In silico analysis of CDC73 gene revealing 11 novel SNPs with possible association to Hyperparathyroidism-Jaw Tumor syndrome

Primary hyperparathyroidism (PHPT) is a disease caused by the autonomous over-secretion of parathyroid hormone (PTH) due to adenoma and hyperplasia of the parathyroid gland, furthermore it has an estimated prevalence of 6.7 per “1,000” population. The majority of PHPT cases are not inherited, while some are due to genetic mutations, it include multiple endocrine neoplasia (MEN), familial hypocalciuric hypercalcemia, neonatal severe hyperparathyroidism, familial isolated hyper parathyroidism and hyperparathy-roidism-jaw tumor (HPT-JT) syndrome (caused by mutations in the CDC73 gene) (1, 2, 3, 4, 5).

Hyperparathyroidism-jaw tumor HPT-JT (OMIM #145001) first observed by Jackson in 1958 .It is an autosomal dominant disorder with variable expression (6, 7, 8). It includes parathyroid adenomas, fibro-osseous jaw tumors, uterine tumors and renal diseases such as hamartomas, polycystic disease and Wilms tumors or adenocarcinoma. Diagnosis of HPT-JT is important because of its genetic involvement and the 24% chance of malignant transformation (9, 10). The nuclear medicine imaging - especially the scintigraphy parathyroid with 99m Tc-MIBI (methoxyisobutyl-isonitrile)- has an important role in establishing the diagnosis (11).

CDC73 -related (HPT-JT) syndrome results from truncating (80%) or missense variants in the tumor suppressor Cell Civision Cycle protein 73 (CDC73) gene (also known as HRPT-2), that is located at chromosome 1q31.2, and encodes the 531-amino acid protein parafibromin (12, 13, 14, 15, 16). this protein regulates transcriptional and post-transcriptional events. The majority of the CDC73 gene mutations related to hyperparathyroidism and parathyroid carcinoma are frame-shift, nonsense or missense occurring within the protein-encoding exons.(16) It has been estimated that 70% of patients suffering from this mutation may develop PHPT (17).

In vitro characterization studies, is a demanding approach requiring a lot a lot of resources, time, and fees. For these reasons, bioinformatics analysis is an appropriate, fast, dependable and cost effective approach to enhance our understanding of the role of mutations in the pathogenesis. Insilco or bio-informatics analysis has become an important tool in the recent years that help in the advancement of biological research through the use of different algorithms and databases (18). Many researches about the role of CDC73 gene in the development of (HPT-JT) syndrome have focused in the deletion type of mutation (5, 19, 20), yet few of them have study single nucleotides polymorphisms (SNPs). This study is unique because it is the first in silico analysis of CDC73 gene associating it with jaw tumor syndrome. Therefore, the aim of this study is to assess the effect of mutational SNPs on CDC73 gene on the structure and function of parafibromin protein using different bioinformatics tools.

Seven hundred and thirty three SNPs were downloaded from NCBI, from these only 184 SNPs were missense mutations. Firstly we analyzed the effect of the SNPs on the function of the protein using four soft wares (SIFT, PROVEAN, Polyhen2, Snap2), which result in 31 SNPs that had an effect on protein function (Table 1). Then we further analyzed them by SNPs&-GO, PHD, PMUT, I-Mutant, COSMIC and dbSNP Short Genetic Variations resulting in 11 SNPs (Table 2, 3). Finally, we studied their effect on the structure of the protein by using Hope and chimera (Fig. 2 -12). The following workflow (Fig. 1) summaries the methodology used in this paper.

Figure 1

Firstly we assess the effect of the missense SNPS on the related protein by SIFT, Polyphen2, PROVEAN and SNAP2, which resulted in 31 combined deleterious SNPS by the four soft wares, with different scores. Polyphen2 prediction shows two types of result (probably damaging prediction with 27 SNPS, and possibly damaging with four SNPs) (Table 1).

Further functional analysis was done using SNPandGO, PHD and P-Mut soft wares. The resulted predictions were varied among the soft wares with different reliability index (RI). When the combined Disease related SNPs were selected from the three software’s, we end up with only 11 SNPs. (Table 2).

In our attempt to study the effect of these eleven SNPs on the protein stability, we used I-Mutant software, which predicted that all the eleven SNPs would decrease the stability of the protein. Furthermore, we used COSMIC software to predict the possible mutation type that could result from each variant. (Some predictions were not available in the database) Then we calculated the frequency alleles of each variant independently by dbSNP Short Genetic Variations. (Some results were also unavailable in the database) (Table 3).

To study the gene-gene interactions and predict the possible function of CDC73 gene we used gene MANIA software, which shows different types of interactions (co-expression and sharing the same domain), with other genes like CTR9 and CHUK. The software also provide us with a list of possible predicted functions. (Table 4 and 5) and (Fig.13).

We used project Hope and Chimera to study the structural changes inflicted by the eleven SNPs on the parafibromin protein, we combined the two-dimensional structure we acquired from Hope reports with the three dimensional structure we designed using chimera software. (Fig. 2-12). These figures show the differences between native and mutant amino acids, in the green and red boxes the schematic structures of the native amino acids (in the left side), and the mutant ones (in the right side). In the 2D image the backbone, which is the same for each amino acid, is colored red and the side chain, unique for each amino acid, is colored black, the 3D wide-type residues colored green and mutant ones colored red, whereas the protein is colored cyan.

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It has been found that many genes with proved association to cancer, usually contain single nucleotide polymorphisms (SNPs) (33), Furthermore these disease-causing SNPs are usually found to occur at evolutionarily conserved regions. Those have essential role in the structural integrity and function of the protein (34, 35), therefore, our focus was dedicated to the coding region, which revealed 11novel mutations in CDC73 gene, out of 184-missense SNPs download from NCBI web site. These SNPs were then analyzed using twelve soft wares to study the effect of the mutation on the structural and function of the parafibromin protein.

Project hope was used to study the effect of the mutation on the physiochemical properties of the protein, where we have found changes on the charge, size and hydrophobicity of the protein illustrated in the hope report, which leads to disturbance in the interactions with other molecules. In the first substitution G49C, The mutant residue is bigger and more hydrophobic than the wild-type residue.in L63PThe mutant residue is smaller than the wild-type residue, which lead to an empty space in the core of the protein. In L64P, we also found the mutant residue is smaller than the wild-type residue, causing an empty space in the core of the protein. In D90H, There is a difference in charge between the wild-type and mutant amino acid. The charge of the buried wild-type residue is lost by this mutation. The wild type and mutant amino acids differ in size,

With the mutant residue been bigger than the wild-type residue. The wild-type residue was buried in the core of the protein, and since the mutant residue is bigger, it probably will not fit. In R222G, There is a difference in charge between the wild-type and mutant amino acid, this can cause loss of interactions with other molecules or residues, The wild-type and mutant amino acids also differ in size, where the mutant residue is smaller, this might lead to loss of interactions. Furthermore, the hydrophobicity of the wild type and mutant residue differs, as the mutation introduces a more hydrophobic residue at this position, this can result in loss of hydrogen bonds and/or disturb correct folding. In W231R, There is a difference in charge between the wild type and mutant amino acid. The mutation introduces a charge; this can cause repulsion of ligands or other residues with the same charge. In addition, the wild type and mutant amino acids differ in size, where the mutant residue is smaller; this might lead to loss of interactions. The hydrophobicity of the wild type and mutant residue also differs, that is why hydrophobic interactions, either in the core of the protein or on the surface may be lost. In P360S, the mutant residue is smaller than the wild-type residue, which is why the mutation will cause an empty space in the core of the protein. The hydrophobicity of the wild type and mutant residue also differs; this difference will cause loss of hydrophobic interactions in the core of the protein. In R441C, The charge of the wild-type residue is lost, causing loss of interactions with other molecules. In addition, the wild type and mutant amino acids have different size; causing a possible loss of external interactions. In R441H, interactions are lost due to the loss of charge in the mutant amino acid. In R504S, the interaction is lost due to difference in size, charge and hydrophobicity. In R504H, the interaction is lost due to loss of charge and the difference in size between the wild and mutant amino acid with the mutant amino acid been smaller in size the wild one.

We also recognized common shared domains, which were Cdc73/Parafibromin IPR007852, C-Terminal Domain Super-family IPR038103 and Cell Division Control Protein 73, C-Terminal IPR031336, which indicated the conservancy and the significance of these SNPs.

Chimera software was used to show the 3D changes in the structure of the protein coupled with 2D schematic structures from project hope for comparison (Fig. 2-12). The structural differences between the wild type and mutant type visualized using these two software, prove the pathogenic impact of the eleven SNPs on parafibromin protein.

We tried to identify the variant in CDC73 gene that could cause mutational impact on the protein that could lead to cancer development. Using COSMIC software. We focused on the 11 novel mutation at hand. We found after analyzation that three SNPs will lead to Nonsense Substitution (R222G, W231R and R441C), while one SNP (L63P) will lead to Frameshift-Deletion. This indicate the significance of theses SNPs in the development of hyperparathyroidism-jaw tumor (HPT-JT) syndrome. Other SNPs prediction was not available at the web side.

We analyzed the allele’s frequency using dbSNP Short Genetic Variations that provided different prediction about the global frequency of our gene in question. We noted R504H SNP to have the highest alleles frequency with global frequency of 0.00004.while other SNPs results ranged from 0,0 to 0.00001 indicating that R504H could be best candidate as a diagnostic marker.

Previous papers report novel mutations associated with Jaw tumor syndrome in the following positions: c.191-192 delT,(19) and (c.1379delT/p.L460Lfs*18) (36). While novel deletion of exons 4 to 10 of CDC73 detected in another study (37).

In other study NGS revealed four pathogenic or likely pathogenic germline sequence variants in CDC73 c.271C>T (p.Arg91*), c.496C>T (p.Gln166*), c.685A>T (p.Arg229*) and c.787C>T (p.Arg263Cys that are related to Primary hyperparathyroidism (PHPT) (2) of those mutations, only (A263C) was found to be pathogenic (by SIFT, PROVEAN, Polyphen2 and SNAP2) in the present study. Furthermore A study done by Sulaiman et al. identified another polymorphism at 109 T>G (38). In addition, CDC73 gene mutation was also reported be associated with other types of cancers like gastric, colorectal, ovarian and head and neck cancers (38). The current work provide new mutations in CDC73 gene which are related to Jaw tumor syndrome, this will add to the growing knowledge about the association between CDC73 gene mutations and Jaw tumor syndrome.

The mutations identified in this study can be used as diagnostic marker for the disease, and serve as “actionable targets” for chemotherapeutic intervention in patients whose disease is no longer surgically curable further in vitro and in vivo studies are needed to confirm these results.

In this study, the effect of the SNPs of CDC73 gene was thoroughly investigated through different bioinformatics prediction soft wares, 11 novel mutations were found to have damaging impact on the structure and function of the protein and may thus be used as diagnostic marker for hyperparathyroidism-jaw tumor (HPT-JT) syndrome.