SAP domain-dependent Mkl1 signaling stimulates proliferation and cell migration by induction of a distinct gene set indicative of poor prognosis in breast cancer patients
© Gurbuz et al.; licensee BioMed Central Ltd. 2014
Received: 28 June 2013
Accepted: 30 January 2014
Published: 5 February 2014
The main cause of death of breast cancer patients is not the primary tumor itself but the metastatic disease. Identifying breast cancer-specific signatures for metastasis and learning more about the nature of the genes involved in the metastatic process would 1) improve our understanding of the mechanisms of cancer progression and 2) reveal new therapeutic targets. Previous studies showed that the transcriptional regulator megakaryoblastic leukemia-1 (Mkl1) induces tenascin-C expression in normal and transformed mammary epithelial cells. Tenascin-C is known to be expressed in metastatic niches, is highly induced in cancer stroma and promotes breast cancer metastasis to the lung.
Using HC11 mammary epithelial cells overexpressing different Mkl1 constructs, we devised a subtractive transcript profiling screen to identify the mechanism by which Mkl1 induces a gene set co-regulated with tenascin-C. We performed computational analysis of the Mkl1 target genes and used cell biological experiments to confirm the effect of these gene products on cell behavior. To analyze whether this gene set is prognostic of accelerated cancer progression in human patients, we used the bioinformatics tool GOBO that allowed us to investigate a large breast tumor data set linked to patient data.
We discovered a breast cancer-specific set of genes including tenascin-C, which is regulated by Mkl1 in a SAP domain-dependent, serum response factor-independent manner and is strongly implicated in cell proliferation, cell motility and cancer. Downregulation of this set of transcripts by overexpression of Mkl1 lacking the SAP domain inhibited cell growth and cell migration. Many of these genes are direct Mkl1 targets since their promoter-reporter constructs were induced by Mkl1 in a SAP domain-dependent manner. Transcripts, most strongly reduced in the absence of the SAP domain were mechanoresponsive. Finally, expression of this gene set is associated with high-proliferative poor-outcome classes in human breast cancer and a strongly reduced survival rate for patients independent of tumor grade.
This study highlights a crucial role for the transcriptional regulator Mkl1 and its SAP domain during breast cancer progression. We identified a novel gene set that correlates with bad prognosis and thus may help in deciding the rigor of therapy.
Most breast cancer patients die from tumor metastases and not from the primary tumor itself. Thus, the identification of genes and signaling pathways influencing the metastatic process are of utmost importance. Once the mechanisms leading to metastasis are uncovered, they can in the future serve as a rational basis for prognosis and intervention. From the beginning of its discovery, tenascin-C has been strongly associated with tumorigenesis and cancer progression in many different types of tumors (reviewed in [1, 2]). Tenascin-C was not only enriched in breast cancer tissue [3, 4], but its high expression was part of a gene signature of breast cancers metastasizing to the lung . There is strong evidence that tenascin-C contributes to the metastatic behavior of breast cancer cells  by providing a niche for their settlement in the lung [7, 8]. The source of tenascin-C can be the tumor cells themselves as well as the stromal cells of the cancer microenvironment. Downregulation of tenascin-C by miR-335 or shRNA in human cancer cells in a mouse xenograft model inhibits metastasis formation , and in tenascin-C-deficient mice, metastasis formation of tenascin-C positive cancer cells is also suppressed .
There are many signaling pathways inducing tenascin-C expression (reviewed in ). Among these, mechanical strain application in vivo as well as to cells in culture is a potent stimulus to induce tenascin-C expression in fibroblasts [11, 12]. We have recently shown that induction of tenascin-C by cyclic mechanical strain requires the action of Mkl1 . Mkl1 is a member of the myocardin-related transcription factor family (MRTF) and a well-known transcriptional co-activator of serum response factor (SRF) [14–16]. SRF target genes, which are regulated upon recruitment of MRTF cofactors, encode proteins involved in actin cytoskeletal function that can either be structural (for example, actin) or related to actin dynamics (for example, talin 1) (reviewed in [17, 18]). However, Mkl1-mediated stretch-induced tenascin-C expression in fibroblasts did not require SRF, but instead depended on the potential DNA-binding SAP domain of Mkl1. This implies a novel mode of Mkl1 action as a bona fide transcription factor in mechanotransduction . Interestingly, normal and transformed mouse mammary epithelial cells also appear to be highly sensitive to Mkl1 signaling, responding to Mkl1 overexpression with several fold induction of tenascin-C .
The present study was designed to find SAP-dependent Mkl1 target genes co-regulated with tenascin-C and to analyze whether such genes could be indicative of specific physiological states of cells that might be controlled by mechanotransduction. For our study, we made use of the HC11 mammary epithelial cell line. HC11 cells are capable of both self-renewal and differentiation and can be cultured for unlimited time in an undifferentiated state , the condition we used in our study. HC11 cells can reconstitute the ductal epithelium of a cleared mammary fat pad in vivo with ductal, alveolar and myoepithelial cells, illustrating their stem cell abilities [19, 20]. In addition, HC11 cells contain a mutated p53 gene that not only increases the replicative potential of stem cells but confers predisposition to mammary carcinoma . Undifferentiated HC11 cells share transcriptome signatures with human breast cancer , supporting the relevance of this model for breast cancer-related studies. We therefore concluded our study by investigating whether the genes co-regulated with tenascin-C would also be implicated in breast cancer progression.
Screen for SAP-dependent Mkl1 target genes
The SAP-dependent Mkl1 target genes are implicated in cancer
SAP-dependent Mkl1 target genes
Fold Reduction in HC11-∆SAP vs. HC11-FL cells
Microarrays in 0.03% FCS
qRT-PCR in 0.03% FCS
qRT-PCR in 3% FCS
Tenascin C, ECM protein
Cell adhesion, cell migration, wound healing and tissue remodeling, cancer cell invasion and metastasis 
Anillin, actin binding protein
NADPH oxidase 4
Metallopeptidase, ECM protein
Keratin 5, intermediate filament protein
2810417H13Rik, PCNA-associated factor
Argininosuccinate synthetase 1
CD34 antigen, stem cell antigen
WNT1 inducible signaling pathway protein 1, ECM protein
Cell proliferation and survival, ECM deposition and turnover, EMT, tumorigenesis, tissue remodeling 
Minichromosome maintenance complex component 6
Cell cycle regulation 
Carbonic anyhydrase 12
Hyaluronectin, TIP30, transcriptional regulator
Kinesin family member 26B
Regulation of adhesion and cell polarity in kidney development 
Lysyl oxidase, ECM protein
Matrix metallopeptidase 12, metalloelastase
Matrix metallopeptidase 3, stromelysin-1
In addition, we monitored changes in the expression of some of the SRF-independent/SAP-dependent Mkl1 targets on a protein level. In agreement with the changes seen at the transcript level, we confirmed the reduction of tenascin-C, Wisp1 and Nox4 proteins in cells overexpressing the ΔSAP-Mkl1 construct compared to the HC11-FL control and HC11-mutB1 cells (Additional file 4: Figure S2). Using zymography, we found that Mmp2, a gene that was not affected by Mkl1 overexpression at the transcript level was highly expressed in all three cell strains, whereas Mmp3 and/or 12, which belonged to the SRF-dependent/SAP-dependent gene set, were almost completely lacking in HC11-mutB1 as well as HC11-ΔSAP cells, corresponding to the data obtained by transcript profiling.
SRF-independent/SAP-dependent transcripts represent direct Mkl1 target genes
The different HC11 cell strains proliferate at different rates and show distinct migration behaviors
Thus, overexpression of FL-Mkl1 protein in HC11 cells did not affect their behavior. However, overexpression of ΔSAP-Mkl1 led to a significant reduction in the proliferative and migratory ability of HC11 epithelial cells, either through a dominant-negative effect of ΔSAP-Mkl1 on SRF-mediated action and/or a positive impact of the SAP-dependent Mkl1 target genes on these functions important for cancer progression.
SAP-dependent Mkl1 target genes are mechanoresponsive
The SRF-independent/SAP-dependent genes represent a bad prognostic signature for breast cancer patients
Given the heterogeneity of mutations in tumor cells, it becomes increasingly clear that not only individual genes but pathways govern the course of tumorigenesis and cancer progression . We have recently shown that induction of tenascin-C by cyclic mechanical strain required the action of the potential DNA-binding SAP domain of Mkl1 independently of an interaction of Mkl1 with SRF . Now, we report a screen for genes co-regulated with tenascin-C by the same SAP-dependent and SRF-independent mechanism in mammary epithelial cells. This screen reveals a set of SAP domain-dependent Mkl1 target genes with a strong implication in cell proliferation, cell motility and cancer.
Interestingly, in parental HC11 cells many of the genes that we found in the SAP-dependent gene set that foster cell proliferation and migration and may cause poor survival of breast cancer patients are also induced by mechanical strain. A recent study has demonstrated that inhibition of cell spreading due to a lack of matrix stiffness is overcome by externally applied stretch, suggesting that similar mechanotransduction mechanisms sense stiffness and stretch . Tumor stroma is typically stiffer than normal stroma. In breast cancer, diseased tissue can be 10 times stiffer than normal breast [70, 71]. It is known that abnormal ECM stiffness plays an important role in cancer progression [72, 73], but the mechanisms by which stiffness influences cancer progression are still under investigation. If we assume that we have discovered a general reaction of mammary epithelial cells to mechanical strain, we envisage that epithelial cells in a stiff, mechanically dynamic tumor environment may react by inducing a SAP-dependent Mkl1 gene set that in turn affects tumor progression. Furthermore, the products of these genes, many of which are involved in ECM turnover and function, for example Lox , Mmps , Adamts16  or Wisp1  might themselves manipulate the tumor microenvironment, thereby influencing tumor cell survival by a positive tumorigenic feedback loop.
Finding how to switch the mode of action of Mkl1 between SRF transactivation versus its SAP-dependent transcriptional activity is a subject of ongoing research in our lab that in future may help with the development of new therapeutic interventions for breast cancer. Post-translational modifications such as sumoylation are known to influence Mkl1 transcriptional activity  and phosphorylation has been shown to influence interaction of Mkl1 with nuclear actin resulting in transcriptional changes [76, 77]. Further characterization of these and other post-transcriptional changes of Mkl1 deserve special attention when trying to answer the above question.
In the current study, we discovered a breast cancer-specific set of genes that is highly interesting as a prognostic marker and therapeutic target for several reasons. (1) The expression of this gene set is regulated by Mkl1 and its SAP domain and is independent of SRF. (2) The SAP-dependent, SRF-independent Mkl1signaling is triggered by mechanical strain and may thus be activated in stiff tumors with a high stromal content and high interstitial tissue pressure. (3) This gene set is composed of interesting members some of which represent novel candidates for playing a functional role in cancer and others that have already been implicated in cancer-related functions, as for example tenascin-C, a metastatic niche component important for lung colonization , or Lox as a gene mediating collagen crosslinking responsible for fibrosis-enhanced metastasis . (4) The SAP-dependent Mkl1 target genes are associated with a poor clinical outcome in breast cancer patients, not receiving adjuvant therapy or having a cancer classified as non-aggressive such as LN-negative, ER-positive, Grade 1 or 2 tumors. This makes these genes potential valuable prognostic markers in selecting patients who may benefit from an immediate and/or more aggressive therapy.
Full length Mkl1 (FL-Mkl1) and the two Mkl1 mutants, mutB1-Mkl1 comprising alanine substitutions of four amino acids (underlined) in the B1 domain of Mkl1 (KKAKELKPKVKKLKYHQYIPPDQKQD)  and ∆SAP-Mkl1 with a deletion of the SAP domain , were constructed based on transcript variant 1 (GenBank accession number NM_153049) as previously described . All Mkl1 variants were expressed as C-terminal RFP-tagged fusions. An empty vector expressing RFP alone was previously described .
HC11 mammary epithelial cells, kindly provided by Dr. N. Hynes (Basel, Switzerland), were grown in RPMI-1640 medium supplemented with 10% FCS, 5 μg/ml insulin (Sigma, Buchs, Switzerland) and 10 ng/ml epidermal growth factor (EGF; Invitrogen, Zug, Switzerland). In most of the experiments, the HC11 cells were starved in 0.03% FCS/RPMI without EGF. To obtain HC11 cells stably expressing FL-Mkl1-RFP (HC11-FL), mutB1-Mkl1-RFP (HC11-mutB1), ∆SAP-Mkl1-RFP (HC11-∆SAP) or RFP alone (HC11-empty vector), cells were transfected using FuGENE® 6 (Roche, Basel, Switzerland) and selected with Geneticin (1 mg/ml; Roche) for 14 days before fluorescence-activated cell sorting (FACS) of RFP-positive cells on a Vantage SE (Becton Dickinson, Basel, Switzerland). Cell viability of the four HC11 cell strains was assessed by the CellTiter-Blue viability assay (Promega, Duebendorf, Switzerland).
Cell proliferation assay
Proliferation rates of the HC11 cell strains were determined using BrdU incorporation assay (Roche). After 24 h of starvation, cells were plated in triplicate on Black 96-well microtiter plates (PerkinElmer, Schwerzenbach, Switzerland) at 5 × 103 cells/well in 3% FCS/RPMI and allowed to proliferate for 0, 24, 48, 72 and 96 h before labeling with BrdU for 2 h. BrdU incorporation into newly synthesized DNA was determined according to the manufacturer’s protocol using a Luminometer Mithras LB940 (Berthold Technologies, Regensdorf, Switzerland). Experimental values were normalized to the values of HC11-∆SAP cells at the time point 0. Data represent means ± SD from three independent experiments.
Cell migration assay
Cell migration was assayed using transwell polycarbonate membrane inserts (6.5 mm; Corning, Amsterdam, The Netherlands) with 8 μm pores as described . After 24 h of starvation, 5 × 104 cells were plated in the top insert chamber with 100 μl serum-free RPMI. The lower chamber was filled with 600 μl 10% FCS/RPMI. Cells were allowed to migrate across the filter for 22 h at 37°C before fixation and crystal violet-staining. Images of duplicate inserts were acquired on a Nikon Eclipse E600 using 10× magnification and a color CCD camera. Migration was quantified by measuring the area covered by migrated cells using the Fiji distribution of ImageJ . Data represent means ± SD from three independent experiments.
Mechanical stimulation of cells
2 × 105 HC11 cells/well were seeded in BioFlex® 6-well culture plates (Flexcell International, Hillsborough, NC, USA) coated with either growth factor reduced-Matrigel (BD Biosciences, Basel, Switzerland) or fibronectin . Cultures were starved for 24 h before applying either equibiaxial cyclic strain (15%, 0.3 Hz) or static strain (20%) at 37°C for 1 h using Flexcell FX-4000 (Flexcell International). Cells cultured under the same conditions and not exposed to strain were used as a resting control. After mechanical stimulation, cells were lysed and total RNA was isolated using the RNeasy Mini Kit (Qiagen, Basel, Switzerland).
Transcript profiling and bioinformatics analysis
HC11 cell strains stably expressing Mkl1 variants were starved for 48 h before total RNA was extracted, converted into labeled cDNA and hybridized to Affymetrix GeneChip Mouse Gene 1.0 ST arrays. RMA-normalized expression values were calculated with the Affy package from Bioconductor 2.4 , and differentially expressed genes were identified using moderated t-statistics calculated with the empirical Bayes method as implemented in the Bioconductor limma package . To be considered as differentially expressed between HC11-FL and HC11-mutB1 or HC11-∆SAP cells, genes had to pass the filters: adjusted P-value ≤ 0.01 (with Benjamin-Hochberg false discovery correction), a minimum absolute linear fold change difference of 2.0 and a minimum average expression value of 4.0 (log2). Microarray data files are available from the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/), accession number GSE44907. Using the above parameters, gene lists of the two contrasts (mutB1/FL and ∆SAP/FL) were compared resulting in the formation of three gene groups: SRF-dependent/SAP-independent, SRF-dependent/SAP-dependent and SRF-independent/SAP-dependent. The three gene sets were analyzed using the bioinformatics softwares: 1) IPA (Ingenuity® Systems; http://www.ingenuity.com); and 2) GOBO (http://co.bmc.lu.se/gobo) . In order to use the latter tool, Affymetrix GeneChip Mouse Gene 1.0 ST IDs were mapped to Affymetrix Human Genome U133A IDs using Biomart for Ensembl build 66. The module “Gene Set Analysis Tumors” was used to investigate the expression pattern and to perform survival and functional correlation analyses for the SRF-dependent/SAP-independent and SRF-independent/SAP-dependent gene sets across 1881 breast cancers characterized by Affymetrix Human Genome U133A arrays.
RNA analyses by qRT-PCR
Total RNA was isolated from HC11 cell strains after 24 h of incubation either in 0.03 or 3% FCS/RPMI. RNA was reverse transcribed and relative tenascin-C and c-fos mRNA levels were detected as described [12, 13]. Relative mRNA levels for the genes listed in Table 1, normalized to Gapdh, were measured using Platinum® SYBR® Green qPCR SuperMix-UDG with ROX (Invitrogen) and the primers listed in Additional file 4: Table S4. Real-time PCR was performed in a StepOnePlus Real-Time PCR System (Applied Biosystems, Rotkreuz, Switzerland) using a standard cycling profile. All samples were run in duplicate. Data were analyzed by the ∆Ct method  and presented as fold changes in mRNA expression levels between HC11-FL and HC11-∆SAP cells. RNA from stretched cells was analyzed by qRT-PCR using the efficiency ∆∆Ct method  that included a further normalization to the resting control. Data represent means ± SD from three independent experiments.
Protein analyses by immunoblotting and zymography
After 24 h of starvation, whole-cell extracts from the three HC11 strains were prepared in RIPA buffer and immunoblotting was performed as described [12, 13]. The following primary antibodies were used: mAb65F13 anti-Mkl1 , MTn12 anti-Tnc , anti-Wisp1/CCN4 (clone 214203, R&D Systems), anti-Nox4 (NB110-58851, Novus Biologicals), anti-Vcl (clone hVIN-1, Sigma) and anti-Gapdh (ab9485, Abcam).
After reaching 90% confluency, HC11 strains were starved for 48 h before conditioned medium was collected, concentrated and analyzed by zymography as described .
The tenascin-C promoter used in this study was described as TNC 247 bp . Promoters of Acta2  and all SRF-independent/SAP-dependent genes described in Table 1 were PCR-amplified from genomic DNA and corresponded to the sequences listed in Additional file 4: Table S5. Each promoter contained ≥ 500 bp 5′ of the TSS and was cloned into the pSEAP2-Basic (Clontech, Saint-Germain-en-Laye, France). For some promoters also 200 bp proximal promoter sequences were cloned as described above. All clones were verified by DNA sequencing.
HC11 cells in 6-well plates were cotransfected with 1 μg of the SEAP reporter vectors, 1 μg of pcDNA3 vectors encoding Mkl1 variants , and 200 ng of the secreted luciferase MetLuc vector (Clontech) used to normalize for transfection efficiency. Cells were cultured in 0.03% FCS/RPMI for 24 h before enzymatic activity measurements were performed as described . Experimental values represent averages of three independent experiments, each performed in duplicate.
Numerical results were expressed as means ± SD. Statistical analysis was completed using GraphPad InStat Software, version 3.05. The two-tailed Student’s t test was used to evaluate differences between two groups. Multiple comparisons were performed using one-way analysis of variance (ANOVA). Values of P less than 0.05 were considered statistically significant. Statistics for bioinformatics analyses is given in figure legends.
We thank Hubertus Kohler for FACS service, Stephane Thiry for microarray hybridization, and Matthias Chiquet and Richard P. Tucker for critical reading of the manuscript. This work was supported by grants from the Cancer League of Basel, the Swiss Cancer League and the Swiss National Science Foundation 3100A0-120235 and 31003A_135584 to R.C.E.
- Orend G, Chiquet-Ehrismann R: Tenascin-C induced signaling in cancer. Cancer Lett. 2006, 244: 143-163. 10.1016/j.canlet.2006.02.017View ArticlePubMedGoogle Scholar
- Brellier F, Chiquet-Ehrismann R: How do tenascins influence the birth and life of a malignant cell?. J Cell Mol Med. 2012, 16: 32-40. 10.1111/j.1582-4934.2011.01360.xPubMed CentralView ArticlePubMedGoogle Scholar
- Jahkola T, Toivonen T, Virtanen I, von Smitten K, Nordling S, von Boguslawski K, Haglund C, Nevanlinna H, Blomqvist C: Tenascin-C expression in invasion border of early breast cancer: a predictor of local and distant recurrence. Br J Cancer. 1998, 78: 1507-1513. 10.1038/bjc.1998.714PubMed CentralView ArticlePubMedGoogle Scholar
- Tsunoda T, Inada H, Kalembeyi I, Imanaka-Yoshida K, Sakakibara M, Okada R, Katsuta K, Sakakura T, Majima Y, Yoshida T: Involvement of large tenascin-C splice variants in breast cancer progression. Am J Pathol. 2003, 162: 1857-1867. 10.1016/S0002-9440(10)64320-9PubMed CentralView ArticlePubMedGoogle Scholar
- Minn AJ, Gupta GP, Siegel PM, Bos PD, Shu W, Giri DD, Viale A, Olshen AB, Gerald WL, Massague J: Genes that mediate breast cancer metastasis to lung. Nature. 2005, 436: 518-524. 10.1038/nature03799PubMed CentralView ArticlePubMedGoogle Scholar
- Calvo A, Catena R, Noble MS, Carbott D, Gil-Bazo I, Gonzalez-Moreno O, Huh JI, Sharp R, Qiu TH, Anver MR: Identification of VEGF-regulated genes associated with increased lung metastatic potential: functional involvement of tenascin-C in tumor growth and lung metastasis. Oncogene. 2008, 27: 5373-5384. 10.1038/onc.2008.155PubMed CentralView ArticlePubMedGoogle Scholar
- Tavazoie SF, Alarcon C, Oskarsson T, Padua D, Wang Q, Bos PD, Gerald WL, Massague J: Endogenous human microRNAs that suppress breast cancer metastasis. Nature. 2008, 451: 147-152. 10.1038/nature06487PubMed CentralView ArticlePubMedGoogle Scholar
- Oskarsson T, Acharyya S, Zhang XHF, Vanharanta S, Tavazoie SF, Morris PG, Downey RJ, Manova-Todorova K, Brogi E, Massague J: Breast cancer cells produce tenascin C as a metastatic niche component to colonize the lungs. Nat Med. 2011, 17: 867-874. 10.1038/nm.2379PubMed CentralView ArticlePubMedGoogle Scholar
- O'Connell JT, Sugimoto H, Cooke VG, MacDonald BA, Mehta AI, LeBleu VS, Dewar R, Rocha RM, Brentani RR, Resnick MB: VEGF-A and Tenascin-C produced by S100A4+ stromal cells are important for metastatic colonization. Proc Natl Acad Sci USA. 2011, 108: 16002-16007. 10.1073/pnas.1109493108PubMed CentralView ArticlePubMedGoogle Scholar
- Chiquet-Ehrismann R, Tucker RP: Tenascins and the importance of adhesion modulation. Cold Spring Harb Perspect Biol. 2011, doi:10.1101/cshperspect.a004960Google Scholar
- Chiquet M, Sarasa-Renedo A, Tunc-Civelek V: Induction of tenascin-C by cyclic tensile strain versus growth factors: distinct contributions by Rho/ROCK and MAPK signaling pathways. Biochim Biophys Acta. 2004, 1693: 193-204. 10.1016/j.bbamcr.2004.08.001View ArticlePubMedGoogle Scholar
- Maier S, Lutz R, Gelman L, Sarasa-Renedo A, Schenk S, Grashoff C, Chiquet M: Tenascin-C induction by cyclic strain requires integrin-linked kinase. Biochim Biophys Acta. 2008, 1783: 1150-1162. 10.1016/j.bbamcr.2008.01.013View ArticlePubMedGoogle Scholar
- Asparuhova MB, Ferralli J, Chiquet M, Chiquet-Ehrismann R: The transcriptional regulator megakaryoblastic leukemia-1 mediates serum response factor-independent activation of tenascin-C transcription by mechanical stress. FASEB J. 2011, 25: 3477-3488. 10.1096/fj.11-187310View ArticlePubMedGoogle Scholar
- Wang DZ, Li S, Hockemeyer D, Sutherland L, Wang Z, Schratt G, Richardson JA, Nordheim A, Olson EN: Potentiation of serum response factor activity by a family of myocardin-related transcription factors. Proc Natl Acad Sci USA. 2002, 99: 14855-14860. 10.1073/pnas.222561499PubMed CentralView ArticlePubMedGoogle Scholar
- Cen B, Selvaraj A, Burgess RC, Hitzler JK, Ma Z, Morris SW, Prywes R: Megakaryoblastic leukemia 1, a potent transcriptional coactivator for serum response factor (SRF), is required for serum induction of SRF target genes. Mol Cell Biol. 2003, 23: 6597-6608. 10.1128/MCB.23.18.6597-6608.2003PubMed CentralView ArticlePubMedGoogle Scholar
- Miralles F, Posern G, Zaromytidou AI, Treisman R: Actin dynamics control SRF activity by regulation of its coactivator MAL. Cell. 2003, 113: 329-342. 10.1016/S0092-8674(03)00278-2View ArticlePubMedGoogle Scholar
- Olson EN, Nordheim A: Linking actin dynamics and gene transcription to drive cellular motile functions. Nat Rev Mol Cell Biol. 2010, 11: 353-365. 10.1038/nrm2890PubMed CentralView ArticlePubMedGoogle Scholar
- Miano JM, Long X, Fujiwara K: Serum response factor: master regulator of the actin cytoskeleton and contractile apparatus. Am J Physiol Cell Physiol. 2007, 292: C70-C81.View ArticlePubMedGoogle Scholar
- Ball R, Friis R, Schoenenberger C, Doppler W, Groner B: Prolactin regulation of beta-casein gene expression and of a cytosolic 120-kd protein in a cloned mouse mammary epithelial cell line. EMBO J. 1988, 7: 2089-2095.PubMed CentralPubMedGoogle Scholar
- Humphreys R, Rosen J: Stably transfected HC11 cells provide an in vitro and in vivo model system for studying Wnt gene function. Cell Growth Differ. 1997, 8: 839-849.PubMedGoogle Scholar
- Cicalese A, Bonizzi G, Pasi CE, Faretta M, Ronzoni S, Giulini B, Brisken C, Minucci S, Di Fiore PP, Pelicci PG: The tumor suppressor p53 regulates polarity of self-renewing divisions in mammary stem cells. Cell. 2009, 138: 1083-1095. 10.1016/j.cell.2009.06.048View ArticlePubMedGoogle Scholar
- Williams C, Helguero L, Edvardsson K, Haldosen LA, Gustafsson JA: Gene expression in murine mammary epithelial stem cell-like cells shows similarities to human breast cancer gene expression. Breast Cancer Res. 2009, 11: R26- 10.1186/bcr2256PubMed CentralView ArticlePubMedGoogle Scholar
- Cen B, Selvaraj A, Prywes R: Myocardin/MKL family of SRF coactivators: key regulators of immediate early and muscle specific gene expression. J Cell Biochem. 2004, 93: 74-82. 10.1002/jcb.20199View ArticlePubMedGoogle Scholar
- Wang DZ, Olson EN: Control of smooth muscle development by the myocardin family of transcriptional coactivators. Curr Opin Genet Dev. 2004, 14: 558-566. 10.1016/j.gde.2004.08.003View ArticlePubMedGoogle Scholar
- Pipes GCT, Creemers EE, Olson EN: The myocardin family of transcriptional coactivators: versatile regulators of cell growth, migration, and myogenesis. Genes Dev. 2006, 20: 1545-1556. 10.1101/gad.1428006View ArticlePubMedGoogle Scholar
- Piekny AJ, Maddox AS: The myriad roles of Anillin during cytokinesis. Semin Cell Dev Biol. 2010, 21: 881-891. 10.1016/j.semcdb.2010.08.002View ArticlePubMedGoogle Scholar
- Hall PA, Todd CB, Hyland PL, McDade SS, Grabsch H, Dattani M: The septin-binding protein anillin is overexpressed in diverse human tumors. Clin Cancer Res. 2005, 11: 6780-6786. 10.1158/1078-0432.CCR-05-0997View ArticlePubMedGoogle Scholar
- Suzuki C, Daigo Y, Ishikawa N, Kato T, Hayama S, Ito T: ANLN plays a critical role in human lung carcinogenesis through the activation of RhoA and by involvement in the phosphoinositide 3-kinase/AKT pathway. Cancer Res. 2005, 65: 11314-11325. 10.1158/0008-5472.CAN-05-1507View ArticlePubMedGoogle Scholar
- Reddy MM, Fernandes MS, Salgia R, Levine RL, Griffin JD, Sattler M: NADPH oxidases regulate cell growth and migration in myeloid cells transformed by oncogenic tyrosine kinases. Leukemia. 2011, 25: 281-289. 10.1038/leu.2010.263PubMed CentralView ArticlePubMedGoogle Scholar
- Ushio-Fukai M, Nakamura Y: Reactive oxygen species and angiogenesis: NADPH oxidase as target for cancer therapy. Cancer Lett. 2008, 266: 37-52. 10.1016/j.canlet.2008.02.044PubMed CentralView ArticlePubMedGoogle Scholar
- Sakamoto N, Oue N, Noguchi T, Sentani K, Anami K, Sanada Y: Serial analysis of gene expression of esophageal squamous cell carcinoma: ADAMTS16 is upregulated in esophageal squamous cell carcinoma. Cancer Sci. 2010, 101: 1038-1044. 10.1111/j.1349-7006.2009.01477.xView ArticlePubMedGoogle Scholar
- Davidson RK, Waters JG, Kevorkian L, Darrah C, Cooper A, Donell ST: Expression profiling of metalloproteinases and their inhibitors in synovium and cartilage. Arthritis Res Ther. 2006, 8: R124- 10.1186/ar2013PubMed CentralView ArticlePubMedGoogle Scholar
- Kim S, Wong P, Coulombe PA: A keratin cytoskeletal protein regulates protein synthesis and epithelial cell growth. Nature. 2006, 441: 362-365. 10.1038/nature04659View ArticlePubMedGoogle Scholar
- Alam H, Sehgal L, Kundu ST, Dalal SN, Vaidya MM: Novel function of keratins 5 and 14 in proliferation and differentiation of stratified epithelial cells. Mol Biol Cell. 2011, 22: 4068-4078. 10.1091/mbc.E10-08-0703PubMed CentralView ArticlePubMedGoogle Scholar
- Hosokawa M, Takehara A, Matsuda K, Eguchi H, Ohigashi H, Ishikawa O: Oncogenic role of KIAA0101 interacting with proliferating cell nuclear antigen in pancreatic cancer. Cancer Res. 2007, 67: 2568-2576. 10.1158/0008-5472.CAN-06-4356View ArticlePubMedGoogle Scholar
- Xu L, Geman D, Winslow R: Large-scale integration of cancer microarray data identifies a robust common cancer signature. BMC Bioinforma. 2007, 8: 275-10.1186/1471-2105-8-275.View ArticleGoogle Scholar
- Turchi L, Fareh M, Aberdam E, Kitajima S, Simpson F, Wicking C: ATF3 and p15PAF are novel gatekeepers of genomic integrity upon UV stress. Cell Death Differ. 2009, 16: 728-737. 10.1038/cdd.2009.2View ArticlePubMedGoogle Scholar
- Amrani YM, Gill J, Matevossian A, Alonzo ES, Yang C, Shieh JH: The Paf oncogene is essential for hematopoietic stem cell function and development. J Exp Med. 2011, 208: 1757-1765. 10.1084/jem.20102170PubMed CentralView ArticlePubMedGoogle Scholar
- Zhao Y, Zhang J, Li H, Li Y, Ren J, Luo M: An NADPH sensor protein (HSCARG) down-regulates nitric oxide synthesis by association with argininosuccinate synthetase and is essential for epithelial cell viability. J Biol Chem. 2008, 283: 11004-11013. 10.1074/jbc.M708697200View ArticlePubMedGoogle Scholar
- Mun GI, Kim IS, Lee BH, Boo YC: Endothelial argininosuccinate synthetase 1 regulates nitric oxide production and monocyte adhesion under static and laminar shear stress conditions. J Biol Chem. 2011, 286: 2536-2542. 10.1074/jbc.M110.180489PubMed CentralView ArticlePubMedGoogle Scholar
- Blanchet MR, Gold M, Maltby S, Bennett J, Petri B, Kubes P: Loss of CD34 Leads To exacerbated autoimmune arthritis through increased vascular permeability. J Immunol. 2010, 184: 1292-1299. 10.4049/jimmunol.0900808View ArticlePubMedGoogle Scholar
- Trempus CS, Morris RJ, Ehinger M, Elmore A, Bortner CD, Ito M: CD34 Expression by hair follicle stem cells is required for skin tumor development in mice. Cancer Res. 2007, 67: 4173-4181. 10.1158/0008-5472.CAN-06-3128PubMed CentralView ArticlePubMedGoogle Scholar
- Maltby S, Freeman S, Gold MJ, Baker JH, Minchinton AI, Gold MR: Opposing roles for CD34 in B16 melanoma tumor growth alter early stage vasculature and late stage immune cell infiltration. PLoS One. 2011, 6: e18160- 10.1371/journal.pone.0018160PubMed CentralView ArticlePubMedGoogle Scholar
- Berschneider B, Koenigshoff M: WNT1 inducible signaling pathway protein 1 (WISP1): A novel mediator linking development and disease. Int J Biochem Cell Biol. 2011, 43: 306-309. 10.1016/j.biocel.2010.11.013View ArticlePubMedGoogle Scholar
- Noseda M, Karsan A: Notch and minichromosome maintenance (MCM) proteins: integration of two ancestral pathways in cell cycle control. Cell Cycle. 2006, 5: 2704-2709. 10.4161/cc.5.23.3515View ArticlePubMedGoogle Scholar
- Hsieh MJ, Chen KS, Chiou HL, Hsieh YS: Carbonic anhydrase XII promotes invasion and migration ability of MDA-MB-231 breast cancer cells through the p38 MAPK signaling pathway. Eur J Cell Biol. 2010, 89: 598-606. 10.1016/j.ejcb.2010.03.004View ArticlePubMedGoogle Scholar
- Neri D, Supuran CT: Interfering with pH regulation in tumours as a therapeutic strategy. Nat Rev Drug Discov. 2011, 10: 767-777. 10.1038/nrd3554View ArticlePubMedGoogle Scholar
- Whitman S, Wang X, Shalaby R, Shtivelman E: Alternatively spliced products CC3 and TC3 have opposing effects on apoptosis. Mol Cell Biol. 2000, 20: 583-593. 10.1128/MCB.20.2.583-593.2000PubMed CentralView ArticlePubMedGoogle Scholar
- Paris S, Sesboue R, Chauzy C, Maingonnat C, Delpech B: Hyaluronectin modulation of lung metastasis in nude mice. Eur J Cancer. 2006, 42: 3253-3259. 10.1016/j.ejca.2006.06.012View ArticlePubMedGoogle Scholar
- Uchiyama Y, Sakaguchi M, Terabayashi T, Inenaga T, Inoue S, Kobayashi C: Kif26b, a kinesin family gene, regulates adhesion of the embryonic kidney mesenchyme. Proc Natl Acad Sci USA. 2010, 107: 9240-9245. 10.1073/pnas.0913748107PubMed CentralView ArticlePubMedGoogle Scholar
- Lucero H, Kagan H: Lysyl oxidase: an oxidative enzyme and effector of cell function. Cell Mol Life Sci. 2006, 63: 2304-2316. 10.1007/s00018-006-6149-9View ArticlePubMedGoogle Scholar
- Rodriguez C, Rodriguez-Sinovas A, Martinez-Gonzalez J: Lysyl oxidase as a potential therapeutic target. Drug News Perspect. 2008, 21: 218-224. 10.1358/dnp.2008.21.4.1213351View ArticlePubMedGoogle Scholar
- Shiomi T, Lemaitre V, D'Armiento J, Okada Y: Matrix metalloproteinases, a disintegrin and metalloproteinases, and a disintegrin and metalloproteinases with thrombospondin motifs in non-neoplastic diseases. Pathol Int. 2010, 60: 477-496. 10.1111/j.1440-1827.2010.02547.xPubMed CentralView ArticlePubMedGoogle Scholar
- Hua H, Li M, Luo T, Yin Y, Jiang Y: Matrix metalloproteinases in tumorigenesis: an evolving paradigm. Cell Mol Life Sci. 2011, 68: 3853-3868. 10.1007/s00018-011-0763-xView ArticlePubMedGoogle Scholar
- Elberg G, Chen L, Elberg D, Chan MD, Logan CJ, Turman MA: MKL1 mediates TGF-β1-induced α-smooth muscle actin expression in human renal epithelial cells. Am J Physiol Renal Physiol. 2008, 294: F1116-F1128. 10.1152/ajprenal.00142.2007View ArticlePubMedGoogle Scholar
- Long X, Cowan SL, Miano JM: Mitogen-activated protein kinase 14 is a novel negative regulatory switch for the vascular smooth muscle cell contractile gene program. Arterioscler Thromb Vasc Biol. 2013, 33: 378-386. 10.1161/ATVBAHA.112.300645View ArticlePubMedGoogle Scholar
- Quaglino A, Salierno M, Pellegrotti J, Rubinstein N, Kordon E: Mechanical strain induces involution-associated events in mammary epithelial cells. BMC Cell Biol. 2009, 10: 55- 10.1186/1471-2121-10-55PubMed CentralView ArticlePubMedGoogle Scholar
- Cox TR, Bird D, Baker AM, Barker HE, Ho MWY, Lang G, Erler JT: LOX-mediated collagen crosslinking is responsible for fibrosis-enhanced metastasis. Cancer Res. 2013, 73: 1721-1732. 10.1158/0008-5472.CAN-12-2233PubMed CentralView ArticlePubMedGoogle Scholar
- Ringner M, Fredlund E, Hakkinen J, Borg Å, Staaf J: GOBO: gene expression-based outcome for breast cancer online. PLoS One. 2011, 6: e17911- 10.1371/journal.pone.0017911PubMed CentralView ArticlePubMedGoogle Scholar
- Parker JS, Mullins M, Cheang MCU, Leung S, Voduc D, Vickery T, Davies S, Fauron C, He X, Hu Z: Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009, 27: 1160-1167. 10.1200/JCO.2008.18.1370PubMed CentralView ArticlePubMedGoogle Scholar
- Fredlund E, Staaf J, Rantala J, Kallioniemi O, Borg A, Ringner M: The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition. Breast Cancer Res. 2012, 14: R113- 10.1186/bcr3236PubMed CentralView ArticlePubMedGoogle Scholar
- Minn AJ, Bevilacqua E, Yun J, Rosner MR: Identification of novel metastasis suppressor signaling pathways for breast cancer. Cell Cycle. 2012, 11: 2452-2457. 10.4161/cc.20624PubMed CentralView ArticlePubMedGoogle Scholar
- Scharenberg MA, Chiquet-Ehrismann R, Asparuhova MB: Megakaryoblastic leukemia protein-1 (MKL1): Increasing evidence for an involvement in cancer progression and metastasis. Int J Biochem Cell Biol. 2010, 42: 1911-1914. 10.1016/j.biocel.2010.08.014View ArticlePubMedGoogle Scholar
- Medjkane S, Perez-Sanchez C, Gaggioli C, Sahai E, Treisman R: Myocardin-related transcription factors and SRF are required for cytoskeletal dynamics and experimental metastasis. Nat Cell Biol. 2009, 11: 257-268. 10.1038/ncb1833View ArticlePubMedGoogle Scholar
- Descot A, Hoffmann R, Shaposhnikov D, Reschke M, Ullrich A, Posern G: Negative regulation of the EGFR-MAPK cascade by actin-MAL-mediated Mig6/Errfi-1 induction. Mol Cell. 2009, 35: 291-304. 10.1016/j.molcel.2009.07.015View ArticlePubMedGoogle Scholar
- Leitner L, Shaposhnikov D, Descot A, Hoffmann R, Posern G: Epithelial protein lost in neoplasm alpha (Eplin-alpha) is transcriptionally regulated by G-actin and MAL/MRTF coactivators. Mol Cancer. 2010, 9: 60- 10.1186/1476-4598-9-60PubMed CentralView ArticlePubMedGoogle Scholar
- Yoshio T, Morita T, Tsujii M, Hayashi N, Sobue K: MRTF-A/B suppress the oncogenic properties of v-ras- and v-src-mediated transformants. Carcinogenesis. 2010, 31: 1185-1193. 10.1093/carcin/bgq065View ArticlePubMedGoogle Scholar
- Brandt DT, Baarlink C, Kitzing TM, Kremmer E, Ivaska J, Nollau P, Grosse R: SCAI acts as a suppressor of cancer cell invasion through the transcriptional control of beta1-integrin. Nat Cell Biol. 2009, 11: 557-568. 10.1038/ncb1862View ArticlePubMedGoogle Scholar
- Throm Quinlan A, Sierad L, Capulli A, Firstenberg L, Billiar K: Combining dynamic stretch and tunable stiffness to probe cell mechanobiology in vitro. PLoS One. 2011, 6: e23272- 10.1371/journal.pone.0023272PubMed CentralView ArticlePubMedGoogle Scholar
- Levental KR, Yu H, Kass L, Lakins JN, Egeblad M, Erler JT, Fong SFT, Csiszar K, Giaccia A, Weninger W: Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell. 2009, 139: 891-906. 10.1016/j.cell.2009.10.027PubMed CentralView ArticlePubMedGoogle Scholar
- Lopez JI, Kang I, You WK, McDonald DM, Weaver VM: In situ force mapping of mammary gland transformation. Integr Biol (Camb). 2011, 3: 910-921. 10.1039/c1ib00043hView ArticleGoogle Scholar
- Cox TR, Erler JT: Remodeling and homeostasis of the extracellular matrix: implications for fibrotic diseases and cancer. Dis Model Mech. 2011, 4: 165-178. 10.1242/dmm.004077PubMed CentralView ArticlePubMedGoogle Scholar
- Lu P, Weaver VM, Werb Z: The extracellular matrix: A dynamic niche in cancer progression. J Cell Biol. 2012, 196: 395-406. 10.1083/jcb.201102147PubMed CentralView ArticlePubMedGoogle Scholar
- Kessenbrock K, Plaks V, Werb Z: Matrix metalloproteinases: Regulators of the tumor microenvironment. Cell. 2010, 141: 52-67. 10.1016/j.cell.2010.03.015PubMed CentralView ArticlePubMedGoogle Scholar
- Nakagawa K, Kuzumaki N: Transcriptional activity of megakaryoblastic leukemia 1 (MKL1) is repressed by SUMO modification. Genes Cells. 2005, 10: 835-850. 10.1111/j.1365-2443.2005.00880.xView ArticlePubMedGoogle Scholar
- Muehlich S, Wang R, Lee SM, Lewis TC, Dai C, Prywes R: Serum-induced phosphorylation of the serum response factor coactivator MKL1 by the extracellular signal-regulated kinase 1/2 pathway inhibits its nuclear localization. Mol Cell Biol. 2008, 28: 6302-6313. 10.1128/MCB.00427-08PubMed CentralView ArticlePubMedGoogle Scholar
- Muehlich S, Hampl V, Khalid S, Singer S, Frank N, Breuhahn K, Gudermann T, Prywes R: The transcriptional coactivators megakaryoblastic leukemia 1/2 mediate the effects of loss of the tumor suppressor deleted in liver cancer 1. Oncogene. 2012, 31: 3913-3923. 10.1038/onc.2011.560View ArticlePubMedGoogle Scholar
- Zaromytidou AI, Miralles F, Treisman R: MAL and ternary complex factor use different mechanisms to contact a common surface on the serum response factor DNA-binding domain. Mol Cell Biol. 2006, 26: 4134-4148. 10.1128/MCB.01902-05PubMed CentralView ArticlePubMedGoogle Scholar
- Brellier F, Ruggiero S, Zwolanek D, Martina E, Hess D, Brown-Luedi M, Hartmann U, Koch M, Merlo A, Lino M, Chiquet-Ehrismann R: SMOC1 is a tenascin-C interacting protein over-expressed in brain tumors. Matrix Biol. 2011, 30: 225-233. 10.1016/j.matbio.2011.02.001View ArticlePubMedGoogle Scholar
- Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B: Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012, 9: 676-682. 10.1038/nmeth.2019View ArticlePubMedGoogle Scholar
- Gentleman R, Carey V, Bates D, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004, 5: R80- 10.1186/gb-2004-5-10-r80PubMed CentralView ArticlePubMedGoogle Scholar
- Smyth GK, Speed T: Normalization of cDNA microarray data. Methods. 2003, 31: 265-273. 10.1016/S1046-2023(03)00155-5View ArticlePubMedGoogle Scholar
- Schmittgen TD, Livak KJ: Analyzing real-time PCR data by the comparative CT method. Nat Protoc. 2008, 3: 1101-1108. 10.1038/nprot.2008.73View ArticlePubMedGoogle Scholar
- Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001, 25: 402-408. 10.1006/meth.2001.1262View ArticlePubMedGoogle Scholar
- Aufderheide E, Ekblom P: Tenascin during gut development: appearance in the mesenchyme, shift in molecular forms, and dependence on epithelial-mesenchymal interactions. J Cell Biol. 1988, 107: 2341-2349. 10.1083/jcb.107.6.2341View ArticlePubMedGoogle Scholar
- Li DQ, Meller D, Liu Y, Tseng SCG: Overexpression of MMP-1 and MMP-3 by Cultured Conjunctivochalasis Fibroblasts. Invest Ophthalmol Vis Sci. 2000, 41: 404-410.PubMedGoogle Scholar
- Min BH, Foster DN, Strauch AR: The 5′-flanking region of the mouse vascular smooth muscle alpha-actin gene contains evolutionarily conserved sequence motifs within a functional promoter. J Biol Chem. 1990, 265: 16667-16675.PubMedGoogle Scholar
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