Showing papers by "Hans-Peter Lenhof published in 2020"

miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database.

Abstract: Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.

Evaluating the Use of Circulating MicroRNA Profiles for Lung Cancer Detection in Symptomatic Patients.

Abstract: Importance The overall low survival rate of patients with lung cancer calls for improved detection tools to enable better treatment options and improved patient outcomes. Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures. Objective To investigate the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants. Design, Setting, and Participants This multicenter, cohort study included patients from case-control and cohort studies (TREND and COSYCONET) with 3102 patients being enrolled by convenience sampling between March 3, 2009, and March 19, 2018. For the cohort study TREND, population sampling was performed. Clinical diagnoses were obtained for 3046 patients (606 patients with non–small cell and small cell lung cancer, 593 patients with nontumor lung diseases, 883 patients with diseases not affecting the lung, and 964 unaffected control participants). No samples were removed because of experimental issues. The collected data were analyzed between April 2018 and November 2019. Main Outcomes and Measures Sensitivity and specificity of liquid biopsy using miRNA signatures for detection of lung cancer. Results A total of 3102 patients with a mean (SD) age of 61.1 (16.2) years were enrolled. Data on the sex of the participants were available for 2856 participants; 1727 (60.5%) were men. Genome-wide miRNA profiles of blood samples from 3046 individuals were evaluated by machine-learning methods. Three classification scenarios were investigated by splitting the samples equally into training and validation sets. First, a 15-miRNA signature from the training set was used to distinguish patients diagnosed with lung cancer from all other individuals in the validation set with an accuracy of 91.4% (95% CI, 91.0%-91.9%), a sensitivity of 82.8% (95% CI, 81.5%-84.1%), and a specificity of 93.5% (95% CI, 93.2%-93.8%). Second, a 14-miRNA signature from the training set was used to distinguish patients with lung cancer from patients with nontumor lung diseases in the validation set with an accuracy of 92.5% (95% CI, 92.1%-92.9%), sensitivity of 96.4% (95% CI, 95.9%-96.9%), and specificity of 88.6% (95% CI, 88.1%-89.2%). Third, a 14-miRNA signature from the training set was used to distinguish patients with early-stage lung cancer from all individuals without lung cancer in the validation set with an accuracy of 95.9% (95% CI, 95.7%-96.2%), sensitivity of 76.3% (95% CI, 74.5%-78.0%), and specificity of 97.5% (95% CI, 97.2%-97.7%). Conclusions and Relevance The findings of the study suggest that the identified patterns of miRNAs may be used as a component of a minimally invasive lung cancer test, complementing imaging, sputum cytology, and biopsy tests.

GeneTrail 3: advanced high-throughput enrichment analysis.

Abstract: We present GeneTrail 3, a major extension of our web service GeneTrail that offers rich functionality for the identification, analysis, and visualization of deregulated biological processes. Our web service provides a comprehensive collection of biological processes and signaling pathways for 12 model organisms that can be analyzed with a powerful framework for enrichment and network analysis of transcriptomic, miRNomic, proteomic, and genomic data sets. Moreover, GeneTrail offers novel workflows for the analysis of epigenetic marks, time series experiments, and single cell data. We demonstrate the capabilities of our web service in two case-studies, which highlight that GeneTrail is well equipped for uncovering complex molecular mechanisms. GeneTrail is freely accessible at: http://genetrail.bioinf.uni-sb.de.

SUMO pathway inhibition targets an aggressive pancreatic cancer subtype

Abstract: Objective Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies. Design We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC. Results We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition. Conclusion SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.

Wrinkle in the plan: miR-34a-5p impacts chemokine signaling by modulating CXCL10/CXCL11/CXCR3-axis in CD4+, CD8+ T cells, and M1 macrophages.

Abstract: Background In 2016 the first-in-human phase I study of a miRNA-based cancer therapy with a liposomal mimic of microRNA-34a-5p (miR-34a-5p) was closed due to five immune related serious adverse events (SAEs) resulting in four patient deaths. For future applications of miRNA mimics in cancer therapy it is mandatory to unravel the miRNA effects both on the tumor tissue and on immune cells. Here, we set out to analyze the impact of miR-34a-5p over-expression on the CXCL10/CXCL11/CXCR3 axis, which is central for the development of an effective cancer control. Methods We performed a whole genome expression analysis of miR-34a-5p transfected M1 macrophages followed by an over-representation and a protein–protein network analysis. In-silico miRNA target prediction and dual luciferase assays were used for target identification and verification. Target genes involved in chemokine signaling were functionally analyzed in M1 macrophages, CD4+ and CD8+ T cells. Results A whole genome expression analysis of M1 macrophages with induced miR-34a-5p over-expression revealed an interaction network of downregulated target mRNAs including CXCL10 and CXCL11. In-silico target prediction in combination with dual luciferase assays identified direct binding of miR-34a-5p to the 3′UTRs of CXCL10 and CXCL11. Decreased CXCL10 and CXCL11 secretion was shown on the endogenous protein level and in the supernatant of miR-34a-5p transfected and activated M1 macrophages. To complete the analysis of the CXCL10/CXCL11/CXCR3 axis, we activated miR-34a-5p transfected CD4+ and CD8+ T cells by PMA/Ionomycin and found reduced levels of endogenous CXCR3 and CXCR3 on the cell surface. Conclusions MiR-34a-5p mimic administered by intravenous administration will likely not only be up-taken by the tumor cells but also by the immune cells. Our results indicate that miR-34a-5p over-expression leads in M1 macrophages to a reduced secretion of CXCL10 and CXCL11 chemokines and in CD4+ and CD8+ T cells to a reduced expression of CXCR3. As a result, less immune cells will be attracted to the tumor site. Furthermore, high levels of miR-34a-5p in naive CD4+ T cells can in turn hinder Th1 cell polarization through the downregulation of CXCR3 leading to a less pronounced activation of cytotoxic T lymphocytes, natural killer, and natural killer T cells and possibly contributing to lymphocytopenia.

Quantitative and time-resolved miRNA pattern of early human T cell activation

Abstract: T cells are central to the immune response against various pathogens and cancer cells. Complex networks of transcriptional and post-transcriptional regulators, including microRNAs (miRNAs), coordinate the T cell activation process. Available miRNA datasets, however, do not sufficiently dissolve the dynamic changes of miRNA controlled networks upon T cell activation. Here, we established a quantitative and time-resolved expression pattern for the entire miRNome over a period of 24 h upon human T-cell activation. Based on our time-resolved datasets, we identified central miRNAs and specified common miRNA expression profiles. We found the most prominent quantitative expression changes for miR-155-5p with a range from initially 40 molecules/cell to 1600 molecules/cell upon T-cell activation. We established a comprehensive dynamic regulatory network of both the up- and downstream regulation of miR-155. Upstream, we highlight IRF4 and its complexes with SPI1 and BATF as central for the transcriptional regulation of miR-155. Downstream of miR-155-5p, we verified 17 of its target genes by the time-resolved data recorded after T cell activation. Our data provide comprehensive insights into the range of stimulus induced miRNA abundance changes and lay the ground to identify efficient points of intervention for modifying the T cell response.