Computational identification of mutually exclusive transcriptional drivers dysregulating metastatic microRNAs in prostate cancer

HOXC6 drives a therapeutically targetable pancreatic cancer growth and metastasis pathway by regulating MSK1 and PPP2R2B

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, which lacks effective therapies. Here, we demonstrate that the transcription factor, homeobox C6 (HOXC6), is overexpressed in most PDACs, and its inhibition blocks PDAC tumor growth and metastasis. HOXC6 transcriptionally activates tumor-promoting kinase MSK1 and suppresses tumor-inhibitory protein PPP2R2B in PDAC. HOXC6-induced PPP2R2B suppression causes mammalian target of rapamycin (mTOR) pathway activation, which facilitates PDAC growth. Also, MSK1 upregulation by HOXC6 is necessary for PDAC growth because of its ability to suppress apoptosis via its substrate DDX17. Combinatorial pharmacological inhibition of MSK1 and mTOR potently suppressed PDAC tumor growth and metastasis in PDAC mouse models. PDAC cells with acquired resistance to MSK1/mTOR-inhibitors displayed activated insulin-like growth factor 1 receptor (IGF1R) signaling and were successfully eradicated by IGF1R inhibitor. Furthermore, MEK inhibitor trametinib enhanced the efficacy of dual MSK1 and mTOR inhibition. Collectively, these results identify therapeutic vulnerabilities of PDAC and an approach to overcome acquired drug resistance to prolong therapeutic benefit.

Loss of MAGEC3 Expression Is Associated with Prognosis in Advanced Ovarian Cancers

Simple Summary

Familial studies connect variants in the X-linked gene MAGEC3 to early-onset ovarian cancers. In this retrospective cohort study, we determined that, unlike other MAGE family members, the MAGEC3 protein is normally expressed in ovarian tissue but is lost in half of the ovarian cancers. Similar to other predisposition genes like BRCA2, survival modeling suggests that expression loss is associated with favorable progression-free survival, and continued expression is associated with response to platinum therapy. Because of the assumed antigenicity of MAGE genes, we tested and observed associations with lymphocyte infiltration, NY-ESO-1 seropositivity, and the co-expression of tumor antigens at Xq28. Using transcriptomic modeling, we predicted that MAGEC3 expression is associated with stress-related cell cycle stalling and DNA repair pathway expression.

Abstract

Rare variants in MAGEC3 are associated with BRCA negative, early-onset ovarian cancers. Given this association, we evaluated the impact of MAGEC3 protein expression on prognosis and transcription. We quantified normal and tumor protein expression of MAGEC3 via immunohistochemistry in n = 394 advanced ovarian cancers, assessed the correlation of these values with clinicopathologic and immunological features and modeled survival using univariate and multivariate models. To extend these results, we quantified MAGEC3 protein expression in n = 180 cancers and used matching RNA sequencing data to determine MAGEC3-associated differentially expressed genes and to build an RNA-based model of MAGEC3 protein levels. This model was tested in a third independent cohort of patients from TCGA’s OV dataset (n = 282). MAGEC3 protein was sporadically lost in ovarian cancers, with half of the cases falling below the 9.5th percentile of normal tissue expression. Cases with MAGEC3 loss demonstrated better progression-free survival [HR = 0.71, p = 0.004], and analyses performed on predicted protein scores were consistent [HR = 0.57 p = 0.002]. MAGEC3 protein was correlated with CD8 protein expression [Pearson’s r = 0.176, p = 0.011], NY-ESO-1 seropositivity, and mRNA expression of tumor antigens at Xq28. Results of gene set enrichment analysis showed that genes associated with MAGEC3 protein expression cluster around G2/M checkpoint (NES = 3.20, FDR < 0.001) and DNA repair (NES = 2.28, FDR < 0.001) hallmark pathways. These results show that MAGEC3 is a prognostic biomarker in ovarian cancer.

Interaction between Non-Coding RNAs and Androgen Receptor with an Especial Focus on Prostate Cancer

The androgen receptor (AR) is a member of the nuclear receptor superfamily and has three functional domains, namely the N-terminal, DNA binding, and C-terminal domain. The N-terminal domain harbors potent transactivation functions, whereas the C-terminal domain binds to androgens and antiandrogens used to treat prostate cancer. AR has genomic activity being DNA binding-dependent or through interaction with other DNA-bound transcription factors, as well as a number of non-genomic, non-canonical functions, such as the activation of the ERK, AKT, and MAPK pathways. A bulk of evidence indicates that non-coding RNAs have functional interactions with AR. This type of interaction is implicated in the pathogenesis of human malignancies, particularly prostate cancer. In the current review, we summarize the available data on the role of microRNAs, long non-coding RNAs, and circular RNAs on the expression of AR and modulation of AR signaling, as well as the effects of AR on their expression. Recognition of the complicated interaction between non-coding RNAs and AR has practical importance in the design of novel treatment options, as well as modulation of response to conventional therapeutics.

Abnormal expression of homeobox c6 in the atherosclerotic aorta and its effect on proliferation and migration of rat vascular smooth muscle cells

Homeobox c6 (Hoxc6) affects the proliferation, migration, and infiltration of malignant tumor cells; however, the effect of Hoxc6 on atherosclerosis (AS) as well as the proliferation and migration of vascular smooth muscle cells (VSMCs), which play a role in promoting AS, has not yet been well clarified. In the present study, we tested the hypothesis that Hoxc6 affects the proliferation and migration of rat VSMCs, and hence is involved in AS. The results showed that the expression of Hoxc6 mRNA and protein was higher in normal rat aortic wall than in the myocardium. Subsequently, a rat model of AS was established by high-fat feeding for 2 months. The expression of Hoxc6 mRNA and protein was increased significantly in AS lesions, while the expression of p53 protein was decreased and that of proliferating cell nuclear antigen (PCNA) was increased. Moreover, not only the proliferation and mobility of cells in normal culture were decreased, but also the proliferation was stimulated by oxidized low-density lipoprotein, which was decreased after downregulation of Hoxc6 expression in VSMCs in rat. Consecutively, the expression of PCNA protein was decreased, while that of p53 was increased. These results indicated that Hoxc6 is probably involved in AS via p53 and PCNA by affecting the proliferation and migration of VSMCs.

DECO: decompose heterogeneous population cohorts for patient stratification and discovery of sample biomarkers using omic data profiling

Motivation

Patient and sample diversity is one of the main challenges when dealing with clinical cohorts in biomedical genomics studies. During last decade, several methods have been developed to identify biomarkers assigned to specific individuals or subtypes of samples. However, current methods still fail to discover markers in complex scenarios where heterogeneity or hidden phenotypical factors are present. Here, we propose a method to analyze and understand heterogeneous data avoiding classical normalization approaches of reducing or removing variation.

Results

DEcomposing heterogeneous Cohorts using Omic data profiling (DECO) is a method to find significant association among biological features (biomarkers) and samples (individuals) analyzing large-scale omic data. The method identifies and categorizes biomarkers of specific phenotypic conditions based on a recurrent differential analysis integrated with a non-symmetrical correspondence analysis. DECO integrates both omic data dispersion and predictor–response relationship from non-symmetrical correspondence analysis in a unique statistic (called h-statistic), allowing the identification of closely related sample categories within complex cohorts. The performance is demonstrated using simulated data and five experimental transcriptomic datasets, and comparing to seven other methods. We show DECO greatly enhances the discovery and subtle identification of biomarkers, making it especially suited for deep and accurate patient stratification.

Availability and implementation

DECO is freely available as an R package (including a practical vignette) at Bioconductor repository (http://bioconductor.org/packages/deco/).

Supplementary information

Supplementary data are available at Bioinformatics online.

SMAD7 and SERPINE1 as novel dynamic network biomarkers detect and regulate the tipping point of TGF-beta induced EMT

Epithelial-mesenchymal transition (EMT) is a complex nonlinear biological process that plays essential roles in fundamental biological processes such as embryogenesis, wounding healing, tissue regeneration, and cancer metastasis. A hallmark of EMT is the switch-like behavior during state transition, which is characteristic of phase transitions. Hence, detecting the tipping point just before mesenchymal state transition is critical for understanding molecular mechanism of EMT. Through dynamic network biomarkers (DNB) model, a DNB group with 37 genes was identified which can provide the early-warning signals of EMT. Particularly, we found that two DNB genes, i.e., SMAD7 and SERPINE1 promoted EMT by switching their regulatory network which was further validated by biological experiments. Survival analyses revealed that SMAD7 and SERPINE1 as DNB genes further acted as prognostic biomarkers for lung adenocarcinoma.

miR-6086 inhibits ovarian cancer angiogenesis by downregulating the OC2/VEGFA/EGFL6 axis

miRNAs have emerged as a pivotal component of gene regulatory networks, mediating cytokines secretion, cell cycle, and differentiation regulation. However, how miRNAs collaborate with transcription factors and downstream effector proteins that determine the fate of ovarian cancer cells remains to be understood, especially regarding to mechanism of tumor angiogenesis regulation. Based on the qRT-PCR and IHC analysis, we found that miR-6086 was maintained a very low level both in ovarian cancer cell lines and tissues. Further, we identified OC2 and EGFL6 as the direct targets of miR-6086 by luciferase assay and we observed an inverse relationship between the expression of miR-6086 and the OC2/VEGFA/EGFL6 axis. The Western blotting analysis suggested that OC2 could directly upregulate VEGFA and indirectly up-regulate EGFL6 through VEGFA. Moreover, miR-6086 could indirectly downregulate VEGFA through OC2. In addition, miR-6086, siOC2 and siEGFL6 could negatively regulate the tumor growth and angiogenesis of ovarian cancer (Skov3) in the animal studies, with the inhibition rates of 77.07%, 69.89%, and 73.62%, respectively (**p < 0.01). Moreover, the tumor cell proliferation, migration, and invasion of ovarian cancer cell lines (Caov3 and Skov3) and vascular formation (HUVECs) were significantly suppressed in vitro, by decreasing the AKT/MAPK pathways (*p < 0.05). Taken together, our results reveal that miR-6086 can suppress the angiogenesis networks in ovarian cancer by down-regulating the OC2/VEGFA/EGFL6 axis, directly or indirectly, which may provide potential targets for tumor therapeutics.

AAV-Anti-miR-214 Prevents Collapse of the Femoral Head in Osteonecrosis by Regulating Osteoblast and Osteoclast Activities

Osteonecrosis of the femoral head, an intractable but common disease that eventually triggers collapse of the femoral head, is characterized by increased osteoclast activity and markedly decreased osteoblast activity in the necrotic region of the femoral head. MicroRNA (miRNA)-214 (miR-214) may play important roles in vertebrate skeletal development by inhibiting osteoblast function by targeting activating transcription factor 4 (ATF4) and promoting osteoclast function via phosphatase and tensin homolog (PTEN). This study revealed significantly increased levels of miR-214 in necrotic regions, with commensurate changes in the numbers of its target cells (both osteoblasts and osteoclasts). To investigate whether targeting miR-214 could prevent femoral head collapse, we constructed an adeno-associated virus (AAV)-associated anti-miR-214 (AAV-anti-miR-214) and evaluated its function in vivo. AAV-anti-miR-214 promoted osteoblast activity and diminished osteoclast activity, effectively preventing collapse of the femoral head in a rat model of osteonecrosis.

A Multidimensional Characterization of E3 Ubiquitin Ligase and Substrate Interaction Network

E3 ubiquitin ligases (E3s) play a critical role in molecular and cellular mechanisms. However, a large number of E3-substrate interactions (ESIs) remain unrevealed. Here, we integrated the increasing omics data with biological knowledge to characterize and identify ESIs. Multidimensional features were computed to obtain the association patterns of ESIs, and an ensemble prediction model was constructed to identify ESIs. Comparison with non-ESI cases revealed the specific association patterns of ESIs, which provided meaningful insights into ESI interpretation. Reliability of the prediction model was confirmed from various perspectives. Notably, our evaluations on leucine-rich repeat family of F box (FBXL) family were consistent with a proteomic study, and several substrates for SKP2 and an orphan E3 FBXL6 were experimentally verified. Moreover, a cancer hallmark ESI landscape was studied. Taken together, our study catches a glimpse at the omics-driven ESI association patterns and provides a valuable resource (http://www.esinet.dicp.ac.cn/home.php) to assist ubiquitination research.

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Systematically describe E3 ligase and substrate association patterns

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Build a computational model for predicting E3 ligase and substrate interactions

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Predict and validate promising substrates for F box family E3 ligases

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Construct a valuable data resource on potential E3-substrate interactions

CAMIRADA: Cancer microRNA association discovery algorithm, a case study on breast cancer

In recent studies, non-coding protein RNAs have been identified as microRNA that can be used as biomarkers for early diagnosis and treatment of cancer, that decrease mortality in cancer. A microRNA may target hundreds or thousands of genes and a gene may regulate several microRNAs, so determining which microRNA is associated with which cancer is a big challenge. Many computational methods have been performed to detect micoRNAs association with cancer, but more effort is needed with higher accuracy. Increasing research has shown that relationship between microRNAs and TFs play a significant role in the diagnosis of cancer. Therefore, we developed a new computational framework (CAMIRADA) to identify cancer-related microRNAs based on the relationship between microRNAs and disease genes (DG) in the protein network, the functional relationships between microRNAs and Transcription Factors (TF) on the co-expression network, and the relationship between microRNAs and the Differential Expression Gene (DEG) on co-expression network. The CAMIRADA was applied to assess breast cancer data from two HMDD and miR2Disease databases. In this study, the AUC for the 65 microRNAs of the top of the list was 0.95, which was more accurate than the similar methods used to detect microRNAs associated with the cancer artery.

Genome-wide miRNA methylome analysis in oral cancer: possible biomarkers associated with patient survival

AIM

The methylome associated with miRNA loci was investigated in oral cancer to explore tobacco specific methylation and potential biomarkers for patient survival.

METHODS

Methylome data was generated from 16 pairs of cancer-normal tissues by reduced representation bisulfite sequencing method. Differentially methylated regions were identified using the DMAP pipeline. In silico validation and Kaplan-Meier survival analyses were performed on The Cancer Genome Atlas data based on our miRNA methylome data.

RESULTS

A total of 4310 unique differentially methylated regions, mapping to 144 miRNA loci, were identified. Three distinct groups of miRNAs were differentially methylated in cancer tissues from smokers, chewers and mixed habitués. Hypermethylation of miR-503, miR-200a/b, miR-320b and miR-489 was associated with worse 5-year survival.

CONCLUSION

Differential methylation patterns in miRNA loci are associated with poor survival underscoring their potential as predictive and prognostic biomarkers in oral cancer.

Neural Transcription Factors in Disease Progression

Progression to the malignant state is fundamentally dependent on transcriptional regulation in cancer cells. Optimum abundance of cell cycle proteins, angiogenesis factors, immune evasion markers, etc. is needed for proliferation, metastasis or resistance to treatment. Therefore, dysregulation of transcription factors can compromise the normal prostate transcriptional network and contribute to malignant disease progression.The androgen receptor (AR) is considered to be a key transcription factor in prostate cancer (PCa) development and progression. Consequently, androgen pathway inhibitors (APIs) are currently the mainstay in PCa treatment, especially in castration-resistant prostate cancer (CRPC). However, emerging evidence suggests that with increased administration of potent APIs, prostate cancer can progress to a highly aggressive disease that morphologically resembles small cell carcinoma, which is referred to as neuroendocrine prostate cancer (NEPC), treatment-induced or treatment-emergent small cell prostate cancer. This chapter will review how neuronal transcription factors play a part in inducing a plastic stage in prostate cancer cells that eventually progresses to a more aggressive state such as NEPC.

MicroRNAs as Regulators of Prostate Cancer Metastasis

Prostate cancer causes significant morbidity in men and metastatic disease is a major cause of cancer related deaths. Prostate metastasis is controlled by various cellular intrinsic and extrinsic factors, which are often under the regulatory control of various metastasis-associated genes. Given the dynamic nature of metastatic cancer cells, the various factors controlling this process are themselves regulated by microRNAs which are small non-coding RNAs. Significant research work has shown differential microRNA expression in primary and metastatic prostate cancer suggesting their importance in prostate pathogenesis. We will review the roles of different microRNAs in controlling the various steps in prostate metastasis.

Multi-omics Approach Reveals Distinct Differences in Left- and Right-Sided Colon Cancer

Increasing evidence suggests that left-sided colon cancer (LCC) and right-sided colon cancer (RCC) are emerging as two different colorectal cancer types with distinct clinical characteristics. However, the discrepancy in the underlying molecular event between these types of cancer has not been thoroughly elucidated to date and warrants comprehensive investigation. To this end, an integrated dataset from The Cancer Genome Atlas was used to compare and contrast LCC and RCC, covering mutation, DNA methylation, gene expression, and miRNA. Briefly, the signaling pathway cross-talk is more prevalent in RCC than LCC, such as RCC-specific PI3K pathway, which often exhibits cross-talk with the RAS and P53 pathways. Meanwhile, methylation signatures revealed that RCC was hypermethylated relative to LCC. In addition, differentially expressed genes (n = 253) and differentially expressed miRNAs (n = 16) were determined between LCC and RCC. Especially for Prostate Cancer Susceptibility Candidate 1 (PRAC1), a gene that was closely associated with hypermethylation, was the top significantly downregulated gene in RCC. Multi-omics comparison of LCC and RCC suggests that there are more aggressive markers in RCC and that tumor heterogeneity occurs within the location-based subtypes of colon cancer. These results clarify the debate regarding the conflicting prognosis between LCC and RCC, as proposed by different studies.Implications: The underlying molecular features present in LCC and RCC identified in this study are beneficial for adopting reasonable therapeutic approaches to prolong overall survival and progression-free survival in colorectal cancer patients. Mol Cancer Res; 16(3); 476-85. ©2017 AACR.