Bereavement outcomes: a quantitative survey identifying risk factors in family carers bereaved through cancer.

Background: Enabling patients to die in their preferred place is important but achieving preferred place of death may increase the informal carer’s risk into bereavement. Aim: to determine risk factors of family carers bereaved through cancer in Northern Ireland. Design: These results form part of a larger QUALYCARE-NI study which used postal questionnaires to capture quantitative data on carer’s bereavement scores using the Texas Revised Inventory of Grief. Setting/participants: Participants were individuals who: registered the death of a person between 1st December 2011 and 31st May 2012; where cancer (defined by ICD10 codes C00-D48) was the primary cause; where the deceased was over 18 years of age and death occurred at home, hospice, nursing home or hospital in Northern Ireland. Participants were approached in confidence by the Demography and Methodology Branch of the Northern Ireland Statistics and Research Agency. Those wishing to decline participation were invited to return the reply slip. Non-responders received a second questionnaire six weeks after initial invitation. Results indicated that risk factors positively influencing bereavement outcomes included patients having no preference for place of death and carers remaining in employment pre or post bereavement. In contrast, patients dying in hospital, carers stopping work, being of lower socio-economic status and close kinship to the deceased negatively impacted on bereavement scores. Family carers should be adequately supported to continue in employment; priority should be given to assessing the financial needs of families from lower socio-economic areas; and bereavement support should focus on close relatives of the deceased.

The role of glycans in the development and progression of prostate cancer

Prostate cancer is a unique and heterogeneous disease. Currently, a major unmet clinical need exists to develop biomarkers that enable indolent disease to be distinguished from aggressive disease. The prostate is an abundant secretor of glycoproteins of all types, and alterations in glycans are, therefore, attractive as potential biomarkers and therapeutic targets. Despite progress over the past decade in profiling the genome and proteome, the prostate cancer glycoproteome remains relatively understudied. A wide range of alterations in the glycoproteins on prostate cancer cells can occur, including increased sialylation and fucosylation, increased O-β-N-acetylglucosamine (GlcNAc) conjugation, the emergence of cryptic and high-mannose N-glycans and alterations to proteoglycans. Glycosylation can alter protein function and has a key role in many important biological processes in cancer including cell adhesion, migration, interactions with the cell matrix, immune surveillance, cell signalling and cellular metabolism; altered glycosylation in prostate cancer might modify some, or all of these processes. In the past three years, powerful tools such as glycosylation-specific antibodies and glycosylation gene signatures have been developed, which enable detailed analyses of changes in glycosylation. Thus, emerging data on these often overlooked modifications have the potential to improve risk stratification and therapeutic strategies in patients with prostate cancer.

The Importance of DNA methylation in Prostate Cancer development

After briefly reviewing the nature of DNA methylation, its general role in cancer and the tools available to interrogate it, we consider the literature surrounding DNA methylation as relating to prostate cancer. Specific consideration is given to recurrent alterations. A list of frequently reported genes is synthesised from seventeen studies that have reported on methylation changes in malignant prostate tissue, and we chart the timing of those changes in the diseases history through amalgamation of several previously published data sets. We also review associations with genetic alterations and hormone signalling, before the practicalities of investigating prostate cancer methylation using cell lines are assessed. We conclude by outlining the interplay between DNA methylation and prostate cancer metabolism and their regulation by Androgen Receptor, with a specific discussion of the mitochondria and their associations with DNA methylation.

Stratified analysis reveals chemokine-like factor (CKLF) as a potential prognostic marker in the MSI-immune consensus molecular subtype CMS1 of colorectal cancer

The Colorectal Cancer (CRC) Subtyping Consortium (CRCSC) recently published four consensus molecular subtypes (CMS’s) representing the underlying biology in CRC. The Microsatellite Instable (MSI) immune group, CMS1, has a favorable prognosis in early stage disease, but paradoxically has the worst prognosis following relapse, suggesting the presence of factors enabling neoplastic cells to circumvent this immune response. To identify the genes influencing subsequent poor prognosis in CMS1, we analyzed this subtype, centered on risk of relapse.
In a cohort of early stage colon cancer (n=460), we examined, in silico, changes in gene expression within the CMS1 subtype and demonstrated for the first time the favorable prognostic value of chemokine-like factor (CKLF) gene expression in the adjuvant disease setting [HR=0.18, CI=0.04-0.89]. In addition, using transcription profiles originating from cell sorted CRC tumors, we delineated the source of CKLF transcription within the colorectal tumor microenvironment to the leukocyte component of these tumors. Further to this, we confirmed that CKLF gene expression is confined to distinct immune subsets in whole blood samples and primary cell lines, highlighting CKLF as a potential immune cell-derived factor promoting tumor immune-surveillance of nascent neoplastic cells, particularly in CMS1 tumors. Building on the recently reported CRCSC data, we provide compelling evidence that leukocyte-infiltrate derived CKLF expression is a candidate biomarker of favorable prognosis, specifically in MSI-immune stage II/III disease.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

Is it time for standards and a common data exchange format for digital image analysis?

Digital image analysis is at a crossroads. While the technology has made great strides over the past few decades, there is an urgent need for image analysis to inform the next wave of large scale tissue biomarker discovery studies in cancer. Drawing parallels from the growth of next generation sequencing, this presentation will consider the case for a common language or standard format for storing and communicating digital image analysis data. In this context, image analysis data comprises more than simply an image with markups and attached key-value pair metrics. The desire to objectively benchmark competing platforms or a push for data to be deposited to public repositories much like genomics data may drive the need for a standard that also encompasses granular, cell-by-cell data.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

Digoxin use after diagnosis of colorectal cancer and survival: a population-based cohort study.

BACKGROUND:

Digoxin has been shown to affect a number of pathways that are of relevance to cancer, and its use has been associated with increased risks of breast and uterus cancer and, more recently, a 40% increase in colorectal cancer risk. These findings raise questions about the safety of digoxin use in colorectal cancer patients, and, therefore, we investigated whether digoxin use after colorectal cancer diagnosis increased the risk of colorectal cancer-specific mortality.

METHODS:

A cohort of 10,357 colorectal cancer patients newly diagnosed from 1998 to 2009 was identified from English cancer registries and linked to the UK Clinical Practice Research Datalink (to provide digoxin and other prescription records) and to the Office of National Statistics mortality data (to identify 2,724 colorectal cancer-specific deaths). Using time-dependent Cox regression models, unadjusted and adjusted HRs and 95% confidence intervals (CI) were calculated for the association between postdiagnostic exposure to digoxin and colorectal cancer-specific mortality.

RESULTS:

Overall, 682 (6%) colorectal cancer patients used digoxin after diagnosis. Digoxin use was associated with a small increase in colorectal cancer-specific mortality before adjustment (HR, 1.25; 95% CI, 1.07-1.46), but after adjustment for confounders, the association was attenuated (adjusted HR, 1.10; 95% CI, 0.91-1.34) and there was no evidence of a dose response.

CONCLUSIONS:

In this large population-based colorectal cancer cohort, there was little evidence of an increase in colorectal cancer-specific mortality with digoxin use after diagnosis.

IMPACT:

These results provide some reassurance that digoxin use is safe in colorectal cancer patients.

Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

Perceived positive and negative consequences after surviving cancer and their relation to quality of life

Surviving childhood cancer has multiple implications on both physical and psychological domains of the individual. However, its study and possible effects on health-related quality of life (HRQoL) outcomes of adolescent survivors has been understudied. The objective of this study was twofold; to assess positive and negative cancer-related consequences (psychosocial and physical) in a sample of adolescent cancer survivors and to explore their relationship with HRQoL outcomes. Forty-one participants answered two questions about positive and negative consequences in the aftermath of cancer and filled in the KIDSCREEN-52 self-reported version. Data were analysed using mixed methods approach. 87.8% of the sample identified positive consequences and 63.4% negative consequences in survivorship. Four positive categories and five negative categories with regard to cancer-related consequences were found. Changed perspectives in life narratives seem to be the positive consequence more related to HRQoL (physical well-being, mood & emotions, autonomy, social support & peers), followed by useful life experience (physical well-being, autonomy, social support & peers). Psychological impact was the most referred negative consequence with a significant detrimental effect on social support and peers HRQoL dimension. Even if the majority of survivors reported benefit finding in the aftermath of cancer, concomitant positive and negative consequences have been found. However, findings only reveal a significant relationship between positive narratives and HRQoL, and negative consequences do not seem to have a significant influence on overall HRQoL in survivorship.

Novel therapeutic targets in colon cancer

Tese de doutoramento, Farmácia (Biologia Celular e Molecular), Universidade de Lisboa, Faculdade de Farmácia, 2016

Cancer-associated fibroblasts in brain metastases

Tese de mestrado. Oncobiologia, Faculdade de Medicina, Universidade de Lisboa, 2015

Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Using a whole person approach to support people with cancer: a longitudinal, mixed methods service evaluation

Introduction: Improved models of care are needed to meet all the support needs of people with cancer, which encompass psychological, emotional, physical, spiritual, sexual, occupational, social and existential needs. The aim of this paper is to (1) evaluate short and long-term impacts of using a whole person approach to support people with cancer on the Living Well with the Impact of Cancer Course (LWC); (2) use these data to inform strategic decisions about future service provision at Penny Brohn UK. Methods: Longitudinal mixed-methods service evaluation (n=135). Data collected included health related quality of life (HRQoL) (FACIT-SpEx); Concerns (types and severity - MYCaW); lifestyle behaviour (bespoke questionnaire) and participants’ experiences over 12 months post course. Results: Statistically and clinically significant improvements from baseline - 12 months in severity of MYCaW Concerns (n=64; p<0.000) and mean total HRQoL (n=66; p<0.000). The majority of MYCaW concerns were ‘psychological and emotional’ and about participants’ wellbeing. Spiritual, emotional and functional wellbeing contributed most to HRQoL improvements at 12 months. Barriers to maintaining healthy lifestyle changes included lack of support from family and friends, time constraints, and returning to work. 3-6 months post-course was identified as the time when more support was most likely to be needed. Conclusions: Using a whole person approach for the LWC enabled the needs of participants to be met, and statistically and clinically significant improvements in HRQoL and MYCaW Concerns were reported. Qualitative data analysis explored how experiencing whole person support enabled participants to make and sustain healthy lifestyle changes associated with improved survivorship. Barriers experienced to making health behaviour change were also identified. These data then informed wider and more person-centred clinical provision to increase the maintenance of positive long-term behaviour changes. Comparison of whole person approaches to cancer treatment and support and standard care are now urgently needed.

Modelo de data mining para detecção de tumores em exames de rastreio

Dissertação para obtenção do grau de Mestre em Engenharia Informática