Exploiting evolution to treat drug resistance: Combination therapy and the double bind

Although many anti cancer therapies are successful in killing a large percentage of tumour cells when initially administered, the evolutionary dynamics underpinning tumour progression mean that often resistance is an inevitable outcome, allowing for new tumour phenotypes to emerge that are unhindered by the therapy. Research in the field of ecology suggests that an evolutionary double bind could be an effective way to treat tumours. In an evolutionary double bind two therapies are used in combination such that evolving resistance to one leaves individuals more susceptible to the other. In this paper we present a general evolutionary game theory model of a double bind to study the effect that such approach would have in cancer. Furthermore we use this mathematical framework to understand recent experimental results that suggest a synergistic effect between a p53 cancer vaccine and chemotherapy. Our model recapitulates the experimental data and provides an explanation for its effectiveness based on the commensalistic relationship between the tumour phenotypes

The impact of cellular characteristics on the evolution of shape homeostasis

The importance of individual cells in a developing multicellular organism is well known but precisely how the individual cellular characteristics of those cells collectively drive the emergence of robust, homeostatic structures is less well understood. For example cell communication via a diffusible factor allows for information to travel across large distances within the population, and cell polarisation makes it possible to form structures with a particular orientation, but how do these processes interact to produce a more robust and regulated structure? In this study we investigate the ability of cells with different cellular characteristics to grow and maintain homeostatic structures. We do this in the context of an individual-based model where cell behaviour is driven by an intra-cellular network that determines the cell phenotype. More precisely, we investigated evolution with 96 different permutations of our model, where cell motility, cell death, long-range growth factor (LGF), short-range growth factor (SGF) and cell polarisation were either present or absent. The results show that LGF has the largest positive impact on the fitness of the evolved solutions. SGF and polarisation also contribute, but all other capabilities essentially increase the search space, effectively making it more difficult to achieve a solution. By perturbing the evolved solutions, we found that they are highly robust to both mutations and wounding. In addition, we observed that by evolving solutions in more unstable environments they produce structures that were more robust and adaptive. In conclusion, our results suggest that robust collective behaviour is most likely to evolve when cells are endowed with long range communication, cell polarisation, and selection pressure from an unstable environment

A mathematical model of tumor self-seeding reveals secondary metastatic deposits as drivers of primary tumor growth

Two models of circulating tumor cell (CTC) dynamics have been proposed to explain the phenomenon of tumor 'self-seeding', whereby CTCs repopulate the primary tumor and accelerate growth: Primary Seeding, where cells from a primary tumor shed into the vasculature and return back to the primary themselves; and Secondary Seeding, where cells from the primary first metastasize in a secondary tissue and form microscopic secondary deposits, which then shed cells into the vasculature returning to the primary. These two models are difficult to distinguish experimentally, yet the differences between them is of great importance to both our understanding of the metastatic process and also for designing methods of intervention. Therefore we developed a mathematical model to test the relative likelihood of these two phenomena in the subset of tumours whose shed CTCs first encounter the lung capillary bed, and show that Secondary Seeding is several orders of magnitude more likely than Primary seeding. We suggest how this difference could affect tumour evolution, progression and therapy, and propose several possible methods of experimental validation.Comment: 20 pages, 4 figure

Sistem Informasi Pencatatan Material Untuk Pengadaan Barang Masuk Dan Keluar

Manajemen material pada proyek konstruksi sipil yang kurang baik seringkali mengakibatkan keterlambatan penyelesaian proyek. Dapat ditemukan beberapa masalah di lapangan seperti pembuatan dokumentasi data pembelian & penggunaan material konstruksi dan laporan yang masih dilakukan secara manual, sulitnya di lapangan untuk mengecek ketersediaan material konstruksi dan dibutuhkannya proses autorisasi untuk mengeluarkan material konstruksi dari gudang. Untuk menyelesaikan masalah di atas, dibutuhkan bantuan dari bidang ilmu lain, dalam hal ini Sistem Informasi untuk membantu memanajemen material pada sebuah proyek konstruksi. Dengan adanya Sistem Informasi dapat ditemukan masalah pada sistem di lapangan yang dinilai dapat dirubah, kemudian dibuat sebuah sistem baru untuk menyelesaikan masalah tersebut. Dengan adanya aplikasi dengan bahasa pemrograman Java ini diharapkan dapat membantu pihak – pihak yang bekerja pada sebuah proyek konstruksi untuk memanajemen material di lapangan.Dengan menggunakan aplikasi ini manajemen material akan menjadi lebih mudah, cepat, aman, efisien, akan ada pengurangan dalam penggunaan kertas kerja dan pengurangan pekerjaan yang masih dilakukan secara manual

Investigating prostate cancer tumour-stroma interactions - clinical and biological insights from an evolutionary game

BACKGROUND: Tumours are made up of a mixed population of different types of cells that include normal structures as well as ones associated with the malignancy, and there are multiple interactions between the malignant cells and the local microenvironment. These intercellular interactions, modulated by the microenvironment, effect tumour progression and represent a largely under appreciated therapeutic target. We use observations of primary tumor biology from prostate cancer to extrapolate a mathematical model: specifically; it has been observed that in prostate cancer three disparate cellular outcomes predominate: (i) the tumour remains well differentiated and clinically indolent - in this case the local stromal cells may act to restrain the growth of the cancer; (ii) early in its genesis the tumour acquires a highly malignant phenotype, growing rapidly and displacing the original stromal population (often referred to as small cell prostate cancer) - these less common aggressive tumours are relatively independent of the local microenvironment; and, (iii) the tumour co-opts the local stroma - taking on a classic stromagenic phenotype where interactions with the local microenvironment are critical to the cancer growth. METHODS: We present an evolutionary game theoretical construct that models the influence of tumour-stroma interactions in driving these outcomes. We consider three characteristic and distinct cellular populations: stromal cells, tumour cells that are self-reliant in terms of microenvironmental factors and tumour cells that depend on the environment for resources but can also co-opt stroma. 
RESULTS: Using evolutionary game theory we explore a number of different scenarios that elucidate the impact of tumour-stromal interactions on the dynamics of prostate cancer growth and progression and how different treatments in the metastatic setting can affect different types of tumors.
CONCLUSIONS: The tumour microenvironment plays a crucial role selecting the traits of the tumour cells that will determine prostate cancer progression. Equally important, treatments like hormone therapy affect the selection of these cancer phenotypes making it very important to understand how they impact prostate cancer’s somatic evolution