0000000000064059
AUTHOR
Maria-jose Calasanz
Transcriptional profiling of circulating tumor cells in multiple myeloma: a new model to understand disease dissemination
The reason why a few myeloma cells egress from the bone marrow (BM) into peripheral blood (PB) remains unknown. Here, we investigated molecular hallmarks of circulating tumor cells (CTCs) to identify the events leading to myeloma trafficking into the bloodstream. After using next-generation flow to isolate matched CTCs and BM tumor cells from 32 patients, we found high correlation in gene expression at single-cell and bulk levels (r ≥ 0.94, P = 10−16), with only 55 genes differentially expressed between CTCs and BM tumor cells. CTCs overexpressed genes involved in inflammation, hypoxia, or epithelial–mesenchymal transition, whereas genes related with proliferation were downregulated in CTCs…
Measurable Residual Disease by Next-Generation Flow Cytometry in Multiple Myeloma.
[Purpose] Assessing measurable residual disease (MRD) has become standard with many tumors, but the clinical meaning of MRD in multiple myeloma (MM) remains uncertain, particularly when assessed by next-generation flow (NGF) cytometry. Thus, we aimed to determine the applicability and sensitivity of the flow MRD-negative criterion defined by the International Myeloma Working Group (IMWG).
Biological and clinical significance of dysplastic hematopoiesis in patients with newly diagnosed multiple myeloma
On behalf of the PETHEMA/GEM Cooperative Group.
Prognostic heterogeneity of adult B-cell precursor acute lymphoblastic leukaemia patients with t(1;19)(q23;p13)/TCF3-PBX1 treated with measurable residual disease-oriented protocols.
Programa para el Tratamiento de Hemopatias Malignas (PETHEMA) Group (Spanish Society of Hematology, SEHH).
Deep MRD profiling defines outcome and unveils different modes of treatment resistance in standard- and high-risk myeloma
PETHEMA/GEM Cooperative Group.
Preneoplastic somatic mutations including MYD88(L265P) in lymphoplasmacytic lymphoma
Normal cell counterparts of solid and myeloid tumors accumulate mutations years before disease onset; whether this occurs in B lymphocytes before lymphoma remains uncertain. We sequenced multiple stages of the B lineage in elderly individuals and patients with lymphoplasmacytic lymphoma, a singular disease for studying lymphomagenesis because of the high prevalence of mutated MYD88 . We observed similar accumulation of random mutations in B lineages from both cohorts and unexpectedly found MYD88 L265P in normal precursor and mature B lymphocytes from patients with lymphoma. We uncovered genetic and transcriptional pathways driving malignant transformation and leveraged these to model lymph…
Role of MTHFR (677, 1298) haplotype in the risk of developing secondary leukemia after treatment of breast cancer and hematological malignancies
Therapy-related myelodysplasia and acute myeloid leukemia (t-MDS/AML) is a malignancy occurring after exposure to chemotherapy and/or radiotherapy. Polymorphisms involved in chemotherapy/radiotherapy response genes could be related to an increased risk of developing this neoplasia. We have studied 11 polymorphisms in genes of drug detoxification pathways (NQO1, glutathione S-transferase pi) and DNA repair xeroderma pigmentosum, complementation group (3) (XPC(3), X-ray repair cross complementing protein (1)), Nijmegen breakage syndrome (1), excision repair cross-complementing rodent repair deficiency, complementation group (5) and X-ray repair cross complementing protein (3) and in the methy…
A machine learning model based on tumor and immune biomarkers to predict undetectable MRD and survival outcomes in multiple myeloma
Abstract Purpose: Undetectable measurable residual disease (MRD) is a surrogate of prolonged survival in multiple myeloma. Thus, treatment individualization based on the probability of a patient achieving undetectable MRD with a singular regimen could represent a new concept toward personalized treatment, with fast assessment of its success. This has never been investigated; therefore, we sought to define a machine learning model to predict undetectable MRD at the onset of multiple myeloma. Experimental Design: This study included 487 newly diagnosed patients with multiple myeloma. The training (n = 152) and internal validation cohorts (n = 149) consisted of 301 transplant-eligible patients…