Estimating telomere length from whole genome sequencing data

This thesis details the development of two computational tools, Telomerecat and Parabam, as well as their applications to whole genome sequencing (WGS) data. Telomerecat is a tool for estimating telomere length from WGS data. The strength of Telomerecat lies in its applicability. This applicability is due to a number of advantages over previous attempts to estimate telomere length from WGS. Chief amongst these advantages is that it makes no assumption about the underlying chromosome count or size of the genome within input samples. This means that Telomerecat lends itself well to analysing cancer samples where such assumptions are unfounded. This also means it is applicable to non-human samples, a first for tools of its kind. Furthermore, a novel method for filtering reads derived from interstitial telomere sequences means that it does not rely on previously applied analyses, a source of bias. The other tool described in this thesis is Parabam. Parabam is the first tool of its kind to allow users to apply a function to all of the reads in sequence alignment files, in parallel. Furthermore, Parabam includes a novel method for iterating over index sorted sequence files as if they were name sorted. We provide evidence that Parabam is a quicker way to create complex subsets and statistics from sequence alignment files. In the latter half of the thesis we detail two applications of Telomerecat to large scale WGS projects. The first application, to the Prostate ICGC UK cohort, unveils hitherto uncovered associations between telomere length and previously identified molecular subtypes as well as cancer stage. In the second application, to the NIHR BioResource - Rare Disease cohort, we discover a previously unidentified variant in DKC1 that we propose is directly linked to short telomeres and an immunodeficient phenotype.Funded by Cancer Research UK PhD Studentshi

Genomic Evolution Shapes Prostate Cancer Disease Type

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression

VIP Enhances Phagocytosis of Fibrillar Beta-Amyloid by Microglia and Attenuates Amyloid Deposition in the Brain of APP/PS1 Mice

Vasoactive intestinal peptide (VIP) is a multifunctional neuropeptide with demonstrated immunosuppressive and neuroprotective activities. It has been shown to inhibit Amyloid beta (Aβ)-induced neurodegeneration by indirectly suppressing the production and release of a variety of inflammatory and neurotoxic factors by activated microglia. We demonstrated that VIP markedly increased microglial phagocytosis of fibrillar Aβ42 and that this enhanced phagocytotic activity depended on activation of the Protein kinase C (PKC) signaling pathway. In addition, VIP suppressed the release of tumor necrosis factor alpha (TNF-α) and nitric oxide(NO) from microglia activated by combined treatment with fibrillar Aβ42 and low dose interferon-γ (IFN-γ). We utilized an adenovirus-mediated gene delivery method to overexpress VIP constitutively in the hippocampus of APPswPS1 transgenic mice. The Aβ load was significantly reduced in the hippocampus of this animal model of Alzheimer's disease, possibly due to the accumulation and activation of cd11b-immunoactive microglial cells. The modulation of microglial activation, phagocytosis, and secretion by VIP is a promising therapeutic option for the treatment of Alzheimer's disease(AD)

Genomic evolution shapes prostate cancer disease type

H.R.F. was supported by a Cancer Research UK Programme Grant to Simon Tavaré (C14303/A17197), as, partially, was A.G.L. A.G.L. acknowledges the support of the University of St Andrews. A.G.L. and J.H.R.F. also acknowledge the support of the Cambridge Cancer Research Fund.The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Aalternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.Peer reviewe

Deciphering the genomic, epigenomic, and transcriptomic landscapes of pre-invasive lung cancer lesions.

The molecular alterations that occur in cells before cancer is manifest are largely uncharted. Lung carcinoma in situ (CIS) lesions are the pre-invasive precursor to squamous cell carcinoma. Although microscopically identical, their future is in equipoise, with half progressing to invasive cancer and half regressing or remaining static. The cellular basis of this clinical observation is unknown. Here, we profile the genomic, transcriptomic, and epigenomic landscape of CIS in a unique patient cohort with longitudinally monitored pre-invasive disease. Predictive modeling identifies which lesions will progress with remarkable accuracy. We identify progression-specific methylation changes on a background of widespread heterogeneity, alongside a strong chromosomal instability signature. We observed mutations and copy number changes characteristic of cancer and chart their emergence, offering a window into early carcinogenesis. We anticipate that this new understanding of cancer precursor biology will improve early detection, reduce overtreatment, and foster preventative therapies targeting early clonal events in lung cancer

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Publisher Correction: Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome