Enteropathy-type T-cell lymphoma.

Session 7 of the Society for Hematopathology/European Association for Haematopathology Workshop was devoted to case presentations and discussion of enteropathy-type T-cell lymphoma (ETL) and other T-cell lymphomas involving the gastrointestinal tract. ETL is a rare type of T-cell lymphoma, often associated with a history of celiac disease, that usually arises in the jejunum but can involve other gastrointestinal tract sites (eg, stomach and colon). As the cases submitted illustrate, there are 2 histologic groups of ETL that correlate with clinical and immunophenotypic features. Pleomorphic-anaplastic ETL is usually associated with a history of celiac disease and histologic evidence of enteropathy and is most often CD56-. Monomorphic ETL often occurs without a history of celiac disease, has variable histologic evidence of enteropathy, and is usually CD56+. Comparative genomic hybridization has shown recurrent chromosomal gains and losses that are characteristic of ETL and uncommon in other T-cell lymphomas, providing useful ancillary data for the diagnosis of ETL.

Integrating copy number polymorphisms into array CGH analysis using a robust HMM.

MOTIVATION: Array comparative genomic hybridization (aCGH) is a pervasive technique used to identify chromosomal aberrations in human diseases, including cancer. Aberrations are defined as regions of increased or decreased DNA copy number, relative to a normal sample. Accurately identifying the locations of these aberrations has many important medical applications. Unfortunately, the observed copy number changes are often corrupted by various sources of noise, making the boundaries hard to detect. One popular current technique uses hidden Markov models (HMMs) to divide the signal into regions of constant copy number called segments; a subsequent classification phase labels each segment as a gain, a loss or neutral. Unfortunately, standard HMMs are sensitive to outliers, causing over-segmentation, where segments erroneously span very short regions. RESULTS: We propose a simple modification that makes the HMM robust to such outliers. More importantly, this modification allows us to exploit prior knowledge about the likely location of "outliers", which are often due to copy number polymorphisms (CNPs). By "explaining away" these outliers with prior knowledge about the locations of CNPs, we can focus attention on the more clinically relevant aberrated regions. We show significant improvements over the current state of the art technique (DNAcopy with MergeLevels) on previously published data from mantle cell lymphoma cell lines, and on published benchmark synthetic data augmented with outliers. AVAILABILITY: Source code written in Matlab is available from http://www.cs.ubc.ca/~sshah/acgh.