Expectation-Maximization Based Mixture-Model Exploiting Pathway Knowledge for Cancer Heterogeneity

Cancer cells are much more prone to mutations than normal cells, generating over time, more genetic variants of themselves within the tissue. Drugs designed for one variant might not work as intended for other variants. As such, effective drug design requires estimation of proportion of various cancer subpopulations. In this work, a mixture model based approach with expectation maximization is proposed for determination of cancer heterogeneity. We exploit the pathway knowledge collected by biologists over time to surpass the limitations of identifiability shown by mixture models. Also in cases where Expectation-Maximization converges to more than one solution, pathway knowledge is used to break the tie by defining an error metric. Finally, using experimental data, changes in composition of the mixture over time are estimated using the model. The approach can also be used to compare the effectiveness of different drugs on a heterogeneous cancer tissue by observing the response over time

Determination of Cancer Tissue Heterogeneity

Understanding the heterogeneous nature of cancer tissue is a very important problem in cancer research. It can give insights into the cause of disease, its progression and explain induced drug resistance. There are two models that are used to explain heterogeneity, Cancer Stem Cells and Clonal Evolution. This thesis aims to address this challenge by developing an algorithm to determine the ratio of different components of a heterogeneous cancer tissue. This algorithm is robust and does not depend on the heterogeneity model. The proposed algorithm uses response vector, which is a vector of observable response of cell lines. A database of the response of individual cell lines is developed by collecting cell-by-cell response measurements. A heterogeneous cancer tissue is modeled as being a mixture of these cell lines. Avoiding the high cost cell-by-cell analysis, the collective response of the heterogeneous cancer tissue is observed. The algorithm uses Bayesian inference to estimate the probability distribution of the number of cells of individual cell lines based on the response of individual cell lines and the observed collective response. The results of the algorithm are validated using synthetic data and real-world data collected from cell lines, which are mixed in a ratio known a priori

The DLK1-MEG3 locus in malignant cells of proposed primordial germ cell origins.

Primordial germ cells (PGCs) are hypothesized to deposit hematopoietic stem cells (HSCs) along their migration route through the embryo during the early stages of embryogenesis. PGCs also undergo global chromatin remodeling, including the erasure and reestablishment of genomic imprints, during this migration. While PGCs do not spontaneously form teratomas, their malignant development into germ cell tumors (GCTs) in vivo is often accompanied by the retention of hypomethylation at the IGF2-H19 imprinting control differentially methylated region (DMR). Previous studies in bimaternal embryos determined that proper genomic imprinting at two paternally imprinted loci was necessary for their growth and development: Igf2-H19 and Dlk1-Meg3. Hypomethylation at DMRs within these two loci confers a tumor-suppressing phenotype, thus provoking the question of whether changes in genomic imprinting at these loci may be important for the development of GCTs. Similarly, these loci were recently implicated in the quiescence and maintenance of HSCs, and there is evidence to suggest that both loci are involved in leukemogenesis. Here, I investigated the DLK1-MEG3 locus in acute myeloid leukemia (AML) patient samples, and discovered significant associations between patient survival and the methylation and expression patterns from this locus. In addition, I investigated the methylation of DMRs within the IGF2-H19 and DLK1-MEG3 loci in the human embryonal carcinoma (EC) cell line NTera2 and found that, while the IGF2-H19 control DMR was hypomethylated, the DLK1-MEG3 control DMR and secondary MEG3 DMR were hypermethylated in these cells. The expression ratio of imprinted genes from both loci also agreed with proposed imprinting mechanisms for these phenotypes, and changes in these expression ratios accompanied a decrease in the proliferation rate of these cells during treatment with the DNA methyltransferase inhibitor 5-aza-2’-deoxycytidine. While NTera2 cells functionally responded to exogenous insulin-like growth factors, including IGF2, these cells exhibited strong nuclear staining for DLK1, and shRNA-mediated knockdown of DLK1 revealed a requirement for this gene for the in vitro and in vivo malignant properties of these cells. Furthermore, isolation of potential cancer stem cells (CSCs) from the NTera2 cell line based on CD133 and SSEA4 surface expression produced subpopulations of cells with unique gene expression signatures and migratory characteristics. However, little difference in the DLK1 or OCT4 expression was found among these subpopulations, and the emergence of CD133+SSEA4+ cells from in vitroexpanded CD133-, SSEA4-, and CD133-SSEA4- singly-sorted cells indicated that, while the overall stemness of these cells was fixed, the phenotype of this established cell line is actually in flux. In conclusion, DLK1 is a potential target to treat AML and EC, meriting future investigations into the development of DLK1-targeting therapies, including the use of specific antibodies, aptamers, and vaccination strategies. EC cell growth and metastasis could also be inhibited by employing DNA methyltransferase inhibitors, and investigations into the effect of these drugs on the expression of genes from the DLK1-MEG3 locus in AML could provide valuable information for the development of patient-specific treatments for this disease

Terapia génica y microambiente tumoral: efecto de los cambios en la proliferación celular sobre la expresión y localización del cotransportador sodio/yodo en un modelo in vitro de cáncer de colon

El cotransportador sodio-yodo (NIS) es una proteína que cataliza un transporte activo de yodo, hacia el interior de la célula, aprovechando el gradiente de sodio creado por la bomba sodio/potasio. Se localiza a nivel basolateral en diferentes tipos celulares, pero principalmente en células foliculares de tiroides. Por su capacidad de acumulación de yodo, esta proteína ha sido ampliamente utilizada como herramienta diagnostico-terapéutica contra el cáncer de tiroides. Dada su funcionalidad, la utilización de radioisótopos de yodo es una herramienta altamente efectiva. Hoy en día su aplicabilidad en otros tipos de cáncer es prometedora debido a la implementación de la terapia génica. con el fin de evaluar la efectividad de la terapia génica basada en la introducción heteróloga de la proteína NIS, investigadores de la unidad TIRO de la Université de Nice – Sophia Antipolis, generaron una línea celular a partir de células de la línea de carcinoma de colon HT29, transfectándolas establemente con el transportador NIS (HT29-NIS). Esta línea ha sido utilizada para generar tumores en ratones con el fin de evaluar la efectividad de esta herramienta. Los resultados de estos estudios permitieron establecer que la función del transportador no es homogénea a lo largo de los tumores generados, observándose una mayor captación de yodo en las zonas externas del tumor, y una captación muy baja o nula al interior del mismo. Una de las posibles fuentes de variación puede ser la heterogeneidad tumoral, un fenómeno que hace referencia a la variedad de fenotipos de las células tanto cancerígenas como de los otros tipos celulares que conforman el microambiente tumoral. Dado este contexto, el objetivo de este trabajo fue determinar los posibles efectos de cambios en la proliferación celular sobre la expresión y localización de NIS in vitro. Para ello, las diferencias en la proliferación se simularon mediante la disminución de suero en el medio de cultivo. Por otro lado, para evaluar la expresión y localización de NIS se aplicaron metodologías de Western Blot e Inmunocitoquímica. Los cambios en el estado de proliferación de las células HT29-NIS generaron variaciones en el ii patrón de expresión y en la localización intracelular del transportador, posiblemente asociados con variaciones en su estado de glicosilación. Esta observación, sugiere que posiblemente una o más rutas de señalización asociadas a la proliferación celular pueden ser responsables de algún tipo de regulación sobre el transporte de yoduro en los tumores de células HT29-NIS generados en ratones. Con base en lo anterior, se realizó una búsqueda de posibles rutas de señalización asociadas tanto con la regulación de la proliferación como con la regulación del transportador. Una de las rutas de señalización que sobresalió fue la ruta PI3K/AKT, ya que en diferentes modelos celulares puede regular la expresión de NIS y además es una ruta de señalización ampliamente asociada a la proliferación celular. Por ello, se utilizó Wortmanina, inhibidor de ésta para tener una aproximación al efecto de su inhibición sobre la expresión del transportador. La acción de tal inhibidor no mostró diferencias significativas sobre la expresión ni el patrón de expresión del cotransportador. En conjunto, estos experimentos permiten un acercamiento inicial a uno de los fenómenos que puede estar afectando negativamente la aplicación de radioterapia metabólica basada en NIS: el estado proliferativo de las células, nunca dejando de lado los conceptos de heterogeneidad tumoral y microambiente tumoral.Abstract. Sodium-Iodide symporter (NIS) a protein that actively cotransports sodium and iodide has been widely used as a diagnostic and therapeutic tool against thyroid cancer. Mostly, NIS is expressed in thyroid follicular cells as a transmembrane protein. Because of its functional mechanisms the utilization of iodide radioisotopes as thyroid cancer therapy is a highly effective tool. Nowadays its usability in other cancer types becomes promising due to the utilization of genetic therapy. Previous to this research work, researches at TIRO unit in Universitè Sophie Antopolis generated an HT29 cell line transfected with NIS symporter (HT29-NIS). This cell line has been used to generate xenografts in order to assess the effectivity of this tool. However, the function of the symporter is not homogeneous along the xenografts. One of the possible sources of variation might be the tumor heterogeneity. This phenomenon is described as the variety of phenotypes present in the tumor forming cells and the tumor stroma and microenvironment cells. Given this context, the aim of this study was to assess the possible effect of proliferation changes on NIS symporter expression and localization in vitro. In order to do so, decreasing serum supplementation percentage in the culture media simulated the different proliferation states. Western Blot and Immunocytochemistry determined NIS expression and subcellular localization. Changes in the proliferation state of HT29-NIS cells generated variations on the expression pattern and intracellular localization of NIS protein, possibly associated with its glycosylation state. These results suggest that proliferation-related pathways might be associated with the heterogeneous transport of iodide on HT29-NIS xenografts. Having in mind the suggestion above, a wide search about signaling pathways regulating proliferation and NIS expression was held. As a result the PI3K/AKT pathway was one of the signaling pathways that meet our criteria. In order to test the effects of inhibiting this pathway we apply Wortmannin as the inhibitory agent. It didn’t yield significant variations on the expression or expression pattern of the transporter. As a hole, this experiments shed a light into one of the different phenomenon negatively affecting the application of NIS-based metabolic radiotherapy: the cellular proliferative state, never leaving appart its association with tumor heterogeneity and tumoral microenvironment.Maestrí

Evaluación de la respuesta al tratamiento con radiaciones ionizantes en células de carcinoma de colon modificadas con el transportador NIS (HT29-NIS)

La utilización de radioisótopos de yodo en medicina nuclear es una herramienta muy efectiva para el diagnóstico y tratamiento del cáncer tiroideo, basada en la actividad del co-transportador sodio/yodo (NIS) que cataliza el transporte activo de yodo. Recientemente se ha planteado la utilización de este transportador en terapia génica, para inducir su expresión en tejidos tumorales que normalmente no la producen y tratarlos con radioterapia metabólica (131I) y radioterapia de fuente externa como terapia combinada. Hallazgos in-vivo demostraron distribución heterogénea en captación de yodo y expresión del transportador en un modelo de tumor generado en ratones desnudos, sugiriendo una posible relación con las características heterogéneas del tumor. Sobre esta base, la presente investigación se enfocó en la evaluación del efecto de la expresión del transportador NIS en la respuesta al tratamiento con radiaciones ionizantes de fuente externa, y si dicho posible efecto permanece o se modifica al cambiar del estado proliferativo a quiescente, simulando una condición del microambiente tumoral. Todo lo anterior se realizó con miras a que esta alternativa sea utilizada como parte de un tratamiento combinado (terapia génica, radioterapia de haz externo y radioterapia metabólica) superando los problemas relacionados con la expresión heterogénea del transportador NIS. Con este propósito, partiendo de un modelo celular parental (HT29-WT) y un modelo establemente transfectado con el transportador (HT29-NIS) en condiciones de cultivo que simulan la heterogeneidad tumoral en cuanto a grados de proliferación se refiere (proliferación y quiescencia) se evaluaron los siguientes aspectos: inicialmente la supervivencia celular posterior a la exposición con radiaciones ionizantes mediante ensayos clonogénicos, posteriormente se analizó de manera más detallada el efecto biológico de la radiación, evaluando tanto la medición del daño y reparación del ADN, mediante ensayo cometa y determinación de la activación de sistemas de reparación del ADN por medio de la aparición de focos de la histona γH2AX; finalmente, se evaluó la alteración del estrés oxidativo mediante la medición de especies reactivas de oxígeno (ROS) y evaluación de los niveles de expresión de proteína Nrf-2. Entre los resultados se destaca la mayor radiosensibilidad de las células que expresan el transportador comparada con la línea parental, y la mayor radiosensibilidad de las células en condición de quiescencia, soportado no solamente por los resultados obtenidos en las curvas de supervivencia sino también en la evaluación del daño y reparación del ADN y respuesta al estrés oxidativo celular. En resumen, la terapia génica puede ser aprovechada para obtener un mejor resultado en el tratamiento de tumores sólidos mediante la combinación de radioterapia metabólica y de haz externo.Abstract. Using iodine radioisotopes in nuclear medicine is an effective tool in the diagnosis and treatment of thyroid cancer; this therapy is based in the activity of the natrium/iodide symporter (NIS) which catalyzes the active flow of iodine. Recently, the usage of this transporter in gene therapy has been proposed, this by inducing its expression in tumoral tissues that do not normally express it and subsequently treat it them with metabolic radiotherapy (131I) and external beam radiotherapy as a combined treatment. Findings in in vivo- studies using a naked mice tumor model have shown a heterogeneous distribution in the iodine uptake and expression of NIS protein, suggesting a relationship with the heterogeneous characteristics of the tumor, on this basis the present study was focused on the evaluation of the effect of NIS expression in external beam radiotherapy cell response, furthermore, was evaluated if this plausible effect remains or changes in proliferative and a quiescent state, simulating one condition of tumor microenvironment, this with a view to stablish this therapy as an alternative of combined treatment (gene therapy, external beam radiotherapy and metabolic therapy) and therefore overcoming problems related to the heterogeneous distribution of the expression of NIS transporter. Cell models, wild-type (HT29-WT) and the transporter based model (HT29-NIS) in culture conditions that simulated tumor heterogeneity referring to proliferative and quiescent conditions were used to evaluate: initially cell survival after the exposure to ionizing radiation with clonogenic assays, subsequently the biological effect of radiation evaluating DNA damage and activation of repairing systems with γH2AX focis and comet assay, finally the oxidative stress was evaluated through the measuring of ROS and expression levels of Nrf-2. Among the most relevant results it raises special attention the increased radiosensibility of cells expressing the transporter compared to the wild type cell line and the radiosensibility of cells in quiescent conditions this supported by the results obtained in the survival curves and in the DNA damage response and oxidative stress response, in conclusion gene therapy could be used to obtain better results in the treatment of solid tumors by means of combining metabolic therapy and external beam therapy.Maestrí

Customization of Treatment for Cancer Patients: An Engineering Approach

Cancer is a disease associated with uncontrolled cell proliferation or reduced cell death, either of which can lead to tumorigenesis. A possible route through which cancer can develop is by breakdowns in the signaling cascade of proteins at the cellular level. Since there are many ways in which such breakdowns can occur, anti-cancer chemotherapeutic drugs show varying degrees of efficacy in different patients. Thus, there is an urgent need to personalize the drug treatment regimen for better response to treatment while trying to reduce the side effects of these drugs. One way to meet this need would be to try every possible drug combination on cell lines extracted from a patient and find the combination with the least number of drugs in the mix but providing the best possible output. Although this method may work it is tedious and time consuming as the number of combinations increase exponentially with every new drug that is introduced into the repertoire. First, we consider the problem where the tumor is homogeneous in nature but the mutations within the mutated cells are unknown. We use Boolean network models with monotonicity properties to reduce the number of test cases, while still getting the best possible combination with the least number of drugs in the mix. This approach is efficient both in terms of time required and the costs involved. This method has also been applied to both simulated and real-world data collected from fibroplasts using qPCR to demonstrate the usefulness of the method. Another important area of study in cancer research concerns the heterogeneous nature of tumors. The clonal evolution of tumors is the driving force leading to heterogeneity in cancer tissues. Thus, in order to customize the treatment of cancer we need to be able to better model the heterogeneous subpopulations in the tumor. This can be done by estimating the impact of the various sub-populations and by modeling the interplay of various sub-populations within the heterogeneous tumor. Prior works in the literature have already addressed the problems of estimating the proportion of the sub-populations within a tumor and of modeling the interaction between the various sub-populations. In this work we present a way to improve the accuracy of the Bayesian hierarchical model which helps in estimating the proportional breakup of the tumor population. Additionally, it looks at ways to use the knowledge of the proportional breakup of tumor subpopulations and the interplay between the various subpopulations to help customize the treatment for the patient by making use of evolutionary game theory. We demonstrate the improvement of the presented methods as compared to the existing Bayesian hierarchical model by applying these techniques to qPCR and fluorescent data. Finally, the problem becomes more challenging when the nature and the number of the subpopulations are variable and difficult to estimate. In this work, we present a feasible way to find the best possible drug combination for such a scenario by training two neural network models on synthetic and real-world cancer data. Then we test each model, to verify their effectiveness and to demonstrate their usefulness in choosing the appropriate combination therapy. The models were evaluated on synthetic qPCR data and fluorescent data obtained from experiments. The results obtained from these methods take us a step closer to the realization of customized treatment for cancer patients. This will not only make the treatment more effective but also help reduce the side effects of the drug treatment