RESUMO
Fusion oncogenes can be cancer-defining molecular alterations that are essential for diagnosis and therapy selection.1,2 Rapid and accessible molecular diagnostics for fusion-driven leukemias such as acute promyelocytic leukemia (APL), Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL), and chronic myeloid leukemia (CML) are unavailable, creating a barrier to timely diagnosis and effective targeted therapy in many healthcare settings, including community hospitals and low-resource environments. We developed CRISPR-based RNA-fusion transcript detection assays using SHERLOCK (Specific High-sensitivity Enzymatic Reporter unLOCKing) for the diagnosis of fusion-driven leukemias. We validated these assays using diagnostic APL and CML patient samples from academic centers and dried blood spots from low-resource environments, demonstrating 100% sensitivity and specificity. We identified assay optimizations to enable the use of these tests outside of tertiary cancer centers and clinical laboratories, enhancing the potential impact of this technology. Rapid point-of-care diagnostics can improve outcomes in cancer patients by expanding access to therapies for highly treatable diseases that would otherwise lead to serious adverse outcomes due to delayed or missed diagnoses.
RESUMO
Background: Cytogenetic analysis encompasses a suite of standard-of-care diagnostic testing methods that is routinely applied in cases of acute myeloid leukemia (AML) to assess chromosomal changes that are clinically relevant for risk classification and treatment decisions. Objective: In this study, we assess the use of Genomic Proximity Mapping (GPM) for cytogenomic analysis of AML diagnostic specimens for detection of cytogenetic risk variants included in the European Leukemia Network (ELN) risk stratification guidelines. Methods: Archival patient samples (N=48) from the Fred Hutchinson Cancer Center leukemia bank with historical clinical cytogenetic data were processed for GPM and analyzed with the CytoTerra® cloud-based analysis platform. Results: GPM showed 100% concordance for all specific variants that have associated impacts on risk stratification as defined by ELN 2022 criteria, and a 72% concordance rate when considering all variants reported by the FH cytogenetic lab. GPM identified 39 additional variants, including variants of known clinical impact, not observed by cytogenetics. Conclusions: GPM is an effective solution for the evaluation of known AML-associated risk variants and a source for biomarker discovery.