A novel stratification framework for predicting outcome in patients with prostate cancer

Background: Unsupervised learning methods, such as Hierarchical Cluster Analysis, are commonly used for the analysis of genomic platform data. Unfortunately, such approaches ignore the well-documented heterogeneous composition of prostate cancer samples. Our aim is to use more sophisticated analytical approaches to deconvolute the structure of prostate cancer transcriptome data, providing novel clinically actionable information for this disease. Methods: We apply an unsupervised model called Latent Process Decomposition (LPD), which can handle heterogeneity within individual cancer samples, to genome-wide expression data from eight prostate cancer clinical series, including 1,785 malignant samples with the clinical endpoints of PSA failure and metastasis. Results: We show that PSA failure is correlated with the level of an expression signature called DESNT (HR = 1.52, 95% CI = [1.36, 1.7], P = 9.0 × 10 −14, Cox model), and that patients with a majority DESNT signature have an increased metastatic risk (X 2 test, P = 0.0017, and P = 0.0019). In addition, we develop a stratification framework that incorporates DESNT and identifies three novel molecular subtypes of prostate cancer. Conclusions: These results highlight the importance of using more complex approaches for the analysis of genomic data, may assist drug targeting, and have allowed the construction of a nomogram combining DESNT with other clinical factors for use in clinical management

IL7 genetic variation and toxicity to immune checkpoint blockade in patients with melanoma

Treatment with immune checkpoint blockade (ICB) frequently triggers immune-related adverse events (irAEs), causing considerable morbidity. In 214 patients receiving ICB for melanoma, we observed increased severe irAE risk in minor allele carriers of rs16906115, intronic to IL7. We found that rs16906115 forms a B cell-specific expression quantitative trait locus (eQTL) to IL7 in patients. Patients carrying the risk allele demonstrate increased pre-treatment B cell IL7 expression, which independently associates with irAE risk, divergent immunoglobulin expression and more B cell receptor mutations. Consistent with the role of IL-7 in T cell development, risk allele carriers have distinct ICB-induced CD8+ T cell subset responses, skewing of T cell clonality and greater proportional repertoire occupancy by large clones. Finally, analysis of TCGA data suggests that risk allele carriers independently have improved melanoma survival. These observations highlight key roles for B cells and IL-7 in both ICB response and toxicity and clinical outcomes in melanoma

DESNT: A Poor Prognosis Category of Human Prostate Cancer.

BACKGROUND: A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes. OBJECTIVE: To devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches. DESIGN, SETTING, AND PARTICIPANTS: Our analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biochemical failure was assessed using log-rank analysis and Cox regression analysis. RESULTS AND LIMITATIONS: Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p=2.65×10-5, p=4.28×10-5, and p=2.98×10-8). When these three datasets were combined the independent predictive value of DESNT membership was p=1.61×10-7 compared with p=1.00×10-5 for Gleason sum. A limitation of the study is that only prediction of prostate-specific antigen failure was examined. CONCLUSIONS: Our results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease. PATIENT SUMMARY: Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.This work was funded by the Bob Champion Cancer Trust, The Masonic Charitable Foundation successor to The Grand Charity, The King Family, and The University of East Anglia. We acknowledge support from Movember, from Prostate Cancer UK, Callum Barton, and from The Andy Ripley Memorial Fund. The research presented in this paper was carried out on the High Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia. Cancer Research UK Grant 10047 funded the generation of the prostate CancerMap expression microarray dataset. We would like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge UK

Characterising peripheral responses to immune checkpoint inhibitors

The introduction of immune checkpoint blockade (ICB) therapy for metastatic melanoma (MM) has dramatically improved survival in this patient group. However, only some patients experience durable clinical response, and many will develop immune-related adverse events (irAEs). The identification of predictive biomarkers which can be assessed in a biopsy-free manner may facilitate early detection of non-responders and optimal targeting of treatment. There is emerging evidence to show that the circulating monocyte population has a prognostic and predictive role in the context of ICB, but this has yet to be fully characterised. Circulating-cell free DNA (cfDNA) is derived predominantly from leukocytes, but in patients with cancer may comprise circulating tumour DNA (ctDNA). Assessment of epigenetic cfDNA profiles may provide tumour profiling and reflect immune responses as a ‘liquid biopsy’. Although epigenetic tumour profiles have diagnostic and prognostic utility across multiple cancer types, epigenetic cfDNA profiles in MM and following ICB are not yet characterised. In this thesis I dissect both circulating myeloid and epigenetic cfDNA profiles in MM patients. Firstly, I explore MM-associated monocyte transcriptomic profiles with bulk RNA sequencing (RNA-seq), characterising on-treatment modulation and association with clinical response. I then use scRNA-seq to explore the transcriptional heterogeneity of the peripheral monocyte compartment, and describe monocyte subset-wise responses to ICB. Lastly, I characterise epigenetic cfDNA profiles in this cohort, revealing distinct 5-hydroxymethylcytosine (5hmC) and 5-methylcytosine (5mC) cfDNA profiles in MM and following ICB. In this thesis I present novel findings regarding peripheral myeloid and epigenetic cfDNA responses to ICB and demonstrate that these profiles may have potential diagnostic and predictive clinical utility

Primary Clear Cell Microcystic Adenoma of the Sinonasal Cavity: Pathological or Fortuitous Association?

Primary clear cell microcystic adenoma of the sinonasal cavity is rare. It has previously been described only as a VHL-associated tumour. Von Hippel-Lindau (VHL) syndrome is an inherited cancer syndrome characterised by an elevated risk of neoplasia including clear cell renal cell carcinoma (ccRCC), haemangioblastoma, and phaeochromocytoma. We describe the second reported case of a primary clear cell microcystic adenoma of the sinonasal cavity. The 39-year-old patient with VHL syndrome had previously undergone resection and ablation of ccRCC. He presented with epistaxis. Imaging demonstrated a mass in the ethmoid sinus. Initial clinical suspicion was of metastatic ccRCC. However, tumour morphology and immunoprofile were distinct from the previous ccRCC and supported a diagnosis of primary microcystic adenoma. Analysis of DNA extracted from sinonasal tumour tissue did not show loss of the wild-type allele at the VHL locus. Although this did not support tumour association with VHL disease, it was not possible to look for a loss-of-function mutation. The association of primary microcystic adenoma of the sinonasal cavity with VHL disease remains speculative. These lesions are benign but are likely to require regular surveillance. Such tumours may require repeated surgical excision

Impact of the transition to digital pathology in a clinical setting on histopathologists in training: experiences and perceived challenges within a UK training region

Aims: With increasing utility of digital pathology (DP), it is important to consider the experiences of histopathologists in training, particularly in view of the varied access to DP across a training region and the consequent need to remain competent in reporting on glass slides (GS), which is also relevant for the Fellowship of the Royal College of Pathologists part 2 examination. Understanding the impact of DP on training is limited but could aid development of guidance to support the transition. We sought to investigate the perceptions of histopathologists in training around the introduction of DP for clinical diagnosis within a training region, and the potential training benefits and challenges. Methods: An anonymous online survey was circulated to 24 histopathologists in training within a UK training region, including a hospital which has been fully digitised since summer 2020. Results: 19 of 24 histopathologists in training responded (79%). The results indicate that DP offers many benefits to training, including ease of access to cases to enhance individual learning and teaching in general. Utilisation of DP for diagnosis appears variable; almost half of the (10 of 19) respondents with DP experience using it only for ancillary purposes such as measurements, reporting varying levels of confidence in using DP clinically. For those yet to undergo the transition, there was a perceived anxiety regarding digital reporting despite experience with DP in other contexts. Conclusions: The survey evidences the need for provision of training and support for histopathologists in training during the transition to DP, and for consideration of their need to maintain competence and confidence with GS reporting

Immune Checkpoint Blockade sensitivity and Progression-Free Survival associates with baseline CD8+ T cell clone size and cytotoxicity

This data forms the key input files for the analysis of single cell data as outlined in the publication titled: Immune Checkpoint Blockade sensitivity and Progression-Free Survival associates with baseline CD8+ T cell clone size and cytotoxicity. This is currently available as a pre-print on BioRXiv (DOI: https://doi.org/10.1101/2020.11.15.383786) and at the time of deposition is undergoing peer review. The abstract for this work is as follows: Immune checkpoint blockers (ICB) exert their anti-cancer effects via CD8+ T cells, although how responses vary over sub-populations and across clones is incompletely understood. We performed single-cell RNA-sequencing of CD8+ T cells and their receptors pre- and post-ICB across eight patients, integrating results with bulk-sequencing data (n=209). We identify seven subsets with divergent responses to ICB, finding the effector cluster demonstrates the most pronounced changes. Likewise, transcriptomic response to ICB relates to clone size, with large clones demonstrating increased numbers of regulated genes of higher immunological pertinence. Cytotoxic effector clones were more likely to persist long-term following ICB and overlapped with public tumour-infiltrating lymphocyte clonotypes. Notably, pre-treatment CD8+ cytotoxicity associated with progression-free survival, highlighting the importance of the baseline CD8+ immune landscape in long-term response. This work further advances understanding of the molecular determinants of ICB response and assists in the search for peripheral prognostic biomarkers. The data consists of three files: 1. Gene expression matrix of CD8 T cells pre- and post-treatment. Each cell barcode is prefixed with an alpha-numeric which specifies the timepoint (A=pre-treatment, B=post-treatment) and the individual donor. 2. Seurat object containing gene expression data and metadata for CD8 T cells (pre- and post-treatment) 3. Seurat object contianing just CD8 T cells which have co-comitant V(D)J sequencing data available. The cells contained within the expression matrices and Seurat objects have undergone full pre-processing and QC steps and are used for the analysis and figures in the linked manuscript. For raw data, please refer to the FASTQ files which have been deposited in the European Genome–phenome Archive, which is hosted by the European Bioinformatics Institute and the Centre for Genomic Regulation (accession no. EGAS00001005507). Scripts used in the analysis of this data can be found on the Fairfax Lab bitbucket account (https://bitbucket.org/bpfairfax/immune-checkpoint-blockade-sensitivity-and-progression-free/src/master/

Natural Killer cells demonstrate distinct eQTL and transcriptome-wide disease associations, highlighting their role in autoimmunity

Natural Killer cells are innate lymphocytes with central roles in immunosurveillance and are implicated in autoimmune pathogenesis. The degree to which regulatory variants affect Natural Killer cell gene expression is poorly understood. Here we perform expression quantitative trait locus mapping of negatively selected Natural Killer cells from a population of healthy Europeans (n = 245). We find a significant subset of genes demonstrate expression quantitative trait loci specific to Natural Killer cells and these are highly informative of human disease, in particular autoimmunity. A Natural Killer cell transcriptome-wide association study across five common autoimmune diseases identifies further novel associations at 27 genes. In addition to these cis observations, we find novel master-regulatory regions impacting expression of trans gene networks at regions including 19q13.4, the Killer cell Immunoglobulin-like Receptor region, GNLY, MC1R and UVSSA. Our findings provide new insights into the unique biology of Natural Killer cells, demonstrating markedly different expression quantitative trait loci from other immune cells, with implications for disease mechanisms