Zepeda-Mendoza, Cinthya J.

Context.— One objective of the College of American Pathologists/American College of Medical Genetics Cytogenetics Committee is to ensure the accurate detection and clinical interpretation of abnormalities observed by fluorescence in situ hybridization (FISH) analysis when evaluating hematologic neoplasms. Objective.— To report a 20-year performance summary (2005–2024) of FISH challenges focusing on hematologic neoplasms. Design.— A retrospective review was performed from 2005 through 2024 to identify FISH challenges specifically addressing hematologic neoplasms. The overall performance of participants was evaluated to identify potential recurring errors of clinical relevance. Results.— A total of 124 hematologic neoplasm FISH challenges from 2005 to 2024 were provided to participating laboratories, including 45 paper challenges (results and/or images were provided for interpretation purposes), 43 liquid challenges (bone marrow aspirate or peripheral blood), and 36 formalin-fixed paraffin-embedded (FFPE) tissue challenges. Of the 124 challenges, 120 (97%) exceeded the required 80% consensus for grading purposes. Of the 4 failed challenges (3%), 2 (1 liquid, 1 paper) involved the interpretation of atypical FISH signal patterns; 1 (paper) involved the interpretation of FISH signal patterns correlating involvement by myeloid versus lymphoid interphase nuclei; and 1 (liquid) likely involved a specimen processing or handling error that resulted in discordant participant responses. All 36 FFPE tissue challenges exceeded the 80% consensus for grading purposes. Conclusions.— This 20-year retrospective review demonstrates that clinical cytogenomic laboratories have been and continue to be highly proficient in the detection and interpretation of FISH abnormalities associated with hematologic neoplasms.

AbstractBalanced and apparently balanced chromosome abnormalities (BCAs) have long been known to generate disease through position effects, either by altering local networks of gene regulation or by positioning genes in architecturally different chromosome domains. Despite these observations, identification of genes distally affected by BCAs is often neglected, especially when predicted gene disruptions are found elsewhere in the genome. In this article, we provide detailed instructions on how to run a computational pipeline that identifies relevant candidates for non‐coding BCA position effects. This methodology facilitates quick identification of genes potentially involved in disease by non‐coding BCAs and other types of rearrangements, and expands on the importance of considering the long‐range consequences of genomic lesions. © 2018 by John Wiley & Sons, Inc.