Targeting multiple genetic aberrations in isolated tumor cells by spectral fluorescence in situ hybridization (S-FISH)

M.L. Slovak, F. Zhang, L. Tcheurekdjian, D. Bobadilla, V. Bedell, D.A. Arber, J.L. Murata-Collins

City of Hope National Medical Center, Duarte, CA

AIM: Human cancers are clonal disorders of single cells that have accumulated multiple mutations in critical genes either through inherited germline alterations or mutations of cellular genes by environmental factors. Biologic and epidemiological evidence suggests neoplastic cell growth with subsequent tumor formation is fundamentally dysregulation of genes associated with immortalization, transformation, cell cycle progression and checkpoint pathways, invasion/ metastasis, and angiogenesis. These data suggest critical aberrations occur at the chromosomal and gene level in cancer and their detection in patient specimens is necessary to improve prognostication, detect minimal residual disease, identify genes that predict biological behavior (tumor progression), and define molecular targets for directed novel therapeutic strategies. Current fluorescence in situ hybridization (FISH) assays reliably detect one to three targets in a single hybridization. Simultaneous detection of more than three chromosomal or gene targets should increase the overall sensitivity of molecular cytogenetics by permitting detection of multiple genetic aberrations at the single cell level. METHODS: Spectral FISH (S-FISH) is a novel molecular cytogenetic approach that targets multiple disease-specific chromosomal aberrations in interphase nuclei via a single hybridization, using combinatorial fluorescence and digital imaging microscopy developed for the Applied Spectral Imaging System. We have developed several tumor-specific S-FISH DNA probe panels to survey 3-10 genetic targets in breast, melanoma, bladder and leukemia samples using a unique two-dye combination of four fluorophores. Samples from cytogenetic residual cell pellets (bone marrow and blood), cryopreserved samples, touch preparations, and bladder washings have been analyzed. Validation of S-FISH was performed by classic cytogenetics when metaphase cells were available or by conventional FISH analyses. RESULTS: S-FISH readily identified multiple clonal aberrations at the single cell level in a variety of pathological specimens. Chromosome-enumeration panels assessed ploidy in solid tumors, disease-specific panels allowed for the identification of clonal genetic aberrations in newly diagnosed breast tumors or recurrent bladder cancer, and patient-tailored panels allowed for the detection of minimal residual disease (MRD) in acute leukemia. Advantages of S-FISH include increased sensitivity by surveying six genetic targets, critical when tumor samples are of limited size, identifying aberrations in non-mitotic cells, and its ability to detect specific aberrations at the single cell level. Disadvantages include labor intensive screening, interpretive challenges with signal overlap in highly aneuploid specimens, and focal plane distortions. Panels in development will target 1) genes associated with tumor progression in melanoma (i.e., molecular markers of metastatic disease) to identify patients at high risk for recurrent disease and 2) locus-specific sites commonly observed in therapy-related myelodysplasia and acute leukemia to screen autologous stem cell aliquots for transplantation. CONCLUSIONS: Interphase S-FISH is an especially useful assay to diagnose and monitor locus-specific and non-PCR amenable clonal genetic aberrations, such as aneuploidy, variable translocations (e.g., 14q32/IgH) or deletions of chromosomal regions [e.g., del(6q)] in non-mitotic or archival tumor specimens. Accordingly, S-FISH appears to be a sensitive MRD assay with significant clinical application for early detection of new or re-emerging clones, allowing for earlier therapeutic intervention.

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Paper presented at the International Symposium on Predictive Oncology and Intervention Strategies; Paris, France; February 9 - 12, 2002; in the section on Predictive Markers.