FindDNAFusion: An Analytical Pipeline with Multiple Software Tools Improves Detection of Cancer-Associated Gene Fusions from Genomic DNA.

Detection of cancer-associated gene fusions is crucial for diagnosis, prognosis, and treatment selection. Many bioinformatics tools are available for the detection of fusion transcripts by RNA sequencing, but there are fewer well-validated software tools for DNA next-generation sequencing (NGS). A 542-gene solid tumor NGS panel was designed, with exonic probes supplemented with intronic bait probes against genes commonly involved in oncogenic fusions, with a focus on lung cancer. Three software tools for the detecting gene fusions in this DNA-NGS panel were selected and evaluated. The performance of these tools was compared after a pilot study, and each was configured for optimal batch analysis and detection rate. A blacklist for filtering common tool-specific artifacts, and criteria for selecting clinically reportable fusions, were established. Visualization tools for annotating and confirming somatic fusions were applied. Subsequently, a full clinical validation was used for comparing the results to those from in situ hybridization and/or RNA sequencing. With JuLI, Factera, and GeneFuse, 94.1%, 88.2%, and 66.7% of expected fusions were detected, respectively. With a combinatorial pipeline (termed FindDNAFusion), developed by integrating fusion-calling tools with methods for fusion filtering, annotating, and flagging reportable calls, the accuracy of detection of intron-tiled genes was improved to 98.0%. FindDNAFusion is an accurate and efficient tool in detecting somatic fusions in DNA-NGS panels with intron-tiled bait probes when RNA is unavailable.

Samples from patients with AML show high concordance in detection of mutations by NGS at local institutions vs central laboratories.

Next-generation sequencing (NGS) to identify pathogenic mutations is an integral part of acute myeloid leukemia (AML) therapeutic decision-making. The concordance in identifying pathogenic mutations among different NGS platforms at different diagnostic laboratories has been studied in solid tumors but not in myeloid malignancies to date. To determine this interlaboratory concordance, we collected a total of 194 AML bone marrow or peripheral blood samples from newly diagnosed patients with AML enrolled in the Beat AML Master Trial (BAMT) at 2 academic institutions. We analyzed the diagnostic samples from patients with AML for the detection of pathogenic myeloid mutations in 8 genes (DNMT3A, FLT3, IDH1, IDH2, NPM1, TET2, TP53, and WT1) locally using the Hematologic Neoplasm Mutation Panel (50-gene myeloid indication filter) (site 1) or the GeneTrails Comprehensive Heme Panel (site 2) at the 2 institutions and compared them with the central results from the diagnostic laboratory for the BAMT, Foundation Medicine, Inc. The overall percent agreement was over 95% each in all 8 genes, with almost perfect agreement (κ > 0.906) in all but WT1, which had substantial agreement (κ = 0.848) when controlling for site. The minimal discrepancies were due to reporting variants of unknown significance (VUS) for the WT1 and TP53 genes. These results indicate that the various NGS methods used to analyze samples from patients with AML enrolled in the BAMT show high concordance, a reassuring finding given the wide use of NGS for therapeutic decision-making in AML.

Activation of the RAS pathway through uncommon BRAF mutations in mucinous pancreatic cysts without KRAS mutation.

Diagnostic testing of pancreatic cyst fluid obtained by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) has traditionally utilized elevated carcinoembryonic antigen (CEA) (≥192 ng/ml) and cytomorphologic examination to differentiate premalignant mucinous from benign pancreatic cystic lesions (PCLs). Molecular testing for KRAS/GNAS mutations has been shown to improve accuracy of detecting mucinous PCLs. Using a targeted next-generation sequencing (NGS) panel, we assess the status of PCL-associated mutations to improve understanding of the key diagnostic variables. Molecular analysis of cyst fluid was performed on 108 PCLs that had concurrent CEA and/or cytological analysis. A 48-gene NGS assay was utilized, which included genes commonly mutated in mucinous PCLs such as GNAS, KRAS, CDKN2A, and TP53. KRAS and/or GNAS mutations were seen in 59 of 68 (86.8%) cases with multimodality diagnosis of a mucinous PCL. Among 31 patients where surgical histopathology was available, the sensitivity, specificity, and diagnostic accuracy of NGS for the diagnosis of mucinous PCL was 88.5%, 100%, and 90.3%, respectively. Cytology with mucinous/atypical findings were found in only 29 of 62 cases (46.8%), with fluid CEA elevated in 33 of 58 cases (56.9%). Multiple KRAS mutations at different variant allele frequencies were seen in seven cases favoring multiclonal patterns, with six of them showing at least two separate PCLs by imaging. Among the 6 of 10 cases with GNAS + /KRAS- results, uncommon, non-V600E exon 11/15 hotspot BRAF mutations were identified. The expected high degree of accuracy of NGS detection of KRAS and/or GNAS mutations for mucinous-PCLs, as compared with CEA and cytological examination, was demonstrated. Multiple KRAS mutations correlated with multifocal cysts demonstrated by radiology. In IPMNs that lacked KRAS mutations, the concurring BRAF mutations with GNAS mutations supports an alternate mechanism of activation in the Ras pathway.