Dataset Information

Understanding the hypoxic niche of multiple myeloma: therapeutic implications and contributions of mouse models.

ABSTRACT: Multiple myeloma (MM) is the second most common hematological malignancy and is characterized by the clonal expansion of plasma cells in the bone marrow. Recently, hypoxia has received increased interest in the context of MM, in both basic and translational research. In this review, we describe the discovery of the hypoxic niche in MM and how it can be targeted therapeutically. We also discuss mouse models that closely mimic human MM, highlighting those that allow preclinical research into new therapies that exploit the hypoxic niche in MM.

SUBMITTER: Hu J

PROVIDER: S-EPMC3484859 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Understanding the hypoxic niche of multiple myeloma: therapeutic implications and contributions of mouse models.

Hu Jinsong J Van Valckenborgh Els E Menu Eline E De Bruyne Elke E Vanderkerken Karin K

Disease models & mechanisms 20121101 6

Multiple myeloma (MM) is the second most common hematological malignancy and is characterized by the clonal expansion of plasma cells in the bone marrow. Recently, hypoxia has received increased interest in the context of MM, in both basic and translational research. In this review, we describe the discovery of the hypoxic niche in MM and how it can be targeted therapeutically. We also discuss mouse models that closely mimic human MM, highlighting those that allow preclinical research into new t ...[more]

PMID: 23115205

Similar Datasets

Project description:BackgroundWith the rapid development of next-generation sequencing (NGS) technologies, researchers are making efforts to reveal the genomic landscape of multiple myeloma (MM). However, the clinical significance of many mutations remains poorly defined due to the genetic heterogeneity of MM. To systematically explore the clinical implications of gene mutations and build practical prognostic models, we performed DNA sequencing in newly diagnosed MM patients.MethodsMM cells were purified from bone marrow aspirates using CD138 microbeads and subjected to sequencing with a 387-gene Panel. Nomogram was developed using Cox's proportional hazards model, and candidate variables were screened by stepwise regression. Internal validation was carried out by the bootstrap method.ResultsBetween July 2016 and December 2020, a total of 147 patients were included in our study. We found patients with a higher mutational load had a significantly shorter progress-free survival (PFS) (19.0 vs. 32.0 months, P = 0.0098) and overall survival (OS) (3-year OS rates were 66.1% and 80.0%, P = 0.0290). Mutations in chromatin regulators (CRs) including KMT2C (14.3%), KMT2D (14.3%), EP300 (11.6%) and ARID gene family (31.3%) were highly frequent in newly diagnosed MM patients. Interestingly, proteins encoded by these genes could form a complex called KMT2C/D COMPASS (KCDCOMs). Patients with mutations of ARID gene family had a significantly shorter PFS (15.5 vs. 34.0 months, P = 0.0003) and OS (3-year OS rates were 64.9% and 81.0%, P = 0.0351) than patients without ARID gene mutations. Incorporating ARID gene mutations into the current staging system could successfully improve their prognostic performance. The PFS and OS nomogram models (including 1q21 copies, ARID gene mutations, extramedullary disease, mutational load and TP53 mutations) showed good predicting performance in both training and validation sets.ConclusionOur findings emphasized the importance of CRs mutations in newly diagnosed MM patients and indicated the mutations affecting KCDCOMs might promote the development of MM. High mutational load and harboring mutations in the ARID gene family were novel predictors of adverse prognosis in MM. Prognostic models based on gene mutations were commendably prognostic evaluation methods that could provide a reference for clinical practices.

Dataset Information

Understanding the hypoxic niche of multiple myeloma: therapeutic implications and contributions of mouse models.

Publications

Understanding the hypoxic niche of multiple myeloma: therapeutic implications and contributions of mouse models.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets