Dataset Information

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.

ABSTRACT:

Background

Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized diploid cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified.

Results

Tissue sections that fail more frequently show low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces are more likely to show FFPE-specific errors, akin to "edge effects" seen in histology, while the inner samples display no quality degradation related to fixation time.

Conclusions

To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC9241261 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.

Zhang Yifan Y Blomquist Thomas M TM Kusko Rebecca R Stetson Daniel D Zhang Zhihong Z Yin Lihui L Sebra Robert R Gong Binsheng B Lococo Jennifer S JS Mittal Vinay K VK Novoradovskaya Natalia N Yeo Ji-Youn JY Dominiak Nicole N Hipp Jennifer J Raymond Amelia A Qiu Fujun F Arib Hanane H Smith Melissa L ML Brock Jay E JE Farkas Daniel H DH Craig Daniel J DJ Crawford Erin L EL Li Dan D Morrison Tom T Tom Nikola N Xiao Wenzhong W Yang Mary M Mason Christopher E CE Richmond Todd A TA Jones Wendell W Johann Donald J DJ Shi Leming L Tong Weida W Willey James C JC Xu Joshua J

Genome biology 20220629 1

<h4>Background</h4>Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized diploid cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to differen ...[more]

PMID: 35768876

Similar Datasets

Project description:BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.MethodsWe optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.ResultsSamples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with TPM > 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples.ConclusionsWe provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Dataset Information

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.

Background

Results

Conclusions

Publications

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.

Similar Datasets

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