Computational Analysis of Multilevel High-throughput Data from Cancer Tissue

The emergence of high-throughput measurement technologies has greatly expanded the possibilities for detecting and quantifying biomolecules involved in various subcellular and biomolecular processes on a larger scale than previously possible. These measurements, along with their accurate and robust analysis, play a crucial role in deepening our understanding and explaining a wide range of biological phenomena, including the development and progression of cancers. Consequently, this knowledge can be harnessed to develop effective interventions, particularly in the management and treatment of cancer. Within this dissertation, we have pursued two primary aims. Firstly, we aimed to develop novel computational and statistical tools and methods for the effective and efficient analysis of high-throughput data within the context of cancer. Secondly, using the tools and methods we developed, we sought to investigate single and multilevel high-throughput data to identify key alterations that drive the development and progression of prostate cancer. To accomplish the first aim, we devised a computational tool capable of detecting somatic copy number alterations. Additionally, we developed other computational and statistical approaches to mitigate the inherent biases present in data obtained from high- throughput sequencing technologies. As for the second aim, using the methods and tools we developed, we analyzed single and multilevel high-throughput data from a cohort of prostate cancer patients at various stages of their disease, identified multiple alterations, and presented our observations in detail. In summary, our study demonstrates the potential of the analysis of single and multilevel high-throughput data. Through this approach, we were able to replicate previous findings and uncover alterations that impact biological processes at different levels during the development and progression of prostate cancer

Development of a tool for copy number analysis of cancer genomes using high throughput sequencing data

Genomic copy number alterations (CNA) and loss of heterozygozity (LOH) are two types of genomic instabilities associated with cancer. Acquisition of these genomic instabilities affects the expression level of oncogenes and tumor suppressor genes. Thus, accurate detection of these abnormalities is a crucial step in identifying novel oncogenes and tumor suppressor genes. Whole-genome sequencing of tumor tissues has enabled new opportunities for the detection of such aberrations and the characterization of genomic aberrations in tumor samples. In this work, a fast tool for the identification of CNAs and copy-neutral LOH in tumor samples using whole-genome sequencing data was developed. The developed tool segments the genome by analyzing the read-depth and B-allele fraction profiles using a double sliding window method. It requires a matched normal sample to correct for biases such as GC-content and mapability and to discriminate somatic from germline events. The developed tool was evaluated on both simulated and real whole-genome sequencing data against competing, state of the art tools to demonstrate its accuracy. The tool, written in the Python programming language, is fast and performs segmentation of a whole genome in less than two minutes

Single cell and spatial transcriptomics highlight the interaction of club-like cells with immunosuppressive myeloid cells in prostate cancer

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 120 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells are associated with myeloid inflammation previously linked to androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting

Aberrant DNA methylation distorts developmental trajectories in atypical teratoid/rhabdoid tumors

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness and aberrant but still unresolved epigenetic regulation. To better understand their malignancy, we investigated how AT/RT-specific DNA hyper-methylation was associated with gene expression and altered transcription factor binding and how it is linked to upstream regulation. Medulloblastomas, choroid plexus tumors, pluripo-tent stem cells, and fetal brain were used as references. A part of the genomic regions, which were hypermethylated in AT/RTs similarly as in pluripotent stem cells and demethylated in the fetal brain, were targeted by neural transcriptional regulators. AT/RT-unique DNA hypermethylation was associated with poly-comb repressive complex 2 and linked to suppressed genes with a role in neural development and tumorigenesis. Activity of the several NEUROG/NEUROD pioneer factors, which are unable to bind to methylated DNA, was compromised via the suppressed expression or DNA hypermethylation of their target sites, which was also experimentally validated for NEUROD1 in medullo-blastomas and AT/RT samples. These results highlight and characterize the role of DNA hypermethylation in AT/RT malignancy and halted neural cell differentiation.Peer reviewe

Development of a tool for copy number analysis of cancer genomes using high throughput sequencing data

Genomic copy number alterations (CNA) and loss of heterozygozity (LOH) are two types of genomic instabilities associated with cancer. Acquisition of these genomic instabilities affects the expression level of oncogenes and tumor suppressor genes. Thus, accurate detection of these abnormalities is a crucial step in identifying novel oncogenes and tumor suppressor genes. Whole-genome sequencing of tumor tissues has enabled new opportunities for the detection of such aberrations and the characterization of genomic aberrations in tumor samples. In this work, a fast tool for the identification of CNAs and copy-neutral LOH in tumor samples using whole-genome sequencing data was developed. The developed tool segments the genome by analyzing the read-depth and B-allele fraction profiles using a double sliding window method. It requires a matched normal sample to correct for biases such as GC-content and mapability and to discriminate somatic from germline events. The developed tool was evaluated on both simulated and real whole-genome sequencing data against competing, state of the art tools to demonstrate its accuracy. The tool, written in the Python programming language, is fast and performs segmentation of a whole genome in less than two minutes

Information and Communication Technologies in Support of Remembering : A Postphenomenological Study

This thesis aimed to study the everyday use of ICT-enabled memory aids in order to understand and to describe the technological mediations that are brought by them (i.e. how they shape/mediate experiences and actions of their users). To do this, a post-phenomenological approach was appropriated. Postphenomenology is a modified, hybrid phenomenology that tries to overcome the limitations of phenomenology. As for theoretical framework, ‘Technological Mediation’ was adopted to conduct the study. Technological Mediation as a theory provides concepts suitable for explorations of the phenomenon of human-technology relation. It was believed that this specific choice of approach and theoretical framework would provide a new way of exploring the use of concrete technologies in everyday life of human beings and the implications that this use might have on humans’ lives. The study was conducted in the city of Växjö, Sweden. Data was collected by conducting twelve face-to-face semi-structured interviews. Collected data was, then, analyzed by applying the concepts within the theoretical framework – Technological Mediation - to them. The results of this study provided a list of ICT-enabled devices and services that participants were using in their everyday life in order to support their memory such as: calendars, alarms, notes, bookmarks, etc. Furthermore, this study resulted in a detailed description of how these devices and services shaped/mediated the experiences and the actions of their users.

Segmentum: a tool for copy number analysis of cancer genomes

Abstract Background Somatic alterations, including loss of heterozygosity, can affect the expression of oncogenes and tumor suppressor genes. Whole genome sequencing enables detailed characterization of such aberrations. However, due to the limitations of current high throughput sequencing technologies, this task remains challenging. Hence, accurate and reliable detection of such events is crucial for the identification of cancer-related alterations. Results We introduce a new tool called Segmentum for determining somatic copy numbers using whole genome sequencing from paired tumor/normal samples. In our approach, read depth and B-allele fraction signals are smoothed, and double sliding windows are used to detect breakpoints, which makes our approach fast and straightforward. Because the breakpoint detection is performed simultaneously at different scales, it allows accurate detection as suggested by the evaluation results from simulated and real data. We applied Segmentum to paired tumor/normal whole genome sequencing samples from 38 patients with low-grade glioma from the TCGA dataset and were able to confirm the recurrence of copy-neutral loss of heterozygosity in chromosome 17p in low-grade astrocytoma characterized by IDH1/2 mutation and lack of 1p/19q co-deletion, which was previously reported using SNP array data. Conclusions Segmentum is an accurate, user-friendly tool for somatic copy number analysis of tumor samples. We demonstrate that this tool is suitable for the analysis of large cohorts, such as the TCGA dataset

Whole-exome sequencing identifies germline mutation in TP53 and ATRX in a child with genomically aberrant AT/RT and her mother with anaplastic astrocytoma

Brain tumors typically arise sporadically and do not affect several family members simultaneously. In the present study, we describe clinical and genetic data from two patients, a mother and her daughter, with familial brain tumors. Exome sequencing revealed a germline missense mutation in the TP53 and ATRX genes in both cases, and a somatic copy-neutral loss of heterozygosity (LOH) in TP53 in both atypical teratoid/rhabdoid tumor (AT/RT) and astrocytoma tumors. ATRX mutation was associated with the loss of ATRX protein expression. In the astrocytoma case, R132C missense mutation was found in the known hotspot site in isocitrate dehydrogenase 1 (IDH1) and LOH was detected in TP53. The mother carried few other somatic alterations, suggesting that the IDH1 mutation and LOH in TP53 were sufficient to drive tumor development. The genome in the AT/RT tumor was atypically aneuploid: Most chromosomes had experienced copy-neutral LOH or whole-chromosome gains. Only Chromosome 18 had normal diploid status. INI1/hSNF5/SMARCB1 was homozygously deleted in the AT/RT tumor. This report provides further information about tumor development in a predisposed genetic background and describes two special Li–Fraumeni cases with a familial brain tumor.</jats:p