scholarly journals Functional comparison of exome capture-based methods for transcriptomic profiling of formalin-fixed paraffin-embedded tumors

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Kyrillus S. Shohdy ◽  
Rohan Bareja ◽  
Michael Sigouros ◽  
David C. Wilkes ◽  
Princesca Dorsaint ◽  
...  
Keyword(s):  
Molecular Subtype ◽  
Expression Profiles ◽  
Exome Capture ◽  
Clinical Samples ◽  
Precision Oncology ◽  
Rna Seq ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Fresh Frozen ◽  
Formalin Fixed

AbstractThe availability of fresh frozen (FF) tissue is a barrier for implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. We performed transcriptomic analysis of 32 FFPE tumor samples from 11 patients using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to the TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. The Spearman’s correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72–0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable gene transcripts, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen’s k = 0.7, p < 0.01). The Agilent and IDT assays detected all the clinically relevant fusions that were initially identified in FF-TruSeq. All FFPE exome capture-based methods had comparable performance and concordance with FF-TruSeq. Our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

scholarly journals Functional Comparison of Different Exome Capture-based Methods for Transcriptomic Profiling of Formalin-Fixed Paraffin-Embedded Tumor Samples

2021 ◽  
Author(s):  
Kyrillus S. Shohdy ◽  
Rohan Bareja ◽  
Michael Sigouros ◽  
David C. Wilkes ◽  
Princesca Dorsaint ◽  
...  
Keyword(s):  
Gene Expression ◽  
Exome Capture ◽  
Rna Seq ◽  
Transcriptomic Profiling ◽  
Immune Genes ◽  
Formalin Fixed Paraffin ◽  
Ffpe Tumor ◽  
Formalin Fixed Paraffin Embedded ◽  
Fresh Frozen ◽  
Formalin Fixed

AbstractBackgroundThe need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are processed in clinical laboratories and stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture has recently emerged as a promising approach for RNA-seq from FFPE samples. Multiple exome capture platforms are now available. However, their performances have not been systematically compared.MethodsTranscriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features, including the expression of key immune genes, expression outliers often associated with actionable genes, gene expression-based subtypes, and fusions using each of these capture methods.ResultsThe Spearman’s correlation coefficients between global expression profiles of the three capture-based methods and matched FF tumor samples, analyzed using TruSeq RNA-seq, were high (rho = 0.72-0.9, p < 0.05). There was a significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05). All three exome capture-based methods reliably detected the outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG, initially detected in FF-TruSeq. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtyping agreement with FF-TruSeq (Cohen’s k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions which were initially identified in FF-TruSeq.ConclusionAll exome capture-based methods had comparable performance and concordance with FF-TruSeq. These findings provide a path for the transcriptomic profiling of vast numbers of FFPE currently stored in biobanks. For specific applications such as fusion detection and gene expression-based subtyping, some methods performed better. By enabling the interrogation of FFPE tumor samples, our findings open the door for implementing RNA-seq in the clinic to guide precision oncology approaches.

scholarly journals Mining the archives: a cross-platform analysis of gene expression profiles in archival formalin-fixed paraffin-embedded (FFPE) tissue

2015 ◽  
Author(s):  
Anna Francina Webster ◽  
Paul Zumbo ◽  
Jennifer Fostel ◽  
Jorge Gandara ◽  
Susan D Hester ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Ffpe Tissue ◽  
Rna Seq ◽  
Preservation Method ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

Formalin-fixed paraffin-embedded (FFPE) tissue samples represent a potentially invaluable resource for transcriptomic-based research into the molecular basis of disease. However, use of FFPE samples in gene expression studies has been limited by technical challenges resulting from degradation of nucleic acids. Here we evaluated gene expression profiles derived from fresh-frozen (FRO) and FFPE mouse liver tissues using two DNA microarray protocols and two whole transcriptome sequencing (RNA-seq) library preparation methodologies. The ribo-depletion protocol outperformed the other three methods by having the highest correlations of differentially expressed genes (DEGs) and best overlap of pathways between FRO and FFPE groups. We next tested the effect of sample time in formalin (18 hours or 3 weeks) on gene expression profiles. Hierarchical clustering of the datasets indicated that test article treatment, and not preservation method, was the main driver of gene expression profiles. Meta- and pathway analyses indicated that biological responses were generally consistent for 18-hour and 3-week FFPE samples compared to FRO samples. However, clear erosion of signal intensity with time in formalin was evident, and DEG numbers differed by platform and preservation method. Lastly, we investigated the effect of age in FFPE block on genomic profiles. RNA-seq analysis of 8-, 19-, and 26-year-old control blocks using the ribo-depletion protocol resulted in comparable quality metrics, including expected distributions of mapped reads to exonic, UTR, intronic, and ribosomal fractions of the transcriptome. Overall, our results suggest that FFPE samples are appropriate for use in genomic studies in which frozen samples are not available, and that ribo-depletion RNA-seq is the preferred method for this type of analysis in archival and long-aged FFPE samples.

scholarly journals MIXnorm: normalizing RNA-seq data from formalin-fixed paraffin-embedded samples

2020 ◽  
Vol 36 (11) ◽  
pp. 3401-3408 ◽  
Author(s):  
Shen Yin ◽  
Xinlei Wang ◽  
Gaoxiang Jia ◽  
Yang Xie
Keyword(s):  
Maximum Likelihood Estimates ◽  
Supplementary Information ◽  
Rna Seq ◽  
Computationally Efficient ◽  
Component Mixture ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Fresh Frozen ◽  
Truncated Normal ◽  
Formalin Fixed

Abstract Motivation Recent studies have shown that RNA-sequencing (RNA-seq) can be used to measure mRNA of sufficient quality extracted from formalin-fixed paraffin-embedded (FFPE) tissues to provide whole-genome transcriptome analysis. However, little attention has been given to the normalization of FFPE RNA-seq data, a key step that adjusts for unwanted biological and technical effects that can bias the signal of interest. Existing methods, developed based on fresh-frozen or similar-type samples, may cause suboptimal performance. Results We proposed a new normalization method, labeled MIXnorm, for FFPE RNA-seq data. MIXnorm relies on a two-component mixture model, which models non-expressed genes by zero-inflated Poisson distributions and models expressed genes by truncated normal distributions. To obtain maximum likelihood estimates, we developed a nested EM algorithm, in which closed-form updates are available in each iteration. By eliminating the need for numerical optimization in the M-step, the algorithm is easy to implement and computationally efficient. We evaluated MIXnorm through simulations and cancer studies. MIXnorm makes a significant improvement over commonly used methods for RNA-seq expression data. Availability and implementation R code available at https://github.com/S-YIN/MIXnorm. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A Comparison of RNA-Seq Results from Paired Formalin-Fixed Paraffin-Embedded and Fresh-Frozen Glioblastoma Tissue Samples

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0170632 ◽  
Author(s):  
Anna Esteve-Codina ◽  
Oriol Arpi ◽  
Maria Martinez-García ◽  
Estela Pineda ◽  
Mar Mallo ◽  
...  
Keyword(s):  
Rna Seq ◽  
Tissue Samples ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Fresh Frozen ◽  
Formalin Fixed

scholarly journals Impact of RNA Extraction and Target Capture Methods on RNA Sequencing Using Formalin-Fixed, Paraffin Embedded Tissues

2019 ◽  
Author(s):  
Christopher A. Hilker ◽  
Aditya V. Bhagwate ◽  
Jin Sung Jang ◽  
Jeffrey G Meyer ◽  
Asha A. Nair ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fusion Gene ◽  
Rna Extraction ◽  
Extraction Methods ◽  
Rna Seq ◽  
Gene Detection ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Whole Transcriptome ◽  
Formalin Fixed

AbstractFormalin fixed paraffin embedded (FFPE) tissues are commonly used biospecimen for clinical diagnosis. However, RNA degradation is extensive when isolated from FFPE blocks making it challenging for whole transcriptome profiling (RNA-seq). Here, we examined RNA isolation methods, quality metrics, and the performance of RNA-seq using different approaches with RNA isolated from FFPE and fresh frozen (FF) tissues. We evaluated FFPE RNA extraction methods using six different tissues and five different methods. The reproducibility and quality of the prepared libraries from these RNAs were assessed by RNA-seq. We next examined the performance and reproducibility of RNA-seq for gene expression profiling with FFPE and FF samples using targeted (Kinome capture) and whole transcriptome capture based sequencing. Finally, we assessed Agilent SureSelect All-Exon V6+UTR capture and the Illumina TruSeq RNA Access protocols for their ability to detect known gene fusions in FFPE RNA samples. Although the overall yield of RNA varied among extraction methods, gene expression profiles generated by RNA-seq were highly correlated (>90%) when the input RNA was of sufficient quality (≥DV200 30%) and quantity (≥ 100 ng). Using gene capture, we observed a linear relationship between gene expression levels for shared genes that were captured using either All-Exon or Kinome kits. Gene expression correlations between the two capture-based approaches were similar using RNA from FFPE and FF samples. However, TruSeq RNA Access protocol provided significantly higher exon and junction reads when compared to the SureSelect All-Exon capture kit and was more sensitive for fusion gene detection. Our study established pre and post library construction QC parameters that are essential to reproducible RNA-seq profiling using FFPE samples. We show that gene capture based NGS sequencing is an efficient and highly reproducible strategy for gene expression measurements as well as fusion gene detection.

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