Results of first proficiency test for KRAS testing with formalin-fixed, paraffin-embedded cell lines in China

2014 ◽  
Vol 52 (12) ◽  
Author(s):  
Rui Zhang ◽  
Yanxi Han ◽  
Jie Huang ◽  
Liang Ma ◽  
Yulong Li ◽  
...  
Keyword(s):  
Cell Lines ◽  
Laboratory Testing ◽  
Proficiency Test ◽  
Cultured Cell ◽  
Proficiency Panel ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

AbstractLaboratory testing forArtificial FFPE samples were prepared from cultured cell lines to construct a proficiency panel of 10 samples covering eightThe percentages of mutant

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 Time and tumor type (primary or metastatic) do not influence the detection of BRAF/NRAS mutations in formalin fixed paraffin embedded samples from melanomas

2016 ◽  
Vol 54 (11) ◽  
Author(s):  
Miriam Potrony ◽  
Celia Badenas ◽  
Bénédicte Naerhuyzen ◽  
Paula Aguilera ◽  
Joan Anton Puig-Butille ◽  
...  
Keyword(s):  
Melanoma Patient ◽  
Primary Melanoma ◽  
Sentinel Lymph Nodes ◽  
Tumor Type ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Complete Sequencing ◽  
Formalin Fixed ◽  
Tumor Area

AbstractBackground:Methods:DNA was obtained from 144 FFPE samples (62 primary melanoma, 43 sentinel lymph nodes [SLN] and 39 metastasis).Results:Complete sequencing results were obtained from 75% (108/144) of the samples, and at least one gene was sequenced in 89% (128/144) of them.Conclusions:Preserving sufficient tumor area in FFPE blocks is important. It is necessary to keep the FFPE blocks, no matter their age, as they are necessary to decide the best treatment for the melanoma patient.

scholarly journals Comparison of Whole Genome Amplification Methods for Analysis of DNA Extracted from Microdissected Early Breast Lesions in Formalin-Fixed Paraffin-Embedded Tissue

ISRN Oncology ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Nona Arneson ◽  
Juan Moreno ◽  
Vladimir Iakovlev ◽  
Arezou Ghazani ◽  
Keisha Warren ◽  
...  
Keyword(s):  
Comparative Genomic Hybridization ◽  
Whole Genome Amplification ◽  
Comparative Genomic ◽  
Whole Genome ◽  
Genomic Hybridization ◽  
Genome Amplification ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

To understand cancer progression, it is desirable to study the earliest stages of its development, which are often microscopic lesions. Array comparative genomic hybridization (aCGH) is a valuable high-throughput molecular approach for discovering DNA copy number changes; however, it requires a relatively large amount of DNA, which is difficult to obtain from microdissected lesions. Whole genome amplification (WGA) methods were developed to increase DNA quantity; however their reproducibility, fidelity, and suitability for formalin-fixed paraffin-embedded (FFPE) samples are questioned. Using aCGH analysis, we compared two widely used approaches for WGA: single cell comparative genomic hybridization protocol (SCOMP) and degenerate oligonucleotide primed PCR (DOP-PCR). Cancer cell line and microdissected FFPE breast cancer DNA samples were amplified by the two WGA methods and subjected to aCGH. The genomic profiles of amplified DNA were compared with those of non-amplified controls by four analytic methods and validated by quantitative PCR (Q-PCR). We found that SCOMP-amplified samples had close similarity to non-amplified controls with concordance rates close to those of reference tests, while DOP-amplified samples had a statistically significant amount of changes. SCOMP is able to amplify small amounts of DNA extracted from FFPE samples and provides quality of aCGH data similar to non-amplified samples.

scholarly journals A novel use of random priming-based single-strand library preparation for whole genome sequencing of formalin-fixed paraffin-embedded tissue samples

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Emily A Saunderson ◽  
Ann-Marie Baker ◽  
Marc Williams ◽  
Kit Curtius ◽  
J Louise Jones ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Preparation Method ◽  
Degraded Dna ◽  
Whole Genome ◽  
Library Preparation ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed ◽  
Library Preparation Method

Abstract The desire to analyse limited amounts of biological material, historic samples and rare cell populations has collectively driven the need for efficient methods for whole genome sequencing (WGS) of limited amounts of poor quality DNA. Most protocols are designed to recover double-stranded DNA (dsDNA) by ligating sequencing adaptors to dsDNA with or without subsequent polymerase chain reaction amplification of the library. While this is sufficient for many applications, limited DNA requires a method that can recover both single-stranded DNA (ssDNA) and dsDNA. Here, we present a WGS library preparation method, called ‘degraded DNA adaptor tagging’ (DDAT), adapted from a protocol designed for whole genome bisulfite sequencing. This method uses two rounds of random primer extension to recover both ssDNA and dsDNA. We show that by using DDAT we can generate WGS data from formalin-fixed paraffin-embedded (FFPE) samples using as little as 2 ng of highly degraded DNA input. Furthermore, DDAT WGS data quality was higher for all FFPE samples tested compared to data produced using a standard WGS library preparation method. Therefore, the DDAT method has potential to unlock WGS data from DNA previously considered impossible to sequence, broadening opportunities to understand the role of genetics in health and disease.

PDL-1 and immunohistochemistry markers in esophageal adenocarcinoma.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e15567-e15567
Author(s):  
Dawn E. Jaroszewski ◽  
Joanne Xiu ◽  
Zoran Gatalica ◽  
Staci Beamer ◽  
Melissa Stanton ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Esophageal Adenocarcinoma ◽  
Neoadjuvant Treatment ◽  
Formalin Fixed Paraffin ◽  
Ffpe Tumor ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

e15567 Background: Esophageal adenocarcinoma (EAC) prognosis is poor and there is a need to identify patients that benefit most from neoadjuvant therapy. To examine the association of various biomarkers with clinical outcomes in neoadjuvant treatment of EAC, we retrospectively evaluated the biomarker expression (TS, ERCC1, TOPO1, PD-L1, PD-1) in patient matched formalin-fixed paraffin-embedded (FFPE) tumor samples. Methods: Immunohistochemistry of TS (TS106/4H4B1) , ERCC1 (Ab. 8F1), TOPO1 (1D6), PD-L1 (both 22c3 and SP142), PD-1 (NAT105), and chromogenic in-situ hybridization (CISH) of Her2 were performed on FFPE samples from 35 patients across 2 institutions at time of EAC diagnosis and after treatment when available. Retrospective clinical data and survival (5/2006-1/2016) was analyzed with a mean follow up of 110 months (range 22-306). Results: Overexpression (pre/post-treatment) of TS (60%/54%), ERCC1 (69%/16%), TOPO1 (74%/50%), PD-1 (54%/63%), PD-L1 (SP142) (2.9%/4%), PD-L1 (22c3) (0%/4%) and amplification of Her2 (18%/23%) were observed. Pretreatment observed PD-L1 levels were lower in our study (3%) when compared to other studies in EAC specimens (35%). Immunohistochemistry and changes observed after chemoradiation are reviewed in Table. No markers had significant correlation with prognosis however TS negative expression showed a non-significant (p=0.15) trend towards improved survival. Conclusions: Analyzing biomarkers in our neoadjuvant EAC cohort demonstrated a lower than expected PD-L1 positivity. In the largest cohort, to our knowledge, of patient matched FFPE tumor samples, we did not observe a statistically significant association between TS, ERCC1, TOPO1, PD-L1, or PD-1 with improved clinical outcomes. [Table: see text]

scholarly journals HYPERsol: flash-frozen results from archival FFPE tissue for clinical proteomics

2019 ◽  
Author(s):  
Dylan M. Marchione ◽  
Ilyana Ilieva ◽  
Benjamin A. Garcia ◽  
Darryl J. Pappin ◽  
John P. Wilson ◽  
...  
Keyword(s):  
Protein Extraction ◽  
Ffpe Tissue ◽  
Clinical Proteomics ◽  
High Yield ◽  
Proteome Coverage ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Proteomics Research ◽  
Formalin Fixed

Massive formalin-fixed, paraffin-embedded (FFPE) tissue archives exist worldwide, representing a potential gold mine for clinical proteomics research. However, current protocols for FFPE proteomics lack standardization, efficiency, reproducibility, and scalability. Here we present High-Yield Protein Extraction and Recovery by direct SOLubilization (HYPERsol), an optimized workflow using adaptive-focused acoustics (AFA) ultrasonication and S-Trap sample processing that enables proteome coverage and quantification from FFPE samples comparable to that achieved from flash-frozen tissue (average R = 0.936).

scholarly journals Protein Classification of Diffuse-Type Gastric Cancer Using Formalin-Fixed Paraffin-Embedded Samples

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 224s-224s
Author(s):  
W. Huang ◽  
X. Xia ◽  
J. Gao ◽  
Z. Li ◽  
S. Ge ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Rna Processing ◽  
Protein Classification ◽  
Diffuse Type ◽  
Proteome Profiling ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
Diffuse Type Gastric Cancer ◽  
Formalin Fixed

Background: Gastric cancer (GC) is the third leading cause of cancer deaths in the world. It is highly heterogeneous. Many molecular therapies for GC have entered clinical trials but, apart from trastuzumab, apatinib and ramucirumab, all have failed. One important reason is that insufficient attention is paid to the underlying subtypes and characteristics of GC, especially the diffuse-type gastric cancer (DGC) according to the Lauren classification with worst clinical outcomes. Aim: Here we firstly investigated formalin-fixed paraffin-embedded (FFPE) samples of DGC to establish clinically relevant molecular classification based on proteomics analysis. Also, we tried to generate a suitable classifier of DGC that can guide patient therapy. Methods: We screened a total of 2548 cases retrospectively, who underwent GC resection at Beijing Cancer Hospital from October 2006 to December 2011. We used a fast mass spectrometry workflow for proteome profiling. Finally we carried out proteome profiling of 99 DGC paired tumor-nearby tissues from FFPE sections. Median overall survival of the whole population was 55.0 months. Proteome profiling data from these samples were used to develop a subtype prediction model. We used consensus clustering to identify molecular subtypes based on differentially expressed proteins. The pathway enrichment was performed by GSEA, and the prediction classifier was generated by elastic-net machine learning. Kaplan-Meier survival analysis and Cox regression multivariate analysis were used. Results: A total of 8201 gene products were identified in this study, and 1249 differential expressed proteins between tumor and nearby-normal tissue was detected (FDR q-value < 0.01 by SAM). Tumor upregulated proteins mostly enriched into pathways including RNA processing, epithelial-mesenchymal transition (EMT), immune response and inflammation related pathways. Tumor downregulated proteins mostly enriched into metabolic pathways such as oxidative phosphorylation pathway. Based on proteome profiling alone, DGC can be subtyped into 3 major classes (PX1-3) that exhibit distinct proteome features and correlate with distinct clinical outcomes. PX1 (31 patients) exhibits RNA processing proteins and associates with the best prognosis; PX2 (26 patients) exhibits highly expressed cell cycle features, and the patients have poorer prognosis than those with cluster1 but better prognosis than those with cluster3; PX3 (42 patients) features EMT and the worst prognosis. We built a classifier of 12 marker proteins that can stratify DGC patients into these 3 subtypes, opening a door for protein classification in clinical application and intervention. Conclusion: Our study demonstrated that proteome profiling alone from FFPE samples was able to subtype DGC into 3 protein subtypes that were linked to distinct patterns of molecular alterations and prognosis. The prediction model need to be further verified in more clinical cohorts.

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