Anàlisi bioinformàtica de la base genética de la susceptibilitat al càncer de mama

En aquesta tesi, s’analitzen les dades d’un GWAS de càncer de mama més enllà de l’anàlisi estadístic. Sota la perspectiva de la biologia de sistemes, s’apliquen unes estratègies basades en conjunts de gens/proteïnes funcionalment relacionats per identificar nous gens de baixa penetrància, els processos biològics en els que participen i els mecanismes moleculars mitjançant els quals confereixen el risc així com les seves interaccions. El càncer de mama és un exemple de malaltia complexa on participen tant factors genètics com ambientals en la seva etiologia. Entendre la base genètica del càncer de mama en profunditat podria permetre entendre millor la malaltia i desenvolupar millors eines de diagnòstic, pronòstic i/o tractament. D’aquesta manera, s’ha determinat que podrien influir en el risc de càncer de mama variants comunes en els gens dels processos biològics Cell Communication i Cell Adhesion; així com en determinats loci de les driver kinases, particularment en els gens que codifiquen per receptors d’EPHs. A més, variants comunes en el locus EPHB1 podrien estar associades amb el risc a càncer de mama en portadors de mutacions en BRCA1 i BRCA2. D’altra banda, s’ha determinat que les interaccions gen-gen podrien contribuir a explicar part de la missing heritability i inclourien freqüentment gens relacionats amb processos fonamentals en diferents tipus cel·lulars, com són el metabolisme i la biosíntesi de molècules. A més, les interaccions gen-gen associades al risc de càncer podrien ser predites en part mitjançant els patrons complexes de coexpressió gènica específics del tipus de càncer. Recentment, a partir dels resultats del metanàlisi de càncer de mama més gran realitzat fins el moment, s’ha suggerit que existeixen molts més loci (potser alguns milers), la majoria amb 0,95 < ORs < 1,05 que contribueixen a la susceptibilitat. Aquests resultats donen suport a la hipòtesi del model infinitesimal per explicar la missing heritability en càncer de mama. Segons aquesta hipòtesi, centenars o milers d’al·lels comuns, amb efectes relativament molt petits, contribuirien a la susceptibilitat a la malaltia. Així, els GWAS portats a terme fins ara, haurien detectat els al·lels amb un efecte major, la resta dels al·lels de susceptibilitat no poden ser detectats degut als estrictes llindars de significació utilitzats en aquests estudis. En aquest context, les interaccions genètiques tampoc poden ser detectades amb robustesa degut als estrictes llindars de significació requerits. Aquest fet, justifica la nostra estratègia basada en la biologia de sistemes per l’anàlisi dels resultats del GWAS en lloc de centrar-nos en els SNPs/gens individualment.In GWAS, genes are interpreted individually, and a gene ranked below the significance threshold will not be measured or experimentally characterized in relation to the disease or to genes that passed the threshold. Given these statistical constraints of GWAS, a Systems Biology approach can facilitate interpretation of GWAS results. In this thesis, we applied an integrative approach for identifying candidate low- penetrance breast cancer susceptibility genes, their characteristics and molecular networks through the analysis of diverse sources of biological evidence. Breast cancer is a complex disease; both genetic and environmental factors contribute to its etiology. A deep knowledge of genetic basis of breast cancer contributes to disease understanding and better diagnostic, prognostic and treatment tools. As a result of this work we propose that breast cancer risk may be influenced by common variants in Cell Communication and Cell Adhesion Biological Processes; also in driver kinases loci, specifically in genes encoding EPHs receptors. Moreover common variants in EPHB1 locus may be associated to breast cancer in BRCA1 and BRCA2 mutation carriers. In the other hand, gene-gene interactions might contribute to missing heritability. In addition, gene-gene interactions associated to breast cancer may be predicted using complex co-expression patterns in the specific cancer type

Anàlisi bioinformàtica de la base genética de la susceptibilitat al càncer de mama

[cat] En aquesta tesi, s’analitzen les dades d’un GWAS de càncer de mama més enllà de l’anàlisi estadístic. Sota la perspectiva de la biologia de sistemes, s’apliquen unes estratègies basades en conjunts de gens/proteïnes funcionalment relacionats per identificar nous gens de baixa penetrància, els processos biològics en els que participen i els mecanismes moleculars mitjançant els quals confereixen el risc així com les seves interaccions. El càncer de mama és un exemple de malaltia complexa on participen tant factors genètics com ambientals en la seva etiologia. Entendre la base genètica del càncer de mama en profunditat podria permetre entendre millor la malaltia i desenvolupar millors eines de diagnòstic, pronòstic i/o tractament. D’aquesta manera, s’ha determinat que podrien influir en el risc de càncer de mama variants comunes en els gens dels processos biològics Cell Communication i Cell Adhesion; així com en determinats loci de les driver kinases, particularment en els gens que codifiquen per receptors d’EPHs. A més, variants comunes en el locus EPHB1 podrien estar associades amb el risc a càncer de mama en portadors de mutacions en BRCA1 i BRCA2. D’altra banda, s’ha determinat que les interaccions gen-gen podrien contribuir a explicar part de la missing heritability i inclourien freqüentment gens relacionats amb processos fonamentals en diferents tipus cel·lulars, com són el metabolisme i la biosíntesi de molècules. A més, les interaccions gen-gen associades al risc de càncer podrien ser predites en part mitjançant els patrons complexes de coexpressió gènica específics del tipus de càncer. Recentment, a partir dels resultats del metanàlisi de càncer de mama més gran realitzat fins el moment, s’ha suggerit que existeixen molts més loci (potser alguns milers), la majoria amb 0,95 < ORs < 1,05 que contribueixen a la susceptibilitat. Aquests resultats donen suport a la hipòtesi del model infinitesimal per explicar la missing heritability en càncer de mama. Segons aquesta hipòtesi, centenars o milers d’al·lels comuns, amb efectes relativament molt petits, contribuirien a la susceptibilitat a la malaltia. Així, els GWAS portats a terme fins ara, haurien detectat els al·lels amb un efecte major, la resta dels al·lels de susceptibilitat no poden ser detectats degut als estrictes llindars de significació utilitzats en aquests estudis. En aquest context, les interaccions genètiques tampoc poden ser detectades amb robustesa degut als estrictes llindars de significació requerits. Aquest fet, justifica la nostra estratègia basada en la biologia de sistemes per l’anàlisi dels resultats del GWAS en lloc de centrar-nos en els SNPs/gens individualment.[eng] In GWAS, genes are interpreted individually, and a gene ranked below the significance threshold will not be measured or experimentally characterized in relation to the disease or to genes that passed the threshold. Given these statistical constraints of GWAS, a Systems Biology approach can facilitate interpretation of GWAS results. In this thesis, we applied an integrative approach for identifying candidate low- penetrance breast cancer susceptibility genes, their characteristics and molecular networks through the analysis of diverse sources of biological evidence. Breast cancer is a complex disease; both genetic and environmental factors contribute to its etiology. A deep knowledge of genetic basis of breast cancer contributes to disease understanding and better diagnostic, prognostic and treatment tools. As a result of this work we propose that breast cancer risk may be influenced by common variants in Cell Communication and Cell Adhesion Biological Processes; also in driver kinases loci, specifically in genes encoding EPHs receptors. Moreover common variants in EPHB1 locus may be associated to breast cancer in BRCA1 and BRCA2 mutation carriers. In the other hand, gene-gene interactions might contribute to missing heritability. In addition, gene-gene interactions associated to breast cancer may be predicted using complex co-expression patterns in the specific cancer type

Evolutionary Changes after Translational Challenges Imposed by Horizontal Gene Transfer

Genes acquired by horizontal gene transfer (HGT) may provide the recipient organism with potentially new functions, but proper expression level and integration of the transferred genes in the novel environment are not granted. Notably, transferred genes can differ from the receiving genome in codon usage preferences, leading to impaired translation and reduced functionality. Here, we characterize the genomic and proteomic changes undergone during experimental evolution of Escherichia coli after HGT of three synonymous versions, presenting very different codon usage preference, of an antibiotic resistance gene. The experimental evolution was conducted with and without the corresponding antibiotic and the mutational patterns and proteomic profiles after 1,000 generations largely depend on the experimental growth conditions (e.g., mutations in antibiotic off-target genes), and on the synonymous gene version transferred (e.g., mutations in genes responsive to translational stress). The transfer of an exogenous gene extensively modifies the whole proteome, and these proteomic changes are different for the different version of the transferred gene. Additionally, we identified conspicuous changes in global regulators and in intermediate metabolism, confirmed the evolutionary ratchet generated by mutations in DNA repair genes and highlighted the plasticity of bacterial genomes accumulating large and occasionally transient duplications. Our results support a central role of HGT in fuelling evolution as a powerful mechanism promoting rapid, often dramatic genotypic and phenotypic changes. The profound reshaping of the pre-existing geno/phenotype allows the recipient bacteria to explore new ways of functioning, far beyond the mere acquisition of a novel function

Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap

Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome

Background: Polygenic risk scores (PRSs) have been used to stratify colorectal cancer (CRC) risk in the general population, whereas its role in Lynch syndrome (LS), the most common type of hereditary CRC, is still conflicting. We aimed to assess the ability of PRS to refine CRC risk prediction in European-descendant individuals with LS. Methods: 1465 individuals with LS (557 MLH1, 517 MSH2/EPCAM, 299 MSH6 and 92 PMS2) and 5656 CRC-free population-based controls from two independent cohorts were included. A 91-SNP PRS was applied. A Cox proportional hazard regression model with 'family' as a random effect and a logistic regression analysis, followed by a meta-analysis combining both cohorts were conducted. Results: Overall, we did not observe a statistically significant association between PRS and CRC risk in the entire cohort. Nevertheless, PRS was significantly associated with a slightly increased risk of CRC or advanced adenoma (AA), in those with CRC diagnosed <50 years and in individuals with multiple CRCs or AAs diagnosed <60 years. Conclusion: The PRS may slightly influence CRC risk in individuals with LS in particular in more extreme phenotypes such as early-onset disease. However, the study design and recruitment strategy strongly influence the results of PRS studies. A separate analysis by genes and its combination with other genetic and non-genetic risk factors will help refine its role as a risk modifier in LS

Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment

Background: Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases. Methods: We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes. In a novel approach, we first used pathway analysis of all published genome-wide association studies (GWAS) to find a cell type common to many diseases. Results: The analysis showed over-representation of the T helper cell differentiation pathway, which is expressed in T cells. This led us to focus on expression profiling of CD4(+) T cells from highly diverse inflammatory and malignant diseases. We found that pleiotropic genes were highly interconnected and formed a pleiotropic module, which was enriched for inflammatory, metabolic and proliferative pathways. The general relevance of this module was supported by highly significant enrichment of genetic variants identified by all GWAS and cancer studies, as well as known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed the importance of both pleiotropic and disease specific modules for clinical stratification. Conclusions: In summary, this translational genomics study identified a pleiotropic module, which has key pathogenic, diagnostic and therapeutic roles

Serum 25-hydroxyvitamin D3 levels and vitamin D receptor variants in melanoma patients from the Mediterranean area of Barcelona

BACKGROUND: Serum 25-hydroxyvitamin D3 (Vitamin D) insufficiency and single-nucleotide polymorphisms (SNPs) on its receptor, Vitamin D receptor (VDR), have been reported to be involved in melanoma susceptibility in populations mostly from northern countries. OBJECTIVE: To investigate 25-hydroxyvitamin D3 levels and VDR SNPs in melanoma patients from sunny area of Barcelona, two studies were carried out. The first study evaluated the levels of Vitamin D at time of melanoma diagnosis and the second one analyzed the association between VDR genetic variants and risk of having a high nevus number, the strongest phenotypic risk factor for melanoma. METHODS: The levels of 25-hydroxyvitamin D3 in 81 melanoma patients at diagnosis were measured. In a second group of melanoma patients, including 150 with low and 113 with high nevus number, 11 VDR SNPs were analyzed for their association with nevus number. RESULTS: In the first study, 68% of patients had insufficient levels of 25-hydroxyvitamin D3 (<25 ng/ml). Autumn-winter months and fair phototype were associated with 25-hydroxyvitamin D3 insufficiency; after multivariate analysis, season of sampling remained the only independent predictor of 25-hydroxyvitamin D3 levels. In the second study, VDR variant rs2189480 (P = 0.006) was associated with risk of high nevus number whereas rs2239179 (P = 0.044) and rs7975128 (P = 0.0005) were protective against high nevus number. After Bonferroni adjustment only rs7975128 remained significant. In stratified analysis, SNP rs7975128 was found protective against multiple melanomas (P = 0.021). CONCLUSION: This study showed that even in Barcelona, a sunny Mediterranean area, 25-hydroxyvitamin D3 levels were sub-optimal in the majority of melanoma patients at diagnosis. The involvement of VDR in nevi and, in turn, in melanoma susceptibility has also been suggested. Larger studies are needed to confirm our findings

Assessing Associations between the AURKA-HMMR-TPX2-TUBG1 Functional Module and Breast Cancer Risk in BRCA1/2 Mutation Carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04-1.15, p = 1.9 x 10(-4) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03-1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted pinteraction values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients' survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers

Generation and integrated analysis of advanced patient-derived orthoxenograft models (PDOX) for the rational assessment of targeted therapies in endometrial cancer

Clinical management of endometrial cancer (EC) is handicapped by the limited availability of second line treatments and bona fide molecular biomarkers to predict recurrence. These limitations have hampered the treatment of these patients, whose survival rates have not improved over the last four decades. The advent of coordinated studies such as The Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma (TCGA_UCEC) has partially solved this issue, but the lack of proper experimental systems still represents a bottleneck that precludes translational studies from successful clinical testing in EC patients. Within this context, the first study reporting the generation of a collection of endometrioid-EC-patient-derived orthoxenograft (PDOX) mouse models is presented that is believed to overcome these experimental constraints and pave the way toward state-of-the-art precision medicine in EC. The collection of primary tumors and derived PDOXs is characterized through an integrative approach based on transcriptomics, mutational profiles, and morphological analysis; and it is demonstrated that EC tumors engrafted in the mouse uterus retain the main molecular and morphological features from analogous tumor donors. Finally, the molecular properties of these tumors are harnessed to assess the therapeutic potential of trastuzumab, a human epidermal growth factor receptor 2 (HER2) inhibitor with growing interest in EC, using patient-derived organotypic multicellular tumor spheroids and in vivo experiments

High-sensitivity microsatellite instability assessment for the detection of mismatch repair defects in normal tissue of biallelic germline mismatch repair mutation carriers

Introduction: Lynch syndrome (LS) and constitutional mismatch repair deficiency (CMMRD) are hereditary cancer syndromes associated with mismatch repair (MMR) deficiency. Tumours show microsatellite instability (MSI), also reported at low levels in non-neoplastic tissues. Our aim was to evaluate the performance of high-sensitivity MSI (hs-MSI) assessment for the identification of LS and CMMRD in non-neoplastic tissues. Materials and methods: Blood DNA samples from 131 individuals were grouped into three cohorts: baseline (22 controls), training (11 CMMRD, 48 LS and 15 controls) and validation (18 CMMRD and 18 controls). Custom next generation sequencing panel and bioinformatics pipeline were used to detect insertions and deletions in microsatellite markers. An hs-MSI score was calculated representing the percentage of unstable markers. Results: The hs-MSI score was significantly higher in CMMRD blood samples when compared with controls in the training cohort (p<0.001). This finding was confirmed in the validation set, reaching 100% specificity and sensitivity. Higher hs-MSI scores were detected in biallelic MSH2 carriers (n=5) compared with MSH6 carriers (n=15). The hs-MSI analysis did not detect a difference between LS and control blood samples (p=0.564). Conclusions: The hs-MSI approach is a valuable tool for CMMRD diagnosis, especially in suspected patients harbouring MMR variants of unknown significance or non-detected biallelic germline mutations. Keywords: constitutional mismatch repair deficiency; highly sensitive methodologies; lynch syndrome; microsatellite instability; next generation sequencing