Citations

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal "Modified BSD" open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.

Atypical teratoid/rhabdoid tumor (ATRT) is a highly malignant brain tumor predominantly encountered in infants. Mutations of the SMARCB1 gene are the characteristic genetic lesion. A small group of ATRT stands out clinically, because these tumors are located in the sellar region of adults. To investigate if sellar region ATRT in adults represents a molecular distinct entity, we characterized molecular alterations in 7 sellar region ATRTs in adults as compared with 150 pediatric ATRTs and 47 pituitary adenomas using SMARCB1 sequencing, multiplex ligation-dependent probe amplification and fluorescence in situ hybridization as well as DNA methylation profiling. The median age of the 6 female and 1 male patients was 56 years. On histopathologic examination, all tumors were malignant rhabdoid tumors showing loss of SMARCB1/INI1 protein expression. Two cases displayed compound heterozygous SMARCB1 point mutations, 3 cases showed heterozygous SMARCB1 deletions with point mutations of the other allele and 1 case a homozygous SMARCB1 deletion; in 1 case, underlying SMARCB1 alterations could not be identified. On unsupervised hierarchical cluster analysis of DNA methylation profiles, sellar region ATRTs did not form a distinct group, but clustered with ATRT-MYC, 1 of 3 recently described molecular subgroups of ATRT. On analysis of DNA methylation array intensity data, only 1 sellar region ATRT showed characteristic features of pediatric ATRT-MYC, that is, major copy number losses affecting the SMARCB1 region. In conclusion, these results suggest that sellar region ATRTs in adults form a clinically distinct entity with a different mutational spectrum, but epigenetic similarities with pediatric ATRTs of the ATRT-MYC subgroup.

Abstract Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.