Improved early outcome prediction by MRI-based 3D tumor volume assessment in patients with CNS lymphomas.

BACKGROUND: Central nervous system lymphomas (CNSL) display remarkable clinical heterogeneity, yet accurate prediction of outcomes remains challenging. The IPCG criteria are widely used in routine practice for the assessment of treatment response. However, the value of the IPCG criteria for ultimate outcome prediction is largely unclear, mainly due to the uncertainty in delineating complete from partial responses during and after treatment. METHODS: We explored various MRI features including semi-automated 3D tumor volume measurements at different disease milestones and their association with survival in 93 CNSL patients undergoing curative-intent treatment. RESULTS: At diagnosis, patients with more than 3 lymphoma lesions, periventricular involvement, and high 3D tumor volumes showed significantly unfavorable PFS and OS. At first interim MRI during treatment, the IPCG criteria failed to discriminate outcomes in responding patients. Therefore, we randomized these patients into training and validation cohorts to investigate whether 3D tumor volumetry could improve outcome prediction. We identified a 3D tumor volume reduction of ≥97% as the optimal threshold for risk stratification (=3D early response, 3D_ER). Applied to the validation cohort, patients achieving 3D_ER had significantly superior outcomes. In multivariate analyses, 3D_ER was independently prognostic of PFS and OS. Finally, we leveraged prognostic information from 3D MRI features and circulating biomarkers to build a composite metric that further improved outcome prediction in CNSL. CONCLUSIONS: We developed semi-automated 3D tumor volume measurements as strong and independent early predictors of clinical outcomes in CNSL patients. These radiologic features could help improve risk stratification and help guide future treatment approaches.

Clinical applications of circulating tumor DNA in central nervous system lymphoma.

Detection and characterization of circulating tumor DNA (ctDNA) in body fluids have the potential to revolutionize management of patients with lymphoma. Minimal access to malignant DNA through a simple blood draw or lumbar puncture is particularly appealing for CNS lymphomas (CNSL), which cannot be easily or repeatedly sampled without invasive surgeries. Profiling of ctDNA provides a real-time snapshot of the genetic composition in patients with CNSL and enables ultrasensitive quantification of lymphoma burden at any given time point during the course of the disease. Here, we broadly review technical challenges of ctDNA identification in CNSL, recent advances of innovative liquid biopsy technologies, potential clinical applications of ctDNA and how it may improve CNSL risk stratification, outcome prediction, and monitoring of measurable residual disease. Finally, we discuss clinical trials and scenarios in which ctDNA could be implemented to guide risk-adapted and personalized treatment decisions.

Circulating Tumor DNA Profiling for Detection, Risk Stratification, and Classification of Brain Lymphomas.

PURPOSE: Clinical outcomes of patients with CNS lymphomas (CNSLs) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure is challenging. Furthermore, CNSL diagnosis often remains unconfirmed because of contraindications for invasive stereotactic biopsies. Therefore, improved biomarkers are needed to better stratify patients into risk groups, predict treatment response, and noninvasively identify CNSL. PATIENTS AND METHODS: We explored the value of circulating tumor DNA (ctDNA) for early outcome prediction, measurable residual disease monitoring, and surgery-free CNSL identification by applying ultrasensitive targeted next-generation sequencing to a total of 306 tumor, plasma, and CSF specimens from 136 patients with brain cancers, including 92 patients with CNSL. RESULTS: Before therapy, ctDNA was detectable in 78% of plasma and 100% of CSF samples. Patients with positive ctDNA in pretreatment plasma had significantly shorter progression-free survival (PFS, P < .0001, log-rank test) and overall survival (OS, P = .0001, log-rank test). In multivariate analyses including established clinical and radiographic risk factors, pretreatment plasma ctDNA concentrations were independently prognostic of clinical outcomes (PFS HR, 1.4; 95% CI, 1.0 to 1.9; P = .03; OS HR, 1.6; 95% CI, 1.1 to 2.2; P = .006). Moreover, measurable residual disease detection by plasma ctDNA monitoring during treatment identified patients with particularly poor prognosis following curative-intent immunochemotherapy (PFS, P = .0002; OS, P = .004, log-rank test). Finally, we developed a proof-of-principle machine learning approach for biopsy-free CNSL identification from ctDNA, showing sensitivities of 59% (CSF) and 25% (plasma) with high positive predictive value. CONCLUSION: We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings highlight the role of ctDNA as a noninvasive biomarker and its potential value for personalized risk stratification and treatment guidance in patients with CNSL.[Media: see text].

Circulating tumor DNA in B-cell lymphoma: technical advances, clinical applications, and perspectives for translational research.

Noninvasive disease monitoring and risk stratification by circulating tumor DNA (ctDNA) profiling has become a potential novel strategy for patient management in B-cell lymphoma. Emerging innovative therapeutic options and an unprecedented growth in our understanding of biological and molecular factors underlying lymphoma heterogeneity have fundamentally increased the need for precision-based tools facilitating personalized and accurate disease profiling and quantification. By capturing the entire mutational landscape of tumors, ctDNA assessment has some decisive advantages over conventional tissue biopsies, which usually target only one single tumor site. Due to its non- or minimal-invasive nature, serial and repeated ctDNA profiling provides a real-time picture of the genetic composition and facilitates quantification of tumor burden any time during the course of the disease. In this review, we present a comprehensive overview of technologies used for ctDNA detection and genotyping in B-cell lymphoma, focusing on pre-analytical and technical requirements, the advantages and limitations of various approaches, and highlight recent advances around improving sensitivity and suppressing technical errors. We broadly review potential applications of ctDNA in clinical practice and for translational research by describing how ctDNA might enhance lymphoma subtype classification, treatment response assessment, outcome prediction, and monitoring of measurable residual disease. We finally discuss how ctDNA could be implemented in prospective clinical trials as a novel surrogate endpoint and be utilized as a decision-making tool to guide lymphoma treatment in the future.