Meme Kanserinde SUVmax ile Tümör-Stroma Oranı Arasındaki İlişki: Patolojik Bir Korelasyon Çalışması

Öz

Amaç: Çalışmamızda, birçok kanser türünde prognostik bir belirteç olarak kabul edilen tümör-stroma oranı ile yarı kantitatif bir parametre olan lezyon maksimum standardize uptake volüm değeri (SUVmax) arasındaki korelasyonu araştırmak ve eğer anlamlı bir ilişki saptanırsa, SUVmax değerlerinin çok merkezli çalışmalarla desteklendiğinde prognostik bir belirteç olarak da kullanılabileceğini göstermeyi amaçladık. Yöntem: Tamamı kadın olan, meme kanseri tanısı almış ve ikincil primeri bulunmayan toplam 42 hasta çalışmaya dahil edildi. Kemoterapi veya radyoterapi almış hastalar çalışma dışı bırakıldı. Patolojik preparatlar ve evreleme amacıyla çekilmiş F-18 FDG PET/BT arşiv görüntüleri retrospektif olarak incelendi. Tüm hastalar için patolojik tümör-stroma oranı ile PET/BT incelemesinde tümör tracking yöntemiyle hesaplanan SUVmax değerleri elde edildi. Bulgular: Tamamı kadın olan bu çalışmada, hastaların ortalama yaşı 55.86±14.11 (30–79) yıl, ortalama SUVmax değeri 8.18±5.05 (1.26–20.26) ve ortalama tümör-stroma oranı 0.70±0.42 (0.16–1.93) olarak hesaplandı. SUVmax değerleri ile tümör-stroma oranı arasında düşük düzeyde anlamlı pozitif bir korelasyon saptandı (r=0.277, p=0.042). Sonuç: Çalışmamızda, birçok kanser türünde önemli bir prognostik belirteç olarak kabul edilen tümör-stroma oranı ile lezyon SUVmax değerleri arasında düşük düzeyde anlamlı pozitif bir korelasyon olduğu gösterilmiştir. Bu bulguya göre, yeterli hasta sayısı ve çok merkezli çalışmalarla desteklendiği takdirde, SUVmax değerlerinin de prognostik belirteç olarak kullanılabileceği öngörülmektedir. Meme kanserinde SUVmax ile tümör-stroma oranı arasındaki ilişkiyi araştıran başka bir çalışmaya literatürde rastlanmamıştır.

Anahtar Kelimeler

• Meme Kanseri
• SUVmax
• Tümör-stroma oranı

Association Between SUVmax and Tumour-Stroma Ratio in Breast Cancer: A Pathological Correlation Study

Öz

Objective: In our study, we purposed to investigate the correlation between tumour-stroma ratio, which is considered a prognostic marker in many types of cancer, and lesion maximum standardized uptake values (SUVmax), which is a semiquantitative parameter, and to show that, if significant, SUVmax values can also be used as a prognostic marker when supported by multicenter studies. Method: A total of 42 patients, all female, who were diagnosed with breast cancer, had no secondary primary. The patient who had received chemotherapy or radiotherapy treatments, were excluded. Pathological preparations and staging F-18 FDG PET/CT archive images were examined retrospectively. The pathological tumour-stroma ratio and SUVmax calculated by the tumour tracking method in the PET/CT examination were obtained for all patients. Results: In this all-female study, the mean age was calculated as 55.86±14.11(30-79) years, mean SUVmax was 8.18±5.05 (1.26-20.26) and mean tumour-stroma ratio was 0.70±0.42 (0.16-1.93). There was a poor level significant positive correlation between the SUVmax values and tumour-stroma ratio (r=0.277, p=0.042). Conclusion: In our study the tumour stroma ratio, which is considered as an important prognostic marker in many cancer types, correlates with the lesion SUVmax values. According to this information, it is predicted that we can foresee that SUVmax values can be used as prognostic markers when supported by appropriate patient number and multi-center studies. No other studies have examined the correlation between SUVmax and tumour stroma ratio in the breast cancer.

Anahtar Kelimeler

• Breast cancer
• SUVmax
• Tumour-stroma ratio

Kaynakça

1. 1. Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011). Global cancer statistics. CA: A Cancer Journal for Clinicians, 61(2), 69–90.
2. 2. Hoover, R. (1996). Breast cancer: Geographic, migrant and time–trend patterns. In J. S. P. Fortner (Ed.), Accomplishments in cancer research (pp. 403–425). New York, NY: Lippincott–Raven.
3. 3. Baring, C. C., Squires, T. S., & Tang, T. (1993). Cancer statistics 1993. CA: A Cancer Journal for Clinicians, 43, 4– 26.
4. 4. Sivenberg, E., & Lubera, J. (1987). Cancer statistics 1987. CA: A Cancer Journal for Clinicians, 37, 19.
5. 5. Spratt, J. S., & Tabin, G. R. (1995). Gross anatomy of the breast. In W. L. Donegan & J. S. Spratt (Eds.), Cancer of the breast (4th ed., pp. 22–42). Philadelphia, PA: W. B. Saunders.
6. 6. Kalaycı, G., Acarlı, K., Demirkol, K., & Ertekin, C. (2002). Meme anatomisi ve gelişmesi. Genel cerrahi (Cilt 1, pp. 537–542). İstanbul, Türkiye: Nobel.
7. 7. Osborne, M. P. (1991). Breast development and anatomy. In J. R. Harris, S. Helleman, I. C. Henderson, & D. W. Kinve (Eds.), Breast disease (2nd ed., pp. 1–13). Philadelphia, PA: J. B. Lippincott.
8. 8. Romrell, L. J., & Blend, K. I. (1995). Anatomy of the breast, axilla, chest wall and related metastatic sites. In K. I. Blend & E. M. Copeland (Eds.), The breast: Comprehensive management of benign and malignant disease (2nd ed., pp. 16–21). Philadelphia, PA: W. B. Saunders.

9. 9. Kuhns, J. G., & Ackermann, D. M. (1995). Microscopic anatomy of the breast. In W. L. Donegan & J. S. Spratt (Eds.), Cancer of the breast (4th ed., pp. 16–21). Philadelphia, PA: W. B. Saunders.
10. 10. Cooper, A. P. (1845). The anatomy and diseases of the breast. Philadelphia, PA: Lea and Blanchard.
11. 11. Unlu, M., Cetinayak, H., Onder, D., Ecevit, C., Akman, F., Ikiz, A., et al. (2013). The prognostic value of tumour– stroma proportion in laryngeal squamous cell carcinoma. Turkish Journal of Pathology, 29, 27–35.
12. 12. Yanagisawa, N., Li, R., Rowley, D., Liu, H., Kadmon, D., Miles, B. J., et al. (2007). Stromogenic prostatic carcinoma pattern in needle biopsies predicts biochemical recurrence-free survival after radical prostatectomy. Human Pathology, 38, 1611–1620.
13. 13. Mesker, W. E., Junggeburt, J. M., Szuhai, K., de Heer, P., Morreau, H., Tanke, H. J., et al. (2007). The carcinoma– stromal ratio of colon carcinoma is an independent factor for survival compared to lymph node status and tumour stage. Cellular Oncology, 29, 387–398.
14. 14. West, N. P., Dattani, M., McShane, P., Hutchins, G., Grabsch, J., Mueller, W., et al. (2010). The proportion of tumour cells is an independent predictor for survival in colorectal cancer patients. British Journal of Cancer, 103, 1519– 1523.
15. 15. de Kruijf, E. M., van Nes, J. G., van de Velde, C. J., Putter, H., Smit, V. T., Liefers, G. J., et al. (2011). Tumour–stroma ratio in the primary tumour is a prognostic factor in early breast cancer patients, especially in triple-negative carcinoma patients. Breast Cancer Research and Treatment, 125, 687–696.
16. 16. Courrech Staal, E. F., Wouters, M. W., van Sandick, J. W., Takkenberg, M. M., Smit, V. T., Junggeburt, J. M., Spitzer- Naaykens, J. M., et al. (2010). The stromal part of adenocarcinomas of the oesophagus: Does it conceal targets for therapy? European Journal of Cancer, 46, 720–728.
17. 17. Moorman, A. M., Vink, R., Heijmans, H. J., van der Palen, J., & Kouwenhoven, E. A. (2012). The prognostic value of tumour–stroma ratio in triple-negative breast cancer. European Journal of Surgical Oncology, 38, 307–313.
18. 18. Maeshima, A. M., Niki, T., Maeshima, A., Yamada, T., Kondo, H., & Matsuno, Y. (2002). Modified scar grade: A prognostic indicator in small peripheral lung adenocarcinoma. Cancer, 95, 2546–2554.
19. 19. Witkiewicz, A. K., Kline, J., Queenan, M., Brody, J. R., Tsirigos, A., Bilal, E., et al. (2011). Molecular profiling of a lethal tumour microenvironment, as defined by stromal caveolin-1 status in breast cancer. Cell Cycle, 10, 1794–1809.
20. 20. Witkiewicz, A. K., Whitaker-Menezes, D., Dasgupta, A., Philip, N. J., Lin, Z., Gandara, R., et al. (2012). Using the “reverse Warburg effect” to identify high-risk breast cancer patients: Stromal MCT4 predicts poor clinical outcome in triple-negative breast cancers. Cell Cycle, 11, 1108–1117.
21. 21. Christensen, J. D., Colby, T. V., & Patz, E. F. (2010). Correlation of 18F-fluorodeoxyglucose PET standardized uptake values with the cellular composition of stage I non-small-cell lung cancer. Cancer, 116, 4095–4102.
22. 22. Duhaylongsod, F. G., Lowe, V. J., Patz, E. F. Jr., Vaughn, A. L., Coleman, R. E., & Wolfe, W. G. (1995). Lung tumour growth correlates with glucose metabolism measured by fluorine-18 fluorodeoxyglucose positron emission tomography. The Annals of Thoracic Surgery, 60, 1348–1352.
23. 23. Lu, P., Yu, L., Li, Y., & Sun, Y. (2010). A correlation study between maximum standardized uptake values and pathology and clinical staging in non-small-cell lung cancer. Nuclear Medicine Communications, 31, 646–651.
24. 24. Khalaf, M., Abdel-Nabi, H., Baker, J., Shao, Y., Lamonica, D., & Gona, J. (2008). Relation between nodule size and 18F-FDG PET SUV for malignant and benign pulmonary nodules. Journal of Hematology & Oncology, 1, 13.
25. 25. Li, M., Sun, Y., Han, A., Zhao, S., Ma, L., Zheng, J., et al. (2010). Relationship between primary lesion FDG uptake and clinical stage at PET/CT for non-small cell lung cancer patients: An observation. Lung Cancer, 68, 394–397.
26. 26. Al-Sarraf, N., Gately, K., Lucey, J., Aziz, R., Doddakula, K., Wilson, L., et al. (2008). Clinical implication and prognostic significance of standardized uptake value of primary non-small cell lung cancer on positron emission tomography: Analysis of 176 cases. European Journal of Cardio-Thoracic Surgery, 34, 892–897.
27. 27. Ogawa, J., Inoue, H., & Koide, S. (1997). Glucose-transport-type-1-gene amplification correlates with sialyl- Lewis-X synthesis and proliferation in lung cancer. International Journal of Cancer, 74, 189–192.
28. 28. Koksal, D., Demirag, F., Bayiz, H., Ozmen, O., Tatci, E., Berktas, B., et al. (2013). The correlation of SUVmax with pathological characteristics of primary tumour and the value of tumour–lymph node SUVmax ratio for predicting metastasis to lymph nodes in resected NSCLC patients. Journal of Cardiothoracic Surgery, 8, 63.
29. 29. Wu, J., Liang, C., Chen, M., & Su, W. (2016). Association between tumour–stroma ratio and prognosis in solid tumour patients: A systematic review and meta-analysis. Oncotarget, 7(42), 68954–68965.