Centrosome amplification and clonal evolution in multiple myeloma: Short review

Association between diabetes and acute lymphocytic leukemia, acute myeloid leukemia, non-Hopkin lymphoma, and multiple myeloma

Objective

Diabetes increases the risk for cancers. However, whether it is associated with hematologic malignancies is not clear. The present study investigated the association between diabetes and acute lymphocytic leukemia (ALL), acute myeloid leukemia (ML), non-Hopkin lymphoma (NHL), and multiple myeloma (MM).

Methods

Newly diagnosed adult cancer patients were recruited consecutively from our clinical database. Peoples from a local enterprise were recruited to create a small-scale population-based dataset. We compared the diabetes prevalence between the cancer patients and the local people; an increase in diabetes prevalence in the cancer patients suggests an association between diabetes and the cancer(s).

Results

We found that the prevalence of diabetes was 19.7%, 21.3%, 12.5%, and 12.0% in ALL, AML, NHL, and MM, respectively, which was higher than that (9.1%) in the local people. Despite that there were more male than female cancer patients, there were more female than male diabetic patients. The increase in diabetes prevalence occurred in ALL and NHL patients aged 18 to 39 years old as well as in AML patients over 40. In MM patients, the increase in diabetes prevalence (18.6%) occurred only in females. Approximately 70% of the diabetic patients were undiagnosed before the diagnosis of the blood cancer. Approximately half of the pre-existing diabetic patients had anti-diabetic treatment, with over 70% of them still had poor glycemic control.

Conclusions

Our results suggest that diabetes is associated with ALL, AML, NHL, and MM, at least in adult patients.

Multiple Myeloma: Personalised Medicine Based on Pathogenesis

Multiple myeloma is increasingly being recognised as more than one disease, characterised by marked cytogenetic, molecular, and proliferative heterogeneity. The prognosis is widely varied, ranging from low to very high-risk, based on cytogenetic and molecular studies. Although novel agents, such as proteasome inhibitors and immunomodulators, have been developed, which have improved treatment responses and disease prognosis, multiple myeloma remains an incurable disease. Based on highly sensitive detection tools, such as gene expression profiling and next generation sequence analysis, and the understanding of the pathogenesis of multiple myeloma, many potential agents, including monoclonal antibodies, drug-conjugated antibodies, drugs targeted to molecular abnormalities, microRNA inhibitors or mimics, and immune therapies, such as chimeric antigen receptors T cells and anti-PD1 agents, can be considered personalised therapies. In this paper, multiple myeloma pathogenesis and potential molecular and immunotherapies are reviewed.

Centrosome associated genes pattern for risk sub-stratification in multiple myeloma

Background

The genome of multiple myeloma (MM) cells is extremely unstable, characterized by a complex combination of structure and numerical abnormalities. It seems that there are several “myeloma subgroups” which differ in expression profile, clinical manifestations, prognoses and treatment response. In our previous work, the list of 35 candidate genes with a known role in carcinogenesis and associated with centrosome structure/function was used as a display of molecular heterogeneity with an impact in myeloma pathogenesis. The current study was devoted to establish a risk stratification model based on the aforementioned candidate genes.

Methods

A total of 151 patients were included in this study. CD138+ cells were separated by magnetic-activated cell sorting (MACS). Gene expression profiling (GEP) and Interphase FISH with cytoplasmic immunoglobulin light chain staining (cIg FISH) were performed on plasma cells (PCs). All statistical analyses were performed using freeware R and its additional packages. Training and validation cohort includes 73 and 78 patients, respectively.

Results

We have finally established a model that includes 12 selected genes (centrosome associated gene pattern, CAGP) which appears to be an independent prognostic factor for MM stratification. We have shown that the new CAGP model can sub-stratify prognosis in patients without TP53 loss as well as in IMWG high risk patients’ group.

Conclusions

We assume that newly established risk stratification model complements the current prognostic panel used in multiple myeloma and refines the classification of patients in relation to the disease risks. This approach can be used independently as well as in combination with other factors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-0906-9) contains supplementary material, which is available to authorized users.