Population-based characterization of the genetic landscape of chronic lymphocytic leukemia patients referred for cytogenetic testing in British Columbia, Canada: the role of provincial laboratory standardization

作者：Gerrie Alina S; Huang Steven J T; Bruyere Helene; Dalal Chinmay; Hrynchak Monica; Karsan Aly; Ramadan Khaled M; Smith Adam C; Tyson Christine; Toze Cynthia L; Gillan Tanya L^*

来源：Cancer Genetics, 2014, 207(7-8): 316-325.

DOI：10.1016/j.cancergen.2014.08.006

• Chronic lymphocytic leukemia
• cytogenetic
• fluorescence in situ hybridization
• validation
• population-based

Detection of recurrent chromosome abnormalities by fluorescence in situ hybridization (FISH) is an essential component of care in chronic lymphocytic leukemia (CLL) patients. In the province of British Columbia (BC), Canada, population 4.6 million, CLL patients receive uniform evaluation and therapy with FISH testing performed in three jurisdictions. The aims of this study were to (i) validate CLL-FISH testing among the BC cytogenetic laboratories to ensure standardization of results and (ii) characterize population-level CLL-FISH abnormalities by pooling provincial data. From 2004 to 2011, 585 consecutive patients underwent pretreatment CLL-FISH testing at laboratory A (50.1%), laboratory B (32.3%), or laboratory C (17.6%). For validation purposes, 26 CLL-FISH abnormalities were tested by each laboratory's protocol, with 91% result concordance. Discordant results involved percent abnormalities at or near cutoff values; therefore, a 10% universal cutoff was established when pooling results. Applying the universal cutoff to the provincial cohort, CLL-FISH abnormalities were detected in 74.9%: 54.9% 13q-, 18.8% +12, 8.5% 11q-, and 7.7% 17p-. In this large population-based cohort of patients referred for CLL-FISH testing, frequencies of abnormalities detected by FISH analysis were highly consistent with those reported in single-institution and clinical trial populations. Provinces or districts that work together to care for CLL patients can effectively pool data with appropriate laboratory validation to ensure standardization of results.

• 出版日期2014-8