Low-cost and clinically applicable copy number profiling using repeat DNA.

BACKGROUND: Somatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell's genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling. RESULTS: We present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman's rank correlation coefficient, rs=0.94) between conliga's inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (rs=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (rs=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga's hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information. CONCLUSIONS: We show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

Genomics of Esophageal Cancer and Biomarkers for Early Detection.

In-depth molecular characterization of esophageal oncogenesis has improved over the recent years. Advancement in molecular biology and bioinformatics has led to better understanding of its genomic landscape. More specifically, analysis of its pathogenesis at the genetic level has uncovered the involvement of a number of tumor suppressor genes, cell cycle regulators, and receptor tyrosine kinases. Due to its poor prognosis, the development of clinically applicable biomarkers for diagnosis, progression, and treatment has been the focus of many research studies concentrating on upper gastrointestinal malignancies. As in other cancers, early detection and subsequent intervention of the preneoplastic condition significantly improves patient outcomes. Currently, clinically approved surveillance practices heavily depend on expensive, invasive, and sampling-error-prone endoscopic procedures. There is, therefore, a great demand to establish clearly reliable biomarkers that could identify those patients at higher risk of neoplastic progression and hence would greatly benefit from further monitoring and/or intervention. This chapter will present the most recent advances in the analysis of the esophageal cancer genome serving as basis for biomarker development.

Preexisting oncogenic events impact trastuzumab sensitivity in ERBB2-amplified gastroesophageal adenocarcinoma.

Patients with gastric and esophageal (GE) adenocarcinoma tumors in which the oncogene ERBB2 has been amplified are routinely treated with a combination of cytotoxic chemotherapy and the ERBB2-directed antibody trastuzumab; however, the addition of trastuzumab, even when tested in a selected biomarker-positive patient population, provides only modest survival gains. To investigate the potential reasons for the modest impact of ERBB2-directed therapies, we explored the hypothesis that secondary molecular features of ERBB2-amplified GE adenocarcinomas attenuate the impact of ERBB2 blockade. We analyzed genomic profiles of ERBB2-amplified GE adenocarcinomas and determined that the majority of ERBB2-amplified tumors harbor secondary oncogenic alterations that have the potential to be therapeutically targeted. These secondary events spanned genes involved in cell-cycle regulation as well as phosphatidylinositol-3 kinase and receptor tyrosine kinase signaling. Using ERBB2-amplified cell lines, we demonstrated that secondary oncogenic events could confer resistance to ERBB2-directed therapies. Moreover, this resistance could be overcome by targeting the secondary oncogene in conjunction with ERBB2-directed therapy. EGFR is commonly coamplified with ERBB2, and in the setting of ERBB2 amplification, higher EGFR expression appears to mark tumors with greater sensitivity to dual EGFR/ERBB2 kinase inhibitors. These data suggest that combination inhibitor strategies, guided by secondary events in ERBB2-amplified GE adenocarcinomas, should be evaluated in clinical trials.