0000000000676135
AUTHOR
Hervé Avet-loiseau
Longitudinal Immunogenomic Profiling of Tumor and Immune Cells for Minimally-Invasive Monitoring of Smoldering Multiple Myeloma (SMM): The Immunocell Study
Background: Although great strides were made in the management of MM, our best chances to eradicate this malignancy may lie in preventing its progression.Most current models to predict risk of transformation in SMM are commonly established at diagnosis and not reevaluated over time, because some parameters such as tumor burden or genetic abnormalities require invasive bone marrow (BM) aspirates. It could be hypothesized that periodic monitoring of tumor biomarkers is needed to improve risk-stratification of SMM patients, and so would be new minimally-invasive methods that can replace those performed in BM samples. Such methods should also monitor immune profiles, to identify patients with s…
Efficacy and safety of daratumumab, bortezomib, and dexamethasone (D-Vd) in relapsed or refractory multiple myeloma (RRMM) based on cytogenetic risk: Updated subgroup analysis of CASTOR.
8040 Background: MM patients (pts) with high cytogenetic risk have poor outcomes. In CASTOR, D-Vd prolonged progression-free survival (PFS) vs bortezomib and dexamethasone (Vd) alone, and exhibited tolerability in RRMM pts. We conducted a subgroup analysis of D-Vd vs Vd in CASTOR, based on cytogenetic risk. Methods: Pts received ≥1 prior line of therapy. Cytogenetic risk was based on a combined analysis of next-generation sequencing (NGS) and fluorescence in situ hybridization/karyotype testing. High-risk pts had t(4;14), t(14;16), or del17p abnormalities. Standard (std)-risk pts were confirmed negative for all 3 abnormalities. Minimal residual disease (MRD; 10–5) was assessed via NGS usin…
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.