Serum proteome modulations upon treatment provides biological insight on response to treatment in relapsed mantle cell lymphoma

BackgroundThe possibility to monitor patient's serum proteome during treatment can provide deepened understanding of the biology associated with response to specific drugs. Non-invasive serum sampling provides an opportunity for sustainable repetitive sampling of patients, which allows for more frequent evaluation of the biological response and enhanced flexibility in treatment selection in contrast to tissue biopsies.AimTo pin-point biologically relevant changes in pre- and on-treatment serum proteome samples in relapsed mantle cell lymphoma (MCL) patients, leading to insight into mechanisms behind response to treatment in sub-groups of patients.MethodsPre- and on-treatment serum samples from relapsed MCL patients treated with a triple combination therapy of rituximab, ibrutinib and lenalidomide were available for the study, together with detailed clinicopathological information. A microarray technology targeting 158 serum proteins using 371 antibody-fragments was used to compare the serum proteome at the two time-points.ResultsProteins modulated by the treatment were shown to be associated to a MCL sub-group with ATM/TP53 alterations, which emphasizes the importance of treatment stratification. Absolute values of serum protein levels in on-treatment samples were highly variable and showed no correlation to outcome. To circumvent the challenge of variability in absolute serum protein levels, the velocity of change of individual serum proteins was used to identify proteins associated with clinical response. Increased values of TGF-β1, CD40 and complement component 4 comparing pre- and on-treatment samples were associated with remaining minimal residual disease (MRD) and increased BTK was associated with short progression-free survival (PFS).ConclusionWe show that the genetic sub-type of MCL affects the biological response to treatment in serum and that the change in defined serum proteins reveals the biology associated with clinical response.