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Entirely noninvasive outcome prediction in central nervous system lymphomas using circulating tumor DNA.

Jan-Michel HegerJulia MattlenerJessica SchneiderPhilipp GödelNoëlle SiegFabian UllrichRichard Ian LewisTeodora Bucaciuc-MracicaRoland F SchwarzDaniel RueßMaximilian Ingolf RugeManuel Montesinos-RongenMartina DeckertTobias BlauNadine KutschHyatt Balke-WantJonathan WeissKerstin BeckerH Christian H ReinhardtMichael HallekPeter BorchmannBastian von TresckowSven Borchmann
Published in: Blood (2023)
State-of-the-art response assessment of central nervous system lymphoma (CNSL) by magnetic resonance imaging (MRI) is challenging and an insufficient predictor of treatment outcomes. Accordingly, the development of novel risk stratification strategies in CNSL is a high unmet medical need. We applied ultrasensitive circulating tumor (ct)DNA sequencing to 146 plasma and cerebrospinal fluid (CSF) samples from 67 patients, aiming to develop an entirely noninvasive dynamic risk model considering clinical and molecular features of CNSL. Our ultrasensitive method allowed for the detection of CNSL-derived mutations in plasma ctDNA with high concordance to CSF and tumor tissue. Undetectable plasma ctDNA at baseline was associated with favorable outcomes. We tracked tumor-specific mutations in plasma-derived ctDNA over time and developed a novel CNSL biomarker based on this information: peripheral residual disease (PRD). Persistence of PRD post-treatment was highly predictive of relapse. Integrating established baseline clinical risk factors with assessment of radiographic response and PRD during treatment resulted in the development and independent validation of a novel tool for risk stratification: Molecular prognostic index for CNSL (MOP-C). MOP-C proved to be highly predictive of outcomes in CNSL patients (failure-free survival hazard ratio (HR) per risk group 6.60; 95% confidence interval (CI) 3.12-13.97; p < 0.0001) and is publicly available at www.mop-c.com. Our results highlight the role of ctDNA sequencing in CNSL. MOP-C has the potential to improve the current standard of clinical risk stratification and radiographic response assessment in patients with CNSL, ultimately paving the way towards individualized treatment.
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