Single-cell cell-fate decisions in cancer treatment
As part of the current standard treatment, most cancer patients receive a combination of chemotherapy and radiotherapy. Despite its success, still many patients gain little or no benefit from this treatment, as evidenced from the elevated rates of locoregional recurrence, distant metastatic spread, and cancer deaths. Unfortunately, those patients will nevertheless suffer the short and long-term side effects of the inefficient therapy. My ultimate aim is to develop patient-specific strategies that maximize the damage in tumor cells while minimizing the damage to normal cells.
After the chemo- or radiotherapy a fraction of tumor cells will die, some cells will remain quiescent, while other cells will survive and continue dividing. This is a characteristic response to cancer therapy known as fractional response, where a subpopulation of cells survives the treatment. My research focuses on studying the cellular events and signaling dynamics that control the heterogeneous cell fate response of individual cells in time. Specifically, how internal cycling factors, such as the circadian clock, the cell cycle, and the p53 protein dynamics interact with the DNA damage response pathway to determine the response to radiotherapy and chemotherapy in cancer cells.
I develop methods that combine long-term live single-cell microscopy with time series analysis and mathematical modeling to track the evolving internal cellular state and the outcome cell fate. Gaining understanding on the internal state and dynamics of cell fate decision of individual tumor cells will help us to identify sensitive cellular states and to design optimal schedules for future cancer treatments.
This project is done in collaboration with the Laboratory of Galit Lahav from the Systems Biology Department at Harvard Medical School and the Laboratory of Jacob Stewart-Ornstein from the Department of Computational & Systems Biology from the School of Medicine, University of Pittsburgh.
My experimental pipeline to design and encode fluorescent markers, track individual cellular rhythms and quantify the outcome cell fate decisions in our long-term live setup.
Mammalian Circadian Clock - from single cells to human behaviour
Since millions of years the spinning of the Earth imposes daily periodically recurring environmental conditions on its inhabitants. Most organisms living on our planet have adapted by evolving their own internal about a day oscillator. This endogenous circadian oscillatory system controls an organism’s daily internal rhythms. In mammals, the central pacemaker responsible for generating such internal pace is the suprachiasmatic nucleus. The suprachiasmatic nucleus (SCN) is located in the base of the brain, in a region called the hypothalamus just above the optic chiasm, where the two optic nerves cross over. This tiny neural nucleus is responsible for controlling endogenous circadian rhythms. Many different body functions like sleep-wake cycles, body temperature and endocrine rhythms are regulated by the outputs of this nucleus.
Single-cell circadian rhythms of well-synchronized SCN neurons. Bioluminescence signal from PER2::LUC mouse brain slice.
Acquired by Ute Abraham from Achim's Kramer Lab
Intracellular Coupling and Entrainment Mechanisms
In addition to the SCN, peripheral oscillators, such as lung tissue, exhibit damped and usually less precise oscillations, which are thought to be brought about by the lack of intercellular coupling. Both SCN and oscillators in peripheral tissues share almost identical single-cell molecular clocks, but they behave surprisingly different upon external periodic perturbations (entrainment). Carrying out a combined theoretical and experimental study of whole tissue and single-cell circadian oscillations, my work has contributed to the understanding of the central role played by the intercellular coupling that explains the entrainment differences. In a separate theoretical study we focused on the different dynamics from hypothesized models of intercellular coupling. Our predictions clarified how coupling mechanisms affect entrainment properties.
* equal contribution.
An interative loop between theoretical tools, single cell microscopy with pharmacological interventions and time series analysis.
Circadian desynchronization and Timescales of entrainment
Experiments elucidating SCN heterogeneity are often invasive and thus implicitly modify the SCN tissue in an unknown manner. An novel experimental protocol was proposed to non-invasively dissociate this circadian oscillatory network in vivo. Rats exposed to exotic short Light-Dark cycles express two stable circadian motor activity rhythms (a fast and a slow rhythm). Motivated by these exciting works that characterized SCN heterogeneity, we developed a computational model and made predictions to help elucidate the sources of the observed heterogeneity (see first publication below). In addition, when an oscillator is entrained, its endogenous period is adjusted to that of the external recurring environment. Despite its heterogeneity, the SCN has the striking ability of fast entrainment. We have identified the core oscillator properties that determine the timescales to entrainment.
Generic properties derived from the theory of coupled oscillators explain the observed differences in the timescales of entraiment.
Human Chronotypes and Seasonal effects
Commonly known as the “early birds” or “night owls”, a person's chronotype is the propensity for the individual to sleep at a particular time during the day. A central question in human circadian research is to understand the interaction of the internal and environmental components that determine this chronotypes. Multiple major studies have characterized human chronotypes and study the distributions of human chronotypes but little is known about the factors that determine the shape of this distributions. In a series of works we have provided a framework to explain the distributions observed in human chronotypes and how the wake up time (phase of entrainment) depends on seasons and on additional internal human circadian clock parameters such as relaxation times and inter-cellular coupling.
The relationship between entrainment range and phase of entraiment
Perturbation and Information theory to study circadian oscillators.
Phase response curves are widely used in circadian clocks, neuroscience and heart physiology. They quantify the response of an oscillator to pulse-like perturbations. Phase response curves provide valuable information on the properties of oscillators and their synchronization. In the first publication listed below we discuss biological self-sustained oscillators (circadian clock, physiological rhythms, etc.) in the context of nonlinear dynamics theory. While direct synchronization by light is restricted to light-sensitive clock cells (e.g. in the eye), temperature cycles can be perceived by the majority of body cells, rendering it an elegant means to study environmental information transfer in mammalian clock cells. We studied the role of temperature oscillations as a zeitgeber for peripheral tissues. We combined information theory and theory of coupled oscillators to generate a set of theoretical predictions and tested them experimentally. See book chapeter below.
The generation of a behavior involves interactions between the nervous system, the morphology of the peripheral system and the environment. The biomechanics of a peripheral system imposes constraints on the neural control, and also provides opportunities for the emergence of complexity in behavior. A rich example is birdsong, where neural instructions drive a complex respiratory system in order to activate the vocal organ. The dynamical state of the respiratory system feeds back into the nuclei in charge of expiration and inspiration, and therefore the emerging dynamics can be potentially extremely rich. As part of my master thesis I use bifucation theory and simulations to inspected the respiratory patterns that can be generated as the result of the interaction of the respiratory nuclei and the respiratory peripheral system.
This work was done at the laboratory of Gabriel Mindlin from Buenos Aires University.