Association between MYH9 and APOL1 Gene Polymorphisms and the Risk of Diabetic Kidney Disease in Patients with Type 2 Diabetes in a Chinese Han Population

Single-nucleotide polymorphisms (SNPs) in MYH9-APOL1 gene regions have been reported to be associated with diabetic kidney disease (DKD) in the American population. We examined the association between polymorphisms in MYH9-APOL1 and DKD susceptibility in a Chinese Han population. MYH9 rs3752462 (T>C) and APOL1 rs136161 (C>G) were genotyped in 303 DKD patients and 364 type 2 diabetes mellitus (T2DM) patients without kidney disease using the TaqMan SNP genotyping assay. Chi-squared test and multivariate logistic regression were used to evaluate the association. We observed that only MYH9 rs3752462 was associated with DKD (genotype, P = 0.004; allele, P = 0.002). Genetic model analysis revealed that rs3752462 was associated with increased risk of DKD under a dominant model adjusted by age and sex (adjusted odds ratio (aOR), 1.675; 95% CI 1.225–2.289; P = 0.001) and an additive model (TC versus TT: aOR, 1.649; 95% CI 1.187–2.290; CC versus TT: aOR, 1.817; 95% CI 0.980–3.367; P = 0.005). The combined effect of rs3752462 TC + rs136161 CC genotype showed an association of DKD adjusted by age and sex (aOR, 1.732; 95% CI 1.128–2.660; P = 0.012). After a Holm-Bonferroni correction for multiple tests, the C allele frequencies of the rs3752462 and the TC + CC genotype in the dominant model were considered statistically significant with a markedly increased risk of DKD (P < 0.00208; P < 0.002). Our results suggest that MYH9 rs3752462 is significantly associated with an increased risk of DKD in Chinese Han individuals.

Introduction
Diabetic kidney disease (DKD) is a common and serious microvascular complication of diabetes mellitus (DM), which is characterized by an elevated urinary albumin excretion rate, elevated blood pressure, and declined renal function. Approximately 30-40% of DM patients will develop DKD, which is the leading cause of end-stage renal disease (ESRD) and renal failure [1]. Genetic factors appear critical in its pathogenesis based upon the evidence including aggregation in families, variable incidence rates of DKD between different races, and the highly heritable nature of diabetic renal clinic and histologic changes [2]. Compared to the Caucasian population, the Asia populations are more likely to suffer from DKD [3]. Identification of potentially susceptible genes and loci is needed to facilitate earlier identification and prevention of DKD, particularly in China.
The MYH9 gene located on chromosome 22 q12.3-13.2 encodes nonmuscle myosin IIA. The approximately 224 kDa protein is widely expressed in most cells in the body [4,5]. Polymorphisms in MYH9 have been strongly associated with ESRD according to genome-wide association studies (GWAS), including human immunodeficiency virus-(HIV-) associated nephropathy in African Americans and idiopathic focal segmental glomerulosclerosis in European Americans and Hispanic Americans. Multiple common single-nucleotide polymorphisms (SNPs) in MYH9 are associated with a greater risk for nondiabetic ESRD [6][7][8]. The APOL1 gene, which is also located on chromosome 22, encodes apolipoprotein L-1. This gene has been associated with kidney disease in African Americans [9]. APOL1 gene polymorphisms have also been more intensely associated with the risk of kidney disease previously attributed to MYH9 [10]. The two genes cosegregate in many populations, which makes it difficult to differentiate between the two association signals.
A few studies reported the association of MYH9 or APOL1 with DKD. A GWAS and transethnic meta-analysis established the significant associations of MYH9 and APOL1 on chromosome 22 q12.3 with DKD in European American, African American, and American Indian populations. Furthermore, MYH9 (rs5750250)-APOL1 (rs136161) contributed the strongest association with DKD in African American populations [11]. Another study reported the association of four MYH9 SNPs (rs4821480, rs2032487, rs4281481, and rs3752462) with T2DM-ESRD susceptibility in European Americans [8]. However, among them, only MYH9 rs3752462 and APOL1 rs136161 present genetic polymorphisms in Chinese Han individuals.
The susceptibility of MYH9 and APOL1 polymorphisms with DKD in Chinese populations has not been well studied. Considering the strong ethnic heterogeneity for gene polymorphisms, we evaluated the association of MYH9 rs3752462 (T>C) and APOL1 rs136161 (C>G) with DKD in a Chinese Han population.

Materials and Methods
2.1. Subjects. The clinic-based, case-control study recruited a total of 667 volunteers with T2DM. Among them, 303 patients with a history of DKD were defined as the case group. The remaining 364 participants, who had been diagnosed as T2DM for at least 7 years and had no history of DKD, were defined as the control group, regardless of age and sex.
Type 2 diabetes patients were diagnosed according to the 2012 American Diabetes Association diagnostic criteria; DKD patients were defined by the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF K-DOQI) guidelines.
This study was approved by the institutional ethics committee of the China-Japan Friendship Hospital (Beijing, China), and written informed consent was obtained from all individuals.
2.2. DNA Isolation and Genotyping. Genomic DNA was extracted from peripheral blood using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer's protocol and quantified using a NanoDrop 1000 spectrophotometer (Thermo Scientific, Waltham, MA, USA). Genotyping was confirmed using the TaqMan SNP genotyping assay (Applied Biosystems, Waltham, MA, USA) and the ABI PRISM 7500 Sequence Detection System (Applied Biosystems).
Polymerase chain reaction (PCR) amplification was performed in a 25 μL reaction mixture containing 50 ng DNA, 12.5 μL of Premix Ex Taq (Takara, Shiga, Japan), 5 pmol of each primer (Applied Biosystems), and 3 pmol of each probe (Applied Biosystems). The amplification conditions consisted of 40 cycles of 95°C for 10 min, 92°C for 15 seconds, and 60°C for 1 min. The primers used to detect SNPs were synthesized by Applied Biosystems.

Statistical Analyses.
Clinical data, including age, gender, body mass index (BMI), blood pressure, duration of diabetes, A1C, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), and homocysteine (Hcy), were non-Gaussian distributed. Wilcoxon signed-rank test was used to analyze the differences in clinical characteristics of the DKD and diabetic groups, and the data are presented as median (interquartile range). The Hardy-Weinberg equilibrium analysis of both SNPs was conducted using the Chi-squared test. The genotype and allelic frequencies of SNPs were also assessed by the Chi-squared test.
Multivariate logistic regression was carried out to analyze the association between each SNP and susceptibility to DKD after adjustment for age and gender in the additive, recessive, or dominant models. Multivariate logistic regression was also used for the combined effect of both MYH9 rs3752462 and APOL1 rs136161 polymorphism on DKD. An example to define these genetic models is the rs3752462 SNP, where C is the minor allele. For the dominant model, CC and TC were coded as 1 and TT was coded as 0. For the recessive model, CC was coded as 1 and TC and TT were coded as 0. For the additive model, CC, TC, and TT were coded as 2, 1, and 0, respectively. For SNP rs136161, G is the minor allele.
The Holm-Bonferroni correction was started by ordering the P values (from lowest to highest) as P 1 … P m and let the associated hypotheses be H 1 … H m . For a given significance level α, let κ be the minimal index such that P > α/ m + 1 − κ . Reject the null hypotheses H 1 … H κ−1 and reject H κ … H m . In present research, association analysis was performed for 26 times, m = 26.

Subjects.
A total of 667 T2DM participants were included, including 303 patients with a history of DKD and 364 patients without a history of kidney disease. The clinical characteristics of the participants are listed in Table 1.
There were no significant differences in gender, smoking, TC, and LDL-C between the two groups. However, there were significant differences in age, BMI, duration of diabetes, blood pressure, A1C, Hcy, HDL-C, and TG between the DKD and T2DM groups.

Genotype and Allele Distributions of MYH9 rs3752462
and APOL1 rs136161 Polymorphisms. The genotype and allele frequencies of the rs3752462 and rs136161 polymorphisms in DKD and T2DM groups are shown in Table 2. Both SNPs were in Hardy-Weinberg equilibrium (P > 0 05), and their minor allele frequencies were >5%. The genotype and allele frequencies of the rs3752462 were different between DKD and T2DM groups (genotype, P = 0 004; allele, P = 0 002). A significant association with the increased risk of DKD remained for the minor allele C after a Holm-Bonferroni correction (P < 0 00208). However, there was no significant differences in the genotype and allele frequencies of the rs136161 between the two groups (genotype, P = 0 944; allele, P = 0 751).

Association of MYH9 rs3752462 and APOL1 rs136161
Polymorphisms with DKD. Different genetic models were applied to verify the associations of MYH9 rs3752462 and APOL1 rs136161 polymorphisms with DKD (Table 3). We assumed that the minor alleles of both SNPs were the risk factors compared to the common alleles. In the dominant model, multivariate logistic regression analysis revealed that when the rs3752462 TT genotype was used as the reference, the TC + CC genotype was associated with a high risk of DKD (TC + CC versus TT: odds ratio (OR), 1.690; 95% CI 1.240-2.303; P = 0 001). In the additive model, when the rs3752462 TT homozygote genotype was used as the reference, the TC and CC genotypes were associated with a decreased risk of DKD (TC versus TT: OR, 1.684; 95% CI 1.216-2.332; CC versus TT: OR, 1.720; 95% CI 0.935-3.162; P = 0 004). In the recessive model, when the rs3752462 TT + TC genotype was used as the reference, the CC genotype was not associated with the risk of DKD (CC versus TT + TC: OR, 1.398; 95% CI 0.772-2.533; P = 0 269). The results were remained similar after adjusted by age and sex. After the Holm-Bonferroni correction, only the TC + CC genotype showed significant association with an increased risk of DKD (P < 0 002). There was no significant association between APOL1 rs136161 and the risk of DKD under these genetic models, which was remained similar after adjustment for age and sex (Table 3).

Combined
Effect of MYH9 rs3752462 and APOL1 rs136161 Polymorphisms on DKD. Multivariate logistic regression analysis was applied to analyze the combined effect of both SNPs on DKD (Table 4). When the rs3752462 TT + rs136161 CC genotype was used as the reference, we found that the patients with rs3752462 TC + rs136161 CC genotype showed a higher risk of DKD (OR, 1.734; 95% CI 1.134-2.652; P = 0 011). The combined effect of other genotypes of rs3752462 and rs136161 was also examined; however, no difference was found. After adjustment by age and sex, the results were similar (Table 4). However, there was no significant association after Holm-Bonferroni correction.

Discussion
DKD is one of the most frequent microvascular complications of diabetes and is the leading cause of ESRD worldwide. Genetic heterogeneity and gene-gene or gene-environment interactions are frequently hypothesized as being important in this complex genetic disorder [12]. In the present study, 667 participants (303 DKD patients and 364 DM patients) were enrolled to investigate associations of MYH9 rs3752462 and APOL1 rs136161 with the risk of DKD in a Chinese Han population. Our results indicate that the minor allele of SNP rs3752462 is associated with an increased risk of DKD, while APOL1 rs136161 was not significantly associated with DKD. The results suggest that MYH9 rs3752462 might play an important role in the risk of DKD in the Chinese Han population.
The first association study of MYH9 with kidney disease was observed in the patients with the giant platelet syndromes, a group of diseases caused by MYH9 mutations and with a spectrum of abnormalities including low platelet count, hearing loss, giant platelets, and cataract may present focal segmental glomerular sclerosis (FSGS) [7]. APOL1 is a neighbor gene presenting very strong cosegregation with MYH9 in African descendants. Two studies reported stronger association with CKD of APOL1 than MYH9, being the marker possibly responsible for the effect previously attributed to MYH9 [9,13]. Previous studies suggested that common polymorphisms in MYH9 were strongly associated   with nondiabetic kidney diseases in several ethnic populations [14][15][16]. However, polymorphisms in MYH9 have been proven to be associated with diabetic nephropathy in 1963 European Americans, including 536 cases with T2DM-ESRD and 1427 nonnephropathy controls [8]. A recent GWAS and transethnic meta-analysis showed that SNPs in the MYH9-APOL1 gene region showed the strongest association with DKD in African Americans, which provided suggestive evidence for association with DKD, although it did not reach genome-wide significance (P < 5 × 10 −8 ) [11]. Our results indicated that MYH9 rs3752462 was strongly associated with clinically diagnosed DKD in a Chinese Han population, and the minor allele C contributed to the increased risk of DKD, which might be due to genetic heterogeneity. Although the genotype and allele frequencies of APOL1 rs136161 were not associated with DKD, SNP rs136161 CC genotype combined with SNP rs3752462 TC genotype showed association with the risk of DKD, providing further evidence that single genetic abnormalities were rarely the only cause of complex disease. MYH9 encodes the nonmuscle myosin heavy chain 9, which forms myosin II with other subunits. Myosin II, a motor protein, binds actin to regulate cellular motility. MYH9 is mainly expressed in the podocytes, as well as in mesangial cells and arteriolar and peritubular capillaries in kidneys. As a motor protein, abnormal MYH9 expression, localization, or function change will lead to cytoskeleton damage, further causing proteinuria or renal failure in patients with CKD [17][18][19]. Classical deletion of Myh9 in mice results in embryonic lethality due to the loss of cell-cell adhesion and cell movement during gastrulation [20,21]. Podocytespecific deletion of Myh9 in C57BL/6 mice causes significant susceptibility to experimental doxorubicin hydrochloride glomerulopathy [22]. A common missense mutation in MYH9 (E1841K) alters podocyte cytoskeletal structure and renders podocytes more susceptible to injury after a damaging stimulus [23]. However, the mechanisms responsible for them have not been defined. Wasik et al. found that the activity of myosin II was reduced by septin 7, which could hinder GLUT4 storage vesicle and fusion with the plasma membrane, reduce glucose uptake into podocytes, and further cause insulin resistance [24]. Fan et al. showed that NM-IIA activity was also inhibited by SLIT2/ROBO2 signaling, which could reduce podocyte adhesion in kidney glomeruli and aggravate the injuries of the glomerular filtration barrier in patients with CKD [25]. SNP rs3752462 is located in intron 13 of MYH9, and the functional effect has not been reported. One possibility was that the mutation in noncoding areas modulated gene transcription or pre-mRNA splicing. Furthermore, MYH9 rs3752462 might directly regulate gene expression or on a more distant gene (such as APOL1). It has been reported that the strongest kidney disease association was mapped to the region of introns 13-15 by genotyping 79 MYH9 SNPs in a total of 2496 cases (FSGS, HIV-associated nephropathy, and ESRD attributed to hypertension) and healthy controls [26]. Therefore, SNP rs3752462 in MYH9 might be a functional variation or just a tag SNP in strong linkage disequilibrium with the causal functional SNP. This hypothesis needs confirmation in a future study.
Recently, MYH9 rs3752462 was associated with cerebrovascular blood flow (CBF) in patients with type 2 diabetes [27]. Both cerebrovascular disease and DKD were the main vascular complications of T2DM, which implies similar molecular mechanisms in the association of MYH9 rs3752462 with cerebrovascular disease and DKD. In addition, the T allele of SNP rs3752462 was associated with an excess risk for high blood pressure in patients with CKD in a Chinese population. It was also revealed that SNP rs3752462 was an independent predictor of a reduced glomerular filtration rate in the Spanish RENAS-TUR cohort population [28]. Therefore, blood pressure or glomerular filtration rate might be involved in the risk of MYH9 rs3752462 on DKD.
The association of MYH9-APOL1 is very interesting in DKD. It could provide the genetic tool to identify DM patients with increased risk of progressing to DKD, at least in populations in whom the mutations are known to be prevalent variations. Comprehension of the biological mechanisms determining proteinuria and CKD in patients presenting these mutations can create opportunity for new therapeutic targets and measures.
In conclusion, our study suggests that MYH9 SNP rs3752462 is significantly associated with DKD in patients with DM and confirms the minor allele C as a risk factor of DKD. APOL1 rs136161 was not related to the risk of DKD in our sample, but the result can be related to our small sample size. It will be a current challenge to explore the biological mechanisms underlying this association in future research.


extfieldsofstudy: Biology Medicine

text:
Dissecting the Mutational Landscape of Cutaneous Melanoma: An Omic Analysis Based on Patients from Greece

Melanoma is a lethal type of skin cancer, unless it is diagnosed early. Formalin-fixed, paraffin-embedded (FFPE) tissue is a valuable source for molecular assays after diagnostic examination, but isolated nucleic acids often suffer from degradation. Here, for the first time, we examine primary melanomas from Greek patients, using whole exome sequencing, so as to derive their mutational profile. Application of a bioinformatic framework revealed a total of 10,030 somatic mutations. Regarding the genes containing putative protein-altering mutations, 73 were common in at least three patients. Sixty-five of these 73 top common genes have been previously identified in melanoma cases. Biological processes related to melanoma were affected by varied genes in each patient, suggesting differences in the components of a pathway possibly contributing to pathogenesis. We performed a multi-level analysis highlighting a short list of candidate genes with a probable causative role in melanoma.

Introduction
Cutaneous melanoma (CM) is a malignant tumour of epidermal melanocytes, the cells producing melanin located in the basal layer of the epidermis. Melanocytes originate from the neural crest, a transient embryonic structure consisting of highly migratory pluripotent cells, which will give rise to a number of cell types including melanocytes [1]. Although CM accounts for less than 5% of skin cancer incidence, it is responsible for the majority of deaths related to skin cancer due to its highly aggressive nature [2].
During the last decades, a continuous increase of CM frequency rates has been observed in Caucasian populations worldwide, making CM the most rapidly increasing cancer. CM incidence varies significantly within populations from different geographic regions, with Australia and New Zealand presenting the highest incidence rates worldwide. In Europe, the rates are lower, but still showed a three-fold to five-fold increase over the last decades [3]. CM occurrence differs a lot in European countries, with Switzerland showing the highest rate and Greece belonging to the group of low-incidence countries [4,5].
CM development is a complex, multi-factorial process involving the interplay of genetic and environmental risk factors. The most well-established environmental risk factor is the exposure to ultraviolet radiation (UVR) [2]. Regarding the genetic background, several susceptibility genes have been identified, including highly penetrative genes such as CDKN2A, the first familial melanoma gene identified [6,7] which is found mutated in approximately 40% of melanoma high-density families. Other less frequent mutations have been identified in genes of high or more moderate penetration, including CDK4 and the more recently described BAP1, TERT, POT1, ACD, TERF2IP and MITF [8]. Genome-wide association studies (GWASs) have also revealed numerous recurring single nucleotide polymorphisms (SNPs) associated with melanoma risk [9][10][11][12]. Further characterisation of the genetic risk factors in different patient populations could help develop more efficient prevention strategies and improve strategies for early diagnosis.
In the last decade, important steps towards characterising the somatic mutational landscape of melanoma have been achieved [13,14]. Identifying causative melanoma mutations is of great importance in order to understand the molecular basis of melanoma genesis and progression. Towards this end, next generation sequencing (NGS) technologies are a valuable tool and have been exploited in a number of recent studies, comparing sequencing data from melanoma tissue and a matched normal control in order to identify somatic mutations [13,[15][16][17][18][19]. In such approaches, discriminating driver mutations from passenger ones remains a challenge from both the experimental as well as the bioinformatics point of view [20][21][22][23][24]. Especially in the case of melanoma, which is one of the cancers with the highest mutation burden and heterogeneity, this problem is even more difficult to address, due to the confounding impact of melanoma's high mutation rate.
The majority of studies utilising NGS for the characterisation of melanoma genome are using fresh-frozen tissue samples [25]. Nevertheless, formalin-fixed, paraffin-embedded (FFPE) tissue is the most common specimen available for molecular assays on tissue after diagnostic histopathological examination, and a number of archived samples are available for retrospective studies. The major limitation of using FFPE samples in molecular biology analyses is that nucleic acids isolated from FFPE tissue often suffer from degradation and chemical modifications. Particularly in the case of primary melanomas, which generally have a small size at the time of diagnosis, most of the tissue is used for diagnostic evaluation, rendering an additional issue of tissue-availability. However, several protocols have been developed to improve the isolation of DNA/RNA from FFPE specimens [26,27] as well as specialised library construction methods allowing NGS-based analyses starting from nucleic acids of limited quantity and poor quality [28]. Studies evaluating the quality of genomic variant calling and/or gene expression quantification by NGS, based on nucleic acids isolated from FFPE specimens as compared to fresh-frozen tissue, revealed that this approach, although challenging, can produce accurate data [28][29][30][31][32].
In this work, we aimed to exploit FFPE samples for the identification of somatic mutations and germ-line variants in patients with primary melanomas by exome sequencing. Regarding the genetic factors involved in melanoma susceptibility, a number of studies concerning melanoma patients from the Greek population have been reported [12,33]. Still, the characterisation of melanoma somatic mutations in Greek patients has been limited and, to the best of our knowledge, this is the first attempt to characterise the somatic mutational profile at the exome level of primary melanoma patients in Greece.

Sequencing Data
In this study, we used FFPE tissue from nine patients with cutaneous melanoma after excisional biopsy. Our samples consisted of the paired tumour and surrounding normal skin that was used as control. All patients had no reported family history of melanoma and all examined melanoma tissues were from the primary lesion.
The whole exome sequencing (WES) data were aligned to the human genome, with an average alignment rate of >91%, an average sequence coverage of >100× and over 96% of targets with at least 20× coverage, enabling the achievement of the intended mutational profile [31,[34][35][36]. Only one sample attained a lower score in terms of coverage (normal sample for patient 8), but this did not affect further analysis, since high coverage is necessary in the tumour samples to overcome endogenous heterogeneity. Table 1 summarises the calculated alignment scores and sequencing depths for all the samples.

Identification of Germ-Line Variation
Aiming to examine whether the patients had germ-line variations on possible melanoma susceptibility loci, we focused on a panel of SNPs previously reported to be associated with CM risk. In particular, a list of SNPs from the GWAS catalog database [37] enriched by putative melanoma risk SNPs based on the MelGene database [10,33] was assessed. The analysis was restricted to 22 SNPs located in exon regions, since all SNPs on intronic or intragenomic regions were excluded because our data was derived from exome sequencing. Table 2 demonstrates the germ-line SNPs associated to melanoma risk found in the analysed patients. The relevant genes include pigmentation associated genes (SLC45A2, OCA2, TYR), as well as cell cycle and DNA repair genes (ATM, CDKN2A, ERCC5). Specific melanoma susceptibility alleles [38][39][40][41][42][43] were found in a number of patients. Table 2. Germ-line single nucleotide polymorphisms (SNPs) putatively associated with melanoma, based on genome-wide association studies (GWAS) and MelGene databases.

Identification of Somatic Coding Mutations
In order to identify somatic mutations, we used the MuTect algorithm [35] which detects somatic variations at low allelic fraction with high sensitivity and low false positive rate, based on the paired analysis of tumour and matched-normal sequencing data [44]. We identified a total of 10,030 somatic mutations in all patients (see Table S1). The majority of patients had comparable numbers of somatic mutations (median: 589), with the exception of two patients: patient 12, who had a total of 5324 somatic mutations, affecting 3752 genes, and patient 10 who had 27 somatic mutations, affecting 23 genes. Table 3 displays the number of somatic mutations for all the patients, the mutation frequency per Mb, along with the number of non-synonymous mutations and the relevant number of affected genes.
In particular, 3955 protein-altering somatic mutations were identified. Excluding patient 10, the median mutation frequency was 12.75 mutations/Mb (ranging from 10.1 to 105.7), which is in agreement with the previously reported mutation burden of melanoma genome, which is considered one of the highest among cancer genomes [45]. Regarding the sample from patient 10, it was the only case of acral melanoma, which has been reported to have markedly less somatic mutations. Next, we analysed the distribution of somatic substitutions per base change and all patients, except patient 10, showed a UVR characteristic mutational spectrum with a high ratio of C > T transitions (median rate 85.6%), which has been reported to characterise sun-exposed melanomas [25,46] (Figure 1).

Characterisation of Mutated Genes and Copy Number Variations
The 10,030 mutations corresponded to 6030 unique genes, of which 2890 harboured non-synonymous mutations, most likely affecting protein functionality. Among them, 421 genes were found in at least two and 73 genes were common in at least three patients. In order to gain insights about the functional role of these common genes, the Network of Cancer Genes (NCG) [47] was accessed so as to identify all the cancer-related genes from this 73-gene top common list. NCG is a manually curated literature-based repository containing 1571 cancer genes with either known involvement in cancer or high probability of association due to statistical analysis from numerous NGS studies. Out of the 73 genes, 33 were referred to as cancer genes according to NCG, namely DNAH7, PCLO, TTN, CSMD1, GPR98, MUC16, PKHD1L1, MYOM2, NEB, RELN, SPHKAP, UNC13C, ADCY8, ANK3, BAI3, CD163L1, CNTN5, COL22A1, DNAH14, EYS, FAT1, FAT3, FLT1, GRIN2A, KMT2D, PCDH18, PKHD1, SHROOM3, THSD7B, TNC, BRAF, LRP1B and RYR1. In addition, the COSMIC database [48,49] was accessed to identify genes previously reported in melanoma. 65 of the 73 top common genes were previously identified in melanoma cases, with a frequency over 5%. Figure 2a demonstrates that the majority of the 73 genes, found mutated in at least three patients, either belonged to the candidate cancer gene list of NCG (containing 1571 genes) or were previously reported in COSMIC with a mutation frequency of >5% in melanoma samples (1181 genes). Among the seven genes identified only in our study, WD repeat domain 87 (WDR87), was found mutated in seven patients (87.5%). WDR87 is a protein coding gene, but little is known about its function and its implication in melanoma. In COSMIC, it is found mutated in 4.2% of the samples. Additionally, we accessed TCGA's cBioPortal database [50,51] to investigate preceding discoveries for WDR87. This search exposed two melanoma studies, with WDR87 mutated in 55% and 16% of the samples examined [52,53]. Further analysis is needed to clarify the potential significance of the high mutation frequency observed for WDR87 gene in the specific subjects.
Somatic copy number variation (CNV) was assessed using differences in sequence coverage between each tumour specimen and all same-sex adjacent skin samples utilising CNVkit, a methodology which uses both on-target and off-target reads to infer copy number consistently across the genome. This analysis revealed several CNV events in genes implicated in melanoma and reported to harbour amplifications or deletions [17,54]. Specifically, CDKN2A (9p21) presented a deletion signal on three of the patients, and PTEN (10q23) on two. In addition, CCND1 (11q13.3) and MITF (3p13) were amplified in two patients and BRAF (7q34) was amplified in one patient (Figure 2b). Next, we searched the whole list of 2890 genes found to contain non-synonymous mutations in at least one patient, exploring the COSMIC database which contains data of somatic mutations for specific cancer types but also data for genes causally implicated in cancer. The notable melanoma-associated mutation BRAF V600E was detected in three patients, while RAS mutations were not detected. Among the mutated genes, only BRAF, CTNNB1, NF1 and TP53 carried specific mutations that have been previously reported in COSMIC (in more than 15 cases), as shown in Table S2. We used two criteria to characterise the genes carrying non-synonymous mutations in our study: the frequency that a gene has been found mutated in melanoma and the characterisation of a gene as cancer census. Specifically, we searched for genes mutated in melanomas with a frequency >20% and in addition Cancer Census genes reported as mutated in melanoma with a frequency >5%, both based on COSMIC ( Figure 2b). Furthermore, the MutSigCV algorithm (version 1.41) was used to identify significantly mutated genes, incorporating patient-specific mutation frequency with gene expression and replication time data. The small sample size prevents statistical significance in our results; still, the algorithm offers valuable information, by prioritising genes with putative significant mutations (denoted with * in Figure 2b), mainly after correcting for gene-specific mutation rates. It should be noted that among the most frequently mutated genes in our results, there are several constantly found mutated in cancer (e.g., PCLO, TTN) that are considered non-oncogenic [23]. Still, focusing only on the top melanoma census genes from COSMIC, the majority of them are also mutated in the analysed cases ( Figure S1).

Bioinformatics Pathway Analysis
In order to examine whether the genes found to carry somatic mutations were related to specific biological mechanisms, we performed enrichment analysis on the union of non-synonymous mutations for all the patients, particularly missense, nonsense, frame-shifting, splice site and non-stop mutations. Excluding the genes that were solely mutated in patient 12 (1303 genes) to avoid patient-specific bias, as well patient 10, who harboured very few mutated genes, a starting list of 1587 genes was obtained. Aiming to focus on genes putatively contributing to melanoma pathophysiology and filter out those carrying non-significant mutations, we applied two filtering steps at the 1587 gene list. Firstly, taking into account the predicted impact of each mutation on protein functionality, as predicted by PolyPhen2 tool [55], we excluded all genes carrying neutral mutations. Moreover, we explored whether these genes are expressed in melanoma through TCGA's cBioPortal dataset, and retained for pathway analysis only those appearing to have at least low expression in over 30% of the cases. These filtering steps reduced the list to 769 genes, which were used as input for enrichment analysis based on gene ontology (GO) and Reactome. The BioInfoMiner tool was used and statistically significant enriched terms were revealed, which were grouped according to their biological relevance in Figure 3a. A great number of genes fall in the categories of developmental processes (295 genes) and cell adhesion (138 genes). Interestingly, 67 genes were related to neural system characteristic mechanisms, as indicated by GO terms such as 'neuronal action potential', 'synapse organisation', 'regulation of myelination' and 'neuron projection guidance', grouped under the label 'synapse formation and neuronal signal transduction'. With the scope of distinguishing putatively causative genes, we focused on those with implication in diverse cross-talking biological processes, reflecting genes with a central role in cellular physiology. For this reason, we performed topological analysis using BioInfoMiner, which exploits semantic information to detect and rank genes based on their centrality, as described in different databases (e.g., GO and Reactome). This analysis resulted in a short list of genes ( Figure 3b) with possible causal implications in melanoma. Interestingly, in the proposed list there are several genes with a well-established connection to cancer, like BRAF, ATM and TP53, but also others like PDPK1 and DMD which could represent intriguing, yet poorly explored targets for further evaluation and possibly cancer treatment. Particularly, PDPK1 (3-phosphoinositide dependent kinase 1) was found altered in three patients, two of them carrying a gene amplification and one carrying a possibly damaging point mutation. Regarding DMD (Duchenne muscular dystrophy), it is a long gene of 2.5 Mb, located on chromosome X. In two patients, DMD was found containing protein-altering point mutations. It is worth mentioning that significant pathways are enriched by different genes in each patient, suggesting that the great diversity observed in genes affected by somatic mutations could reflect deregulation of common molecular mechanisms. Indeed, regarding processes with an established role in melanoma genesis and progression, such as the MAPK pathway and cell cycle (Table S3), all patients are found to have at least one mutated gene annotated by GO to the aforementioned biological processes. The fact that all these genes are expressed and bear damaging mutations supports their potential implication in a malfunctioning mechanism contributing to melanoma.

Discussion
In this study, we report the characterisation of somatic mutations and germ-line variants in patients with primary melanomas from Greece by exome sequencing analysis. This is the first study, to our knowledge, where primary CM tissue from a low-incidence, southern European country is analysed at the exome level. In particular, FFPE tissue paired samples were used. Despite the limitations of using FFPE samples in NGS analyses, they represent a valuable source of knowledge that needs to be exploited, especially in the case of CM, where clinical practice renders fresh-frozen primary tissue availability limited. Towards this end, the present work consists of a pilot study aiming to overcome technical difficulties and establish bioinformatics workflows for the exploitation of NGS approaches on FFPE clinical samples. Our goal is to expand this analysis to a greater number of patients, aiming to study any possible associations between germ-line and somatic alterations in melanoma patients. In the present analysis, the consequences of the fixation procedure were minimised, ensuring the validity of the presented results, at the cost of the inevitable loss in sensitivity. In spite of the limited number of patients analysed, we performed a multi-level analysis, exploiting vastly established databases and state-of-the-art tools to incorporate information aiming at a better understanding of the underlying mechanisms involved with melanoma. We present a short list of candidate genes with probable causative role in CM, which contains both well-known melanoma-associated genes, but also potential new players, such as PDPK1 and DMD. PDPK1 was originally characterised as a serine-threonine kinase, phosphorylating and activating AKT [56]. PDPK1 is a key element at the crossroad of signal transduction pathways such as Ras/MAPK pathway and Myc-cascade, in addition to PI3K/AKT [57]. Furthermore, PDPK1 is frequently amplified at the gene level or over-expressed in several tumour types [58,59], including melanoma [60]. As far as DMD is concerned, it was recently reported as a tumour suppressor in cancers, featuring myogenic programmes [61]. In melanoma cell lines, the DMD gene was found with deletions while the protein was frequently absent or down-regulated [62].
In addition, a recent study based on genomic data from public repositories of diverse cancer types, showed that DMD expression was decreased in the majority of the analysed tumours. Specifically in the case of melanoma, DMD was down-regulated as compared to benign nevi that already showed a reduced expression compared to normal skin [63].

Melanoma Samples
All samples were acquired in the context of the 12CHN-204 PROMISE project, under the strict conformity to the rules of the call. The samples derived from FFPE tissue blocks from excisional biopsies histopathologically confirmed as melanomas. Areas from tumour and adjacent healthy skin tissue were assessed and separated by a pathologist. Paired tissue samples, tumour and normal samples respectively, from nine patients, both male and female, with cutaneous melanoma were collected.

DNA Extraction and Exome Sequencing
DNA was isolated from the samples using QIAamp DNA FFPE Tissue protocol from QIAGEN (Hilden, Germany), with several modifications to deparaffinisation, washing and proteinase K digestion steps, to ensure better quality and higher quantity of the extracted DNA. More specifically, deparaffinisation of FFPE samples was performed with xylene (2 times) at 56 • C for 3 min and the precipitate was sequentially washed with 100%, 70% and 50% ethanol [27]. Proteinase K digestion was performed at 56 • C while stirring the samples and the incubation time was increased to 3 days with daily re-addition of proteinase K. The quantity and purity of the samples were checked using NanoPhotometer (IMPLEN, Munich, Germany). The extracted DNA was prepared and captured with the Agilent SureSelect Human All Exon 50 Mb kit (Agilent SureSelect v5, Santa Clara, CA, USA) and whole exome sequencing was performed on an Illumina HiSeq 4000 sequencer (San Diego, CA, USA), as paired-end reads.

Raw Data Analysis
Bioinformatic data analysis was performed utilising various state-of-the-art tools, as previously presented [64]. For this study, we used version 3.6 of GATK [65], which incorporates somatic SNP calling with somatic indel (insertions & deletions) calling, as carried out by MuTect2 [35] and Indelocator [66], comparing the tumour-normal pairs in order to characterise somatic mutations. Strand-specific artefacts, possibly due to DNA damage resulting from formalin fixation and storage time, were excluded from further analyses. Germ-line variants were identified using the HaplotypeCaller tool, by comparing the normal samples with the reference sequence, and specific coding SNPs were investigated from a known panel of germ-line variants associated with melanoma based on GWAS studies and established databases [10,33,37], focusing on those found on coding regions. Annotation of all mutations was performed using Oncotator [67]. Significantly mutated genes among the patients were identified using MutSigCV (version 1.41) [23], which ranks the genes by estimating a background mutation rate (BMR) through the number of silent versus non-coding mutations in the gene and the surrounding regions. BioInfoMiner [68] was used for the functional analysis of the mutated genes, so as to identify the molecular pathways influenced by these mutations, and to isolate the genes with central role, implicated in diverse and major mechanisms from various vocabularies. For the functional prediction of the somatic mutations we utilised dbNSFP [69] through Oncotator, a database that provides information for functional predictions and annotations for human non-synonymous variants. Copy number variation (CNV) analysis was performed using CNVkit [70], which specialises on CNV detection on targeted DNA sequencing. Expression of genes was evaluated through TCGA's cBioPortal datasets. Genes with TPM (transcripts per million) between 0.5 and 10 were considered to have low expression, between 11 and 1000 medium, and if TPM was over 1000, the genes were considered as highly expressed in a given case. Overall, genes were considered as expressed when encompassing at least low expression in over 30% of the cases.

Conclusions
In this study, we present the characterisation of somatic mutations by WES analysis of paired tissue from FFPE melanoma samples. A number of the identified mutated genes were previously found in melanoma, including established, cancer-related genes. Our multi-level analysis highlights a short list of candidate genes with a probable causative role in melanoma that could be promising targets for future investigation.
Supplementary Materials: The following are available online at http://www.mdpi.com/2072-6694/10/4/96/s1, Table S1: Total somatic mutations for all the samples; Table S2: Recurrent mutations based on COSMIC; Table S3: Biological processes from GO (MAPK pathway and Cell cycle), with the corresponding mutated genes in each patient; Figure S1: Top Census genes in melanoma from COSMIC database and the type of mutation found in all patients.

Conflicts of Interest:
The authors declare no conflict of interest. A-adenine, C-cytosine, G-guanine, T-thymine Amino-Acids E-glutamic acid, V-valine


Assessment of the Sensitizing Potential of Proteins in BALB/c Mice: Comparison of Three Protocols of Intraperitoneal Sensitization

Most food allergy cases are associated with a limited group of allergens. This could be attributed to an increased ability of some foods to sensitize and trigger allergic reactions. However, there are no validated animal models to evaluate the sensitizing or allergenic potentials of proteins. Our aim was to evaluate three protocols of adjuvant-free intraperitoneal sensitization that differ in the time points for sample collection (days 14, 28 and 35 from beginning of the sensitization) and also in the number of immunizations (2, 5 and 3, respectively). Ovalbumin (OVA; 0.05 mg), cow milk proteins (CMP; 0.025, 0.05 and 0.25 mg), and potato acid phosphatase (PAP; low allergenic protein; 250.0 mg) were administered intraperitoneally (ip) to BALB/c mice (n = 4–6) and the protein-specific IgE and IgG antibody responses were evaluated using ELISA. Additional serum protein-specific IgE antibodies evaluations were carried out after IgG depletion. Anti-OVA IgE antibodies were detected in mice from all three protocols. The responses were higher in the group of mice that underwent the 28-day protocol than in those that underwent the 14- or 35-day protocols (p < 0.01 and p < 0.05, respectively). Anti-CMP IgE antibodies were detected in both the 14- and 28-day protocols, but the response was higher in the group that underwent the 28-day protocol (p < 0.001). The anti-CMP IgE antibody response detection was improved after serum IgG depletion (p < 0.001). Anti-PAP IgE antibodies were not detected. Mice with undetectable serum levels of protein-specific IgE triggered anti-OVA, -CMP, and -PAP IgG responses. An adjuvant-free 28-day protocol with five ip immunizations seems appropriate for evaluation of the inherent sensitizing or allergenic capacity of the studied proteins. Reproducible results were obtained utilizing the BALB/c mouse strain. Inter-laboratory studies including a larger number of proteins should be carried out to validate this model.

Introduction
IgE-mediated food allergy is an adverse food reaction triggered by the ingestion of allergenic proteins in sensitized individuals. This disorder affects more than 1%, but less than 10%, of the general population [1]. Sensitization per se is not enough to trigger the symptoms associated with allergic reactions, but is essential for potential IgE-mediated allergic disease. The clinical manifestations of the condition vary from mild and transient symptoms to life-threatening anaphylaxis. Certainly, most cases of food allergy are associated with a limited number of allergens, such as peanut, tree nuts, hen's egg, cow's milk, fish and shellfish, although the number of food allergens is large [2,3]. This could be attributed to an increased ability of these foods to sensitize and trigger allergic reactions and suggests that "a spectrum of allergenic or sensitizing potentials exists amongst food proteins" [4]. If such a spectrum does exist, the sensitizing potential of proteins, defined as the inherent capacity of proteins to trigger an IgE-mediated immune response, could be assessed not only in naturally occurring protein allergens, but also in food proteins derived from transgene products or proteins modified upon food processing.
One study suggested that only an in vivo model could be used to evaluate the allergenicity of proteins resulting from de novo sensitization [5], but there are currently no validated animal models available to evaluate the sensitizing or allergenic potential of proteins [6]. A model for the evaluation of such potentials should be able to identify and distinguish commonly allergenic from rarely allergenic proteins [7] by utilizing a standardized adjuvant-free sensitization procedure. Although sensitization to proteins via intraperitoneal (ip) injection has some limitations, it seems to be the method of choice in the mouse model. This is mainly because ip sensitization avoids induction of oral tolerance to administered protein.
The BALB/c mouse strain is considered to favor type 2 immune responses with atopic-like phenotype [8,9], therefore protocols of ip sensitization of BALB/c mice have been proposed [10,11]. Notably, these protocols generate consistent and reproducible results from an intra-protocol point of view. However, the robustness of the IgE antibody response triggered after the ip administration of the reference allergen ovalbumin (OVA; the major allergenic component of egg protein) significantly differ between the proposed BALB/c protocols [11]. In order to validate animal models for the evaluation of the sensitizing potential of proteins, the sensitization protocols should be evaluated using common, weak, and rare allergens. In particular, to evaluate whether the protocol distinguishes commonly allergenic from rarely allergenic proteins. Thus, the aim of this study was to evaluate the use of the BALB/c mouse model to measure sensitizing potential of the common allergens OVA and cow milk protein (CMP), and the rarely allergenic potato protein (PAP) using three different IgE protocols.

Animals
Six-to Eight-week-old female BALB/c mice were purchased from Bioterium Claude Bernard (Benemérita Universidad Autónoma de Puebla, Puebla, México). The mice were maintained on a cow's milk-egg-potato protein-free standard diet for at least three generations (Mazuri Rat and Mouse Diet #5663) and housed in an animal room at 23 ± 3 • C and 50 ± 10% relative humidity with a 12:12-h light-dark cycle. Water and diet were available ad libitum. The ethics review board of the Autonomous University of Sinaloa (Universidad Autónoma de Sinaloa) approved the study design (Ethical approval number: CE-UACNyG-2014-JUL-001).

Test Materials
The reference allergen OVA (grade V ≥98% pure) and the hypoallergenic potato acid phosphatase (PAP, 0.5-3.0 unit/mg solid) [10,12] were obtained from Sigma Chemical. Cow's milk protein rich in casein (milk protein) was obtained from MP Biomedicals (Solon, OH, USA) (protein content ≥ 99%, Cat. 0219509605-5). For ip injection, the proteins were solubilized in sterile PBS 7.4 (SIGMA) as follows: (a) 0.02% OVA solution, (b) 10% PAP solution, and (c) 1, 0.5 and 0.1 mg/mL milk protein solutions. Milk protein was macerated until a fine powder was obtained. Samples (5 mg/mL) of milk protein powder in PBS were heated at 50 • C for 1 h with continuous shaking (400 RPM) in a ThermoMixer ® C (Eppendorf, Hamburg, Germany). After this, the casein samples were centrifuged at 13,400× g for 5 min and the supernatants collected and stored at −80 • C until their use. The protein content of the milk protein preparations was determined using the bicinchoninic acid method according to the manufacturer's instructions (BCA assay, PierceTM Thermo Scientific, Rockford, IL, USA).

Sensitization Procedure
Groups of mice (n = 4-6) were injected with 250 µL of 0.02% OVA (0.05 mg per mouse), 10% PAP (250.0 mg per mouse) or a range of concentrations of CMP (1, 0.2 and 0.1 mg/mL) in PBS. The control groups (n = 6) were ip injected with 250 µL of PBS only (Sigma-Aldrich cat P5368, Saint Louis, Missouri). The immunization treatments with OVA, PAP and CMP were repeated at different time points: days 0 and 7 for 14-day protocol, days 0, 3, 6, 9 and 12 for 28-day protocol, and days 0, 14 and 28 for 35-day protocol. The mice were exsanguinated (from the tail vein) after 14, 28 or 35 days following exposure to the proteins. The three protocols are described in short in Figure 1. Individual serum samples were stored at −80 • C until analysis.

Test Materials
The reference allergen OVA (grade V ≥98% pure) and the hypoallergenic potato acid phosphatase (PAP, 0.5-3.0 unit/mg solid) [10,12] were obtained from Sigma Chemical. Cow's milk protein rich in casein (milk protein) was obtained from MP Biomedicals (Solon, Ohio, USA) (protein content ≥ 99%, Cat. 0219509605-5). For ip injection, the proteins were solubilized in sterile PBS 7.4 (SIGMA) as follows: (a) 0.02% OVA solution, (b) 10% PAP solution, and (c) 1, 0.5 and 0.1 mg/mL milk protein solutions. Milk protein was macerated until a fine powder was obtained. Samples (5 mg/mL) of milk protein powder in PBS were heated at 50 °C for 1 h with continuous shaking (400 RPM) in a ThermoMixer ® C (Eppendorf, Hamburg, Germany). After this, the casein samples were centrifuged at 13,400× g for 5 min and the supernatants collected and stored at −80 °C until their use. The protein content of the milk protein preparations was determined using the bicinchoninic acid method according to the manufacturer's instructions (BCA assay, PierceTM Thermo Scientific, Rockford, Illinois, USA).

Milk Protein Gel Electrophoresis
The purity analysis of cow milk proteins (MP Biomedicals) was carried out by gel electrophoresis in reducing conditions (SDS-PAGE) according to the method of Laemmli [13]. Commercially

Sensitization Procedure
Groups of mice (n = 4-6) were injected with 250 μL of 0.02% OVA (0.05 mg per mouse), 10% PAP (250.0 mg per mouse) or a range of concentrations of CMP (1, 0.2 and 0.1 mg/mL) in PBS. The control groups (n = 6) were ip injected with 250 μL of PBS only (Sigma-Aldrich cat P5368, Saint Louis, Missouri). The immunization treatments with OVA, PAP and CMP were repeated at different time points: days 0 and 7 for 14-day protocol, days 0, 3, 6, 9 and 12 for 28-day protocol, and days 0, 14 and 28 for 35-day protocol. The mice were exsanguinated (from the tail vein) after 14, 28 or 35 days following exposure to the proteins. The three protocols are described in short in Figure 1. Individual serum samples were stored at −80 °C until analysis.

IgG Depletion of Serum Samples
Serum samples were diluted 1:10 with ELISA diluent (BioLegend. Cat. 408804, San Diego, California, USA). IgG antibodies were removed from the diluted serum samples. For this purpose, we took advantage of the SureBeads™ Magnetic Beads system (BIO-RAD. Cat. 161-4823). The system

IgG Depletion of Serum Samples
Serum samples were diluted 1:10 with ELISA diluent (BioLegend. Cat. 408804, San Diego, CA, USA). IgG antibodies were removed from the diluted serum samples. For this purpose, we took advantage of the SureBeads™ Magnetic Beads system (BIO-RAD. Cat. 161-4823). The system contains magnetic beads designed to capture IgG or IgA antibodies. The beats can attach IgG or IgA antibodies from the FC region. The procedure was carried as follows: 100 µL of magnetic beads (SureBeads protein G) were transferred to 1.5 mL tubes. The beads were washed three times with 1 mL of PBS + 0.01% Tween 20. After magnetization of the beads, the wash solution was discarded and 350 µL of diluted serum samples were added into the tube. Samples were left rotating for 10 min at RT and magnetized again. The supernatants (serum samples depleted in IgG) were collected and stored at −80 • C until analysis.

Specific Antibody Analyses
OVA-, PAP-or cow milk protein-specific IgE and IgG were detected using enzyme-linked immunosorbent assay (ELISA). Ninety six-well flat-bottomed polystyrene plates (NUNC Maxisorb #442404) were coated with 20 µg of individual proteins in 100 µL of coating buffer pH 9.5 (BioLegend. Cat. 421701). The plates were incubated overnight at 4 • C, then washed twice with PBS + 0.05% Tween 20 and incubated for 2 h at RT with 200 µL of blocking solution (10% FCS in PBS). The blocking solution was discarded and 100 µL of serum samples diluted 1:10 in ELISA diluent (BioLegend, cat. 421203) were added to individual wells. After overnight incubation at 4 • C, wells were washed three times with PBS + 0.05% Tween 20. 100 µL of the biotinylated detection antibody at 2 µg/mL (Biotin rat IgG1 anti-mouse IgE, BioLegend. Cat. 408804) was added to each well and incubated for 1 h at RT. Wells were washed as before, then 100 µL of streptavidin-horseradish peroxidase (Diluted 1:1000 in ELISA diluent, BioLegend. Cat. 405210) was added to each well and incubated for 30 min at RT. Finally, the assays were developed with 100 µL of tetramethylbenzidine (TMB, Thermo Scientific, Cat. 34028, Rockford, IL, USA) substrate for 30 min at RT. H 2 SO 4 2M (50 µL) was used as stop solution. An automated ELISA reader (Multiskan™ FC Microplate Photometer, Thermo Scientific, Cat. 34028, Rockford, IL, USA) was used to measure absorbance at 450 nm. The specific IgG antibodies were determined as stated above, but serum samples were diluted 1:1000 and the biotinylated detection antibody was an anti-mouse IgG at 2 µg/mL (Diluted 1-250 in ELISA diluent, BioLegend. Cat. 405303). The assays were developed for 5 min at RT.

Statistical Analysis
Data were analyzed using GraphPad Prism Version 5.0 (GraphPad Software, San Diego, CA, USA). Normality testing of the data was carried out using Kolmogorov-Smirnov test. Unpaired t-tests were used to compare the difference between two different groups and paired t-tests were used to compare the levels of antibodies in the same group of animals. One-way ANOVA followed by Tukey's multiple comparison test for comparison of more than two groups. When normality test failed, Kruskall-Wallis tests followed by Dunn's multiple comparison tests were used for comparison of more than two groups. Significance was taken to be p < 0.05. IgG or IgE antibody responses to antigen were assessed following subtraction of background responses (pre-immune serum samples).

Electrophoretic Profile of Cow's Milk Protein
The SDS-PAGE analysis of the cow milk protein revealed the presence of fifteen bands (Figure 2). Caseins and globulins were identified. The percentage of caseins was 87.1%. The densitometric analysis of proteins was carried out considering only the data obtained from lanes 5-9 as at these sample concentrations the image analyzer system detected the total number of bands ( Figure 2).

BALB/c Mice Are Efficiently Sensitized to OVA
Three ip protocols of sensitization to OVA were evaluated in this study. The three protocols triggered an anti-OVA IgE immune response that was detected using ELISA ( Figure 3). Although the same dose of OVA was administered in each ip protocol, the 28-day protocol with 5 ip injections was more efficient at triggering an anti-OVA IgE immune response than both the 14-day protocol with two injections and the 35-day protocol with 3 injections (p < 0.01 and p < 0.05, respectively) ( Figure 3).

BALB/c Mice Are Efficiently Sensitized to OVA
Three ip protocols of sensitization to OVA were evaluated in this study. The three protocols triggered an anti-OVA IgE immune response that was detected using ELISA ( Figure 3). Although the same dose of OVA was administered in each ip protocol, the 28-day protocol with 5 ip injections was more efficient at triggering an anti-OVA IgE immune response than both the 14-day protocol with two injections and the 35-day protocol with 3 injections (p < 0.01 and p < 0.05, respectively) ( Figure 3). The animals (n = 5-6 per group) were randomly assigned to a 14-, 28-or 35-day protocol and were injected ip with 250 μL of 0.02% OVA (0.05 mg) for 2, 5, or 3 times respectively (see Figure  1 for details). The mice were exsanguinated after 14, 28 or 35 days according to the protocol used. Different letters mean statistical differences (p < 0.05) by one-way ANOVA and Tukey's multiple comparison tests. All serum samples were evaluated using ELISA.

Sensitization to Cow's Milk Protein Depends on the Dose and Frequency of Ip Injections
Three protocols of adjuvant-free ip sensitization that differ in the number and frequency of injections were evaluated. Two of the protocols were carried out with three different doses of CMP (14-and 28-day protocols). Regarding the 14-day protocol, no anti-CMP IgE antibodies were detected in the sera of mice that were administered 0.25 mg of CMP. The other two groups (0.025 mg and 0.05 mg) showed weak anti-CMP IgE antibodies responses (Figure 4a). The strongest anti-CMP IgE immune responses were triggered after the ip administration of 0.05 mg and 0.025 mg of CMP, and this occurred in the mice from the 28-day protocol. These responses were higher than those triggered by the groups of mice that underwent the 14-or 35-day protocols (p < 0.001) (Figure 4a). The 35-day protocol failed to trigger an anti-CMP IgE immune response (Figure 4a). The mice that yielded weak or undetectable anti-CMP IgE antibodies were able to trigger an anti-CMP IgG immune response (Figure 4b). The levels of anti-CMP IgE antibodies were evaluated before and after IgG depletion in three groups of mice. The results showed increased anti-CMP IgE antibodies after IgG depletion, but most serum samples that showed undetectable levels of anti-CMP IgE antibodies remained as such after IgG depletion (Figure 4c). In this same series of experiments, the serum levels of anti-CMP IgE antibodies were significantly increased in a group of mice that underwent the 28-day protocol (p < 0.001) (Figure 4c).

A Twenty-Eight Day Protocol with Five Ip Injections Triggers Anti-Pap IgG but Not IgE Antibody Responses in Balb/C Mice
Two ip protocols (14-and 28-day) of sensitization were evaluated. As expected, anti-PAP IgE antibodies were not detected in the sera of the mice, after either the 14-or the 28-day protocols, but strong anti-PAP IgG antibody responses were detected in both groups ( Figure 5). The IgG antibody responses were higher in the group injected five times (28-day protocol) than in the group that was injected twice (14-day protocol) (p < 0.05) ( Figure 5). The animals (n = 5-6 per group) were randomly assigned to a 14-, 28-or 35-day protocol and were injected ip with 250 µL of 0.02% OVA (0.05 mg) for 2, 5, or 3 times respectively (see Figure 1 for details). The mice were exsanguinated after 14, 28 or 35 days according to the protocol used. Different letters mean statistical differences (p < 0.05) by one-way ANOVA and Tukey's multiple comparison tests. All serum samples were evaluated using ELISA.

Sensitization to Cow's Milk Protein Depends on the Dose and Frequency of Ip Injections
Three protocols of adjuvant-free ip sensitization that differ in the number and frequency of injections were evaluated. Two of the protocols were carried out with three different doses of CMP (14-and 28-day protocols). Regarding the 14-day protocol, no anti-CMP IgE antibodies were detected in the sera of mice that were administered 0.25 mg of CMP. The other two groups (0.025 mg and 0.05 mg) showed weak anti-CMP IgE antibodies responses (Figure 4a). The strongest anti-CMP IgE immune responses were triggered after the ip administration of 0.05 mg and 0.025 mg of CMP, and this occurred in the mice from the 28-day protocol. These responses were higher than those triggered by the groups of mice that underwent the 14-or 35-day protocols (p < 0.001) (Figure 4a). The 35-day protocol failed to trigger an anti-CMP IgE immune response (Figure 4a). The mice that yielded weak or undetectable anti-CMP IgE antibodies were able to trigger an anti-CMP IgG immune response (Figure 4b). The levels of anti-CMP IgE antibodies were evaluated before and after IgG depletion in three groups of mice. The results showed increased anti-CMP IgE antibodies after IgG depletion, but most serum samples that showed undetectable levels of anti-CMP IgE antibodies remained as such after IgG depletion (Figure 4c). In this same series of experiments, the serum levels of anti-CMP IgE antibodies were significantly increased in a group of mice that underwent the 28-day protocol (p < 0.001) (Figure 4c).

A Twenty-Eight Day Protocol with Five Ip Injections Triggers Anti-Pap IgG but Not IgE Antibody Responses in Balb/C Mice
Two ip protocols (14-and 28-day) of sensitization were evaluated. As expected, anti-PAP IgE antibodies were not detected in the sera of the mice, after either the 14-or the 28-day protocols, but strong anti-PAP IgG antibody responses were detected in both groups ( Figure 5). The IgG antibody responses were higher in the group injected five times (28-day protocol) than in the group that was injected twice (14-day protocol) (p < 0.05) ( Figure 5). Groups of mice (n = 5) were injected ip with CMP following either a 14-or 28-day protocol with 2 or 5 ip injections respectively. The presence of anti-CMP IgE antibodies in 14-and 28-day serum samples was evaluated before and after IgG depletion. Different letters mean statistical differences (p < 0.05) by paired t test. All serum samples were evaluated using ELISA. (c) Groups of mice (n = 5) were injected ip with CMP following either a 14-or 28-day protocol with 2 or 5 ip injections respectively. The presence of anti-CMP IgE antibodies in 14-and 28-day serum samples was evaluated before and after IgG depletion. Different letters mean statistical differences (p < 0.05) by paired t test. All serum samples were evaluated using ELISA. Figure 5. Comparison of the 14-and 28-day protocols to trigger an anti-PAP IgE and IgG antibody response in BALB/c mice. Groups of mice (n = 6) were injected ip with 250 μL of 10% PAP. Blood samples were collected either 14 (2 injections) or 28 (5 injections) days after the first injection. The presence of anti-PAP IgE and IgG antibodies was evaluated using ELISA. Different letters mean statistical differences (p < 0.05) by unpaired t test.

Discussion
Mouse models of allergy to a variety of food allergens have been developed [14], but there are no mouse models available to evaluate the inherent sensitizing or allergenic potential of proteins. A model for the evaluation of the previously mentioned potentials requires specific characteristics, such as adjuvant-free conditions, capability to discriminate between commonly allergenic and rarely allergenic proteins, capability to detect allergens that hardly triggers IgE responses under adjuvantfree experimental conditions, and capability to discriminate among common, weak, and rare allergens. Particularly, CMP hardly sensitize mice under adjuvant-free experimental conditions although it is a well-known allergen [15,16]. Contrarily, adjuvant-free protocols to sensitize mice to OVA have been well-documented [11,14,17,18]. In this study, BALB/c mice were used to assess the sensitizing potentials of two commonly allergenic proteins (OVA and CMP) and one rarely allergenic protein (PAP). Two previously published protocols of ip sensitization were followed in detail [8,9,11]. An additional 35-day protocol of ip sensitization was evaluated for comparative purposes, but no anti-CMP IgE immune responses were triggered in the mice that underwent this protocol. These results highlight that the source of allergen is of particular relevance for the evaluation of an animal model for assessing the inherent sensitizing or allergenic potential of proteins.
Previous studies have shown that a 14-day protocol with two ip injections can distinguish commonly allergenic from rarely allergenic proteins [17,18]. However, in these studies the IgE immune response was evaluated by passive cutaneous anaphylaxis assays, an assay that in our hands is technically demanding and difficult to implement. Alternatively, a 28-day protocol to evaluate the allergenic potential of proteins has been proposed [11]. The authors claim that the 28-day protocol triggers more robust IgE immune responses than the 14-day using the reference standard OVA [11] and, notably, the anti-OVA IgE antibodies produced could be readily detected using ELISA. Our results highlight that BALB/c mice that underwent the 28-day protocol with five ip injections and OVA doses of 0.05 mg triggered significantly higher anti-OVA IgE responses than the 14-day protocol with two ip injections. Furthermore, the 28-day protocol not only triggers robust IgE immune responses, but also can discriminate between commonly allergenic and rarely allergenic proteins, such as OVA and PAP respectively. Therefore, our data support the notion that the 28-day protocol

Discussion
Mouse models of allergy to a variety of food allergens have been developed [14], but there are no mouse models available to evaluate the inherent sensitizing or allergenic potential of proteins. A model for the evaluation of the previously mentioned potentials requires specific characteristics, such as adjuvant-free conditions, capability to discriminate between commonly allergenic and rarely allergenic proteins, capability to detect allergens that hardly triggers IgE responses under adjuvant-free experimental conditions, and capability to discriminate among common, weak, and rare allergens. Particularly, CMP hardly sensitize mice under adjuvant-free experimental conditions although it is a well-known allergen [15,16]. Contrarily, adjuvant-free protocols to sensitize mice to OVA have been well-documented [11,14,17,18]. In this study, BALB/c mice were used to assess the sensitizing potentials of two commonly allergenic proteins (OVA and CMP) and one rarely allergenic protein (PAP). Two previously published protocols of ip sensitization were followed in detail [8,9,11]. An additional 35-day protocol of ip sensitization was evaluated for comparative purposes, but no anti-CMP IgE immune responses were triggered in the mice that underwent this protocol. These results highlight that the source of allergen is of particular relevance for the evaluation of an animal model for assessing the inherent sensitizing or allergenic potential of proteins.
Previous studies have shown that a 14-day protocol with two ip injections can distinguish commonly allergenic from rarely allergenic proteins [17,18]. However, in these studies the IgE immune response was evaluated by passive cutaneous anaphylaxis assays, an assay that in our hands is technically demanding and difficult to implement. Alternatively, a 28-day protocol to evaluate the allergenic potential of proteins has been proposed [11]. The authors claim that the 28-day protocol triggers more robust IgE immune responses than the 14-day using the reference standard OVA [11] and, notably, the anti-OVA IgE antibodies produced could be readily detected using ELISA. Our results highlight that BALB/c mice that underwent the 28-day protocol with five ip injections and OVA doses of 0.05 mg triggered significantly higher anti-OVA IgE responses than the 14-day protocol with two ip injections. Furthermore, the 28-day protocol not only triggers robust IgE immune responses, but also can discriminate between commonly allergenic and rarely allergenic proteins, such as OVA and PAP respectively. Therefore, our data support the notion that the 28-day protocol is more suitable than 14-day to develop a BALB/c mouse model to evaluate the inherent sensitizing or allergenic potential of proteins.
To corroborate our data with previous findings, the three protocols were carried out utilizing CMP. This commonly allergenic protein was chosen because there is scarce information describing adjuvant-free protocols to sensitize mice to CMP [14]. Previous studies have shown that a six-week-transdermal sensitization protocol is effective to sensitize BALB/c mice to CMP under adjuvant-free conditions [15]. Others have shown that BALB/c mice can be sensitized to CMP without the use of adjuvants after ip injections, but the mice have to be born and grew up in germ-free conditions [16]. The 28-day protocol has the advantages of being shorter than the six-week-transdermal sensitization procedure, and that BALB/c mice can be sensitized after ip injections without the need of germ-free animal facilities. Furthermore, our results show that the 28-day protocol can detect allergens that hardly trigger IgE immune responses under adjuvant-free experimental conditions. Most notably, the IgE responses are robust in a dose dependent manner and are readily detected using ELISA. Overall, the findings highlight a critical role for the dose of allergen, as well as the number and frequency of immunizations, to successfully sensitize BALB/c mice to food proteins, as stated by others [16,19].
Additionally, to show that the undetectable serum levels of anti-CMP IgE antibodies from the 14-day protocol mice were not due to IgG masking of epitopes [20,21], the serum levels of anti-CMP IgE antibodies were evaluated after IgG depletion. After the depletion treatment, anti-CMP IgE antibodies remained undetectable in most serum samples. Contrary, serum samples with detectable levels of anti-CMP IgE antibodies significantly increased the level of detection after IgG depletion showing that IgG masking of epitopes negatively impact on the detection of allergen-specific IgE antibodies.
Animal models have been widely used to evaluate the immune response to antigens in health and disease. The mouse seems to be the animal model of choice to evaluate the inherent sensitizing and allergenic potential of proteins, largely due to the availability of many mouse-specific immunological reagents, their short generation time, the possibility of large experimental groups of animals, and the low cost of purchase and maintenance [22]. Furthermore, it has been reported that the overall structure of the mouse immune system is quite similar to humans [23]. Certainly, the genetic background of each mouse strain has a close association with the type and intensity of the immune response they trigger after antigen exposure, and this characteristic should be taken into account in the search of a mouse model to evaluate the inherent sensitizing or allergenic potential of food proteins [24]. Notably, the BALB/c mouse strain is considered to favor type 2 immune responses with atopic-like phenotype) [8,9,25,26]. Thus, this mouse strain has been widely used in the search for a validated murine model to evaluate the sensitizing or allergenic potential of proteins [4,5,8,9,11].
We should acknowledge that our study has some limitations. Firstly, the anti-IgG immune responses using the 35-day protocol were evaluated in four mice only, and groups of a minimum of five mice have been suggested to evaluate the allergenic potential of food proteins [27]. Furthermore, due to the inter-individual variability in the immune responses, more than six mice should be tested. This consideration should be taken into account in future studies. Secondly, weak allergens were not tested in this study although the results justify their evaluation. Further studies to demonstrate the capability of the 28-day protocol to discriminate between strong and weak allergens are warranted. Thirdly, our data do not support an explanation about the reasons why the 14-day protocol efficiently sensitizes to OVA, but not to CMP. Despite the previous, the results highlight that the 28-day protocol with five ip immunizations triggers a robust IgE immune response that is readily detected using ELISA, can differentiate between commonly allergenic and rarely allergenic proteins, and can detect allergens that hardly trigger IgE immune responses under adjuvant-free experimental conditions. Therefore, the 28-day protocol could be used as an animal model to evaluate the inherent sensitizing or allergenic potential of naturally occurring proteins, biotechnology-derived proteins, or the impact of food processing on the allergenic potential of proteins.

Conclusions
An adjuvant-free 28-day ip sensitization protocol with five immunizations and doses of 0.05 mg of OVA or CMP is suitable to trigger an IgE immune response detectable by ELISA in BALB/c mice. Notably, the protocol failed to trigger IgE immune responses, but not IgG, to rarely allergenic proteins such as PAP. Thus, the adjuvant-free 28-day protocol could be a useful tool to evaluate the inherent sensitizing or allergenic potential of proteins in BALB/c mice. Inter-laboratory studies with a larger number of common, weak, and rare allergens should be carried out to validate this model.