Homo sapiens isolate:FFPE identifier
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ABSTRACT:
PROVIDER: PRJNA554686 | ENA |
REPOSITORIES: ENA
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Project description:We present FFPE-ATAC, a new ATAC-seq tool for chromatin accessibility profiling that decodes the chromatin accessibility from mouse FFPE tissue and clinical archived FFPE tissues. The FFPE-ATAC generates the high-quality chromatin accessibility profiles from clinical FFPE tissue sections with 5-20 µm thickness, and reveals the disease-associated regulatory elements in different types of FFPE archived tissue. FFPE-ATAC enables to decode the chromatin states regulating the gene regulation in the cancer and understand the epigenetic regulation in the translational studies.
2021-06-30 | GSE163306 | GEO
Project description:Formalin-fixed, paraffin-embedded (FFPE) tissue samples are an invaluable resource to study the underlying molecular mechanisms of the diseases and when coupled with laser capture microdissection (LCM, isolation of sub histological regions of the tissue sections is readily obtained for further analysis. LCM-based FFPE tissue proteomics is gaining clinicopathological significance particularly in biomarker discovery driven research, beyond its conventional morphology-based application in laboratory diagnosis. Processing of laser capture microdissected tissue sections can be challenging for quantitative proteomic analysis due to lower amount of protein retrieved and losses during the sample processing. A robust, streamlined and automated sample preparation workflow for efficient processing of large cohort of LCM samples which is a primary requisite for biomarker type of studies is needed. Here, we propose a new sample processing workflow for processing of FFPE samples and enable scalable, automated extraction of clean peptides from unprocessed or H&E-stained FFPE tissue sections for deep bottom-up protein profiling and quantification.
2023-10-24 | PXD040727 | Pride
Project description:Background and Aims Formalin-fixed, paraffin-embedded (FFPE) tissue is the most commonly available form of archived clinical specimens, which are often stored as thin sections on glass slides. RNA isolated from such archived section (AS) of FFPE tissue is more degraded compared to freshly cut (FC) FFPE section because of prolonged air exposure. In this study, we evaluated performance of transcriptome profiling-based disease classification in AS-FFPE tissue. Methods Genome-wide gene-expression profiles of AS-FFPE tissues of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina), and compared with the profiles previously produced by using FC tissue sections from the same FFPE blocks. Quality of the profiles and performance of gene signature-based class prediction were systematically evaluated. Results RNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate ~ poor quality FC-FFPE samples (R2 as high as 0.93). Gene-expression signal was detected in lower number of probes in AS FFPE samples compared to FC-FFPE samples (proportion of probes with present signal (%P-call): 10%~60% and 70%~90% in AS- and FC-FFPE profiles, respectively). Based on %P-call quality threshold of 20%, 64/88 (77%) HCC and 37/48 (77%) liver profiles were judged as having relatively good quality data with comparable inter-sample correlation. Inter-sample correlation coefficient, as a measure to detect outlier profiles due to poor RNA quality, was also lower in AS-FFPE (0.4~0.9) compared to FC-FFPE (0.6~1.0). In the genome-wide profiling analysis, previously identified molecular subclasses of HCC tumors were reproduced in 67/83 (81%) samples, which was improved to 43/48 (90%) samples when we focused on statistically confident predictions (p<0.05). A 186-gene prognostic signature in liver cirrhosis was reproduced in 32/47 (68%) samples, which was slightly improved to 11/16 (69%) when focused on statistically significant predictions. Conclusions We observed decay of genome-wide transcriptional profiles in AS-FFPE tissues in quantitative manner. However, disease classification was still possible, which suggests potential of AS-FFPE material for clinical diagnosis and prognosis.
2014-01-31 | GSE46444 | GEO
Project description:Background and Aims Formalin-fixed, paraffin-embedded (FFPE) tissue is the most commonly available form of archived clinical specimens, which are often stored as thin sections on glass slides. RNA isolated from such archived section (AS) of FFPE tissue is more degraded compared to freshly cut (FC) FFPE section because of prolonged air exposure. In this study, we evaluated performance of transcriptome profiling-based disease classification in AS-FFPE tissue. Methods Genome-wide gene-expression profiles of 5-year-old AS-FFPE tissues of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina), and compared with the profiles previously produced by using FC tissue sections from the same FFPE blocks. Previously reported 186-gene liver signature of poor prognosis was also analyzed by digital transcript counting technology (nCounter assay, NanoString). Quality of the profiles and performance of gene signature-based class prediction were systematically evaluated. Results RNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate ~ poor quality FC-FFPE samples (R2 as high as 0.93). Gene-expression signal was detected in lower number of probes in AS FFPE samples compared to FC-FFPE samples (proportion of probes with present signal (%P-call): 10-60% and 70-90% in AS- and FC-FFPE profiles, respectively). Based on %P-call quality threshold of 20%, 64/88 (77%) HCC and 37/48 (77%) liver profiles were judged as having relatively good quality data with comparable inter-sample correlation. Inter-sample correlation coefficient, as a measure to detect outlier profiles due to poor RNA quality, was also lower in AS-FFPE (0.4-0.9) compared to FC-FFPE (0.6-1.0). In the genome-wide profiling analysis, previously identified molecular subclasses of HCC tumors were reproduced in 67/83 (81%) samples, which was improved to 43/48 (90%) samples when we focused on statistically confident predictions (p<0.05). A 186-gene prognostic signature in liver cirrhosis was reproduced in 32/47 (68%) samples, which was slightly improved to 11/16 (69%) when focused on statistically significant predictions. Switch of prediction to another subclass was observed in 6% or less of the patients. nCounter assay yielded highly confident prediction: p<0.05 in 20/24 samples (83%). Switch of the prediction was observed in 2/24 samples (8%). Conclusions We observed decay of genome-wide transcriptional profiles in AS-FFPE tissues in a quantitative manner. However, disease classification was still possible, which suggests potential of AS-FFPE material for clinical diagnosis and prognosis. Digital transcript counting is a promising option to measure gene-expression signatures in AS-FFPE tissue.
2014-01-31 | GSE47594 | GEO
Project description:Background and Aims Formalin-fixed, paraffin-embedded (FFPE) tissue is the most commonly available form of archived clinical specimens, which are often stored as thin sections on glass slides. RNA isolated from such archived section (AS) of FFPE tissue is more degraded compared to freshly cut (FC) FFPE section because of prolonged air exposure. In this study, we evaluated performance of transcriptome profiling-based disease classification in AS-FFPE tissue. Methods Genome-wide gene-expression profiles of AS-FFPE tissues of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina), and compared with the profiles previously produced by using FC tissue sections from the same FFPE blocks. Quality of the profiles and performance of gene signature-based class prediction were systematically evaluated. Results RNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate ~ poor quality FC-FFPE samples (R2 as high as 0.93). Gene-expression signal was detected in lower number of probes in AS FFPE samples compared to FC-FFPE samples (proportion of probes with present signal (%P-call): 10%~60% and 70%~90% in AS- and FC-FFPE profiles, respectively). Based on %P-call quality threshold of 20%, 64/88 (77%) HCC and 37/48 (77%) liver profiles were judged as having relatively good quality data with comparable inter-sample correlation. Inter-sample correlation coefficient, as a measure to detect outlier profiles due to poor RNA quality, was also lower in AS-FFPE (0.4~0.9) compared to FC-FFPE (0.6~1.0). In the genome-wide profiling analysis, previously identified molecular subclasses of HCC tumors were reproduced in 67/83 (81%) samples, which was improved to 43/48 (90%) samples when we focused on statistically confident predictions (p<0.05). A 186-gene prognostic signature in liver cirrhosis was reproduced in 32/47 (68%) samples, which was slightly improved to 11/16 (69%) when focused on statistically significant predictions. Conclusions We observed decay of genome-wide transcriptional profiles in AS-FFPE tissues in quantitative manner. However, disease classification was still possible, which suggests potential of AS-FFPE material for clinical diagnosis and prognosis. FFPE tissue sections (10 micron-thick) sliced from 5~16-year-old FFPE blocks and archived for 6~7 years on glass slide Gene-expression profiles of archived section of formalin-fixed paraffin-embedded (AS-FFPE) liver tissues from HCC patients: 47 samples Gene-expression profiles of archived section of formalin-fixed paraffin-embedded (AS-FFPE) tumor tissues from HCC patients: 83 samples
2014-01-31 | E-GEOD-46444 | biostudies-arrayexpress
Project description:Background and Aims Formalin-fixed, paraffin-embedded (FFPE) tissue is the most commonly available form of archived clinical specimens, which are often stored as thin sections on glass slides. RNA isolated from such archived section (AS) of FFPE tissue is more degraded compared to freshly cut (FC) FFPE section because of prolonged air exposure. In this study, we evaluated performance of transcriptome profiling-based disease classification in AS-FFPE tissue. Methods Genome-wide gene-expression profiles of 5-year-old AS-FFPE tissues of 83 hepatocellular carcinoma (HCC) and 47 liver cirrhosis samples were generated by using whole-genome DASL assay (Illumina), and compared with the profiles previously produced by using FC tissue sections from the same FFPE blocks. Previously reported 186-gene liver signature of poor prognosis was also analyzed by digital transcript counting technology (nCounter assay, NanoString). Quality of the profiles and performance of gene signature-based class prediction were systematically evaluated. Results RNA quality and assay reproducibility of AS-FFPE RNA were comparable to intermediate ~ poor quality FC-FFPE samples (R2 as high as 0.93). Gene-expression signal was detected in lower number of probes in AS FFPE samples compared to FC-FFPE samples (proportion of probes with present signal (%P-call): 10-60% and 70-90% in AS- and FC-FFPE profiles, respectively). Based on %P-call quality threshold of 20%, 64/88 (77%) HCC and 37/48 (77%) liver profiles were judged as having relatively good quality data with comparable inter-sample correlation. Inter-sample correlation coefficient, as a measure to detect outlier profiles due to poor RNA quality, was also lower in AS-FFPE (0.4-0.9) compared to FC-FFPE (0.6-1.0). In the genome-wide profiling analysis, previously identified molecular subclasses of HCC tumors were reproduced in 67/83 (81%) samples, which was improved to 43/48 (90%) samples when we focused on statistically confident predictions (p<0.05). A 186-gene prognostic signature in liver cirrhosis was reproduced in 32/47 (68%) samples, which was slightly improved to 11/16 (69%) when focused on statistically significant predictions. Switch of prediction to another subclass was observed in 6% or less of the patients. nCounter assay yielded highly confident prediction: p<0.05 in 20/24 samples (83%). Switch of the prediction was observed in 2/24 samples (8%). Conclusions We observed decay of genome-wide transcriptional profiles in AS-FFPE tissues in a quantitative manner. However, disease classification was still possible, which suggests potential of AS-FFPE material for clinical diagnosis and prognosis. Digital transcript counting is a promising option to measure gene-expression signatures in AS-FFPE tissue. FFPE tissue sections (10 micron-thick) sliced from 5~16-year-old FFPE blocks and archived for 6~7 years on glass slide
2014-01-31 | E-GEOD-47594 | biostudies-arrayexpress
Project description:Genome-wide DNA-methylation profiling of intra- and extracranial melanoma metastases. The goal of the study was to identify differences between methylomes of intra- and extracranial metastases. For each metastasis, FFPE material was used to extract genomic DNA from a punch biopsy of a marked metastasis area. The Illumina Infinium MethylationEPIC array was used for hybridization.
2023-01-18 | GSE203152 | GEO
Project description:The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.
2018-09-05 | GSE93337 | GEO
Project description:Formalin-fixed paraffin-embedded (FFPE) tissues are stable when stored at ambient temperature; they are primarily used for histopathology and immunohistochemistry (IHC). The use of FFPE tissues in molecular biological applications has increased over the years and they can be used for cancer proteomic study and biomarker discovery. Prolonged storage time and poor storage conditions would affect the antigenicity of tissue sections that are cut from FFPE blocks and used for IHC. However, it is not known if these factors would have similar impacts on proteomic analysis. To determine this, tissue sections were cut from rat brain, kidney and liver FFPE blocks on day 0 and stored at RT or -80°C for up to 48 weeks before they were processed and analysed by LC-MS on 11 experiment days (1, 2, 3, 4, 8, 12, 16, 20, 24, 37 and 48 weeks after day 0). Fresh tissue sections were cut from the same FFPE blocks on the experiment day and used as controls. All peptide digests (n = 297) were analysed on Sciex TripleTOF 6600 mass spectrometers in data-dependent acquisition (DDA) mode; kidney and liver digests (n = 165) were also analysed in data-independent acquisition (DIA) mode. From both DDA and DIA analysis, the overall proteome and post-translational modifications (PTMs) that are specific for FFPE samples were not affected by the storage time and storage temperature. This indicates that FFPE tissue sections can be stored at either RT or -80°C for at least 48 weeks without compromising proteomic analysis.
2025-03-26 | PXD054596 | Pride
Project description:The reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.
2018-09-05 | GSE93336 | GEO