Abstract
Although much is known about the molecular biology and genomics of breast cancer at the subcellular level, clinical manifestations of the disease and its diagnosis, prognosis and treatment continue to pose major challenges. This chapter is an attempt at critical review and analysis of a few principal hypotheses about the natural history of invasive breast cancer and the effects of surgery. We address a fundamental question regarding the universality of benefits of surgery and whether it should be dropped for some categories of breast cancer patients. We present a mathematical model of metastasis that allows for evaluating the post-surgery dynamics of the metastatic cascade. We show that statistical inference from the results of clinical trials may lead to false knowledge and irreproducible results. Finally, we make a case for identification of the categories of breast cancer patients that could benefit from surgery through a model-based analysis of post-surgery metastatic relapse times. The mathematical model could also serve as an in silico surrogate for clinical trials comparing various breast cancer treatments with and without surgery.
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References
Fisher B (1980) Laboratory and clinical research in breast cancer: a personal adventure. The David A. Karnofsky memorial lecture. Cancer Res 40:3863–3874
Cooke R (2001) Dr. Folkman’s war: angiogenesis and the struggle to defeat cancer. Random House, New York
Folkman J (1974) Tumor angiogenesis factor. Cancer Res 34:2109–2113
Moiseenko VM (2002) “Natural history” of breast cancer growth. Pract Oncol 3(1):6–14 (in Russian)
Holmgren K, O’Reilly MS, Folkman J (1995) Dormancy of micrometastases: balanced proliferation and apoptosis in the presence of angiogenesis suppression. Nat Med 1:149–153
Demicheli R, Retsky MW, Swartzendruber DE, Bonadonna G (1997) Proposal for a new model of breast cancer metastatic development. Ann Oncol 8:1075–1080
Fisher B (1999) From Halsted to prevention and beyond: advances in the management of breast cancer during the twentieth century. Eur J Cancer 35:1963–1973
Douglas JRS (1971) Significance of the size distribution of bloodborne metastases. Cancer 27:379–390
Cox B (1997) Variation in the effectiveness of breast screening by year of follow-up. JNCI Monographs 22:69–72
Gøetsche P (2012) Mammography screening: truth, lies and controversy. Radcliffe Publishing, London
Baines CJ (2011) Rational and irrational issues in breast cancer screening. Cancers 3:252–266
Welch HG, Black WC (2010) Overdiagnosis in cancer. JNCI 102(9):605–613
Sachs RK, Heidenreich WF, Brenner DJ (1996) Dose timing in tumor radiotherapy: considerations of cell number stochasticity. Math Biosci 138:131–146
Fakir H, Hlatky L, Li H, Sachs R (2013) Repopulation of interacting tumor cells during fractionated radiotherapy: stochastic modeling of the tumor control probability. Med Phys 40(12):121716
Hanin L, Zaider M (2014) Optimal schedules of fractionated radiation therapy by way of the greedy principle: biologically-based adaptive boosting. Phys Med Biol 59:4085–4098
Poincaré H (1952) Science and hypothesis. Dover Publications, New York
Boyd W (1966) The spontaneous regression of cancer. Thomas, Springfield, IL
Everson TC, Cole WH (1966) Spontaneous regression of cancer. Saunders, Philadelphia, PA
Zahl P-H, Mæhlen J, Welch HG (2008) The natural history of invasive breast cancer detected by screening mammography. Arch Intern Med 168:2311–2316
Smithers DW (1967) Spontaneous regression of cancer. Ann R Coll Surg Engl 41(Suppl):160–162
Sonnenschein C, Soto AM (2000) Somatic mutation theory of carcinogenesis: why it should be dropped and replaced. Mol Carcinog 29:205–211
Soto AM, Sonnenschein C (2004) The somatic mutation theory of cancer: growing problems with the paradigm? BioEssays 26:1097–1107
Sonnenschein C, Soto AM (2008) Theories of carcinogenesis: an emerging perspective. Semin Cancer Biol 18:372–377
Andersen J, Nielsen M, Jensen J (1985) Essential histological findings in the female breast at autopsy. In: Zander J, Baltzer J (eds) Early breast cancer. Berlin, Springer, pp 52–63
Hanin L, Rose J (2016) Uncovering the natural history of cancer from post mortem cross-sectional diameters of hepatic metastases. Math Med Biol 33(4):397–416
Hanin L, Seidel K, Stoevesandt D (2016) A “universal” model of metastatic cancer, its parametric forms and their identification: what can be learned from site-specific volumes of metastases. J Math Biol 72(6):1633–1662
Ehrlich P (1906) Experimentelle Karzinomstudien an Mäusen. Arch Koiglichen Inst Exp Ther Frankfurt am Main 1:65–103
Bashford E, Murray J, Cramer W (1907) The natural and induced resistance of mice to the growth of cancer. Proc R Soc Lond 79:164–187
Gorelik E (1983) Concomitant tumor immunity and resistance to a second tumor challenge. Adv Cancer Res 39:71–120
Demicheli R, Retsky M, Hrushesky WJ, Baum M, Gukas ID (2008) The effects of surgery on tumor growth: a century of investigations. Ann Oncol 19:1821–1828
Retsky M, Demicheli R, Hrushesky W, Baum M, Gukas I (2010) Surgery triggers outgrowth of latent distant disease in breast cancer: an inconvenient truth? Cancers 2:305–337
Peeters CFJM, de Waal RMW, Wobbes T, Westphal JR, Ruers TJM (2006) Outgrowth of human liver metastases after resection of the primary colorectal tumor: a shift in the balance between apoptosis and proliferation. Int J Cancer 119:1249–1253
Ang KK, Thames HD, Jones SD, Jiang G-L, Milas L, Peters LJ (1988) Proliferation kinetics of a murine fibrosarcoma during fractionated irradiation. Radiat Res 116:327–336
Dillekås H, Transeth M, Pilskog M, Assmus J, Straume O (2014) Differences in metastatic patterns in relation to time between primary surgery and first relapse from breast cancer suggests synchronized growth of dormant micrometastases. Breast Cancer Res Treat 146:627–636
Georgiu GK, Igglezou M, Sainis I, Vareli K, Batsis H, Briasoulis E, Fatouros M (2013) Impact of breast cancer surgery on angiogenesis circulating biomarkers: a prospective longitudinal study. World J Surg Oncol 11:213
Prehn RT (1993) Two competing influences that may explain concomitant tumor resistance. Cancer Res 53:3266–3269
Maida V, Ennis M, Kuziemsky C, Corban J (2009) Wounds and survival in cancer patients. Eur J Cancer 45:3237–3244
Lanca T, Silva-Santos B (2012) The split nature of tumor-infiltrating leukocytes. Implications for cancer surveillance and immunotherapy. Oncoimmunology 1(5):717–725
Forget P, Vandenhende J, Berliere M, Machiels JP, Nussbaum B, Legrand C, DeKock M (2010) Do intraoperative analgesics influence breast cancer recurrence after mastectomy? A retrospective analysis. Anesth Analg 110(6):1630–1635
Retsky M, Rogers R, Demicheli R, Hrushesky WJ, Gukas I, Vaidya JS, Baum M, Forget P, DeKock M, Pachmann K (2012) NSAID analgesic ketorolac used perioperatively may suppress early breast cancer relapse: particular relevance to triple negative subgroup. Breast Cancer Res Treat 134(2):881–888
Retsky M, Demicheli R, Hrushesky WJM, Forget P, DeKock M, Gukas I, Rogers R, Baum M, Pachmann K, Vaidya JS (2012) Promising development from translational or perhaps anti-translational research in breast cancer. Clin Transl Med 1:17
Retsky M, Demicheli R, Hrushesky WJM, Forget P, DeKock M, Gukas I, Rogers RA, Baum M, Sukhatme V, Vaidya JS (2013) Reduction of breast cancer relapses with perioperative non-steroidal anti-inflammatory drugs: new findings and a review. Curr Med Chem 20(33):4163–4176
Demicheli R, Osaro E, Retsky M, Forget P, Vaidya JS, Bello SO (2016) Protocol for a randomised, multicentre, double blinded phase III study of perioperative ketorolac in women of African descent with operable breast cancer. Jacobs J Intern Medicine 2(1):017
Bloom H, Richardson W, Harries E (1962) Natural history of untreated breast cancer (1805–1933). British Med J 2:213–221
Brinkley D, Haybittle J (1975) The curability of breast cancer. Lancet 2(7925):95–97
Karrison TG, Ferguson DJ, Meier P (1999) Dormancy of mammary carcinoma after mastectomy. J Natl Cancer Inst 91:80–85
Rutqvist L, Wallgren A (1985) Longterm survival of 458 young breast cancer patients. Cancer 55:658–665
Hanin LG, Rose J, Zaider M (2006) A stochastic model for the sizes of detectable metastases. J Theor Biol 243:407–417
Hanin LG (2008) Distribution of the sizes of metastases: mathematical and biomedical considerations. In: Tan WY, Hanin LG (eds) Handbook of cancer models with applications. World Scientific, Singapore, pp 141–169
Hanin L, Zaider M (2011) Effects of surgery and chemotherapy on metastatic progression of prostate cancer: evidence from the natural history of the disease reconstructed through mathematical modeling. Cancers 3:3632–3660
Hanin L, Pavlova L (2016) A quantitative insight into metastatic relapse of breast cancer. J Theor Biol 394:172–181
Hadfield G (1954) The dormant cancer cell. Br Med J 2:607–610
Sugarbaker EV, Ketcham AS, Cohen AM (1971) Studies of dormant tumor cells. Cancer 28:545–552
Meltzer A (1990) Dormancy and breast cancer. J Surg Oncol 43:181–188
Demicheli R (2001) Tumour dormancy: findings and hypotheses from clinical research on breast cancer. Semin Cancer Biol 11:297–306
Dick JE (2003) Breast cancer stem cells revealed. PNAS 100(7):3547–3549
Al-Hajj M, Wicha MS, Benito-Hernandez A, Morrison SJ, Clarke MF (2003) Prospective identification of tumorigenic breast cancer cells. PNAS 100(7):3983–3988
Kai K, Arima Y, Kamiya T, Saya H (2010) Breast cancer stem cells. Breast Cancer 17:80–85
Retsky M, Demicheli R (2014) Multimodal hazard rate for relapse in breast cancer: quality of data and calibration of computer simulation. Cancers 6:2343–2355
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Hanin, L. (2017). Do Breast Cancer Patients Benefit from Surgery? Hypotheses, Mathematical Models and False Beliefs. In: Retsky, M., Demicheli, R. (eds) Perioperative Inflammation as Triggering Origin of Metastasis Development. Springer, Cham. https://doi.org/10.1007/978-3-319-57943-6_7
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DOI: https://doi.org/10.1007/978-3-319-57943-6_7
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