Somatic whole genome dynamics of precancer in Barrett's esophagus reveals features associated with disease progression.

While the genomes of normal tissues undergo dynamic changes over time, little is understood about the temporal-spatial dynamics of genomes in premalignant tissues that progress to cancer compared to those that remain cancer-free. Here we use whole genome sequencing to contrast genomic alterations in 427 longitudinal samples from 40 patients with stable Barrett's esophagus compared to 40 Barrett's patients who progressed to esophageal adenocarcinoma (ESAD). We show the same somatic mutational processes are active in Barrett's tissue regardless of outcome, with high levels of mutation, ESAD gene and focal chromosomal alterations, and similar mutational signatures. The critical distinction between stable Barrett's versus those who progress to cancer is acquisition and expansion of TP53-/- cell populations having complex structural variants and high-level amplifications, which are detectable up to six years prior to a cancer diagnosis. These findings reveal the timing of common somatic genome dynamics in stable Barrett's esophagus and define key genomic features specific to progression to esophageal adenocarcinoma, both of which are critical for cancer prevention and early detection strategies.

Distinct Classes of Complex Structural Variation Uncovered across Thousands of Cancer Genome Graphs.

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g., deletion) or complex (e.g., chromothripsis) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,778 tumor whole-genome sequences, we uncovered three novel complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early-replicating regions, superenhancers, and breast or ovarian cancers. Rigma comprise "chasms" of low-JCN deletions enriched in late-replicating fragile sites and gastrointestinal carcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold-back inversions associated with expressed protein-coding fusions, breakend hypermutation, and acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis.

A model of pulldown alignments from SssI-treated DNA improves DNA methylation prediction.

BACKGROUND: Protein pulldown using Methyl-CpG binding domain (MBD) proteins followed by high-throughput sequencing is a common method to determine DNA methylation. Algorithms have been developed to estimate absolute methylation level from read coverage generated by affinity enrichment-based techniques, but the most accurate one for MBD-seq data requires additional data from an SssI-treated Control experiment. RESULTS: Using our previous characterizations of Methyl-CpG/MBD2 binding in the context of an MBD pulldown experiment, we build a model of expected MBD pulldown reads as drawn from SssI-treated DNA. We use the program BayMeth to evaluate the effectiveness of this model by substituting calculated SssI Control data for the observed SssI Control data. By comparing methylation predictions against those from an RRBS data set, we find that BayMeth run with our modeled SssI Control data performs better than BayMeth run with observed SssI Control data, on both 100 bp and 10 bp windows. Adapting the model to an external data set solely by changing the average fragment length, our calculated data still informs the BayMeth program to a similar level as observed data in predicting methylation state on a pulldown data set with matching WGBS estimates. CONCLUSION: In both internal and external MBD pulldown data sets tested in this study, BayMeth used with our modeled pulldown coverage performs better than BayMeth run without the inclusion of any estimate of SssI Control pulldown, and is comparable to - and in some cases better than - using observed SssI Control data with the BayMeth program. Thus, our MBD pulldown alignment model can improve methylation predictions without the need to perform additional control experiments.

Correction to: NSAID use and somatic exomic mutations in Barrett's esophagus.

It was highlighted that in the original article [1] the Availability of data and materials section was incorrect.

NSAID use and somatic exomic mutations in Barrett's esophagus.

BACKGROUND: Use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to protect against tetraploidy, aneuploidy, and chromosomal alterations in the metaplastic condition Barrett's esophagus (BE) and to lower the incidence and mortality of esophageal adenocarcinoma (EA). The esophagus is exposed to both intrinsic and extrinsic mutagens resulting from gastric reflux, chronic inflammation, and exposure to environmental carcinogens such as those found in cigarettes. Here we test the hypothesis that NSAID use inhibits accumulation of point mutations/indels during somatic genomic evolution in BE. METHODS: Whole exome sequences were generated from 82 purified epithelial biopsies and paired blood samples from a cross-sectional study of 41 NSAID users and 41 non-users matched by sex, age, smoking, and continuous time using or not using NSAIDs. RESULTS: NSAID use reduced overall frequency of point mutations across the spectrum of mutation types, lowered the frequency of mutations even when adjusted for both TP53 mutation and smoking status, and decreased the prevalence of clones with high variant allele frequency. Never smokers who consistently used NSAIDs had fewer point mutations in signature 17, which is commonly found in EA. NSAID users had, on average, a 50% reduction in functional gene mutations in nine cancer-associated pathways and also had less diversity in pathway mutational burden compared to non-users. CONCLUSIONS: These results indicate NSAID use functions to limit overall mutations on which selection can act and supports a model in which specific mutant cell populations survive or expand better in the absence of NSAIDs.

Cap homeostasis is independent of poly(A) tail length.

Cap homeostasis is a cyclical process of decapping and recapping that maintains the cap on a subset of the cytoplasmic transcriptome. Interfering with cytoplasmic capping results in the redistribution of target transcripts from polysomes to non-translating mRNPs, where they accumulate in an uncapped but nonetheless stable form. It is generally thought that decapping is preceded by shortening of the poly(A) tail to a length that can no longer support translation. Therefore recapped target transcripts would either have to undergo cytoplasmic polyadenylation or retain a reasonably long poly(A) tail if they are to return to the translating pool. In cells that are inhibited for cytoplasmic capping there is no change in the overall distribution of poly(A) lengths or in the elution profile of oligo(dT)-bound targets. Poly(A) tail lengths were similar for target mRNAs on polysomes or in non-translating mRNPs, and the presence of polyadenylated uncapped mRNA in mRNPs was confirmed by separation into capped and uncapped pools prior to assay. Finally, in silico analysis of cytoplasmic capping targets revealed significant correlations with genes encoding transcripts with uridylated or multiply modified 3' ends, and genes possessing multiple 3'-untranslated regions (UTRs) generated by alternative cleavage and polyadenylation.