Tumor Biol. DOI 10.1007/s13277-015-3735-1
RESEARCH ARTICLE
Association between cell cycle gene transcription and tumor size in oral squamous cell carcinoma Marina Gonçalves Diniz 1 & Jeane de Fatima Correia Silva 1 & Fabricio Tinôco Alvim de Souza 1 & Núbia Braga Pereira 1 & Carolina Cavaliéri Gomes 2 & Ricardo Santiago Gomez 1
Received: 30 March 2015 / Accepted: 29 June 2015 # International Society of Oncology and BioMarkers (ISOBM) 2015
Abstract Higher tumor size correlates with poor prognosis and is an independent predictive survival factor in oral squamous cell carcinoma (OSCC) patients. However, the molecular events underlining OSCC tumor evolution are poorly understood. We aimed to investigate if large OSCC tumors show different cell cycle gene transcriptional signature compared to small tumors. Seventeen fresh OSCC tumor samples with different tumor sizes (T) were included in the study. Tumors were from the tongue or from the floor of the mouth, and only three patients were nonsmokers. Samples were categorized according to clinical tumor size in tumors ≤2 cm (T1, n=5) or tumors >2 cm (T2, n=9; T3, n=2; T4, n=1). The group of tumors ≤2 cm was considered the reference group, while the larger tumors were considered the test group. We assessed the expression of 84 cell cycle genes by qRT-PCR array and normalized it to the expression of two housekeeping genes. Results were analyzed according to the formula 2^−DeltaCt. A fivefold change cutoff was used, and p values 2 cm) compared to the small ones (lesions ≤2 cm) with a fold change greater than five. Differential expression reached statistical significance in 13 genes, and all of them were more expressed in small tumors. This result indicates a more intense transcriptional activity of some cell cycle genes in early stage tumors, possibly reflecting a higher growth rate. It is well know that during solid tumor growth, cells acquire sustained chronic proliferation and are challenged by metabolic stress caused by nutrient depletion, pH alterations, and hypoxia. The major cancer cell physiological strategies to metabolic adaptation include cell cycle inhibition and induction of autophagy [13, 14]. Therefore, tumor cells may undergo a period of decreased tumor growth rate as an adaptive change enabling them to overcome this metabolic stress or undergo apoptosis (Fig. 3, adapted from Jones and Thompson 2009 [14]). Ki-67, which is encoded by MKI67, is an important marker of cell proliferation expressed during all cell cycle phases. In our series, although some cell cycle mRNAs were upregulated in small tumors compared to larger tumors, this difference was not confirmed at protein level using the most important proliferation marker. Additionally, MKI67 mRNA levels were not correlated
with Ki-67 staining. Intrinsic differences between the qPCR and IHC methods, such as accuracy, precision, and sensitivity, explain in part why both methods are many times divergent. In addition, several posttranscriptional gene regulation mechanisms (such as miRNAs) and tumor heterogeneity may influence the levels of gene transcripts and their corresponding proteins. Anaphase promoting complex subunit 4 (ANAPC4) and cullin 1 (CUL1) were the cell cycle genes that showed the highest differences in fold change between the two groups. Both showed not only a statistical significant difference in expression, but also showed a fold change higher than 10 [15]. It means that in our series, the larger tumors expressed ×10 less ANAPC4 and CUL1 mRNAs than the smaller tumors. Such differential expression might indicate that CUL1 and ANAPC4 expression is relevant at early stages of OSCC development, while in late stages, their expression is lost or decreased, and other genes might play an important role. ANAPC4 and CUL1 protein are reported to exhibit a diffuse cytoplasmic and nuclear immunolocalization in OSCC [16, 17]. Both proteins are part of the E3 ligases, which catalyze the ubiquitination of a variety of protein substrates for targeted degradation via the 26S proteasome [18]. These proteins are targets in cancer treatment [18]; however, further studies in a larger cohort of OSCC samples are necessary to confirm the importance of our findings. In conclusion, our findings suggest that the transcriptional activity of specific cell cycle genes varies according to the size of OSCC tumor, which probably reflects tumor molecular evolution and adaptation to the microenvironment.
Tumor Biol. Acknowledgments This study was supported in part by the following Brazilian funding agencies: Coordination for the Improvement of Higher Education Personnel (CAPES), Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), and National Council for Scientific and Technological Development (CNPq), Brazil. Diniz, M.G. is a research fellow at CAPES. Gomez, R.S. and Gomes, C.C. are research fellows at CNPq. Conflict of interest None.
References 1.
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Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015. doi:10.1002/ijc.29210. Patel SG, Shah JP. TNM staging of cancers of the head and neck: striving for uniformity among diversity. Cancer J Clin. 2005. doi: 10.3322/canjclin.55.4.242. Hanahan D, Weinberg RA. Hallmarks of cancer. Cell. 2011. doi:10. 1016/j.cell.2011.02.013. Todd R, Hinds PW, Munger K, et al. Cell cycle dysregulation in oral cancer. Crit Rev Oral Biol Med. 2002. doi:10.1177/ 154411130201300106. Stewart BW, Wild CP, editors. World Cancer Report. 3rd ed. Lyon: IARC; 2014. Helliwell T, Woolgar J. Dataset for histopathology reporting of mucosal malignancies of the oral cavity. London: The Royal College of Pathologists; 2013. Kademani D, Bell RB, Bagheri S, et al. Prognostic factors in intra oral squamous cell carcinoma: the influence of histologic grade. J Oral Maxillofac Surg. 2005. doi:10.1016/j.joms.2005.07.011.
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Arduino PG, Carrozzo M, Chiecchio A, et al. Clinical and histopathologic independent prognostic factors in oral squamous cell carcinoma: a retrospective study of 334 cases. J Oral Maxillofac Surg. 2008. doi:10.1016/j.joms.2007.12.024. 9. Sobin L, Gospodarowicz M, Wittekind C, editors. TNM Classification of Malignant Tumours. 8th ed. New Jersey: Wiley; 2009. 10. Bonner JA, Harari PM, Giralt J, et al. Radiotherapy plus cetuximab for locoregionally advanced head and neck cancer: 5-year survival data from a phase 3 randomised trial, and relation between cetuximab-induced rash and survival. Lancet Oncol. 2010. doi:10. 1016/S1470-2045(09)70311-0. 11. Warnakulasuriya S. Prognostic and predictive markers for oral squamous cell carcinoma: the importance of clinical, pathological and molecular markers. Saudi J Med Med Sci. 2014. doi:10.4103/ 1658-631X.128400. 12. Tabatabaeifar S, Kruse TA, Thomassen M, et al. Use of next generation sequencing in head and neck squamous cell carcinomas: a review. Oral Oncol. 2014. doi:10.1016/j.oraloncology.2014.08. 013. 13. Cairns RA, Harris IS, Mak TW. Regulation of cancer cell metabolism. Nat Rev Cancer. 2011. doi:10.1038/nrc2981. 14. Jones RG, Thompson CB. Tumor suppressors and cell metabolism: a recipe for cancer growth. Genes Dev. 2009. doi:10.1101/gad. 1756509. 15. Sullivan GM, Feinn R. Using effect size-or why the p value is not enough. J Grad Med Educ. 2012. doi:10.4300/JGME-D-12-00156. 1. 16. The human protein atlas, http://www.proteinatlas.org 17. Uhlen M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Tissue-based map of the human proteome. Science. 2015. doi:10.1126/science.1260419. 18. Sun Y. Targeting E3 ubiquitin ligases for cancer therapy. Cancer Biol Ther. 2003. doi:10.4161/cbt.2.6.677.
RESEARCH ARTICLE
Association between cell cycle gene transcription and tumor size in oral squamous cell carcinoma Marina Gonçalves Diniz 1 & Jeane de Fatima Correia Silva 1 & Fabricio Tinôco Alvim de Souza 1 & Núbia Braga Pereira 1 & Carolina Cavaliéri Gomes 2 & Ricardo Santiago Gomez 1
Received: 30 March 2015 / Accepted: 29 June 2015 # International Society of Oncology and BioMarkers (ISOBM) 2015
Abstract Higher tumor size correlates with poor prognosis and is an independent predictive survival factor in oral squamous cell carcinoma (OSCC) patients. However, the molecular events underlining OSCC tumor evolution are poorly understood. We aimed to investigate if large OSCC tumors show different cell cycle gene transcriptional signature compared to small tumors. Seventeen fresh OSCC tumor samples with different tumor sizes (T) were included in the study. Tumors were from the tongue or from the floor of the mouth, and only three patients were nonsmokers. Samples were categorized according to clinical tumor size in tumors ≤2 cm (T1, n=5) or tumors >2 cm (T2, n=9; T3, n=2; T4, n=1). The group of tumors ≤2 cm was considered the reference group, while the larger tumors were considered the test group. We assessed the expression of 84 cell cycle genes by qRT-PCR array and normalized it to the expression of two housekeeping genes. Results were analyzed according to the formula 2^−DeltaCt. A fivefold change cutoff was used, and p values 2 cm) compared to the small ones (lesions ≤2 cm) with a fold change greater than five. Differential expression reached statistical significance in 13 genes, and all of them were more expressed in small tumors. This result indicates a more intense transcriptional activity of some cell cycle genes in early stage tumors, possibly reflecting a higher growth rate. It is well know that during solid tumor growth, cells acquire sustained chronic proliferation and are challenged by metabolic stress caused by nutrient depletion, pH alterations, and hypoxia. The major cancer cell physiological strategies to metabolic adaptation include cell cycle inhibition and induction of autophagy [13, 14]. Therefore, tumor cells may undergo a period of decreased tumor growth rate as an adaptive change enabling them to overcome this metabolic stress or undergo apoptosis (Fig. 3, adapted from Jones and Thompson 2009 [14]). Ki-67, which is encoded by MKI67, is an important marker of cell proliferation expressed during all cell cycle phases. In our series, although some cell cycle mRNAs were upregulated in small tumors compared to larger tumors, this difference was not confirmed at protein level using the most important proliferation marker. Additionally, MKI67 mRNA levels were not correlated
with Ki-67 staining. Intrinsic differences between the qPCR and IHC methods, such as accuracy, precision, and sensitivity, explain in part why both methods are many times divergent. In addition, several posttranscriptional gene regulation mechanisms (such as miRNAs) and tumor heterogeneity may influence the levels of gene transcripts and their corresponding proteins. Anaphase promoting complex subunit 4 (ANAPC4) and cullin 1 (CUL1) were the cell cycle genes that showed the highest differences in fold change between the two groups. Both showed not only a statistical significant difference in expression, but also showed a fold change higher than 10 [15]. It means that in our series, the larger tumors expressed ×10 less ANAPC4 and CUL1 mRNAs than the smaller tumors. Such differential expression might indicate that CUL1 and ANAPC4 expression is relevant at early stages of OSCC development, while in late stages, their expression is lost or decreased, and other genes might play an important role. ANAPC4 and CUL1 protein are reported to exhibit a diffuse cytoplasmic and nuclear immunolocalization in OSCC [16, 17]. Both proteins are part of the E3 ligases, which catalyze the ubiquitination of a variety of protein substrates for targeted degradation via the 26S proteasome [18]. These proteins are targets in cancer treatment [18]; however, further studies in a larger cohort of OSCC samples are necessary to confirm the importance of our findings. In conclusion, our findings suggest that the transcriptional activity of specific cell cycle genes varies according to the size of OSCC tumor, which probably reflects tumor molecular evolution and adaptation to the microenvironment.
Tumor Biol. Acknowledgments This study was supported in part by the following Brazilian funding agencies: Coordination for the Improvement of Higher Education Personnel (CAPES), Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), and National Council for Scientific and Technological Development (CNPq), Brazil. Diniz, M.G. is a research fellow at CAPES. Gomez, R.S. and Gomes, C.C. are research fellows at CNPq. Conflict of interest None.
References 1.
2.
3. 4.
5. 6.
7.
Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015. doi:10.1002/ijc.29210. Patel SG, Shah JP. TNM staging of cancers of the head and neck: striving for uniformity among diversity. Cancer J Clin. 2005. doi: 10.3322/canjclin.55.4.242. Hanahan D, Weinberg RA. Hallmarks of cancer. Cell. 2011. doi:10. 1016/j.cell.2011.02.013. Todd R, Hinds PW, Munger K, et al. Cell cycle dysregulation in oral cancer. Crit Rev Oral Biol Med. 2002. doi:10.1177/ 154411130201300106. Stewart BW, Wild CP, editors. World Cancer Report. 3rd ed. Lyon: IARC; 2014. Helliwell T, Woolgar J. Dataset for histopathology reporting of mucosal malignancies of the oral cavity. London: The Royal College of Pathologists; 2013. Kademani D, Bell RB, Bagheri S, et al. Prognostic factors in intra oral squamous cell carcinoma: the influence of histologic grade. J Oral Maxillofac Surg. 2005. doi:10.1016/j.joms.2005.07.011.
8.
Arduino PG, Carrozzo M, Chiecchio A, et al. Clinical and histopathologic independent prognostic factors in oral squamous cell carcinoma: a retrospective study of 334 cases. J Oral Maxillofac Surg. 2008. doi:10.1016/j.joms.2007.12.024. 9. Sobin L, Gospodarowicz M, Wittekind C, editors. TNM Classification of Malignant Tumours. 8th ed. New Jersey: Wiley; 2009. 10. Bonner JA, Harari PM, Giralt J, et al. Radiotherapy plus cetuximab for locoregionally advanced head and neck cancer: 5-year survival data from a phase 3 randomised trial, and relation between cetuximab-induced rash and survival. Lancet Oncol. 2010. doi:10. 1016/S1470-2045(09)70311-0. 11. Warnakulasuriya S. Prognostic and predictive markers for oral squamous cell carcinoma: the importance of clinical, pathological and molecular markers. Saudi J Med Med Sci. 2014. doi:10.4103/ 1658-631X.128400. 12. Tabatabaeifar S, Kruse TA, Thomassen M, et al. Use of next generation sequencing in head and neck squamous cell carcinomas: a review. Oral Oncol. 2014. doi:10.1016/j.oraloncology.2014.08. 013. 13. Cairns RA, Harris IS, Mak TW. Regulation of cancer cell metabolism. Nat Rev Cancer. 2011. doi:10.1038/nrc2981. 14. Jones RG, Thompson CB. Tumor suppressors and cell metabolism: a recipe for cancer growth. Genes Dev. 2009. doi:10.1101/gad. 1756509. 15. Sullivan GM, Feinn R. Using effect size-or why the p value is not enough. J Grad Med Educ. 2012. doi:10.4300/JGME-D-12-00156. 1. 16. The human protein atlas, http://www.proteinatlas.org 17. Uhlen M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Tissue-based map of the human proteome. Science. 2015. doi:10.1126/science.1260419. 18. Sun Y. Targeting E3 ubiquitin ligases for cancer therapy. Cancer Biol Ther. 2003. doi:10.4161/cbt.2.6.677.
