Clinicopathological and prognostic significance of mitogen-activated protein kinases (MAPK) in breast cancers

Ahmad, Dena; Negm, Ola H.; Alabdullah, Muslim; Mirza, Sameer; Hamed, Mohamed R.; Band, Vimla; Green, Andrew; Ellis, Ian O.; Rakha, Emad A.

doi:10.1007/s10549-016-3967-9

Cited by 27 publications

(24 citation statements)

References 53 publications

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“…This study showed that nuclear MAPK1/3 phosphorylation was associated with better outcome, especially in tamoxifen-treated cases. All these immunohistochemical studies in large cohorts of (luminal) breast cancer specimens confirm in part our in silico findings in relation to PIK3CA mutation [18] and our TMA findings that nuclear MAPK1/3 phosphorylation correlates with favorable outcome [16] , [17] . Future prospective studies are needed to verify above retrospective findings and to establish MAPK1/3 phosphorylation as biomarker.…”

Section: Discussionsupporting

confidence: 86%

“…The other study demonstrated a trend between tamoxifen response and MAPK1/3 phosphorylation [15] . Additionally, nuclear and cytoplasmic MAPK1/3 phosphorylation were also studied in large well-characterized breast cancer series to investigate its biological and clinical significance [16] , [17] . This study showed that nuclear MAPK1/3 phosphorylation was associated with better outcome, especially in tamoxifen-treated cases.…”

Section: Discussionmentioning

confidence: 99%

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Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis

Ramirez-Ardila

Timmermans

Helmijr

et al. 2017

Translational Oncology

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INTRODUCTION: While mutations in PIK3CA are most frequently (45%) detected in luminal breast cancer, downstream PI3K/AKT/mTOR pathway activation is predominantly observed in the basal subtype. The aim was to identify proteins activated in PIK3CA mutated luminal breast cancer and the clinical relevance of such a protein in breast cancer patients. MATERIALS AND METHODS: Expression levels of 171 signaling pathway (phospho-)proteins established by The Cancer Genome Atlas (TCGA) using reverse phase protein arrays (RPPA) were in silico examined in 361 breast cancers for their relation with PIK3CA status. MAPK1/3 phosphorylation was evaluated with immunohistochemistry on tissue microarrays (TMA) containing 721 primary breast cancer core biopsies to explore the relationship with metastasis-free survival. RESULTS: In silico analyses revealed increased phosphorylation of MAPK1/3, p38 and YAP, and decreased expression of p70S6K and 4E–BP1 in PIK3CA mutated compared to wild-type luminal breast cancer. Augmented MAPK1/3 phosphorylation was most significant, i.e. in luminal A for both PIK3CA exon 9 and 20 mutations and in luminal B for exon 9 mutations. In 290 adjuvant systemic therapy naïve lymph node negative (LNN) breast cancer patients with luminal cancer, high MAPK phosphorylation in nuclei (HR = 0.49; 95% CI, 0.25–0.95; P = .036) and in tumor cells (HR = 0.37; 95% CI, 0.18–0.79; P = .010) was related with favorable metastasis-free survival in multivariate analyses including traditional prognostic factors. CONCLUSION: Enhanced MAPK1/3 phosphorylation in luminal breast cancer is related to PIK3CA exon-specific mutations and correlated with favorable prognosis especially when located in the nuclei of tumor cells.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis

Ramirez-Ardila

Timmermans

Helmijr

et al. 2017

Translational Oncology

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“…Generally, MAPKs are associated with good prognosis across most classifications of breast cancer, notably in those with positive ER. 154 …”

Section: Mitogen-activated Protein Kinasementioning

confidence: 99%

“…Furthermore, the function of MAPKs is affected by their cross talk and interaction with other pathways, which can influence their behavior. 154 …”

Section: Mitogen-activated Protein Kinasementioning

confidence: 99%

The crossroads of breast cancer progression: insights into the modulation of major signaling pathways

Velloso¹,

Bianco²,

Farias³

et al. 2017

OTT

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Cancer is the disease with highest public health impact in developed countries. Particularly, breast cancer has the highest incidence in women worldwide and the fifth highest mortality in the globe, imposing a significant social and economic burden to society. The disease has a complex heterogeneous etiology, being associated with several risk factors that range from lifestyle to age and family history. Breast cancer is usually classified according to the site of tumor occurrence and gene expression profiling. Although mutations in a few key genes, such as BRCA1 and BRCA2, are associated with high breast cancer risk, the large majority of breast cancer cases are related to mutated genes of low penetrance, which are frequently altered in the whole population. Therefore, understanding the molecular basis of breast cancer, including the several deregulated genes and related pathways linked to this pathology, is essential to ensure advances in early tumor detection and prevention. In this review, we outline key cellular pathways whose deregulation has been associated with breast cancer, leading to alterations in cell proliferation, apoptosis, and the delicate hormonal balance of breast tissue cells. Therefore, here we describe some potential breast cancer-related nodes and signaling concepts linked to the disease, which can be positively translated into novel therapeutic approaches and predictive biomarkers.

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“…Using MOSTWAS and iCOGs summary-level GWAS statistics for breast cancer-specific survival [36], we identified 11 survival-associated loci that are enriched for p53 binding and oxidoreductase activity pathways [66,67]. These loci include two genes (MAP3K6 and MAP4K5 ) encoding mitogen-activated protein kinases, which are signaling transduction molecules involved in the progression of aggressive breast cancer hormone subtypes [68]. TWAS using MOSTWAS models was able to recapitulate 5 out of 14 known…”

Section: Discussionmentioning

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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Clinicopathological and prognostic significance of mitogen-activated protein kinases (MAPK) in breast cancers

Cited by 27 publications

References 53 publications

Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis

Increased MAPK1/3 Phosphorylation in Luminal Breast Cancer Related with PIK3CA Hotspot Mutations and Prognosis

The crossroads of breast cancer progression: insights into the modulation of major signaling pathways

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

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