554 research outputs found

    High-accuracy prediction of colorectal cancer chemotherapy efficacy using machine learning applied to gene expression data

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    Introduction: FOLFOX and FOLFIRI chemotherapy are considered standard first-line treatment options for colorectal cancer (CRC). However, the criteria for selecting the appropriate treatments have not been thoroughly analyzed.Methods: A newly developed machine learning model was applied on several gene expression data from the public repository GEO database to identify molecular signatures predictive of efficacy of 5-FU based combination chemotherapy (FOLFOX and FOLFIRI) in patients with CRC. The model was trained using 5-fold cross validation and multiple feature selection methods including LASSO and VarSelRF methods. Random Forest and support vector machine classifiers were applied to evaluate the performance of the models.Results and Discussion: For the CRC GEO dataset samples from patients who received either FOLFOX or FOLFIRI, validation and test sets were >90% correctly classified (accuracy), with specificity and sensitivity ranging between 85%-95%. In the datasets used from the GEO database, 28.6% of patients who failed the treatment therapy they received are predicted to benefit from the alternative treatment. Analysis of the gene signature suggests the mechanistic difference between colorectal cancers that respond and those that do not respond to FOLFOX and FOLFIRI. Application of this machine learning approach could lead to improvements in treatment outcomes for patients with CRC and other cancers after additional appropriate clinical validation

    Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

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    ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK

    Examining interactions among SNPs that can explain the prognostic variability in colorectal cancer

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    Background: Colorectal cancer is a significant medical burden worldwide and in Newfoundland and Labrador. Examining the relationships of SNP interactions with survival outcomes can help identify new prognostic markers for this disease. Objectives: To examine associations between colorectal cancer survival outcomes and interactions of SNPs from MMP family and VEGF interactome genes using data-reduction methods. Methods: Two data-reduction software programs, Cox-MDR and GMDR 0.9, were applied to the data of patients from the Newfoundland Familial Colorectal Cancer Registry. Eight datasets were investigated: one for the MMP gene SNPs (201 SNPs), and seven for the VEGF interaction networks (total 1,517 SNPs). Significance of interaction models was assessed using permutation testing. Associations between significant interaction models and clinical outcomes were confirmed using multivariable regression methods. Results: For the MMP dataset two multi-SNP models and one single-SNP model were identified, while fifteen novel multi-SNP models and thirteen single-SNP models were identified for the VEGF interaction network datasets. All but one of these models were able to distinguish patients based on their outcome risk in multivariable regression models (p-value range: 0.03 – 2.2E-9). Conclusion: This research demonstrated that novel genetic interactions associated with outcome risk in colorectal cancer can be found using data-reduction methods. This proves the utility of these methods in prognostic research

    Understanding Metastasis Organotropism Patterns Through Within-cell and Between-cells Molecular Interaction Networks

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    Tese de mestrado, Bioquímica e Biomedicina, 2023, Universidade de Lisboa, Faculdade de CiênciasMetastasis is responsible for the majority of cancer-related deaths. It occurs when cells from a primary tumour disseminate and initiate new tumours at distant organ sites. Metastasizing cells have to exhibit especial characteristics that allow them to surpass all barriers and bottlenecks in their way to effective colonization. Ensuring survival throughout this process depends on how those cells communicate with the surrounding environments. Patterns of metastasis are remarkably variable between cancer types. In fact, distinct cancers seem to be predisposed to metastasize to specific organs, a feature known as metastasis organotropism. Our work is based on the hypothesis that organotropism can be partially explained by the extent of intercellular communication between metastasizing cells and cells in the secondary organ. Some proteins that establish intercellular interactions are tissue-specific and can be expressed in pre-cancerous tissue. Using RNA-seq data from non-diseased tissue, we built networks of intercellular proteinprotein interactions between cells from the primary cancer tissue and cells from a potential metastasis tissue. Controlling for other factors that affect organotropism, we found that sites where cancers metastasize more often tend to establish a larger number of intercellular interactions than sites with low incidence of metastasis. We detected 528 literature curated interactions that might play a role in metastasis formation and contribute to the observed differences in cellcell communication, some previously known to be related to cancer and/or metastasis. Finally, using a network of signalling pathways, we observed that proteins involved in metastasisassociated interactions and their closest neighbours in the network are enriched in cancer driver genes and biological processes linked to invasion and metastasis. In conclusion, we identified intercellular interactions and proteins that drive metastasis development and help explain organotropism. These insights might constitute new research and therapeutic opportunities to treat and prevent metastasis

    Investigating mechanisms and indicators of sensitivity to replication stress-targeting therapies in glioblastoma

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    Introduction Evidence suggests a subpopulation of treatment resistant glioblastoma (GBM) cancer stem cells (GSCs) is responsible for tumour recurrence, an almost universally deadly characteristic of this cancer of extreme unmet need. Current treatments fail to eradicate GSCs and novel GSC targeting therapies are a clinical priority. Elevated DNA replication stress (RS) in GSCs has been described, leading to constitutive DNA damage response activation and treatment resistance and targeting RS with combined ATR and PARP inhibition (CAiPi) has provided potent GSC cytotoxicity. Nevertheless, there are a relative lack of studies investigating the underlying mechanisms of response to CAiPi in GBM and a lack of robust transcriptional signatures or genomic biomarkers correlated with CAiPi response in GSCs. Aims This thesis aims to investigate RS as a targetable vulnerability of GSCs. It aims to achieve this by studying the mechanisms of sensitivity to inhibition of the RS response to inform transcriptional indicators of sensitivity. Lastly, it aims to investigate the feasibility of this therapeutic strategy in a preclinical model. Methods Paired GSC-enriched and GSC-depleted, differentiated (‘bulk’) populations, derived from resected GBM specimens, were maintained in serum-free, stemenriching conditions or differentiating conditions respectively. WGS and RNAseq were utilised to characterise the genomic and transcriptomic landscape of the cell line panel. Responses to CAiPi were assessed by clonogenic and cell viability assays and validated in a CD133 sorted population by neurosphere assay. Replication dynamics in paired GSC and bulk cells were investigated by a DNA fibre assay. Dysregulated S phase was analysed by quantification of 53BP1 nuclear bodies (53BP1NB), indicative of under-replication of the genome, and quantification of re-replicating cells by flow cytometry. Chromosomal instability was interrogated by quantification of chromatin bridges and micronuclei. Novel mechanistic discoveries prevalent in GSCs with potent CAiPi-sensitivity were used to curate a transcriptional marker of sensitivity for interrogation in GBM cell lines and in published clinical datasets. Lastly the feasibility of CAiPi was investigated in an in vivo preclinical model, assessing tolerability and tumour penetration. Results CAiPi was potently cytotoxic to a population of GSCs but highly heterogenous responses to CAiPi were observed across a panel of seven paired GSCs and bulk cells. Sensitivity was not predicted by elevated RS in GSCs or any previously defined biomarkers of RS or CAiPi sensitivity. Differential sensitivity was exploited for further investigations which identified transcriptional dysregulation of DNA replication, specifically in a CAiPi-responsive GSC line. Subsequent analysis of DNA replication identified PARPi-induced increase in origin firing, associated with PARP trapping. GSCs with this origin firing phenotype also exhibited an increase in both under-replicated DNA and re-replication in response to CAiPi, with an increase in chromosomal aberrations and instability. A curated transcriptional signature, based on mechanistic discoveries in CAiPisensitive GSCs, predicted GSC sensitivity and identified populations of GBM patients with poor survival who may respond to CAiPi treatment. In vivo studies demonstrated murine blood brain barrier (BBB) penetration of a PARPi and an ATRi with minimal toxicity, however optimal dosing and scheduling remains a challenge. Conclusions We propose that CAiPi-sensitivity is marked by loss of replication coordination leading to chromosomal damage as cells move through S phase. Additionally, we propose a model whereby under-replication and re-replication can occur due to spatial and temporal uncoupling during S phase. Targeting RS via CAiPi represents a promising therapeutic strategy for selectively targeting recurrence driving GSCs to improve clinical outcomes in GBM

    Novel tools for identification of oncogenic driver mutations

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    Genetic alterations contribute to the development and pathogenesis of several human cancers. These mutations accumulate in a cancer tissue over the course of time due to the instability of the cancer genome. Large-scale sequencing efforts have enabled identification of an abundance of these somatic mutations, and the amount of data is constantly increasing due to the improved accessibility of next-generation sequencing technologies. From this multitude of cancer-associated somatic mutations, a large majority are predicted to be inconsequential “passenger” mutations, (i.e., mutations which do not confer a selective growth advantage to the cancer cells); and only a handful have been validated as “driver” mutations (i.e., mutations playing a critical role in the development or maintenance of cancer). These driver mutations also function as predictive markers for survival, therapeutic efficacy, and often make the cancer cells susceptible to therapeutic intervention. Identification of driver mutations is an integral part of biomarker discovery in cancer research, and my thesis aimed to address this by developing a screening platform and a database. The in vitro Screen for Activating Mutations (iSCREAM) is a high-throughput screening workflow which was established with Epidermal Growth Factor Receptor (EGFR) as a model. The screen was validated by detection of known activating mutations like EGFR L858R. A previously known EGFR variant of unknown significance (VUS), EGFR A702V, was discovered in the screen and was functionally characterized to be an activating mutation. The iSCREAM screening methodology was further used to systematically study ERBB4, another gene in the EGFR family of receptor tyrosine kinases. We detected ERBB4 VUS R687K, and E715K in the screen and identify them as activating mutations. The ERBB4 mutations were characterized for their effect on ERBB4 phosphorylation, their sensitivity to various tyrosine kinase inhibitors, and their tumorigenicity was evaluated with in vivo allografts. The Database Of Recurrent Mutations (DORM), was prepared by analyzing a public registry of somatic mutations and preparing a catalog of the mutations identified from genome-wide studies to recapitulate the “real-world” frequency of all the recurrent (n > 1) somatic mutations. DORM allows limiting the scope of search to 38 tissue types and supports advanced queries using regular expressions. The easy-to-use database and its backend are written to be very responsive and fast in comparison to contemporary public cancer databases. Taken together, the findings and resources presented in this thesis establish grounds for further studies with other tyrosine kinases and potentially enable diversification into new niches.Uusia työkaluja syöpää aiheuttavien mutaatioiden tunnistamiseksi Geneettiset muutokset vaikuttavat useiden ihmisen syöpien syntyyn ja kehittymiseen. Syöpäkudokseen geenimutaatioita kertyy yhä enemmän ajan kuluessa syövän genomisen instabiliteetin vuoksi. Laajamittaisten sekvensointihankkeiden avulla on pystytty tunnistamaan paljon erilaisia somaattisia eli hankinnallisia mutaatioita ja sekvensointitulosten määrä kasvaa jatkuvasti uuden sukupolven sekvensointitekniikoiden (engl. next generation sequencing, NGS) paremman saatavuuden ansiosta. Näistä lukuisista syöpään liittyvistä somaattisista mutaatioista suurin osa on potilaan ennusteen kannalta merkityksettömiä "matkustajamutaatioita" (engl. passenger mutation) eli mutaatioita, jotka eivät anna valikoivaa kasvuetua syöpäsoluille. Vain muutamia somaattisia mutaatioita on validoitu "ajajamutaatioiksi" (engl. driver mutation) eli mutaatioiksi, joilla on kriittinen rooli syövän kehittymisessä tai ylläpitämisessä. Nämä ajajamutaatiot toimivat usein eloonjäämisen sekä hoidon tehon ennusteellisina markkereina ja usein myös herkistävät syöpäsoluja hoidoille. Ajajamutaatioiden tunnistaminen on olennainen osa syövän biomarkkereiden tutkimusta. Väitöskirjatyöni tavoitteena oli kehittää ajajamutaatioiden seulonta-alusta ja tietokanta. Aktivoivien mutaatioiden in vitro -seulonta (engl. in vitro Screen for Activating Mutations, iSCREAM) on tehoseulontamenetelmä, jonka kehittämistyössä käytettiin mallina epidermaalista kasvutekijäreseptoria (EGFR) koodaavaa geeniä iSCREAM-seulonnalla tunnistettiin jo tunnettuja aktivoivia EGFR-mutaatioita, kuten L858R, mikä validoi menetelmän toimivuuden. Seulontamenetelmällä tunnistettiin ja karakterisoitiin myös uusi EGFR-geenin aktivoiva mutaatio, A702V, jonka oletettu toimintamekanismi selvitettiin. iSCREAM-seulontamenetelmää hyödynnettiin tässä työssä myös EGFR-reseptorityrosiinikinaasiperheen toisen geenin, ERBB4-geenin, systemaattiseen tutkimiseen, jonka avulla löydettiin uusina aktivoivina mutaatioina ERBB4 R687K ja E715K. Näiden ERBB4-mutaatioiden vaikutusta ERBB4:n fosforylaatioon ja lääkeherkkyyteen erilaisille tyrosiinikinaasiestäjille karakterisoitiin, ja niiden tuumorigeenisyys validoitiin in vivo -allografteissa. Toistuvien mutaatioiden tietokanta (engl. Database Of Recurrent Mutations, DORM) luotiin analysoimalla somaattisten mutaatioiden julkista rekisteriä ja laatimalla luettelo genominlaajuisissa tutkimuksissa tunnistetuista mutaatioista, jotta kaikkien toistuvien (n > 1) somaattisten mutaatioiden "todellinen" esiintymistiheys voitaisiin laskea. DORM mahdollistaa haun rajoittamisen 38:aan kudostyyppiin ja tukee edistyneempiä kyselyjä säännöllisten lausekkeiden (engl. regular expression) avulla. Helppokäyttöinen tietokanta ja sen taustajärjestelmä kehitettiin hyvin reagoivaksi ja nopeaksi nykyisiin julkisiin syöpätietokantoihin verrattuna. Tässä työssä esitetyt havainnot ja resurssit luovat yhdessä perustan jatkotutkimuksille muilla tyrosiinikinaaseilla ja ovat mahdollisesti laajennettavissa muillekin tutkimusalueille

    Alternative pre-mRNA splicing as a source of cancer neoepitopes

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    Robust identification of neoepitopes is crucial for the efficacy and safety of immunotherapy, the most promising treatment strategy for several cancer types. Current approaches have provided limited numbers of immunogenic and tumor-specific targets, thus preventing the broad application of targeted immunotherapy. Here, the focus on somatic mutation-derived neoantigens often overlooks possible neoepitopes originating from mRNA processing events. A potential new source of tumor-specific peptides is alternative pre-mRNA splicing, a widely dysregulated process in several cancer subtypes. However, there is limited insight regarding the potential of alternative splicing to generate peptides that are also presented on the cell surface. Thus, in this thesis, I aimed to investigate how perturbation of the splicing machinery contributes to the neoepitope repertoire in tumor cells. To explore alternative splicing-derived neoantigens, I performed immunopeptidomics to determine the HLA-I ligandome of wild-type RPE-1 cells and RPE-1 cell lines carrying common cancer mutations. To facilitate the presentation of alternative splicing-derived neoepitopes, I treated these cell lines with the splicing inhibitor GEX1A. I then performed HLA-I immunopurification to recover HLA-I-bound peptides of these cells, followed by peptide identification through mass spectrometry. To be able to identify non-canonical peptides from mass spectra, I generated sample-specific custom reference databases based on matching RNA-seq data. This strategy allowed me to identify more than 8,000 unique HLA-I-presented peptides per cell line. In parallel, I specifically identified neoepitopes originating from aberrant alternative splice events. By performing differential splicing analysis between the various conditions, I obtained thousands of differentially regulated splice junction events. Particularly in cells treated with the splicing inhibitor GEX1A, alternative splicing analysis revealed numerous novel, non-annotated splice events. To examine whether these dysregulated events were translated into novel peptides, I subsequently mapped the candidate peptides to the differential splice events. With this strategy, I was able to identify and validate several alternative splicing-derived neoepitope candidates that exhibited a high immunogenic potential in in vivo immunization assays. In conclusion, my work demonstrates that pharmacological modulation of the splicing machinery has the potential to promote the presentation of neoepitopes derived from alternative splice variants. These findings have potential implications for immunotherapy of cancer types with low tumor mutational burden. Exploring the splicing-derived neopeptidome could reveal novel therapeutic targets and serve as a predictive biomarker for response to immune checkpoint blockade therapy

    An investigation of the tumour-derived Glasgow Microenvironment Score and survival in patients with operable colorectal cancer

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    Background: Colorectal cancer poses a significant disease burden worldwide, remaining the 2nd cause of cancer related death. The TNM staging system, whilst being constantly improved, is limited by its assessment of the tumour alone and not the host. Whereas, as the knowledge base grows regarding of the consensus molecular subtypes in colorectal cancer and the different microscopic phenotypes that these may produce, further disease biomarkers are required that reflect this understanding. The Glasgow Microenvironment Score (GMS) was developed by combining assessment of two phenotypic assessments of the colorectal cancer (CRC) microenvironment, both of which have been shown to have independent prognostic significance: the immune phenotype (assessed by Klintrup-Mäkinen grade (KM)) and the mesenchymal phenotype, assessed by tumour stroma percentage (TSP). However, further understanding of the pathological mechanisms underlying these phenotypic features is required. Methods: The present thesis examines the prognostic utility of the GMS in several Scottish cohorts in order to validate the score in independent patient cohorts and also to assess its utility in detecting disease recurrence and understand its relevance in the context of current chemotherapy. Results: In chapter 3, associations between markers of Epithelial-mesenchymal Transition (EMT) and the Glasgow Microenvironment Score were assessed. GMS 0 was associated with lower membrane Fascin and also lower membrane and nuclear B-catenin. GMS 1 was associated with high cytoplasmic Fascin, whereas GMS 2 was associated with higher nuclear B-catenin, a hallmark of EMT. In Chapter 4, several cohorts were examined in order to validate the GMS in independent cohorts, including the patients from the Scot chemotherapy trial (TransScot cohort). The GMS was found to stratify survival in all of these cohorts. Furthermore, GMS 2 was found to be a risk factor for poor survival in an otherwise low-risk group. In Chapter 5, the role of GMS in predicting disease recurrence patterns was assessed both for CRC as a whole and also in colon and rectal cancer individually. GMS independently predicted recurrence at any location for CRC and also for rectal cancers, although in colon cancers alone, this was not independent. GMS was also able to predict local recurrence, but not independently of T-stage and N-stage. GMS 2 had the highest risk for recurrence and therefore enhanced surveillance in this subgroup is recommended. Associations between GMS and chemotherapy was assessed in Chapter 6. Standard chemotherapy did not appear to be particularly effective against GMS 2 tumours, although this data had its limitations and requires to be assessed in other cohorts. In the TransScot cohort, survival of patients with GMS 0 was better with FOLFOX compared with CAPOX. Finally, in Chapter 7, the role of PDL1 (CD274) in prognosis of colorectal cancer and also in terms of response to immunotherapy in current trials. Whilst the expression of CD274 on immune cells was associated with good prognosis, expression on tumour tissue was equivocal in terms of survival outcomes. There is insufficient evidence regarding CD274 as a marker of response to immunotherapy in CRC and this needs to be addressed moving forward. Conclusions: GMS has been validated in independent patient cohorts and shown to stratify survival as in the original cohort. GMS 2 has utility both in identifying patients at high-risk of disease recurrence, but also potentially in selecting patients for specific chemotherapy regimen

    Systems biology of degenerative diseases

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