204 research outputs found
Statin use in myelodysplastic syndromes is associated with a better survival and decreased progression to leukemia
Inhibition of E-Selectin (GMI-1271) or E-selectin together with CXCR4 (GMI-1359) re-sensitizes multiple myeloma to therapy
A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry
Cross center single-cell RNA sequencing study of the immune microenvironment in rapid progressing multiple myeloma
Despite advancements in understanding the pathophysiology of Multiple Myeloma (MM), the cause of rapid progressing disease in a subset of patients is still unclear. MM\u27s progression is facilitated by complex interactions with the surrounding bone marrow (BM) cells, forming a microenvironment that supports tumor growth and drug resistance. Understanding the immune microenvironment is key to identifying factors that promote rapid progression of MM. To accomplish this, we performed a multi-center single-cell RNA sequencing (scRNA-seq) study on 102,207 cells from 48 CD13
Decision-making factors for an autologous stem cell transplant for older adults with newly diagnosed multiple myeloma: A qualitative analysis
PurposeA utologous stem cell transplant (ASCT) remains a standard of care among older adults (aged ≥65) with multiple myeloma (MM). However, heterogeneity in the eligibility and utilization of ASCT remains. We identified decision-making factors that influence ASCT eligibility and utilization among older adults with MM.MethodsA qualitative study across two academic and two community centres in Ontario was conducted between July 2019-July 2020. Older adults with MM (newly diagnosed MM aged 65-75 in whom a decision had been made about ASCT in <12 months) and treating oncologists completed a baseline survey and a subsequent interview, which was analyzed using thematic analysis.ResultsEighteen patients completed the survey and 9 follow-up interviews were conducted. Patients were happy with their treatment decision with “trust in their oncologist” and “wanting the best treatment” as the most important to proceed with ASCT. “Afraid of side effects” was the most common reason for declining ASCT. Fifteen oncologists completed the survey and 10 follow-up interviews were conducted. Most relied on the ‘eye-ball’ test for ASCT eligibility over geriatric screening tools. The lack of both high-quality evidence and local guidelines impacted decision-making. Both oncologists and patients felt that chronological age alone should not affect ASCT eligibility.ConclusionWhile decision-making factors regarding ASCT can be variable, both oncologists and patients indicated that chronological age alone should not represent a barrier for ASCT among older adults. Future simplification and incorporation of ASCT eligibility geriatric assessment tools in studies as well as the inclusion of these tools in local guidelines may further improve ASCT decision-making
Validation of the Fiala multi-node thermophysiological model for UTCI application
The important requirement that COST Action 730 demanded of the physiological model to be used for the Universal Thermal Climate Index (UTCI) was its capability of accurate simulation of human thermophysiological responses across a wide range of relevant environmental conditions, such as conditions corresponding to the selection of all habitable climates and their seasonal changes, and transient conditions representing the temporal variation of outdoor conditions. In the first part of this study, available heat budget/two-node models and multi-node thermophysiological models were evaluated by direct comparison over a wide spectrum of climatic conditions. The UTCI-Fiala model predicted most reliably the average human thermal response, as shown by least deviations from physiologically plausible responses when compared to other models. In the second part of the study, this model was subjected to extensive validation using the results of human subject experiments for a range of relevant (steady-state and transient) environmental conditions. The UTCI-Fiala multi-node model proved its ability to predict adequately the human physiological response for a variety of moderate and extreme conditions represented in the COST 730 database. The mean skin and core temperatures were predicted with average root-mean-square deviations of 1.35 ± 1.00°C and 0.32 ± 0.20°C, respectivel
Comprehensive characterization of the multiple myeloma immune microenvironment using integrated scRNA-seq, CyTOF, and CITE-seq analysis
UNLABELLED: As part of the Multiple Myeloma Research Foundation (MMRF) immune atlas pilot project, we compared immune cells of multiple myeloma bone marrow samples from 18 patients assessed by single-cell RNA sequencing (scRNA-seq), mass cytometry (CyTOF), and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to understand the concordance of measurements among single-cell techniques. Cell type abundances are relatively consistent across the three approaches, while variations are observed in T cells, macrophages, and monocytes. Concordance and correlation analysis of cell type marker gene expression across different modalities highlighted the importance of choosing cell type marker genes best suited to particular modalities. By integrating data from these three assays, we found International Staging System stage 3 patients exhibited decreased CD4
SIGNIFICANCE: scRNA-seq, CyTOF, and CITE-seq are increasingly used for evaluating cellular heterogeneity. Understanding their concordances is of great interest. To date, this study is the most comprehensive examination of the measurement of the immune microenvironment in multiple myeloma using the three techniques. Moreover, we identified markers predicted to be significantly associated with multiple myeloma rapid progression
Machine learning-based scoring models to predict hematopoietic stem cell mobilization in allogeneic donors
Mobilized peripheral blood has become the primary source of hematopoietic stem cells for both autologous and allogeneic stem cell transplantation. Granulocyte colony-stimulating factor (G-CSF) is currently the standard agent used in the allogeneic setting. Despite the high mobilization efficacy in most donors, G-CSF requires 4-5 days of daily administration, and a small percentage of the donors fail to mobilize an optimal number of stem cells necessary for a safe allogeneic stem cell transplant. In this study, we retrospectively reviewed 1361 related allogeneic donors who underwent stem cell mobilization at Washington University. We compared the standard mobilization agent G-CSF with five alternative mobilization regimens, including GM-CSF, G-CSF+GM-CSF, GM-CSF + Plerixafor, Plerixafor and BL-8040. Cytokine-based mobilization strategies (G-CSF or in combination with GM-CSF) induce higher CD34 cell yield after 4-5 consecutive days of treatment, while CXCR4 antagonists (plerixafor and BL-8040) induce significantly less but rapid mobilization on the same day. Next, using a large dataset containing the demographic and baseline laboratory data from G-CSF-mobilized donors, we established machine learning (ML)-based scoring models that can be used to predict patients who may have less than optimal stem cell yields after a single leukapheresis session. To our knowledge, this is the first prediction model at the early donor screening stage, which may help identify allogeneic stem cell donors who may benefit from alternative approaches to enhance stem cell yields, thus ensuring safe and effective stem cell transplantation
A pilot study of 3D tissue‑engineered bone marrow culture as a tool to predict patient response to therapy in multiple myeloma
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