Introduction
Multiple myeloma (MM) is a clonally B cell malignancy and is described by the accumulation of malignant plasma cells in the bone marrow, the presence of a monoclonal immunoglobulin in the serum and/or urine, lytic bone lesions, frequent anemia, and renal impairment (1-3). The progression of MM begins as monoclonal gammopathy of undetermined significance (MGUS), progresses to smoldering myeloma, and becomes eventually (symptomatic) myeloma (4,5). MM accounts for approximately 10% of hematological malignancies (6). MM predominantly affects 71% of patients diagnosed at age 65 years and over (7).
MM is still considered an incurable malignancy (8). MM is a heterogeneous disease with different clinical outcomes, chromosomal aberrations, and molecular characteristics. The cause of MM has not yet been identified. Further knowledge of the biological events underlying the development of MM is needed to determine new biomarkers. Interactions of MM cells especially with mesenchymal stromal cells and osteoclasts cause activation of multiple cellular signaling pathways on myeloma cells (PI3K/AKT, JAK/STAT3, RAS/RAF/MAPK/ERK, NFκB) which support their proliferation, survival, migration and even resistance to therapeutic agents (5,9).
We aimed to determine the intracellular pathways involved in the pathogenesis of the disease with changing expression of the identified genes in insulin signaling pathway and ErbB signaling pathway in MM patients.
Methods
Patients
In this study, we included 17 patients (11 males, 6 females) aged 51-74 years who was diagnosed with MM according to the International Myeloma Working Group diagnostic criteria and Durie-Salmon criteria. The study was approved by the local Ethics Committee of İstanbul Faculty of Medicine, İstanbul University (No: 2014/927), and all patients provided informed consent in accordance with the Declaration of Helsinki.
Real-Time Reverse Transcription-Polymerase Chain Reaction
Total RNA was isolated from bone marrow using the RNeasy Mini kit (Qiagen Venlo, Netherlands) and RNA samples were quantified using a NanoDrop® ND-2000 spectrophotometer. Total RNA was reverse transcribed into total cDNA with the cDNA Synthesis Kit (Thermo Fisher Scientific, Wilmington, Delaware, USA). Gene expression analysis was performed by quantitative reverse transcription (qRT)-polymerase chain reaction (PCR) (LightCycler 480 II, Roche, Germany).
The PCR reaction started with a denaturation step at 95°C for 10 minutes (1 cycle), followed by 45 cycles at 95°C for 15 seconds, 60°C for 60 seconds and 60°C for 1 second. Subsequently, a melting curve program was applied with continuous fluorescence measurement. A standard curve for genes templates was generated through four times dilution of PCR products and the β-actin gene was used as reference for normalization of the gene expression levels. Each reaction was performed in duplicate. Designed primers are shown in Table 1.
The relative gene expression (fold change) was measured with the comparative threshold cycle (Ct) method using β-actin as housekeeping gene and the 2–ΔΔCt formula.
Statistical Analysis
In all statistical analyses, the SPSS version 13.0 was used. The threshold cycle (Ct) was determined for each sample. ΔCt indicated the difference in expression levels with the Ct value of the related gene and mean of housekeeping gene (ΔCt = Ctx gene – Cthousekeeping), and ΔΔCt indicated the difference in the ΔCt value between treatment and control groups (ΔΔCt = ΔCtES− ΔCtcontrol). The p values were calculated based on a Student’s t-test of the replicate 2−ΔCt values for each gene in the control and treatment groups. All tests were two-sided, and a p value of less than 0.05 was considered statistically significant.
Results
The average and standard deviation values of the clinical parameters of the patients are shown below (Table 2). The expression levels of genes in the ErbB and insulin signaling pathways are shown in Figure 1, 2 and Table 3.
Discussion
Currently, development of novel targeted therapies for MM is a very active area of research. Advances in molecular biological thechniques and understanding the interactions between genes in pathways related to disease pathogenesis and prognosis are expected to allow the use of new targeted therapies in the near future. Signal transduction is now considered to be the one of the key mechanisms impaired in many types of cancer. Therefore, identifying the main pathways, the genes interacting with each other in these pathways and novel prognostic markers will help not only early diagnosis of MM, but also effective treatment of this disease.
In 2002, Sukru Ozturk et al. made a project named “Comparative Gene Expression Profilling of Multiple Myeloma, Smoldering Myeloma and Monoclonal Gammopathy Undetermine Significance Caces” and found 405 fusion sequences. This project was supported by İstanbul University (Project no: 7348). These fusions were analyzed using the UCSC website (https://genome.ucsc.edu/). After that, using Venny program, we found the genes that can be related with the disease. These genes were analysed by WebGestalt database and ten pathways were detected; because of financial means, we choosed two of them. Insulin and ErbB signaling pathways, which take part especially in cell poliferation and protein synthesis, were evaluated by bioinformatics analysis.
ErbB4 is a transmembrane tyrosine kinase that regulates cell proliferation and differentiation (10). ErbB4 does not arise from hematopoietic origin, but is known to be associated with poor prognosis in endometrial cancer (11). ErbB4 gene expression levels decreases in pancreas and kidney tumors. In many studies, it has been shown that ErbB4 was overexpressed in series of breast cancer, colorectal cancer and osteosarcoma (12). In their study, Mahtouk et al. (13) reported expression of ErbB4 gene in 9 of 17 human myeloma cell lines. Also primary myeloma cells were expressed in 14 of 21 patients, and they showed that the gene was not expressed in normal plasmablastic cell and bone marrow plasma cells. In this study, ErbB4 gene was found to be nine fold upregulated in the bone marrow of MM patients.
MTOR is a molecular sensor that regulates cell proliferation, protein synthesis, and promotes cell cycle progression from G1 to S phase (14). Maiso and et al. (15) showed that MM1S, U266 and U266LR7 cell lines have low RPTOR gene expression; RAPTOR and RICTOR genes were expressed in OPM1, OPM2, MM1R, H929 and RPM18226 cell lines. In our study, we did not find a significant expression of RICTOR; we found that RAPTOR and MTOR were upregulated nine fold and five fold, respectively.
The regulation of PI3K/AKT/MTOR pathway impaired in human cancers and this affects cell survival, proliferation and metastasis. Phosphatidylinositol are messenger molecule of lipid kinases that are a subclass of the PI3Ks. PI3Ks are activated by cell membrane receptors. When PI3Ks are phosphorylated, they act as second messenger activating downstream pathways including AKT (14). PI3K/AKT signaling pathway is involved in cell survival and proliferation in various cancers. Inhibition of PI3K leads to MM cell death but overactivation leads to cell proliferation (16). In their study performed in 2013, Azab et al. (17) in 2013, they detected increased gene expression of PI3KCA in MM. Our results are consistent with the literature; we showed that PI3KCA gene expression was upregulated three fold.
The most important down-stream effector of the PI3K pathway is a protein kinase B, also known as AKT. AKT is involved in cellular processes such as cell proliferation survival and migration, glucose metabolism and transcription of genes (18,19). In a study by López-Corral et al. (20), it has been showen that AKT1 gene was more expressed in MM than in MGUS. In our study, we found that the expression of AKT1 gene increased six times.
There was no statistically significant difference in the level of GYS1 gene expression between patients and controls. It can be explained by two reasons; first GYS1 gene encodes the rate-limiting enzyme for glycogen synthesis. This catalyst function is regulated through phosphorylation by kinases. Especially the expression levels of the gene change according to stage of the disease. Second, in cardiovascular disease, GYS1 expression levels increase because GYS1 gene is expressed mostly in skeletal and cardiac muscle.
PKA is acAMP-dependent protein kinase and takes part in AKT signal transduction pathway. PKA plays a role in antilipolytic mechanism, cell growth, apoptosis and gene transcription. Recently, it has been shown that the disruption in regulation of PKA causes dysregulation of D-type cyclins including cyclin D1. Schraders et al. (21) stated that the expression of PRKACB gene decreases in half of mantle cell lymphoma tumors. The levels of cAMP are so important because of their effects on cell cycle proliferation, apoptosis and cyclin D1.
It has been shown that PKA genes subtypes had different expression levels in many types of cancer. It is upregulated in stomach cancer and breast cancer (22,23). In our study, PRKACB gene was three fold upregulated also; there has been no other study analyzing the relationship between PRKACB gene level and MM.
AKT gene is induced by PI3K which is in insulin signal pathway and is phosphorylated by PDK1/2. AKT leads to protein synthesis by phosphorylating MTOR and RAPTOR genes and induces glycogenesis by dephosphorylation of GYS and PHK genes. The RAS gene which exists in the same pathway leads to differentiation and proliferation by phosphorylating RAF, MEK and ERK1/2 genes. All these events suggest that all the genes are involved in different mechanism and they alter mRNA levels of each other. All these effects are correlated with and connected to each other. The results of our study showed that especially gene expression levels increase approximately in the same rate with each other in MM patients. The consistency of our findings supports their pathogenetic significance.
PKA which takes part in insulin signal pathway is active after phosphorylation. PRKAR2A and PRKACB are the most remarkable subtypes among the subtypes of proteins because the genes have both catalytic and regulatory functions. There are many studies showing that PRKAR2A gene is upregulated in cancer. For example; in their study performed in 2013, Bidkhori et al. (24) stated that PRKAR2A was overexpressed in lung adenocarcinoma. In their study with 29 patients performed in 2004, Neben et al. (25) found that PRKAR2A was related to centromere structure and functions. According to the cell growth results, PRKAR2A was expressed greater than two fold in AML patients. Our results are correlated with those of the study by Neben et al. (25) PRKAR2A expression increases in breast, colorectal and various human non-endocrine cancers (26) and especially in cervical cancer, and this increased expression is related with poor prognosis. In our study, we determined that PRKAR2A gene is five fold upregulated. To our knowledge, there is no study showing the relationship of this gene with MM.
Conclusion
In conclusion, insulin signaling pathway is involved in protein synthesis, gluconeogenesis and proliferation. ErbB signaling pathway is also involved in protein synthesis and cell cycle. In this study, some gene expressions which exist in insulin and ErbB signal pathways (MTOR, RPTOR, PIK3CA, AKT1, ErbB4, PRKAR2A, and PRKACB) were analyzed. There was no significant difference between the expression of GYS1 and RICTOR genes in MM patients. Especially ErbB4 and MTOR, RPTOR, PIK3CA, AKT1, PRKAR2A, PRKACB genes expression levels were found to be 3-10 times greater than in control group. Our results can be useful for explanation of the etiopathogenesis of MM.
Authorship Contributions
Surgical and Medical Practices: G.Ç., E.O., M.A., M.N.Y. Concept: Ş.Ö., D.Ü., Ş.P., K.C., E.M.C. Design: E.M.C., Ş.P., K.C. Data Collection or Processing: D.Ö., E.M.C., C.G.E. Analysis or Interpretation: E.M.C., D.Ö. Literature Search: D.Ö. Writing: D.Ö.
Conflict of Interest: No conflict of interest was declared by the authors.
Financial Disclosure: The authors declared that this study received no financial support.