Linking Hematopoietic Differentiation to Co-Expressed Sets of Pluripotency-Associated and Imprinted Genes and to Regulatory microRNA-Transcription Factor Motifs

Molecular Characterization of the Response to Conventional Chemotherapeutics in Pro-B-ALL Cell Lines in Terms of Tumor Relapse

Little is known about optimally applying chemotherapeutic agents in a specific temporal sequence to rapidly reduce the tumor load and to improve therapeutic efficacy. The clinical optimization of drug efficacy while reducing side effects is still restricted due to an incomplete understanding of the mode of action and related tumor relapse mechanisms on the molecular level. The molecular characterization of transcriptomic drug signatures can help to identify the affected pathways, downstream regulated genes and regulatory interactions related to tumor relapse in response to drug application. We tried to outline the dynamic regulatory reprogramming leading to tumor relapse in relapsed MLL-rearranged pro-B-cell acute lymphoblastic leukemia (B-ALL) cells in response to two first-line treatments: dexamethasone (Dexa) and cytarabine (AraC). We performed an integrative molecular analysis of whole transcriptome profiles of each treatment, specifically considering public knowledge of miRNA regulation via a network-based approach to unravel key driver genes and miRNAs that may control the relapse mechanisms accompanying each treatment. Our results gave hints to the crucial regulatory roles of genes leading to Dexa-resistance and related miRNAs linked to chemosensitivity. These genes and miRNAs should be further investigated in preclinical models to obtain more hints about relapse processes.

TFmiR2: constructing and analyzing disease-, tissue- and process-specific transcription factor and microRNA co-regulatory networks

SUMMARY

TFmiR2 is a freely available web server for constructing and analyzing integrated transcription factor (TF) and microRNA (miRNA) co-regulatory networks for human and mouse. TFmiR2 generates tissue- and biological process-specific networks for the set of deregulated genes and miRNAs provided by the user. Furthermore, the service can now identify key driver genes and miRNAs in the constructed networks by utilizing the graph theoretical concept of a minimum connected dominating set. These putative key players as well as the newly implemented four-node TF-miRNA motifs yield novel insights that may assist in developing new therapeutic approaches.

AVAILABILITY AND IMPLEMENTATION

The TFmiR2 web server is available at http://service.bioinformatik.uni-saarland.de/tfmir2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Radiogenomic Approach for Decoding Molecular Mechanisms Underlying Tumor Progression in Prostate Cancer

Prostate cancer (PCa) is a genetically heterogeneous cancer entity that causes challenges in pre-treatment clinical evaluation, such as the correct identification of the tumor stage. Conventional clinical tests based on digital rectal examination, Prostate-Specific Antigen (PSA) levels, and Gleason score still lack accuracy for stage prediction. We hypothesize that unraveling the molecular mechanisms underlying PCa staging via integrative analysis of multi-OMICs data could significantly improve the prediction accuracy for PCa pathological stages. We present a radiogenomic approach comprising clinical, imaging, and two genomic (gene and miRNA expression) datasets for 298 PCa patients. Comprehensive analysis of gene and miRNA expression profiles for two frequent PCa stages (T2c and T3b) unraveled the molecular characteristics for each stage and the corresponding gene regulatory interaction network that may drive tumor upstaging from T2c to T3b. Furthermore, four biomarkers (ANPEP, mir-217, mir-592, mir-6715b) were found to distinguish between the two PCa stages and were highly correlated (average r = ± 0.75) with corresponding aggressiveness-related imaging features in both tumor stages. When combined with related clinical features, these biomarkers markedly improved the prediction accuracy for the pathological stage. Our prediction model exhibits high potential to yield clinically relevant results for characterizing PCa aggressiveness.

Combined Casein Kinase II inhibition and epigenetic modulation in acute B-lymphoblastic leukemia

Background

The tumor suppressor protein phosphatase and tensin homolog (PTEN) is a key regulator of the PI3K/AKT pathway which is frequently altered in a variety of tumors including a subset of acute B-lymphoblastic leukemias (B-ALL). While PTEN mutations and deletions are rare in B-ALL, promoter hypermethylation and posttranslational modifications are the main pathways of PTEN inactivation. Casein Kinase II (CK2) is often upregulated in B-ALL and phosphorylates both PTEN and DNA methyltransferase 3A, resulting in increased PI3K/AKT signaling and offering a potential mechanism for further regulation of tumor-related pathways.

Methods

Here, we evaluated the effects of CK2 inhibitor CX-4945 alone and in combination with hypomethylating agent decitabine on B-ALL proliferation and PI3K/AKT pathway activation. We further investigated if CX-4945 intensified decitabine-induced hypomethylation and identified aberrantly methylated biological processes after CK2 inhibition. In vivo tumor cell proliferation in cell line and patient derived xenografts was assessed by longitudinal full body bioluminescence imaging and peripheral blood flow cytometry of NSG mice.

Results

CX-4945 incubation resulted in CK2 inhibition and PI3K pathway downregulation thereby inducing apoptosis and anti-proliferative effects. CX-4945 further affected methylation patterns of tumor-related transcription factors and regulators of cellular metabolism. No overlap with decitabine-affected genes or processes was detected. Decitabine alone revealed only modest anti-proliferative effects on B-ALL cell lines, however, if combined with CX-4945 a synergistic inhibition was observed. In vivo assessment of CX-4945 in B-ALL cell line xenografts resulted in delayed proliferation of B-ALL cells. Combination with DEC further decelerated B-ALL expansion significantly and decreased infiltration in bone marrow and spleen. Effects in patient-derived xenografts all harboring a t(4;11) translocation were heterogeneous.

Conclusions

We herein demonstrate the anti-leukemic potential of CX-4945 in synergy with decitabine in vitro as well as in vivo identifying CK2 as a potentially targetable kinase in B-ALL.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5411-0) contains supplementary material, which is available to authorized users.

A workflow for the integrative transcriptomic description of molecular pathology and the suggestion of normalizing compounds, exemplified by Parkinson's disease

The volume of molecular observations on human diseases in public databases is continuously increasing at accelerating rates. A bottleneck is their computational integration into a coherent description, from which researchers may derive new well-founded hypotheses. Also, the need to integrate data from different technologies (genetics, coding and regulatory RNA, proteomics) emerged in order to identify biomarkers for early diagnosis and prognosis of complex diseases and therefore facilitating the development of novel treatment approaches. We propose here a workflow for the integrative transcriptomic description of the molecular pathology in Parkinsons’s Disease (PD), including suggestions of compounds normalizing disease-induced transcriptional changes as a paradigmatic example. We integrated gene expression profiles, miRNA signatures, and publicly available regulatory databases to specify a partial model of the molecular pathophysiology of PD. Six genetic driver elements (2 genes and 4 miRNAs) and several functional network modules that are associated with PD were identified. Functional modules were assessed for their statistical significance, cellular functional homogeneity, literature evidence, and normalizing small molecules. In summary, our workflow for the joint regulatory analysis of coding and non-coding RNA, has the potential to yield clinically as well as biologically relevant information, as demonstrated here on PD data.