Cancer proteogenomics : connecting genotype to molecular phenotype

The central dogma of molecular biology describes the one-way road from DNA to RNA and finally to protein. Yet, how this flow of information encoded in DNA as genes (genotype) is regulated in order to produce the observable traits of an individual (phenotype) remains unanswered. Recent advances in high-throughput data, i.e., ‘omics’, have allowed the quantification of DNA, RNA and protein levels leading to integrative analyses that essentially probe the central dogma along all of its constituent molecules. Evidence from these analyses suggest that mRNA abundances are at best a moderate proxy for proteins which are the main functional units of cells and thus closer to the phenotype. Cancer proteogenomic studies consider the ensemble of proteins, the so-called proteome, as the readout of the functional molecular phenotype to investigate its influence by upstream events, for example DNA copy number alterations. In typical proteogenomic studies, however, the identified proteome is a simplification of its actual composition, as they methodologically disregard events such as splicing, proteolytic cleavage and post-translational modifications that generate unique protein species – proteoforms. The scope of this thesis is to study the proteome diversity in terms of: a) the complex genetic background of three tumor types, i.e. breast cancer, childhood acute lymphoblastic leukemia and lung cancer, and b) the proteoform composition, describing a computational method for detecting protein species based on their distinct quantitative profiles. In Paper I, we present a proteogenomic landscape of 45 breast cancer samples representative of the five PAM50 intrinsic subtypes. We studied the effect of copy number alterations (CNA) on mRNA and protein levels, overlaying a public dataset of drug- perturbed protein degradation. In Paper II, we describe a proteogenomic analysis of 27 B-cell precursor acute lymphoblastic leukemia clinical samples that compares high hyperdiploid versus ETV6/RUNX1-positive cases. We examined the impact of the amplified chromosomes on mRNA and protein abundance, specifically the linear trend between the amplification level and the dosage effect. Moreover, we investigated mRNA-protein quantitative discrepancies with regard to post-transcriptional and post-translational effects such as mRNA/protein stability and miRNA targeting. In Paper III, we describe a proteogenomic cohort of 141 non-small cell lung cancer clinical samples. We used clustering methods to identify six distinct proteome-based subtypes. We integrated the protein abundances in pathways using protein-protein correlation networks, bioinformatically deconvoluted the immune composition and characterized the neoantigen burden. In Paper IV, we developed a pipeline for proteoform detection from bottom-up mass- spectrometry-based proteomics. Using an in-depth proteomics dataset of 18 cancer cell lines, we identified proteoforms related to splice variant peptides supported by RNA-seq data. This thesis adds on the previous literature of proteogenomic studies by analyzing the tumor proteome and its regulation along the flow of the central dogma of molecular biology. It is anticipated that some of these findings would lead to novel insights about tumor biology and set the stage for clinical applications to improve the current cancer patient care

Interplay between inflammation and calcification in cardiovascular diseases

Cardiovascular calcification has been linked to all-cause mortality and is a broadly adopted predictor of cardiovascular (CV) events. Rather than a mere by-product of the changing disease environment, calcification impacts actively the disease progression and pathogenesis as it predominates both in early- and late-stages, through mediating tissue biomechanical destabilisation and directly impacting tissue inflammation. However, its clinical contribution to the fate of the disease remains to be elucidated. Emerging body of evidence from both basic and clinical research has demonstrated the significance of the innate immune system in cardiovascular diseases (CVDs). Here, inflammation and calcification are engaged in a vicious cycle particularly at early-stages, whereas in advanced-lesions, large calcifications linked with suppressed inflammation and plaque stability. However, this interaction during disease progression remains largely elusive. The aim of this thesis is to investigate the interplay between inflammation and calcification in advanced atherosclerosis and calcific aortic valve disease (CAVD). Study I explores gene and protein expression signatures and biological pathways of advanced CAVD lesions in order to characterise the underlining mechanisms associated with the disease pathology. Multi-omics integration of overlapping transcriptome/proteome molecules with miRNAs, identified a unique CAVD-related protein-protein 3D layered interaction network. After addition of a metabolite layer, Alzheimer's disease (AD) was identified in the core of the gene-disease network. This study suggests a novel molecular CAVD network potentially linked to amyloid-like structures formation. Study II characterises osteomodulin (OMD) in the context of atherosclerosis, chronic kidney disease (CKD) and CAVD. Plasma OMD levels were correlated with markers of inflammation and bone turnover, with the protein being present in the calcified arterial media of patients with CKD stage 5. Circulating OMD levels were also associated with cardiac valve calcification in the same patients and its positive signal was detected in calcified valve leaflets by immunohistochemistry. In patients with carotid atherosclerosis, plasma OMD levels were increased in association with plaque calcification as assessed by computed tomography. Transcriptomic and proteomic data analysis showed that OMD expression was upregulated in atherosclerotic compared to non-atherosclerotic control arteries, and particularly in highly calcified plaques, where its expression correlated positively with markers of vascular smooth muscle cells (VSMCs) and osteoblasts. In vivo, OMD was enriched in VSMCs around calcified nodules in aortic media of nephrectomised rats and in plaques from ApoE-/- mice on warfarin. In vitro experiments revealed that exogenous administration of recombinant human OMD protein repressed the calcification process of VSMCs treated with phosphate by maintaining the VSMC contractile phenotype along with enriched extracellular matrix (ECM) organisation, thereby attenuating VSMC osteoblastic transformation. Study III analyses OMD expression in human carotid plaques and particularly its link with future CV events. Transcriptomic analysis revealed that OMD levels were increased in plaques from asymptomatic patients compared to symptomatic ones, with high levels being associated with fewer CV events in a follow-up analysis. Study IV investigates the link between mast cell (MC) activation and key features of human plaque vulnerability, and the role of MC in VSMC-mediated calcification. Integrative analyses from a large biobank of human plaques showed that MC activation is inversely associated with macrocalcification and positively with morphological parameters of plaque vulnerability. Bioinformatic analyses revealed associations of MCs with NK cells and other immune cells in plaques. Mechanistic in vitro experiments showed that calcification attenuated MC activation, while both active and resting MCs induced VSMC calcification and triggered their dedifferentiation towards a pro-inflammatory- and osteochondrocyte-like phenotype. Overall, this thesis demonstrates that the underlying mechanisms of CVD related to inflammation and calcification can be comprehensively characterised by integration of largescale multi-omics datasets along with cellular and molecular assays on one side, and disease specific biomarkers and advanced diagnostic imaging tools on the other. In summary, these studies not only indicate that advanced-calcification is a stabilising factor for plaque and disease progression but also, unveil novel insights into the cardiovascular calcification pathobiology, and offer promising biomarkers and new therapeutic avenues for further exploration

Proteo-Transcriptomic Dynamics of Cellular Response to HIV-1 Infection.

Throughout the HIV-1 replication cycle, complex host-pathogen interactions take place in the infected cell, leading to the production of new virions. The virus modulates the host cellular machinery in order to support its life cycle, while counteracting intracellular defense mechanisms. We investigated the dynamic host response to HIV-1 infection by systematically measuring transcriptomic, proteomic, and phosphoproteomic expression changes in infected and uninfected SupT1 CD4+ T cells at five time points of the viral replication process. By means of a Gaussian mixed-effects model implemented in the new R/Bioconductor package TMixClust, we clustered host genes based on their temporal expression patterns. We identified a proteo-transcriptomic gene expression signature of 388 host genes specific for HIV-1 replication. Comprehensive functional analyses of these genes confirmed the previously described roles of some of the genes and revealed novel key virus-host interactions affecting multiple molecular processes within the host cell, including signal transduction, metabolism, cell cycle, and immune system. The results of our analysis are accessible through a freely available, dedicated and user-friendly R/Shiny application, called PEACHi2.0. This resource constitutes a catalogue of dynamic host responses to HIV-1 infection that provides a basis for a more comprehensive understanding of virus-host interactions

Computational Systems Analysis on Polycystic Ovarian Syndrome (PCOS)

Complex diseases are caused by a combination of genetic and environmental factors. Unraveling the molecular pathways from the genetic factors that affect a phenotype is always difficult, but in the case of complex diseases, this is further complicated since genetic factors in affected individuals might be different. Polycystic ovarian syndrome (PCOS) is an example of a complex disease with limited molecular information. Recently, PCOS molecular omics data have increasingly appeared in many publications. We conduct extensive bioinformatics analyses on the data and perform strong integration of experimental and computational biology to understand its complex biological systems in examining multiple interacting genes and their products. PCOS involves networks of genes, and to understand them, those networks must be mapped. This approach has emerged as powerful tools for studying complex diseases and been coined as network biology. Network biology encompasses wide range of network types including those based on physical interactions between and among cellular components and those baised on similarity among patients or diseases. Each of these offers distinct biological clues that may help scientists transform their cellular parts list into insights about complex diseases. This chapter will discuss some computational analysis aspects on the omics studies that have been conducted in PCOS

A transcriptomic and molecular approach uncovering ASCL2 as a novel tumourigenic gene in breast cancer

Breast cancer is highly heterogeneous and is considered a collection of molecularly distinct tumour subtypes. Substantial efforts have been made to explore the gene expression profiles underlying the subtypes, and to elucidate possible markers associated with clinical outcomes. However, research in this area has been met with significant challenges and despite ongoing advancements in diagnostics and targeted therapeutics, incidence and mortality continues to rise. Thus, there is a need for greater molecular characterisation of breast tumours, to further understand the mechanistic roles of genes within their respective signalling pathways. With the advent of high-throughput technologies in transcriptomics, as well as the use of open databases and bioinformatics analysis tools, it is now possible to examine thousands of genes in parallel, generating an unprecedented amount of information. This provides a means for researchers to identify novel genes and targets from large volumes of gene expression data. However, the task of extracting clinically relevant results, is a prominent challenge. Therefore, the aim of this study was to use a streamlined in silico pipeline, integrated with in vitro methods to identify and functionally investigate a novel genetic marker demonstrating a key role in breast carcinogenesis. Gene expression profiles from breast cancer cell lines were obtained from public databases (Array Express and Gene Expression Omnibus). Data was filtered and subjected to an extreme variation analysis to generate a list of differentially expressed genes. Subsequently, multiple pathway analysis tools were used to identify a novel candidate gene for further investigation. Achaete-scute complex homolog 2 (ASCL2) is a transcription factor and Wnt-target gene, recognised as a regulator of stem cell identity and embryogenesis. Gene expression was validated in vitro by Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR), and to assess the tumourigenic potential of ASCL2, siRNA knockdown was performed; assays were employed to measure proliferation, wound-healing and apoptosis. Data mining of patient tumours obtained from the METABRIC study was also undertaken to ascertain the potential of ASCL2 as a prognostic indicator. This work utilised a systematic pipeline used by the wider scientific community for the identification of candidate genes from transcriptomic data. Differential expression of ASCL2 was observed across multiple breast cancer cell lines, with largest the expression seen in MCF7 cells. Although evidence did not support the usage of ASCL2 as a prognostic indicator in patient tumours, data integrated from multiple lines of investigation suggested that this gene may influence the migratory capacity of breast tumour cells, whilst exercising its tumourigeneic function via the Wnt signalling pathway in breast cancer. Thus, this potential novel role of ASCL2 in breast tumourigenesis highlights a prominent area for further exploration

From multi-omics approaches to personalized medicine in myocardial infarction

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI

Immunometabolic reprogramming during suppressive HIV-1 infection

Since the implementation of antiretroviral therapy (ART), infection with human immunodeficiency virus type-1 (HIV-1) has been transformed into a chronic lifelong condition. The main obstacle for a HIV-1 cure is the persistence of latently infected cells in viral reservoirs. The viral endurance can instigate detrimental changes on the function and activity of immune cells, creating a chronic inflammatory environment in people living with HIV-1 (PLWH) on successful long-term suppressive antiretroviral therapy (PLWHART). The continuous activation of immune cells may lead to an earlier onset of age-related diseases. Immunometabolism is an emerging field that studies how metabolic reprogramming has an impact on the activation, differentiation, and function of immune cells. Given that these underlying processes are likely to contribute to chronic inflammation in PLWH, the overall aim of this thesis was to evaluate how immunometabolism is reprogrammed during “controlled” HIV-1 infection, either by ART in PLWHART or in PLWH with natural control of infection, elite controllers (PLWHEC). In paper I, we integrated proteomic and transcriptomic data to investigate features distinct to the PLWHEC phenotype in a male cohort. We identified dysregulated hypoxia inducible factor (HIF) signalling and altered metabolism as unique characteristics of the male PLWHEC phenotype. As controlled HIV-1 infection still induce changes in the immune system we aimed to compare differences in the immune phenotype between PLWHEC and PLWHART and its relation to HIV-1 persistence in paper II. We identified a unique phenotype of decreased CCR6 expression on CD4+ and CD8+ T cells in PLWHEC compared to PLWHART and healthy controls (HC). Additionally, the CD4+CCR6+ cells exhibited a proteomic profile indicative of increased sensitivity towards cell death mechanisms in PLWHEC compared to PLWHART. A reduced proportion of integrated HIV-1 DNA in the reservoir of PLWHEC was found, although no difference in the amount of intact provirus. Continuing our evaluation of differences between PLWHEC and PLWHART we performed metabolo-transcriptomic analysis to understand and infer changes on a multisystem level in paper III. We detected a system level metabolic aberration mainly revolving around OXPHOS in PLWHART compared to PLWHEC. Using pharmacological modulation, we identified how this dysregulation of OXPHOS possibly affects HIV-1 reservoir dynamics and the immune senescence profile. Furthermore, to understand how HIV-1 chronicity affects long-lasting metabolic flexibility and adaptation we conducted plasma metabolomics to understand alterations during suppressive ART in a Swedish cohort in paper IV. We also aimed to characterize the cell populations that mainly contribute to changes in the metabolic environment. We detected aberrant energy metabolism in PLWHART, mainly revolving around the tricarboxylic acid cycle and amino acid synthesis. Cell-type specific evaluation showed that the main metabolic alterations occurred on monocytic cell populations, and that PLWHART exhibited dysregulated chemokine receptor expression of CCR2, CCR5, and CX3CR1 on myeloid cell lineages. In paper V, we wanted to evaluate if the altered metabolic environment was consistent on a global scale using two cohorts from low and middle-income countries (namely, Cameroon and India) using plasma metabolomics. We detected a dysregulation of amino acid metabolism and a switch towards glutaminolysis during long-term suppressive ART. In summary, the research covered in this thesis illuminates the importance of metabolic reprogramming during HIV-1 persistence in PLWH with controlled infection

Paving the Way:Contributions of Big Data to Apicomplexan and Kinetoplastid Research

In the age of big data an important question is how to ensure we make the most out of the resources we generate. In this review, we discuss the major methods used in Apicomplexan and Kinetoplastid research to produce big datasets and advance our understanding of Plasmodium, Toxoplasma, Cryptosporidium, Trypanosoma and Leishmania biology. We debate the benefits and limitations of the current technologies, and propose future advancements that may be key to improving our use of these techniques. Finally, we consider the difficulties the field faces when trying to make the most of the abundance of data that has already been, and will continue to be, generated