L’arrivée récente de l’immunothérapie a bouleversé la prise en charge des cancers broncho-pulmonaires non à petites cellules (CBNPC). Le nivolumab, anticorps inhibiteur du point de contrôle immunitaire PD-1, a montré des résultats remarquables en deuxième ligne métastatique après échec des chimiothérapies standards de première intention. Cependant, seul un quart des patients tire un bénéfice durable de la prise de ce traitement. `A ce jour, aucun biomarqueur prédictif de l'efficacité thérapeutique du nivolumab n'a pu être identifié de manière claire et consensuelle. La recherche de biomarqueurs prédictifs de bénéfice ou de résistance à ce traitement répresente donc un enjeu majeur.L’apparition du séquençage à haut débit au cours de la dernière décennie a eu un impact considérable sur la recherche clinique et fondamentale, permettant d’appréhender la génétique d’une tumeur dans son ensemble. Ces nouvelles techniques s’ajoutent à d’autres déjà éprouvées telles que l’immunophénotypage ou l’immunohistochimie à disposition des chercheurs pour une analyse extensive des caractéristiques de la tumeur et du patient.L’objectif de ce travail a été d’identifier des marqueurs prédictifs d’efficacité du nivolumab dans le traitement des CBNPC avancés au moyen de ces différentes technologies. Pour cela, notre étude s'est alors intéressée à une cohorte multicentrique de 115 patients atteints de CBNPC et traités par nivolumab en deuxième ou troisième ligne métastatique après échec d'un doublet cytotoxique. Dans les limites de disponibilité et de qualité des échantillons, les profils génétique, transcriptomique et immunohistochimique de la tumeur ainsi que les profils clinique et immunologique des patients ont été analysés.Nos résultats mettent en évidence des marqueurs prédictifs majeurs de réponse au nivolumab. Ainsi, une bonne réponse au doublet cytotoxique de première intention favorise une efficacité optimale du nivolumab en ligne ultérieure. Par ailleurs, un contrôle régulier de l'évolution des cellules myéloïdes immunosuppresives et des cellules cytotoxiques exprimant TIM-3 d'un patient permet de détecter une résistance primaire ou secondaire au traitement. D'autre part, l'estimation conjointe des expressions des protéines PD-L1 et CD8 par séquençage d'ARN constitue un marqueur prédictif majeur de réponse. Sa capacité prédictive surpasse celle de l'estimation de PD-L1 seule et celle d'autres signatures transcriptomiques précédemment établies et composées d'un nombre plus important de gènes. Enfin, l'étude des séquençages d'exome des tumeurs montre l'importance d'une analyse étendue de la génétique tumorale et la nécessité de ne pas se limiter à l'estimation de sa charge mutationnelle.Dans ce travail, nous avons pu mettre en évidence des marqueurs prédictifs d'efficacité du nivolumab dans le traitement des CBNPC avancés. Nos résultats soulignent l'importance de l'utilisation de plusieurs technologies pour la caractérisation de la biologie tumorale et de l'immunité du patient dans une démarche de découverte de biomarqueurs et de construction de modèles prédictifs d'efficacité des immunothérapies. / The recent introduction of immunotherapy has disrupted the management of non-small cell lung cancer (NSCLC). Nivolumab, an antibody targeting the immune checkpoint inhibitor PD-1, has shown remarkable results in seconde-line setting after failure of standard first-line chemotherapy. However, only a quarter of patients benefits from this therapy. To date, no predictive biomarker of the therapeutic efficacy of nivolumab has been identified in a clear and consensual manner. The research for predictive biomarkers of efficacy or resistance to this treatment is, therefore, a major challenge.The emergence of high-throughput sequencing over the past decade has had a significant impact on clinical and fundamental research, making possible to understand the genetics of a tumor as a whole. These new techniques are in addition to other already proven techniques such as immunophenotyping or immunohistochemistry available to researchers for extensive analysis of tumor and patient characteristics.The objective of this work was to identify predictors of the efficacy of nivolumab in the treatment of advanced NSCLC using these different technologies. To do this, our study focused on a multicentre cohort of 115 NSCLC patients treated with nivolumab in the second- or third-line after failure of a cytotoxic doublet. Within the limits of sample availability and quality, the genetic, transcriptomic and immunohistochemical profiles of the tumor as well as the clinical and immunological profiles of the patients were analysed.Our results highlight major predictive markers of response to nivolumab. Thus, a good response to the first-line cytotoxic doublet promotes optimal efficacy of subsequent online nivolumab. In addition, regular monitoring of the evolution of a patient's immunosuppressive myeloid cells and cytotoxic cells expressing TIM-3 can detect primary or secondary resistance to treatment. On the other hand, the joint estimation of PD-L1 and CD8 protein expressions by RNA sequencing is a major predictive marker of response. Its predictive capacity surpasses that of the PD-L1 estimate alone and that of other previously established transcriptomic signatures composed of a larger number of genes. Finally, the study of tumor exome sequencing shows the importance of extensive analysis of tumor genetics and the need not only to focus on the estimation its mutation burden.In this work, we were able to identify predictive markers of the efficacy of nivolumab in the treatment of advanced NSCLC. Our results highlight the importance of using several technologies for the characterization of tumor biology and patient immunity in a process of biomarker discovery and the construction of predictive models of the efficacy of immunotherapies.

As the field of next-generation sequencing (NGS) matures and the technology grows more advanced, it is becoming an increasingly strong tool for solving various biological problems. Harvesting and analysing the full genomic sequence of an individual and comparing it to a reference genome can unravel information about detrimental mutations, in particular ones that give rise to diseases such as cancer. At the Rudbeck Laboratory, Uppsala University, a fully automatic software pipeline for somatic mutational analysis of cancer patient sequence data is in development. This will increase the efficiency and accuracy of a process which today consists of several discrete computation steps. In turn, this will reduce the time to result and facilitate the process of making a diagnosis and delegate the optimal treatment for the patient. However, the genomic data of an individual is very sensitive and private, which demands that great security precautions are taken. Moreover, as more and more data are produced storage space is becoming increasingly valuable, which requires that data are handled and stored as efficiently as possible. In this project, I developed a Python pipeline for automatic compression and encryption of NGS alignment data, which aims to ensure full privacy protection of patient data while maintaining high computational and storage efficiency. The pipeline uses a state-of-the-art real-time compression algorithm combined with an Advanced Encryption Standard cipher. It offers security that meets rigorous modern standards, and performance which at least matches that of existing solutions. The system is made to be easily integrated in the somatic mutation analysis pipeline. This way, the data generated during the analysis, which are too large to be kept in operational memory, can safely be stored to disk.

A list of genes have been identified to carry mutations causing familial ALS such as SOD1, TARDBP, C9orf72. But for sporadic ALS, which is 90% of all ALS cases, the underlying genetic variants are still largely unknown. There are multiple genome-wide association study (GWAS) for sporadic ALS, but usually a large number nominated SNP can hardly be replicated in larger cohort analysis. Also majority of GWAS SNP lie within noncoding region of genome, imposing a huge challenge to study their biological role in ALS pathology. With the rapid development of next-generation sequencing technology, we are able to sequence exome and whole-genome of a large number of ALS patients to search for novel genetic variants and their potential biological function. Here by analyzing exam data, we discovered two novel or extremely rare missense mutations of DPP6 from a Mestizo Mexican ALS family. We showed the two mutations could exert loss-of-function effect by affecting electrophysiological properties of Potassium channels as well as the membrane localization of DPP6. To our knowledge this is the first report of DPP6 nonsynonymous mutations in familial ALS patients. In addition, by analyzing whole-genome data, we discovered strong linkage disequilibrium between SNP rs12608932, a repeatedly significant ALS GWAS signal, and one polymorphic TGGA tetra-nucleotide tandem repeat, which is further flanked by large TGGA repetitive sequences. We also demonstrated rs12608932 risk allele is associated with reduced UNC13A expression level in human cerebellum and UNC13A knockout could lead to shorter survival in SOD1-G93A ALS mice. Thus the TGGA repeat might be the real underlying genetic variation that confer risk to sporadic ALS.

Indiana University-Purdue University Indianapolis (IUPUI) / Triple-negative breast cancers (TNBCs) are pathologically defined by the absence of estrogen, progesterone, and HER2 receptors. Compared to other breast cancers, TNBC has a relatively high mortality. In addition, TNBC patients are more likely to relapse in the first few years after treatment, and experiencing a shorter median time from recurrence to death. Detecting the presence of tumor in patients who are technically “disease-free” after neoadjuvant chemotherapy and surgery as early as possible might be able to predict recurrence of patients, and then provide timely intervention for additional therapy. To this end, I applied the analysis of “liquid biopsies” for early detection of minimal residual disease (MRD) on early-stage TNBC patients using next-generation sequencing. For the first part of this study, I focused on detecting circulating tumor DNA (ctDNA) from TNBC patients after neoadjuvant chemotherapy and surgery. First, patient-specific somatic mutations were identified by sequencing primary tumors. From these data, 82% of the patients had at least one TP53 mutation, followed by 16% of the patients having at least one PIK3CA mutation. Next, I sequenced matched plasma samples collected after surgery to identify ctDNA with the same mutations. I observed that by detecting corresponding ctDNA I was able to predict rapid recurrence, but not distant recurrence. To increase the sensitivity of MRD detection, in the second part I developed a strategy to co-detect ctDNA along with circulating tumor RNA (ctRNA). An advantage of ctRNA is its active release into the circulation from living cancer cells. Preliminary data showed that more mutant molecules were identified after incorporating ctRNA with ctDNA detection in a metastatic breast cancer setting. A validation study in early-stage TNBC is in progress. In summary, my study suggests that co-detection of ctDNA and ctRNA could be a potential solution for the early detection of disease recurrence. / 2021-08-05

The use of the MinION sequencer (Oxford Nanopore) was tested on samples prepared to simulate infectious samples. The tested procedure is to simulate work with a sample with an unknown pathogen. Therefore, a metagenomic approach was chosen. Three kits were tested: Rapid Barcoding Sequencing, PCR Barcoding and Premium whole genome amplification. Each kit differed in duration, difficulty to prepare and in amplification of nucleic acids. In total it was chosen eight viruses with different genome lengths and with varying types of the genome (5,6 - 152 kb, ss/ds RNA, dsDNA). Ten samples were prepared to simulate different types of infection (respiratory, gastrointestinal tract and urine), and one sample contained pure water as a negative control. Before preparation of the library with Oxford Nanopore's kits, DNase/RNase treatment was used. The viral RNA was transcribed into DNA and in chosen samples were amplificated to reach a higher concentration of nucleic acids. Rapid barcoding sequencing kit detected all selected viruses with the highest number of viral reads (4403) with a length between 100 and 250 nt and quality coverage of viral genomes. PCR Barcoding kit detected five out of eight viruses, and the number of identified reads with a length of 100-200 nt distinctly decreased. Premium whole genome...

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Ovarian cancer (OC) is the deadliest gynecologic malignancy with a substantial proportion of hereditary cases and a frequent association with breast cancer (BC). Genetic testing facilitates preventive management for carriers of mutations in OC-susceptibility genes. However, the prevalence of germline mutations varies among populations and many rarely mutated OC predisposition genes remain to be identified. We analyzed 219 genes in 1333 Czech OC patients and 2278 population-matched controls (PMC) using next-generation sequencing. Altogether, 427/1333 (32%) patients and 58 /2278 (2,5%) PMC carried pathogenic mutations in 18 known/anticipated OC predisposition genes. Mutations in BRCA1, BRCA2, RAD51C, RAD51D, BARD1 and mismatch repair genes conferred a high OC risk (with OR>5). Mutations in BRIP1 and NBN were associated with moderate risk (both OR ≥2 - <5). BRCA1/2 mutations dominated in almost all clinicopathological subgroups including sporadic borderline tumors of ovary (BTO). Analysis of remaining 201 genes revealed somatic mosaics in PPM1D and germline mutations in SHPRH and NAT1 associating with a high/moderate OC risk significantly; however, further studies are warranted to delineate their contribution to OC development in other populations. Results of this study demonstrate the high proportion...

In this study we build solutions to three common challenges in the fields of bioinformatics through utilizing statistical methods and developing computational approaches. First, we address a common problem in genome wide association studies, which is linking genotype features within organisms of the same species to their phenotype characteristics. We specifically studied FHA domain genes in Arabidopsis thaliana distributed within Eurasian regions by clustering those plants that share similar genotype characteristics and comparing that to the regions from which they were taken. Second, we also developed a tool for calculating transposable element density within different regions of a genome. The tool is built to utilize the information provided by other transposable element annotation tools and to provide the user with a number of options for calculating the density for various genomic elements such as genes, piRNA and miRNA or for the whole genome. It also provides a detailed calculation of densities for each family and subamily of the transposable elements. Finally, we address the problem of mapping multi reads in the genome and their effects on gene expression. To accomplish this, we implemented methods to determine the statistical significance of expression values within the genes utilizing both a unique and multi-read weighting scheme. We believe this approach provides a much more accurate measure of gene expression than existing methods such as discarding multi reads completely or assigning them randomly to a set of best assignments, while also providing a better estimation of the proper mapping locations of ambiguous reads. Overall, the solutions we built in these studies provide researchers with tools and approaches that aid in solving some of the common challenges that arise in the analysis of high throughput sequence data.

Indiana University-Purdue University Indianapolis (IUPUI) / Triple-negative breast cancers (TNBCs) are negative for the expression of estrogen (ER), progesterone (PR), and HER-2 receptors. TNBC accounts for 15% of all breast cancers and results in disproportionally higher mortality compared to ER & HER2-positive tumours. Moreover, there is a paucity of therapies for this subtype of breast cancer resulting primarily from an inadequate understanding of the transcriptional differences that differentiate TNBC from normal breast. To this end, we embarked on a comprehensive examination of the transcriptomes of TNBCs and normal breast tissues using next-generation whole transcriptome sequencing (RNA-Seq). By comparing RNA-seq data from these tissues, we report the presence of differentially expressed coding and non-coding genes, novel transcribed regions, and mutations not previously reported in breast cancer. From these data we have identified two major themes. First, BRCA1 mutations are well known to be associated with development of TNBC. From these data we have identified many genes that work in concert with BRCA1 that are dysregulated suggesting a role of BRCA1 associated genes with sporadic TNBC. In addition, we observe a mutational profile in genes also associated with BRCA1 and DNA repair that lend more evidence to its role. Second, we demonstrate that using microdissected normal epithelium maybe an optimal comparator when searching for novel therapeutic targets for TNBC. Previous studies have used other controls such as reduction mammoplasties, adjacent normal tissue, or other breast cancer subtypes, which may be sub-optimal and have lead to identifying ineffective therapeutic targets. Our data suggests that the comparison of microdissected ductal epithelium to TNBC can identify potential therapeutic targets that may lead to be better clinical efficacy. In summation, with these data, we provide a detailed transcriptional landscape of TNBC and normal breast that we believe will lead to a better understanding of this complex disease.

<p>  </p> <p>Plant complex traits are controlled by multi-layer of dynamic and complicated gene networks regulated at different levels. To better inform crop breeding to promote desired traits, a comprehensive and fundamental understanding of their genetic basis is much needed. With the rapid developments of <em>omics</em> planforms and next generation sequencing technology, we now have large-scale data from genome, epigenome, transcriptome, metabolome, and others for the crop plants. Integration of those multiple <em>omics</em> data together with computational approaches led to the establishment of a novel science known as system biology. Research described in this thesis used system biology approaches to dissect complex crop traits such as disease response of tomato (Chapter2 and Chapter3) and the heterosis of nitrogen use efficiency of maize (Chapter4).</p> <p>Plant disease response is an elaborate, multilayered complex trait involving several lines of defense signaling. In the past decades, progress in molecular analyses of plant immune system has revealed key elements of a complex response network in Arabidopsis, a model species. Histone modifications, a type of epigenetic regulation, have emerged as key modulators that regulate defense responses, while our understanding of the role of histone-modifying enzymes in this process is still in its infancy. Here, we described the immune function of two histone methyltransferases SDG33 and SDG34 in tomato. We found the single mutants in <em>sdg33</em> and <em>sdg34</em> showed increased susceptibility to hemibiotrophic bacterial pathogen <em>Pseudomonas syringae</em> whereas the double mutant <em>sdg33sdg34</em> is comparable to wild type. Using RNA-seq and histone ChIP-seq approaches, we investigated the possible underlying mechanisms and found that the expression of a set of immune-related genes is misregulated by <em>P. syringae</em> only in the single mutants but not in the double mutant. Integrating with epigenomic data, we found that the misexpression of those SDG33/SDG34 dependent immune-response genes was associated with altered histone methylation status in the single mutant. Intriguingly, the double mutant also showed altered histone methylation but unaffected gene expression, suggesting a compensating regulatory mechanism at play. The function of SDG33 and SDG34 in immune response seems to be specific for the pathogen, as the double mutants exhibited enhanced resistance the single mutants showed no altered responses when treated with necrotrophic fungal pathogen <em>Botrytis cinerea</em>. Network analysis found the most regulatory gene by <em>B. cinerea</em> in a SDG33/SDG34 dependent manner have been implicated in biotic stress response such as <em>ERF4, TOPLESS, PUB23 </em>and<em> RCD1</em>. Comparing the immune response of double mutant against <em>P. syringae</em> and <em>B. cinerea</em>, we found that the disease related genes are only mis-regulated in the interaction of <em>B. cinerea</em> treatment not in the <em>P. syringae</em> treatment, which could be the reason of enhanced resistance to <em>B. cinerea</em> but not for <em>P. syringae</em> in the double mutants. In summary, we found the histone methyltransferases SDG33 and SDG34 has different functions in the immune response against <em>P. syringae</em> and <em>B. cinerea</em>, which might be direct or indirect relevant to the histone methylation level of the expression of downstream immune related gene.</p> <p>In addition to biotic stress, another complex trait studied in this thesis is the heterosis of nitrogen use efficiency (NUE) in Maize. NUE is another complex trait associated with multiple physiological processes including N sensing, uptake, assimilation, transport, and storage. Heterosis refers to a phenomenon where the progeny generated by crossing two different cultivars of the same species exhibit superior fitness than the inbred parents. Even though, heterosis has been exploited to improve complex traits including NUE, the underlying molecular mechanisms is not completely understood. Here, we analyzed N-responsive transcriptomes and physiological traits of a panel of six maize hybrids and their corresponding inbreds grown in the field at two different N levels. We observed diverse levels of trait heterosis that are dependent on the N conditions and organ types. We discovered dramatic pattern shift of beyond-parental-range gene expression in hybrids in response to varying N levels. We identified through integrative analyses a set of genes whose expression heterosis are quantitatively correlated to trait heterosis. These genes are involved in response to stimulus, photosynthesis, and N metabolism, and likely mediate the heterosis phenotype of N-use and growth traits in maize. In summary, our integrated analysis provided insights into the mechanistic basis of the heterosis of NUE. </p> <p>Together, applying systems and functional genomics approaches to investigate important agricultural traits could lead to a comprehensive understanding of plant complex traits to inform future engineering and breeding for better crops.</p>