Enabling large-scale screening of Barrett's esophagus using weakly supervised deep learning in histopathology.

Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, can improve patient survival rates. The Cytosponge-TFF3 test, a non-endoscopic minimally invasive procedure, has been used for diagnosing intestinal metaplasia in Barrett's. However, it depends on pathologist's assessment of two slides stained with H&E and the immunohistochemical biomarker TFF3.

Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma.

A variety of mutational processes drive cancer development, but their dynamics across the entire disease spectrum from pre-cancerous to advanced neoplasia are poorly understood. We explore the mutagenic processes shaping oesophageal adenocarcinoma tumorigenesis in 997 instances comprising distinct stages of this malignancy, from Barrett Oesophagus to primary tumours and advanced metastatic disease. The mutational landscape is dominated by the C[T > C/G]T substitution enriched signatures SBS17a/b, which are linked with TP53 mutations, increased proliferation, genomic instability and disease progression.

Rearrangement processes and structural variations show evidence of selection in oesophageal adenocarcinomas.

Oesophageal adenocarcinoma (OAC) provides an ideal case study to characterize large-scale rearrangements. Using whole genome short-read sequencing of 383 cases, for which 214 had matched whole transcriptomes, we observed structural variations (SV) with a predominance of deletions, tandem duplications and inter-chromosome junctions that could be identified as LINE-1 mobile element (ME) insertions. Complex clusters of rearrangements resembling breakage-fusion-bridge cycles or extrachromosomal circular DNA accounted for 22% of complex SVs affecting known oncogenes.

Use of a Cytosponge biomarker panel to prioritise endoscopic Barrett's oesophagus surveillance: a cross-sectional study followed by a real-world prospective pilot.

Background: Endoscopic surveillance is recommended for patients with Barrett's oesophagus because, although the progression risk is low, endoscopic intervention is highly effective for high-grade dysplasia and cancer. However, repeated endoscopy has associated harms and access has been limited during the COVID-19 pandemic. We aimed to evaluate the role of a non-endoscopic device (Cytosponge) coupled with laboratory biomarkers and clinical factors to prioritise endoscopy for Barrett's oesophagus.

Limitations of Heartburn and Other Societies' Criteria in Barrett's Screening for Detecting De Novo Esophageal Adenocarcinoma.

Background & Aims: Despite extensive Barrett's esophagus (BE) screening efforts, most patients with esophageal adenocarcinoma (EAC) present de novo. It is unclear how much of this problem is the result of insensitivity or poor applications of current screening guidelines. We aimed to evaluate the sensitivity of guidelines by determining the proportion of prevalent EAC cases that meet the American College of Gastroenterology (ACG) or the British Society of Gastroenterology (BSG) guidelines for BE screening and determine whether changes to criteria would enhance detection.

Evolution and progression of Barrett's oesophagus to oesophageal cancer.

Cancer cells are shaped through an evolutionary process of DNA mutation, cell selection and population expansion. Early steps in this process are driven by a set of mutated driver genes and structural alterations to the genome through copy number gains or losses. Oesophageal adenocarcinoma (EAC) and the pre-invasive tissue, Barrett's oesophagus (BE), provide an ideal example in which to observe and study this evolution.

Genomic instability signals offer diagnostic possibility in early cancer detection.

Emerging evidence from the large numbers of cancer genomes analyzed in recent years indicates that chromosomal instability (CI), a well-established hallmark of cancer cells, is detectable in precancerous lesions. In this opinion, we discuss the association of this instability with tumor progression and cancer risk. We highlight the opportunity that early genomic instability presents for the diagnosis of esophageal adenocarcinoma (EAC) and its precancerous lesion, Barrett's esophagus (BE).

Practical early cancer detection: distinguishing stable from unstable genomes in pre-cancerous tissues.

Barrett's oesophagus has been known for many years to display early changes to the genome consistent with the risk for oesophageal adenocarcinoma. Recently we have shown that this information can be used without knowledge of individual gene mutations to accurately predict a patient's future risk of malignant progression.

Genomic copy number predicts esophageal cancer years before transformation.

Recent studies show that aneuploidy and driver gene mutations precede cancer diagnosis by many years. We assess whether these genomic signals can be used for early detection and pre-emptive cancer treatment using the neoplastic precursor lesion Barrett's esophagus as an exemplar. Shallow whole-genome sequencing of 777 biopsies, sampled from 88 patients in Barrett's esophagus surveillance over a period of up to 15 years, shows that genomic signals can distinguish progressive from stable disease even 10 years before histopathological transformation.

Aneuploidy in targeted endoscopic biopsies outperforms other tissue biomarkers in the prediction of histologic progression of Barrett's oesophagus: A multi-centre prospective cohort study.

Background: The cancer risk in Barrett's oesophagus (BO) is difficult to estimate. Histologic dysplasia has strong predictive power, but can be missed by random biopsies. Other clinical parameters have limited utility for risk stratification.

Identification of Subtypes of Barrett's Esophagus and Esophageal Adenocarcinoma Based on DNA Methylation Profiles and Integration of Transcriptome and Genome Data.

Background & Aims: Esophageal adenocarcinomas (EACs) are heterogeneous and often preceded by Barrett's esophagus (BE). Many genomic changes have been associated with development of BE and EAC, but little is known about epigenetic alterations. We performed epigenetic analyses of BE and EAC tissues and combined these data with transcriptome and genomic data to identify mechanisms that control gene expression and genome integrity.

Comparison of Phenotypes and Risk Factors for Esophageal Adenocarcinoma at Present vs Prior Decades.

Background & Aims: The incidence of esophageal adenocarcinoma (EAC) has increased over the past decades. It is unclear if this increase is the result of a new cancer phenotype or an increase in risk factors for EAC. We aimed to compare risk factors, the proportions of intestinal and nonintestinal phenotypes of EAC, and survival times of patients during the 2009 to 2012 time period vs the 1996 to 1997 time period.

The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic.

Esophageal adenocarcinoma (EAC) is a poor-prognosis cancer type with rapidly rising incidence. Understanding of the genetic events driving EAC development is limited, and there are few molecular biomarkers for prognostication or therapeutics. Using a cohort of 551 genomically characterized EACs with matched RNA sequencing data, we discovered 77 EAC driver genes and 21 noncoding driver elements.

Identification of Prognostic Phenotypes of Esophageal Adenocarcinoma in 2 Independent Cohorts.

Background & Aims: Most patients with esophageal adenocarcinoma (EAC) present with de novo tumors. Although this could be due to inadequate screening strategies, the precise reason for this observation is not clear. We compared survival of patients with prevalent EAC with and without synchronous Barrett esophagus (BE) with intestinal metaplasia (IM) at the time of EAC diagnosis.

Identification of large-scale genomic variation in cancer genomes using in silico reference models.

Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly variant and complex tumor genomes. To address this challenge we developed a method that uses available breakpoint information to generate models of structural variations.

FIGG: simulating populations of whole genome sequences for heterogeneous data analyses.

Background: High-throughput sequencing has become one of the primary tools for investigation of the molecular basis of disease. The increasing use of sequencing in investigations that aim to understand both individuals and populations is challenging our ability to develop analysis tools that scale with the data. This issue is of particular concern in studies that exhibit a wide degree of heterogeneity or deviation from the standard reference genome.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

Background: For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed.

Interfaces to PeptideAtlas: a case study of standard data access systems.

Access to public data sets is important to the scientific community as a resource to develop new experiments or validate new data. Projects such as the PeptideAtlas, Ensembl and The Cancer Genome Atlas (TCGA) offer both access to public data and a repository to share their own data. Access to these data sets is often provided through a web page form and a web service API.

Methods for visual mining of genomic and proteomic data atlases.

Background: As the volume, complexity and diversity of the information that scientists work with on a daily basis continues to rise, so too does the requirement for new analytic software. The analytic software must solve the dichotomy that exists between the need to allow for a high level of scientific reasoning, and the requirement to have an intuitive and easy to use tool which does not require specialist, and often arduous, training to use. Information visualization provides a solution to this problem, as it allows for direct manipulation and interaction with diverse and complex data.

Mining PeptideAtlas for biomarkers and therapeutics in human disease.

Mass spectrometry information has long offered the potential of discovering biomarkers that would enable clinicians to diagnose disease, and treat it with targeted therapies. PeptideAtlas currently provides access to large-scale spectra data and identification information. This data, and the generation of targeted peptide information, represents the first step in the process of locating disease biomarkers.

SAMQA: error classification and validation of high-throughput sequenced read data.

Background: The advances in high-throughput sequencing technologies and growth in data sizes has highlighted the need for scalable tools to perform quality assurance testing. These tests are necessary to ensure that data is of a minimum necessary standard for use in downstream analysis. In this paper we present the SAMQA tool to rapidly and robustly identify errors in population-scale sequence data.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments.

Background: High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires.

Results: Existing software solutions provide static and well-established algorithms in a restrictive package.

Cytoscape: a community-based framework for network modeling.

Cytoscape is a general network visualization, data integration, and analysis software package. Its development and use has been focused on the modeling requirements of systems biology, though it has been used in other fields. Cytoscape's flexibility has encouraged many users to adopt it and adapt it to their own research by using the plugin framework offered to specialize data analysis, data integration, or visualization.