Whole-genome profiling of primary cutaneous anaplastic large cell lymphoma.

Primary cutaneous anaplastic large cell lymphoma (pcALCL), a hematological neoplasm caused by skin-homing CD30+ malignant T cells, is part of the spectrum of primary cutaneous CD30+ lymphoproliferative disorders. To date, only a small number of molecular alterations have been described in pcALCL and, so far, no clear unifying theme that could explain the pathogenetic origin of the disease has emerged among patients. In order to clarify the pathogenetic basis of pcALCL, we performed high-resolution genetic profiling (genome/transcriptome) of this lymphoma (n=12) by using whole-genome sequencing, whole-exome sequencing and RNA sequencing. Our study, which uncovered novel genomic rearrangements, copy number alterations and small-scale mutations underlying this malignancy, revealed that the cell cycle, T-cell physiology regulation, transcription and signaling via the PI-3-K, MAPK and G-protein pathways are cellular processes commonly impacted by molecular alterations in patients with pcALCL. Recurrent events affecting cancer-associated genes included deletion of PRDM1 and TNFRSF14, gain of EZH2 and TNFRSF8, small-scale mutations in LRP1B, PDPK1 and PIK3R1 and rearrangements involving GPS2, LINC-PINT and TNK1. Consistent with the genomic data, transcriptome analysis uncovered upregulation of signal transduction routes associated with the PI-3-K, MAPK and G-protein pathways (e.g., ERK, phospholipase C, AKT). Our molecular findings suggest that inhibition of proliferation-promoting pathways altered in pcALCL (particularly PI-3-K/AKT signaling) should be explored as potential alternative therapy for patients with this lymphoma, especially, for cases that do not respond to first-line skin-directed therapies or with extracutaneous disease.

cblaster: a remote search tool for rapid identification and visualization of homologous gene clusters.

Motivation: Genes involved in coordinated biological pathways, including metabolism, drug resistance and virulence, are often collocalized as gene clusters. Identifying homologous gene clusters aids in the study of their function and evolution, however, existing tools are limited to searching local sequence databases. Tools for remotely searching public databases are necessary to keep pace with the rapid growth of online genomic data. Results: Here, we present cblaster, a Python-based tool to rapidly detect collocated genes in local and remote databases. cblaster is easy to use, offering both a command line and a user-friendly graphical user interface. It generates outputs that enable intuitive visualizations of large datasets and can be readily incorporated into larger bioinformatic pipelines. cblaster is a significant update to the comparative genomics toolbox. Availability and implementation: cblaster source code and documentation is freely available from GitHub under the MIT license (github.com/gamcil/cblaster). Supplementary information: Supplementary data are available at Bioinformatics Advances online.