|Year : 2016 | Volume
| Issue : 1 | Page : 58-61
Bioinformatic analysis of c-Myc target from laryngeal cancer cell gene of laryngeal cancer
Wei-Dong Zhang1, He-Xin Chen2, Yun-Xia Wang3, Zhi-Ping Chen4, Zhong-Jie Shan1, Guang Xu1
1 Department of Otorhinolaryngology, People's Hospital of Zhengzhou, Henan, Henan Province, China
2 Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat Sen University, Guangdong, China
3 Department of Stomatology, People's Hospital of Zhengzhou, Henan, Henan Province, China
4 Department of Radiology, Children's Hospital of Zhengzhou, Henan Province, China
|Date of Web Publication||13-Apr-2016|
No. 33, Huanghe Road, Zhengzhou, Henan Province
Source of Support: None, Conflict of Interest: None
Aim of Study: The aim was to explore the structure and functions of new target spot c-Myc target from laryngeal cancer cell. (MTLC) of c-Myc gene.
Methods: This study adopted bioinformatic methods to analyze the physicochemical property, secondary structure, hydrophobic region, a transmembrane region, and prediction of functions.
Results: The results showed that the whole length of the open reading frames was 708 bp, coding was 235 amino acids. This protein was a basic protein possessed two transmembrane structures and weight was about 26592.5 Da. The main elements of secondary structure were alpha-helix and random coil. MTLC was a membrane constitutive protein that possessed signal transduction and regulation may locate on karyotheca as results of subcellular localization and function prediction.
Conclusion: This study has provided the theoretical basis for the further discussion of the effect and mechanism of action of MTLC in the occurrence of laryngeal cancer.
Keywords: Bioinformatics analysis, c-Myc, laryngeal cancer, c-Myc target from laryngeal cancer cell, structure and function
|How to cite this article:|
Zhang WD, Chen HX, Wang YX, Chen ZP, Shan ZJ, Xu G. Bioinformatic analysis of c-Myc target from laryngeal cancer cell gene of laryngeal cancer. J Can Res Ther 2016;12:58-61
|How to cite this URL:|
Zhang WD, Chen HX, Wang YX, Chen ZP, Shan ZJ, Xu G. Bioinformatic analysis of c-Myc target from laryngeal cancer cell gene of laryngeal cancer. J Can Res Ther [serial online] 2016 [cited 2019 Nov 16];12:58-61. Available from: http://www.cancerjournal.net/text.asp?2016/12/1/58/146083
| > Introduction|| |
Laryngeal cancer is a common malignant tumor in upper respiratory tract with the proportion of 1-8.4% of the malignant tumors in the whole body. Though the current therapies, such as operation, chemotherapy and radiotherapy, can alleviate the suffering of patients to different degrees, there are severe dysfunction and local deformity after treatment, which seriously threatens the patients' health., Genetic studies found that there were oncogenes such as ras, c-Myc, epidermal growth factor receptor, PRAD, Int-2, c-Myc target from laryngeal cancer cell (MTLC), and anti-oncogenes such as p53, Rb, p16, FHIT, both of which were related to the event of laryngeal cancer. Moreover, the latest research verified that MTLC was a target gene of c-Myc with similar structure and biological functions, such as inhibiting cell growth and promoting cell apoptosis and so on. Furthermore, it could control and promote the growth and apoptosis of Hep2 cell. At present, there are relatively few studies of MTLC gene in occurrence of laryngeal cancer, especially the dimmer mechanism of actions in that of laryngeal cancer. The study adopted bioinformatic methods and began with the gene sequences of MTLC, to predict and analyze the physicochemical property, molecule structure and function of this gene to provide a theoretical basis for the further discussion of its effect in the occurrence and development of the tumors like laryngeal cancer.
| > Subjects and Methods|| |
The sequences of the gene of MTLC were from Genbank (accession number: AF527367). Amino acid sequence of the gene was obtained through DANMAN software (Lynnon Biosoft Co., USA); physicochemical properties such as the amino acid composition, molecular weight, and isoelectric point of MTLC gene were analyzed using the ORF online software (National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, USA) of NCBI, which combined with Prot Parma online study in Expasy website; the hydrophobicity and transmembrane region were analyzed, respectively, by ProtScale system (The SIB Swiss Institute of Bioinformatics, Swiss) and TMHMM Server V.2.0 system (Technical University of Denmark, Denmark); signal peptide of protein-encoding were analyzed by SingnalP4.1server (Technical University of Denmark, Denmark); sub-cells were localized by ProtComp v. 9.0; Hopfield neural net was used to make secondary structure prediction; Functions of proteins were predicted by Protfun software (Technical University of Denmark, Denmark).
| > Results|| |
Analysis of physicochemical properties of c-Myc target from laryngeal cancer cell
ORF prediction and Bioedit analysis showed the full length of MTLC gene was 708 bp, encoding 235 amino acids [Figure 1]. Prot Param predicted that MTLC protein was a sort of basic protein, which the molecular weight was 26592.5 Da, theoretical isoelectric point was 9.88, the content of serine was the most that can even be 16.2% of the total components, basic amino acids were more than acidic amino acids, and instability index was 64.24.
|Figure 1: ORF analysis of human c-Myc target from laryngeal cancer cell (MTLC) gene sequence. (Note: ORF prediction and Bioedit analysis showed the full length of MTLC gene was 708 bp, encoding 235 amino acids)|
Click here to view
Prediction of hydrophobic region and transmembrane region of c-Myc target from laryngeal cancer cell
ProtScale program (The SIB Swiss Institute of Bioinformatics, Swiss) (http://www.expasy.ch/tools/protscale.html/) was chosen to analyze the protein hydrophobicity of MTLC amino acid sequence based on Kyte–Doolittle method (Hphob.). The ordinate represented the hydrophobic score. According to the dividing value was 0, the higher the score was, the stronger the hydrophobicity was. The abscissa represented the location of amino acids. The results of hydrophobicity analysis are shown in [Figure 2]. The consequences indicated that MTLC protein had two obviously regions with strong hydrophobicity, located in 1–100 residue region, whereas the 100-235aa region of the protein showed remarkable amphipathy.
|Figure 2: Analysis of hydrophobicity of c-Myc target from laryngeal cancer cell encoded protein. (Note: The ordinate represented the hydrophobic score. According to the dividing value was 0, the higher the score was, the stronger the hydrophobicity was. The abscissa represented the location of amino acids. The consequences indicated that MTLC protein had two obviously regions with strong hydrophobicity, located in 1–100 residue region whereas the 100–235aa region of the protein showed remarkable amphipathy)|
Click here to view
TMHMM Server V.2.0 system was adopted to examine the transmembrane region of MTLC sequence, and the results showed that there were two transmembrane helical domains, respectively, located in the 26-48th amino acid residue and 68-90th residue. [Figure 3]. These transmembrane regions were the effects of the combination of strong hydrophobicity of the amino acid and the presence of the lipid bilayer.
|Figure 3: Probability of finding a transmembrane region for c-Myc target from laryngeal cancer cell sequence. (Note: The results showed that there were two transmembrane helical domains, respectively, located in the 26-48th amino acid residue and 68-90th residue)|
Click here to view
Analysis of c-Myc target from laryngeal cancer cell protein signal peptide
Signal peptide is a short peptide sequence consists of 3–60 amino acids. It is the identification signal leading the new synthesized protein to their destination, and it is also called target signal. SignalP 4.1 Server tool was adopted to predict the human MTLC signal peptide, as shown in [Figure 4]. The 51st asparaginate residue had the highest C-score (cleavage site score) and the highest Y-score (combined cleavage site score). The 50th asparaginate residue possessed the highest S-score (signal peptide score). As the highest value among the three, the sequences of the signal peptide did not exist in the sequences of protein by the analysis of SignalP4.1 Server. As a result, the MTLC protein was nonsecretory protein.
|Figure 4: Prediction of amino acids sequences signal peptide of c-Myc target from laryngeal cancer cell encoded products. (Note: The 51st asparaginate residue had the highest C-score (cleavage site score) and the highest Y-score (combined cleavage site score). The 50th asparaginate residue possessed the highest S-score (signal peptide score). As the highest value among the three, the sequences of the signal peptide did not exist in the sequences of protein by the analysis of SignalP4.1 Server. As a result, the MTLC protein was nonsecretory protein)|
Click here to view
Prediction of secondary structure
Hopfield neural network was adopted to predict the secondary structure of MTLC protein [Figure 5], [Table 1]. The results indicated that there were three forms of protein's secondary structure: Alpha-helix, extended strand, and random coil. Random coil had the biggest proportion (51.17%), which centralized from 90 to 220 amino acid residue. Alpha-helix was the secondary main structure of the protein, centralized within 0–90 amino acid residue, which was similar to the position of the transmembrane region, and the proportion was 41.36%.
|Figure 5: The prediction of secondary structure of c-Myc target from laryngeal cancer cell coding production by Hopfield neural network. (Note: Abscissa represented the sequence number of amino acid; ordinate represented the possibility of amino acids' owner structures; blue, pink, and red were, respectively, represented alpha-helix; random coil and extended strand. The results indicated that there were three forms of protein's secondary structure: Alpha-helix, extended strand, and random coil)|
Click here to view
Sub-cellular localization of c-Myc target from laryngeal cancer cell protein
Sub-cellular localization analysis of ProtComp v. 9.0 (Softberry, Inc. 116 Radio Circle, Suite 400 Mount Kisco, NY, USA) showed protein expressed by MTLC mainly distributed in the membrane, endoplasmic reticulum, and Golgi body [Table 2]. The location weights of membranes were the heaviest, which indicated that the protein probably located upon the structure of membranes.
|Table 2: Prediction results of sub-cellular localization of MTLC encoded protein|
Click here to view
Prediction of c-Myc target from laryngeal cancer cell protein function
This study used Protfun software (Technical University of Denmark, Denmark) to analyze MTLC protein and found it was nonenzyme. Functional category showed that MTLC had transfer and combination function (Prob. =0.809, odds = 1.974) and GO category showed that MTLC was a structural protein (Prob. = 0.115, odds = 4.101) [Table 3]. The value of Prob. was the estimated probability that the entry belonged to the class in question. It was influenced by the prior probability of that class. The value of odds represented the odds that the sequence belonged to that class/category. It was independent of the prior probability.
| > Discussion|| |
c-Myc target from laryngeal cancer cell is a nuclear protein gene in 6q25 regions of human chromosome. The whole length of the gene is 21,000 bp, consisting two exons and one intron. Experiments manifested that MTLC was a target gene of c-Myc that had multiple biological effects, including promoting cell apoptosis and genomic instability, inhibiting cell differentiation, etc. c-Myc is a transcription factor containing a leukine zipper and can take part in cell transformation, cell differentiation, apoptosis, and cell cycle control, etc., through a large number of target genes, such as CAD, ODC, and rcl.,,, Human chromosome 6p25 region is related to many tumors including laryngeal cancer., As a result, MTLC gene is closely related to the occurrence and development of laryngeal cancer.
Laryngeal cancer is a malignant tumor, which is seriously harmful to human health. It is caused by the interaction of genetic and environment factors, but the molecular mechanism of laryngeal cancer is still not clear. Studies found that the low expression of MTLC in laryngeal cancer tissue and the disease of Hep2 cells by MTLC can inhibit the cell growth and promote cell apoptosis. There are reports, have proved that other gene of c-Myc, such as p21 and overexpression of GADD45, could produce a similar effect. As a new gene that was just found out, MTLC gene attracted more and more attention.
Through the bioinformatic prediction of MTLC gene, this study found that MTLC was a basic protein with two transmembrane regions by sequence analysis, which separately located within 26-48th and 68-90th amino acid. These two transmembrane regions both possess higher hydrophobicity and alpha-helix structure. The main secondary structure elements of MTLC protein were random coil, alpha-helix, and extended strand that dispersed in the protein. The results of function prediction and subcellular localization indicated that MTLC probably a membrane constitutive protein possessed transportation and combination. MTLC may locate on karyotheca to participate in the signal transduction and regulation, combined with the experimental results of subcellular localization by Qiu et al.
Hence far, materials about the structure and function of MTLC are few, the detailed mechanism of such a gene taking part in the event and development of tumors, its upstream regulatory mechanism, downstream target gene as well as its position in the cell signal transduction pathway, are not clear. This study analyzed the structure and possibly possessed function of MTLC gene in aspect of bioinformatics in a relatively comprehensive way, which has important guiding significance for the further study of mechanism of action in the occurrence and development of MTLC gene, and its target gene would enrich the acting mechanism of c-Myc in many diseases including tumors and that is also meaningful to the study of targeted therapy of tumor gene.
| > Authors' Contribution|| |
Zhang WD carried out studies, participated in and drafted the manuscript. Chen HX participated in the design of the study and performed the statistical analysis. Chen ZP collected the questionnaire and conducted the analysis. Shan ZJ conceived of the study, and participated in its design and coordination and helped to draft the manuscript. Xu G did the test and experiment. All authors read and approved the final manuscript.
| > References|| |
Silver CE, Beitler JJ, Shaha AR, Rinaldo A, Ferlito A. Current trends in initial management of laryngeal cancer: The declining use of open surgery. Eur Arch Otorhinolaryngol 2009;266:1333-52.
Forastiere AA, Goepfert H, Maor M, Pajak TF, Weber R, Morrison W, et al.
Concurrent chemotherapy and radiotherapy for organ preservation in advanced laryngeal cancer. N Engl J Med 2003;349:2091-8.
Preuss SF, Cramer K, Klussmann JP, Eckel HE, Guntinas-Lichius O. Transoral laser surgery for laryngeal cancer: Outcome, complications and prognostic factors in 275 patients. Eur J Surg Oncol 2009;35:235-40.
Chen AY, Halpern M. Factors predictive of survival in advanced laryngeal cancer. Arch Otolaryngol Head Neck Surg 2007;133:1270-6.
Tang X, He X. Strategies of identifying novel genes by bioinformatics. Prog Mod Bio 2008;7:57.
Ren J, Zhu D, Liu M, Sun Y, Tian L. Downregulation of miR-21 modulates Ras expression to promote apoptosis and suppress invasion of Laryngeal squamous cell carcinoma. Eur J Cancer 2010;46:3409-16.
Guo WQ, Li LZ, He ZY, Zhang Q, Liu J, Hu CY, et al.
Anti-proliferative effects of Atractylis lancea
(Thunb.) DC. via down-regulation of the c-myc/hTERT/telomerase pathway in Hep-G2 cells. Asian Pac J Cancer Prev 2013;14:6363-7.
Yang M, Li W, Fu S. Study on inactivation and function related to corresponding sites of MTLC as a candidate tumor suppressor gene in laryngeal squamous cell carcinoma. Int J Genet 2010;33:78.
Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982;157:105-32.
Qiu G, Qiu G, Xu Z, Huang D, Gong L, Li C, et al.
Cloning and characterization of MTLC, a novel gene in 6q25. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 2003;20:94-7.
Yin X, Grove L, Rogulski K, Prochownik EV. Myc target in myeloid cells-1, a novel c-Myc target, recapitulates multiple c-Myc phenotypes. J Biol Chem 2002;277:19998-20010.
Prochownik EV. c-Myc: linking transformation and genomic instability. Curr Mol Med 2008;8:446-58.
Gao P, Tchernyshyov I, Chang TC, Lee YS, Kita K, Ochi T, et al.
c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature 2009;458:762-5.
Hoffman B, Liebermann DA. Apoptotic signaling by c-MYC. Oncogene 2008;27:6462-72.
Liu Z, Liu J, Qiu G. Effect of siRNA targeting MYCT-1 gene on cell apoptosis, proliferation and cell cycle in GES-1 cell. J Mol Diagn Ther 2010;2:50-3.
Wang VW, Bell DA, Berkowitz RS, Mok SC. Whole genome amplification and high-throughput allelotyping identified five distinct deletion regions on chromosomes 5 and 6 in microdissected early-stage ovarian tumors. Cancer Res 2001;61:4169-74.
Acevedo CM, Henríquez M, Emmert-Buck MR, Chuaqui RF. Loss of heterozygosity on chromosome arms 3p and 6q in microdissected adenocarcinomas of the uterine cervix and adenocarcinoma in situ
. Cancer 2002;94:793-802.
Qiu G, Hao D, Gogn L. MTLC gene was down-regulated in laryngeal cancer tissues and could promote apoptosis of Hep2 cells. Chin J Lab Med 2005;28:111.
Felsher DW, Zetterberg A, Zhu J, Tlsty T, Bishop JM. Overexpression of MYC causes p53-dependent G2 arrest of normal fibroblasts. Proc Natl Acad Sci U S A 2000;97:10544-8.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3]