Esophageal adenocarcinoma (EAC) claims the lives of half of patients within the first year of diagnosis, and its incidence has rapidly increased since the 1970s despite extensive research into etiological factors. The changes in the microbiome within the distal esophagus in modern populations may help explain the growth in cases that other common EAC risk factors together cannot fully explain. The precursor to EAC is Barrett's esophagus (BE), a metaplasia adapted to a reflux-mediated microenvironment that can be challenging to diagnose in patients who do not undergo endoscopic screening. Non-invasive procedures to detect microbial communities in saliva, oral swabs and brushings from the distal esophagus allow us to characterize taxonomic differences in bacterial population abundances within patients with BE versus controls, and may provide an alternative means of BE detection. Unique microbial communities have been identified across healthy esophagus, BE, and various stages of progression to EAC, but studies determining dynamic changes in these communities, including migration from proximal stomach and oral cavity niches, and their potential causal role in cancer formation are lacking. Helicobacter pylori is negatively associated with EAC, and the absence of this species has been implicated in the evolution of chromosomal instability, a main driver of EAC, but joint analyses of microbiome and host genomes are needed. Acknowledging technical challenges, future studies on the prediction of microbial dynamics and evolution within BE and the progression to EAC will require larger esophageal microbiome datasets, improved bioinformatics pipelines, and specialized mathematical models for analysis.

The presence and role of microbes in human cancers has come full circle in the last century. Tumors are no longer considered aseptic, but implications for cancer biology and oncology remain underappreciated. Opportunities to identify and build translational diagnostics, prognostics, and therapeutics that exploit cancer's second genome-the metagenome-are manifold, but require careful consideration of microbial experimental idiosyncrasies that are distinct from host-centric methods. Furthermore, the discoveries of intracellular and intra-metastatic cancer bacteria necessitate fundamental changes in describing clonal evolution and selection, reflecting bidirectional interactions with non-human residents. Reconsidering cancer clonality as a multispecies process similarly holds key implications for understanding metastasis and prognosing therapeutic resistance while providing rational guidance for the next generation of bacterial cancer therapies. Guided by these new findings and challenges, this Review describes opportunities to exploit cancer's metagenome in oncology and proposes an evolutionary framework as a first step towards modeling multispecies cancer clonality. Also see the video abstract here: https://youtu.be/-WDtIRJYZSs.

Although Barrett's metaplasia of the esophagus (BE) is the only known precursor lesion to esophageal adenocarcinomas (EACs), drivers of cellular transformation in BE remain incompletely understood. We use an artificial intelligence-guided network approach to study EAC initiation and progression. Key predictions are subsequently validated in a human organoid model, in patient-derived biopsy specimens of BE, a case-control study of genomics of BE progression, and in a cross-sectional study of 113 patients with BE and EACs. Our model classified healthy esophagus from BE and BE from EACs in several publicly available gene expression data sets (n = 932 samples). The model confirmed that all EACs must originate from BE and pinpointed a CXCL8/IL8↔neutrophil immune microenvironment as a driver of cellular transformation in EACs and gastroesophageal junction adenocarcinomas. This driver is prominent in White individuals but is notably absent in African Americans (AAs). Network-derived gene signatures, independent signatures of neutrophil processes, CXCL8/IL8 expression, and an absolute neutrophil count (ANC) are associated with risk of progression. SNPs associated with changes in ANC by ethnicity (e.g., benign ethnic neutropenia [BEN]) modify that risk. Findings define a racially influenced immunological basis for cell transformation and suggest that BEN in AAs may be a deterrent to BE→EAC progression.

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2-12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.

Circular extrachromosomal DNA (ecDNA) in patient tumors is an important driver of oncogenic gene expression, evolution of drug resistance and poor patient outcomes. Applying computational methods for the detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA-positive medulloblastoma were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. A subset of tumors harbored multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging and CRISPR inhibition experiments in medulloblastoma models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative 'enhancer rewiring' events on ecDNA. This study reveals the frequency and diversity of ecDNA in medulloblastoma, stratified into molecular subgroups, and suggests copy number heterogeneity and enhancer rewiring as oncogenic features of ecDNA.