Abstract 139: cfDNA methylation profiling distinguishes lineage-specific hematologic malignancies

Introduction: Hematologic (heme) malignancies and their precursor conditions are highly prevalent. They are also diverse in biology, clinical presentation, and outcomes, underlining the importance of differentiating them. Previously, we demonstrated that a blood-based targeted methylation assay detected multiple cancer types across stages. Here, we examined test performance on various heme cancers, identifying specific methylation signatures. Methods: From the second substudy (training set) of the Circulating Cell-free Genome Atlas (CCGA) study (NCT02889978), we evaluated 325 participants from 17 different heme disease subtypes and 3,211 non-cancer controls enrolled without a cancer diagnosis. A cross-validated mutual information-based algorithm was used to identify features that discriminated heme subtypes. The resulting feature distribution was visualized using uniform manifold approximation and projection (UMAP) dimensionality reduction on held-out data. In cross validation with feature selection, we then trained a multinomial classifier to distinguish from among the major heme cancers and non-cancer and correlated the model's class probabilities to positions in feature space. Results: Dimensionality reduction and visualization of input features demonstrated that heme malignancies separated into five major clusters reflecting developmental lineages and disease ontogeny: myeloid, circulating lymphomas, hodgkin lymphomas, non-hodgkin lymphomas, and plasma cell neoplasm. The position of samples within each heme cluster correlated with the cancer signal strength. At 99.4% specificity [95% CI: 99.1, 99.7], heme cancer detection was 74.5% [69.4, 79.1] overall, 67.7% [41.1, 87.8] for myeloid, 77.9% [66.3, 86.9] for circulating lymphomas, 90.7% [73.2, 98.4] for hodgkin lymphomas, 68.6% [60.4, 76.1] for other non-hodgkin lymphomas, and 78.8% [67.0, 87.9] for plasma cell neoplasms. Of 18 non-cancer participants who were classified as having heme cancers, 4 were predicted as myeloid, 6 as circulating lymphoid, and 8 as other non-hodgkin lymphoid neoplasms (