Sonic hedgehog medulloblastoma cancer stem cells mirnome and transcriptome highlight novel functional networks

Molecular classification has improved the knowledge of medulloblastoma (MB), the most common malignant brain tumour in children, however current treatments cause severe side effects in patients. Cancer stem cells (CSCs) have been described in MB and represent a sub population characterised by self-renewal and the ability to generate tumour cells, thus representing the reservoir of the tumour. To investigate molecular pathways that characterise this sub population, we isolated CSCs from Sonic Hedgehog Medulloblastoma (SHH MB) arisen in Patched 1 (Ptch1) heterozygous mice, and performed miRNA-and mRNA-sequencing. Comparison of the miRNA-sequencing of SHH MB CSCs with that obtained from cerebellar Neural Stem Cells (NSCs), allowed us to obtain a SHH MB CSC miRNA differential signature. Pathway enrichment analysis in SHH MB CSCs mirnome and transcriptome was performed and revealed a series of enriched pathways. We focused on the putative targets of the SHH MB CSC miRNAs that were involved in the enriched pathways of interest, namely pathways in cancer, PI3k-Akt pathway and protein processing in endoplasmic reticulum pathway. In silico analysis was performed in SHH MB patients and identified several genes, whose expression was associated with worse overall survival of SHH MB patients. This study provides novel candidates whose functional role should be further investigated in SHH MB

MicroRNA profiling associated with non-small cell lung cancer: next generation sequencing detection, experimental validation, and prognostic value

[EN] Background: The average five-year survival for non-small cell lung cancer (NSCLC) patients is approximately 15%. Emerging evidence indicates that microRNAs (miRNAs) constitute a new class of gene regulators in humans that may play an important role in tumorigenesis. Hence, there is growing interest in studying their role as possible new biomarkers whose expression is aberrant in cancer. Therefore, in this study we identified dysregulated miRNAs by next generation sequencing (NGS) and analyzed their prognostic value. Methods: Sequencing by oligo ligation detection technology was used to identify dysregulated miRNAs in a training cohort comprising paired tumor/normal tissue samples (N = 32). We validated 22 randomly selected differentially-expressed miRNAs by quantitative real time PCR in tumor and adjacent normal tissue samples (N = 178). Kaplan-Meier survival analysis and Cox regression were used in multivariate analysis to identify independent prognostic biomarkers. Results: NGS analysis revealed that 39 miRNAs were dysregulated in NSCLC: 28 were upregulated and 11 were downregulated. Twenty-two miRNAs were validated in an independent cohort. Interestingly, the group of patients with high expression of both miRNAs (miR-21(high) and miR-188(high)) showed shorter relapse-free survival (RFS) and overall survival (OS) times. Multivariate analysis confirmed that this combined signature is an independent prognostic marker for RFS and OS (p = 0.001 and p < 0.0001, respectively). Conclusions: NGS technology can specifically identify dysregulated miRNA profiles in resectable NSCLC samples. MiR-21 or miR-188 overexpression correlated with a negative prognosis, and their combined signature may represent a new independent prognostic biomarker for RFS and OS.This work was supported by the RD12/0036/0025 and RD06/0020/1024 PI12-02838, ISCIII, grants from the Fondo Europeo de Desarrollo Regional (FEDER), by funds from the Proyecto de Investigacion Fundamental Orientada a la Transmision de Conocimiento a la Empresa (TRACE; TRA09-0132) and Beca Roche Oncohematologia.Gallach-Garcia, S.; Jantus-Lewintre, E.; Calabuig-Fariñas, S.; Montaner, D.; Alonso, S.; Sirera Pérez, R.; Blasco, A.... (2017). MicroRNA profiling associated with non-small cell lung cancer: next generation sequencing detection, experimental validation, and prognostic value. Oncotarget. 8(34):56143-56157. https://doi.org/10.18632/oncotarget.18603S561435615783

Modeling of non-steroidal anti-inflammatory drug effect within signaling pathways and miRNA-regulation pathways

To date, it is widely recognized that Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) can exert considerable anti-tumor effects regarding many types of cancers. The prolonged use of NSAIDs is highly associated with diverse side effects. Therefore, tailoring down the NSAID application onto individual patients has become a necessary and relevant step towards personalized medicine. This study conducts the systemsbiological approach to construct a molecular model (NSAID model) containing a cyclooxygenase (COX)-pathway and its related signaling pathways. Four cancer hallmarks are integrated into the model to reflect different developmental aspects of tumorigenesis. In addition, a Flux-Comparative-Analysis (FCA) based on Petri net is developed to transfer the dynamic properties (including drug responsiveness) of individual cellular system into the model. The gene expression profiles of different tumor-types with available drug-response information are applied to validate the predictive ability of the NSAID model. Moreover, two therapeutic developmental strategies, synthetic lethality and microRNA (miRNA) biomarker discovery, are investigated based on the COX-pathway. In conclusion, the result of this study demonstrates that the NSAID model involving gene expression, gene regulation, signal transduction, protein interaction and other cellular processes, is able to predict the individual cellular responses for different therapeutic interventions (such as NS-398 and COX-2 specific siRNA inhibition). This strongly indicates that this type of model is able to reflect the physiological, developmental and pathological processes of an individual. The approach of miRNA biomarker discovery is demonstrated for identifying miRNAs with oncogenic and tumor suppressive functions for individual cell lines of breast-, colon- and lung-tumor. The achieved results are in line with different independent studies that investigated miRNA biomarker related to diagnostics of cancer treatments, therefore it might shed light on the development of biomarker discovery at individual level. Particular results of this study might contribute to step further towards personalized medicine with the systemsbiological approach

An integrative workflow to study large-scale biochemical networks

I propose an integrative workflow to study large-scale biochemical networks by combining omics data, network structure and dynamical analysis to unravel disease mechanisms. Using the workflow, I identified core regulatory networks from the E2F1 network underlying EMT in bladder and breast cancer and detected disease signatures and drug targets, which were experimentally validated. Further, I developed a hybrid modeling framework that combines ODE- with logical-models to analyze the dynamics of large-scale non-linear systems. This thesis is a contribution to interdisciplinary cancer research

Unraveling a tumor type-specific regulatory core underlying E2F1-mediated epithelial-mesenchymal transition to predict receptor protein signatures

Cancer is a disease of subverted regulatory pathways. In this paper, we reconstruct the regulatory network around E2F, a family of transcription factors whose deregulation has been associated to cancer progression, chemoresistance, invasiveness, and metastasis. We integrate gene expression profiles of cancer cell lines from two E2F1-driven highly aggressive bladder and breast tumors, and use network analysis methods to identify the tumor type-specific core of the network. By combining logic-based network modeling, in vitro experimentation, and gene expression profiles from patient cohorts displaying tumor aggressiveness, we identify and experimentally validate distinctive, tumor type-specific signatures of receptor proteins associated to epithelial-mesenchymal transition in bladder and breast cancer. Our integrative network-based methodology, exemplified in the case of E2F1-induced aggressive tumors, has the potential to support the design of cohort- as well as tumor type-specific treatments and ultimately, to fight metastasis and therapy resistance

MicroRNA Genes and Their Target 3′-Untranslated Regions Are Infrequently Somatically Mutated in Ovarian Cancers

MicroRNAs are key regulators of gene expression and have been shown to have altered expression in a variety of cancer types, including epithelial ovarian cancer. MiRNA function is most often achieved through binding to the 3′-untranslated region of the target protein coding gene. Mutation screening using massively-parallel sequencing of 712 miRNA genes in 86 ovarian cancer cases identified only 5 mutated miRNA genes, each in a different case. One mutation was located in the mature miRNA, and three mutations were predicted to alter the secondary structure of the miRNA transcript. Screening of the 3′-untranslated region of 18 candidate cancer genes identified one mutation in each of AKT2, EGFR, ERRB2 and CTNNB1. The functional effect of these mutations is unclear, as expression data available for AKT2 and EGFR showed no increase in gene transcript. Mutations in miRNA genes and 3′-untranslated regions are thus uncommon in ovarian cancer

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors

MiR-21 Is Induced by Hypoxia and Down-Regulates RHOB in Prostate Cancer

Tumour hypoxia is a well-established contributor to prostate cancer progression and is also known to alter the expression of several microRNAs. The over-expression of microRNA-21 (miR-21) has been consistently linked with many cancers, but its role in the hypoxic prostate tumour environment has not been well studied. In this paper, the link between hypoxia and miR-21 in prostate cancer is investigated. A bioinformatic analysis of The Cancer Genome Atlas (TCGA) prostate biopsy datasets shows the up-regulation of miR-21 is significantly associated with prostate cancer and clinical markers of disease progression. This up-regulation of miR-21 expression was shown to be caused by hypoxia in the LNCaP prostate cancer cell line in vitro and in an in vivo prostate tumour xenograft model. A functional enrichment analysis also revealed a significant association of miR-21 and its target genes with processes related to cellular hypoxia. The over-expression of miR-21 increased the migration and colony-forming ability of RWPE-1 normal prostate cells. In vitro and in silico analyses demonstrated that miR-21 down-regulates the tumour suppressor gene Ras Homolog Family Member B (RHOB) in prostate cancer. Further a TCGA analysis illustrated that miR-21 can distinguish between different patient outcomes following therapy. This study presents evidence that hypoxia is a key contributor to the over-expression of miR-21 in prostate tumours, which can subsequently promote prostate cancer progression by suppressing RHOB expression. We propose that miR-21 has good potential as a clinically useful diagnostic and prognostic biomarker of hypoxia and prostate cancer

Circulating and Intracellular miRNAs as Prognostic and Predictive Factors in HER2-Positive Early Breast Cancer Treated with Neoadjuvant Chemotherapy: A Review of the Literature

SIMPLE SUMMARY: Breast cancer is a leading cause of female cancer-related death worldwide. Anti-HER2-targeted therapies dramatically improved prognosis for HER2-positive breast cancer patients. Despite that, growing drug resistance due to the pressure of therapy is relatively frequent. For that reason, it is necessary to find biomarkers able to predict treatment sensitivity and survival outcomes. Increasing research has shown how miRNAs, secreted by tumor cells, are strongly involved in cancer development. In this review, we will discuss the recent evidence on the predictive and prognostic value of miRNAs involved in HER2-positive early breast cancer progression. ABSTRACT: MicroRNAs (miRNA) are small noncoding RNAs that can act as both oncogene and tumor suppressors. Deregulated miRNA expression has been detected in human cancers, including breast cancer (BC). Considering their important roles in tumorigenesis, miRNAs have been investigated as potential prognostic and diagnostic biomarkers. Neoadjuvant setting is an optimal model to investigate in vivo the mechanism of treatment resistance. In the management of human epidermal growth factor receptor-2 (HER2)-positive early BC, the anti-HER2-targeted therapies have drastically changed the survival outcomes. Despite this, growing drug resistance due to the pressure of therapy is relatively frequent. In the present review, we focused on the main miRNAs involved in HER2-positive BC tumorigenesis and discussed the recent evidence on their predictive and prognostic value