Abstract 3663: Extending and analytical validation of a hematological cancer panel for simultaneous detection of driver mutations, copy number variations and translocations in tissue and blood samples
Authors: Huang Yong , Zhang Tom , Xie Feng , Dong Jianrong , Wang Xiaohong , Zhao Zhixin , Luo Shujun , Zhou Kemin , Jia Shidong , Du Pan 
Published: March 2024

Background Hematological cancers represent approximately 9.4% of all new cancer cases in the US, with varying prevalence among different age groups. For instance, Acute Lymphocytic Leukemia (ALL) is more prevalent in children (less than 15 years), while Multiple Myeloma and Non-Hodgkin Lymphoma are commonly identified in older population (65 or older). Each hematological cancer subtype has distinct mutation and expression profiles, necessitating the coverage of various variant types, including point mutations, gene copy number variations (CNVs), and translocations. In this study, we extend the PredicineHEME panel to encompass long-range translocation and CNV detections.

Methods The extension of the original PredicineHEME panel involves three key modifications. First, a genome-wide SNP backbone was incorporated to enhance the sensitive detection of both gene and chromosomal-level CNVs and Loss of Heterozygosity (LOH). Second, additional coverage of translocation breakpoint regions was added, considering the panel's application in liquid biopsy samples. Coverage included the most frequently found translocations in major hematological cancers. Third, the driver gene list was supplemented to include genes and mutations treated as active therapeutic targets in clinical studies. Analytical validation was conducted using contrived reference materials, cell lines with known biomarker status, and healthy and clinical samples with known mutations or translocation status.

Results The expanded panel underwent balanced testing with healthy normal saliva gDNA samples to ensure even capture of targeted genomic regions. Assay testing followed CLIA/CAP guidelines on analytical validation materials. The Limit of Detection for SNV/INDEL and known translocation breakpoint reached as low as 0.3%. Our assay detected over 90% of covered and reported translocation breakpoints in the validation materials. Chromosome arm level CNVs reported in the validation materials were detected with 100% sensitivity and specificity.

Conclusions The expansion of the PredicineHEME panel underwent analytical validation, meeting design expectations. With this extension, the assay can effectively detect driver mutations (SNVs/INDELs), CNVs at gene and chromosomal levels, and targeted large translocations in major hematological cancers.

Citation Format: Yong Huang, Tom Zhang, Feng Xie, Jianrong Dong, Xiaohong Wang, Zhixin Zhao, Shujun Luo, Kemin Zhou, Shidong Jia, Pan Du. Extending and analytical validation of a hematological cancer panel for simultaneous detection of driver mutations, copy number variations and translocations in tissue and blood samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3663.