Activity of HSP90 Inhibiton in a Metastatic Lung Cancer Patient With a Germline BRCA1 Mutation

Heat shock proteins (HSPs) are molecular chaperones that maintain proteins in their correct conformation to ensure stability and protect carcinoma cells from apoptosis. HSP90 inhibitors (HSP90i) block multiple targets simultaneously, and despite responses in a selected population, no HSP90i have yet been approved. We present a patient with a lung tumor with an exceptional response to cisplatin/gemcitabine in combination with HSP90i, which nowadays continues with HSP90i maintenance after three years. Whole-exome sequencing of the lung tumor unveiled a BRCA1/2 deficiency mutational signature, and mutation analysis confirmed a germline BRCA1 mutation. The striking efficacy of HSP90i plus chemotherapy vs chemotherapy alone was reproduced in a patient-derived xenograft (PDX) model from a breast cancer patient with a BRCA1 mutation (mean tumor volume [SD], No. of tumors: vehicle 8.38 [7.07] mm 3, n = 3; HSP90i 4.18 [1.93] mm 3, n = 5; cisplatin plus gemcitabine 3.31 [1.95] mm 3, n = 5; cisplatin plus gemcitabine plus HSP90i 0.065 [0.076] mm 3, n = 6). This case and the PDX demonstrate the efficacy for therapeutic inhibition of HSP90 in a BRCA- mutated patient, opening a new potential avenue for better identifying patients who might benefit most from HSP90i

The identification and characterisation of germline genetic variants that affect human cancer

Single nucleotide polymorphisms (SNPs) have great potential to serve as important biomarkers in the clinic to identify those at increased risk for developing cancer, progressing more rapidly, and not responding to therapies. However, the clinical application of cancer-associated SNPs has proven to be more complicated than expected. One of the necessary steps will certainly be the description of the molecular and cellular mechanisms behind the observed associations. The p53 tumour suppressor pathway harbours well-described SNPs that affect p53 signalling and cancer. The aim of the work presented in this thesis was to utilise this knowledge to more efficiently characterise cancer-associated SNPs. Firstly, cancer-associated SNPs in a p53 network gene, CD44, were studied. Specifically, based on CD44’s known roles in both p53-dependent and independent signalling, it was predicted that the cancer-associated SNPs could function as biomarkers for chronic lymphocytic leukaemia progression, and for the response to anti-EGFR therapy for colorectal cancer. Indeed, supportive data is presented. Next, a methodology is presented that aims to identify cancer-associated SNPs in functional p53 binding sites using genome-wide datasets. Interestingly, a SNP is identified that dramatically influences the ability of p53 to regulate transcription of the KITLG oncogene and that associates with one of the largest risks of cancer identified to date. Intriguingly, the SNP is also shown to have undergone positive selection throughout human evolution, signifying a selective advantage, but similar SNPs are demonstrated to be rare in the genome due to negative selection, indicating that polymorphisms in p53 binding sites have been primarily detrimental to humans. Lastly, and in order to begin to explore if other polymorphic transcription factor binding motifs could be found in cancer-associated SNPs, a methodology was designed to identify SNPs in E-box transcription factor binding motifs, as they are sensitive to single base pair changes and affect cancer. Taken together, the work presented in this thesis shows how the study of how SNPs associate with, and impact upon, cancer has great potential to improve both biological knowledge and clinical outcomes.</p

The identification and characterisation of germline genetic variants that affect human cancer

Single nucleotide polymorphisms (SNPs) have great potential to serve as important biomarkers in the clinic to identify those at increased risk for developing cancer, progressing more rapidly, and not responding to therapies. However, the clinical application of cancer-associated SNPs has proven to be more complicated than expected. One of the necessary steps will certainly be the description of the molecular and cellular mechanisms behind the observed associations. The p53 tumour suppressor pathway harbours well-described SNPs that affect p53 signalling and cancer. The aim of the work presented in this thesis was to utilise this knowledge to more efficiently characterise cancer-associated SNPs. Firstly, cancer-associated SNPs in a p53 network gene, CD44, were studied. Specifically, based on CD44’s known roles in both p53-dependent and independent signalling, it was predicted that the cancer-associated SNPs could function as biomarkers for chronic lymphocytic leukaemia progression, and for the response to anti-EGFR therapy for colorectal cancer. Indeed, supportive data is presented. Next, a methodology is presented that aims to identify cancer-associated SNPs in functional p53 binding sites using genome-wide datasets. Interestingly, a SNP is identified that dramatically influences the ability of p53 to regulate transcription of the KITLG oncogene and that associates with one of the largest risks of cancer identified to date. Intriguingly, the SNP is also shown to have undergone positive selection throughout human evolution, signifying a selective advantage, but similar SNPs are demonstrated to be rare in the genome due to negative selection, indicating that polymorphisms in p53 binding sites have been primarily detrimental to humans. Lastly, and in order to begin to explore if other polymorphic transcription factor binding motifs could be found in cancer-associated SNPs, a methodology was designed to identify SNPs in E-box transcription factor binding motifs, as they are sensitive to single base pair changes and affect cancer. Taken together, the work presented in this thesis shows how the study of how SNPs associate with, and impact upon, cancer has great potential to improve both biological knowledge and clinical outcomes.This thesis is not currently available in ORA

Single-nucleotide Polymorphisms in the p53 Signaling Pathway

The p53 tumor suppressor pathway is central both in reducing cancer frequency in vertebrates and in mediating the response of commonly used cancer therapies. This article aims to summarize and discuss a large body of evidence suggesting that the p53 pathway harbors functional inherited single-nucleotide polymorphisms (SNPs) that affect p53 signaling in cells, resulting in differences in cancer risk and clinical outcome in humans. The insights gained through these studies into how the functional p53 pathway SNPs could help in the tailoring of cancer therapies to the individual are discussed. Moreover, recent work is discussed that suggests that many more functional p53 pathway SNPs are yet to be fully characterized and that a thorough analysis of the functional human genetics of this important tumor suppressor pathway is required

The Inheritance of p53

The p53 pathway constitutes a major cellular gene network that is crucial in directing the suppression of cancer formation, mediating the response to commonly used cancer therapies, as well as the regulation of germline maintenance, fertility, and reproduction. It has been demonstrated that various cancer predisposition syndromes are caused by low-frequency, highly penetrant inherited mutations in the p53 network, the knowledge of which is already positively affecting patient survival. Mounting evidence from studies utilizing human material, patient cohorts, and mouse models suggests that higher frequency, lesser penetrant genetic variants can also affect p53 signaling, resulting in differences in cancer risk, prognosis, response to therapies, and/or natural selection. Indeed, multiple genes in the p53 network have been shown to harbor functional single nucleotide polymorphisms (SNPs). Comprehensive analyses of two SNPs have demonstrated that their effects on cancer can be modified by factors such as gender, estrogen, and other p53 pathway SNPs. Together these insights suggest that genetic variants in the p53 network could present an excellent opportunity to further define individuals in their abilities to react to stress, suppress tumor formation, and respond to therapies

M-learning : el uso de dispositivos móviles por una generación conectada

Este artigo tem por objetivo analisar a construção de aplicativos educacionais a fim de auxiliar no desenvolvimento do m-learning. Essa modalidade surgiu pela necessidade de planejar e implementar o uso crítico dos dispositivos móveis na educação, principalmente, por uma geração conectada em rede. A metodologia adotada foi uma abordagem qualitativa e quantitativa, do tipo estudo de caso, com estudantes de turmas de graduação de uma universidade pública. Na coleta de dados, foram disponibilizados dois instrumentos: a observação participante e o questionário com perguntas abertas e fechadas. Os dados permitiram verificar que o m-learning pode contribuir significativamente no processo de ensino e de aprendizagem dos estudantes. Nesse contexto, destaca-se o potencial para promover inovações no meio escolar, novas formas de comunicação, de interação e novas possibilidades para compreensão de conteúdos escolares através de aplicativosThis article aims to analyze the construction of educational applications in order to assist in the development of m-learning. This modality arose from the need to plan and implement the critical use of mobile devices in education, mainly by a networked generation. The methodology adopted was a qualitative and quantitative approach, of the case study type, with undergraduate students from a public university. In the data collection, two instruments were made available: the participant observation and the questionnaire with open and closed questions. The data allowed to verify that the m-learning can contribute significantly in the process of teaching and learning of the students. In this context, we highlight the potential to promote innovations in the school environment, new forms of communication, interaction and possibilities for understanding school content through applications.Este artículo pretende analizar la construcción de aplicaciones educativas para ayudar en el desarrollo del m-learning. Esta modalidad surgió de la necesidad de planificar e implementar el uso crítico de dispositivos móviles en la educación, principalmente por una generación en red. La metodología adoptada fue un enfoque cualitativo y cuantitativo, del tipo de estudio de caso, con estudiantes universitarios de una universidad pública. En la recopilación de datos, se pusieron a disposición dos instrumentos: la observación participante y el cuestionario con preguntas abiertas y cerradas. Los datos permitidos para verificar que el m-learning puede contribuir significativamente en el proceso de enseñanza y aprendizaje de los estudiantes. En este contexto, destacamos el potencial para promover innovaciones en el entorno escolar, nuevas formas de comunicación, interacción y posibilidades para comprender el contenido escolar a través de aplicaciones

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response.

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.This work was funded in part by the Ludwig Institute for Cancer Research, the Nuffield Department of Medicine, the Development Fund, Oxford Cancer Research Centre, University of Oxford, UK, by the Intramural Research Program of the National Institute of Environmental Health Sciences-National Institutes of Health (Z01-ES100475), and NIH grant (DP5-OD017937), US, and by the S-CORT Consortium from the Medical Research Council and Cancer Research UK

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Responsep53 Pathway SNPs and Mutations Interact to Affect Cancer

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets