    Contribution
    Resources
    Competing interests
    No competing interests declared
  8. Hao Zhang

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

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

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

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared
  12. Jinqi Xue

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Contribution
    Validation
    Competing interests
    No competing interests declared
  13. Xudong Zhu

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    Contribution
    Validation
    Competing interests
    No competing interests declared
  14. Yu Zhao

    Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, United States
    Contribution
    Visualization, Writing - review and editing
    Competing interests
    No competing interests declared
  15. Yongliang Yang

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. School of Bioengineering, Dalian University of Technology, Dalian, China
    Contribution
    Project administration, Validation
    For correspondence
    everbright99@foxmail.com
    Competing interests
    No competing interests declared
  16. Caigang Liu

    1. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, China
    2. Cancer Stem Cell and Translational Medicine Laboratory, Shengjing Hospital of China Medical University, Shenyang, China
    3. Innovative Cancer Drug Research and Development Engineering Center of Liaoning Province, Shenyang, China
    Contribution
    Conceptualization, Funding acquisition, Project administration, Writing - review and editing
    For correspondence
    angel-s205@163.com
    Competing interests
    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

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

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).

Senior Editor

  1. Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States

Reviewing Editor

  1. Renata Pasqualini, Rutgers University, United States

Reviewer

  1. Bedrich Eckhardt, Olivia Newton-John Cancer Research Institute, Australia

Publication history

  1. Received: March 17, 2021
  2. Accepted: March 7, 2022
  3. Accepted Manuscript published: March 14, 2022 (version 1)
  4. Version of Record published: March 21, 2022 (version 2)

Copyright

© 2022, Zhang et al.

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

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  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

Further reading

    1. Epidemiology and Global Health
    2. Medicine
    Botond Antal et al.
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    Background: Type 2 diabetes mellitus is known to be associated with neurobiological and cognitive deficits; however, their extent, overlap with aging effects, and the effectiveness of existing treatments in the context of the brain are currently unknown.

    Methods: We characterized neurocognitive effects independently associated with T2DM and age in a large cohort of human subjects from the UK Biobank with cross-sectional neuroimaging and cognitive data. We then proceeded to evaluate the extent of overlap between the effects related to T2DM and age by applying correlation measures to the separately characterized neurocognitive changes. Our findings were complemented by meta-analyses of published reports with cognitive or neuroimaging measures for T2DM and healthy controls (HC). We also evaluated in a cohort of T2DM diagnosed individuals using UK Biobank how disease chronicity and metformin treatment interact with the identified neurocognitive effects.

    Results: The UK Biobank dataset included cognitive and neuroimaging data (N=20,314) including 1,012 T2DM and 19,302 HC, aged between 50 and 80 years. Duration of T2DM ranged from 0-31 years (mean 8.5±6.1 years); 498 were treated with metformin alone, while 352 were unmedicated. Our meta-analysis evaluated 34 cognitive studies (N=22,231) and 60 neuroimaging studies: 30 of T2DM (N=866) and 30 of aging (N=1,088). As compared to age, sex, education, and hypertension-matched HC, T2DM was associated with marked cognitive deficits, particularly in executive functioning and processing speed. Likewise, we found that the diagnosis of T2DM was significantly associated with gray matter atrophy, primarily within the ventral striatum, cerebellum, and putamen, with reorganization of brain activity (decreased in the caudate and premotor cortex and increased in the subgenual area, orbitofrontal cortex, brainstem and posterior cingulate cortex). The structural and functional changes associated with T2DM show marked overlap with the effects correlating with age but appear earlier, with disease duration linked to more severe neurodegeneration. Metformin treatment status was not associated with improved neurocognitive outcomes.

    Conclusions: The neurocognitive impact of T2DM suggests marked acceleration of normal brain aging. T2DM gray matter atrophy occurred approximately 26% ± 14% faster than seen with normal aging; disease duration was associated with increased neurodegeneration. Mechanistically, our results suggest a neurometabolic component to brain aging. Clinically, neuroimaging-based biomarkers may provide a valuable adjunctive measure of T2DM progression and treatment efficacy based on neurological effects.

    Funding: The research described in this paper was funded by the W. M. Keck Foundation (to LRMP), the White House Brain Research Through Advancing Innovative Technologies (BRAIN) Initiative (NSFNCS-FR 1926781 to LRMP), and the Baszucki Brain Research Fund (to LRMP). None of the funding sources played any role in the design of the experiments, data collection, analysis, interpretation of the results, the decision to publish, or any aspect relevant to the study. DJW reports serving on data monitoring committees for Novo Nordisk. None of the authors received funding or in-kind support from pharmaceutical and/or other companies to write this manuscript.

    1. Medicine
    Hauke Basedau et al.
    Research Article

    Background:

    Monoclonal antibodies (mAbs) against calcitonin gene-related peptides (CGRP) are novel treatments for migraine prevention. Based on a previous functional imaging study which investigated the CGRP receptor mAb (erenumab), we hypothesized that (i) the CGRP ligand mAb galcanezumab would alter central trigeminal pain processing; (ii) responders to galcanezumab treatment would show specific hypothalamic modulation in contrast to non-responders; and (iii) the ligand and the receptor antibody differ in brain responses.

    Methods:

    Using an established trigeminal nociceptive functional magnetic imaging paradigm, 26 migraine patients were subsequently scanned twice: before and 2–3 weeks after administration of galcanezumab.

    Results:

    We found that galcanezumab decreases hypothalamic activation in all patients and that the reduction was stronger in responders than in non-responders. Contrasting erenumab and galcanezumab showed that both antibodies activate a distinct network. We also found that pre-treatment activity of the spinal trigeminal nucleus (STN) and coupling between the STN and the hypothalamus covariates with the response to galcanezumab.

    Conclusions:

    These data suggest that despite relative impermeability of the blood-brain barrier for CGRP mAb, mAb treatment induces certain and highly specific brain effects which may be part of the mechanism of their efficacy in migraine treatment.

    Funding:

    This work was supported by the German Ministry of Education and Research (BMBF) of ERA-Net Neuron under the project code BIOMIGA (01EW2002 to AM) and by the German Research Foundation (SFB936-178316478-A5 to AM). The funding sources did not influence study conduction in any way.

    Clinical trial number:

    The basic science study was preregistered in the Open Science Framework (https://osf.io/m2rc6).