Contributions
Abstract: EP959
Type: E-Poster Presentation
Session title: Myeloma and other monoclonal gammopathies - Biology & Translational Research
Background
Multiple myeloma bone disease (MMBD) affects approximately 80% of newly diagnosed multiple myeloma (MM) patients and is associated with poor quality of life and worse survival. The pathophysiology of MMBD is complex and results from deregulation of bone remodeling. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at post-transcriptional and/or translational level. miRNAs are implicated in the regulation of key physiological processes, including bone remodeling. However, little is known about their implication in MMBD.
Aims
The purpose of the current study was the evaluation of an established panel of 19 miRNAs associated with bone disease in osteoporosis of different etiology, in MMBD.
Methods
Small RNAs were isolated from blood plasma samples of 64 newly diagnosed MM cases, i.e. 37 patients with and 27 without osteolytic lesions, assessed via whole-body low-dose computed tomography. After RNA polyadenylation and first-strand cDNA synthesis, 19 miRNAs (let-7b-5p, miR-17-5p, miR-19b-3p, miR-29b-3p, miR-31-5p, miR-127-3p, miR-133b, miR-141-3p, miR-143-3p, miR-144-5p, miR-152-3p, miR-188-5p, miR-203a, miR-214-3p, miR-320a, miR-335-5p, miR-375, miR-550a-3p, miR-582-5p) were quantified by means of real-time qPCR, using LNA-enhanced forward and reverse primers as well as miGreen for detection. Spike-in control RNAs were used for normalization of miRNA levels. Last, biostatistical analysis was performed.
Results
Significantly lower levels of miR-143-3p (p=0.022), miR-17-5p (p=0.023), miR-214-3p (p=0.003), and miR-335-5p (p=0.018) were observed in MM patients with osteolytic lesions, compared to MM patients without osteolytic lesions. Receiver operating characteristic (ROC) curve analysis showed that each of the aforementioned miRNAs can accurately distinguish MM patients with MMBD from MM patients without MMBD: miR-17-5p (AUC=0.67; p=0.023), miR-143-3p (AUC=0.68; p=0.022), miR-214-3p (AUC=0.74; p=0.003), and miR-335-5p (AUC=0.69; p=0.018). In order to obtain a miRNA signature with higher discriminatory ability regarding MMBD, we built multivariate logistic regression models combining the levels of multiple miRNAs, selected among miR-17-5p, miR-143-3p, miR-214-3p, and miR-335-5p. The best predictive model resulted from the combination of these 4 miRNAs (function: F=0.66 x log(miR-335-5p) – 0.90 x log(miR-17-5p) – 0.44 x log(miR-143-3p) –1.67 x log(miR-143-3p) + 5.378. The evaluation of the proposed model using ROC analysis showed its significantly increased performance to successfully detect the presence of osteolytic bone disease in MM patients (AUC=0.80; p=0.001). Furthermore, a cutoff value of Fc=0.40, corresponds to increased diagnostic sensitivity of the described model (sensitivity: 96%, specificity: 53%), while a cutoff value of Fc=0.77 corresponds to increased diagnostic specificity (sensitivity: 48%, specificity: 94%).
Conclusion
Our study proposes a diagnostic model consisting of 4 miRNAs (miR-17-5p, miR-143-3p, miR-214-3p, and miR-335-5p) which and predict the occurrence of osteolytic lesions in MM patients. The suggested miRNA signature could be a useful tool able to guide therapeutic decision making, especially in ambiguous cases.
Acknowledgement: This research is co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Study of the expression of small non-coding RNAs in multiple myeloma and their correlation with bone disease.”(MIS 5047940).
Keyword(s): Bone disease, Diagnosis, Multiple myeloma, Quantitative RT-PCR
Abstract: EP959
Type: E-Poster Presentation
Session title: Myeloma and other monoclonal gammopathies - Biology & Translational Research
Background
Multiple myeloma bone disease (MMBD) affects approximately 80% of newly diagnosed multiple myeloma (MM) patients and is associated with poor quality of life and worse survival. The pathophysiology of MMBD is complex and results from deregulation of bone remodeling. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at post-transcriptional and/or translational level. miRNAs are implicated in the regulation of key physiological processes, including bone remodeling. However, little is known about their implication in MMBD.
Aims
The purpose of the current study was the evaluation of an established panel of 19 miRNAs associated with bone disease in osteoporosis of different etiology, in MMBD.
Methods
Small RNAs were isolated from blood plasma samples of 64 newly diagnosed MM cases, i.e. 37 patients with and 27 without osteolytic lesions, assessed via whole-body low-dose computed tomography. After RNA polyadenylation and first-strand cDNA synthesis, 19 miRNAs (let-7b-5p, miR-17-5p, miR-19b-3p, miR-29b-3p, miR-31-5p, miR-127-3p, miR-133b, miR-141-3p, miR-143-3p, miR-144-5p, miR-152-3p, miR-188-5p, miR-203a, miR-214-3p, miR-320a, miR-335-5p, miR-375, miR-550a-3p, miR-582-5p) were quantified by means of real-time qPCR, using LNA-enhanced forward and reverse primers as well as miGreen for detection. Spike-in control RNAs were used for normalization of miRNA levels. Last, biostatistical analysis was performed.
Results
Significantly lower levels of miR-143-3p (p=0.022), miR-17-5p (p=0.023), miR-214-3p (p=0.003), and miR-335-5p (p=0.018) were observed in MM patients with osteolytic lesions, compared to MM patients without osteolytic lesions. Receiver operating characteristic (ROC) curve analysis showed that each of the aforementioned miRNAs can accurately distinguish MM patients with MMBD from MM patients without MMBD: miR-17-5p (AUC=0.67; p=0.023), miR-143-3p (AUC=0.68; p=0.022), miR-214-3p (AUC=0.74; p=0.003), and miR-335-5p (AUC=0.69; p=0.018). In order to obtain a miRNA signature with higher discriminatory ability regarding MMBD, we built multivariate logistic regression models combining the levels of multiple miRNAs, selected among miR-17-5p, miR-143-3p, miR-214-3p, and miR-335-5p. The best predictive model resulted from the combination of these 4 miRNAs (function: F=0.66 x log(miR-335-5p) – 0.90 x log(miR-17-5p) – 0.44 x log(miR-143-3p) –1.67 x log(miR-143-3p) + 5.378. The evaluation of the proposed model using ROC analysis showed its significantly increased performance to successfully detect the presence of osteolytic bone disease in MM patients (AUC=0.80; p=0.001). Furthermore, a cutoff value of Fc=0.40, corresponds to increased diagnostic sensitivity of the described model (sensitivity: 96%, specificity: 53%), while a cutoff value of Fc=0.77 corresponds to increased diagnostic specificity (sensitivity: 48%, specificity: 94%).
Conclusion
Our study proposes a diagnostic model consisting of 4 miRNAs (miR-17-5p, miR-143-3p, miR-214-3p, and miR-335-5p) which and predict the occurrence of osteolytic lesions in MM patients. The suggested miRNA signature could be a useful tool able to guide therapeutic decision making, especially in ambiguous cases.
Acknowledgement: This research is co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Study of the expression of small non-coding RNAs in multiple myeloma and their correlation with bone disease.”(MIS 5047940).
Keyword(s): Bone disease, Diagnosis, Multiple myeloma, Quantitative RT-PCR