Detection of B Cell Lymphomas By a Simple Epigenetic Blood Test
Authors: Avivi Irit Mazza , Neaman Miriam , Lowenton-Spier Noa , Perry Chava , Joffe Erel , Vitkon Roy , Bogol Vlada , Michaeli Yael , Gilat Noa , Itelson Lynne , Zirkin Shahar , Deek Jasline , Kastritis Efstathios , Sablauskas Karolis , Cernauskiene Skirmante , Vaitekėnaitė Vilmantė , Zucenka Andrius , Papajik Tomas , Kriegova Eva , Gajdos Petr , Ebenstein Yuval 
Published: December 2024

Background
The SANGUINE project is an EU-funded initiative aimed to address the need for minimally invasive, affordable, and accurate molecular testing for the early detection, pathological characterization, and disease monitoring of hematological malignancies. The project utilizes a novel technology developed by JaxBio, which evaluates methylation profiles of whole blood samples and cell-free DNA (cfDNA) with an immunofluorescence assay that is rapid and uncostly.
Here we present an interim result of the SANGUINE trial, for the detection of diffuse large cell B cell lymphoma (DLBCL) and follicular lymphoma (FL) at diagnosis, assuming that future employment of this test in the clinic, would enable to diagnose FL and DLBCL at early disease stages and promote an early detection of relapse.
Methods
Patients were enrolled in a prospective, multi-center (4 sites), open-label controlled trial (NCT05735704). Inclusion criteria included: age ≥18 years old and diagnosis of FL or DLBCL. Exclusion criteria were prior treatment for anti -NHL, diagnosis of cancer within the last 5 years, HIV diagnosis and active autoimmune disease. Age matched volunteers, with no prior history of HIV, autoimmune disease or cancer served as control.
Peripheral blood samples were collected in Streck tubes and processed within 7 to 10 days. Genomic DNA was extracted from the buffy coat, and cell-free DNA was extracted from the plasma of each sample. Epigenetic markers were then fluorescently labeled using a proprietary chemoenzymatic reaction, followed by hybridization to a high-content microarray chip. A deep neural network (DNN) machine learning algorithm was subsequently employed to select 50-100 epigenetic biomarkers, for distinguishing between DLBCL /FL samples and control samples.
Results
Patient characteristics:
Seventy newly diagnosed, previously untreated B cell Non Hodgkin Lymphoma patients: 28 with FL and 42 with DLBCL were included in the study cohort. Sixty-six age matched healthy volunteers were included as a control. Median age of patients diagnosed with DLBCL and FL were 64 (IQR 73-55) and 65 (IQR 72-54) respectively. All FL patients had an advanced disease stage, 11/28 (39%) with a low disease burden. Most DLBCL patients, had an advanced disease, including 22, diagnosed with stage 4.
Test results:
Cell-free DNA analysis demonstrated a sensitivity, specificity and area under the curve (AUC) of 86%, 93% and 96%, respectively, for correctly identifying newly diagnosed FL, using 100 probes only. The performance for the detection of newly diagnosed DLBCL was similar, achieving sensitivity, specificity and AUC of 90%, 90% and 95%, respectively. Analysis of whole blood samples demonstrated comparable performance to cfDNA, achieving 89% sensitivity and 93% specificity for diagnosing FL, and 90% sensitivity and 93% specificity for diagnosing DLBCL in newly diagnosed patients. When differentiating between the two diseases, 89% of DLBCL and 86% of FL patients were correctly classified.
Conclusion
Diagnosis of both FL and DLBCL in patients with no prior history of NHL can be easily and accurately obtained by performing our methylation analysis in both cfDNA and whole blood, using arrays of 50 or 100 probes. Moreover, the proposed method distinguishes between FL and DLBCL, potentially enabling an early detection of transformation of FL to DLBCL. The selected biomarkers will be printed on a custom-targeted “Lympho-Chip” array, providing an accurate and low-cost test. These results appear to be superior to those previously reported for FL and DLBCL, whereas methylation analysis of cfDNA provided sensitivity of 47.8% and 70% respectively (Westgate, C ASH 2023).
Data on a larger cohort of patients, including analysis of consecutive samples obtained from FL and DLBCL patients prior and post therapy will be presented, aiming to support the role of this novel technology in diagnosing and monitoring disease status in patients with FL and DLBCL.