Levels And Patterns Of Expression Of Hypoxia-inducible Factor-1α, Vascular Endothelial Growth Factor, Glucose Transporter-1 And Cd105 In Adenoid Cystic Carcinomas With High-grade Transformation

Aims: To compare the expression of proteins regulated by hypoxia between adenoid cystic carcinoma (ACC) with and without high-grade transformation (HGT). Methods and results: In eight ACC-HGT and 18 ACC without HGT, expression of hypoxia-inducible factor-1 (HIF-1α), vascular endothelial growth factor (VEGF), glucose transporter-1 (GLUT-1) and microvascular density (MVD) by CD105 (a hypoxia-inducible protein expressed in angiogenic endothelial cells) was determined. Expression levels of HIF-1α and VEGF as well as CD105-MVD did not differ significantly between: (i) transformed and conventional areas (TA and CA, respectively) of ACC-HGT, (ii) CA and ordinary ACC. HIF-1α was detected in 100% of cases and presented a diffuse expression pattern. No significant association was found between levels of HIF-1α expression and tumour size, metastasis and recurrence. GLUT-1 showed a prostromal expression pattern and was observed exclusively in TA (three of six cases) and in only three of 14 ACC. Conclusions: Both the absence of significant alterations in levels of expression of HIF-1α, VEGF and CD105 and the patterns of expression of HIF-1α and GLUT-1 suggest that hypoxia may not play a key role in the process of high-grade transformation of ACC. Although HIF-1α expression is a common finding in ACC, it cannot be used as a marker of tumour aggressiveness. © 2012 Blackwell Publishing Limited.605816825El-Naggar, A.K., Huvos, A.G., Adenoid cystic carcinoma (2005) World Health Organization classification of tumour. Pathology and genetics. Head and neck tumours, pp. 223-224. , Barnes L, Eveson JW, Reichart P, Sidransky D eds. Lyon: IARC PressSimpson, R.H., Pereira, E.M., Ribeiro, A.C., Abdulkadir, A., Reis-Filho, J.S., Polymorphous low-grade adenocarcinoma of the salivary glands with transformation to high-grade carcinoma (2002) Histopathology, 41, pp. 250-259Nagao, T., Gaffey, T.A., Serizawa, H., Dedifferentiated adenoid cystic carcinoma: a clinicopathologic study of 6 cases (2003) Mod. Pathol., 16, pp. 1265-1272Seethala, R.R., Hunt, J.L., Baloch, Z.W., Livolsi, V.A., Leon Barnes, E., Adenoid cystic carcinoma with high-grade transformation: a report of 11 cases and a review of the literature (2007) Am. J. Surg. Pathol., 31, pp. 1683-1694Skalová, A., Sima, R., Vanecek, T., Acinic cell carcinoma with high-grade transformation: a report of 9 cases with immunohistochemical study and analysis of TP53 and HER-2/neu genes (2009) Am. J. Surg. Pathol., 33, pp. 1137-1145Roy, P., Bullock, M.J., Perez-Ordoñez, B., Dardick, I., Weinreb, I., Epithelial-myoepithelial carcinoma with high-grade transformation (2010) Am. J. Surg. Pathol., 34, pp. 1258-1265Costa, A.F., Altemani, A., Vékony, H., Genetic profile of adenoid cystic carcinomas (ACC) with high-grade transformation versus solid type (2011) Cell. Oncol., 34, pp. 369-379Costa, A.F., Altemani, A., Hermsen, M., Current concepts on dedifferentiation/high-grade transformation in salivary gland tumors (2011) Patholog. Res. Int., 2011, p. 325965Cheuk, W., Chan, J.K., Ngan, R.K., Dedifferentiation in adenoid cystic carcinoma of salivary gland. An uncommon complication associated with an accelerated clinical course (1999) Am. J. Surg. Pathol., 23, pp. 465-472Harris, A.L., Hypoxia - a key regulatory factor in tumour growth (2002) Nat. Rev. Cancer, 2, pp. 38-47Jögi, A., Øra, I., Nilsson, H., Poellinger, L., Axelson, H., Pahlman, S., Hypoxia-induced dedifferentiation in neuroblastoma cells (2003) Cancer Lett., 197, pp. 145-150Axelson, H., Fredlund, E., Ovenberger, M., Landberg, G., Pahlman, S., Hypoxia-induced dedifferentiation of tumor cells: a mechanism behind heterogeneity and aggressiveness of solid tumors (2005) Semin. Cell Dev. Biol., 16, pp. 554-563Semenza, G.L., HIF-1: mediator of physiological and pathophysiological responses to hypoxia (2000) J. Appl. Physiol., 88, pp. 1474-1480Gatenby, R.A., Gillies, R.J., Why do cancers have high aerobic glycolysis? (2004) Nat. Rev. Cancer, 4, pp. 891-899Behrooz, A., Ismail-Beigi, F., Stimulation of glucose transport by hypoxia: signals and mechanisms (1999) News Physiol. Sci., 14, pp. 105-110Chen, C., Pore, N., Behrooz, A., Ismail-Beigi, F., Maity, A., Regulation of glut1 mRNA by hypoxia-inducible factor-1. Interaction between H-ras and hypoxia (2001) J. Biol. Chem., 276, pp. 9519-9525Gillies, R.J., Gatenby, R.A., Adaptive landscapes and emergent phenotypes: why do cancers have high glycolysis? (2007) J. Bioenerg. Biomembr., 39, pp. 251-257Haber, R.S., Rathan, A., Weiser, K.R., GLUT1 glucose transporter expression in colorectal carcinoma: a marker for poor prognosis (1998) Cancer, 83, pp. 34-40Kalir, T., Wang, B.Y., Goldfischer, M., Immunohistochemical staining of GLUT1 in benign, borderline, and malignant ovarian epithelia (2002) Cancer, 94, pp. 1078-1082Burstein, D.E., Nagi, C., Kohtz, D.S., Lee, L., Wang, B., Immunodetection of GLUT1, p63 and phospho-histone H1 in invasive head and neck squamous carcinoma: correlation of immunohistochemical staining patterns with keratinization (2006) Histopathology, 48, pp. 717-722Ferrara, N., Gerber, H.P., LeCouter, J., The biology of VEGF and its receptors (2003) Nat. Med., 9, pp. 669-676Adams, R.H., Alitalo, K., Molecular regulation of angiogenesis and lymphangiogenesis (2007) Nat. Rev. Mol. Cell Biol., 8, pp. 464-478Li, C., Issa, R., Kumar, P., CD105 prevents apoptosis in hypoxic endothelial cells (2003) J. Cell Sci., 116, pp. 2677-2685Duff, S.E., Li, C., Garland, J.M., Kumar, S., CD105 is important for angiogenesis: evidence and potential applications (2003) FASEB J., 17, pp. 984-992Li, C., Guo, B., Bernabeu, C., Kumar, S., Angiogenesis in breast cancer: the role of transforming growth factor beta and CD105 (2001) Microsc. Res. Tech., 52, pp. 437-449Seeber, L.M., Horrée, N., van der Groep, P., van der Wall, E., Verheijen, R.H., van Diest, P.J., Necrosis related HIF-1alpha expression predicts prognosis in patients with endometrioid endometrial carcinoma (2010) BMC Cancer, 10, pp. 307-317Bonfitto, V.L., Demasi, A.P., Costa, A.F., Bonfitto, J.F., Araujo, V.C., Altemani, A., High-grade transformation of adenoid cystic carcinomas: a study of the expression of GLUT1 glucose transporter and of mitochondrial antigen (2010) J. Clin. Pathol., 63, pp. 615-619Iyer, N.V., Kotch, L.E., Agani, F., Cellular and developmental control of O 2 homeostasis by hypoxia-inducible factor 1 alpha (1998) Genes Dev., 12, pp. 149-162Zhong, H., De Marzo, A.M., Laughner, E., Overexpression of hypoxia-inducible factor 1alpha in common human cancers and their metastases (1999) Cancer Res., 59, pp. 5830-5835Bos, R., Zhong, H., Hanrahan, C.F., Levels of hypoxia-inducible factor-1alpha during breast carcinogenesis (2001) J. Natl. Cancer Inst., 93, pp. 309-314Mabjeesh, N.J., Amir, S., Hypoxia-inducible factor (HIF) in human tumorigenesis (2007) Histol. Histopathol., 22, pp. 559-572Sivridis, E., Giatromanolaki, A., Gatter, K.C., Harris, A.L., Koukourakis, M.I., Association of hypoxia-inducible factors 1alpha and 2alpha with activated angiogenic pathways and prognosis in patients with endometrial carcinoma (2002) Cancer, 95, pp. 1055-1063Vleugel, M.M., Greijer, A.E., Shvarts, A., Differential prognostic impact of hypoxia induced and diffuse HIF-1alpha expression in invasive breast cancer (2005) J. Clin. Pathol., 58, pp. 172-177Tomes, L., Emberley, E., Niu, Y., Necrosis and hypoxia in invasive breast carcinoma (2003) Breast Cancer Res. Treat., 81, pp. 61-69Moreno-Sánchez, R., Rodríguez-Enríquez, A., Marín-Hernández, A., Saavedra, E., Energy metabolism in tumour cells (2007) FEBS J., 274, pp. 1393-1418Mazurek, S., Boschek, C.B., Eigenbrodt, E., The role of phosphometabolites in cell proliferation, energy metabolism, and tumor therapy (1997) J. Bioenerg. Biomembr., 29, pp. 315-330Li, C., Hampson, I.N., Hampson, L., Kumar, P., Bernabeu, C., Kumar, S., CD105 antagonizes the inhibitory signaling of transforming growth factor beta1 on human vascular endothelial cells (2000) FASEB J., 14, pp. 55-64Neufeld, G., Cohen, T., Gengrinovitch, S., Poltorak, Z., Vascular endothelial growth factor (VEGF) and its receptors (1999) FASEB J., 13, pp. 9-22Kimura, H., Weisz, A., Ogura, T., Identification of hypoxia-inducible factor 1 ancillary sequence and its function in vascular endothelial growth factor gene induction by hypoxia and nitric oxide (2001) J. Biol. Chem., 276, pp. 2292-2298Sánchez-Elsner, T., Botella, L.M., Velasco, B., Langa, C., Bernabéu, C., Endoglin expression is regulated by transcriptional cooperation between the hypoxia and transforming growth factor-beta pathways (2002) J. Biol. Chem., 277, pp. 43799-4380

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Increasing amounts of data, together with more computing power and better machine learning algorithms to analyse the data, are causing changes in almost every aspect of our lives. This trend is expected to continue as more data keep becoming available, computing power keeps improving and machine learning algorithms keep improving as well. Flood risk and impact assessments are also being influenced by this trend, particularly in areas such as the development of mitigation measures, emergency response preparation and flood recovery planning. Machine learning methods have the potential to improve accuracy as well as reduce calculating time and model development cost. It is expected that in the future more applications will become feasible and many process models and traditional observation methods will be replaced by machine learning. Examples of this include the use of machine learning on remote sensing data to estimate exposure and on social media data to improve flood response. Some improvements may require new data collection efforts, such as for the modelling of flood damages or defence failures. In other components, machine learning may not always be suitable or should be applied complementary to process models, for example in hydrodynamic applications. Overall, machine learning is likely to drastically improve future flood risk and impact assessments, but issues such as applicability, bias and ethics must be considered carefully to avoid misuse. This paper presents some of the current developments on the application of machine learning in this field and highlights some key needs and challenges..Hydraulic Structures and Flood RiskWater Resource

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