Fusion Gene Detection Using Whole-Exome Sequencing Data in Cancer Patients

Several fusion genes are directly involved in the initiation and progression of cancers. Numerous bioinformatics tools have been developed to detect fusion events, but they are mainly based on RNA-seq data. The whole-exome sequencing (WES) represents a powerful technology that is widely used for disease-related DNA variant detection. In this study, we build a novel analysis pipeline called Fuseq-WES to detect fusion genes at DNA level based on the WES data. The same method applies also for targeted panel sequencing data. We assess the method to real datasets of acute myeloid leukemia (AML) and prostate cancer patients. The result shows that two of the main AML fusion genes discovered in RNA-seq data, PML-RARA and CBFB-MYH11, are detected in the WES data in 36 and 63% of the available samples, respectively. For the targeted deep-sequencing of prostate cancer patients, detection of the TMPRSS2-ERG fusion, which is the most frequent chimeric alteration in prostate cancer, is 91% concordant with a manually curated procedure based on four other methods. In summary, the overall results indicate that it is challenging to detect fusion genes in WES data with a standard coverage of ∼ 15–30x, where fusion candidates discovered in the RNA-seq data are often not detected in the WES data and vice versa. A subsampling study of the prostate data suggests that a coverage of at least 75x is necessary to achieve high accuracy

Location of Organ Procurement and Distribution Organisation Decisions and Their Impact on Kidney Allocations: A Developing Country Perspective

Managing organ transplant networks is a complex task. It intertwines between locating the organ procurement and distribution organization (OPDO) (long-term decision) and allocating organs to the suitable destination (short-term decision). The literature lacks deliberation on the effect of those long-term decisions on short-term ones under the influence of clinical and non-clinical factors. This paper addresses this gap using a k-sum model for locational choice, and a discrete simulation approach for the allocation procedure for a real-life case study from a developing economy perspective. The study explores the trade-off between efficiency (distance-centric models) and equity (the result of time-centric allocation models). Our analysis of the efficiency of locational models and equity of the allocation policies reveal strong inter-dependence of both these decisions, a significant finding of this research. These findings offer an integrated model for high-level decision-makers, which can be used during the locational planning stage and provide input to design standard operating procedures for transplantation schemes. \textcopyright 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature

External Validation of the Prostate Biopsy Collaborative Group Risk Calculator and the Rotterdam Prostate Cancer Risk Calculator in a Swedish Population-based Screening Cohort

Background: External validation of risk calculators (RCs) is necessary to determine their clinical applicability beyond the setting in which these were developed. Objective: To assess the performance of the Rotterdam Prostate Cancer RC (RPCRC) and the Prostate Biopsy Collaborative Group RC (PBCG-RC). Design, setting, and participants: We used data from the prospective, population-based STHLM3 screening study, performed in 2012–2015. Participants with prostate-specific antigen ≥3 ng/ml who underwent systematic prostate biopsies were included. Outcome measurements and statistical analysis: Probabilities for clinically significant prostate cancer (csPCa), defined as International Society of Urological Pathology grade ≥2, were calculated for each participant. External validity was assessed by calibration, discrimination, and clinical usefulness for both original and recalibrated models. Results and limitations: Out of 5841 men, 1054 (18%) had csPCa. Distribution of risk predictions differed between RCs; median risks for csPCa using the RPCRC and PBCG-RC were 3.3% (interquartile range [IQR] 2.1–7.1%) and 20% (IQR 15–28%), respectively. The correlation between RC risk estimates on individual level was moderate (Spearman's r = 0.55). Using the RPCRC's recommended risk threshold of ≥4% for finding csPCa, 36% of participants would get concordant biopsy recommendations. At 10% risk cut-off, RCs agreed in 23% of cases. Both RCs showed good discrimination, with areas under the curves for the RPCRC of 0.74 (95% confidence interval [CI] 0.72–0.76) and the PBCG-RC of 0.70 (95% CI 0.68–0.72). Calibration was adequate using the PBCG-RC (calibration slope: 1.13 [95% CI 1.03–1.23]), but the RPCRC underestimated the risk of csPCa (calibration slope: 0.73 [0.68–0.79]). The PBCG-RC showed a net benefit in a decision curve analysis, whereas the RPCRC showed no net benefit at clinically relevant risk threshold levels. Recalibration improved clinical benefit, and differences between RCs decreased. Conclusions: Assessment of calibration is essential to ensure the clinical value of risk prediction tools. The PBCG-RC provided clinical benefit in its current version online. O the contrary, the RPCRC cannot be recommended in this setting. Patient summary: Predicting the probability of finding prostate cancer on biopsy differed between two assessed risk calculators. After recalibration, the agreement of the models improved, and both were shown to be clinically useful

Physiological ranges of matrix rigidity modulate primary mouse hepatocyte function in part through hepatocyte nuclear factor 4 alpha

Matrix rigidity has important effects on cell behavior and is increased during liver fibrosis; however, its effect on primary hepatocyte function is unknown. We hypothesized that increased matrix rigidity in fibrotic livers would activate mechanotransduction in hepatocytes and lead to inhibition of hepatic-specific functions. To determine the physiologically relevant ranges of matrix stiffness at the cellular level, we performed detailed atomic force microscopy analysis across liver lobules from normal and fibrotic livers. We determined that normal liver matrix stiffness was around 150Pa and increased to 1–6kPa in areas near fibrillar collagen deposition in fibrotic livers. In vitro culture of primary hepatocytes on collagen matrix of tunable rigidity demonstrated that fibrotic levels of matrix stiffness had profound effects on cytoskeletal tension and significantly inhibited hepatocyte-specific functions. Normal liver stiffness maintained functional gene regulation by hepatocyte nuclear factor 4 alpha (HNF4α) whereas fibrotic matrix stiffness inhibited the HNF4α transcriptional network. Fibrotic levels of matrix stiffness activated mechanotransduction in primary hepatocytes through focal adhesion kinase (FAK). In addition, blockade of the Rho/Rho-associated protein kinase (ROCK) pathway rescued HNF4α expression from hepatocytes cultured on stiff matrix. CONCLUSION: Fibrotic levels of matrix stiffness significantly inhibit hepatocyte-specific functions in part by inhibiting the HNF4α transcriptional network mediated through the Rho/ROCK pathway. Increased appreciation of the role of matrix rigidity in modulating hepatocyte function will advance our understanding of the mechanisms of hepatocyte dysfunction in liver cirrhosis and spur development of novel treatments for chronic liver disease