Prospective study to assess treatment response and predict patient prognosis by a blood-based multi-omics assay in lymphoma patients.

Abstract

116 Background: Lymphoma represents a diverse group of cancer that arises from clonal proliferation of lymphocytes. Clinical existing imaging and biomarkers do not reliably predict treatment response across diverse lymphoma subtypes and treatment regimens. Only rare data show circulating tumor DNA (ctDNA) testing may perform as a good predictive biomarker for assessment of therapeutic response. We conducted a prospective study to assess treatment response and predict patient prognosis via our multi-omics assay (SeekInClarity) in lymphoma patients. Methods: SeekInClarity assay utilized common 7 protein tumor markers (PTMs) and cancer genomic hallmarks: copy number aberration (CNA) and fragment size (FS), which were analyzed by shallow whole genome sequencing, to calculate the molecular tumor burden (MTB) score. 8ml peripheral blood samples were collected from patients before and after every 2 cycles of treatment respectively, meanwhile, samples from a part of patients after 1 cycle of treatment were also collected. Results: Before treatment, 95 out of 133 patients (71.4%) were succeeded in detecting cancer signals with higher MTB scores (defined as baseline+). The proportion of patients with baseline+ was higher in patients with higher tumor stages. After 2 cycles of treatment, 39 out of 112 patients had a higher MTB score (defined as MRD+). The proportion of patients with progression in MRD+ group was significantly higher than that in MRD- group (p<0.001). Meanwhile, MRD+ patients had a worse PFS than MRD- patients (p <0.0001, HR: 26.4, 95% CI:8.7~80.3), regardless of tumor stages, lymphoma subtypes and treatment regimens. Among baseline+ patients, after 2 cycles of treatment the patients with MTB score decrease had a better PFS than that with MTB score increase (P<0.001, HR: 7.5 95% CI:0.7~76.7). Among the baseline- group, patients who remained negative after treatment had extremely well PFS (100% PFS). As for the patients after 1 cycle of treatment, MTB value has a good concordance with that after 2 cycles of treatment which demonstrated a lead time in monitoring treatment response. 54 patients with longitudinal monitoring samples, 9(16.7%) patients were always MRD- during the treatment, who had the best PFS (100% PFS), regardless of baseline status. 11 out of 54 patients with always MRD+ had the worst PFS (p < 0.05). Conclusions: This study demonstrates the clinical utility of multidimensional blood-based SeekInClarity assay in pan-cancer/pan-indication treatment response assessment and patient prognosis. After treatment, the dynamic change of MTB score and MRD status were independently associated with patient’s PFS, which indicated both could be used as biomarkers to predict the effectiveness of treatment. Compared with clinical image evaluation after 2 cycles of treatment, SeekInClarity test after 1 cycle of treatment is sufficient to assess treatment response.