Biology subjects

Koster, J.

Publications and source records attributed to Koster, J..

3 recordsLinked to original sources

bioRxiv2018

A Tumor Suppressor-Regulated Cell Cycle Derived Gene Signature Is Prognostic Of Recurrence Risk In Prostate Cancer

BackgroundThe clinical behavior of prostate cancer (PCa) is variable, and while the majority of cases remain indolent, 10% of patients progress to deadly forms of the disease. Current clinical predictors used at the time of diagnosis have limitations to accurately establish progression risk. Here we describe the development of a tumor suppressor regulated, cell-cycle gene expression based prognostic signature for PCa, and validate its independent contribution to risk stratification in several radical prostatectomy (RP) patient cohorts.\n\nMethodsWe used RNA interference experiments in PCa cell lines to identify a gene expression based gene signature associated with Tmeff2, an androgen regulated, tumor suppressor gene whose expression shows remarkable heterogeneity in PCa. Gene expression was confirmed by qRT-PCR. Correlation of the signature with disease outcome (time to recurrence) was retrospectively evaluated in four geographically different cohorts of patients that underwent RP (834 samples), using multivariate logistical regression analysis. Multivariate analysis were adjusted for standard clinicopathological variables. Performance of the signature was compared to previously described gene expression based signatures using the SIgCheck software.\n\nResultsLow levels of Tmeff2 mRNA significantly (p<0.0001) correlated with reduced disease-free survival (DFS) in patients from the Memorial Sloan Kettering Cancer Center (MSKCC) dataset. We identified a panel of 11 TMEFF2 regulated cell cycle related genes (TMCC11), with strong prognostic value. TMCC11 expression was significantly associated with time to recurrence after prostatectomy in four geographically different patient cohorts (2.9[≤]HR[≥]4.1; p[≤]0.002), served as an independent indicator of poor prognosis in the four RP cohorts (1.96[≤]HR[≥]4.28; p[≤]0.032) and improved the prognostic value of standard clinicopathological markers. The prognostic ability of TMCC11 panel exceeded previously published oncogenic gene signatures (p=0.00017).\n\nConclusionsThis study provides evidence that the TMCC11 gene signature is a robust independent prognostic marker for PCa, reveals the value of using highly heterogeneously expressed genes, like Tmeff2, as guides to discover prognostic indicators, and suggests the possibility that low Tmeff2 expression marks a distinct subclass of PCa.

cancer biology↗

bioRxiv2017

Enhancing Sensitivity And Controlling False Discovery Rate In Somatic Indel Discovery Using A Latent Variable Model

Cancer is a genetic disorder in the first place. Therefore, next-generation sequencing (NGS) based discovery of somatically acquired genetic variants has gained widespread attention. Computational prediction of somatic variants, however, is affected by a variety of confounding factors. In addition to the uncertainties that one commonly encounters also in germline variation prediction, such as misplaced and/or inaccurate read alignments, cancer heterogeneity and impure samples significantly add to the issues. Overall, this hampers state-of-the-art indel discovery tools to discover somatic indels at operable performance rates, although they perform excellently when calling germline indels. While affecting all size ranges, both common and cancer-specific problems interfere in particularly unfavorable ways in the prediction of somatic midsize (30-150 bp) insertions and deletions.\n\nHere, we present a latent variable model that can take the major confounding factors and uncertainties into a unifying account. Using this modeling framework, we first demonstrate how to efficiently compute the probability for a (putative) indel to be somatic, thereby resolving a principled computational runtime bottleneck in Bayesian uncertainty quantification. Second, we show how to reliably estimate the allele frequencies for a given list of indels. Third, we also present an intuitive and effective way to control the false discovery rate, an issue in genetic variant discovery that has been found notoriously hard to deal with. As a tool that implements all methodology developed, we present PROSIC (PROcessing Somatic Indel Calls). PROSIC achieves significant improvements in particular in terms of recall when applied to deletion call sheets, as provided by prevalent state-of-the-art tools, in comparison to their integrated somatic indel calling routines.\n\nThe software is publicly available at https://prosic.github.io and can be easily installed via https://bioconda.github.io.

bioinformatics↗

bioRxiv2017

A homozygous missense mutation in ERAL1, encoding a mitochondrial rRNA chaperone, causes Perrault syndrome

Perrault syndrome (PS) is a rare recessive disorder characterized by ovarian dysgenesis and sensorineural deafness. It is clinically and genetically heterogeneous, and previously mutations have been described in different genes, mostly related to mitochondrial proteostasis. We diagnosed three unrelated females with PS and set out to identify the underlying genetic cause using exome sequencing. We excluded mutations in the known PS genes, but identified a single homozygous mutation in the ERAL1 gene (c.707A>T; p.Asn236Ile). Since ERAL1 protein binds to the mitochondrial 12S rRNA and is involved in the assembly of the small mitochondrial ribosomal subunit, the identified variant represented a likely candidate. In silico analysis of a 3D model for ERAL1 suggested that the mutated residue hinders protein-substrate interactions, potentially affecting its function. On a molecular basis, PS skin fibroblasts had reduced ERAL1 protein levels. Complexome profiling of the cells showed an overall decrease in the levels of assembled small ribosomal subunit, indicating that the ERAL1 variant affects mitochondrial ribosome assembly. Moreover, levels of the 12S rRNA were reduced in the patients, and were fully rescued by lentiviral expression of wild type ERAL1. At the physiological level, mitochondrial respiration was markedly decreased in PS fibroblasts, confirming disturbed mitochondrial function. Finally, knockdown of the C. elegans ERAL1 homologue E02H1.2 almost completely blocked egg production in worms, mimicking the compromised fertility in PS-affected women. Our cross-species data in patient cells and worms support the hypothesis that mutations in ERAL1 can cause PS and are associated with changes in mitochondrial metabolism.

genetics↗