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

Whole-genome sequencing provides new insights into the clonal architecture of Barrett's esophagus and esophageal adenocarcinoma

The molecular genetic relationship between esophageal adenocarcinoma (EAC) and its precursor lesion, Barrett's esophagus, is poorly understood. Using whole-genome sequencing on 23 paired Barrett's esophagus and EAC samples, together with one in-depth Barrett's esophagus case study sampled over time and space, we have provided the following new insights: (i) Barrett's esophagus is polyclonal and highly mutated even in the absence of dysplasia; (ii) when cancer develops, copy number increases and heterogeneity persists such that the spectrum of mutations often shows surprisingly little overlap between EAC and adjacent Barrett's esophagus; and (iii) despite differences in specific coding mutations, the mutational context suggests a common causative insult underlying these two conditions. From a clinical perspective, the histopathological assessment of dysplasia appears to be a poor reflection of the molecular disarray within the Barrett's epithelium, and a molecular Cytosponge technique overcomes sampling bias and has the capacity to reflect the entire clonal architecture.</p

Disentangling oncogenic amplicons in esophageal adenocarcinoma

Esophageal adenocarcinoma is a prominent example of cancer characterized by frequent amplifications in oncogenes. However, the mechanisms leading to amplicons that involve breakage-fusion-bridge cycles and extrachromosomal DNA are poorly understood. Here, we use 710 esophageal adenocarcinoma cases with matched samples and patient-derived organoids to disentangle complex amplicons and their associated mechanisms. Short-read sequencing identifies ERBB2, MYC, MDM2, and HMGA2 as the most frequent oncogenes amplified in extrachromosomal DNAs. We resolve complex extrachromosomal DNA and breakage-fusion-bridge cycles amplicons by integrating of de-novo assemblies and DNA methylation in nine long-read sequenced cases. Complex amplicons shared between precancerous biopsy and late-stage tumor, an enrichment of putative enhancer elements and mobile element insertions are potential drivers of complex amplicons’ origin. We find that patient-derived organoids recapitulate extrachromosomal DNA observed in the primary tumors and single-cell DNA sequencing capture extrachromosomal DNA-driven clonal dynamics across passages. Prospectively, long-read and single-cell DNA sequencing technologies can lead to better prediction of clonal evolution in esophageal adenocarcinoma