The Axis “Human Papillomavirus - Anal Squamous Cell Carcinoma”: A Review

Main Article Content

Ana Carolina Borges Monteiro
Reinaldo Padilha França
Yuzo Iano
Valeria Tananska
Abdeldjalil Khelassi
Rangel Arthur

Abstract

Background: Anal Squamous Cell Carcinoma (ASCC) is an infrequent neoplasia that represents 2% of the digestive tumors and it has a growing incidence.


Objective: This investigation (i) studies the pathogenesis of an increasingly prevalent disease, (ii) its treatment and prognosis along with (iii) a bibliographical review of the main characteristics of the Human Papillomavirus (HPV) as well as its effects on humans.


Methods: A literature review is performed, comprising articles up to 2019 and cross-research manuscripts with the initial research.


Results: Several studies demonstrate the HPV role as a significant risk factor to the development of ASCC, as well as its higher incidence in HIV-positive individuals and in those who engage in receptive anal intercourse. Future trends in theragnostic using information technology are examined.


Conclusions: ASCC is a neoplasm mostly associated with HPV. Many studies are needed to improve the treatment as well as in the evaluation of the tumor characteristics.

Downloads

Download data is not yet available.

Article Details

How to Cite
The Axis “Human Papillomavirus - Anal Squamous Cell Carcinoma”: A Review. (2020). Medical Technologies Journal, 3(4), 471-484. https://doi.org/10.26415/2572-004X-vol3iss4p471-484
Section
Medical technologies

How to Cite

The Axis “Human Papillomavirus - Anal Squamous Cell Carcinoma”: A Review. (2020). Medical Technologies Journal, 3(4), 471-484. https://doi.org/10.26415/2572-004X-vol3iss4p471-484

Share

References

[1] Global Cancer Observatory (GCO). Cancer Fact Sheets. access 08.11.2019.
[2] Martin, D., Balermpas, P., Winkelmann, R, Rödel, F., Rödel, C, Fokas, E. (2018). Anal squamous cell carcinoma - State of the art management and future perspectives. Cancer Treatment Reviews. 65, 11-21. https://doi.org/10.1016/j.ctrv.2018.02.001 PMid:29494827
[3] Bosman, F.T., Carneiro, F., Hruban, R.H., et al. (2010). WHO classification of tumours of the digestive system, 4th edition. Lyon: International Agency for Research on Cancer. (3), 184-93.
[4] Harald zur Hausen. Nobel Prize Award' Biographicals. access 09.11.2019.
[5] Le cancer de l'anus. Société Nationale Française de Colo-Proctologie. < www.snfcp.org/informations-maladies/cancer/cancer-de-lanus-2014/> access 09.11.2019.
[6] Hellner, K., Munger, K. (2011). Human papillomaviruses as therapeutic targets in human cancer. Journal of Clinical Oncology, 29(13), 1785-94. https://doi.org/10.1200/JCO.2010.28.2186 PMid:21220591 PMCid:PMC3675666
[7] Doorbar J., Egawa, N., Griffin, H., Kranjec, C., & Murakami, I. (2015). Human papillomavirus molecular biology and disease association. Reviews in medical virology, 25, 2-23. https://doi.org/10.1002/rmv.1822 PMid:25752814 PMCid:PMC5024016
[8] Maxwell J.H., Khan S., Ferris R.L. (2015). The molecular biology of hpv-related head and neck cancer. In: Fakhry C., D'Souza G. (eds) HPV and Head and Neck Cancers. Head and Neck Cancer Clinics. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2413-6_4
[9] Snell, R. S. (2012). Clinical anatomy by regions, 9th ed. Wolters Kluwer-Lippincott Williams & Wilkins.
[10] Beck, D. (2011). Sexually transmitted diseases. ASCRS Textbook of Colon and Rectal Surgery, 2nd ed. New York: Springer : 295-307.https://doi.org/10.1007/978-1-4419-1584-9_17
[11] Whitlow, C.B. (2004). Bacterial Sexually Transmitted Diseases. Clinics in Colon and Rectal Surgery. 17(4): 209-214 https://doi.org/10.1055/s-2004-836940
[12] AJCC 7th Ed Cancer Staging Manual, 7th ed., ch.15 Anus., 181 - 6 (2015). < https://cancerstaging.org/references-tools/deskreferences/Documents/AJCC%207th%20Ed%20Cancer%20Staging%20Manual.pdf> accessed 9.11.2019.
[13] Okami, K. (2016). A new risk factor for head and neck squamous cell carcinoma: human papillomavirus. International Journal of Clinical Oncology, 21(5), 817. https://doi.org/10.1007/s10147-016-1012-y PMid:27368335
[14] Mammas, I. N., & Spandidos, D. A. (2017). Paediatric Virology as a new educational initiative: An interview with Nobelist Professor of Virology Harald zur Hausen. Experimental and Therapeutic Medicine. 14(4), 3329-3331. https://doi.org/10.3892/etm.2017.5006 PMid:29042913 PMCid:PMC5639320
[15] Jesus, S. P. D., et al. (2018). A high prevalence of human papillomavirus 16 and 18 co-infections in cervical biopsies from southern Brazil. Braz. J. Microbiology, 49, 220-223. https://doi.org/10.1016/j.bjm.2018.04.003 PMid:29720351 PMCid:PMC6328718
[16] Ribeiro, A. A., Costa, M. C., Alves, R. R. F., Villa, L. L., Saddi, V. A., dos Santos Carneiro, M. A., & Rabelo-Santos, S. H. (2015). HPV infection and cervical neoplasia: Associated risk factors. Infectious Agents and Cancer, 10(1), 16. https://doi.org/10.1186/s13027-015-0011-3 PMid:26244052 PMCid:PMC4524198
[17] Cseke, L. J., Kirakosyan, A., Kaufman, P. B., & Westfall, M. V. (2016). Handbook of molecular and cellular methods in biology and medicine. CRC Press. https://doi.org/10.1201/b11351
[18] Erkekoglu, P. (2019). Oncogenes and Carcinogenesis. https://doi.org/10.5772/intechopen.74727
[19] Abreu, M. N. S., et al. (2018). Conhecimento e percepção sobre o HPV na população com mais de 18 anos da cidade de Ipatinga, MG, Brasil. Ciência & Saúde Coletiva, 23, 849-860. https://doi.org/10.1590/1413-81232018233.00102016 PMid:29538565
[20] Allen, D. C., Cameron, R. I. (Eds.) (2017). Histopathology specimens: clinical, pathological and laboratory aspects. Springer.
[21] Minsky, B. D., Guillem, J. G. (2016). Neoplasms of the anus. Holland‐Frei Cancer Medicine, 1-12.
[22] Júnior, J.C.M.S. (2007). Câncer Ano- retocólico - Aspectos atuais: I - Câncer Anal. Rev. Bras. Coloproct;27(2): 2109-223. https://doi.org/10.1590/S0101-98802007000200016
[23] Nadal, S.R; et al. (2009). Quanto a escova deve ser introduzida no canal anal para avaliação citológica mais eficaz? Rev Assoc Med Bras; 55(6): 749-51. https://doi.org/10.1590/S0104-42302009000600022 PMid:20191232
[24] Duarte, B. F., da Silva, M. A. B., Germano, S., & Leonart, M. S. S. (2016). Anal cancer diagnosis in patients with human papilomavírus (HPV) and human immunodeficiency virus (HIV) coinfection. Rev Inst Adolfo Lutz. 75, 1710.
[25] Monteiro, A. C. B., da Cruz Pires, D. V. D. (2015). Characterization of the risk factors for anus cancer and its relationship with Human Papillomaviruses. Rev. Saude em Foco. https://doi.org/10.17648/unifia-saude-foco-ed-8-vol-1-032
[26] Chaves, E. B. M., Capp, E., Corleta, H. V. E., Folgierini, H. J. (2011). A citologia na prevenção do câncer anal. Femina: Rio de Janeiro. 39(11), p. 532-537.
[27] Cuevas, M. (2019). Virus del papiloma humano y salud femenina. Ediciones i.
[28] Magalhães, M.N., & Barbosa, L.E.: Anal canal squamous carcinoma. J. Coloproctol. 37(1), 72-79, (2017). Doi: 10.1016/j.jcol.2016.08.003
[29] Cutrim, P. T.: Papilomavírus humano (hpv) e sua associação entre as lesões cervical e anal em mulheres (2017).
[30] Darragh, T. M., Palefsky, J. M. (2015). Anal cytology. In The Bethesda System for Reporting Cervical Cytology (pp. 263-285). Springer, Cham. https://doi.org/10.1007/978-3-319-11074-5_8
[31] Bernardy, J. P., Bierhals, N. D., Possuelo, L. G., & Renner, J. D. P. (2018). Padronização da PCR em tempo real para a genotipagem de HPV 6-11, HPV 16 e HPV 18 utilizando controle interno. Revista Jovens Pesquisadores, 8(1), 37-48. https://doi.org/10.17058/rjp.v8i1.12090
[32] Clifford, G. M., et al. (2016). Comparison of two widely-used HPV detection and genotyping methods: GP5+/6+ PCR followed by reverse line blot hybridization and multiplex type-specific E7 PCR. Journal of Clinical Microbiology, JCM-0061. https://doi.org/10.1128/JCM.00618-16 PMid:27225411 PMCid:PMC4963525
[33] Wang, X., et al. (2014). MicroRNAs are biomarkers of oncogenic human papillomavirus infections. Proc. National Academy of Sciences of the United States of America, 111(11), 4262-4267. https://doi.org/10.1073/pnas.1401430111 PMid:24591631 PMCid:PMC3964092
[34] Allison, D. B., Olson, M. T., Maleki, Z., & Ali, S. Z. (2016). Metastatic urinary tract cancers in pap test: Cytomorphologic findings and differential diagnosis. Diagn. Cytopathology, 44(12), 1078-1081. https://doi.org/10.1002/dc.23543 PMid:27434279
[35] Greene, F.L. (2003).TNM staging for malignancies of the digestive tract: 2003 changes and beyond. Seminars in Surgical Oncology. 21, 23 - 9. https://doi.org/10.1002/ssu.10018 PMid:12923913
[36] TNM classification system for cancer. UICC. access 09.11.2019.
[37] Monteiro, A.C.B., Iano, Y., França, R.P., Arthur R., Estrela, V.V. (2019). A comparative study between methodologies based on the Hough transform and watershed transform on the blood cell count. In: Iano, Y., Arthur, R., Saotome, O., Estrela, V. V., Loschi, H.J. (eds) Proc. 4th Braz. Technology Symposium (BTSym'18). Smart Innovation, Systems and Technologies, vol 140. Springer, Cham. doi: 10.1007/978-3-030-16053-1_7
[38] Gurcan, M.N., Boucheron, L.E., Can, A., Madabhushi, A., Rajpoot, N.M., & Yener, B. (2009). Histopathological image analysis: A review. IEEE Reviews in Biomedical Engineering, 2, 147-171. https://doi.org/10.1109/RBME.2009.2034865 PMid:20671804 PMCid:PMC2910932
[39] Razmjooy, N., Estrela, V.V., Loschi, H.J. (2019). A study on metaheuristic-based neural networks for image segmentation purposes, in Q. A. Memon, S. A. Khoja (eds) Data Science Theory, Analysis and Applications, Taylor and Francis. https://doi.org/10.1201/9780429263798-2
[40] Komura, D., & Ishikawa, S. (2018). Machine Learning Methods for Histopathological Image Analysis. Computational and Structural Biotechnology Journal. https://doi.org/10.1016/j.csbj.2018.01.001 PMid:30275936 PMCid:PMC6158771
[41] Vaisali, Parvathy, Vyshnavi, H., & Namboori, K. (2019). ' Tumor Hypoxia Diagnosis ' using deep CNN learning strategy: A theranostic pharmacogenomic approach.
[42] Razmjooy, N., Estrela, V.V., Loschi, H.J. (2019). A survey of potatoes image segmentation based on machine vision. In: Applications of Image Processing and Soft Computing Systems in Agriculture. IGI Global, 1-38. 2019. doi:10.4018/978-1-5225-8027-0.ch001
[43] de Jesus MA, Estrela VV, Saotome O, Stutz D. (2018). Super-resolution via particle swarm optimization variants. In: Hemanth J., Balas V. (eds) Biologically Rationalized Computing Techniques For Image Processing Applications. Lecture Notes in Computational Vision and Biomechanics, vol 25. Springer, Cham doi: 10.1007/978-3-319-61316-1_14
[44] Hemanth, D.J., & Estrela, V.V. (2017). Deep Learning for Image Processing Applications. Advances in Parallel Computing Series, Vol. 31, IOS Press, ISBN 978-1-61499-821-1 (print), ISBN 978-1-61499-822-8 (online)
[45] Xu, Y., Jia, Z., Wang, L., Ai, Y., Zhang, F., Lai, M., & Chang, E.I. (2017). Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features. BMC Bioinformatics. https://doi.org/10.1186/s12859-017-1685-x
[46] Mistrangelo, M., & Lesca, A. (2013). PET-CT in anal cancer: Indications and limits. In: Misciagna, S. (Ed.), Positron Emission Tomography - Recent Developments in Instrumentation, Research and Clinical Oncological Practice. IntechOpen. doi: 10.5772/57121. PMCid:PMC3593553
[47] Zacho, H.D., et al. (2018). Prospective comparison of 68Ga-PSMA PET/CT, 18F-sodium fluoride PET/CT and diffusion weighted-MRI at for the detection of bone metastases in biochemically recurrent prostate cancer. European Journal of Nuclear Medicine and Molecular Imaging, 45, 1884-1897. https://doi.org/10.1007/s00259-018-4058-4 PMid:29876619
[48] Voduc, D., Kenney, C., & Nielsen, T.O. (2008). Tissue microarrays in clinical oncology. Seminars in Radiation Oncology, 18 2, 89-97. https://doi.org/10.1016/j.semradonc.2007.10.006 PMid:18314063 PMCid:PMC2292098
[49] Mascini, N.E., Teunissen, J., Noorlag, R., Willems, S.M., & Heeren, R.M. (2018). Tumor classification with MALDI-MSI data of tissue microarrays: A case study. Methods, 151, 21-27 . https://doi.org/10.1016/j.ymeth.2018.04.004 PMid:29656077
[50] Alves, F.D., Estrela, V.V., & Matos, L.F. (2011). Hyperspectral analysis of remotely sensed images. In: Sustainable Water Management in the Tropics and Subtropics - And Case Studies in Brazil. Vol. 2, University of Kassel. ISBN 978-85-63337-21-4
[51] Mezheyeuski, A., Bergsland, C.H., Backman, M., Djureinovic, D., Sjöblom, T., Bruun, J., & Micke, P. (2018). Multispectral imaging for quantitative and compartment‐specific immune infiltrates reveals distinct immune profiles that classify lung cancer patients. The J. Pathology, 244, 421-431. https://doi.org/10.1002/path.5026 PMid:29282718
[52] Ferro, A., Mestre, T., Carneiro, P., Sahumbaiev, I., Seruca, R., & Sanches, J.M. (2017). Blue intensity matters for cell cycle profiling in fluorescence DAPI-stained images. Laboratory Investigation, 97, 615-625. https://doi.org/10.1038/labinvest.2017.13 PMid:28263290
[53] Tasoglu, S., Kavaz, D., Gurkan, U.A., Guven, S., Chen, P., Zheng, R., & Demirci, U. (2012). Paramagnetic levitational assembly of hydrogels TIO. Adv. Mater. 25 (8) 1137. https://doi.org/10.1002/adma.201200285 PMid:23288557 PMCid:PMC3823061
[54] Asghar, W., Assal, R.E., Shafiee, H., Pitteri, S.J., Paulmurugan, R., & Demirci, U. (2015). Engineering cancer microenvironments for in vitro 3-D tumor models. Mat. Today. https://doi.org/10.1016/j.mattod.2015.05.002 PMid:28458612 PMCid:PMC5407188
[55] Rodell, C.B., & Burdick, J.A. (2014). Materials science: Radicals promote magnetic gel assembly. Nature 514 (7524) 574. https://doi.org/10.1038/514574a PMid:25355357
[56] Zhou, Q., Vincent, M., Deng, Y., Yu, J., Xu, J., Xu, T., Tang, T., Bian, L., Wang, Y.J., Kostarelos, K., & Zhang, L. (2017). Multifunctional biohybrid magnetite microrobots for imaging-guided therapy. Science Robotics, 2. https://doi.org/10.1126/scirobotics.aaq1155
[57] Mohammadzadeh N, Safdari R (2014). Robotic surgery in cancer care: opportunities and challenges. Asian Pac J Cancer Prev 15:1081-1083. https://doi.org/10.7314/APJCP.2014.15.3.1081 PMid:24606422
[58] Oblak, I., Češnjevar, M., Anžič, M., Hadžić, J.B., Ermenc, A.S., Anderluh, F., Velenik, V., Jeromen, A., & Korošec, P. (2016). The impact of anaemia on treatment outcome in patients with squamous cell carcinoma of anal canal and anal margin. Radiology and oncology. https://doi.org/10.1515/raon-2015-0015
[59] Norat, T., et al. (2005). Meat, fish, and colorectal cancer risk: the European Prospective Investigation into cancer and nutrition. J. Nat. Cancer Inst. 97 12, 906-16. https://doi.org/10.1093/jnci/dji164 PMid:15956652 PMCid:PMC1913932
[60] Amirabdollahian, F., Livatino, S., Vahedi, B. et al. Prevalence of haptic feedback in robot-mediated surgery: a systematic review of literature. J Robotic Surg (2018) 12: 11. https://doi.org/10.1007/s11701-017-0763-4 PMid:29196867
[61] Razmjooy, N., & Estrela, V.V. (2019). Applications of Image Processing and Soft Computing Systems in Agriculture, IGI Global. doi: 10.4018/978-1-5225-8027-0
[62] Brodie, A. (2018). The future of robotic surgery. Ann R Coll Surf Engl. 100(7), 4-13. https://doi.org/10.1308/rcsann.supp2.4 PMid:30179048 PMCid:PMC6216754
[63] Lhachemi, H., Malik, A., & Shorten, R. (2019). augmented reality, cyber-physical systems, and feedback control for additive manufacturing: A review. IEEE Access. 7, 750119 – 50135 https://doi.org/10.1109/ACCESS.2019.2907287
[64] Estrela, V.V., Monteiro, A.C.B., França, R.P., Iano, Y, Khelassi, A., & Razmjooy, N. (2019). Health 4.0: Applications, management, technologies and review. Med Tech J, 2019;2(4):262-76. doi: 10.26415/2572-004X-vol2iss1p262-276. 262.
[65] Billah, M., Waheed, S., & Rahman, M.M. (2017). An automatic gastrointestinal polyp detection system in video endoscopy using fusion of color wavelet and convolutional neural network features. Int. J. Biomedical Imaging. https://doi.org/10.1155/2017/9545920 PMid:28894460 PMCid:PMC5574296
[66] Estrela, V.V., Coelho, A.M. (2013). State-of-the art motion estimation in the context of 3D TV. In: Multimedia Networking and Coding. IGI Global, 148-173. doi:10.4018/978-1-4666-2660-7.ch006. https://doi.org/10.4018/978-1-4666-2660-7.ch006
[67] Liang, H., Liang, W., Lei, Z., Liu, Z., Wang, W., He, J., Zeng, Y., Huang, W., Wang, M., Chen, Y., He, J., & Group, W.O. (2018). Three-dimensional versus two-dimensional video-assisted endoscopic surgery: A meta-analysis of clinical data. World Journal of Surgery, 42, 3658-3668. https://doi.org/10.1007/s00268-018-4681-z PMid:29946785
[68] Ito, Y., Ogawa, T., & Haseyama, M. (2017). Personalized video preference estimation based on early fusion using multiple users' viewing behavior. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3006-3010. https://doi.org/10.1109/ICASSP.2017.7952708
[69] Cruz, B. F., de Assis, J. T., Estrela, V. V., & Khelassi, A. (2019). A compact SIFT-based strategy for visual information retrieval in large image databases. Medical Technologies J., 3(2), 402-412, doi: 10.26415/2572-004X-vol3iss2p402-412.

Most read articles by the same author(s)

1 2 > >>