Skip to main content
NCBI home page
American Journal of Cancer Research logoLink to American Journal of Cancer Research
. 2020 Apr 1;10(4):1238–1254.

SH3BGRL2 exerts a dual function in breast cancer growth and metastasis and is regulated by TGF-β1

Dou-Dou Li 1,2,3, Ling Deng 1, Shu-Yuan Hu 1, Fang-Lin Zhang 1,2,3, Da-Qiang Li 1,2,3,4
PMCID: PMC7191107  PMID: 32368399

Abstract

SH3 domain-binding glutamic acid-rich-like protein 2 (SH3BGRL2) is a poorly defined member of the SH3BGR gene family with potential roles in cell differentiation and tissue development. Here, we report for the first time that SH3BGRL2 exerts a dual function in breast tumor growth and metastasis. SH3BGRL2 was downregulated in a subset of primary breast tumors, and suppressed breast cancer cell proliferation and colony formation in vitro and xenograft tumor growth in vivo. Strikingly, SH3BGRL2 enhanced breast cancer cell migratory, invasive, and lung metastatic capacity. Mechanistic investigations revealed that SH3BGRL2 interacted with and transcriptionally repressed spectrin alpha, non-erythrocytic 1 (SPTAN1) and spectrin beta, non-erythrocytic 1 (SPTBN1), two important cytoskeletal proteins. Functional rescue assays further demonstrated that depletion of SH3BGRL2 reduced breast cancer cell invasive potential, which was partially rescued by knockdown of SPTAN1 and SPTBN1 using specific small interfering RNA. Moreover, transforming growth factor-β1 (TGF-β1) transcriptionally activated SH3BGRL2 expression in breast cancer cells through the canonical TGF-β receptor-Smad pathway. Collectively, these results establish a dual function of SH3BGRL2 in breast cancer growth and metastasis and uncover SH3BGRL2 as a downstream target of the TGF-β1 signaling pathway in breast cancer cells.

Keywords: Breast cancer, SH3BGRL2, SPTAN1, SPTBN1, TGF-β signaling

Introduction

Breast cancer is the most frequently diagnosed malignancy among women worldwide and is a highly heterogeneous disease with diverse molecular profiles [1-3]. Clinical evidence shows that the majority of breast cancer-related deaths occur as a result of distant metastasis rather than primary tumor itself [4-6]. Thus, a better understanding of the molecular mechanisms behind breast cancer metastasis is desperately needed. Emerging evidence shows that transforming growth factor-β (TGF-β) is an important player in breast cancer metastasis through regulating its downstream target gene expression [7-10]. Canonically, TGF-β binds to its type 2 receptor (TGFBR2) leading to activating its type 1 receptor (TGFBR1), which then phosphorylates intracellular effectors Smad2 and Smad3. The phosphorylated Smad2/3 proteins form a complex with common mediator Smad4 and then translocate into the nucleus to regulate TGF-β target gene expression [11-13]. An upregulation of TGF-β signaling is closely associated with breast cancer progression and poor prognosis [10]. Consequently, blockade of TGF-β signaling suppresses breast cancer cell motility, invasion, and metastasis [14-18]. However, the mechanisms underlying the TGF-β mediated breast cancer metastasis remain incompletely understood.

SH3 domain-binding glutamic acid-rich-like protein 2 (SH3BGRL2) is a member of the SH3 domain-binding glutamic acid-rich (SH3BGR) protein family, in addition to SH3BGR, SH3BGRL, and SH3BGRL3 [19-23]. With the exception of SH3BGRL3, this family of proteins contains a highly conserved proline-rich domain [21], which is involved in an interaction with proteins containing specific binding modules, such as the Src homology 3 (SH3), WW, and Enabled/VASP homology-1 (EVH1) domains [24]. To date, the biological functions of SH3BGRL2 are largely unknown. Very limited evidence shows that SH3BGRL2 may be involved in erythroid differentiation [25], diabetes [26], dietary fat intake [27], and zebrafish development [20]. Most recently, SH3BGRL2 was shown to act as a tumor suppressor in clear cell renal cell carcinoma through regulating Hippo/TEAD1-Twist1 signaling [28]. We recently found by analysis of publicly available databases that SH3BGRL2 is aberrantly expressed in breast tumors, but its functional and mechanistic role in breast cancer remains unexplored.

Spectrin is a widely expressed cytoskeletal protein in various cell types and is comprised of α- and β-subunits that interact in an antiparallel manner to form an heterodimer [29]. According to its distribution, spectrin is traditionally divided into erythroid and nonerythroid forms [30]. Spectrin alpha, non-erythrocytic 1 (SPTAN1) and spectrin beta, non-erythrocytic 1 (SPTBN1) are two most common members of non-erythrocytic spectrins and contain an SH3 domain [31]. As important cytoskeletal proteins and signaling molecules, SPTAN1 and SPTBN1 are involved in a number of fundamental cellular processes including cell adhesion, migration, and intercellular signaling transduction, and their deregulation has significant impacts on cancer progression [30,32,33]. In this context, SPTAN1 has been shown to influence cancer progression in both positive and negative ways depending on its localization and regulation [32]. Similarly, SPTBN1 expression and function differ between different tumor states or types [33]. However, the function and related regulatory mechanism for SPTAN1 and SPTBN1 in breast cancer remain largely unknown.

In this study, we provide evidence for the first time that SH3BGRL2 is downregulated in a subset of primary breast tumors and exerts a dual function in breast cancer growth and metastasis. Moreover, SH3BGRL2 manifests its function on breast cancer metastasis through regulating SPTAN1 and SPTBN1 expression. In addition, SH3BGRL2 is regulated by the TGF-β signaling pathway in breast cancer cells. These findings highlight a paradoxical role of SH3BGRL2 in breast cancer and may facilitate development of new targeted therapies to improve the outcome of breast cancer patients.

Materials and methods

Cell culture and reagents

The human breast cell lines (MCF-7, T47D, SK-BR-3, BT474, ZR-75-1, BT20, MDA-MB-231, BT549, and Hs578T), human mammary epithelial cell lines (MCF10A and HMEC), and human embryonic kidney 293T (HEK293T) cell line were obtained from the Cell Bank of Chinese Academy of Sciences (Shanghai, China). All cell lines were authenticated by monitoring cell vitality, mycoplasma contamination, and short tandem repeat profiling. MCF10A cells were cultured in DMEM/F12 supplemented with 5% donor horse serum (Thermofisher), 10 mg/mL insulin, 20 ng/mL epidermal growth factor (EGF), 0.5 mg/mL hydrocortisone, and 100 ng/mL cholera toxin. HMEC cells were cultured in DMEM containing 5% fetal bovine serum (FBS, ExCell Bio), 20 ng/μL EGF, 0.5 μg/mL hydrocortisone, 10 μg/mL insulin, and 1% penicillin/streptomycin. SK-BR-3 cells were cultured in McCoy’s 5A medium and other cell lines were maintained in DMEM medium supplemented with 10% FBS and 1% penicillin/streptomycin. MG-132, TGF-β receptor inhibitor SB431542, and Smad3 inhibitor SIS3 were obtained from Selleck Chemicals. Cycloheximide (CHX) was purchased from Cell Signaling Technology. Other chemicals and regents were purchased from Sigma-Aldrich unless otherwise noted. The detailed information for chemical inhibitors used in this study is provided in Table S1.

Tissue samples

A total of 28 pairs of primary breast tumor tissues and matched adjacent normal breast tissues were collected from breast cancer patients who underwent surgery at Fudan University Shanghai Cancer Center. No patients received chemotherapy, radiotherapy, or endocrine therapy before operation. This study was approved by the Research Ethics Committee of Fudan University Shanghai Cancer Center. Written informed consents were obtained from all the participants. All procedures were conducted in accordance with the ethical guidelines of the Declaration of Helsinki.

DNA constructs, shRNAs, and siRNAs

SH3BGRL2 cDNA in pEnter vector with C terminal Flag and His tag was purchased from Vigene Bioscience. Short hairpin RNAs (shRNAs) targeting human SH3BGRL2 (shSH3BGRL2) in GIPZ lentiviral vector and corresponding control constructs were purchased from Dharmacon. To generate Flag-SH3BGRL2 construct, SH3BGRL2 cDNAs were amplified by PCR and subcloned into the lentiviral vector pCDH-CMV-MCSEF1-Puro (System Biosciences). The detailed information of expression vectors and primers for molecular cloning is provided in Tables S2 and S3. Small interfering RNAs (siRNAs) targeting SPTAN1, SPTBN1, SMAD2, SMAD3, SMAD4, TGFBR1, TGFBR2, and negative control siRNA (siNC) were purchased from GenePharma, and their target sequences are listed in Table S4.

Plasmid transfection and lentiviral infection

Plasmid transfection was performed using Neofect DNA transfection reagent (Tengyi Biotech) following the manufacturer’s protocol. To generate stable cell lines, plasmid constructs or shRNAs in lentiviral expression vectors were transfected into HEK293T together with packaging plasmid mix using Neofect DNA transfection reagent. Supernatants were collected after 48 h of transfection and used for infecting cells in the presence of 8 mg/mL of polybrene. After 24 h of infection, cells were selected with 2 mg/mL of puromycin (Cayman Chemicals) for 1 week.

RNA isolation and quantitative reverse transcription-PCR

Total RNA was isolated using Trizol reagent (Invitrogen) according to the manufacturer’s protocol. Reverse transcription was performed using a PrimeScript RT reagent Kit (TaKara). Quantitative real-time PCR (qPCR) was performed using SYBR green II (Takara) to compare the relative expression levels of specific mRNAs on an Eppendorf Mastercycleer ep realplex4 instrument (Eppendorf). All oligonucleotide primers were synthesized in HuaGene Biotech. Primer sequences for qPCR are listed in Table S5. All reactions were performed in triplicate. The data is present as mean ± SD.

Dual-luciferase reporter assays

The promoter sequences of SPTAN1 and SPTBN1 were cloned into the pLG3-basic vector. Then, 10 ng of pGL3-SPTAN1, -SPTBN1, or control vectors were transfected into the corresponding cells using Neofect DNA transfection reagents (Tengyi Biotech). After 24 h of transfection, the activity of SPTAN1 and SPTBN1 promoter was determined using the dual-luciferase reporter assay system (Promega) according to the manufacturer’s protocol. All assays were repeated at least three times.

Antibodies, immunoblotting and immunoprecipitation

The information for primary antibodies used in this study is listed in Table S6. For immunoblotting, cells and tissues were lysed in RIPA buffer with 1 × protease inhibitors and phosphatase inhibitors (Bimake). The bicinchoninic acid assay kit (Yeasen) was used to determine protein concentrations. Equal amounts of proteins were separated by SDS-PAGE and transferred onto a PVDF membrane (Millipore). The membranes were incubated with indicated primary antibodies and detected with enhanced chemiluminescence detection kit (Yeasen). Quantitation of immunoblotting bands was performed using ImageJ software, and the relative expression levels of proteins were normalized to those of internal control vinculin. For immunoprecipitation (IP), cell extracts were incubated with indicated antibodies overnight at 4°C, followed by incubation with protein A/G magnetic beads (Bimake) for another 3 h. The immunoprecipitates were washed with lysis buffer three times and then analyzed by immunoblotting.

Proteomics analysis

To detect SH3BGRL2 interacting proteins, cellular lysates from HEK293T cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to IP assays with anti-Flag magnetic beads (Bimake). The immunoprecipated proteins were resolved by SDS-PAGE, visualized by Coomassie Blue staining, and then subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis as described previously [34]. All raw data was searched against Swiss-Prot database by SEQUEST. Trans Proteomic Pipeline software (Institute of Systems Biology, Seattle) was used to identify proteins based on the corresponding peptide sequences with 95% confidence.

Cell viability and colony formation assays

Cell viability was determined using Cell Counting Kit-8 (CCK-8) (Dojindo Laboratories) following the manufacturer’s protocol. The absorbance was measured at a wavelength of 450 nm (A450). For colony formation assays, cells were plated in a 6-well plate at a density of 2000 cells/well and cultured for 14 days. Cells were stained with crystal violet and the number of survival colonies was counted.

Wound-healing and transwell invasion assays

For wound-healing assays, the wound was generated using a 100 μl tip when cells reach confluence. The floated cells were removed by washing with PBS and cells were cultured in medium containing 0.1% FBS. Images were taken at the indicated times, and the wound closure ratios were calculated. For transwell invasion assays, cells were resuspended in DMEM containing 1% FBS and seeded at a density of 5 × 104 cells per well into the upper Matrigel invasion chambers (Corning BioCoat). Growth medium containing 10% FBS was placed at the lower chamber. After incubation of the indicated times, cells on the upper surface were gently removed with a cotton swab. Cells on the lower surface were fixed with methanol and then stained with crystal violet. The number of cells was counted under a light microscope with a magnification of 100.

Tumor xenografts and lung metastasis in nude mice

All experiments involving animals were in accordance with the Guides for the Care and Use of Laboratory Animals and were performed according to the institutional ethical guidelines. The study was also approved by the Institutional Animal Care and Use Committee of Fudan University. For subcutaneous inoculation, MDA-MB-231 cells stably expressing pCDH or Flag-SH3BGRL2 were injected into the mammary fat pad of 6-week-old female BALB/c athymic nude mice (4 × 106 cells/mouse, State Key Laboratory of Oncogenes and Related Genes, Shanghai, China). The tumors were measured twice a week after tumor formation and the tumor volume was calculated by the formula of (length × width2)/2. Mice were killed after 8 weeks of the inoculation. The removed tumors were weighed. For experimental lung metastasis assays, MDA-MB-231 cells stably expressing pCDH and Flag-SH3BGRL2 were injected into the tail vein of each mouse (3 × 106 cells/mouse). Mice were sacrificed 8 weeks after injection. The lungs were removed and metastatic nodules were counted. Hematoxylin and eosin staining was performed on sections of mouse lung tissues to verify metastatic lung tumors.

Statistical analysis

All experiments were replicated at least three times and the results are presented as mean ± standard error. The differences between two groups were compared by the unpaired two-tailed Student’s t-test. All statistical analyses were conducted with SPSS version 22.0 software. A p-value less than 0.05 was considered statistically significant difference.

Results

SH3BGRL2 is downregulated in a subset of primary breast tumors

To examine the expression pattern of SH3BGRL2 in breast tumors, we first analyzed SH3BGRL2 mRNA levels in The Cancer Genome Atlas (TCGA) database via UALCAN [35]. Results showed that SH3BGRL2 mRNA levels were reduced in primary breast tumors relative to normal breast tissues (Figure 1A). Moreover, this phenomenon was observed in all of three major molecular subtypes, including luminal, HER2-positive (HER2+), and triple-negative breast cancer (TNBC) (Figure 1B). Analysis of our recently published RNA-sequencing data of 360 primary TNBC tissues and 88 adjacent normal breast tissues [36] also showed that SH3BGRL2 mRNA levels were downregulated in the majority of TNBC tumors compared to normal controls (Figure 1C). Moreover, analysis of The Clinical Proteomic Tumor Analysis Consortium (CPTAC) database [37] revealed that the protein levels of SH3BGRL2 were also reduced in breast tumors, irrelevant to its molecular subtypes, compared to normal breast tissues (Figure 1D and 1E).

Figure 1.

Figure 1

Open in a new tab

SH3BGRL2 is downregulated in a subset of primary breast tumors. (A, B) Analysis of SH3BGRL2 mRNA levels in TCGA database via UALCAN [35]. (C) SH3BGRL2 mRNA levels in 360 primary TNBC tissues and 88 adjacent normal breast tissues [36]. (D, E) Analysis of SH3BGRL2 protein levels in CPTAC database [37]. (F) qPCR analysis of SH3BGRL2 mRNA levels in 28 pairs of breast tumor tissues and matched normal breast tissues. (G, H) Immunoblotting analysis of SH3BGRL2 expression levels in 28 pairs of breast tumor tissues and matched normal breast tissues. The protein gray intensity was quantified using ImageJ software. Relative expression levels of SH3BGRL2 (SH3BGRL2/vinculin) are shown in (H). N, Normal; T, tumor.

To further validate these results, we collected 28 pairs of primary breast tumor specimens and matched adjacent normal breast tissues to detect the mRNA and protein levels of SH3BGRL2 by qPCR and immunoblotting analysis, respectively. As shown in Figure 1F, 92.9% (26/28) of breast tumor tissues showed lower SH3BGRL2 mRNA levels than adjacent normal tissues. In addition, the protein levels of SH3BGRL2 were downregulated in 67.9% (19/28) of primary breast tumor samples compared to adjacent normal tissues (Figure 1G and 1H). Together, these results suggest that SH3BGRL2 is downregulated in a subset of primary breast tumor tissues.

SH3BGRL2 suppresses breast cancer cell proliferation and colony formation in vitro and xenograft tumor growth in vivo

To examine the biological function of SH3BGRL2 in breast cancer, we first examined the protein levels of SH3BGRL2 in two normal human mammary epithelial cell lines and nine representative breast cancer cell lines by immunoblotting analysis. As shown in Figure 2A, the expression levels of SH3BGRL2 in breast cancer MCF-7, BT474, ZR-75-1, BT20, and Hs578T cell lines were relatively lower than normal mammary epithelial MCF10A and HMEC cell lines. Based on SH3BGRL2 expression levels and malignant biological behaviors of those breast cancer cell lines, we next stably overexpressed Flag-SH3BGRL2 in MDA-MB-231 and Hs578T cells (Figure 2B) or depleted endogenous SH3BGRL2 in BT549 and MDA-MB-231 cells (Figure 2C) by infection of cells with lentiviral vectors expressing Flag-SH3BGRL2 or shSH3BGRL2, respectively. Expression status of SH3BGRL2 in these established stable cell lines was validated by immunoblotting analysis (Figure 2B and 2C). CCK-8 and colony formation assays showed that overexpression of SH3BGRL2 in MDA-MB-231 and Hs578T cells suppressed cell proliferation (Figure 2D) and colony formation (Figure 2E and 2F) compared to empty vector control. In contrast, knockdown of SH3BGRL2 enhanced the proliferation and colony formation capability of BT549 and MDA-MB-231 cells (Figure 2G-I). To examine whether SH3BGRL2 affects tumorigenic capacity of breast cancer cells in vivo, MDA-MB-231 cells stably expressing empty vector pCDH and Flag-SH3BGRL2 were subcutaneously injected into mammary fat pads of 6-week-old female BALB/c nude mice. In support of in vitro findings, tumors from SH3BGRL2 overexpressing MDA-MB-231 cells grew much slower at the implantation sites than their control cells (Figure 2J and 2K). Collectively, these results suggest that SH3BGRL2 suppresses breast cancer cell proliferation and colony formation in vitro and xenograft tumor growth in vivo.

Figure 2.

Figure 2

Open in a new tab

SH3BGRL2 suppresses breast cancer cell proliferation and colony formation in vitro and tumorigenesis in vivo. (A) Immunoblotting analysis of SH3BGRL2 protein levels in two normal human mammary epithelial cell lines and nine breast cancer cell lines. (B) MDA-MB-231 and Hs578T cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to immunoblotting analysis with the indicated antibodies. (C) BT549 and MDA-MB-231 cells stably expressing shNC and shSH3BGRL2 were analyzed by immunoblotting. (D-F) MDA-MB-231 and Hs578T cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to cell proliferation assays using CCK-8 kit (D) and colony formation assays (E, F). Representative images of survival colonies (E) and quantitative results (F) are shown. (G-I) BT549 and MDA-MB-231 cells stably expressing shNC and shSH3BGRL2 were subjected to cell proliferation assays using CCK-8 kit (G) and colony formation assays (H, I). Representative images of survival colonies (H) and quantitative results (I) are shown. (J, K) MDA-MB-231 cells stably expressing pCDH and Flag-SH3BGRL2 were subcutaneously injected into mammary fat pads of 6-week-old female BALB/c nude mice (n=5). Images of the xenografted tumors (J) and tumor weight (K) are shown.

SH3BGRL2 enhances breast cancer cell migratory, invasive, and metastatic potential

As breast cancer cells possess the characteristics of invasion and metastasis [4-6], we next investigated the impact of SH3BGRL2 on invasive and metastatic phenotype of breast cancer cells. Wound-healing assays showed that ectopic expression of SH3BGRL2 in MDA-MB-231 and Hs578T cells increased wound closure rate compared to empty vector-expressing control cells (Figures 3A and S1A). Transwell invasion assays showed that MDA-MB-231 and Hs578T cells expressing SH3BGRL2 had increased invasive potential compared to empty vector expressing control cells (Figure 3B and 3C). In contrast, knockdown of endogenous SH3BGRL2 in BT549 and MDA-MB-231 cells significantly inhibited their migratory and invasive capacity (Figures 3D-F and S1B). To examine whether SH3BGRL2 affects the metastatic capacity of breast cancer cells in vivo, MDA-MB-231 cells stably expressing empty vector and SH3BGRL2 were injected into nude mice through the tail vein. As shown in Figure 3G and 3H, SH3BGRL2-overexpressing cells significantly increased the number of metastatic tumors in the lungs of nude mice compared to empty vector-expressing cells. These results were also confirmed by hematoxylin-eosin staining of lung sections of these mice (Figure 3I). Collectively, these results suggest that SH3BGRL2 promotes breast cancer cell migration and invasion in vitro and metastatic capacity in vivo.

Figure 3.

Figure 3

Open in a new tab

SH3BGRL2 enhances breast cancer cell migratory, invasive, and metastatic potential. (A-C) MDA-MB-231 and Hs578T cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to wound-healing assays (A) and Transwell invasion assays (B, C). Representative images of wound-healing assays are shown in Figure S1A and the corresponding quantitative results are shown in (A). Representative images of Transwell invasion assays are shown in (B) and corresponding quantitative results are shown in (C). (D-F) BT549 and MDA-MB-231cells stably expressing shNC and shSH3BGRL2 were subjected to wound-healing assays (D) and Matrigel invasion assays (E, F). Representative images of wound-healing assays are shown in Figure S1B and the corresponding quantitative results are shown in (D). Representative images of Transwell invasion assays are shown in (E) and corresponding quantitative results are shown in (F). (G-I) MDA-MB-231 cells stably expressing pCDH and Flag-SH3BGRL2 were injected into nude mice (n=6) through tail vein. The lungs were harvested after 8 weeks of injection. Representative images of lung metastasis (G), quantitative results of lung nodules (H), and HE-stained sections of lung tissues (I) are shown.

SH3BGRL2 interacts with SPTAN1 and SPTBN1 and transcriptionally represses their expression

As SH3BGRL2 protein contains a highly conserved proline-rich domain that is involved in protein-protein interactions [21,24], we next carried out proteomic analysis to identify SH3BGRL2-interacting proteins. Toward this aim, lysates from HEK293T cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to IP assays with anti-Flag magnetic beads. After being resolved by SDS-PAGE, the precipitated proteins were visualized by Coomassie Blue staining (Figure 4A) and then subjected to LC-MS/MS based proteomic analysis [34]. According to the number of unique peptides, the top 10 potential SH3BGRL2-interacting proteins are shown in Figure 4B. Among them, the top 4 proteins, including SPTAN1, SPTBN1, myosin-1c (MYO1C), and flightless-1 (FLII), were selected for further validation. IP and immunoblotting analysis demonstrated that SH3BGRL2 indeed interacted with those 4 proteins (Figure 4C). Following these observations, we next examined whether SH3BGRL2 affects their expression levels. As showed in Figure 4D and 4E, immunoblotting analysis showed that overexpression of SH3BGRL2 led to a reduction in the protein levels of SPTAN1 and SPTBN1 in MDA-MB-231 and Hs578T cells, whereas knockdown of SH3BGRL2 upregulated their expression in BT549 and MDA-MB-231 cells. In contrast, SH3BGRL2 had no significant impact on the expression levels of FLII and MYO1C under the condition of overexpression or knockdown of SH3BGRL2 (Figure 4D and 4E).

Figure 4.

Figure 4

Open in a new tab

SH3BGRL2 interacts with SPTAN1 and SPTBN1 and transcriptionally represses their expression. (A) HEK293T Cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to IP assays with anti-Flag magnetic beads. SDS-PAGE gel was stained using Coomassie blue solution. (B) Proteomic analysis of SH3BGRL2 interacting proteins. The top 10 SH3BGRL2 interacting proteins according to the number of unique peptides are shown. (C) HEK293T Cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to sequential IP and immunoblotting analyses with the indicated antibodies. (D) Hs578T and MDA-MB-231 cells stably expressing pCDH and Flag-SH3BGRL2 were subjected to immunoblotting analysis with the indicated antibodies. (E) BT549 and MDA-MB-231 cells stably expressing shNC and shSH3BGRL2 were subjected to immunoblotting analysis with the indicated antibodies. (F) qPCR analysis of SH3BGRL2, SPTAN1, and SPTBN1 mRNA levels in MDA-MB-231 cells stably expressing pCDH and Flag-SH3BGRL2. (G) qPCR analysis of SH3BGRL2, SPTAN1, and SPTBN1 mRNA levels in MDA-MB-231 cells stably expressing shNC and shSH3BGRL2. (H) HEK293T cells were transfected with pGL3-SPTAN1 or pGL3-SPTBN1 plasmid DNA in combination with pCDH or Flag-SH3BGRL2. After 48 h of transfection, promoter activities of SPTAN1 and SPTBN1 were analyzed using the dual-luciferase reporter assay system. (I) HEK293T cells were transfected with pGL3-SPTAN1 or pGL3-SPTBN1 plasmid DNA in combination with shNC or shSH3BGRL2. After 48 h of transfection, promoter activities of SPTAN1 and SPTBN1 were analyzed using the dual-luciferase reporter assay system.

To test whether SH3BGRL2 affects SPTAN1 and SPTBN1 protein stability, we treated MDA-MB-231 stably expressing pCDH and Flag-SH3BGRL2 with or without 10 μM proteasome inhibitor MG-132 for 12 h. Results showed that the noted downregulation of SPTAN1 and SPTBN1 in SH3BGRL2 overexpressing cells was not significantly restored following MG-132 treatment (Figure S2A). CHX chase assays also demonstrated that SH3BGRL2 did not significantly affect the half-life of SPTAN1 and SPTBN1 proteins (Figure S2B). These results suggest that SH3BGRL2 does not affect the stability of SPTAN1 and SPTBN1 proteins. qPCR analysis showed that the mRNA levels of both SPTAN1 and SPTBN1 were negatively regulated by SH3BGRL2 (Figure 4F and 4G). In agreement with these data, luciferase reporter assays demonstrated that SH3BGRL2 negatively affected the promoter activities of SPTAN1 and SPTBN1 (Figure 4H and 4I). Together, these results suggest that SH3BGRL2 interacts with SPTAN1 and SPTBN1 and transcriptionally represses their expression.

SH3BGRL2 promotes breast cancer cell migration and invasion partially through negative regulation of SPTAN1 and SPTBN1

Accumulating evidence shows that SPTAN1 and SPTBN1 can influence cancer progression in a context-dependent manner [32,33], but their contribution to breast cancer progression is unknown. To address whether SH3BGRL2 promotes breast cancer migration and invasion through regulating SPTAN1 and SPTBN1, we knocked down SPTAN1 and SPTBN1 in MDA-MB-231 cells stably expressing shNC and shSH3BGRL2. The knockdown efficiency of siRNAs targeting SPTAN1 (siSPTAN1) and SPTBN1 (siSPTBN1) was verified by qPCR assays (Figure 5A and 5B). Transwell invasion assays also showed that reduced cell invasion in cells expressing shSH3BGRL2 was partially rescued following knockdown of SPTAN1 or SPTBN1 (Figure 5C-E). These results indicate that SH3BGRL2 promotes breast cancer cell invasion through, at least in part, negative regulation of SPTAN1 and SPTBN1.

Figure 5.

Figure 5

Open in a new tab

SH3BGRL2 abrogates the ability of SPTAN1 and SPTBN1 to suppress breast cancer cell invasion. (A, B) MDA-MB-231 cells were transfected with siRNAs targeting SPTAN1 (A) or SPTBN1 (B). After 48 h of transfection, qPCR analysis was carried out to examine the SPTAN1 and SPTBN1 mRNA levels in these cells. (C-E) MDA-MB-231 cells stably expressing shNC and shSH3BGRL2 were transfected with siNC, siSPTAN1#3 or siSPTBN1#3 and then subjected to Transwell invasion assays. Representative images are shown in (C) and the corresponding quantitative results are shown in (D) and (E).

SH3BGRL2 is regulated by TGF-β1

As TGF-β has a dual function in breast cancer progression at its different stages [38,39], we next evaluated whether SH3BGRL2 is regulated by TGF-β. Toward this aim, we treated MDA-MB-231 and BT549 cells with TGF-β1 for different times and then measured the mRNA and protein levels of SH3BGRL2, SPTAN1, and SPTBN1. Interestingly, we found that treatment of MDA-MB-231 and BT549 cells with TGF-β1 resulted in an upregulation of SH3BGRL2 mRNA and protein levels in a time- dependent manner (Figure 6A-D). Meanwhile, SPTAN1 and SPTBN1 expression levels showed an opposite pattern (Figure 6A-D). The noted effects of TGF-β1 on SH3BGRL2, SPTAN1, and SPTBN1 expression were blocked by pretreatment of cells with SB431542, an inhibitor for TGFBR1 [40], and SIS3, a specific inhibitor for SMAD3 [41] (Figure 7A and 7B). To further verify these findings, we next knocked down TGFBR1 and TGFBR2 by specific siRNAs and then examined the effects of TGF-β1 on SH3BGRL2, SPTAN1, and SPTBN1 expression levels. Results showed that knockdown of TGFBR1 and TGFBR2 (Figure S3A and S3B) compromised the effect of TGF-β1 on SH3BGRL2, SPTAN1, and SPTBN1 expression levels (Figure 7C and 7D). To examine which SMAD protein is involved in TGF-β1 induced SH3BGRL2 expression, we next knocked down SMAD2, SMAD3, and SMAD4 using specific siRNA, and the knockdown efficacy was verified by qPCR and immunoblotting analysis (Figure S4A-C). As shown in Figure 7E and 7F, knockdown of SMAD3 and SMAD4, but not SMAD2, compromised TGF-β1 induced upregulation of SH3BGRL2. Together, these findings suggest that SH3BGRL2 is a downstream target gene of TGF-β signaling, which regulates SH3BGRL2 expression through the canonical TGFBR/SMAD pathway.

Figure 6.

Figure 6

Open in a new tab

SH3BGRL2 is regulated by TGF-β1. (A-C) MDA-MB-231 cells were treated with or without 10 ng/ml TGF-β1 for the indicated times and then subjected to qPCR analysis of SH3BGRL2 (A), SPTAN1 (B), and SPTBN1 (C) mRNA levels. (D) MDA-MB-231 and BT549 cells treated with 10 ng/ml TGF-β1 for the indicated times and then subjected to immunoblotting analysis with the indicated antibodies. Slug is shown as a positive control.

Figure 7.

Figure 7

Open in a new tab

TGF-β1 regulates SH3BGRL2 through the canonical pathway. (A, B) MDA-MB-231 cells were pretreated with 5 μM SB431542 or 3 μM SIS3 for 2 h and then treated with 10 ng/ml TGF-β1 for another 24 h. qPCR (A) and immunoblotting (B) analysis was carried out to examine the expression levels of SH3BGRL2, SPTAN1, and SPTBN1. (C, D) MDA-MB-231 cells were transfected with siRNAs targeting TGFBR1 or TGFBR2. After 48 h of transfection, cells were treated with or without 10 ng/ml TGF-β1 for another 24 h. qPCR (C) and immunoblotting (D) analysis was carried out to examine the expression levels of SH3BGRL2, SPTAN1, and SPTBN1. (E, F) MDA-MB-231 cells were transfected with siNC, siSMAD2, siSMAD3, or siSMAD4. After 48 h of transfection, cells were treated with or without 10 ng/ml TGF-β1 for another 24 h, and then subjected to qPCR (E) or immunoblotting (F) analysis.

Discussion

In this study, we report a dual function of SH3BGRL2 in tumorigenesis and metastasis of breast cancer. SH3BGRL2 is a member of SH3BGR protein family, which encodes a cluster of small thioredoxin-like proteins [19-23]. SH3BGR was initially cloned in an effort to identify genes potentially involved in Down syndrome-associated congenital heart defects [21,42,43]. Subsequent studies demonstrated that SH3BGR members play predominant roles in tissue development and cell differentiation [20,44]. Emerging evidence shows that the aberrant expression of the members of the SH3BGR gene family is involved in human cancer development and progression. In this context, SH3BGRL is downregulated in cells expressing the v-rel oncogene and suppresses v-Rel-mediated cell transformation [45]. In addition, ectopic expression of murine SH3BGRL facilitates tumor cell invasion and lung metastasis, whereas human SH3BGRL suppresses tumorigenesis and metastasis [46]. A recent study reported that SH3BGRL2 functions as a tumor suppressor in clear cell renal cell carcinoma [28]. However, the functional and mechanistic role for SH3BGRL2 in breast cancer remains unexplored. Analysis of publicly available databases and 28 pairs of matched primary breast tumor specimens and normal breast tissues by immunoblotting and qPCR assays demonstrated that SH3BGRL2 is downregulated in a subset of primary breast tumors (Figure 1). Gain- and loss-of function assays showed that SH3BGRL2 suppresses breast tumor growth but enhances breast cancer metastatic potential (Figures 2 and 3). In support of our results, the dual activities of several cancer-related molecules in tumor development and progression have been documented previously. For instance, SnoN, an important negative regulator of TGF-β signaling, plays both pro-tumorigenic and antitumorigenic roles at different stages of mammalian malignant progression [47]. Similarly, we also recently demonstrated that F-box only protein 22 (FBXO22) possesses both protumorigenic and antimetastatic roles in breast cancer progression [48]. Based on these findings, we speculated that SH3BGRL2 may have different effects on breast cancer depending on its stage.

The TGF-β pathway is well characterized for its pleiotropic roles in human cancer development and progression [8]. Ever-growing studies have unraveled that TGF-β plays a tumor-suppressive role via inhibiting cell proliferation at the early malignant stage. While at the late stage of breast cancer, the cytostatic effects of TGF-β is attenuated along with the enhanced migration, invasion and EMT, which foster tumor progression [49,50]. In this study, we found that TGF-β1, a potent regulator in promoting breast cancer cell invasion [51], regulates SH3BGRL2 expression through the canonical pathway (Figures 6 and 7). These results further support a prometastastic role of SH3BGRL2 in breast cancer.

To address the underlying mechanism by which SH3BGRL2 promotes breast cancer metastasis, we further demonstrated that SH3BGRL2 interacts with SPTAN1 and SPTBN1, two key cytoskeletal proteins, and negatively regulates their expression (Figure 4). SPTAN1 has been shown to be involved in colorectal cancer invasion and metastasis [52,53]. In addition, SPTBN1 has been documented to suppress progression of hepatocellular carcinoma [54], and may be associated with metastases of the uveal melanoma [55]. In this study, we discovered that depletion of SPTAN1 and SPTBN1 enhances breast cancer cell migratory and invasive potential. Moreover, reduced migration and invasion in cells expressing shSH3BGRL2 was partially rescued by knockdown of SPTAN1 or SPTBN1 (Figure 5). These results indicate that SH3BGRL2 promotes breast cancer cell migration and invasion through, at least in part, negative regulation of SPTAN1 and SPTBN1. However, the detailed mechanism for regulation of SPTAN1 and SPTBN1 by SH3BGRL2 remains to be further investigated in the future.

In conclusion, findings presented here suggest SH3BGRL2 exerts a dual function in breast cancer growth and metastasis and is a downstream target of TGF-β. Further investigation into the underlying mechanism behind these observations may provide a new target for developing tailored therapy of breast cancer in the future.

Disclosure of conflict of interest

None.

Supporting Information

ajcr0010-1238-f8.pdf (693.2KB, pdf)

References

  • 1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424. doi: 10.3322/caac.21492. [DOI] [PubMed] [Google Scholar]
  • 2.Zardavas D, Irrthum A, Swanton C, Piccart M. Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol. 2015;12:381–394. doi: 10.1038/nrclinonc.2015.73. [DOI] [PubMed] [Google Scholar]
  • 3.Stingl J, Caldas C. Molecular heterogeneity of breast carcinomas and the cancer stem cell hypothesis. Nat Rev Cancer. 2007;7:791–799. doi: 10.1038/nrc2212. [DOI] [PubMed] [Google Scholar]
  • 4.Weigelt B, Peterse JL, van’t Veer LJ. Breast cancer metastasis: markers and models. Nat Rev Cancer. 2005;5:591–602. doi: 10.1038/nrc1670. [DOI] [PubMed] [Google Scholar]
  • 5.Kast K, Link T, Friedrich K, Petzold A, Niedostatek A, Schoffer O, Werner C, Klug SJ, Werner A, Gatzweiler A, Richter B, Baretton G, Wimberger P. Impact of breast cancer subtypes and patterns of metastasis on outcome. Breast Cancer Res Treat. 2015;150:621–629. doi: 10.1007/s10549-015-3341-3. [DOI] [PubMed] [Google Scholar]
  • 6.Kennecke H, Yerushalmi R, Woods R, Cheang MC, Voduc D, Speers CH, Nielsen TO, Gelmon K. Metastatic behavior of breast cancer subtypes. J. Clin. Oncol. 2010;28:3271–3277. doi: 10.1200/JCO.2009.25.9820. [DOI] [PubMed] [Google Scholar]
  • 7.Derynck R, Zhang YE. Smad-dependent and Smad-independent pathways in TGF-beta family signalling. Nature. 2003;425:577–584. doi: 10.1038/nature02006. [DOI] [PubMed] [Google Scholar]
  • 8.Massague J. TGFbeta in Cancer. Cell. 2008;134:215–230. doi: 10.1016/j.cell.2008.07.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Lamouille S, Xu J, Derynck R. Molecular mechanisms of epithelial-mesenchymal transition. Nat Rev Mol Cell Biol. 2014;15:178–196. doi: 10.1038/nrm3758. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Deckers M, van Dinther M, Buijs J, Que I, Lowik C, van der Pluijm G, ten Dijke P. The tumor suppressor Smad4 is required for transforming growth factor beta-induced epithelial to mesenchymal transition and bone metastasis of breast cancer cells. Cancer Res. 2006;66:2202–2209. doi: 10.1158/0008-5472.CAN-05-3560. [DOI] [PubMed] [Google Scholar]
  • 11.Schmierer B, Hill CS. TGFbeta-SMAD signal transduction: molecular specificity and functional flexibility. Nat Rev Mol Cell Biol. 2007;8:970–982. doi: 10.1038/nrm2297. [DOI] [PubMed] [Google Scholar]
  • 12.Massague J, Seoane J, Wotton D. Smad transcription factors. Genes Dev. 2005;19:2783–2810. doi: 10.1101/gad.1350705. [DOI] [PubMed] [Google Scholar]
  • 13.Feng XH, Derynck R. Specificity and versatility in tgf-beta signaling through Smads. Annu Rev Cell Dev Biol. 2005;21:659–693. doi: 10.1146/annurev.cellbio.21.022404.142018. [DOI] [PubMed] [Google Scholar]
  • 14.Muraoka RS, Dumont N, Ritter CA, Dugger TC, Brantley DM, Chen J, Easterly E, Roebuck LR, Ryan S, Gotwals PJ, Koteliansky V, Arteaga CL. Blockade of TGF-beta inhibits mammary tumor cell viability, migration, and metastases. J Clin Invest. 2002;109:1551–1559. doi: 10.1172/JCI15234. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Fang Y, Chen Y, Yu L, Zheng C, Qi Y, Li Z, Yang Z, Zhang Y, Shi T, Luo J, Liu M. Inhibition of breast cancer metastases by a novel inhibitor of TGFbeta receptor 1. J Natl Cancer Inst. 2013;105:47–58. doi: 10.1093/jnci/djs485. [DOI] [PubMed] [Google Scholar]
  • 16.Ganapathy V, Ge R, Grazioli A, Xie W, Banach-Petrosky W, Kang Y, Lonning S, McPherson J, Yingling JM, Biswas S, Mundy GR, Reiss M. Targeting the transforming growth factor-beta pathway inhibits human basal-like breast cancer metastasis. Mol Cancer. 2010;9:122. doi: 10.1186/1476-4598-9-122. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Park CY, Min KN, Son JY, Park SY, Nam JS, Kim DK, Sheen YY. An novel inhibitor of TGF-beta type I receptor, IN-1130, blocks breast cancer lung metastasis through inhibition of epithelial-mesenchymal transition. Cancer Lett. 2014;351:72–80. doi: 10.1016/j.canlet.2014.05.006. [DOI] [PubMed] [Google Scholar]
  • 18.Son JY, Park SY, Kim SJ, Lee SJ, Park SA, Kim MJ, Kim SW, Kim DK, Nam JS, Sheen YY. EW-7197, a novel ALK-5 kinase inhibitor, potently inhibits breast to lung metastasis. Mol Cancer Ther. 2014;13:1704–1716. doi: 10.1158/1535-7163.MCT-13-0903. [DOI] [PubMed] [Google Scholar]
  • 19.Mazzocco M, Maffei M, Egeo A, Vergano A, Arrigo P, Di Lisi R, Ghiotto F, Scartezzini P. The identification of a novel human homologue of the SH3 binding glutamic acid-rich (SH3BGR) gene establishes a new family of highly conserved small proteins related to thioredoxin superfamily. Gene. 2002;291:233–239. doi: 10.1016/s0378-1119(02)00602-9. [DOI] [PubMed] [Google Scholar]
  • 20.Tong F, Zhang M, Guo X, Shi H, Li L, Guan W, Wang H, Yang S. Expression patterns of SH3BGR family members in zebrafish development. Dev Genes Evol. 2016;226:287–295. doi: 10.1007/s00427-016-0552-5. [DOI] [PubMed] [Google Scholar]
  • 21.Scartezzini P, Egeo A, Colella S, Fumagalli P, Arrigo P, Nizetic D, Taramelli R, Rasore-Quartino A. Cloning a new human gene from chromosome 21q22.3 encoding a glutamic acid-rich protein expressed in heart and skeletal muscle. Hum Genet. 1997;99:387–392. doi: 10.1007/s004390050377. [DOI] [PubMed] [Google Scholar]
  • 22.Yin L, Xiang Y, Zhu DY, Yan N, Huang RH, Zhang Y, Wang DC. Crystal structure of human SH3BGRL protein: the first structure of the human SH3BGR family representing a novel class of thioredoxin fold proteins. Proteins. 2005;61:213–216. doi: 10.1002/prot.20523. [DOI] [PubMed] [Google Scholar]
  • 23.Egeo A, Mazzocco M, Arrigo P, Vidal-Taboada JM, Oliva R, Pirola B, Giglio S, Rasore-Quartino A, Scartezzini P. Identification and characterization of a new human gene encoding a small protein with high homology to the proline-rich region of the SH3BGR gene. Biochem Biophys Res Commun. 1998;247:302–306. doi: 10.1006/bbrc.1998.8763. [DOI] [PubMed] [Google Scholar]
  • 24.Zarrinpar A, Bhattacharyya RP, Lim WA. The structure and function of proline recognition domains. Sci STKE. 2003;2003:RE8. doi: 10.1126/stke.2003.179.re8. [DOI] [PubMed] [Google Scholar]
  • 25.De Andrade T, Moreira L, Duarte A, Lanaro C, De Albuquerque D, Saad S, Costa F. Expression of new red cell-related genes in erythroid differentiation. Biochem Genet. 2010;48:164–171. doi: 10.1007/s10528-009-9310-y. [DOI] [PubMed] [Google Scholar]
  • 26.Collares CV, Evangelista AF, Xavier DJ, Takahashi P, Almeida R, Macedo C, Manoel-Caetano F, Foss MC, Foss-Freitas MC, Rassi DM, Sakamoto-Hojo ET, Passos GA, Donadi EA. Transcriptome meta-analysis of peripheral lymphomononuclear cells indicates that gestational diabetes is closer to type 1 diabetes than to type 2 diabetes mellitus. Mol Biol Rep. 2013;40:5351–5358. doi: 10.1007/s11033-013-2635-y. [DOI] [PubMed] [Google Scholar]
  • 27.Rudkowska I, Perusse L, Bellis C, Blangero J, Despres JP, Bouchard C, Vohl MC. Interaction between common genetic variants and total fat intake on low-density lipoprotein peak particle diameter: a genome-wide association study. J Nutrigenet Nutrigenomics. 2015;8:44–53. doi: 10.1159/000431151. [DOI] [PubMed] [Google Scholar]
  • 28.Yin L, Li W, Xu A, Shi H, Wang K, Yang H, Wang R, Peng B. SH3BGRL2 inhibits growth and metastasis in clear cell renal cell carcinoma via activating hippo/TEAD1-Twist1 pathway. EBioMedicine. 2020;51:102596. doi: 10.1016/j.ebiom.2019.12.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Liem RK. Cytoskeletal integrators: the spectrin superfamily. Cold Spring Harb Perspect Biol. 2016;8 doi: 10.1101/cshperspect.a018259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Machnicka B, Grochowalska R, Boguslawska DM, Sikorski AF, Lecomte MC. Spectrin-based skeleton as an actor in cell signaling. Cell Mol Life Sci. 2012;69:191–201. doi: 10.1007/s00018-011-0804-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Ziemnicka-Kotula D, Xu J, Gu H, Potempska A, Kim KS, Jenkins EC, Trenkner E, Kotula L. Identification of a candidate human spectrin Src homology 3 domain-binding protein suggests a general mechanism of association of tyrosine kinases with the spectrin-based membrane skeleton. J Biol Chem. 1998;273:13681–13692. doi: 10.1074/jbc.273.22.13681. [DOI] [PubMed] [Google Scholar]
  • 32.Ackermann A, Brieger A. The role of nonerythroid spectrin alphaii in cancer. J Oncol. 2019;2019:7079604. doi: 10.1155/2019/7079604. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Chen S, Li J, Zhou P, Zhi X. SPTBN1 and cancer, which links? J Cell Physiol. 2020;235:17–25. doi: 10.1002/jcp.28975. [DOI] [PubMed] [Google Scholar]
  • 34.Zhao J, Yu H, Lin L, Tu J, Cai L, Chen Y, Zhong F, Lin C, He F, Yang P. Interactome study suggests multiple cellular functions of hepatoma-derived growth factor (HDGF) J Proteomics. 2011;75:588–602. doi: 10.1016/j.jprot.2011.08.021. [DOI] [PubMed] [Google Scholar]
  • 35.Chandrashekar DS, Bashel B, Balasubramanya SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi BVSK, Varambally S. UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia. 2017;19:649–658. doi: 10.1016/j.neo.2017.05.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Jiang YZ, Ma D, Suo C, Shi J, Xue M, Hu X, Xiao Y, Yu KD, Liu YR, Yu Y, Zheng Y, Li X, Zhang C, Hu P, Zhang J, Hua Q, Zhang J, Hou W, Ren L, Bao D, Li B, Yang J, Yao L, Zuo WJ, Zhao S, Gong Y, Ren YX, Zhao YX, Yang YS, Niu Z, Cao ZG, Stover DG, Verschraegen C, Kaklamani V, Daemen A, Benson JR, Takabe K, Bai F, Li DQ, Wang P, Shi L, Huang W, Shao ZM. Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies. Cancer Cell. 2019;35:428–440. e425. doi: 10.1016/j.ccell.2019.02.001. [DOI] [PubMed] [Google Scholar]
  • 37.Edwards NJ, Oberti M, Thangudu RR, Cai S, McGarvey PB, Jacob S, Madhavan S, Ketchum KA. The CPTAC data portal: a resource for cancer proteomics research. J Proteome Res. 2015;14:2707–2713. doi: 10.1021/pr501254j. [DOI] [PubMed] [Google Scholar]
  • 38.Baxley SE, Serra R. Inhibiting breast cancer progression by exploiting TGFbeta signaling. Curr Drug Targets. 2010;11:1089–1102. doi: 10.2174/138945010792006771. [DOI] [PubMed] [Google Scholar]
  • 39.Zhao Y, Ma J, Fan Y, Wang Z, Tian R, Ji W, Zhang F, Niu R. TGF-beta transactivates EGFR and facilitates breast cancer migration and invasion through canonical Smad3 and ERK/Sp1 signaling pathways. Mol Oncol. 2018;12:305–321. doi: 10.1002/1878-0261.12162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Koo BH, Kim Y, Cho YJ, Kim DS. Distinct roles of transforming growth factor-beta signaling and transforming growth factor-beta receptor inhibitor SB431542 in the regulation of p21 expression. Eur J Pharmacol. 2015;764:413–423. doi: 10.1016/j.ejphar.2015.07.032. [DOI] [PubMed] [Google Scholar]
  • 41.Jinnin M, Ihn H, Tamaki K. Characterization of SIS3, a novel specific inhibitor of Smad3, and its effect on transforming growth factor-beta1-induced extracellular matrix expression. Mol Pharmacol. 2006;69:597–607. doi: 10.1124/mol.105.017483. [DOI] [PubMed] [Google Scholar]
  • 42.Vidal-Taboada JM, Bergonon S, Scartezzini P, Egeo A, Nizetic D, Oliva R. High-resolution physical map and identification of potentially regulatory sequences of the human SH3BGR located in the Down syndrome chromosomal region. Biochem Biophys Res Commun. 1997;241:321–326. doi: 10.1006/bbrc.1997.7816. [DOI] [PubMed] [Google Scholar]
  • 43.Egeo A, Di Lisi R, Sandri C, Mazzocco M, Lapide M, Schiaffino S, Scartezzini P. Developmental expression of the SH3BGR gene, mapping to the down syndrome heart critical region. Mech Dev. 2000;90:313–316. doi: 10.1016/s0925-4773(99)00253-1. [DOI] [PubMed] [Google Scholar]
  • 44.Jang DG, Sim HJ, Song EK, Medina-Ruiz S, Seo JK, Park TJ. A thioredoxin fold protein Sh3bgr regulates Enah and is necessary for proper sarcomere formation. Dev Biol. 2015;405:1–9. doi: 10.1016/j.ydbio.2015.06.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Majid SM, Liss AS, You M, Bose HR. The suppression of SH3BGRL is important for v-Rel-mediated transformation. Oncogene. 2006;25:756–768. doi: 10.1038/sj.onc.1209107. [DOI] [PubMed] [Google Scholar]
  • 46.Wang H, Liu B, Al-Aidaroos AQ, Shi H, Li L, Guo K, Li J, Tan BC, Loo JM, Tang JP, Thura M, Zeng Q. Dual-faced SH3BGRL: oncogenic in mice, tumor suppressive in humans. Oncogene. 2016;35:3303–3313. doi: 10.1038/onc.2015.391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Zhu Q, Krakowski AR, Dunham EE, Wang L, Bandyopadhyay A, Berdeaux R, Martin GS, Sun L, Luo K. Dual role of SnoN in mammalian tumorigenesis. Mol Cell Biol. 2007;27:324–339. doi: 10.1128/MCB.01394-06. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Sun R, Xie HY, Qian JX, Huang YN, Yang F, Zhang FL, Shao ZM, Li DQ. FBXO22 possesses both protumorigenic and antimetastatic roles in breast cancer progression. Cancer Res. 2018;78:5274–5286. doi: 10.1158/0008-5472.CAN-17-3647. [DOI] [PubMed] [Google Scholar]
  • 49.Akhurst RJ, Derynck R. TGF-beta signaling in cancer--a double-edged sword. Trends Cell Biol. 2001;11:S44–51. doi: 10.1016/s0962-8924(01)02130-4. [DOI] [PubMed] [Google Scholar]
  • 50.Huang F, Shi Q, Li Y, Xu L, Xu C, Chen F, Wang H, Liao H, Chang Z, Liu F, Zhang XH, Feng XH, Han JJ, Luo S, Chen YG. HER2/EGFR-AKT signaling switches TGFbeta from inhibiting cell proliferation to promoting cell migration in breast cancer. Cancer Res. 2018;78:6073–6085. doi: 10.1158/0008-5472.CAN-18-0136. [DOI] [PubMed] [Google Scholar]
  • 51.Wang Y, Lui WY. Transforming growth factor-beta1 attenuates junctional adhesion molecule-A and contributes to breast cancer cell invasion. Eur J Cancer. 2012;48:3475–3487. doi: 10.1016/j.ejca.2012.04.016. [DOI] [PubMed] [Google Scholar]
  • 52.Ackermann A, Schrecker C, Bon D, Friedrichs N, Bankov K, Wild P, Plotz G, Zeuzem S, Herrmann E, Hansmann ML, Brieger A. Downregulation of SPTAN1 is related to MLH1 deficiency and metastasis in colorectal cancer. PLoS One. 2019;14:e0213411. doi: 10.1371/journal.pone.0213411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Hinrichsen I, Ernst BP, Nuber F, Passmann S, Schafer D, Steinke V, Friedrichs N, Plotz G, Zeuzem S, Brieger A. Reduced migration of MLH1 deficient colon cancer cells depends on SPTAN1. Mol Cancer. 2014;13:11. doi: 10.1186/1476-4598-13-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Zhi X, Lin L, Yang S, Bhuvaneshwar K, Wang H, Gusev Y, Lee MH, Kallakury B, Shivapurkar N, Cahn K, Tian X, Marshall JL, Byers SW, He AR. βII-Spectrin (SPTBN1) suppresses progression of hepatocellular carcinoma and Wnt signaling by regulation of Wnt inhibitor kallistatin. Hepatology. 2015;61:598–612. doi: 10.1002/hep.27558. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Xu Y, Han W, Xu WH, Wang Y, Yang XL, Nie HL, Yao J, Shen GL, Zhang XF. Identification of differentially expressed genes and functional annotations associated with metastases of the uveal melanoma. J Cell Biochem. 2019;120:19202–19214. doi: 10.1002/jcb.29250. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

ajcr0010-1238-f8.pdf (693.2KB, pdf)

Articles from American Journal of Cancer Research are provided here courtesy of e-Century Publishing Corporation

RESOURCES