Optimizing radiation therapy treatments by exploring tumour ecosystem dynamics in-silico

In this contribution, we propose a system-level compartmental population dynamics model of tumour cells that interact with the patient (innate) immune system under the impact of radiation therapy (RT). The resulting in silico - model enables us to analyse the system-level impact of radiation on the tumour ecosystem. The Tumour Control Probability (TCP) was calculated for varying conditions concerning therapy fractionation schemes, radio-sensitivity of tumour sub-clones, tumour population doubling time, repair speed and immunological elimination parameters. The simulations exhibit a therapeutic benefit when applying the initial 3 fractions in an interval of 2 days instead of daily delivered fractions. This effect disappears for fast-growing tumours and in the case of incomplete repair. The results suggest some optimisation potential for combined hyperthermia-radiotherapy. Regarding the sensitivity of the proposed model, cellular repair of radiation-induced damages is a key factor for tumour control. In contrast to this, the radio-sensitivity of immune cells does not influence the TCP as long as the radio-sensitivity is higher than those for tumour cells. The influence of the tumour sub-clone structure is small (if no competition is included). This work demonstrates the usefulness of in silico – modelling for identifying optimisation potentials

Spatio-temporal, multicellular and Monte Carlo track-based model of radiotherapy in silico

A notable short-coming in the way radiotherapy is currently practised is that patient-specific radiobiology is minimally and rarely accounted for in the treatment planning process. If this is to be remedied, in silico radiobiological models of radiotherapy will play an essential role. By increasing the complexity of such models, greater accuracy and utility are gained, along with opportunities for new radiobiological insights. A new computational model was developed called “Stochastic Squared Radiotherapy” (S2RT). It is a spatio-temporal/four-dimensional radiotherapy model for head and neck squamous cell carcinoma (HNSCC), that uses stochastic modelling of tumour cells and Monte Carlo track structure simulations. The four main components of the model are tumour growth, tumour irradiation, DNA damage induction and cell death/survival. The tumour growth module generates the initial multicellular tumour and evolves it spatio-temporally in-between dose fractions. Ellipsoidal tumour cells occupy randomised, non-overlapping locations. Cells are pushed outward and fall inward following cell division and cell death, respectively. An epithelial cell hierarchy of stem, transit and differentiated cells is modelled. A connected and chaotic network of blood vessels grows interwoven between the cells. Chronic hypoxia and necrotic cells are simulated at distances far from blood vessels. Hypoxic cells divide slower and necrotic cells are gradually resorbed. Accelerated repopulation may be simulated by increasing the symmetric division of cancer stem cells. Dose fractions are delivered to the tumour in Monte Carlo simulations of radiation tracks. The multicellular tumour is voxelised into nucleus, cytoplasm and intercellular voxels of size 2 μm and imported into Geant4 to perform irradiation. A Geant4 application was developed that uses Geant4-DNA to simulate low-energy physical interactions and radiolytic chemical tracks to account for the indirect effect. The tracks through cell nuclei are converted to DNA damage, including doublestrand breaks (DSBs). This was done by spatially clustering physical interactions such as ionisations and excitations and hydroxyl radical interactions into simulated DNA volumes, each of size 10 base pairs. The DNA damage was made dependent upon the cellular pO2 by increasing the efficiency of DNA radical-to-strand break conversion with increasing pO2. In the model, complex DSBs (cDSBs) produced DNA free-ends that can misrejoin with one another and produce exchange-type chromosome aberrations. Complete exchanges are assumed. The misrejoining probability is modelled as an exponential function of the initial distance between the two cDSBs involved. Cells die if they contain an asymmetric chromosome aberration. Notable findings from the S2RT model include: 1. Symmetric division of cancer stem cells may be as high as 50% during accelerated repopulation. 2. The decrease in the oxygen enhancement ratio for DSB induction with increasing LET can be attributed to spatial clustering alone; i.e., at higher LET, the additional strand breaks produced in the presence of oxygen seldom result in additional DSBs. Instead, they increase DSB complexity. 3. For MV x-rays, misrejoinings between cDSBs produced by the same primary x-ray (including its secondary electrons) do not contribute appreciably to the linear components of chromosome aberration production and cell killing. For HNSCC, which does have an appreciable linear component of cell killing, unrejoined DNA ends (i.e. incomplete exchanges and terminal deletions) may be important. There is promise of accuracy and utility in S2RT because it is predicated on simulating Monte Carlo tracks through a multicellular tumour and simulating cellular tumour growth in-between dose fractions. DNA damage induction and subsequent processes like DNA free-end misrejoining and cell death are modelled stochastically using the track structure. Simulated tumours have realistic spatial distributions of cellular pO2 in relation to the blood vessels, so one can carefully investigate the effect of microscopic regions of tumour hypoxia on treatment efficacy. Since tumour irradiation is performed with track structure, the radiation quality modelled can easily be extended to high LET beams. Modelling a connected network of blood vessels in the tumour also enables consideration of vascular damages. In particular, the model may be used in the future to investigate the extent to which wide-spread vascular damages are responsible for the efficacy of high dose per fraction treatments such as stereotactic body radiotherapy.Thesis (Ph.D.) -- University of Adelaide, School of Physical Sciences, 201

Translational Research in Cancer

Translational research in oncology benefits from an abundance of knowledge resulting from genome-scale studies concerning the molecular pathways involved in tumorigenesis. Translational oncology represents a bridge between basic research and clinical practice in cancer medicine. The vast majority of cancer cases are due to environmental risk factors. Many of these environmental factors are controllable lifestyle choices. Experimental cancer treatments are studied in clinical trials to compare the proposed treatment to the best existing treatment through translational research. The key features of the book include: 1) New screening for the development of radioprotectors: radioprotection and anti-cancer effect of β-Glucan (Enterococcus faecalis) 2) Translational perspective on hepatocellular carcinoma 3) Brachytherapy for endometrial cancer 4) Discovery of small molecule inhibitors for histone methyltransferases in cance

Oncologic Thermoradiotherapy: Need for Evidence, Harmonisation, and Innovation

The road of acceptance of oncologic thermotherapy/hyperthermia as a synergistic modality in combination with standard oncologic therapies is still bumpy. This is partially due to the lack of level I evidence from international, multicentric, randomized clinical trials including large patient numbers and a long term follow-up. Therefore we need more level I EVIDENCE from clinical trials, we need HARMONISATION and global acceptance for existing technologies and a common language understood by all stakeholders and we need INNOVATION in the fields of biology, clinics and technology to move thermotherapy/hyperthermia forward. This is the main focus of this reprint. In this reprintyou find carefully selected and peer-reviewed contributions from Africa, America, Asia, and Europe. The published papers from leading scientists from all over the world covering a broad range of timely research topics might also help to strengthen thermotherapy on a global level

In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application

The Special Issue "In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application", edited by Marta Baiocchi and Ann Zeuner for Cancers, collects original research papers and reviews, depicting the current state and the perspectives of CRC models for preclinical and translational research. Original research papers published in this issue focus on some of the hottest topics in CRC research, such as circulating tumor cells, epigenetic regulation of stemness states, new therapeutic targets, molecular CRC classification and experimental CRC models such as organoids and PDXs. Additionally, four reviews on CRC stem cells, immunotherapy and drug discovery provide an updated viewpoint on key topics linking benchtop to bedside research in CRC

The HYP-RT Hypoxic Tumour Radiotherapy Algorithm and Accelerated Repopulation Dose per Fraction Study

The HYP-RT model simulates hypoxic tumour growth for head and neck cancer as well as radiotherapy and the effects of accelerated repopulation and reoxygenation. This report outlines algorithm design, parameterisation and the impact of accelerated repopulation on the increase in dose/fraction needed to control the extra cell propagation during accelerated repopulation. Cell kill probabilities are based on Linear Quadratic theory, with oxygenation levels and proliferative capacity influencing cell death. Hypoxia is modelled through oxygen level allocation based on pO2 histograms. Accelerated repopulation is modelled by increasing the stem cell symmetrical division probability, while the process of reoxygenation utilises randomised pO2 increments to the cell population after each treatment fraction. Propagation of 108 tumour cells requires 5–30 minutes. Controlling the extra cell growth induced by accelerated repopulation requires a dose/fraction increase of 0.5–1.0 Gy, in agreement with published reports. The average reoxygenation pO2 increment of 3 mmHg per fraction results in full tumour reoxygenation after shrinkage to approximately 1 mm. HYP-RT is a computationally efficient model simulating tumour growth and radiotherapy, incorporating accelerated repopulation and reoxygenation. It may be used to explore cell kill outcomes during radiotherapy while varying key radiobiological and tumour specific parameters, such as the degree of hypoxia