Impact of mutations in Toll-like receptor pathway genes on esophageal carcinogenesis.

Esophageal adenocarcinoma (EAC) develops in an inflammatory microenvironment with reduced microbial diversity, but mechanisms for these influences remain poorly characterized. We hypothesized that mutations targeting the Toll-like receptor (TLR) pathway could disrupt innate immune signaling and promote a microenvironment that favors tumorigenesis. Through interrogating whole genome sequencing data from 171 EAC patients, we showed that non-synonymous mutations collectively affect the TLR pathway in 25/171 (14.6%, PathScan p = 8.7x10-5) tumors. TLR mutant cases were associated with more proximal tumors and metastatic disease, indicating possible clinical significance of these mutations. Only rare mutations were identified in adjacent Barrett's esophagus samples. We validated our findings in an external EAC dataset with non-synonymous TLR pathway mutations in 33/149 (22.1%, PathScan p = 0.05) tumors, and in other solid tumor types exposed to microbiomes in the COSMIC database (10,318 samples), including uterine endometrioid carcinoma (188/320, 58.8%), cutaneous melanoma (377/988, 38.2%), colorectal adenocarcinoma (402/1519, 26.5%), and stomach adenocarcinoma (151/579, 26.1%). TLR4 was the most frequently mutated gene with eleven mutations in 10/171 (5.8%) of EAC tumors. The TLR4 mutants E439G, S570I, F703C and R787H were confirmed to have impaired reactivity to bacterial lipopolysaccharide with marked reductions in signaling by luciferase reporter assays. Overall, our findings show that TLR pathway genes are recurrently mutated in EAC, and TLR4 mutations have decreased responsiveness to bacterial lipopolysaccharide and may play a role in disease pathogenesis in a subset of patients

Evidence that polyploidy in esophageal adenocarcinoma originates from mitotic slippage caused by defective chromosome attachments

Abstract: Polyploidy is present in many cancer types and is increasingly recognized as an important factor in promoting chromosomal instability, genome evolution, and heterogeneity in cancer cells. However, the mechanisms that trigger polyploidy in cancer cells are largely unknown. In this study, we investigated the origin of polyploidy in esophageal adenocarcinoma (EAC), a highly heterogenous cancer, using a combination of genomics and cell biology approaches in EAC cell lines, organoids, and tumors. We found the EAC cells and organoids present specific mitotic defects consistent with problems in the attachment of chromosomes to the microtubules of the mitotic spindle. Time-lapse analyses confirmed that EAC cells have problems in congressing and aligning their chromosomes, which can ultimately culminate in mitotic slippage and polyploidy. Furthermore, whole-genome sequencing, RNA-seq, and quantitative immunofluorescence analyses revealed alterations in the copy number, expression, and cellular distribution of several proteins known to be involved in the mechanics and regulation of chromosome dynamics during mitosis. Together, these results provide evidence that an imbalance in the amount of proteins implicated in the attachment of chromosomes to spindle microtubules is the molecular mechanism underlying mitotic slippage in EAC. Our findings that the likely origin of polyploidy in EAC is mitotic failure caused by problems in chromosomal attachments not only improves our understanding of cancer evolution and diversification, but may also aid in the classification and treatment of EAC and possibly other highly heterogeneous cancers

Open chromatin profiling identifies AP1 as a transcriptional regulator in oesophageal adenocarcinoma.

Oesophageal adenocarcinoma (OAC) is one of the ten most prevalent forms of cancer and is showing a rapid increase in incidence and yet exhibits poor survival rates. Compared to many other common cancers, the molecular changes that occur in this disease are relatively poorly understood. However, genes encoding chromatin remodeling enzymes are frequently mutated in OAC. This is consistent with the emerging concept that cancer cells exhibit reprogramming of their chromatin environment which leads to subsequent changes in their transcriptional profile. Here, we have used ATAC-seq to interrogate the chromatin changes that occur in OAC using both cell lines and patient-derived material. We demonstrate that there are substantial changes in the regulatory chromatin environment in the cancer cells and using this data we have uncovered an important role for ETS and AP1 transcription factors in driving the changes in gene expression found in OAC cells.Our work received funding from the Wellcome Trust (https://wellcome.ac.uk/) the National Institute for Health Research (https://www.nihr.ac.uk/) and Cancer Research UK (http:// www.cancerresearchuk.org/)

Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma.

The poor outcomes in esophageal adenocarcinoma (EAC) prompted us to interrogate the pattern and timing of metastatic spread. Whole-genome sequencing and phylogenetic analysis of 388 samples across 18 individuals with EAC showed, in 90% of patients, that multiple subclones from the primary tumor spread very rapidly from the primary site to form multiple metastases, including lymph nodes and distant tissues-a mode of dissemination that we term 'clonal diaspora'. Metastatic subclones at autopsy were present in tissue and blood samples from earlier time points. These findings have implications for our understanding and clinical evaluation of EAC.MRC core grant (RG84369), an NIHR Research Professorship (RG67258) and Cancer Research UK (RG66287)

Organoid cultures recapitulate esophageal adenocarcinoma heterogeneity providing a model for clonality studies and precision therapeutics

Esophageal adenocarcinoma (EAC) incidence is increasing while 5-year survival rates remain less than 15%. A lack of experimental models has hampered progress. We have generated clinically annotated EAC organoid cultures that recapitulate the morphology, genomic and transcriptomic landscape of the primary tumor including point mutations, copy number alterations and mutational signatures. Karyotyping has confirmed polyclonality reflecting the clonal architecture of the primary and subclones underwent clonal selection associated with driver gene status. Medium throughput drug sensitivity testing demonstrates the potential of targeting receptor tyrosine kinases and downstream mediators. EAC organoid cultures provide a pre-clinical tool for studies of clonal evolution and precision therapeutics

Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance.

Esophageal adenocarcinoma (EAC) has a poor outcome, and targeted therapy trials have thus far been disappointing owing to a lack of robust stratification methods. Whole-genome sequencing (WGS) analysis of 129 cases demonstrated that this is a heterogeneous cancer dominated by copy number alterations with frequent large-scale rearrangements. Co-amplification of receptor tyrosine kinases (RTKs) and/or downstream mitogenic activation is almost ubiquitous; thus tailored combination RTK inhibitor (RTKi) therapy might be required, as we demonstrate in vitro. However, mutational signatures showed three distinct molecular subtypes with potential therapeutic relevance, which we verified in an independent cohort (n = 87): (i) enrichment for BRCA signature with prevalent defects in the homologous recombination pathway; (ii) dominant T>G mutational pattern associated with a high mutational load and neoantigen burden; and (iii) C>A/T mutational pattern with evidence of an aging imprint. These subtypes could be ascertained using a clinically applicable sequencing strategy (low coverage) as a basis for therapy selection.Whole-genome sequencing of esophageal adenocarcinoma samples was performed as part of the International Cancer Genome Consortium (ICGC) through the oEsophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium and was funded by Cancer Research UK. We thank the ICGC members for their input on verification standards as part of the benchmarking exercise. We thank the Human Research Tissue Bank, which is supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, from Addenbrooke’s Hospital and UCL. Also the University Hospital of Southampton Trust and the Southampton, Birmingham, Edinburgh and UCL Experimental Cancer Medicine Centres and the QEHB charities. This study was partly funded by a project grant from Cancer Research UK. R.C.F. is funded by an NIHR Professorship and receives core funding from the Medical Research Council and infrastructure support from the Biomedical Research Centre and the Experimental Cancer Medicine Centre. We acknowledge the support of The University of Cambridge, Cancer Research UK (C14303/A17197) and Hutchison Whampoa Limited. We would like to thank Dr. Peter Van Loo for providing the NGS version of ASCAT for copy number calling. We are grateful to all the patients who provided written consent for participation in this study and the staff at all participating centres. Some of the work was undertaken at UCLH/UCL who received a proportion of funding from the Department of Health’s NIHR Biomedical Research Centres funding scheme. The work at UCLH/UCL was also supported by the CRUK UCL Early Cancer Medicine Centre.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.365

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

A comparative analysis of whole genome sequencing of esophageal adenocarcinoma pre- and post-chemotherapy

The scientific community has avoided using tissue samples from patients that have been exposed to systemic chemotherapy to infer the genomic landscape of a given cancer. Esophageal adenocarcinoma is a heterogeneous, chemoresistant tumor for which the availability and size of pretreatment endoscopic samples are limiting. This study compares whole-genome sequencing data obtained from chemo-naive and chemo-treated samples. The quality of whole-genomic sequencing data is comparable across all samples regardless of chemotherapy status. Inclusion of samples collected post-chemotherapy increased the proportion of late-stage tumors. When comparing matched pre- and post-chemotherapy samples from 10 cases, the mutational signatures, copy number, and SNV mutational profiles reflect the expected heterogeneity in this disease. Analysis of SNVs in relation to allele-specific copy-number changes pinpoints the common ancestor to a point prior to chemotherapy. For cases in which pre- and post-chemotherapy samples do show substantial differences, the timing of the divergence is near-synchronous with endoreduplication. Comparison across a large prospective cohort (62 treatment-naive, 58 chemotherapy-treated samples) reveals no significant differences in the overall mutation rate, mutation signatures, specific recurrent point mutations, or copy-number events in respect to chemotherapy status. In conclusion, whole-genome sequencing of samples obtained following neoadjuvant chemotherapy is representative of the genomic landscape of esophageal adenocarcinoma. Excluding these samples reduces the material available for cataloging and introduces a bias toward the earlier stages of cancer.This study was partly funded by a project grant from Cancer Research UK. R.C.F. is funded by an NIHR Professorship and receives core funding from the Medical Research Council and infrastructure support from the Biomedical Research Centre and the Experimental Cancer Medicine Centre. We acknowledge the support of The University of Cambridge, Cancer Research UK (C14303/A17197) and Hutchison Whampoa Limited

Modeling and Analysis of Distortion Caused by Markov-model Burst Packet Losses in Video Transmission

Abstract—This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. Based on a detailed analysis of the error propagation and the bursty losses, a Distortion Trellis model is proposed, enabling us to estimate at both frame level and sequence level the expected mean-square error (MSE) distortion caused by Markov-model bursty packet losses. The model takes into account the temporal dependencies induced by both the motion compensated coding scheme and the Markov-model channel losses. The model is applicable to most block-based motion compensated encoders, and most Markovmodel lossy channels as long as the loss pattern probabilities for that channel is computable. Based on the study of the decaying behavior of the error propagation, a sliding window algorithm is developed to perform the MSE estimation with low complexity. Simulation results show that the proposed models are accurate for all tested average loss rates and average burst lengths. Based on the experimental results, the proposed techniques are used to analyze the impact of factors such as average burst length on the average decoded video quality. The proposed model is further extended to a more general form, and the modeled distortion is compared with the data produced from realistic networks loss traces. The experiment results demonstrate that the proposed model is also accurate in estimating the expected distortion for video transmission in real networks. Index Terms—distortion modeling, video transmission, burstloss channel, Markov-model loss process, error propagation. I

MODELING OF DISTORTION CAUSED BY MARKOV-MODEL BURST PACKET LOSSES IN VIDEO TRANSMISSION

This paper addresses the problem of distortion modeling for video transmission over burst-loss channels characterized by a finite state Markov chain. A Distortion Trellis model is proposed, enabling us to estimate at the frame level the expected mean-square error (MSE) distortion caused by Markov-model bursty packet losses. A sliding window algorithm is developed to perform the MSE estimation with low complexity. Simulation results show that the proposed models are accurate for all tested average loss rates and average burst lengths. Index Terms — distortion modeling, burst-loss channel, Markov-model loss process, error propagation. 1