Towards Stratified Medicine in Plasma Cell Myeloma

Abstract

Plasma cell myeloma is a clinically heterogeneous malignancy accounting for approximately one to 2% of newly diagnosed cases of cancer worldwide. Treatment options, in addition to long-established cytotoxic drugs, include autologous stem cell transplant, immune modulators, proteasome inhibitors and monoclonal antibodies, plus further targeted therapies currently in clinical trials. Whilst treatment decisions are mostly based on a patient’s age, fitness, including the presence of co-morbidities, and tumour burden, significant scope exists for better risk stratification, sub-classification of disease, and predictors of response to specific therapies. Clinical staging, recurring acquired cytogenetic aberrations, and serum biomarkers such as β-2 microglobulin, and free light chains are in widespread use but often fail to predict the disease progression or inform treatment decision making. Recent scientific advances have provided considerable insight into the biology of myeloma. For example, gene expression profiling is already making a contribution to enhanced understanding of the biology of the disease whilst Next Generation Sequencing has revealed great genomic complexity and heterogeneity. Pathways involved in the oncogenesis, proliferation of the tumour and its resistance to apoptosis are being unravelled. Furthermore, knowledge of the tumour cell surface and its interactions with bystander cells and the bone marrow stroma enhance this understanding and provide novel targets for cell and antibody-based therapies. This review will discuss the development in understanding of the biology of the tumour cell and its environment in the bone marrow, the implementation of new therapeutic options contributing to significantly improved outcomes, and the progression towards more personalised medicine in this disorder.

Efficacy and safety profile of deep responders to carfilzomib-based therapy: a subgroup analysis from ASPIRE and ENDEAVOR

“…Given the number of agents now approved for the treatment of RRMM, treatment decisions are becoming increasingly complex [ 7 , 21 – 24 ]. While the choice of treatment regimen at relapse typically takes account of patient, disease and treatment characteristics (e.g., performance status, comorbidities, tumor burden, cytogenetics, previous treatment responses and toxicities), there is no validated strategy for the identification of patients who are likely to respond well to a given treatment at relapse [ 23 , 25 – 28 ]. Factors such as cytogenetics, serum albumin, serum lactate dehydrogenase (LDH) and β2-microglobulin are established prognostic variables in patients with newly diagnosed MM; however, the role of these factors in predicting prognosis in RRMM has been less well studied [ 25 – 32 ].…”

“…While the choice of treatment regimen at relapse typically takes account of patient, disease and treatment characteristics (e.g., performance status, comorbidities, tumor burden, cytogenetics, previous treatment responses and toxicities), there is no validated strategy for the identification of patients who are likely to respond well to a given treatment at relapse [ 23 , 25 – 28 ]. Factors such as cytogenetics, serum albumin, serum lactate dehydrogenase (LDH) and β2-microglobulin are established prognostic variables in patients with newly diagnosed MM; however, the role of these factors in predicting prognosis in RRMM has been less well studied [ 25 – 32 ]. Recently, a risk stratification algorithm has been developed to help physicians predict survival outcomes in patients starting second-line treatment, which incorporates 16 predictors relating to patient frailty and disease aggressiveness at diagnosis and following first-line treatment [ 33 ].…”

Splice-disrupt genomic variants in prostate cancer

“…B Gene interaction network of CYP2D6, the target gene of rs1800716 variant with the other genes. Mined references underpinning the literature-mining network of rs1800716 is presented in Supplementary 8 has been suggested that PTPRC, as an adhesion molecule, is involved in the spread of the tumour and immortalisation of the tumour cells during malignancy [52]. In gastric cancer, it has been shown that CTSF is involved in the growth and apoptosis where CTSF knockdown promotes proliferation by inhibiting apoptosis [53].…”

Roles of miRNA dysregulation in the pathogenesis of multiple myeloma

“…They found that inhibition of miR-21 significantly impaired cell viability and blocked clonogenic growth of MM cells in stroma-free conditions [24]. Reportedly, expression of some miRNAs, including miR-223, miR-16, miR-519d, and miR-485-5p were found highly expressed in MM-BMSCs compared to normal counterparts [25]. In addition, it was confirmed that upregulation of miR-29b in the bone marrow microenvironment can impair osteoclast differentiation and impede osteoclast activation induced by MM cells [26].…”