Abstract 175: Illumina RNA-sequencing for biomarker analysis from FFPE and fresh frozen tumor specimens
Biomarkers developed from DNA sequencing have improved the accuracy of selecting treatment regimens for oncology patients, such as tumor mutational burden to predict immune checkpoint inhibitor (ICI) response in metastatic non-small cell lung cancer and melanoma. However, mounting evidence demonstra...
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Veröffentlicht in: | Cancer research (Chicago, Ill.) Ill.), 2020-08, Vol.80 (16_Supplement), p.175-175 |
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Zusammenfassung: | Biomarkers developed from DNA sequencing have improved the accuracy of selecting treatment regimens for oncology patients, such as tumor mutational burden to predict immune checkpoint inhibitor (ICI) response in metastatic non-small cell lung cancer and melanoma. However, mounting evidence demonstrates the need for additional biomarkers to identify patients that could benefit from ICIs. Paired DNA and RNA sequencing have the potential to improve patient diagnosis and treatment selection by providing a more comprehensive view of the tumor biology than DNA sequencing alone. Most next-generation sequencing (NGS) diagnostics have primarily been DNA-based assays with limited, if any, scope in biomarkers derived from RNA. Here, tumor RNA profiling for gene expression and gene fusion detection are evaluated with two Illumina RNA-seq applications: RNA exome enrichment and whole transcriptome sequencing (WTS).
RNA exome enriched libraries were prepared with Illumina® TruSeq™ RNA Exome or a modified version of the Illumina TruSight™ Oncology RNA library preparation. WTS libraries were prepared with Illumina TruSeq Stranded Total RNA, a workflow that enables sequencing coding and non-coding transcripts. RNA of variable quality derived from FFPE and fresh frozen tumor tissue, and commercial RNA controls were titrated to determine optimal input quantity. Stranded and non-stranded RNA library preparation workflows were evaluated for differences in gene expression. Gene expression and fusion calling performance were evaluated for each RNA-seq application.
A comparison of RNA exome to WTS demonstrated robust performance for tumor RNA profiling. Optimal RNA input was 40ng for RNA Exome and 100ng for WTS, regardless of input type. Gene expression values for exome-enriched and whole transcriptome libraries were reproducible (r > 0.99 for technical replicates), with minimal differentially expressed genes between coding regions of both RNA-seq workflows (r > 0.83). WTS yielded up to 2-fold more transcripts with the addition of non-coding RNAs that were not captured by the RNA coding exome panel. Commercial RNA controls and FFPE tumor RNAs with validated fusions were used for evaluating fusion calling performance from RNA exome and whole transcriptome libraries. Both workflows yielded adequate library diversity for calling clinically relevant fusions. However, RNA exome enrichment fusion calling sensitivity (84.4%) was impacted when one or both fusion partners were not targeted |
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ISSN: | 0008-5472 1538-7445 |
DOI: | 10.1158/1538-7445.AM2020-175 |