Pathways of Progression From Intraductal Papillary Mucinous Neoplasm to Pancreatic Ductal Adenocarcinoma Based on Molecular Features.

BACKGROUND & AIMS: Intraductal papillary mucinous neoplasms (IPMNs) are regarded as precursors of pancreatic ductal adenocarcinomas (PDAs), but little is known about the mechanism of progression. This makes it challenging to assess cancer risk in patients with IPMNs. We investigated associations of IPMNs with concurrent PDAs by genetic and histologic analyses. METHODS: We obtained 30 pancreatic tissues with concurrent PDAs and IPMNs, and 168 lesions, including incipient foci, were mapped, microdissected, and analyzed for mutations in 18 pancreatic cancer-associated genes and expression of tumor suppressors. RESULTS: We determined the clonal relatedness of lesions, based on driver mutations shared by PDAs and concurrent IPMNs, and classified the lesions into 3 subtypes. Twelve PDAs contained driver mutations shared by all concurrent IPMNs, which we called the sequential subtype. This subset was characterized by less diversity in incipient foci with frequent GNAS mutations. Eleven PDAs contained some driver mutations that were shared with concurrent IPMNs, which we called the branch-off subtype. In this subtype, PDAs and IPMNs had identical KRAS mutations but different GNAS mutations, although the lesions were adjacent. Whole-exome sequencing and methylation analysis of these lesions indicated clonal origin with later divergence. Ten PDAs had driver mutations not found in concurrent IPMNs, called the de novo subtype. Expression profiles of TP53 and SMAD4 increased our ability to differentiate these subtypes compared with sequencing data alone. The branch-off and de novo subtypes had substantial heterogeneity among early clones, such as differences in KRAS mutations. Patients with PDAs of the branch-off subtype had a longer times of disease-free survival than patients with PDAs of the de novo or the sequential subtypes. CONCLUSIONS: Detailed histologic and genetic analysis of PDAs and concurrent IPMNs identified 3 different pathways by which IPMNs progress to PDAs-we call these the sequential, branch-off, and de novo subtypes. Subtypes might be associated with clinical and pathologic features and be used to select surveillance programs for patients with IPMNs.

Performance of Oncomine Fusion Transcript kit for formalin-fixed, paraffin-embedded lung cancer specimens.

Gene fusions play an important role in the carcinogenesis of lung adenocarcinoma. The recent association of four oncogenic driver genes, ALK, ROS1, RET, and NTRK1, as lung tumor predictive biomarkers has increased the need for precision medicine. We used formalin-fixed, paraffin-embedded tissue samples of non-small cell lung cancer from 150 EGFR mutation-negative cases and 10 fusion status-known cases and compared the performance of the Oncomine Dx Fusion Transcript Test (ODxFT) with FISH break-apart for the detection of ALK, RET, and ROS1 fusion genes. RNA was extracted from the paraffin-embedded tissue samples with or without macrodissection under hematoxylin and eosin staining, and the ALK fusion gene was independently determined using these assays. Fusion detection analyses were successfully carried out using ODxFT in 150 cases, with only one invalid case. ALK fusion genes were detected at a frequency of 7.3% (11/150) in the lung cancer specimens. Concordance rate between the ODxFT and ALK-FISH analyses was 99.3% (148/149). Sensitivity and specificity were 91.7% and 99.3%, respectively. All the samples with a known fusion status were accurately matched between the two assays. Our results show a high concordance rate between the ODxFT and ALK-FISH analyses. ODxFT was thus validated as an effective method for detecting clinically significant ALK fusion genes in paraffin-embedded tissue samples.

Simultaneous genomic identification and profiling of a single cell using semiconductor-based next generation sequencing.

Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line) were used as a model. Single-cell capture was performed using laser capture microdissection (LCM) with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈ 10(6) cells) were subjected to whole genome amplification (WGA). For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel) was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 10(31-35). For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100 × were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100 × were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.