ROCK inhibitor enhances the growth and migration of BRAF‐mutant skin melanoma cells

Fei, Chang; Zhang, Yunpeng; Mi, Jun; Zhou, Qian; Bai, Fuxiang; Xu, Xin; Fisher, David E.; Qi-zhong, Sun; Wu, Xunwei

doi:10.1111/cas.13786

Cited by 37 publications

(39 citation statements)

References 32 publications

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“…While observations of human A375 cells and several uveal melanoma lines corroborated these results (3,30), ROCK inhibition in HT-144 cells was associated with a proinvasive effect (33). This lability was recently evidenced by Chang et al who compared consequences of ROCK inhibition across several cell lines (22). Treatment with Y27632 reduced proliferation and migration in B16F1 and MeWo cells, but employment of UACC257, UACC62 and M14 lines yielded contrary results, which our findings are consistent with (22).…”

Section: Discussionsupporting

confidence: 86%

“…This lability was recently evidenced by Chang et al who compared consequences of ROCK inhibition across several cell lines (22). Treatment with Y27632 reduced proliferation and migration in B16F1 and MeWo cells, but employment of UACC257, UACC62 and M14 lines yielded contrary results, which our findings are consistent with (22). This variation was attributed to B-Raf proto-oncogene, serine/threonine kinase (BRAF) status as only BRAF-mutant cells displayed enhanced growth and motility following ROCK inhibition (22).…”

Section: Discussionmentioning

confidence: 82%

“…These seemingly contradictory findings may be at least partly attributed to the choice of different cell lines in various studies. In melanoma, substitution of B16F1 culture with UACC257 or UACC62 cells resulted in opposite observations in proliferation and migration assays -ROCK inhibition impaired melanoma cell growth and motility in the first cell line and promoted these functions in the latter two (11,21,22). This illustrates an important caveat to past functional studies -they do not account for the considerable molecular heterogeneity of naturally occurring melanomas.…”

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confidence: 93%

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ROCK1 and ROCK2 Are Down-regulated in Aggressive and Advanced Skin Melanomas – A Clinicopathological Perspective

et al. 2020

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Background: RhoA and its downstream effectors Rho-associated coiled-coil kinases (ROCK) 1 and 2 are central controllers of cytoskeleton dynamics, and therefore influence cell shape, adhesion and migration. Since modulation of these processes holds promise for an effective anticancer strategy, effects of ROCK inhibition have been evaluated in a number of malignancies. Materials and Methods: Using immunohistochemistry, ROCK1 and ROCK2 expression was semi-quantitatively assessed in 129 patientderived primary melanomas. Results: There was a striking predilection for low melanocytic expression of both kinases in thick, ulcerated and mitogenic tumors, as well as in nodular histological type. ROCK1 and-2 expression in tumor-infiltrating lymphocytes (TILs) was preferentially down-regulated in advanced and aggressive tumors. Moreover, diminished ROCK2 reactivity in melanoma cells and TILs was associated with shorter melanoma-specific and recurrence-free survival. Conclusion: This is the first analysis of ROCK1 and-2 protein expression in clinical melanoma samples and the results indicated the suppression of ROCK signaling in melanocytes of aggressive and late-stage tumors. Functional models that more accurately represent the clinical setting are necessary to dissect the role of ROCK1 and-2 in melanoma. Additionally, our study indicates that ROCK activity in TILs may be involved in the pathogenesis of cancer, and thus merits further investigations.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 82%

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confidence: 93%

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ROCK1 and ROCK2 Are Down-regulated in Aggressive and Advanced Skin Melanomas – A Clinicopathological Perspective

et al. 2020

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“…It is important to note that pan-ROCK inhibition using Y-27632 has been shown to increase the proliferation and migration of a number of in vitro and in vivo cancer models (Adachi et al, 2011;Vishnubhotla et al, 2012;Yang and Kim, 2014;Chang et al, 2018). These effects may be explained by the observation that ROCK activation can contribute to negative feedback mechanisms that regulate pro-proliferative pathways.…”

Section: Rho-associated Protein Kinases (Rocks)mentioning

confidence: 99%

Targeting Rho GTPase Signaling Networks in Cancer

Clayton

Ridley

2020

Front. Cell Dev. Biol.

135

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As key regulators of cytoskeletal dynamics, Rho GTPases coordinate a wide range of cellular processes, including cell polarity, cell migration, and cell cycle progression. The adoption of a pro-migratory phenotype enables cancer cells to invade the stroma surrounding the primary tumor and move toward and enter blood or lymphatic vessels. Targeting these early events could reduce the progression to metastatic disease, the leading cause of cancer-related deaths. Rho GTPases play a key role in the formation of dynamic actin-rich membrane protrusions and the turnover of cell-cell and cellextracellular matrix adhesions required for efficient cancer cell invasion. Here, we discuss the roles of Rho GTPases in cancer, their validation as therapeutic targets and the challenges of developing clinically viable Rho GTPase inhibitors. We review other therapeutic targets in the wider Rho GTPase signaling network and focus on the four best characterized effector families: p21-activated kinases (PAKs), Rho-associated protein kinases (ROCKs), atypical protein kinase Cs (aPKCs), and myotonic dystrophy kinase-related Cdc42-binding kinases (MRCKs).

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“…For 8 of the TWAS-associated 11 loci, at FDR-adjusted P < 0.05, we found significant distal variation added-last associations (see Supplemental Methods and Supplemental Table S2), suggesting that distal variation may contribute to the gene-trait association. All 8 of these loci showed distal association with the gene of interest mediated through a set of four transcription factors (NAA50, ATP6V1A, ROCK2, USF3 ), all highly interconnected with the critical MAPK pathway [52][53][54][55][56][57]. These regulatory sites serve as an example of how distal genomic regions can be prioritized for functional follow-up studies to elucidate the mechanisms underlying the SNP-gene-trait associations.…”

Section: Functional Hypothesis Generation With Mostwasmentioning

confidence: 99%

MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies

Bhattacharya

Love

2020

Preprint

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Traditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process. These approaches ignore the effect of distal-SNPs or possible effects underlying the SNP-gene association. Here, we outline multi-omic strategies for transcriptome imputation from germline genetics for testing gene-trait associations by prioritizing distal-SNPs to the gene of interest. In one extension, we identify mediating biomarkers (CpG sites, microRNAs, and transcription factors) highly associated with gene expression and train predictive models for these mediators using their local SNPs. Imputed values for mediators are then incorporated into the final model as fixed effects with local SNPs to the gene included as regularized effects. In the second extension, we assess distal-eSNPs (SNPs in eQTLs) for their mediation effect through mediators local to these distal-eSNPs. Highly mediated distal-eSNPs are then included in the eventual transcriptomic prediction model. We show considerable gains in percent variance explained of gene expression and TWAS power to detect gene-trait associations using simulation analysis and real data applications with TCGA breast cancer data and in ROS/MAP brain tissue data. This integrative approach to transcriptome-wide imputation and association studies aids in understanding the complex interactions underlying genetic regulation within a tissue and identifying important risk genes for various traits and disorders.the matrix X Mj be the local-genotype dosages in a 500 kilobase window around mediator j, 1 ≤ j ≤ m G . Furthermore, let M j be the intensity of mediator j (methylation M -value if j is a CpG site, expression if j is a miRNA or a gene, etc). Prior to any modeling, we scale Y G and all M j , 1 ≤ j ≤ m G to zero mean and unit variance. We also residualize M j , 1 ≤ j ≤ m G and Y G with the covariate matrix X C to account for population stratification using principal components of the global genotype matrix and relevant clinical covariates to obtainM j , 1 ≤ j ≤ m G andỸ G .Transcriptome prediction in MeTWAS draws from two-step regression, as summarized in Figure 1.First, in the training set for a given training-test split, for 1 ≤ j ≤ m G , we model the residualized intensitỹ M j of training-set specific mediator j with the following additive model:where w j is the effect-sizes of the SNPs in X † Mj onM j in the training set. As in traditional transcriptomic imputation models [3,4], we findŵ j using one of the two following methods with the largest predicted adjusted R 2 : (1) elastic net regression with mixing parameter α = 0.5 and λ tuned over 5-fold cross validation using glmnet [19], or (2) linear mixed modeling assuming random effects for X Mj using rrBLUP [20]. Only significantly heritable (default P < 0.05 for the likelihood ratio test) [21] and well-cross validated (default R 2 ≥ 0.01) expression models are considered.For all j, using these opti...

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ROCK inhibitor enhances the growth and migration of BRAF‐mutant skin melanoma cells

Cited by 37 publications

References 32 publications

ROCK1 and ROCK2 Are Down-regulated in Aggressive and Advanced Skin Melanomas – A Clinicopathological Perspective

ROCK1 and ROCK2 Are Down-regulated in Aggressive and Advanced Skin Melanomas – A Clinicopathological Perspective

Targeting Rho GTPase Signaling Networks in Cancer

MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies

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