Markus, Havell

Genome-wide fragmentation patterns in cell-free DNA (cfDNA) in plasma are strongly influenced by cellular origin due to variation in chromatin accessibility across cell types. Such differences between healthy and cancer cells provide the opportunity for development of novel cancer diagnostics. Here, we investigated whether analysis of cfDNA fragment end positions and their surrounding DNA sequences reveals the presence of tumor-derived DNA in blood. We performed genome-wide analysis of cfDNA from 521 samples and analyzed sequencing data from an additional 2147 samples, including healthy individuals and patients with 11 different cancer types. We developed a metric based on genome-wide differences in fragment positioning, weighted by fragment length and GC content [information-weighted fraction of aberrant fragments (iwFAF)]. We observed that iwFAF strongly correlated with tumor fraction, was higher for DNA fragments carrying somatic mutations, and was higher within genomic regions affected by copy number amplifications. We also calculated sample-level means of nucleotide frequencies observed at genomic positions spanning fragment ends. Using a combination of iwFAF and nine nucleotide frequencies from three positions surrounding fragment ends, we developed a machine learning model to differentiate healthy individuals from patients with cancer. We observed an area under the receiver operative characteristic curve (AUC) of 0.91 for detection of cancer at any stage and an AUC of 0.87 for detection of stage I cancer. Our findings remained robust with as few as 1 million fragments analyzed per sample, demonstrating that analysis of fragment ends can become a cost-effective and accessible approach for cancer detection and monitoring.

e16185 Background: Comprehensive sequencing efforts have identified fibroblast growth factor receptor (FGFR) translocations in numerous cancers. FGFR2 fusions were recently identified as an actionable therapeutic target in ̃17% of cholangiocarcinoma patients, predominantly found in patients with intrahepatic cholangiocarcinoma. Genomic partners for FGFR fusions are variable. In addition, obtaining high yield tissue biopsies for CCA remains challenging and tumor tissue available for molecular analyses is scarce. When combined, these two factors make detection of FGFR fusions in CCA challenging. An accurate molecular assay to detect FGFR fusions in CCA could improve utilization of FGFR-targeted therapies. Methods: The objective of our study was to develop an approach for targeted RNA analysis to improve sensitivity for FGFR fusion detection from limited tumor material. We adapted the sensitive targeted digital sequencing (TARDIS) approach recently developed in our lab for analysis of RNA. This approach utilizes a combination of open-ended targeted amplification followed by ligation, enabling detection of tyrosine kinase fusions without prior knowledge of the precise sequence of the fusion breakpoint or identity of the fusion partner. For evaluation of analytical performance, we analyzed RNA from a CCA organoid model with a known FGFR2 fusion, and Seraseq Fusion RNA Mix v3 Reference Material with two known FGFR3 fusions. Results: Without prior knowledge the partner or coordinates of the fusion breakpoint, we detected an FGFR2-KIF5C fusion in RNA from a CCA organoid model. The fusion breakpoint coordinates predicted by TARDIS-RNA were validated by comparison with RNA-Seq. To assess sensitivity and quantitative performance of the assay, we analyzed a serial dilution of the reference RNA sample from Seraseq with concentration of RNA molecules representing candidate fusions verified by digital PCR. Using TARDIS-RNA to analyze replicates with 5 ng RNA input, we were able to detect candidate fusions represented by as few as 2.7 fusion molecules on average. Concentrations of fusion molecules measured using the two methods were highly correlated (R = 0.96). Conclusions: These results demonstrate sensitivity and quantitative performance of a targeted RNA sequencing assay to detect and quantify FGFR fusions in tumor specimen from intrahepatic cholangiocarcinoma. On-going work is focused on further evaluating assay performance and characterizing FGFR fusions using additional tissue specimen.

293 Background: Cholangiocarcinoma (CCA) is a deadly cancer with ~20% five year survival. Obtaining tissue to confirm diagnosis of CCA is often challenging. This also limits the use of tumor genotyping that could guide potential molecularly targeted treatment (such as FGFR inhibitors for a subset of cases). We investigated whether circulating tumor DNA (ctDNA) analysis in plasma is feasible for noninvasive tumor genotyping in patients with advanced CCA. Methods: We collected and processed plasma samples for ctDNA analysis from 17 patients with CCA at presentation and from 11 healthy volunteers. Following cell-free DNA extraction and quality assessment using digital PCR, we performed low-pass, shallow whole genome sequencing (sWGS). We analyzed sequencing data to identify copy number aberrations and quantify tumor fraction in plasma using recently published computational approaches. Results: Median total cfDNA concentration in patients with CCA was 7,003 genome equivalents (GEs)/mL plasma (range: 1,512- 107,707 GEs/mL) and significantly higher than healthy volunteers (two tailed t-test p < 0.04, median: 1,658 GEs/mL, range: 661-4,938 GEs/mL). We successfully sequenced all tumor libraries, generating a median of 173 million paired-end reads. ctDNA was detectable in 10/17 samples using sWGS. In these 10 samples, median tumor fraction in plasma DNA was 7.1% (range: 3.9%-44.6%). We found recurrent copy number aberrations expected in CCA including 1q gain in 80%, 7p gain in 50%, 1p loss in 70% and 3p loss in 50% of cases. Conclusions: ctDNA analysis for noninvasive tumor genotyping is feasible in patients with advanced cholangiocarcinoma. On-going work is focused on expanding these results using targeted and whole-exome sequencing.