Frank Wucherpfennig

Bio: Frank Wucherpfennig is an academic researcher. The author has contributed to research in topics: Cancer & Cancer cell. The author has an hindex of 1, co-authored 1 publications receiving 176 citations.

miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments

Abstract: Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.

MicroRNA: Biogenesis, Function and Role in Cancer.

Abstract: MicroRNAs are small, highly conserved non-coding RNA molecules involved in the regulation of gene expression. MicroRNAs are transcribed by RNA polymerases II and III, generating precursors that undergo a series of cleavage events to form mature microRNA. The conventional biogenesis pathway consists of two cleavage events, one nuclear and one cytoplasmic. However, alternative biogenesis pathways exist that differ in the number of cleavage events and enzymes responsible. How microRNA precursors are sorted to the different pathways is unclear but appears to be determined by the site of origin of the microRNA, its sequence and thermodynamic stability. The regulatory functions of microRNAs are accomplished through the RNA-induced silencing complex (RISC). MicroRNA assembles into RISC, activating the complex to target messenger RNA (mRNA) specified by the microRNA. Various RISC assembly models have been proposed and research continues to explore the mechanism(s) of RISC loading and activation. The degree and nature of the complementarity between the microRNA and target determine the gene silencing mechanism, slicer-dependent mRNA degradation or slicer-independent translation inhibition. Recent evidence indicates that P-bodies are essential for microRNA-mediated gene silencing and that RISC assembly and silencing occurs primarily within P-bodies. The P-body model outlines microRNA sorting and shuttling between specialized P-body compartments that house enzymes required for slicer –dependent and –independent silencing, addressing the reversibility of these silencing mechanisms. Detailed knowledge of the microRNA pathways is essential for understanding their physiological role and the implications associated with dysfunction and dysregulation.

Circulating microRNAs: Association with disease and potential use as biomarkers

Abstract: The control of gene expression by microRNAs influences many cellular processes and has been implicated in the control of many (patho)physiological states. Recently, microRNAs have been detected in serum and plasma, and circulating microRNA profiles have now been associated with a range of different tumour types, diseases such as stroke and heart disease, as well as altered physiological states such as pregnancy. Here we review the disease-specific profiles of circulating microRNAs, and the methodologies used for their detection and quantification. We also discuss possible functions of circulating microRNAs and their potential as non-invasive biomarkers.

Toward the blood-borne miRNome of human diseases

Abstract: In a multicenter study, we determined the expression profiles of 863 microRNAs by array analysis of 454 blood samples from human individuals with different cancers or noncancer diseases, and validated this 'miRNome' by quantitative real-time PCR. We detected consistently deregulated profiles for all tested diseases; pathway analysis confirmed disease association of the respective microRNAs. We observed significant correlations (P = 0.004) between the genomic location of disease-associated genetic variants and deregulated microRNAs.

MicroRNAs in cerebrospinal fluid identify glioblastoma and metastatic brain cancers and reflect disease activity.

Abstract: An accurate, nonsurgical diagnostic test for brain tumors is currently unavailable, and the methods of monitoring disease progression are not fully reliable. MicroRNA profiling of biological fluids has recently emerged as a diagnostic tool for several pathologic conditions. Here we tested whether microRNA profiling of cerebrospinal fluid (CSF) enables detection of glioblastoma, discrimination between glioblastoma and metastatic brain tumors, and reflects disease activity. We determined CSF levels of several cancer-associated microRNAs for 118 patients diagnosed with different types of brain cancers and nonneoplastic neuropathologies by quantitative reverse transcription PCR analysis. The levels of miR-10b and miR-21 are found significantly increased in the CSF of patients with glioblastoma and brain metastasis of breast and lung cancer, compared with tumors in remission and a variety of nonneoplastic conditions. Members of the miR-200 family are highly elevated in the CSF of patients with brain metastases but not with any other pathologic conditions, allowing discrimination between glioblastoma and metastatic brain tumors. Quantification of as few as 7 microRNAs in CSF enables differential recognition of glioblastoma and metastatic brain cancer using computational machine learning tools (Support Vector Machine) with high accuracy (91%‐99%) on a test set of samples. Furthermore, we show that disease activity and treatment response can be monitored by longitudinal microRNA profiles in the CSF of glioblastoma and non‐small cell lung carcinoma patients. This study demonstrates that microRNA-based detection of brain malignancies can be reliably performed and that microRNAs in CSF can serve as biomarkers of treatment response in brain cancers.