Dataset Information

RNA-Based Detection of Gene Fusions in Formalin-Fixed and Paraffin-Embedded Solid Cancer Samples.

ABSTRACT: Oncogenic gene fusions are important drivers in many cancer types, including carcinomas, with diagnostic and therapeutic implications. Hence, sensitive and rapid methods for parallel profiling in formalin-fixed and paraffin-embedded (FFPE) specimens are needed. In this study we analyzed gene fusions in a cohort of 517 cases where standard treatment options were exhausted. To this end the Archer® DX Solid tumor panel (AMP; 285 cases) and the Oncomine Comprehensive Assay v3 (OCA; 232 cases) were employed. Findings were validated by Sanger sequencing, fluorescence in situ hybridization (FISH) or immunohistochemistry. Both assays demonstrated minimal dropout rates (AMP: 2.4%; n = 7/292, OCA: 2.1%; n = 5/237) with turnaround times of 6-9 working days (median, OCA and AMP, respectively). Hands-on-time for library preparation was 6 h (AMP) and 2 h (OCA). We detected n = 40 fusion-positive cases (7.7%) with TMPRSS2::ERG in prostate cancer being most prevalent (n = 9/40; 22.5%), followed by other gene fusions identified in cancers of unknown primary (n = 6/40; 15.0%), adenoid cystic carcinoma (n = 7/40; 17.5%), and pancreatic cancer (n = 7/40; 17.5%). Our results demonstrate that targeted RNA-sequencing of FFPE samples is feasible, and a well-suited approach for the detection of gene fusions in a routine clinical setting.

SUBMITTER: Kirchner M

PROVIDER: S-EPMC6769558 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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RNA-Based Detection of Gene Fusions in Formalin-Fixed and Paraffin-Embedded Solid Cancer Samples.

Kirchner Martina M Neumann Olaf O Volckmar Anna-Lena AL Stögbauer Fabian F Allgäuer Michael M Kazdal Daniel D Budczies Jan J Rempel Eugen E Brandt Regine R Talla Suranand Babu SB von Winterfeld Moritz M Leichsenring Jonas J Bochtler Tilmann T Krämer Alwin A Springfeld Christoph C Schirmacher Peter P Penzel Roland R Endris Volker V Stenzinger Albrecht A

Cancers 20190905 9

Oncogenic gene fusions are important drivers in many cancer types, including carcinomas, with diagnostic and therapeutic implications. Hence, sensitive and rapid methods for parallel profiling in formalin-fixed and paraffin-embedded (FFPE) specimens are needed. In this study we analyzed gene fusions in a cohort of 517 cases where standard treatment options were exhausted. To this end the Archer<sup>®</sup> DX Solid tumor panel (AMP; 285 cases) and the Oncomine Comprehensive Assay v3 (OCA; 232 ca ...[more]

PMID: 31491926

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Project description:BackgroundWe have developed a gene expression assay (Whole-Genome DASL), capable of generating whole-genome gene expression profiles from degraded samples such as formalin-fixed, paraffin-embedded (FFPE) specimens.Methodology/principal findingsWe demonstrated a similar level of sensitivity in gene detection between matched fresh-frozen (FF) and FFPE samples, with the number and overlap of probes detected in the FFPE samples being approximately 88% and 95% of that in the corresponding FF samples, respectively; 74% of the differentially expressed probes overlapped between the FF and FFPE pairs. The WG-DASL assay is also able to detect 1.3-1.5 and 1.5-2 -fold changes in intact and FFPE samples, respectively. The dynamic range for the assay is approximately 3 logs. Comparing the WG-DASL assay with an in vitro transcription-based labeling method yielded fold-change correlations of R(2) approximately 0.83, while fold-change comparisons with quantitative RT-PCR assays yielded R(2) approximately 0.86 and R(2) approximately 0.55 for intact and FFPE samples, respectively. Additionally, the WG-DASL assay yielded high self-correlations (R(2)>0.98) with low intact RNA inputs ranging from 1 ng to 100 ng; reproducible expression profiles were also obtained with 250 pg total RNA (R(2) approximately 0.92), with approximately 71% of the probes detected in 100 ng total RNA also detected at the 250 pg level. When FFPE samples were assayed, 1 ng total RNA yielded self-correlations of R(2) approximately 0.80, while still maintaining a correlation of R(2) approximately 0.75 with standard FFPE inputs (200 ng).Conclusions/significanceTaken together, these results show that WG-DASL assay provides a reliable platform for genome-wide expression profiling in archived materials. It also possesses utility within clinical settings where only limited quantities of samples may be available (e.g. microdissected material) or when minimally invasive procedures are performed (e.g. biopsied specimens).

Project description:RNA-sequencing (RNA-seq) provides a comprehensive quantification of transcriptomic activities in biological samples. Formalin-Fixed Paraffin-Embedded (FFPE) samples are collected as part of routine clinical procedure, and are the most widely available biological sample format in medical research and patient care. Normalization is an essential step in RNA-seq data analysis. A number of normalization methods, though developed for RNA-seq data from fresh frozen (FF) samples, can be used with FFPE samples as well. The only extant normalization method specifically designed for FFPE RNA-seq data, MIXnorm, which has been shown to outperform the normalization methods, but at the cost of a complex mixture model and a high computational burden. It is therefore important to adapt MIXnorm for simplicity and computational efficiency while maintaining superior performance. Furthermore, it is critical to develop an integrated tool that performs commonly used normalization methods for both FF and FFPE RNA-seq data. We developed a new normalization method for FFPE RNA-seq data, named SMIXnorm, based on a simplified two-component mixture model compared to MIXnorm to facilitate computation. The expression levels of expressed genes are modeled by normal distributions without truncation, and those of non-expressed genes are modeled by zero-inflated Poisson distributions. The maximum likelihood estimates of the model parameters are obtained by a nested Expectation-Maximization algorithm with a less complicated latent variable structure, and closed-form updates are available within each iteration. Real data applications and simulation studies show that SMIXnorm greatly reduces computing time compared to MIXnorm, without sacrificing the performance. More importantly, we developed a web-based tool, RNA-seq Normalization (RSeqNorm), that offers a simple workflow to compute normalized RNA-seq data for both FFPE and FF samples. It includes SMIXnorm and MIXnorm for FFPE RNA-seq data, together with five commonly used normalization methods for FF RNA-seq data. Users can easily upload a raw RNA-seq count matrix and select one of the seven normalization methods to produce a downloadable normalized expression matrix for any downstream analysis. The R package is available at https://github.com/S-YIN/RSEQNORM. The web-based tool, RSeqNorm is available at http://lce.biohpc.swmed.edu/rseqnorm with no restriction to use or redistribute.

Dataset Information

RNA-Based Detection of Gene Fusions in Formalin-Fixed and Paraffin-Embedded Solid Cancer Samples.

Publications

RNA-Based Detection of Gene Fusions in Formalin-Fixed and Paraffin-Embedded Solid Cancer Samples.

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