Using Real-World Data to Guide Ustekinumab Dosing Strategies for Psoriasis: A Prospective Pharmacokinetic-Pharmacodynamic Study.

Variation in response to biologic therapy for inflammatory diseases, such as psoriasis, is partly driven by variation in drug exposure. Real-world psoriasis data were used to develop a pharmacokinetic/pharmacodynamic (PK/PD) model for the first-line therapeutic antibody ustekinumab. The impact of differing dosing strategies on response was explored. Data were collected from a UK prospective multicenter observational cohort (491 patients on ustekinumab monotherapy, drug levels, and anti-drug antibody measurements on 797 serum samples, 1,590 measurements of Psoriasis Area Severity Index (PASI)). Ustekinumab PKs were described with a linear one-compartment model. A maximum effect (Emax ) model inhibited progression of psoriatic skin lesions in the turnover PD mechanism describing PASI evolution while on treatment. A mixture model on half-maximal effective concentration identified a potential nonresponder group, with simulations suggesting that, in future, the model could be incorporated into a Bayesian therapeutic drug monitoring "dashboard" to individualize dosing and improve treatment outcomes

SigFuge: Single gene clustering of RNA-seq reveals differential isoform usage among cancer samples

High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor

Stratified Pathway Analysis to Identify Gene Sets Associated with Oral Contraceptive Use and Breast Cancer

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Combined epithelial marker analysis of tumour budding in stage II colorectal cancer

Tumour budding predicts survival of stage II colorectal cancer (CRC) and has been suggested to be associated with epithelial‐to‐mesenchymal transition (EMT). However, the underlying molecular changes of tumour budding remain poorly understood. Here, we performed multiplex immunohistochemistry (mIHC) to phenotypically profile tumours using known EMT‐associated markers: E‐cadherin (adherence junctions), integrin β4 (ITGB4; basement membrane), ZO‐1 (tight junctions), and pan‐cytokeratin. A subpopulation of patients showed high ITGB4 expression in tumour buds, and this coincided with a switch of ITGB4 localisation from basal membrane of intact epithelium to the cytoplasm of budding cells. Digital image analysis revealed that tumour budding with high ITGB4 expression in tissue microarray (TMA) cores correlated with tumour budding assessed from H&E whole‐sections and independently predicted poor disease‐specific survival in two independent stage II CRC cohorts (hazard ratio (HR) =4 .50 (95% CI=1.50–13.5), n=232; HR=3.52 (95% CI=1.30‐9.53), n=72). Furthermore, digitally obtained ITGB4‐high bud count in random TMA cores associated better with survival outcome than visual tumour bud count in corresponding H&E stained samples. In summary, the mIHC‐based phenotypic profiling of human tumour tissue shows strong potential for the molecular characterisation of tumour biology and for the discovery of novel prognostic biomarkers.</p

Mechanics of Phenotypic Aging Trajectories in C. elegans and Humans

Overall, my dissertation integrates longitudinal measurements of physiology to investigate the aging process. In the first half, I examine the surprising and largely unexplained degree of variation in lifespan within even homogeneous populations. I sought to understand how physiological aging differs between long- and short-lived individuals within a population of genetically identical C. elegans reared in a homogeneous environment. Using a novel culture apparatus, I longitudinally monitored aspects of aging physiology across a large population of isolated individuals. Aggregating several measures into an overall estimate of senescence, I find that long- and short-lived individuals start adulthood on an equal physiological footing. However, longer-lived individuals then experience slower declines in function, but spend a disproportionately large portion of life in poor physiological health. Indeed, the period of early-life good health is much less variable than the period of late-life advanced senescence, which I conclude to be a more plastic phase of life. In the second half, I show that simple physiological measurements have broader lifespan-predictive value than previously believed and that incorporating information from multiple time points can significantly increase that predictive capacity. Using longitudinal data from a cohort of 1349 human participants in the Framingham Heart Study, I show that as early as 28–38 years of age, almost 10% of variation in future lifespan can be predicted from simple clinical parameters. Further, different clinical measurements are predictive of lifespan in different age regimes. Moreover, I find that several blood glucose and blood pressure are best considered as measures of a rate of “damage accrual”, such that total historical exposure, rather than current measurement values, is the most relevant risk factor (as with pack-years of cigarette smoking). Together, this work has established the physiological basis of variation in longevity within an isogenic population of C. elegans and extended our ability to predict mortality from basic clinical measurements in humans

Keratin 5 overexpression is associated with serous ovarian cancer recurrence and chemotherapy resistance

This study investigated the clinical significance of keratin 5 and 6 expression in serous ovarian cancer progression and chemotherapy resistance. KRT5 and KRT6 (KRT6A, KRT6B & KRT6C) gene expression was assessed in publically available serous ovarian cancer data sets, ovarian cancer cell lines and primary serous ovarian cancer cells. Monoclonal antibodies which detect both K5/6 or only K5 were used to assess protein expression in ovarian cancer cell lines and a cohort of high grade serous ovarian carcinomas at surgery (n = 117) and after neoadjuvant chemotherapy (n = 21). Survival analyses showed that high KRT5 mRNA in stage III/IV serous ovarian cancers was significantly associated with reduced progression-free (HR 1.38, P < 0.0001) and overall survival (HR 1.28, P = 0.013) whilst high KRT6 mRNA was only associated with reduced progression-free survival (HR 1.2, P = 0.031). Both high K5/6 (≥ 10%, HR 1.78 95% CI; 1.03−2.65, P = 0.017) and high K5 (≥ 10%, HR 1.90, 95% CI; 1.12−3.19, P = 0.017) were associated with an increased risk of disease recurrence. KRT5 but not KRT6C mRNA expression was increased in chemotherapy resistant primary serous ovarian cancer cells compared to chemotherapy sensitive cells. The proportion of serous ovarian carcinomas with high K5/6 or high K5 immunostaining was significantly increased following neoadjuvant chemotherapy. K5 can be used to predict serous ovarian cancer prognosis and identify cancer cells that are resistant to chemotherapy. Developing strategies to target K5 may therefore improve serous ovarian cancer survival.Carmela Ricciardelli, Noor A Lokman, Carmen E Pyragius, Miranda P Ween, Anne M Macpherson, Andrew Ruszkiewicz, Peter Hoffmann, Martin K Oehle