Motivation Genomic analyses from large cancer cohorts have revealed the mutational heterogeneity problem which hinders the identification of driver genes based only on mutation profiles. One way to tackle this problem is to incorporate the fact that genes act together in functional modules. The connectivity knowledge present in existing protein–protein interaction (PPI) networks together with mutation frequencies of genes and the mutual exclusivity of cancer mutations can be utilized to increase the accuracy of identifying cancer driver modules. Results We present a novel edge-weighted random walk-based approach that incorporates connectivity information in the form of protein–protein interactions (PPIs), mutual exclusivity and coverage to identify cancer driver modules. MEXCOwalk outperforms several state-of-the-art computational methods on TCGA pan-cancer data in terms of recovering known cancer genes, providing modules that are capable of classifying normal and tumor samples and that are enriched for mutations in specific cancer types. Furthermore, the risk scores determined with output modules can stratify patients into low-risk and high-risk groups in multiple cancer types. MEXCOwalk identifies modules containing both well-known cancer genes and putative cancer genes that are rarely mutated in the pan-cancer data. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/MEXCOwalk. Supplementary information Supplementary data are available at Bioinformatics online.

Motivation: Genomic analyses from large cancer cohorts have revealed the mutational heterogeneity problem which hinders the identification of driver genes based only on mutation profiles. One way to tackle this problem is to incorporate the fact that genes act together in functional modules. The connectivity knowledge present in existing protein-protein interaction networks together with mutation frequencies of genes and the mutual exclusivity of cancer mutations can be utilized to increase the accuracy of identifying cancer driver modules. Results: We present a novel edge-weighted random walk-based approach that incorporates connectivity information in the form of protein-protein interactions, mutual exclusivity, and coverage to identify cancer driver modules. MEXCOwalk outperforms several state-of-the-art computational methods on TCGA pancancer data in terms of recovering known cancer genes, providing modules that are capable of classifying normal and tumor samples, and that are enriched for mutations in specific cancer types. Furthermore, the risk scores determined with output modules can stratify patients into low-risk and high-risk groups in multiple cancer types. MEXCOwalk identifies modules containing both well-known cancer genes and putative cancer genes that are rarely mutated in the pan-cancer data. The data, the source code, and useful scripts are available at: https://github.com/abu-compbio/MEXCOwalk. Contact:

Papillary fibroelastomas (PFEs) are the second most common primary cardiac tumors after myxomas. They are typically located on the aortic valve and comprise a short pedicle with multiple papillary fronds. PFEs are benign but highly friable in nature. Patients can be asymptomatic or present with severe thromboembolic complications. Echocardiography is the modality of choice for the diagnosis of these masses and surgical resection is indicated even in asymptomatic patients. Here, we have presented a case of a 53-year-old male who presented with a stroke after embolization of a PFE.

No abstract

Dilated cardiomyopathy (DCM) is a severe myocardial disease with diversified etiologies. Coxsackievirus serotype B (CV-B) is a known cause of infectious myocarditis that leads to DCM. The pathogenesis of CV-B myocarditis is complex and involves a combination of tissue destruction from viral proliferation and host immune response. Diagnosis is based on clinical findings and the presence of post-infection elevated titers of IgM antibodies to CV-B. Echocardiography is an important imaging modality that plays a key role in diagnosing DCM. Rare complications of coxsackievirus infection may include facial paralysis and chronic kidney disease with nephrotic syndrome. Here we present a rare case of a 29-year-old-male with recent Bell's palsy who presented with new-onset heart failure with left ventricular ejection fraction of 5% and focal segmental glomerulosclerosis nephrotic syndrome in the setting of elevated antibodies to CV-B.