Megakaryoblastic leukemia protein-1 (MKL1): Increasing evidence for an involvement in cancer progression and metastasis

Scharenberg, Matthias A.; Chiquet‐Ehrismann, Ruth; Asparuhova, Maria B.

doi:10.1016/j.biocel.2010.08.014

Cited by 54 publications

(44 citation statements)

References 29 publications

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“…Among our top hits for both statistics are multiple SNPs that fall in the gene MKL1 (megakaryoblastic leukemia 1), which is a myocardin-related transcription factor that is involved in smooth muscle cell differentiation, mammary gland function, and cytoskeletal signaling (Parmacek 2007;Maglott et al 2011) and has been associated with various disease phenotypes (Ma et al 2001;Hinohara et al 2009;Scharenberg et al 2010).…”

Section: Robust Candidates In the Hgdp Datamentioning

confidence: 99%

Robust Identification of Local Adaptation from Allele Frequencies

2013

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Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to F ST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population poolsa cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.T HE phenotypes of individuals within a species often vary clinally along environmental gradients (Huxley 1939). Such phenotypic clines have long been central to adaptive arguments in evolutionary biology (Mayr 1942), with diverse examples including latitudinal clines in skin pigmentation in humans (Jablonski 2004), body size and temperature tolerance in Drosophila (Hoffmann and Weeks 2007), and flowering time in plants ( Stinchcombe et al. 2004). Unsurprisingly, comparisons of allele frequencies between populations that differ in environment were among the earliest population genetic tests for selection (Cavalli-Sforza 1966;Lewontin and Krakauer 1973;Endler 1986) and have continued to be central to population genetics to this day (e.g., Coop et al. 2009;Akey et al. 2010).The falling cost of sequencing and genotyping means that such comparisons can now be made on a genome-wide scale, allowing us to start to understand the genetic basis of local adaptation across a broad range of organisms. However, such studies need to acknowledge the sampling issues inherent in population genetic studies of natural populations. In assessing correlations between allele frequencies and environmental vari...

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Section: Robust Candidates In the Hgdp Datamentioning

confidence: 99%

Robust Identification of Local Adaptation from Allele Frequencies

2013

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“…These activities cause a depletion of G-actin, thereby allowing MRTF to activate SRF-dependent transcription. The deregulation of MRTF activity has been implicated in various diseases (48). For instance, it was proposed previously that aberrantly increased MRTF/SRF activity enhances the migration potential of breast cancer (BC) cells (5,27).…”

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confidence: 99%

LMO7 Mediates Cell-Specific Activation of the Rho-Myocardin-Related Transcription Factor-Serum Response Factor Pathway and Plays an Important Role in Breast Cancer Cell Migration

Guo

et al. 2011

Molecular and Cellular Biology

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Serum response factor (SRF) is a ubiquitously expressed transcription factor that regulates cell-specific functions such as muscle development and breast cancer metastasis. The myocardin-related transcription factors (MRTFs), which are transcriptional coactivators mediating cell-specific functions of SRF, are also ubiquitously expressed. How MRTFs and SRF drive cell-specific transcription is still not fully understood. Here we show that LIM domain only 7 (LMO7) is a cell-specific regulator of MRTFs and plays an important role in breast cancer cell migration. LMO7 activates MRTFs by relieving actin-mediated inhibition in a manner that requires, and is synergistic with, Rho GTPase. Whereas Rho is required for LMO7 to activate full-length MRTFs that have three RPEL actin-binding motifs, the disruption of individual actin-RPEL interactions is sufficient to eliminate the Rho dependency and to allow the strong Rho-independent function of LMO7. Mechanistically, we show that LMO7 colocalizes with F-actin and reduces the G-actin/F-actin ratio via a Rho-independent mechanism. The knockdown of LMO7 in HeLa and MDA-MB-231 cells compromises both basal and Rho-stimulated MRTF activities and impairs the migration of MDA-MB-231 breast cancer cells. We also show that LMO7 is upregulated in the stroma of invasive breast carcinoma in a manner that correlates with the increased expression of SRF target genes that regulate muscle and actin cytoskeleton functions. Together, this study reveals a novel cell-specific mechanism regulating Rho-MRTF-SRF signaling and breast cancer cell migration and identifies a role for actin-RPEL interactions in integrating Rho and cell-specific signals to achieve both the synergistic and Rho-dependent activation of MRTFs.

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“…This notion is supported by recent evidence, showing that ablation of ATE1 expression in platelets in vivo did not lead to an impairment in actin polymerization but rather induced the contractile capacity of these cells during clot retraction (22). Also, MRTF-A activity has been shown to play different roles depending on the cell type, the tissue environment, and the signaling pathways in which it is involved (6). For example, a role for MRTF-A has emerged in tumorigenesis, i.e.…”

Section: Discussionmentioning

confidence: 55%

“…Although few publications acknowledged a link between deregulated MRTF-A activity and carcinogenesis (6), its molecular role and mode of action in regulating cellular motility appear to depend on the cell type. Whereas silencing of MRTF-A expression in breast cancer cells reduced cellular motility in vitro as well as inhibited experimental metastasis in vivo (7,8), partial reduction of MRTF-A in murine fibroblastic or epithelial cells induced cellular motility (8).…”

mentioning

confidence: 99%

Inhibition of Arginyltransferase 1 Induces Transcriptional Activity of Myocardin-related Transcription Factor A (MRTF-A) and Promotes Directional Migration

Eisenach

Schikora

Posern

2014

Journal of Biological Chemistry

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Background:The transcriptional co-activator MRTF-A is regulated by changes in actin dynamics. Results: Inhibition of ATE1 activates MRTF-A and modulates directed migration of breast cancer cells. Conclusion: ATE1 function controls MRTF-A activity as well as actin organization and cell-cell adhesion. Significance: Protein arginylation is coordinately affecting MRTF-A-mediated transcription and the motile behavior of carcinoma cells.

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Megakaryoblastic leukemia protein-1 (MKL1): Increasing evidence for an involvement in cancer progression and metastasis

Cited by 54 publications

References 29 publications

Robust Identification of Local Adaptation from Allele Frequencies

Robust Identification of Local Adaptation from Allele Frequencies

LMO7 Mediates Cell-Specific Activation of the Rho-Myocardin-Related Transcription Factor-Serum Response Factor Pathway and Plays an Important Role in Breast Cancer Cell Migration

Inhibition of Arginyltransferase 1 Induces Transcriptional Activity of Myocardin-related Transcription Factor A (MRTF-A) and Promotes Directional Migration

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