Pre-emptive TIPS in high-risk acute variceal bleeding. An updated and revised individual patient data meta-analysis.

BACKGROUND AND AIMS: A previous individual patient data meta-analysis (IPD-MA) showed that compared with drugs+endoscopy, the placement of transjugular portosystemic shunt within 72 hours of admission (pre-emptive transjugular intrahepatic portosystemic shunt: p-TIPS) increases the survival of high-risk patients (Child-Pugh B+ active bleeding and Child-Pugh C<14 points) with cirrhosis and acute variceal bleeding. However, the previous IPD-MA was not a two-stage meta-analysis, did not consider the potential risk of selection bias of observational studies, and did not include the most recent randomized clinical trial. We performed an updated and revised IPD-MA to reassess the efficacy of p-TIPS, addressing all previous issues. APPROACH AND RESULTS: We included all studies from the previous IPD-MA and searched for other possible eligible publications until September 2022. We performed a two-stage IPD-MA of data from 8 studies (4 randomized clinical trials and 4 observational). In addition, we performed a sensitivity analysis excluding those patients dying up to the first 72 hours after admission in the Drugs+Endoscopy arms of the 4 observational studies. The primary end point was the effects of p-TIPS versus Drugs+Endoscopy on 1-year survival.We identified 1389 patients (342 p-TIPS and 1047 Drugs+Endoscopy). The two-stage IPD-MA showed that p-TIPS significantly reduced the mortality in the overall population (HR=0·43, 95% CI: 0.32-0.60, p <0.001. This effect was observed in both subgroups of patients with Child-Pugh. The sensitivity analysis confirmed the survival benefit of p-TIPS. CONCLUSIONS: The updated two-stage IPD-MA confirms the significant survival advantage of p-TIPS in high-risk patients with cirrhosis and acute variceal bleeding. As a result, we recommend p-TIPS as the preferred first-choice treatment for these patients.

Unveiling impaired vascular function and cellular heterogeneity in diabetic donor-derived vascular organoids.

Vascular organoids (VOs), derived from induced pluripotent stem cells (iPSCs), hold promise as in vitro disease models and drug screening platforms. However, their ability to faithfully recapitulate human vascular disease and cellular composition remains unclear. In this study, we demonstrate that VOs derived from iPSCs of donors with diabetes (DB-VOs) exhibit impaired vascular function compared to non-diabetic VOs (ND-VOs). DB-VOs display elevated levels of reactive oxygen species (ROS), heightened mitochondrial content and activity, increased proinflammatory cytokines, and reduced blood perfusion recovery in vivo. Through comprehensive single-cell RNA sequencing, we uncover molecular and functional differences, as well as signaling networks, between vascular cell types and clusters within DB-VOs. Our analysis identifies major vascular cell types (endothelial cells [ECs], pericytes, and vascular smooth muscle cells) within VOs, highlighting the dichotomy between ECs and mural cells. We also demonstrate the potential need for additional inductions using organ-specific differentiation factors to promote organ-specific identity in VOs. Furthermore, we observe basal heterogeneity within VOs and significant differences between DB-VOs and ND-VOs. Notably, we identify a subpopulation of ECs specific to DB-VOs, showing overrepresentation in the ROS pathway and underrepresentation in the angiogenesis hallmark, indicating signs of aberrant angiogenesis in diabetes. Our findings underscore the potential of VOs for modeling diabetic vasculopathy, emphasize the importance of investigating cellular heterogeneity within VOs for disease modeling and drug discovery, and provide evidence of GAP43 (neuromodulin) expression in ECs, particularly in DB-VOs, with implications for vascular development and disease.

Global colorectal cancer research, 2007-2021: Outputs and funding.

The purpose of this study was to provide an evidence base for colorectal cancer research activity that might influence policy, mainly at the national level. Improvements in healthcare delivery have lengthened life expectancy, but within a situation of increased cancer incidence. The disease burden of CRC has risen significantly, particularly in Africa, Asia and Latin America. Research is key to its control and reduction, but few studies have delineated the volume and funding of global research on CRC. We identified research papers in the Web of Science (WoS) from 2007 to 2021, and determined the contributions of the leading countries, the research domains studied, and their sources of funding. We identified 62 716 papers, representing 5.7% of all cancer papers. This percentage was somewhat disproportionate to the disease burden (7.7% in 2015), especially in Eastern Europe. International collaboration increased over the time period in almost all countries except in China. Genetics, surgery and prognosis were the leading research domains. However, research on palliative care and quality-of-life in CRC was lacking. In Western Europe, the main funding source was the charity sector, particularly in the UK, but in most other countries government played the leading role, especially in China and the USA. There was little support from industry. Several Asian countries provided minimal contestable funding, which may have reduced the impact of their CRC research. Certain countries must perform more CRC research overall, especially in domains such as screening, palliative care and quality-of-life. The private-non-profit sector should be an alternative source of support.

MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1-4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. METHODS: Using transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n = 577) and mouse (n = 57 across n = 8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. RESULTS: We developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. CONCLUSIONS: When applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package enables researchers to select suitable mouse models of human CRC subtype for their experimental testing.

FLINO: a new method for immunofluorescence bioimage normalization.

MOTIVATION: Multiplexed immunofluorescence bioimaging of single-cells and their spatial organization in tissue holds great promise to the development of future precision diagnostics and therapeutics. Current multiplexing pipelines typically involve multiple rounds of immunofluorescence staining across multiple tissue slides. This introduces experimental batch effects that can hide underlying biological signal. It is important to have robust algorithms that can correct for the batch effects while not introducing biases into the data. Performance of data normalization methods can vary among different assay pipelines. To evaluate differences, it is critical to have a ground truth dataset that is representative of the assay. RESULTS: A new immunoFLuorescence Image NOrmalization method is presented and evaluated against alternative methods and workflows. Multiround immunofluorescence staining of the same tissue with the nuclear dye DAPI was used to represent virtual slides and a ground truth. DAPI was restained on a given tissue slide producing multiple images of the same underlying structure but undergoing multiple representative tissue handling steps. This ground truth dataset was used to evaluate and compare multiple normalization methods including median, quantile, smooth quantile, median ratio normalization and trimmed mean of the M-values. These methods were applied in both an unbiased grid object and segmented cell object workflow to 24 multiplexed biomarkers. An upper quartile normalization of grid objects in log space was found to obtain almost equivalent performance to directly normalizing segmented cell objects by the middle quantile. The developed grid-based technique was then applied with on-slide controls for evaluation. Using five or fewer controls per slide can introduce biases into the data. Ten or more on-slide controls were able to robustly correct for batch effects. AVAILABILITY AND IMPLEMENTATION: The data underlying this article along with the FLINO R-scripts used to perform the evaluation of image normalizations methods and workflows can be downloaded from https://github.com/GE-Bio/FLINO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The pseudo-caspase FLIP(L) regulates cell fate following p53 activation.

p53 is the most frequently mutated, well-studied tumor-suppressor gene, yet the molecular basis of the switch from p53-induced cell-cycle arrest to apoptosis remains poorly understood. Using a combination of transcriptomics and functional genomics, we unexpectedly identified a nodal role for the caspase-8 paralog and only human pseudo-caspase, FLIP(L), in regulating this switch. Moreover, we identify FLIP(L) as a direct p53 transcriptional target gene that is rapidly up-regulated in response to Nutlin-3A, an MDM2 inhibitor that potently activates p53. Genetically or pharmacologically inhibiting expression of FLIP(L) using siRNA or entinostat (a clinically relevant class-I HDAC inhibitor) efficiently promoted apoptosis in colorectal cancer cells in response to Nutlin-3A, which otherwise predominantly induced cell-cycle arrest. Enhanced apoptosis was also observed when entinostat was combined with clinically relevant, p53-activating chemotherapy in vitro, and this translated into enhanced in vivo efficacy. Mechanistically, FLIP(L) inhibited p53-induced apoptosis by blocking activation of caspase-8 by the TRAIL-R2/DR5 death receptor; notably, this activation was not dependent on receptor engagement by its ligand, TRAIL. In the absence of caspase-8, another of its paralogs, caspase-10 (also transcriptionally up-regulated by p53), induced apoptosis in Nutlin-3A-treated, FLIP(L)-depleted cells, albeit to a lesser extent than in caspase-8-proficient cells. FLIP(L) depletion also modulated transcription of canonical p53 target genes, suppressing p53-induced expression of the cell-cycle regulator p21 and enhancing p53-induced up-regulation of proapoptotic PUMA. Thus, even in the absence of caspase-8/10, FLIP(L) silencing promoted p53-induced apoptosis by enhancing PUMA expression. Thus, we report unexpected, therapeutically relevant roles for FLIP(L) in determining cell fate following p53 activation.

Activation of innate-adaptive immune machinery by poly(I:C) exposes a therapeutic vulnerability to prevent relapse in stroma-rich colon cancer.

OBJECTIVE: Stroma-rich tumours represent a poor prognostic subtype in stage II/III colon cancer (CC), with high relapse rates and limited response to standard adjuvant chemotherapy. DESIGN: To address the lack of efficacious therapeutic options for patients with stroma-rich CC, we stratified our human tumour cohorts according to stromal content, enabling identification of the biology underpinning relapse and potential therapeutic vulnerabilities specifically within stroma-rich tumours that could be exploited clinically. Following human tumour-based discovery and independent clinical validation, we use a series of in vitro and stroma-rich in vivo models to test and validate the therapeutic potential of elevating the biology associated with reduced relapse in human tumours. RESULTS: By performing our analyses specifically within the stroma-rich/high-fibroblast (HiFi) subtype of CC, we identify and validate the clinical value of a HiFi-specific prognostic signature (HPS), which stratifies tumours based on STAT1-related signalling (High-HPS v Low-HPS=HR 0.093, CI 0.019 to 0.466). Using in silico, in vitro and in vivo models, we demonstrate that the HPS is associated with antigen processing and presentation within discrete immune lineages in stroma-rich CC, downstream of double-stranded RNA and viral response signalling. Treatment with the TLR3 agonist poly(I:C) elevated the HPS signalling and antigen processing phenotype across in vitro and in vivo models. In an in vivo model of stroma-rich CC, poly(I:C) treatment significantly increased systemic cytotoxic T cell activity (p<0.05) and reduced liver metastases (p<0.0002). CONCLUSION: This study reveals new biological insight that offers a novel therapeutic option to reduce relapse rates in patients with the worst prognosis CC.

Development of a semi-automated method for tumour budding assessment in colorectal cancer and comparison with manual methods.

AIMS: Tumour budding (TB) is an established prognostic feature in multiple cancers but is not routinely assessed in pathology practice. Efforts to standardise and automate assessment have shifted from haematoxylin and eosin (H&E)-stained images towards cytokeratin immunohistochemistry. The aim of this study was to compare manual H&E and cytokeratin assessment methods with a semi-automated approach built within QuPath open-source software. METHODS AND RESULTS: TB was assessed in cores from the advancing tumour edge in a cohort of stage II/III colon cancers (n = 186). The total numbers of buds detected with each method were as follows: manual H&E, n = 503; manual cytokeratin, n = 2290; and semi-automated, n = 5138. More than four times the number of buds were identified manually with cytokeratin assessment than with H&E assessment. One thousand seven hundred and thirty-four individual buds were identified with both manual and semi-automated assessments applied to cytokeratin images, representing 75.7% of the buds identified manually (n = 2290) and 33.7% of the buds detected with the semi-automated method (n = 5138). Higher semi-automated TB scores were due to any discrete area of cytokeratin immunopositivity within an accepted area range being identified as a bud, regardless of shape or crispness of definition, and to the inclusion of tumour cell clusters within glandular lumina ('luminal pseudobuds'). Although absolute numbers differed, semi-automated and manual bud counts were strongly correlated across cores (ρ = 0.81, P < 0.0001). All methods of TB assessment demonstrated poorer survival associated with higher TB scores. CONCLUSIONS: We present a new QuPath-based approach to TB assessment, which compares favourably with established methods and offers a freely available, rapid and transparent tool that is also applicable to whole slide images.

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN: Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS: Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION: This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.

Exploiting differential Wnt target gene expression to generate a molecular biomarker for colorectal cancer stratification.

OBJECTIVE: Pathological Wnt pathway activation is a conserved hallmark of colorectal cancer. Wnt-activating mutations can be divided into: i) ligand-independent (LI) alterations in intracellular signal transduction proteins (Adenomatous polyposis coli, ß-catenin), causing constitutive pathway activation and ii) ligand-dependent (LD) mutations affecting the synergistic R-Spondin axis (RNF43, RSPO-fusions) acting through amplification of endogenous Wnt signal transmembrane transduction. Our aim was to exploit differential Wnt target gene expression to generate a mutation-agnostic biomarker for LD tumours. DESIGN: We undertook harmonised multi-omic analysis of discovery (n=684) and validation cohorts (n=578) of colorectal tumours collated from publicly available data and the Stratification in Colorectal Cancer Consortium. We used mutation data to establish molecular ground truth and subdivide lesions into LI/LD tumour subsets. We contrasted transcriptional, methylation, morphological and clinical characteristics between groups. RESULTS: Wnt disrupting mutations were mutually exclusive. Desmoplastic stromal upregulation of RSPO may compensate for absence of epithelial mutation in a subset of stromal-rich tumours. Key Wnt negative regulator genes were differentially expressed between LD/LI tumours, with targeted hypermethylation of some genes (AXIN2, NKD1) occurring even in CIMP-negative LD cancers. AXIN2 mRNA expression was used as a discriminatory molecular biomarker to distinguish LD/LI tumours (area under the curve >0.93). CONCLUSIONS: Epigenetic suppression of appropriate Wnt negative feedback loops is selectively advantageous in LD tumours and differential AXIN2 expression in LD/LI lesions can be exploited as a molecular biomarker. Distinguishing between LD/LI tumour types is important; patients with LD tumours retain sensitivity to Wnt ligand inhibition and may be stratified at diagnosis to clinical trials of Porcupine inhibitors.

Standardising RNA profiling based biomarker application in cancer-The need for robust control of technical variables.

Histopathology-based staging of colorectal cancer (CRC) has utility in assessing the prognosis of patient subtypes, but as yet cannot accurately predict individual patient's treatment response. Transcriptomics approaches, using array based or next generation sequencing (NGS) platforms, of formalin fixed paraffin embedded tissue can be harnessed to develop multi-gene biomarkers for predicting both prognosis and treatment response, leading to stratification of treatment. While transcriptomics can shape future biomarker development, currently <1% of published biomarkers become clinically validated tests, often due to poor study design or lack of independent validation. In this review of a large number of CRC transcriptional studies, we identify recurrent sources of technical variability that encompass collection, preservation and storage of malignant tissue, nucleic acid extraction, methods to quantitate RNA transcripts and data analysis pipelines. We propose a series of defined steps for removal of these confounding issues, to ultimately aid in the development of more robust clinical biomarkers.

Prognosis following surgical resection versus local excision of stage pT1 colorectal cancer: A population-based cohort study.

AIMS: To evaluate patient management following stage pT1 colorectal cancer (CRC) diagnosis, and to determine if surgical resection improved outcome compared with local excision, within a population-based study. METHODS: Data were collected from the Northern Ireland Cancer Registry. Cases of stage pT1 CRC diagnosed from 2007 to 2012 were identified. Analyses were conducted using Cox proportional hazard models to calculate hazard ratios (HR) and 95% confidence intervals (CI) for cancer-specific and all-cause mortality for individuals undergoing formal surgery versus local excision. RESULTS: 394 patients with pT1 CRC were included. Of these, 37.1% were treated by local resection, 36.8% had biopsy followed by surgery and 26.1% had local excision followed by surgery. There were 60 deaths over a mean 4.8 years of follow-up, including 10 CRC-specific deaths. An additional 12 patients had a CRC recurrence or metastases during follow-up. Of the CRC-specific deaths or recurrences, 27.3% had local excision only. Individuals treated by formal surgery did not have a reduced risk of CRC-specific death (adjusted HR = 1.51, 95% CI 0.29, 7.89), but did have a reduced risk of all-cause mortality (adjusted HR = 0.51 95% CI 0.30, 0.87) compared with those undergoing local excision only. CONCLUSIONS: Patients with stage pT1 CRC undergoing formal surgery had a reduced risk of all-cause mortality compared with those treated by local excision only. However, this was not explained by a reduced risk of recurrence/disease-free survival or CRC death, and suggests that the observed benefits may simply reflect selection of a healthier patient population in the formal surgery group.

Downregulation of PPARα during Experimental Left Ventricular Hypertrophy Is Critically Dependent on Nox2 NADPH Oxidase Signalling.

Pressure overload-induced left ventricular hypertrophy (LVH) is initially adaptive but ultimately promotes systolic dysfunction and chronic heart failure. Whilst underlying pathways are incompletely understood, increased reactive oxygen species generation from Nox2 NADPH oxidases, and metabolic remodelling, largely driven by PPARα downregulation, are separately implicated. Here, we investigated interaction between the two as a key regulator of LVH using in vitro, in vivo and transcriptomic approaches. Phenylephrine-induced H9c2 cardiomyoblast hypertrophy was associated with reduced PPARα expression and increased Nox2 expression and activity. Pressure overload-induced LVH and systolic dysfunction induced in wild-type mice by transverse aortic constriction (TAC) for 7 days, in association with Nox2 upregulation and PPARα downregulation, was enhanced in PPARα-/- mice and prevented in Nox2-/- mice. Detailed transcriptomic analysis revealed significantly altered expression of genes relating to PPARα, oxidative stress and hypertrophy pathways in wild-type hearts, which were unaltered in Nox2-/- hearts, whilst oxidative stress pathways remained dysregulated in PPARα-/- hearts following TAC. Network analysis indicated that Nox2 was essential for PPARα downregulation in this setting and identified preferential inflammatory pathway modulation and candidate cytokines as upstream Nox2-sensitive regulators of PPARα signalling. Together, these data suggest that Nox2 is a critical driver of PPARα downregulation leading to maladaptive LVH.

Previous Use of Antithrombotic Agents Reduces Mortality and Length of Hospital Stay in Patients With High-risk Upper Gastrointestinal Bleeding.

BACKGROUND & AIMS: Anti-thrombotic agents are risk factors for upper gastrointestinal bleeding (UGIB). However, few studies have evaluated their effects on patient outcomes. We assessed the effects of anti-thrombotic agents on outcomes of patients with high-risk UGIB. METHODS: We performed a prospective study of 619 patients with acute UGIB (defined by hematemesis, coffee-ground vomit or melena) who required intervention and underwent endoscopy at 8 centers in North America, Asia, and Europe, from March 2014 through March 2015. We collected data recorded on use of anti-thrombotic agents, clinical features, and laboratory test results to calculate AIMS65, Glasgow-Blatchford Score, and full Rockall scores. We also collected and analyzed data on co-morbidities, endoscopic findings, blood transfusion, interventional radiology results, surgeries, length of hospital stay, rebleeding, and mortality. RESULTS: Of the 619 patients who required endoscopic therapy, data on use of anti-thrombotic agents was available for 568; 253 of these patients (44%) used anti-thrombotic agents. Compared to patients not taking anti-thrombotic agents, patients treated with anti-thrombotics were older (P < .001), had a higher mean American Society of Anesthesiologists classification score (P < .0001), had a higher mean Rockall score (P < .0001), a higher mean AIMS65 score (P < .0001), and more frequently bled from ulcers (P < .001). There were no differences between groups in sex, systolic blood pressure, level of hemoglobin at hospital admission, frequency of malignancies, Glasgow-Blatchford Score, need for surgery or interventional radiology, number of rebleeding events, or requirement for transfusion. All-cause mortality was lower in patients who took anti-thrombotic drugs (11 deaths, 4%) than in patients who did not (37 deaths, 12%) (P = .002); this was due to lower bleeding-related mortality in patients taking anti-thrombotic drugs (3 deaths, 1%) than in patients who were not (19 deaths, 6%) (P = .003). Patients taking anti-thrombotic drugs had mean hospital stays of 6.9 days (95% CI, 2-23 days) compared to 7.9 days for non-users of anti-thrombotic agents (95% CI, 2-26 days) (P = .04). CONCLUSIONS: Despite being older, with higher American Society of Anesthesiologists classification, AIMS65, and Rockall scores, patients who have UGIB that requires endoscopic therapy and take anti-thrombotic drugs have lower mortality due to GI bleeding and shorter hospital stays, with similar rates of rebleeding, surgery, and transfusions, compared with those not taking anti-thrombotic drugs.

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.

Defining the molecular evolution of extrauterine high grade serous carcinoma.

OBJECTIVE: High grade serous carcinoma (HGSC) is the most common and most aggressive, subtype of epithelial ovarian cancer. It presents as advanced stage disease with poor prognosis. Recent pathological evidence strongly suggests HGSC arises from the fallopian tube via the precursor lesion; serous tubal intraepithelial carcinoma (STIC). However, further definition of the molecular evolution of HGSC has major implications for both clinical management and research. This study aims to more clearly define the molecular pathogenesis of HGSC. METHODS: Six cases of HGSC were identified at the Northern Ireland Gynaecological Cancer Centre (NIGCC) that each contained ovarian HGSC (HGSC), omental HGSC (OMT), STIC, normal fallopian tube epithelium (FTE) and normal ovarian surface epithelium (OSE). The relevant formalin-fixed paraffin embedded (FFPE) tissue samples were retrieved from the pathology archive via the Northern Ireland Biobank following attaining ethical approval (NIB11:005). Full microarray-based gene expression profiling was performed on the cohort. The resulting data was analysed bioinformatically and the results were validated in a HGSC-specific in-vitro model. RESULTS: The carcinogenesis of HGSC was investigated and showed the molecular profile of HGSC to be more closely related to normal FTE than OSE. STIC lesions also clustered closely with HGSC, indicating a common molecular origin. CONCLUSION: This study provides strong evidence suggesting that extrauterine HGSC arises from the fimbria of the distal fallopian tube. Furthermore, several potential pathways were identified which could be targeted by novel therapies for HGSC. These findings have significant translational relevance for both primary prevention and clinical management of the disease.

Epithelial-to-mesenchymal transition signature assessment in colorectal cancer quantifies tumour stromal content rather than true transition.

The process of epithelial-to-mesenchymal transition (EMT) in cancer is a well-described process whereby epithelial tumour cells undergo molecular/phenotypic changes and transition to a mesenchymal biology. To aid in the transcriptional characterisation of this process, gene expression signatures have been developed that attribute a relative EMT score to samples in a given cohort. We demonstrate how such EMT signatures can identify epithelial cell line models with high levels of transition but also highlight that, unsurprisingly, fibroblast cell lines, which are inherently mesenchymal, have a higher EMT score relative to any epithelial cell line studied. In line with these data, we demonstrate how increased tumour stromal composition, and reduced epithelial cellularity, significantly correlates with increasing EMT signature score, which is evident using either in silico subtyping analysis (p < 0.00001) or in situ histopathological characterisation (p < 0.001). Considered together, these results reinforce the importance not only of interdisciplinary research to correctly define the nature of EMT biology but also the requirement for a cadre of multidisciplinary researchers who can analyse and interpret the underlying pathological, bioinformatic and molecular data that are essential for advancing our understanding of the malignant process. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Prospective patient stratification into robust cancer-cell intrinsic subtypes from colorectal cancer biopsies.

Colorectal cancer (CRC) biopsies underpin accurate diagnosis, but are also relevant for patient stratification in molecularly-guided clinical trials. The consensus molecular subtypes (CMSs) and colorectal cancer intrinsic subtypes (CRISs) transcriptional signatures have potential clinical utility for improving prognostic/predictive patient assignment. However, their ability to provide robust classification, particularly in pretreatment biopsies from multiple regions or at different time points, remains untested. In this study, we undertook a comprehensive assessment of the robustness of CRC transcriptional signatures, including CRIS and CMS, using a range of tumour sampling methodologies currently employed in clinical and translational research. These include analyses using (i) laser-capture microdissected CRC tissue, (ii) eight publically available rectal cancer biopsy data sets (n = 543), (iii) serial biopsies (from AXEBeam trial, NCT00828672; n = 10), (iv) multi-regional biopsies from colon tumours (n = 29 biopsies, n = 7 tumours), and (v) pretreatment biopsies from the phase II rectal cancer trial COPERNCIUS (NCT01263171; n = 44). Compared to previous results obtained using CRC resection material, we demonstrate that CMS classification in biopsy tissue is significantly less capable of reliably classifying patient subtype (43% unknown in biopsy versus 13% unknown in resections, p = 0.0001). In contrast, there was no significant difference in classification rate between biopsies and resections when using the CRIS classifier. Additionally, we demonstrated that CRIS provides significantly better spatially- and temporally- robust classification of molecular subtypes in CRC primary tumour tissue compared to CMS (p = 0.003 and p = 0.02, respectively). These findings have potential to inform ongoing biopsy-based patient stratification in CRC, enabling robust and stable assignment of patients into clinically-informative arms of prospective multi-arm, multi-stage clinical trials. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Validation of the systematic scoring of immunohistochemically stained tumour tissue microarrays using QuPath digital image analysis.

AIMS: Output from biomarker studies involving immunohistochemistry applied to tissue microarrays (TMA) is limited by the lack of an efficient and reproducible scoring methodology. In this study, we examine the functionality and reproducibility of biomarker scoring using the new, open-source, digital image analysis software, QuPath. METHODS AND RESULTS: Three different reviewers, with varying experience of digital pathology and image analysis, applied an agreed QuPath scoring methodology to CD3 and p53 immunohistochemically stained TMAs from a colon cancer cohort (n = 661). Manual assessment was conducted by one reviewer for CD3. Survival analyses were conducted and intra- and interobserver reproducibility assessed. Median raw scores differed significantly between reviewers, but this had little impact on subsequent analyses. Lower CD3 scores were detected in cases who died from colorectal cancer compared to control cases, and this finding was significant for all three reviewers (P-value range = 0.002-0.02). Higher median p53 scores were generated among cases who died from colorectal cancer compared with controls (P-value range = 0.04-0.12). The ability to dichomotise cases into high versus low expression of CD3 and p53 showed excellent agreement between all three reviewers (kappa score range = 0.82-0.93). All three reviewers produced dichotomised expression scores that resulted in very similar hazard ratios for colorectal cancer-specific survival for each biomarker. Results from manual and QuPath methods of CD3 scoring were comparable, but QuPath scoring revealed stronger prognostic stratification. CONCLUSIONS: Scoring of immunohistochemically stained tumour TMAs using QuPath is functional and reproducible, even among users of limited experience of digital pathology images, and more accurate than manual scoring.