Abstract 840: Pathway enrichment analysis of gene expression data from formalin-fixed paraffin embedded (FFPE) samples using the GeoMx™ DSP Platform

2020 ◽  
Author(s):  
Tressa R. Hood ◽  
Jason Reeves ◽  
Zach Norgaard ◽  
Margaret Hoang ◽  
Sarah Warren ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Data ◽  
Pathway Enrichment ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

Validation of the Lung Subtyping Panel in Multiple Fresh-Frozen and Formalin-Fixed, Paraffin-Embedded Lung Tumor Gene Expression Data Sets

2015 ◽  
Vol 140 (6) ◽  
pp. 536-542 ◽  
Author(s):  
Hawazin Faruki ◽  
Gregory M. Mayhew ◽  
Cheng Fan ◽  
Matthew D. Wilkerson ◽  
Scott Parker ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Lung Tumor ◽  
Gene Expression Signature ◽  
Data Sets ◽  
Expression Data ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Fresh Frozen ◽  
Formalin Fixed

Context A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription–polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly when classification by standard methods is challenging.

Gene Expression Profiling Using the Illumina ‘DASL’ Platform on RNA Extracted From Formalin Fixed Paraffin Embedded (FFPE) Tissue Identifies Distinct Prognostic Groups In CHOP-R Treated DLBCL

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2485-2485
Author(s):  
Sharon Barrans ◽  
Lisa Worrillow ◽  
Matthew Care ◽  
Simon Crouch ◽  
Alex Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Gene Expression Data ◽  
Expression Profiling ◽  
Expression Data ◽  
Formalin Fixed Paraffin ◽  
Prognostic Groups ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

Abstract Abstract 2485 Diffuse large B cell lymphoma (DLBCL) is a heterogenous disease, which has been subclassified into germinal centre (GCB) and activated B-cell (ABC) type using gene expression profiling. This has been shown to separate DLBCL into distinct prognostic sub-groups in patients treated with either CHOP or CHOP-R therapy. Previous studies have required the use of fresh or frozen samples for the extraction of RNA of sufficient quality to permit whole genome expression analysis. The Illumina ‘DASL' platform allows for highly reproducible gene expression data to be generated from FFPE material, which opens up large series' of retrospective data for detailed expression studies. The aim of this study was therefore to determine whether the Illumina DASL platform could yield reproducible results on formalin fixed paraffin embedded (FFPE) biopsies from a large series of archival CHOP-R treated DLBCL samples. RNA was extracted from paraffin sections using the Ambion Recoverall extraction kit, with 179/206 (87%) of cases yielding >200ng of RNA sufficient for DASL analysis. The DASL assay was performed according to Illumina protocols. Using stringent exclusion criteria, 157/179 (88%) cases yielding results that were considered to be of sufficiently high quality to be included in the analysis. To fully assess the reproducibility of the assay, 35 cases were analysed on 2–8 occasions across multiple experimental days. Using Pearson's correlation, with full-linkage clustering, four discrete clusters were identified (n=28, 40, 46 and 43). Of important note, 95% of the samples were seen to cluster more tightly with their repeats than with any other sample, with all duplicated samples being called in the same cluster with 100% accuracy, suggesting that the technique is highly reproducible. Univariate Kaplan-Meier survival analysis showed that the clusters identified patients with very different outcomes. Two of the clusters showed identical survival curves and therefore these clusters were merged to give 3 clusters with 2-year overall survivals (OS) of 51% (n=71), 65% (n=46) and 77% (n=40), log rank p=0.03, with a 3.7 year follow-up. This data supports the use of gene expression profiling to classify DLBCL patients into clinically relevant prognostic groups. The Illumina DASL assay allows for highly reproducible gene expression data to be produced in valuable, archival data series, and also in the context of clinical trials, where the majority of the tissue available for study is FFPE. The patients identified in this study as having a sub-optimal response to CHOP-R should be considered for alternative therapies, which should be validated in the context of a clinical trial. Disclosures: No relevant conflicts of interest to declare.

scholarly journals BNrich: A Bayesian network approach to the pathway enrichment analysis

2020 ◽  
Author(s):  
Samaneh Maleknia ◽  
Ali Sharifi-Zarchi ◽  
Vahid Rezaei Tabar ◽  
Mohsen Namazi ◽  
Kaveh Kavousi
Keyword(s):  
Gene Expression ◽  
Bayesian Network ◽  
Signaling Pathway ◽  
Gene Expression Data ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Data ◽  
Pathway Enrichment ◽  
Topological Features ◽  
Biological Studies

AbstractMotivationOne of the most popular techniques in biological studies for analyzing high throughput data is pathway enrichment analysis (PEA). Many researchers apply the existing methods without considering the topology of pathways or at least they have overlooked a significant part of the structure, which may reduce the accuracy and generalizability of the results. Developing a new approach while considering gene expression data and topological features like causal relations regarding edge directions will help the investigators to achieve more accurate results.ResultsWe proposed a new pathway enrichment analysis based on Bayesian network (BNrich) as an approach in PEA. To this end, the cycles were eliminated in 187 KEGG human signaling pathways concerning intuitive biological rules and the Bayesian network structures were constructed. The constructed networks were simplified by the Least Absolute Shrinkage Selector Operator (LASSO), and their parameters were estimated using the gene expression data. We finally prioritize the impacted pathways by Fisher’s Exact Test on significant parameters. Our method integrates both edge and node related parameters to enrich modules in the affected signaling pathway network. In order to evaluate the proposed method, consistency, discrimination, false positive rate and empirical P-value criteria were calculated, and the results are compared to well-known enrichment methods such as signaling pathway impact analysis (SPIA), bi-level meta-analysis (BLMA) and topology-based pathway enrichment analysis (TPEA).AvailabilityThe R package is available on carn.

scholarly journals The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Michal Marczyk ◽  
Chunxiao Fu ◽  
Rosanna Lau ◽  
Lili Du ◽  
Alexander J. Trevarton ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Rna Sequencing ◽  
Rna Extraction ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
The Impact ◽  
Formalin Fixed

Abstract Background Utilization of RNA sequencing methods to measure gene expression from archival formalin-fixed paraffin-embedded (FFPE) tumor samples in translational research and clinical trials requires reliable interpretation of the impact of pre-analytical variables on the data obtained, particularly the methods used to preserve samples and to purify RNA. Methods Matched tissue samples from 12 breast cancers were fresh frozen (FF) and preserved in RNAlater or fixed in formalin and processed as FFPE tissue. Total RNA was extracted and purified from FF samples using the Qiagen RNeasy kit, and in duplicate from FFPE tissue sections using three different kits (Norgen, Qiagen and Roche). All RNA samples underwent whole transcriptome RNA sequencing (wtRNAseq) and targeted RNA sequencing for 31 transcripts included in a signature of sensitivity to endocrine therapy. We assessed the effect of RNA extraction kit on the reliability of gene expression levels using linear mixed-effects model analysis, concordance correlation coefficient (CCC) and differential analysis. All protein-coding genes in the wtRNAseq and three gene expression signatures for breast cancer were assessed for concordance. Results Despite variable quality of the RNA extracted from FFPE samples by different kits, all had similar concordance of overall gene expression from wtRNAseq between matched FF and FFPE samples (median CCC 0.63–0.66) and between technical replicates (median expression difference 0.13–0.22). More than half of genes were differentially expressed between FF and FFPE, but with low fold change (median |LFC| 0.31–0.34). Two out of three breast cancer signatures studied were highly robust in all samples using any kit, whereas the third signature was similarly discordant irrespective of the kit used. The targeted RNAseq assay was concordant between FFPE and FF samples using any of the kits (CCC 0.91–0.96). Conclusions The selection of kit to purify RNA from FFPE did not influence the overall quality of results from wtRNAseq, thus variable reproducibility of gene signatures probably relates to the reliability of individual gene selected and possibly to the algorithm. Targeted RNAseq showed promising performance for clinical deployment of quantitative assays in breast cancer from FFPE samples, although numerical scores were not identical to those from wtRNAseq and would require calibration.

scholarly journals Comparative pathway enrichment analysis in gastrointestinal cell lines Caco-2, HT-29, HEPG2, and colon fibroblasts using a custom expression panel for tight-junction and cytoskeletal regulatory genes

2019 ◽  
Author(s):  
JM Robinson
Keyword(s):  
Gene Expression ◽  
Comparative Analysis ◽  
Tight Junction ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Intestinal Epithelial ◽  
Expression Data ◽  
Pathway Enrichment ◽  
Ht 29

AbstractThis brief report details results from a comparative analysis of Nanostring expression data between cell lines HEPG2, Caco-2, HT-29, and colon fibroblasts. Raw and normalized data are available publicly in the NCBI GEO/Bioproject databases. Results identify cell-line specific variations in gene expression relevant to intestinal epithelial function.

scholarly journals Biological Validation of RNA Sequencing Data From Formalin-Fixed Paraffin-Embedded Primary Melanomas

2018 ◽  
pp. 1-19 ◽  
Author(s):  
Lawrence N. Kwong ◽  
Mariana Petaccia De Macedo ◽  
Lauren Haydu ◽  
Aron Y. Joon ◽  
Michael T. Tetzlaff ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Cancer Genome Atlas ◽  
Formalin Fixed ◽  
Genome Atlas

Purpose Initiatives such as The Cancer Genome Atlas and International Cancer Genome Consortium have generated high-quality, multiplatform molecular data from thousands of frozen tumor samples. Although these initiatives have provided invaluable insight into cancer biology, a tremendous potential resource remains largely untapped in formalin-fixed, paraffin-embedded (FFPE) samples that are more readily available but which can present technical challenges because of crosslinking of fragile molecules such as RNA. Materials and Methods We extracted RNA from FFPE primary melanomas and assessed two gene expression platforms—genome-wide RNA sequencing and targeted NanoString—for their ability to generate coherent biologic signals. To do so, we generated an improved approach to quantifying gene expression pathways. We refined pathway scores through correlation-guided gene subsetting. We also make comparisons to The Cancer Genome Atlas and other publicly available melanoma datasets. Results The comparison of the gene expression patterns to each other, to established biologic modules, and to clinical and immunohistochemical data confirmed the fidelity of biologic signals from both platforms using FFPE samples to known biology. Moreover, correlations with patient outcome data were consistent with previous frozen-tissue–based studies. Conclusion FFPE samples from previously difficult-to-access cancer types, such as small primary melanomas, represent a valuable and previously unexploited source of analyte for RNA sequencing and NanoString platforms. This work provides an important step toward the use of such platforms to unlock novel molecular underpinnings and inform future biologically driven clinical decisions.

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