- Academic Editor
†These authors contributed equally.
Background: Oral cancer is the 17th most common cancer worldwide, with
a mortality rate of 1.8%. Their incidence varies considerably, with a
clear prevalence in South Asian countries. In Africa, the mortality rate for
cancers of the oral cavity is 1.3%. Senegal is a perfect illustration a perfect
illustration of the seriousness and scale of this disease, with 177 new cases
recorded in 2020, for a mortality rate of 1.4%. To add to the knowledge of the
molecular mechanisms involved in the carcinogenesis of these pathologies in
Senegal, mutations in the C-MYC proto-oncogene were examined in 22
patients with oral cavity cancers and compared with samples from 32 control
individuals. Methods: Cancerous tissue (CT) and adjacent normal tissue
(ANT) were sampled from diseased individuals, whereas whole blood was obtained
from control individuals (C). A total of 67 samples were collected: 32 from
controls, 22 from CTs, and 13 from ANTs of diseased individuals. Total DNA was
extracted and polymerase chain reaction (PCR) amplification of exon 2 of the
C-MYC gene was performed, followed by Sanger sequencing. Mutation
analysis was performed using Mutation Surveyor Software v5.0.1. The effect of
each non-synonymous mutation on the function of the encoded protein was
determined using the POLYPHEN-2, PANTHER-PSEP, and PROVEAN algorithms. The
probability of non-synonymous mutations causing diseases was predicted using
Prediction of human Deleterious Single Nucleotide Polymorphism (PhD-SNP) and
Predicting disease associated variations using GO terms (SNP&GO). The impact of
non-synonymous variations on the stability of the encoded protein was determined
using I-Mutant2 and In-silico analysis of Protein Stability (INPS).
Results: Of the study participants, 63% were females. The mean age of
patients was 46.43
Oral cavity cancers account for 3% of malignant tumors and 30% of upper digestive tract cancers [1]. They are head and neck squamous cell carcinomas, which are one of the main causes of death [2]. Malignant neoplasms occur in the structures or tissues of the mouth [3].
Oral cancer is the 17th most common cancer worldwide, with a mortality rate of 1.8% [4]. Large geographical variations in the incidence of these pathologies have been noted, with two-thirds of the cases identified in developing countries [5]. The highest incidence rates of oral cancer are observed in South and Southeast Asia (Sri Lanka, India, Pakistan, Bangladesh, and Taiwan), Western and Central Europe (France, Spain, Hungary, and Slovakia), Latin America, the Caribbean (Brazil and Uruguay), and parts of the Pacific (Melanesia) [6, 7]. In Africa, the mortality rate of these pathologies is 1.3%. Senegal is an appropriate illustration of the seriousness of these diseases, with 177 new cases reported in 2020, and a mortality rate of 1.4% [4].
The main risk factors for the occurrence of oral cavity cancers are alcohol and
tobacco consumption whose effects are synergistic [8] without additives [9].
Tobacco and betel nut consumption are considered as causes of oral cancers in the
Pacific and South Asia [10]. In Europe and the United States,
Although the oral cavity is easily accessible for direct visual examination, most cancers in the oral cavity are diagnosed at an advanced stage (stage III or IV) and are associated with a poor prognosis (less than 5 years of survival) [19]. Genetically, many independent studies have suggested the involvement of some genes, including proto-oncogenes, in the development and progression of numerous cancers often associated with poor prognosis [20]. C-MYC, which belongs to the MYC family and is located on chromosome 8q24.21, is one of the most frequent proto-oncogenes involved in human carcinogenesis [21]. This study aimed to determine the mutational profile of C-MYC proto-oncogene in oral cavity cancer in Senegal.
A total of 22 elderly patients with primary oral cancer and 32 control individuals were enrolled in this study. Patients were recruited after informed consent was obtained from the Department of Stomatology and Maxillofacial Surgery at Aristide Le Dantec Hospital. Cancerous tissues (CT) and adjacent normal tissues (ANT) were collected from patients during surgery, whereas whole blood samples were obtained from control individuals (C). A total of 67 samples were collected, including 32 from the controls (C), and 22 CTs and 13 ANTs from patients. In this study, the inclusion criteria for patients were as follows: Senegalese nationality, diagnosis of primary cancer of the oral cavity and signature of the information and informed consent form. Patients whose cancer was a recurrence of a previous cancer and those who declined the informed consent form were excluded from the study. For controls, the inclusion criteria were: non-cancer patients, patient companions, medical staff or any other person volunteering to participate in the study. Individuals who had once been diagnosed with cancer in previous years, even if cured, and those with benign tumours in the mouth were excluded from the control cases.
DNA was extracted using a Zymo Research kit (ZymoBIOMICS DNA & RNA kits, Zymo
Research, Orange County, CA, USA) according to the manufacturer’s protocol. Exon
2 was amplified using the One Taq 2X Master Mix (New England Biolabs, Ipswich, MA, USA)
kit in a reaction volume of 25 µL. The reaction mixture comprised 2
µL of cDNA, 10.375 µL of water, 5 µL of 5X buffer, 0.5 µL
of each primer (5
The obtained sequences were checked, corrected, and aligned using BioEdit
v7.0.5.3 software (Rutherford house, Manchester, UK) [22] and ClustalW multiple
alignment algorithm [23]. To determine the mutations in C-MYC, the
chromatograms obtained after sequencing were input into Mutation Surveyor v5.0.1
software (Softgenetics, State College, PA, USA) [24] and compared with a
reference sequence available on NCBI (NG_007161.2). The effect of each
non-synonymous mutation on the function of the encoded protein was determined
using Polymorphism Phenotyping v2 (POLYPHEN-2) [25], Position-Specific
Evolutionary Preservation of Protein Analysis THrough Evolutionary (PANTHER-PSEP)
[26], and Protein Variation Effect Analyzer (PROVEAN) [27] algorithms. The
probability that non-synonymous substitutions cause disease was determined using
PhD-SNP [28] and SNP&GO [29], which predicted whether the mutations were neutral
(score
To estimate diversity and genetic variability, we determined the total number of sequences without gaps (N), sample size (n), number of invariable sites (c), number of variable non-informative and informative sites (Pi), the total number of mutations (Eta), nature of mutations (s) and (v), mutation rates (R), and types of substitution (Ks) and (Kns). These parameters were determined using DNA sequence polymorphism (DNAsp) v5.10.01 (Barcelona University, Spain) [31] and Molecular Evolutionary Genetics Analysis (Mega) v7.0.14 [32] software. The haplotypic diversity (hd) and nucleotide diversity (Pi) were estimated using DNAsp v5.10.01 [31].
To soften their frequencies, nucleotide sequences were converted into amino acid sequences using Mega v7.0.14 [32] software.
Genetic differentiation was estimated using Nei intra and interpopulation genetic distances obtained using Mega v7.0.14 [32] software. The genetic differentiation factor (Fst) that gives the values for the degree of differentiation between controls, ANTs, and CTs, as well as the degree of differentiation based on the epidemiological factors were obtained using Arlequin v3.5.1.3 (Zoological Institute, University of Berne, Switzerland) [33]. This software was also used to determine the distribution of genetic variability at intra- and interpopulation levels using the Analysis of Molecular Variation (AMOVA) test.
The Z-test of selection was evaluated by selecting the starting hypothesis that exon 2 of C-MYC was under positive selection using the Tumura 3-parameter model and the complete deletion method on Mega v7.0.14 [32].
The study population comprised 54 patients (63% women and 37% men). The mean
age of patients was 46.43
Analysis of the chromatograms using the reference sequence revealed four
mutation spots in our population study, including one spot with a score
Individuals | Mutations | Position | Nature | p. AA | Status | Score |
CT17 | G2793GA | 245 | Transition | Q48QQ | Heterozygous | 33.68 |
ANT17 | G2793GA | 245 | Transition | Q48QQ | Heterozygous | 23.06 |
AA, amino acid.

Heterozygous SNP identified. SNP, Single Nucleotide Polymorphism.
The assessment of the possible modifications using BioEdit revealed the existence of substitutions at T15G and T23G in individual T5; G8A, T15G, and T23A in individual T8; and C10A in individual T9. The analysis performed using the pathogenic test software showed that these nonsynonymous substitutions were damaging, pathogenic, and might decrease the stability of the gene encoded in these individuals (Table 2).
Mutations | G8A | C10A | T15G | T23A | T23G |
p.AA | D31N | D31E | V33G | Y36N | Y36D |
Prediction of the structure and function of the encoded protein | |||||
Protein Variation Effect Analyzer (PROVEAN) prediction | Deleterious | Deleterious | Deleterious | Deleterious | Deleterious |
Polymorphism Phenotyping v2 (POLYPHEN-2) prediction | Benign | Potentially damaging | Potentially damaging | Potentially damaging | Potentially damaging |
Position-Specific Evolutionary Preservation of Protein Analysis THrough Evolutionary (PANTHER-PSEP) prediction | Potentially damaging | Potentially damaging | Potentially damaging | Potentially damaging | Potentially damaging |
Conclusion | Damaging | Damaging | Damaging | Damaging | Damaging |
Probability that mutations cause the disease | |||||
Prediction of human Deleterious Single Nucleotide Polymorphism (PhD-SNP) prediction | Pathogenic | Pathogenic | Pathogenic | Pathogenic | Pathogenic |
Predicting disease associated variations using GO terms (SNP&GO) prediction | Pathogenic | Pathogenic | Pathogenic | Pathogenic | Pathogenic |
Conclusion | Pathogenic | Pathogenic | Pathogenic | Pathogenic | Pathogenic |
Prediction of the stability of the encoded protein | |||||
I-MUTANT prediction | Decreasing | Decreasing | Decreasing | Decreasing | Decreasing |
In-silico analysis of Protein Stability (INPS) prediction | Decreasing | Decreasing | Decreasing | Decreasing | Decreasing |
Conclusion | Decreasing | Decreasing | Decreasing | Decreasing | Decreasing |
Based on the results, the sequences had the same number of sites (433 pb), more than 99% of which were conserved in controls (429), ANTs (432), and CTs (432). In the controls, the percentage of transversions (81.28) was higher than that of transitions (18.72), which correlated with the R-value (0.221). However, in the ANTs and CTs, the percentage of transitions (99.6%) was higher than that of transversions (0.4%). The non-synonymous substitution Kns (0.01) was higher than the synonymous substitution, Ks (0.02), in controls. In the ANTs and CTs, the non-synonymous substitution, Kns (0), was equal to the synonymous substitution Ks (0) (Table 3).
Parameters | Populations | ||
Controls | Cancerous Tissue (CT) | Adjacent Normal Tissue (ANT) | |
Number of sites | 433 | 433 | 433 |
Sample size | 19 | 21 | 12 |
Monomorphic sites (c) | 429 | 432 | 432 |
Polymorphic sites (v) | 4 | 1 | 1 |
Non-informative polymorphic sites (s) | 3 | 1 | 1 |
Informative polymorphic sites (Pi) | 1 | 0 | 0 |
%transition (s) | 18.72 | 99.6 | 99.59 |
%transversion (t) | 81.28 | 0.4 | 0.41 |
Mutation rates (R) | 0.221 | 236.855 | 236.884 |
Synonymous substitutions (Ks) | 0.002 | 0 | 0 |
Nonsynonymous substitutions (Kns) | 0.01 | 0 | 0 |
The C-MYC proto-oncogene displayed low haplotype diversity (0.184) and low nucleotide diversity (0.00070). Low haplotype and nucleotide diversity were also noted in the controls, ANT and CT, with the highest values found in the controls (0.298 and 0.00142) (Table 4).
Populations | Parameters | |
Hd | Pi | |
Controls | 0.298 | 0.00142 |
CT | 0.095 | 0.00022 |
ANT | 0.167 | 0.00038 |
Overall | 0.184 | 0.00070 |
C, control; CT, cancerous tissue; ANT, adjacent normal tissue.
Transcription performed with the second frame reading revealed a significant increase in aspartic acid (8.99), valine (4.09), and tyrosine (4.09) levels in CTs and ANTs. However, significant decreases in glutamic acid (6.98), glycine (6.32), and asparagine (2.85) levels were observed in these populations (Table 5).
Amino acid | Controls | CT | ANT | p-value |
Ala | 6.3 | 6.3 | 6.3 | |
Cys | 2.777777778 | 2.777777778 | 2.777777778 | |
Asp | 8.99122807 | 9.027777778 | 9.027777778 | 2.81 |
Glu | 6.980994152 | 6.944444444 | 6.944444444 | 9.243 |
Phe | 5.555555556 | 5.555555556 | 5.555555556 | |
Gly | 6.323099415 | 6.3 | 6.3 | 2.272 |
His | 0 | 0 | 0 | |
Ile | 4.166666667 | 4.166666667 | 4.166666667 | |
Lys | 4.166666667 | 4.166666667 | 4.166666667 | |
Leu | 7.638888889 | 7.638888889 | 7.638888889 | |
Met | 2.083333333 | 2.083333333 | 2.083333333 | |
Asn | 2.850877193 | 2.777777778 | 2.777777778 | 9.243 |
Pro | 7.638888889 | 7.638888889 | 7.638888889 | |
Gln | 7.638888889 | 7.638888889 | 7.638888889 | |
Arg | 2.777777778 | 2.777777778 | 2.777777778 | |
Ser | 11.11111111 | 11.11111111 | 11.11111111 | |
Thr | 3.472222222 | 3.472222222 | 3.472222222 | |
Val | 4.093567251 | 4.166666667 | 4.166666667 | 1.432 |
Trp | 1.388888889 | 1.388888889 | 1.388888889 | |
Tyr | 4.093567251 | 4.166666667 | 4.166666667 | 1.43 |
Estimation of the genetic distance within each population revealed that the
controls had a low genetic distance (0.001). This genetic distance was zero in
ANTs and CTs (0
Distance | Populations | ||||||
Intrapopulation | Controls | 0.001 | Interpopulation | Controls | CT | ANT | |
CT | 0 | Controls | - | 0.01 | 0.001 | ||
ANT | 0 | CT | 0.001 | - | 0 | ||
ANT | 0.001 | 0 | - |
Based on the genetic differentiation factor (Fst), no statistically
significant genetic difference in C-MYC (p
AMOVA | Fst | ||||||
Intrapopulation | Interpopulation | Populations | Controls/CT | Controls/ANT | CT/ANT | ||
Controls | 2.78 | Controls/ANT | 97.12 | ||||
ANT | 0.37 | Controls/CT | 99.63 | Fst | 0.028 | 0.003 | –0.058 |
CT | 5.81 | ANT/CT | 105.81 | p-value | 0.145 | 0.386 | 1 |
AMOVA, Analysis of Molecular Variation.
Factors | AMOVA | Fst | p-value | ||
Intrapopulation | Interpopulation | ||||
Sex | Male | 2.15 | 97.85 | 0.02145 | 0.15287 |
Female | |||||
Gender | Young ( |
4.86 | 95.14 | 0.04856 | 0.14366 |
Intermediate (40–70) | |||||
Old ( | |||||
Tobacco cons. | Yes | 5.22 | 94.78 | 0.05217 | 0.10683 |
No | |||||
Alcohol cons. | Yes | –13.22 | 113.22 | –0.13220 | 1.00000 |
No |
The non-significant p-value of the Z-test for the selection indicated that exon 2 of C-MYC proto-oncogene followed neutral evolution in CTs and ANTs. In contrast, the significant p-value under the hypothesis of positive selection (0.048) and non-significant p-value under the neutrality hypothesis (1) and negative selection (1) indicate that exon 2 of C-MYC protooncogene is under positive selection in the controls (Table 9).
Population | Z-Test of selection | ||
Neutrality | Positive selection | Negative selection | |
Controls | 0.095 | 0.048 | 1 |
CT | 0.336 | 1 | 0.163 |
ANT | 0.325 | 1 | 0.152 |
The study population predominantly consisted of female patients (63%) who were
non-alcoholics or nonsmokers, with a sex ratio of 0.59. This characteristic is
comparable to that of the study by Toure et al. [34] in Senegal, as 60%
of their study population was female patients who did not smoke or drink alcohol.
This characteristic is similar to that reported by Bambara et al. [35],
who reported a similar predominance (sex ratio of 0.55) in their Ouaguadougou
cohort with a small number of alcoholics and smokers. Mbaye et al. [36]
reported similar values (62%) in their study without the involvement of alcohol
and tobacco consumption. The frequent feminization of this disease matches the
increased risk of nontoxin-induced carcinoma in these patients. However, Varenne
et al. [37] suggested that poor oral hygiene could play an
important role in the occurrence of oral cavity cancers in women, as they
revealed that the average number of carious teeth, missing teeth, and filled
teeth was 6.1, with higher values in women than in men (8 vs 4.4;
p
In the present study, the mean age of occurrence of oral cancers was 46.43
Based on our findings, more than half of the oral cavity cancer cases (80%) were diagnosed as stage III or IV disease in Senegal. Advanced histoprognostic stages have also been reported by some Western authors, including Liu et al. [43] and Lin et al. [13]. The low socioeconomic level that compromises access to oral healthcare has often been implicated [44]. In a study conducted in Ouagadougou in 2015, Bambara et al. [35] found that the long delay in consultation (18 months on average), which is partially related to the low attendance to oral health care, could explain the high proportion of patients with advanced-stage disease, while prognosis is strongly related to the delay in diagnosis. Many reasons could explain this delay, including the trivialization of some symptoms (otalgia and discomfort of chewing) despite their persistence, absence of initial pain, use of traditional medicine first, and difficulty in accessing specialized services [11].
A low rate of polymorphism in the C-MYC proto-oncogene was found in our study population. Such finding suggests that the C-MYC proto-oncogene is not involved in the occurrence of oral cavity cancers in Senegalese patients. However, other authors have revealed the involvement of C-MYC protooncogene mutations in some pathologies, including Johnson [45], who showed that nearly 50% of Burkitt’s lymphomas had C-MYC mutations, and Xu-Monette et al. [46], who found C-MYC mutations in 33% of Diffuse Large B-cell Lymphoma samples. Our results highlight the existence of a single mutation (G2793GA) corresponding to the synonymous substitution, Q48Q. This variation is described as a somatic polymorphism, because it is present in both ANTs and CTs of the same individual. This result shows that it is not possible to have normal tissue in the oral cavity once cancer occurs because the oral cavity is a restricted area.
The substitutions found in the controls were predicted to be damaging and pathogenic (could cause the disease) and might decrease the stability of the encoded protein in these individuals. The functional importance of these substitutions and their involvement in carcinogenesis remain to be elucidated.
The analysis of basic parameters revealed a strong presence of conserved sites (432/433) and missing informative polymorphic sites (0) in CTs and ANTs. Such finding confirmed the hypothesis that the C-MYC proto-oncogene is not subject to mutations in oral cavity cancer in Senegal. Genetic diversity analysis revealed a low haplotype diversity (Hd) and low nucleotide diversity (Pi) in the controls compared with ANTs and CTs but with clear superiority in the controls. Overall, the synonymous substitution rate was equal to the non-synonymous substitution rate, and C-MYC mutations can be deduced to impose few constraints on the encoded proteins. This hypothesis was confirmed by the Z-test of selection, which was statistically non-significant in our study population, indicating the existence of negative selection tending to eliminate nonsynonymous mutations. In contrast, in the controls, the non-synonymous substitutions (Kns) were higher than the synonymous substitutions (0.01) (0.002). Accordingly, we can deduce that somatic mutations involve amino acid changes. These mutations are no longer eliminated by natural elimination processes (splicing, excision, and ligation), which prevent correction of the mutated genes and consequently eliminate the truncated protein in these individuals. These results align with the significant p-value (0.048) under the hypothesis of positive selection in the controls. In this group of controls, some individuals (T5, T8, and T9) should undergo medical follow-up.
A significant increase in the levels of aspartic acid (Asp), valine (Val), and tyrosine (Tyr) was observed in the CTs and ANTs. This increase was associated with a significant decrease in glycine (Gly), asparagine (Asn), and glutamic acid (Glu). Notably, Glu and Gly, which were significantly decreased, are non-essential amino acids (can be synthesized by the body). Recent studies have shown that several non-essential amino acids (e.g., GLU, Ser, and Gly) play important roles in cancer metabolism [47]. Moreover, an increase in valine, an essential amino acid, suggests that the nutrition of tumor cells is influenced by the nutrition of their host [3].
Of all the epidemiological factors considered in this study, no genetic differentiation was found. Thus, there was no genetic differentiation between tumors due to epidemiological factors. Instead, each case was found to be unique at the molecular level.
Oral cavity cancers remain one of the most common and widespread cancers worldwide and constitute a real public health problem. Our study has shown that Senegal is a perfect illustration of the seriousness and extent of this disease. In fact, the majority of patients presenting stage III and IV tumors with lymph node invasion testify the delay in the detection and early diagnosis of these pathologies. We attempted to use a population genetics approach to relate the C-MYC protooncogene mutations with the occurrence and progression of oral cavity cancers in Senegal. However, the results obtained invalidate our initial hypothesis that C-MYC mutations were involved in the onset and progression of these diseases in Senegalese patients. Mutation studies revealed a low rate of polymorphism of the C-MYC in our study population, with the existence of one mutation corresponding to the synonymous substitution, Q48Q which shows that it is not possible to have normal tissue in the oral cavity once cancer occurs because the oral cavity is a restricted area. Moreover, there was no association between the genetic structure and epidemiological factors such as age, sex, alcohol consumption, tobacco consumption, and tumor stage. Nevertheless, the nonsynonymous substitutions noted in the controls could provide new markers for the early clinical diagnosis of oral cavity cancers. The functional significance of these mutations found and their involvement in carcinogenesis need to be studied in more detail to determine how C-MYC has been altered. In addition, further study of other genetic alteration pathways including gene expression could provide useful information on the role of the C-MYC proto-oncogene in the development of oral cancers in Senegal.
These data analyzed during the current study are available from the corresponding author on reasonable request.
DB, FM, HD and MS conceived, designed, analysed, wrote and edited the article. MDS, MMN and ST collected samples. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
The patients and control subjects provided signed, informed consent and the study was approved by the University Cheikh Anta Diop Research Ethics committee (Reference: /2018/CER/UCAD).
The authors acknowledge the genomics laboratory of the Department of Animal Biology, Faculty of Science and Technology, Cheikh Anta Diop University, Dakar.
This research received no external funding.
The authors declare no conflict of interest.
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