Role of Biobanks for Cancer Research and Precision Medicine in Hepatocellular Carcinoma.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a highly complex and deadly cancer. There is an urgent need for new and effective treatment modalities. Since the primary goal in the management of cancer is to cure and improve survival, personalized therapy can increase survival, reduce mortality rates, and improve quality of life. Biobanks hold potential in leading to breakthroughs in biomedical research and precision medicine (PM). They serve as a biorepository, collecting, processing, storing, and supplying specimens and relevant data for basic, translational, and clinical research. OBJECTIVE: We aimed to highlight the fundamental role of biobanks, harboring high quality, sustainable collections of patient samples in adequate size and variability, for developing diagnostic, prognostic, and predictive biomarkers to develop and PM approaches in the management of HCC. METHOD: We obtained information from previously published articles and BBMRI directory. RESULTS AND CONCLUSION: Biobanking of high-quality biospecimens along with patient clinical information provides a fundamental scientific infrastructure for basic, translational, and clinical research. Biobanks that control and eliminate pre-analytical variability of biospecimens, provide a platform to identify reliable biomarkers for the application of PM. We believe, establishing HCC biobanks will empower to underpin molecular mechanisms of HCC and generate strategies for PM. Thus, first, we will review current therapy approaches in HCC care. Then, we will summarize challenges in HCC management. Lastly, we will focus on the best practices for establishing HCC biobanking to support research, translational medicine in the light of new experimental research conducted with the aim of delivering PM for HCC patients.

Meta-microRNA Biomarker Signatures to Classify Breast Cancer Subtypes.

Breast cancer is one of the leading causes of morbidity and mortality that is in need of novel diagnostics and therapeutics. Meta-analysis of microarray data offers promise to combine studies and provide more robust results. We report here a molecular classification of pathological subtypes (estrogen receptor [ER], progesterone receptor [PR], and Human Epidermal Growth Factor Receptor 2 [HER2]) of breast cancers with microRNA (miRNA)-dependent signatures. A ranking-based meta-analysis approach was applied to eight independent microarray data sets and meta-miRNA lists were obtained that are specific to each breast cancer subtype. The comparison of the lists with miRCancer and the PhenomiR 2.0 databases pointed out nine prominent miRNAs: let-7b-5p, let-7c-5p, let-7e-5p, miR-130a-3p, miR-30a-5p, miR-92a-1-5p, miR-211-5p, miR-500a-3p, and miR-516b-3p. Further analysis conducted with the TCGA data showed that these miRNAs can differentiate tumors from normal samples as well as discriminate the molecular subtypes of breast cancer. According to the PAM50 classification, three of these miRNAs (let-7b-5p, let-7c-5p, and miR-30a-5p) downregulated significantly, whereas miR-130a-3p, miR-92a-1-5p, miR-211-5p, and miR-500a-3p upregulated in tumors from the luminal A to the basal-like subtypes. When the prominent meta-miRNAs and their targets were analyzed, they appeared to be taking part in important signaling pathways in cancer such as the PI3K-Akt signaling and the p53 signaling pathways. Furthermore, the regulatory genes, which are key players for ER, PR, and ErBb signaling pathways, were found to be under control of several meta-miRNAs. These meta-miRNAs and the genes they are regulating offer new promise for future translational research and potential targets for precision medicine diagnostics.

Do Perineuronal Net Elements Contribute to Pathophysiology of Spinal Muscular Atrophy? In Vitro and Transcriptomics Insights.

Spinal muscular atrophy (SMA) is one of the most common childhood onset neurodegenerative disorders in global health whereby novel biomarkers and therapeutic targets are sorely needed. SMA is an autosomal recessive genetic disorder resulting in degeneration of α-motor neurons in the brain stem and spinal cord that leads to mortality in infants worldwide. In majority of the patients, SMA is caused by homozygous deletion of the SMN1 gene. The clinical spectrum of the SMA displays, however, large person-to-person variations where the underlying mechanisms are poorly understood. We report in this study transcriptomics insights gleaned from patients with the severe type I (GM03813 and GM09677) and the mild type III. Pathway enrichment and functional analysis showed that especially extracellular matrix (ECM), synapse organization, and ECM receptor interaction pathways were affected. Among the neural ECM components, hyaluronan and proteoglycan link protein (HAPLN1), which is a key triggering molecule of the perineuronal net (PNN), was significantly downregulated in type I fibroblasts compared to type III. PNN is a specialized form of neural ECM around the neuronal cell bodies and dendrites in the central nervous system. In addition, we evaluated the PNN expression in vitro in a model established by SMN silencing in the PC12 rat pheochromocytoma cell line which can be differentiated into neurons with nerve growth factor treatment. In this neuronal in vitro model, we found that HAPLN1 showed a significant 50% decrease. Our results describe the association between PNN elements, especially HAPLN1, and SMA pathophysiology for the first time. These observations collectively inform future translational research on SMA for discovery of novel molecular targets for diagnostics and precision medicine innovation.

hsa-miR-301a- and SOX10-dependent miRNA-TF-mRNA regulatory circuits in breast cancer.

Breast cancer is the most common cancer among women and the molecular pathways that play main roles in breast cancer regulation are still not completely understood. MicroRNAs (miRNAs) and transcription factors (TFs) are important regulators of gene expression. It is important to unravel the relation of TFs, miRNAs, and their targets within regulatory networks to clarify the processes that cause breast cancer and the progression of it. In this study, mRNA and miRNA expression studies including breast tumors and normal samples were extracted from the GEO microarray database. Two independent mRNA studies and a miRNA study were selected and reanalyzed. Differentially expressed (DE) mRNAs and miRNAs between breast tumor and normal samples were listed by using BRBArray Tools. CircuitsDB2 analysis conducted with DE miRNAs and mRNAs resulted in 3 significant circuits that are SOX10- and hsamiR-301a-dependent. The following significant circuits were characterized and validated bioinformatically by using web-based tools: SOX10→hsa-miR-301a→HOXA3, SOX10→hsa-miR-301a→KIT, and SOX10→hsa-miR-301a→NFIB. It can be concluded that regulatory motifs involving miRNAs and TFs may be useful for understanding breast cancer regulation and for predicting new biomarkers.

DICER1 gene and miRNA dysregulation in mesenchymal stem cells of patients with myelodysplastic syndrome and acute myeloblastic leukemia.

Multipotent mesenchymal stem cells (MSC) are key components of the bone marrow (BM) microenvironment. The contribution of this microenvironment to the pathophysiology of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) is not well defined. A recent study in mice demonstrated that DICER1 gene deletion in osteoprogenitor cells from the BM microenvironment suppressed osteogenic differentiation and induced MDS and AML-like haematological findings. The present study evaluated the expression profiles of microRNAs (miRNAs) and DICER1 gene in BM-derived MSC of patients with AML (n=12), MDS (n=10) and healthy controls (HC) (n=8).miRNA expression profiles were analyzed by microarray and confirmations were performed using quantitative real-time PCR (qRT-PCR). Patient MSC displayed impaired proliferative and differentiation potential compared to HC. DICER1 gene expression was lower in MSC from MDS and AML patients than HC and some differentially expressed miRNAs indicated the potential involvement of DICER1 in the pathogenesis of MDS and AML. qRT-PCR confirmation revealed down-regulated miRNAs (hsa-miR-30d-5p, hsa-miR-222-3p and hsa-miR-30a-3p in MDS; hsa-miR-1275, hsa-miR-4725-5p and hsa-miR-143-3p in AML) and over-expressed miRNAs (hsa-miR-4462 in MDS; hsa-miR-134-5p and hsa-miR-874-3p in AML) in MDS and AML. Thus, our findings validate the results of the aforementioned animal study and demonstrate downregulation of DICER1 gene and abnormal miRNA profile in MDS and AML, which may have implications for understanding MDS and AML pathogenesis and contribute to developing targeted treatment strategies.

Identification of Polycystic Ovary Syndrome (PCOS) Specific Genes in Cumulus and Mural Granulosa Cells.

Polycystic ovary syndrome (PCOS) is a metabolic and endocrine disorder which affects women of reproductive age with prevalence of 8-18%. The oocyte within the follicle is surrounded by cumulus cells (CCs), which connect with mural granulosa cells (MGCs) that are responsible for secreting steroid hormones. The main aim of this study is comparing gene expression profiles of MGCs and CCs in PCOS and control samples to identify PCOS-specific differentially expressed genes (DEGs). In this study, two microarray databases were searched for mRNA expression microarray studies performed with CCs and MGCs obtained from PCOS patients and control samples. Three independent studies were selected to be integrated with naive meta-analysis since raw meta-data from these studies were found to be highly correlated. DEGs in these somatic cells were identified for PCOS and control groups. This study enabled us to reveal dysregulation in MAPK (mitogen activated protein kinase), insulin and Wnt signaling pathways between CCs and MGCs in PCOS. The meta-analysis results together with qRT-PCR validations provide evidence that molecular signaling is dysregulated through MGCs and CCs in PCOS, which is important for follicle and oocyte maturation and may contribute to the pathogenesis of the syndrome.