PhD in Veterinary Sciences for Animal Health and Food Safety

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Curriculum vitae

Phd thesis

Re-evaluation of the clinical tumour-nodes-metastasis (TNM) staging system for canine oral tumours

 1) Background

The oral cavity is a common site for a wide variety of malignant and benign tumours, representing about 6% of all neoplasms in dogs.¹ Recommended treatments and prognosis of oral cancers depend on the tumour histology, location, size, local invasiveness and metastatic rate.^2,3 (Figure 1)

Canine oral tumours are classified using a TNM clinical staging system, that provides information about the prognosis and aids the clinician to plan the proper treatment. The TNM staging system describes the anatomical extent of tumour and it is characterized by 3 different parameters: the maximum diameter of primary tumour (T), the status of regional lymph nodes (N) and the presence of distant metastases (M). This classification identifies 4 clinical stages according to the survival rate.^4-7 (Figure 2) The TNM classification has several limitations, in particular, T does not consider the anatomical differences among dog breeds and the different tumour histotypes. N does not specify which and how many lymph nodes should be considered and removed. Besides, M does not consider the number, the size and the site of distant metastasis.^8,9

2) Specific aims of the project, Methods, Results

This project aims to develop a new staging system that will provide a more accurate prognosis, specific for each tumour histotypes, as in human medicine.^6,7,10 Dogs with malignant oral cancer staged with a CT scan, no distant metastasis, achieved local tumour control, no concurrent life-threatening disease and a minimum follow up of 1 year are enrolled in the study. I have included 77 dogs with oral tumours, histologically classified as 42 malignant melanoma (MM), 15 squamous cell carcinoma (SCC), 9 osteosarcoma (OSA) and 6 fibrosarcoma (FA). I have collected all data for each patient and evaluated the median survival times (MST), disease-free interval (DFI) and time to recurrence (TTR).

To provide more information regarding the local extent of the tumour, I have replaced the T parameter with a “I” index, calculated as the ratio between the tumour size and the oral cavity dimension in two different methods. Based on the CT images, for each dog, both I and a radiologist have measured the maximum tumour diameter, tumour implant surface, the mandibular and maxillary lengths and surfaces.

I have conducted the Spearman rank’s correlation to evaluate the relationship between “I” and T with MST, DFI and TTR both for entire population (no statistical significance) and only for dogs with MM (p<0.05). Considering only dogs with MM, ROC analysis revealed two distinct cut off values for categorizing the population into three classes based on the index “I”. Kaplan-Meier curves are built to evaluate the differences among classes (log-rank test for trend, p<0.05). Linear regression analysis has been used to predict the MST of the dogs based on their “I” values (p<0,05, r² =0.11). For enhancing this model, I have incorporated histological prognostic factors using a multiple linear regression analysis, but the statistical significance has not been reached.¹¹ Logistic regression has been employed to estimate the probability of dogs dying from tumours or lymph node metastasis at initial presentation based on the 'I' values (p<0,05).

The contrast uptake of the lymph nodes has been evaluated by a radiologist, however no association with the presence of lymph nodes metastasis was found (Fisher’s exact test).¹² Kaplan-Meier curves did not reveal any significant differences in terms of survival related to lymph node metastasis.

I have conducted all the statistical analyses under the supervision of Professor Ala.

3) Future developments

The upcoming steps in my research involve the enrolment of more patients; the identification of novel clinical and histological parameters aimed to improve the precision of the mathematical model developed for MM; then, I plan to extend our statistical analyses to the other oral tumours. Lastly, I will evaluate the significance of the sentinel lymph node and the role of lymphadenectomy in the treatment of oral melanoma.

4) Bibliography

1. Verstraete FJ. Mandibulectomy and maxillectomy. Vet Clin North Am Small Anim Pract. 35(4):1009-39,
2. Mikiewicz M, Paździor-Czapula K, Gesek M, et al. Canine and Feline Oral Cavity Tumours and Tumour-like Lesions: A Retrospective Study of 486 Cases (2015-2017). J Comp Pathol. 172:80-87, 2019.
3. Liptak JM. Oral tumors. In: Vail DM, Thamm DH, Liptak JM, eds. Withrow and MacEwen's Small Animal Clinical Oncology. 6th ed. St. Louis: Elsevier; 432-448, 2020.
4. Owen LN: TNM classification of tumors in domestic animals, ed 1, Geneva, WHO, 1980.
5. Brierley J, O'Sullivan B, Asamura H, et al. Global Consultation on Cancer Staging: promoting consistent understanding and use. Nat Rev Clin Oncol.16(12):763-771, 2019.Mupparapu M, Shanti RM. Evaluation and Staging of Oral Cancer. Dent Clin North Am.62(1):47-58, 2018.
6. Huang SH, O'Sullivan B. Overview of the 8th Edition TNM Classification for Head and Neck Cancer. Curr Treat Options Oncol.18:40, 2017.
7. Sobin LH. TNM: evolution and relation to other prognostic factors. Semin Surg Oncol.21(1):3-7 2003.
8. Hahn KA, DeNicola DB, Richardson RC, et al. Canine oral malignant melanoma: prognostic utility of an alternative staging system. J Small Anim Pract.;35(5):251-256, 1994.
9. Bergman PJ. Canine oral melanoma. Clin Tech Small Anim Pract. ;22(2):55-60, 2007.
10. Ghantous Y, Nashef A, Sidransky D, et al. Clinical and Prognostic Significance of the Eighth Edition Oral Cancer Staging System. Cancers (Basel); 14(19):4632, 2022.
11. Smedley RC, Sebastian K, Kiupel M. Diagnosis and Prognosis of Canine Melanocytic Neoplasms. Vet Sci.9(4):175, 2022.
12. Grimes JA, Mestrinho LA, Berg J, et al. Histologic evaluation of mandibular and medial retropharyngeal lymph nodes during staging of oral malignant melanoma and squamous cell carcinoma in dogs. J Am Vet Med Assoc. 254(8):938-943, 2019.

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