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PLOS ONE  2012 

A Comparative Study of Gene-Expression Data of Basal Cell Carcinoma and Melanoma Reveals New Insights about the Two Cancers

DOI: 10.1371/journal.pone.0030750

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Abstract:

A comparative analysis of genome-scale transcriptomic data of two types of skin cancers, melanoma and basal cell carcinoma in comparison with other cancer types, was conducted with the aim of identifying key regulatory factors that either cause or contribute to the aggressiveness of melanoma, while basal cell carcinoma generally remains a mild disease. Multiple cancer-related pathways such as cell proliferation, apoptosis, angiogenesis, cell invasion and metastasis, are considered, but our focus is on energy metabolism, cell invasion and metastasis pathways. Our findings include the following. (a) Both types of skin cancers use both glycolysis and increased oxidative phosphorylation (electron transfer chain) for their energy supply. (b) Advanced melanoma shows substantial up-regulation of key genes involved in fatty acid metabolism (β-oxidation) and oxidative phosphorylation, with aerobic metabolism being far more efficient than anaerobic glycolysis, providing a source of the energetics necessary to support the rapid growth of this cancer. (c) While advanced melanoma is similar to pancreatic cancer in terms of the activity level of genes involved in promoting cell invasion and metastasis, the main metastatic form of basal cell carcinoma is substantially reduced in this activity, partially explaining why this cancer type has been considered as far less aggressive. Our method of using comparative analyses of transcriptomic data of multiple cancer types focused on specific pathways provides a novel and highly effective approach to cancer studies in general.

References

[1]  Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, et al. (2007) NCBI GEO: mining tens of millions of expression profiles–database and tools update. Nucleic Acids Res 35: D760–765.
[2]  Sherlock G, Hernandez-Boussard T, Kasarskis A, Binkley G, Matese JC, et al. (2001) The Stanford Microarray Database. Nucleic Acids Res 29: 152–155.
[3]  Rogers HW, Weinstock MA, Harris AR, Hinckley MR, Feldman SR, et al. (2010) Incidence estimate of nonmelanoma skin cancer in the United States, 2006. Arch Dermatol 146: 283–287.
[4]  Polsky D, Wang SQ (2011) Skin Cancer Facts. New York: The Skin Cancer Foundation. www.skincancer.org.
[5]  Jemal A, Siegel R, Xu J, Ward E (2010) Cancer statistics, 2010. CA Cancer J Clin 60: 277–300.
[6]  Jerant AF, Johnson JT, Sheridan CD, Caffrey TJ (2000) Early detection and treatment of skin cancer. Am Fam Physician 62: 357–368, 375–356, 381–352.
[7]  Box NF, Duffy DL, Chen W, Stark M, Martin NG, et al. (2001) MC1R genotype modifies risk of melanoma in families segregating CDKN2A mutations. Am J Hum Genet 69: 765–773.
[8]  Zuo L, Weger J, Yang Q, Goldstein AM, Tucker MA, et al. (1996) Germline mutations in the p16INK4a binding domain of CDK4 in familial melanoma. Nat Genet 12: 97–99.
[9]  Hughes-Davies TH (1998) CDKN2A mutations in multiple primary melanomas. N Engl J Med 339: 347–348.
[10]  Balch CM, Buzaid AC, Soong SJ, Atkins MB, Cascinelli N, et al. (2001) Final version of the American Joint Committee on Cancer staging system for cutaneous melanoma. J Clin Oncol 19: 3635–3648.
[11]  Warburg O (1956) On the origin of cancer cells. Science 123: 309–314.
[12]  Scatolini M, Grand MM, Grosso E, Venesio T, Pisacane A, et al. (2010) Altered molecular pathways in melanocytic lesions. Int J Cancer 126: 1869–1881.
[13]  Lo BK, Yu M, Zloty D, Cowan B, Shapiro J, et al. (2010) CXCR3/ligands are significantly involved in the tumorigenesis of basal cell carcinomas. Am J Pathol 176: 2435–2446.
[14]  Xu K, Cui J, Olman V, Yang Q, Puett D, et al. (2010) A comparative analysis of gene-expression data of multiple cancer types. PLoS One 5: e13696.
[15]  Cui J, Chen Y, Chou WC, Sun L, Chen L, et al. (2011) An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucleic Acids Res 39: 1197–1207.
[16]  Polsky D, Cordon-Cardo C (2003) Oncogenes in melanoma. Oncogene 22: 3087–3091.
[17]  Iwasaki JK, Srivastava D, Moy RL, Lin HJ, Kouba DJ (2010) The molecular genetics underlying basal cell carcinoma pathogenesis and links to targeted therapeutics. J Am Acad Dermatol.
[18]  Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144: 646–674.
[19]  Klymkowsky MW, Savagner P (2009) Epithelial-mesenchymal transition: a cancer researcher's conceptual friend and foe. Am J Pathol 174: 1588–1593.
[20]  Polyak K, Weinberg RA (2009) Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat Rev Cancer 9: 265–273.
[21]  Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100: 57–70.
[22]  Fu L, Lee CC (2003) The circadian clock: pacemaker and tumour suppressor. Nat Rev Cancer 3: 350–361.
[23]  van der Horst GT, Muijtjens M, Kobayashi K, Takano R, Kanno S, et al. (1999) Mammalian Cry1 and Cry2 are essential for maintenance of circadian rhythms. Nature 398: 627–630.
[24]  Bozikov K, Taggart I (2006) Metastatic basal cell carcinoma: is infiltrative/morpheaform subtype a risk factor? Eur J Dermatol 16: 691–692.
[25]  Cui J, Liu Q, Puett D, Xu Y (2008) Computational prediction of human proteins that can be secreted into the bloodstream. Bioinformatics 24: 2370–2375.
[26]  Hong CS, Cui J, Ni Z, Su Y, Puett D, et al. (2011) A computational method for prediction of excretory proteins and application to identification of gastric cancer markers in urine. PLoS One 6: e16875.
[27]  Edgar R, Domrachev M, Lash AE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30: 207–210.
[28]  Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, et al. (2003) DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 4: P3.
[29]  Cui J, Li F, Wang G, Fang X, Puett JD, et al. (2011) Gene-expression signatures can distinguish gastric cancer grades and stages. PLoS One 6: e17819.

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