Survival rates in cancers have improved vastly over the years. However, some survival rates remain extremely low, as is the case for ovarian and lung cancer. The lack of robust and reliable biomarkers is strongly reflected in the absence of pre-screening programs, and as such, most patients in these cancer types are diagnosed only in advanced stages, leaving few treatment options. Moreover, relapse and resistance to therapies adds to the complexities of treating these diseases, even in the era of targeted drug development. Research has shown the presence of cancer material, in the form of circulating cancer cells (CTCs) and genomic material in the blood of patients, opening the possibility of 'liquid biopsies'. Liquid biopsies allow sampling of the disease to provide phenotypic and genomic data on the cancer in real-time and on a routine basis. Moreover, they overcome obstacles currently faced by conventional tissue biopsies. In this work we evaluate the use of a novel CTC imaging flow-cytometry platform, and report the ability to characterise and quantify these cells in blood samples. Moreover, we report significantly higher levels of CTCs in cancer patients compared to controls, and found them to be associated with a poorer prognosis. In particular, in lung cancer we observe these findings even in the early stages, suggesting a potential diagnostic use for this assay. We detect a similar trend in when analysing the ctDNA and suggest the possibility of using this technique with a prognostic value in the advanced setting. We also report on the analysis of existing microarray data by use of unique gene regulatory networks to identify biomarkers of interest. RAD51AP1 was identified by this process. Clinical validation revealed an over-expression of this gene in both tissue and blood of ovarian and lung cancers. Moreover, the gene over-expression was associated with a poor overall survival. Functional analysis in vitro revealed silencing RAD51AP1 suppressed tumour growth, in addition, various tumorigenic proteins were down-regulated, whilst apoptotic and immune genes were up-regulated. These results suggest a role for RAD51AP1 as a potential therapeutic target. In this study, we also demonstrate the ability to further exploit tumour genomic material in the blood by means of RNAseq, cancer panels, and CNI scoring to identify novel markers, that play an important role in disease genesis and evolution. RNAseq analysis identified XIST as a gene up-regulated in the blood and tissue of lung cancers. The ovarian cancer panels revealed 2 unique gene signatures in the ovarian cancer patients. With the CNI analyses also highlighting chromosomal aberrations from plasma analysis of cancer patients. Collectively, the use of all these techniques and exploitation of available blood based biomarkers could see significant improvements to survival rates in these, currently devastating diseases.

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Le projet Milieu Intérieur a pour but d'identifier les facteurs génétiques et environnementaux ayant un impact sur la variabilité immunitaire naturelle. Cette analyse multiparamétrique requière néanmoins d'utiliser des outils standardisés. Afin d'étudier la réponse immune induite, nous avons utilisé un système optimisé prêt à l'emploi de stimulation du sang et développé un protocole unique de quantification de l'ARN afin d'étudier la signature transcriptionnelle en réponse à des immuno-modulateurs. Testant l'hypothèse que la réponse à des composés complexes peut être définie par la signature ARN de cytokines clefs et utilisant une méthode statistique robuste, nous avons identifié 44 gènes capables d'optimiser la capture de la réponse à des stimulations plus complexes aidant à la réduction dimensionnelle pour la décomposition de réponses innées. Dans une seconde étude, l'analyse semi-automatisée par cytomètrie en flux des cellules du sang a été associée à l'analyse épidémiologique et génotypique pour les 1,000 donneurs inclus dans la cohorte. Nous avons observé que le tabac, l'âge, le genre et l'infection latente par le cytomégalovirus sont les facteurs impactant le plus la variabilité immunitaire. Cette étude a montré que les paramètres des cellules innées sont contrôlés par des facteurs génétiques alors que ceux des cellules adaptatives le sont plutôt par des expositions environnementales tout au long de la vie. Des outils interactifs incluant ces données de référence accompagnent ces études. Ces analyses montrent que nous avons développé des outils performants pour une étude intégrative du modèle humain constituant une approche innovante vers une médecine personnalisée. / The project Milieu Intérieur aims to study the genetic and environmental factors that can have a major impact on occurring immunological variance in healthy human population. This characterization requires the use of standardized immunophenotyping technologies for integrating diverse, complex datasets. With this goal in mind, we used an optimized suite of standardized whole-blood stimulation systems to study the human induced immune response in physiological condition and developed a unique standardized protocol to analyze the ARN signatures upon whole-blood stimulation to test the hypothesis that responses to complex stimuli can be defined by the transcriptional signatures of key cytokines. We found 44 genes, identified using Support Vector Machine learning, which captured the diversity of complex innate immune responses with improved segregation between distinct stimuli. This provides new strategies for dimension reduction of large datasets and for deconvolution of innate immune responses, applicable for characterizing novel immunomodulatory molecules.In a second related study, we aimed to identify the environmental and genetic factors driving innate and adaptive immune cell parameters in homeostatic conditions. To do so, we combined semi-automated flow cytometric analysis of blood leukocytes and genome-wide DNA genotyping in the 1,000 healthy donors included in the collection. We show that smoking, age, gender and latent cytomegalovirus infection, are main drivers of human variation (i.e. numbers of Treg and MAIT cells). These results demonstrated that innate cell parameters are strongly controlled by genetic factors, whereas adaptive cells are driven by life-long environmental exposures. In addition, to help on the public data mining, we developed interactive R-Shiny application including healthy donor reference values for both studies.All together, these results indicate that we developed powerful tools for human system biology approaches to support personalized medecine.