From cell population models to tumor control probability: including cell cycle effects.
نویسندگان
چکیده
BACKGROUND Classical expressions for the tumor control probability (TCP) are based on models for the survival fraction of cancer cells after radiation treatment. We focus on the derivation of expressions for TCP from dynamic cell population models. In particular, we derive a TCP formula for a generalized cell population model that includes the cell cycle by considering a compartment of actively proliferating cells and a compartment of quiescent cells, with the quiescent cells being less sensitive to radiation than the actively proliferating cells. METHODS We generalize previously derived TCP formulas of Zaider and Minerbo and of Dawson and Hillen to derive a TCP formula from our cell population model. We then use six prostate cancer treatment protocols as a case study to show how our TCP formula works and how the cell cycle affects the tumor treatment. RESULTS The TCP formulas of Zaider-Minerbo and of Dawson-Hillen are special cases of the TCP formula presented here. The former one represents the case with no quiescent cells while the latter one assumes that all newly born cells enter a quiescent cell phase before becoming active. From our case study, we observe that inclusion of the cell cycle lowers the TCP. CONCLUSION The cell cycle can be understood as the sequestration of cells in the quiescent compartment, where they are less sensitive to radiation. We suggest that our model can be used in combination with synchronization methods to optimize treatment timing.
منابع مشابه
The Role of radiobiological parameters on Tumor control probability (TCP) in prostate cancer
Introduction: The aim of this study was to evaluation radiobiological modeling parameters on tumor control probability (TCP) for prostate cancer in three different models. These parameters included α⁄β ratios and cell surviving fraction at 2 Gy (SF2). Materials and Methods: The Poisson, equivalent uniform dose (EUD) and linear quadratic (LQ) models was used as...
متن کاملDynamical Analysis of Yeast Cell Cycle Using a Stochastic Markov Model
Introduction: The cell cycle network is responsible of control, growth and proliferation of cells. The relationship between the cell cycle network and cancer emergence, and the complex reciprocal interactions between genes/proteins calls for computational models to analyze this regulatory network. Ample experimental data confirm the existence of random behaviors in the interactions between gene...
متن کاملDynamical Analysis of Yeast Cell Cycle Using a Stochastic Markov Model
Introduction: The cell cycle network is responsible of control, growth and proliferation of cells. The relationship between the cell cycle network and cancer emergence, and the complex reciprocal interactions between genes/proteins calls for computational models to analyze this regulatory network. Ample experimental data confirm the existence of random behaviors in the interactions between gene...
متن کاملMutations of p53 Gene in Skin Cancers: a Case Control Study
Background: The most frequently mutated tumor suppressor gene found in human cancer is p53. In a normal situation, p53 is activated upon the induction of DNA damage to either arrest the cell cycle or to induce apoptosis. However, when mutated, p53 is no longer able to properly accomplish these functions. The aim of this study was to investigate the expression of p53 gene in cases of skin cancer...
متن کاملRole of crocin in several cancer cell lines: An updated review
Cancer is a major public health problem worldwide. The most important considerable features of cancer cells are uncontrolled proliferation, up-regulated differentiation, and immortality. Crocin, as a bioactive compound of saffron and as a water-soluble carotenoid has radical scavenging, anti-hyperlipidemia, memory improving, and inhibition of tumor growth effects. The present review was designe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Acta oncologica
دوره 49 8 شماره
صفحات -
تاریخ انتشار 2010