0000000000020224
AUTHOR
Laura Rosinol Dachs
Single-Cell Characterization of the Multiple Myeloma (MM) Immune Microenvironment Identifies CD27-Negative T Cells As Potential Source of Tumor-Reactive Lymphocytes
Background: The broad use of immunomodulatory drugs (IMiDs) and the breakthrough of novel immunotherapies in MM, urge the optimization of immune monitoring to help tailoring treatment based on better prediction of patients' response according to their immune status. For example, current T cells immune monitoring is of limited value because the phenotype of tumor-reactive T cells is uncertain. Aims: To characterize the MM immune microenvironment at the single-cell level and to identify clinically relevant subsets for effective immune monitoring. Methods: We used a semi-automated pipeline to unveil full cellular diversity based on unbiased clustering, in a large flow cytometry dataset of 86 n…
Randomized Trial of Lenalidomide and Dexamethasone Versus Clarythromycin, Lenalidomide and Dexamethasone As First Line Treatment in Patients with Multiple Myeloma Not Candidates for Autologous Stem Cell Transplantation: Results of the GEM-Claridex Clinical Trial
Continuous treatment with lenalidomide (R) and dexamethasone (d) is a standard of care for multiple myeloma (MM) patients (pts) not candidates for autologous stem cell transplantation (ASCT). As previously reported, the addition of Clarithromycin (C) to Rd has proven to be safe and effective, and case-control analyses suggested a significant additive value with the combination. C optimizes the therapeutic effect of glucocorticoids by increasing the area under the curve, has immunomodulatory effects and may have direct antineoplastic properties. However, there are not randomized phase III trials confirming these results. GEM-Claridex in an open, randomized, phase III trial for untreated new…
FlowCT for the analysis of large immunophenotypic data sets and biomarker discovery in cancer immunology
Key Points FlowCT is a new computational workspace for unveiling cellular diversity and objectively identifying biomarkers in large immune monitoring studies.FlowCT identified T-cell biomarkers predictive of malignant transformation and survival in SMM and active MM data sets.