Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples

Abstract

Background Our objective was to assess whether modifications to a customized targeted RNA sequencing (RNAseq) assay to include unique molecular identifiers (UMIs) that collapse read counts to their source mRNA counts would improve quantification of transcripts from formalin-fixed paraffin-embedded (FFPE) tumor tissue samples. The assay (SET4) includes signatures that measure hormone receptor and PI3-kinase related transcriptional activity (SETER/PR and PI3Kges), and measures expression of selected activating point mutations and key breast cancer genes. Methods Modifications included steps to introduce eight nucleotides-long UMIs during reverse transcription (RT) in bulk solution, followed by polymerase chain reaction (PCR) of labeled cDNA in droplets, with optimization of the polymerase enzyme and reaction conditions. We used Lin’s concordance correlation coefficient (CCC) to measure concordance, including precision (Rho) and accuracy (Bias), and nonparametric tests (Wilcoxon, Levene’s) to compare the modified (NEW) SET4 assay to the original (OLD) SET4 assay and to whole transcriptome RNAseq using RNA from matched fresh frozen (FF) and FFPE samples from 12 primary breast cancers. Results The modified (NEW) SET4 assay measured single transcripts (p< 0.001) and SETER/PR (p=0.002) more reproducibly in technical replicates from FFPE samples. The modified SET4 assay was more precise for measuring single transcripts (Rho 0.966 vs 0.888, p< 0.01) but not multigene expression signatures SETER/PR (Rho 0.985 vs 0.968) or PI3Kges (Rho 0.985 vs 0.946) in FFPE, compared to FF samples. It was also more precise than wtRNAseq of FFPE for measuring transcripts (Rho 0.986 vs 0.934, p< 0.001) and SETER/PR (Rho 0.993 vs 0.915, p=0.004), but not PI3Kges (Rho 0.988 vs 0.945, p=0.051). Accuracy (Bias) was comparable between protocols. Two samples carried a PIK3CA mutation, and measurements of transcribed mutant allele fraction was similar in FF and FFPE samples and appeared more precise with the modified SET4 assay. Amplification efficiency (reads per UMI) was consistent in FF and FFPE samples, and close to the theoretically expected value, when the library size exceeded 400,000 aligned reads. Conclusions Modifications to the targeted RNAseq protocol for SET4 assay significantly increased the precision of UMI-based and reads-based measurements of individual transcripts, multi-gene signatures, and mutant transcript fraction, particularly with FFPE samples.

Assessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing

“…Sequencing was performed using Illumina HiSeq 4000 (Illumina, San Diego, California), with six libraries pooled per lane. Targeted RNA‐seq libraries were prepared incorporating unique molecular identifier (UMI) sequences to label individual mRNA molecules during reverse transcription and a customized droplet‐based protocol for amplification of complementary DNA (cDNA), as described previously 20 . RNA was reverse‐transcribed using UMI‐labeled gene‐specific primers to target the regions of interest.…”

“…Targeted RNA-seq libraries were prepared incorporating unique molecular identifier (UMI) sequences to label individual mRNA molecules during reverse transcription and a customized droplet-based protocol for amplification of complementary DNA (cDNA), as described previously. 20 RNA was reverse-transcribed using UMI-labeled gene-specific primers to target the regions of interest. Purified cDNA was added to a polymerase chain reaction (PCR) master mix and distributed among millions of pico-liter sized droplets using RainDance Source system…”

“…Nine mRNA-based gene signatures were selected to include in the study: EndoPredict (EP), 29 70 genes prognosis profile (GENE70), 30 the 3-gene expression prognostic index using subtypes (GENIUS), 31 genomic grade index (GGI), 32 PIK3CA activation signature (PIK3CAGS), 33 a reduced PIK3CA activation prediction signature (PI3Kges), 20 recurrence score (RS), 34 sensitivity to endocrine therapy index (SET ER/PR ), 12 and tamoxifen resistance signature (TAMR). 35 The EndoPredict, GENE70, GENIUS, GGI, PIK3CAGS, RS, and TAMR scores were calculated using the genefu package in R. 36 The SET ER/PR and PI3Kges scores were calculated from log-transformed read counts from both whole transcriptome and targeted sequencing assays using custom R scripts.…”

Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer

“…For PIK3CA and TILs gene signatures, raw intensity files (.CEL) from each microarray were processed using MAS5.0 to generate probe-level intensities and normalized to a median array intensity of 600, transformed to log2 values, and scaled by the expression levels of 1322 breast cancer reference genes within each sample normalized to median values in a reference cohort 35 . Two PIK3CA-related gene signatures were calculated for each microarray: first, a PIK3CA gene signature that measures transcriptional activity associated with PI3KCA mutation 41 , and secondly, a modification of that first signature that includes only the probe sets robust to technical variation and variation due to tumor heterogeneity 42 . Two TIL gene signatures were calculated for each microarray: a gene signature trained on TIL infiltrate (calculated as the mean gene expression of IGKC, CXCL9, CCL5, and TRBC1 minus the mean gene expression of AK2, APPBP2, ATP5MF, DARS1, LDHA, TRIM2, UBE2Z, UGP2, VDAC2, and WIPF2WIPF2), and a signature to predict high TILs after subsequent neoadjuvant chemotherapy 43 .…”

Pre‐analytical effects on whole transcriptome and targeted RNA sequencing analysis in cytology: The effects of prolonged time in storage of effusion specimens prior to preservation

“…The assay also measures selected point mutations in AKT1, PTEN, and ERBB2, and measures the expression level of other single genes (ESR1, PGR, ERBB2, AURKA, FRFR1). 17 We previously demonstrated that two common cytological preparations of malignant effusion specimens (cytospins fixed in Carnoy's solution and cytospins fixed in 95% EtOH) were similar to optimally prepared fresh frozen (FF) high-quality RNA samples stored in an RNA preservative (RNAlater) and superior to cell blocks (FFPE), ThinPrep, SurePath and air-dried Diff-Quik stained cytospins. 8 Therefore, we compared the three best preparation methods (ie compared Carnoy's solution and 95% EtOH fixed cytospins with FF cell pellet) at different durations of refrigerated storage (day 0, 1, 4, and 7) using wtRNAseq and tRNAseq to measure two multigene expression signatures (SET ER/PR and PI3Kges), molecular subtype, and common activating mutations.…”