Topological Structures in the Space of Treatment-Naïve Patients with Chronic Lymphocytic Leukemia.

Patients are complex and heterogeneous; clinical data sets are complicated by noise, missing data, and the presence of mixed-type data. Using such data sets requires understanding the high-dimensional "space of patients", composed of all measurements that define all relevant phenotypes. The current state-of-the-art merely defines spatial groupings of patients using cluster analyses.

Oncogenic role and target properties of the lysine-specific demethylase KDM1A in chronic lymphocytic leukemia.

In chronic lymphocytic leukemia (CLL), epigenetic alterations are considered to centrally shape the transcriptional signatures that drive disease evolution and underlie its biological and clinical subsets. Characterizations of epigenetic regulators, particularly histone-modifying enzymes, are very rudimentary in CLL. In efforts to establish effectors of the CLL-associated oncogene T-cell leukemia 1A (TCL1A), we identified here the lysine-specific histone demethylase KDM1A to interact with the TCL1A protein in B cells in conjunction with an increased catalytic activity of KDM1A.

Refining prognosis in chronic lymphocytic leukemia with normal Fluorescence in situ hybridization results.

Fluorescence in situ hybridization (FISH) to detect the recurrent cytogenetics abnormalities deletion 13q, trisomy 12, deletion 11q, and deletion 17p is important for prognostication in chronic lymphocytic leukemia (CLL). A subset of patients are negative for each of these abnormalities (normal 12/13/11/17 FISH), and outcomes are heterogenous within this group. To elucidate variables important for prognostication in this subgroup we conducted a retrospective analysis of 280 treatment-naïve CLL patients with normal standard CLL FISH results.

Electronic Health Records and Genomics: Perspectives from the Association for Molecular Pathology Electronic Health Record (EHR) Interoperability for Clinical Genomics Data Working Group.

The use of genomics in medicine is expanding rapidly, but information systems are lagging in their ability to support genomic workflows both from the laboratory and patient-facing provider perspective. The complexity of genomic data, the lack of needed data standards, and lack of genomic fluency and functionality as well as several other factors have contributed to the gaps between genomic data generation, interoperability, and utilization. These gaps are posing significant challenges to laboratory and pathology professionals, clinicians, and patients in the ability to generate, communicate, consume, and use genomic test results.