INTRODUÇÃO: De acordo com a estimativa de 2012 do INCA, eram esperados 52.680 novos casos de câncer de mama no Brasil, com um risco estimado de 52 casos a cada 100 mil mulheres. Estes dados mostram a necessidade da identificação de biomarcadores efetivos para rastreamento precoce e seguimento destas mulheres durante seu tratamento. Neste trabalho, para a avaliação de potenciais biomarcadores desta doença, foi idealizado um modelo laboratorial específico que avalie tanto a capacidade de um dado biomarcador rastrear um tumor inicial de mama, bem como testar o seu potencial valor para o seguimento de mulheres já diagnosticadas durante seu tratamento. Este modelo baseia-se na avaliação de células tumorais circulantes e perfilamento gênico tumoral. MÉTODOS: Amostras biológicas (sangue periférico e tumor) de 167 pacientes diagnosticadas com carcinoma mamário estadios I, II e III com indicação de quimioterapia adjuvante para: a) avaliação da presença de células tumorais circulantes através da expressão de CK19 e HER2 na Fração Mononuclear do Sangue Periférico (FMNSP) por RT-PCR quantitativo e b) perfilamento gênico tumoral através da análise da expressão de 21 genes relacionados a importantes processos de carcinogênese mamária em amostras de tecido parafinado por ensaio multiplex de RT-PCR quantitativo utilizando o sistema Plexor®. RESULTADOS: Foi observada uma correlação significativa entre CK19 e HER2 na primeira coleta e queda da concentração de HER2 no SP durante o tratamento; porém, não foi percebida queda significativa do CK19 ao longo do estudo. A expressão de HER2 na segunda coleta de pacientes positivas para HER2 na primeira coleta tendeu a se correlacionar significativamente com um pior Intervalo Livre de Doença (ILD). Através da padronização da pontuação em quartis das análises realizadas em multiplex pelo sistema Plexor, foi percebido que o quartil superior apresentava ILD significativa pior do que a de pacientes nos demais quartis. Também foi observada uma estratificação do estadio clínico II em pior ou melhor prognóstico de acordo com o quartil de pontuação do teste de perfilamento proposto neste estudo; além disso, verificou-se que pacientes submetidas a tratamento neoadjuvante com pontuações inferiores tenderam a responder melhor à quimioterapia. CONCLUSÃO: Pelas características do comportamento evolutivo no presente estudo, HER2 parece ser melhor como possível biomarcador de células tumorais circulantes do que o CK-19. Até o presente momento do seguimento das pacientes incluídas neste estudo, não foi possível criar um modelo com diversas variáveis para prever o prognóstico de pacientes com câncer de mama. Isto ocorreu principalmente pelas características preditivas prognósticas superiores do perfilamento genético do tumor que desloca fatores de prognóstico tais como células circulantes e estadio clínico, expressão hormonal do tumor e idade de um modelo multivariado. Por outro lado, foi padronizada uma tecnologia genômica complexa que poderá viabilizar seu uso para a população se estudos posteriores confirmarem seu valor em outras coortes de pacientes com câncer de mama / BACKGROUND: According to the estimate of 2012 INCA, were expected 52,680 cases of breast cancer in Brazil, with an estimated risk of 52 cases per 100 000 women. These data show the need for effective identification of biomarkers for early screening and follow-up of these women during their treatment. In this work, for the evaluation of potential biomarkers of this disease, a model laboratory was designed to evaluate both the specific capacity of a given biomarker trace an initial breast tumor, as well as test its potential value for the follow-up of women already diagnosed during their treatment. This model was based on the evaluation of circulating tumor cells and tumor gene profiling. METHODS: Biological samples (peripheral blood and tumor) of 167 patients diagnosed with breast cancer stages I, II and III with an indication for adjuvant chemotherapy: a) to evaluate the presence of circulating tumor cells through the expression of HER2 and CK19 in Peripheral Blood Mononuclear fraction (PBMN) by quantitative RT-PCR and b) tumor profiling gene by analyzing the expression of 21 genes related to important processes of mammary carcinogenesis in paraffinized tissue samples by multiplex assay for quantitative RT-PCR using the Plexor ® System. RESULTS: Was observed a significant correlation between HER2 and CK19 in the first collection and decrease in concentration of HER2 in PB during the treatment, but were not perceived significant decrease of CK19 along the study. The expression of HER2 in the second collection of patients positive for HER2 in the first test tended to correlate with a significantly worse disease-free interval (DFI). Through standardization of the scores in quartiles of the analyzes performed at multiplex Plexor system was seen that the upper quartile ILD had significantly worse than patients in the other quartiles. Also stratification was observed in clinical stage II in better or worse prognosis according to quartiles of test score profiling proposed in this study, in addition, it was found that patients submitted to neoadjuvant treatment with lower scores tended to better respond to chemotherapy. CONCLUSION: HER2 seems to be better as possible biomarker of circulating tumor cells than the CK-19. So far the monitoring of patients included in this study, it was not possible to create a model with multiple variables to predict the prognosis of patients with breast cancer. This occurred primarily due to the characteristics predictive prognostic upper genetic profiling of tumor that displaces prognostic factors such as circulating cells and clinical stage, tumor hormone expression and age in a multivariate model. In the other hand, was standardized complex genomic technology that may enable their use for the population if further studies confirm its value in other cohorts of patients with breast cancer

Introdução: Em câncer de mama, existem evidências de que o microambiente pode influenciar o desenvolvimento do tumor no sítio primário, bem como em metástases regionais e a distância. Neste contexto, fibroblastos são importantes células estromais que podem influenciar a proliferação e a migração de células do câncer e podem prover um nicho apropriado para o desenvolvimento tumoral. Objetivos:O principal objetivo deste trabalho é comparar células estromais obtidas do tumor primário (PT), metástase linfonodal (N+) e medula óssea (BM) de pacientes com câncer de mama, através do perfil de expressão gênica. Pacientes e Métodos: Foi analisada a expressão gênica de fibroblastos (cultura primária) de 11 pacientes com câncer de mama. O perfil de expressão foi determinado em PT (n=4), N+(n=3) e BM (n=4) através de uma plataforma de cDNA microarray customizada (contendo 4.800 sequencias imobilizadas, representando cerca de 4600 genes), e os genes diferencialmente expressos foram identificados pelo teste SAM multiclasse, seguido pelo teste SAM de duas classes (TMEV, FDR 0%). A análise funcional foi realizada pelo software DAVID v6.7. Validação técnica foi realizada em 6 amostras previamente analisadas no microarray e a validação biológica em fibroblastos obtidos de outros 16 pacientes utilizando-se de RT-qPCR. Resultados: O perfil de expressão gênica dos fibroblastos obtidos de diferentes sítios mostraram 267 genes diferencialmente expressos, os quais apropriadamente agruparam os fibroblastos de acordo com suas origens (PT vs. N+ vs. BM). Apesar das diferenças entre PT e N+ serem representadas por 20 genes, as diferenças entre PT vs. BM e N+ vs BM foram mais significantes (235 e 245 genes diferencialmente expressos respectivamente). Análise funcional dos genes diferencialmente expressos mostrou enriquecimento de funções relacionadas ao desenvolvimento e morfogênese.A seguir, a expressão de alguns genes selecionados foi analisada em uma série diferente de amostras (validação biológica). Desse modo observamos que NOTCH2 confirmou uma alta expressão em N+ (vs. PT), e ADCY2, HECTD1, HNMT, LOX, MACF1 e USP16 confirmaram alta expressão em BM (vs PT). Conclusão:Em pacientes com câncer de mama, células estromais obtidas de diferentes origens apresentam um perfil de expressão gênica diferencial, o qual pode influenciar o comportamento do tumor / may influence tumor development in the primary site of breast cancer, as well as in regional and distant metastatic sites. In this context, fibroblasts are important stromal cells which influence proliferation and migration of cancer cells and may also provide an appropriate niche to tumor development. Objectives: The main objective of this work is the comparison of stromal cells from the primary tumor (PT), lymph node metastasis (N+) and bone marrow (BM) obtained from breast cancer patients, through gene expression profile. Patients and Methods: The gene expression profile was analyzed in fibroblasts primary culture from 11 breast cancer patients. The expression profiles of PT cells (n=4), N+ cells (n=3) and BM cells (n=4) were determined through a customized cDNA microarray platform (containing 4800 immobilized sequences which represents 4600 genes approximately). The analysis were performed by SAM multiclass (TMEV; FDR 0%), followed by SAM two classes test (TMEV; FDR 0%). Functional analysis was performed using DAVID v6.7. Technical validation was performed in same 6 samples that were previously analyzed in microarray experiments and biological validation was performed in fibroblasts obtained from other group of 16patients by RT-qPCR Results: The expression profile of fibroblasts obtained from three sites revealed 267 differentially expressed genes, which appropriately clustered fibroblasts in three different branches, in accordance with their origin (PT vs. N+ vs. BM). Although the differences between PT and N+ were represented by 20 genes, differences between PT vs. BM and N+ vs. BM were more significant (235 and 245 differentially expressed genes respectively). Functional analysis revealed enrichment of functions related to development and morphogenesis. Afterwards, the expression of some selected genes were analyzed in a different batch of samples (biological validation).Thereby, NOTCH2 confirmed high expression in N+ (vs. PT), and ADCY2, HECTD1, HNMT, LOX, MACF1 and USP16 confirmed high expression in BM (vs. PT). Conclusion: In breast cancer patients, stromal cells obtained from different origins present a differential gene expression profile, which may influence tumor behavior

Advancements in the field of biotechnology are expanding the scientific horizon and a promising era is envisioned with personalized medicine for improved health. The amount of genetic data is growing at an ever-escalating pace due to the availability of novel technologies that allow massively parallel sequencing and whole-genome genotyping, that are supported by the advancements in computer science and information technologies. As the amount of information stored in databases throughout the world is growing and our knowledge deepens, genetic signatures with significant importance are discovered. The surface of such a set in the data mining process may include causative- or marker single nucleotide polymorphisms (SNPs), revealing predisposition to disease, or gene expression signatures, profiling a pathological state. When targeting a reduced set of signatures in a large number of samples for diagnostic- or fine-mapping purposes, efficient interrogation and scoring require appropriate preparations. These needs are met by miniaturized and parallelized platforms that allow a low sample and template consumption. This doctoral thesis describes an attempt to tackle some of these challenges by the design and implementation of a novel assay denoted Trinucleotide Threading (TnT). The method permits multiplex amplification of a medium size set of specific loci and was adapted to genotyping, gene expression profiling and digital allelotyping. Utilizing a reduced number of nucleotides permits specific amplification of targeted loci while preventing the generation of spurious amplification products. This method was applied to genotype 96 individuals for 75 SNPs. In addition, the accuracy of genotyping from minute amounts of genomic DNA was confirmed. This procedure was performed using a robotic workstation running custom-made scripts and a software tool was implemented to facilitate the assay design. Furthermore, a statistical model was derived from the molecular principles of the genotyping assay and an Expectation-Maximization algorithm was chosen to automatically call the generated genotypes. The TnT approach was also adapted to profiling signature gene sets for the Swedish Human Protein Atlas Program. Here 18 protein epitope signature tags (PrESTs) were targeted in eight different cell lines employed in the program and the results demonstrated high concordance rates with real-time PCR approaches. Finally, an assay for digital estimation of allele frequencies in large cohorts was set up by combining the TnT approach with a second-generation sequencing system. Allelotyping was performed by targeting 147 polymorphic loci in a genomic pool of 462 individuals. Subsequent interrogation was carried out on a state-of-the-art massively parallelized Pyrosequencing instrument. The experiment generated more than 200,000 reads and with bioinformatic support, clonally amplified fragments and the corresponding sequence reads were converted to a precise set of allele frequencies. / QC 20100813

No description available.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Background: The endocrine pancreas contains multiple cell types co-localized into clusters called the Islets of Langerhans. The predominant cell types include alpha and beta cells, which produce glucagon and insulin, respectively. The regulated release of these hormones maintains whole body glucose homeostasis, essential for normal metabolism and to prevent diabetes and complications from the disease. Given the heterogeneous nature of islet composition and absence of unique surface markers, many previous studies have focused on the whole islet. Sorting islet cells by intracellular hormone expression overcomes this limitation and provides pure populations of individual islet cell subsets, specifically alpha and beta cells. This technique provides the framework for characterizing human islet composition and will work towards identifying the genetic changes alpha and beta cells undergo during development, growth, and proliferation. Methods: Human islets obtained from cadaveric donors are dissociated into a single cell suspension, fixed, permeabilized, and labeled with antibodies specific to glucagon, insulin, and somatostatin. Individual alpha, beta, and delta cell populations are simultaneously isolated using fluorescence activated cell sorting. Candidate gene expression and microRNA profiles have been obtained for alpha and beta cell populations using a quantitative nuclease protection assay. Thus far, RNA has been extracted from whole islets and beta cells and subjected to next generation sequencing analysis. Results: The ratio of beta to alpha cells significantly increases with donor age and trends higher in female donors; BMI does not appear to significantly alter the ratio. Further, we have begun to investigate the unique gene expression profiles of alpha and beta cells versus whole islets, and have characterized the microRNA profiles of the two cell subsets. Conclusions: By establishing methods to profile multiple characteristics of alpha and beta cells, we hope to determine how gene, miRNA, and protein expression patterns change under environmental conditions that lead to beta cell failure or promote beta cell development, growth, and proliferation.

INTRODUÇÃO: De acordo com a estimativa de 2012 do INCA, eram esperados 52.680 novos casos de câncer de mama no Brasil, com um risco estimado de 52 casos a cada 100 mil mulheres. Estes dados mostram a necessidade da identificação de biomarcadores efetivos para rastreamento precoce e seguimento destas mulheres durante seu tratamento. Neste trabalho, para a avaliação de potenciais biomarcadores desta doença, foi idealizado um modelo laboratorial específico que avalie tanto a capacidade de um dado biomarcador rastrear um tumor inicial de mama, bem como testar o seu potencial valor para o seguimento de mulheres já diagnosticadas durante seu tratamento. Este modelo baseia-se na avaliação de células tumorais circulantes e perfilamento gênico tumoral. MÉTODOS: Amostras biológicas (sangue periférico e tumor) de 167 pacientes diagnosticadas com carcinoma mamário estadios I, II e III com indicação de quimioterapia adjuvante para: a) avaliação da presença de células tumorais circulantes através da expressão de CK19 e HER2 na Fração Mononuclear do Sangue Periférico (FMNSP) por RT-PCR quantitativo e b) perfilamento gênico tumoral através da análise da expressão de 21 genes relacionados a importantes processos de carcinogênese mamária em amostras de tecido parafinado por ensaio multiplex de RT-PCR quantitativo utilizando o sistema Plexor®. RESULTADOS: Foi observada uma correlação significativa entre CK19 e HER2 na primeira coleta e queda da concentração de HER2 no SP durante o tratamento; porém, não foi percebida queda significativa do CK19 ao longo do estudo. A expressão de HER2 na segunda coleta de pacientes positivas para HER2 na primeira coleta tendeu a se correlacionar significativamente com um pior Intervalo Livre de Doença (ILD). Através da padronização da pontuação em quartis das análises realizadas em multiplex pelo sistema Plexor, foi percebido que o quartil superior apresentava ILD significativa pior do que a de pacientes nos demais quartis. Também foi observada uma estratificação do estadio clínico II em pior ou melhor prognóstico de acordo com o quartil de pontuação do teste de perfilamento proposto neste estudo; além disso, verificou-se que pacientes submetidas a tratamento neoadjuvante com pontuações inferiores tenderam a responder melhor à quimioterapia. CONCLUSÃO: Pelas características do comportamento evolutivo no presente estudo, HER2 parece ser melhor como possível biomarcador de células tumorais circulantes do que o CK-19. Até o presente momento do seguimento das pacientes incluídas neste estudo, não foi possível criar um modelo com diversas variáveis para prever o prognóstico de pacientes com câncer de mama. Isto ocorreu principalmente pelas características preditivas prognósticas superiores do perfilamento genético do tumor que desloca fatores de prognóstico tais como células circulantes e estadio clínico, expressão hormonal do tumor e idade de um modelo multivariado. Por outro lado, foi padronizada uma tecnologia genômica complexa que poderá viabilizar seu uso para a população se estudos posteriores confirmarem seu valor em outras coortes de pacientes com câncer de mama / BACKGROUND: According to the estimate of 2012 INCA, were expected 52,680 cases of breast cancer in Brazil, with an estimated risk of 52 cases per 100 000 women. These data show the need for effective identification of biomarkers for early screening and follow-up of these women during their treatment. In this work, for the evaluation of potential biomarkers of this disease, a model laboratory was designed to evaluate both the specific capacity of a given biomarker trace an initial breast tumor, as well as test its potential value for the follow-up of women already diagnosed during their treatment. This model was based on the evaluation of circulating tumor cells and tumor gene profiling. METHODS: Biological samples (peripheral blood and tumor) of 167 patients diagnosed with breast cancer stages I, II and III with an indication for adjuvant chemotherapy: a) to evaluate the presence of circulating tumor cells through the expression of HER2 and CK19 in Peripheral Blood Mononuclear fraction (PBMN) by quantitative RT-PCR and b) tumor profiling gene by analyzing the expression of 21 genes related to important processes of mammary carcinogenesis in paraffinized tissue samples by multiplex assay for quantitative RT-PCR using the Plexor ® System. RESULTS: Was observed a significant correlation between HER2 and CK19 in the first collection and decrease in concentration of HER2 in PB during the treatment, but were not perceived significant decrease of CK19 along the study. The expression of HER2 in the second collection of patients positive for HER2 in the first test tended to correlate with a significantly worse disease-free interval (DFI). Through standardization of the scores in quartiles of the analyzes performed at multiplex Plexor system was seen that the upper quartile ILD had significantly worse than patients in the other quartiles. Also stratification was observed in clinical stage II in better or worse prognosis according to quartiles of test score profiling proposed in this study, in addition, it was found that patients submitted to neoadjuvant treatment with lower scores tended to better respond to chemotherapy. CONCLUSION: HER2 seems to be better as possible biomarker of circulating tumor cells than the CK-19. So far the monitoring of patients included in this study, it was not possible to create a model with multiple variables to predict the prognosis of patients with breast cancer. This occurred primarily due to the characteristics predictive prognostic upper genetic profiling of tumor that displaces prognostic factors such as circulating cells and clinical stage, tumor hormone expression and age in a multivariate model. In the other hand, was standardized complex genomic technology that may enable their use for the population if further studies confirm its value in other cohorts of patients with breast cancer

Introdução: Em câncer de mama, existem evidências de que o microambiente pode influenciar o desenvolvimento do tumor no sítio primário, bem como em metástases regionais e a distância. Neste contexto, fibroblastos são importantes células estromais que podem influenciar a proliferação e a migração de células do câncer e podem prover um nicho apropriado para o desenvolvimento tumoral. Objetivos:O principal objetivo deste trabalho é comparar células estromais obtidas do tumor primário (PT), metástase linfonodal (N+) e medula óssea (BM) de pacientes com câncer de mama, através do perfil de expressão gênica. Pacientes e Métodos: Foi analisada a expressão gênica de fibroblastos (cultura primária) de 11 pacientes com câncer de mama. O perfil de expressão foi determinado em PT (n=4), N+(n=3) e BM (n=4) através de uma plataforma de cDNA microarray customizada (contendo 4.800 sequencias imobilizadas, representando cerca de 4600 genes), e os genes diferencialmente expressos foram identificados pelo teste SAM multiclasse, seguido pelo teste SAM de duas classes (TMEV, FDR 0%). A análise funcional foi realizada pelo software DAVID v6.7. Validação técnica foi realizada em 6 amostras previamente analisadas no microarray e a validação biológica em fibroblastos obtidos de outros 16 pacientes utilizando-se de RT-qPCR. Resultados: O perfil de expressão gênica dos fibroblastos obtidos de diferentes sítios mostraram 267 genes diferencialmente expressos, os quais apropriadamente agruparam os fibroblastos de acordo com suas origens (PT vs. N+ vs. BM). Apesar das diferenças entre PT e N+ serem representadas por 20 genes, as diferenças entre PT vs. BM e N+ vs BM foram mais significantes (235 e 245 genes diferencialmente expressos respectivamente). Análise funcional dos genes diferencialmente expressos mostrou enriquecimento de funções relacionadas ao desenvolvimento e morfogênese.A seguir, a expressão de alguns genes selecionados foi analisada em uma série diferente de amostras (validação biológica). Desse modo observamos que NOTCH2 confirmou uma alta expressão em N+ (vs. PT), e ADCY2, HECTD1, HNMT, LOX, MACF1 e USP16 confirmaram alta expressão em BM (vs PT). Conclusão:Em pacientes com câncer de mama, células estromais obtidas de diferentes origens apresentam um perfil de expressão gênica diferencial, o qual pode influenciar o comportamento do tumor / may influence tumor development in the primary site of breast cancer, as well as in regional and distant metastatic sites. In this context, fibroblasts are important stromal cells which influence proliferation and migration of cancer cells and may also provide an appropriate niche to tumor development. Objectives: The main objective of this work is the comparison of stromal cells from the primary tumor (PT), lymph node metastasis (N+) and bone marrow (BM) obtained from breast cancer patients, through gene expression profile. Patients and Methods: The gene expression profile was analyzed in fibroblasts primary culture from 11 breast cancer patients. The expression profiles of PT cells (n=4), N+ cells (n=3) and BM cells (n=4) were determined through a customized cDNA microarray platform (containing 4800 immobilized sequences which represents 4600 genes approximately). The analysis were performed by SAM multiclass (TMEV; FDR 0%), followed by SAM two classes test (TMEV; FDR 0%). Functional analysis was performed using DAVID v6.7. Technical validation was performed in same 6 samples that were previously analyzed in microarray experiments and biological validation was performed in fibroblasts obtained from other group of 16patients by RT-qPCR Results: The expression profile of fibroblasts obtained from three sites revealed 267 differentially expressed genes, which appropriately clustered fibroblasts in three different branches, in accordance with their origin (PT vs. N+ vs. BM). Although the differences between PT and N+ were represented by 20 genes, differences between PT vs. BM and N+ vs. BM were more significant (235 and 245 differentially expressed genes respectively). Functional analysis revealed enrichment of functions related to development and morphogenesis. Afterwards, the expression of some selected genes were analyzed in a different batch of samples (biological validation).Thereby, NOTCH2 confirmed high expression in N+ (vs. PT), and ADCY2, HECTD1, HNMT, LOX, MACF1 and USP16 confirmed high expression in BM (vs. PT). Conclusion: In breast cancer patients, stromal cells obtained from different origins present a differential gene expression profile, which may influence tumor behavior

Hepatocellular carcinoma (HCC) is a common malignancy of the liver that is one of the most frequent causes of cancer-related death in the world. Surgical resection and liver transplantation are the only curative options for HCC, and tumor invasion and metastasis render many patients ineligible for these treatments. Identification of the mechanisms that contribute to invasive and metastatic disease may enlighten therapeutic strategies for those not eligible for surgical treatments. In this dissertation, I describe two sets of experiments to elucidate mechanisms underlying HCC dissemination, involving the activities of Krüppel-like factor 6 and a particular p53 point mutation, R172H. Gene expression profiling of migratory HCC subpopulations demonstrated reduced expression of Krüppel-like factor 6 (KLF6) in invasive HCC cells. Knockdown of KLF6 in HCC cells increased cell transformation and migration. Single-copy deletion of Klf6 in a HCC mouse model results in increased tumor formation, increased metastasis to the lungs, and decreased survival, indicating that KLF6 suppresses both tumor formation and metastasis in HCC. To elucidate the mechanism of KLF6-mediated tumor and metastasis suppression, we performed gene expression profiling and ChIP-sequencing to identify direct transcriptional targets of KLF6 in HCC cells. This analysis revealed novel transcriptional targets of KLF6 in HCC including CDC42EP3 and VAV3, both of which are positive regulators of Rho family GTPases. Concordantly, KLF6 knockdown cells demonstrate increased activity of the Rho family GTPases RAC1 and CDC42, and RAC1 is required for migration induced following KLF6 knockdown. Moreover, VAV3 and CDC42EP3 are also required for enhanced cell migration in HCC cells with KLF6 knockdown. Together, this work describes a novel signaling axis through which KLF6-mediated repression of VAV3 and CDC42EP3 inhibits RAC1Gmediated HCC cell migration in culture, and potentially HCC metastasis in vivo. TP53 gene mutations are commonly found in HCC and are associated with poor prognosis. Prior studies have suggested that p53 mutants can display gain-of- function properties in other tumor types. Therefore, I sought to determine if a particular hotspot p53 mutation, p53R172H, provided enhanced, gain-of-function properties compared to p53 loss in HCC. In vitro, soft agar colony formation and cell migration is reduced upon knockdown of p53R172H, indicating that this mutation is required for transformation-associated phenotypes in these cells. However, p53R172H-expressing mice did not have enhanced tumor formation or metastasis compared to p53-null mice. These data suggest that p53R172H and p53 deletion are functionally equivalent in vivo, and that p53R172H is not a gain-of-function mutant in HCC. Inhibition of the related transcription factors p63 and p73 has been suggested as a potential mechanism by which mutant p53 exerts its gain-of-function effects. Analysis of p63 and p73 target genes demonstrated that they are similarly suppressed in p53-null and p53R172H-expressing HCC cell lines, suggesting a potential explanation for the phenotypes I observed in vivo and in vitro. Together, the studies described in this dissertation increase our understanding of the mechanisms underlying HCC progression and metastasis. Specifically, we find and characterize KLF6 as a novel suppressor of HCC metastasis, and determine the contribution of a common p53 point mutation in HCC. This work contributes to ongoing efforts to improve treatment options for HCC patients.