Carlos Palacio

In chronic lymphocytic leukemia (CLL) the level of minimal residual disease (MRD) after therapy is an independent predictor of outcome. Given the increasing number of new agents being explored for CLL therapy, using MRD as a surrogate could greatly reduce the time necessary to assess their efficacy. In this European Research Initiative on CLL (ERIC) project we have identified and validated a flow-cytometric approach to reliably quantitate CLL cells to the level of 0.0010% (10(-5)). The assay comprises a core panel of six markers (i.e. CD19, CD20, CD5, CD43, CD79b and CD81) with a component specification independent of instrument and reagents, which can be locally re-validated using normal peripheral blood. This method is directly comparable to previous ERIC-designed assays and also provides a backbone for investigation of new markers. A parallel analysis of high-throughput sequencing using the ClonoSEQ assay showed good concordance with flow cytometry results at the 0.010% (10(-4)) level, the MRD threshold defined in the 2008 International Workshop on CLL guidelines, but it also provides good linearity to a detection limit of 1 in a million (10(-6)). The combination of both technologies would permit a highly sensitive approach to MRD detection while providing a reproducible and broadly accessible method to quantify residual disease and optimize treatment in CLL.

The levels of cell free circulating tumor DNA (ctDNA) in plasma correlated with treatment response and outcome in systemic lymphomas. Notably, in brain tumors, the levels of ctDNA in the cerebrospinal fluid (CSF) are higher than in plasma. Nevertheless, their role in central nervous system (CNS) lymphomas remains elusive. We evaluated the CSF and plasma from 19 patients: 6 restricted CNS lymphomas, 1 systemic and CNS lymphoma, and 12 systemic lymphomas. We performed whole exome sequencing or targeted sequencing to identify somatic mutations of the primary tumor, then variant-specific droplet digital PCR was designed for each mutation. At time of enrolment, we found ctDNA in the CSF of all patients with restricted CNS lymphoma but not in patients with systemic lymphoma without CNS involvement. Conversely, plasma ctDNA was detected in only 2/6 patients with restricted CNS lymphoma with lower variant allele frequencies than CSF ctDNA. Moreover, we detected CSF ctDNA in 1 patient with CNS lymphoma in complete remission and in 1 patient with systemic lymphoma, 3 and 8 months before CNS relapse was confirmed; indicating CSF ctDNA might detect CNS relapse earlier than conventional methods. Finally, in 2 cases with CNS lymphoma, CSF ctDNA was still detected after treatment even though a complete decrease in CSF tumor cells was observed by flow cytometry (FC), indicating CSF ctDNA better detected residual disease than FC. In conclusion, CSF ctDNA can better detect CNS lesions than plasma ctDNA and FC. In addition, CSF ctDNA predicted CNS relapse in CNS and systemic lymphomas.

BACKGROUND: TNF alpha blockade agents like infliximab are actually the treatment of choice for those rheumatoid arthritis (RA) patients who fail standard therapy. However, a considerable percentage of anti-TNF alpha treated patients do not show a significant clinical response. Given that new therapies for treatment of RA have been recently approved, there is a pressing need to find a system that reliably predicts treatment response. We hypothesized that the analysis of whole blood gene expression profiles of RA patients could be used to build a robust predictor to infliximab therapy. METHODS AND FINDINGS: We performed microarray gene expression analysis on whole blood RNA samples from RA patients starting infliximab therapy (n = 44). The clinical response to infliximab was determined at week 14 using the EULAR criteria. Blood cell populations were determined using flow cytometry at baseline, week 2 and week 14 of treatment. Using complete cross-validation and repeated random sampling we identified a robust 8-gene predictor model (96.6% Leave One Out prediction accuracy, P = 0.0001). Applying this model to an independent validation set of RA patients, we estimated an 85.7% prediction accuracy (75-100%, 95% CI). In parallel, we also observed a significantly higher number of CD4+CD25+ cells (i.e. regulatory T cells) in the responder group compared to the non responder group at baseline (P = 0.0009). CONCLUSIONS: The present 8-gene model obtained from whole blood expression efficiently predicts response to infliximab in RA patients. The application of the present system in the clinical setting could assist the clinician in the selection of the optimal treatment strategy in RA.

BACKGROUND: The presence of minimal residual disease detected by polymerase chain reaction techniques prior to allogeneic hematopoietic stem cell transplantation has proven to be an independent prognostic factor for poor outcome in children with acute lymphoblastic leukemia. DESIGN AND METHODS: The aim of this study was to ascertain whether the presence of minimal residual disease detected by multiparametric flow cytometry prior to allogeneic hematopoietic stem cell transplantation is related to outcome in children acute lymphoblastic leukemia. Minimal residual disease was quantified by multiparametric flow cytometry at a median of 10 days prior to hematopoietic stem cell transplantation in 31 children (age range, 10 months to 16 years) with acute lymphoblastic leukemia. Thirteen patients were transplanted in first remission. Stem cell donors were HLA-identical siblings in 8 cases and matched unrelated donors in 23. Twenty-six children received a total body irradiation-containing conditioning regimen. According to the level of minimal residual disease, patients were divided into two groups: minimal residual disease-positive (>or=0.01%) (n=10) and minimal residual disease-negative (<0.01%) (n=21). RESULTS: Estimated event-free survival rates at 2 years for the minimal residual disease-negative and -positive subgroups were 74% and 20%, respectively (P=0.004) and overall survival rates were 80% and 20%, respectively (P=0.005). Bivariate analysis identified pre-transplant minimal residual disease as the only significant factor for relapse and also for death (P<0.01). CONCLUSIONS: The presence of minimal residual disease measured by multiparametric flow cytometry identified a group of patients with a 9.5-fold higher risk of relapse and a 3.2-fold higher risk of death than those without minimal residual disease. This study supports the strong relationship between pre-transplantation minimal residual disease measured by multiparametric flow cytometry and outcome following allogeneic hematopoietic stem cell transplantation and concur with the results of previous studies using polymerase chain reaction techniques.