Measurement of gene expression biomarkers by qNPA from archived NSCLC FFPE: Prognosis of 5-year survival

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 11098-11098
Author(s):  
M. M. Joshi ◽  
B. Seligmann ◽  
C. Sabalos ◽  
D. H. Harpole
Keyword(s):  
Gene Expression ◽  
B Cell Lymphoma ◽  
Base Hydrolysis ◽  
Data Set ◽  
S1 Nuclease ◽  
Tissue Samples ◽  
Frozen Tissue ◽  
Fresh Frozen ◽  
Cox Analysis ◽  
Stage 1

11098 Background: There are vast archives of formalin fixed paraffin-embedded (FFPE) tissue samples that are clinically annotated offering great research potential. However, the technology currently available to assess gene expression is limited to fresh, frozen, tissue. Recently, a method for measuring gene expression from FFPE using the quantitative Nuclease Protection Assay (qNPA) has been published in a model of diffuse large B-cell lymphoma. It was demonstrated that identical results were obtained from small amounts of FFPE as from matched frozen tissue, or from freshly fixed versus 18 year archived FFPE. Methods: This study used the qNPA assay to measure gene expression in archived FFPE primary tumor samples of patients with stage 1 NSCLC for whom the survival outcomes are known (n=86). HTG lysis buffer is added to the sample; nuclease protection probes that are complementary to the mRNA of interest are then added to the solution. The probes hybridize to all RNA, soluble and cross-linked. After hybridization, S1 nuclease was added and destroys all nonspecific, single strand nucleic acid, producing a stoichiometric amount of target-mRNA to probe duplexes. Base hydrolysis releases the probe from these duplexes. Probes were transferred to a programmed ArrayPlate, detection linker added, and both probes and detection linkers were captured onto the array. The ArrayPlate was washed, HRP-labeled detection probe added, incubated, washed, and chemiluminescent substrate was added. Finally, the ArrayPlate was imaged, to measure the expression of each gene in all the wells. Results: Mantel-Cox analysis indicates that the detection of increased expression of G-CSF (p = 0.07; H.R. =1.904; 95% CI=0.9003–4.028) and Leptin (p=0.09; H.R. =1.910; 95% CI=0.9299–3.924) individually suggest an improved survival. Age, gender and T size were found to not be significant in this data set. Conclusions: These results suggest an improved survival advantage in patients with an elevated native GCSF level in stage 1 NSCLC that is consistent with the survival benefits associated with the prophylactic treatment of GCSF for chemosensitivity in stage III or IV NSCLC patients. These results are currently being assessed using a larger cohort. [Table: see text]

Muscle Biopsy Samples for Histochemical Processing: Alterations Induced by Storage

1988 ◽  
Vol 25 (1) ◽  
pp. 77-82 ◽  
Author(s):  
K. G. Braund ◽  
K. A. Amling
Keyword(s):  
Skeletal Muscle ◽  
Cell Morphology ◽  
Type I ◽  
Type Ii ◽  
Tissue Samples ◽  
Frozen Tissue ◽  
Fresh Frozen ◽  
Healthy Dogs ◽  
Morphology And Morphometry ◽  
Type Ii Fibers

Skeletal muscle samples from two healthy dogs were stored in ice at 0 C for up to 30 hours to examine the influence of time on cell morphology and morphometry. Cytochemical and histochemical properties of muscle to 18 hours were not markedly different from fresh frozen tissue. Samples stored to 30 hours were still satisfactory, despite a decline and unevenness in depth of staining. Morphometry from samples stored at 0 C for 6 hours or longer is not recommended, due to the statistically significant increase in diameter (from 21 to 25%) of type I and type II fibers.

scholarly journals Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data

2007 ◽  
Vol 5 ◽  
pp. 117693510700500
Author(s):  
K-A. Do ◽  
G.J. McLachlan ◽  
R. Bean ◽  
S. Wen
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Clusters ◽  
Gene Clustering ◽  
Expression Data ◽  
Colon Tissue ◽  
Data Set ◽  
Tissue Samples ◽  
Gene Shaving

Researchers are frequently faced with the analysis of microarray data of a relatively large number of genes using a small number of tissue samples. We examine the application of two statistical methods for clustering such microarray expression data: EMMIX-GENE and GeneClust. EMMIX-GENE is a mixture-model based clustering approach, designed primarily to cluster tissue samples on the basis of the genes. GeneClust is an implementation of the gene shaving methodology, motivated by research to identify distinct sets of genes for which variation in expression could be related to a biological property of the tissue samples. We illustrate the use of these two methods in the analysis of Affymetrix oligonucleotide arrays of well-known data sets from colon tissue samples with and without tumors, and of tumor tissue samples from patients with leukemia. Although the two approaches have been developed from different perspectives, the results demonstrate a clear correspondence between gene clusters produced by GeneClust and EMMIX-GENE for the colon tissue data. It is demonstrated, for the case of ribosomal proteins and smooth muscle genes in the colon data set, that both methods can classify genes into co-regulated families. It is further demonstrated that tissue types (tumor and normal) can be separated on the basis of subtle distributed patterns of genes. Application to the leukemia tissue data produces a division of tissues corresponding closely to the external classification, acute myeloid meukemia (AML) and acute lymphoblastic leukemia (ALL), for both methods. In addition, we also identify genes specific for the subgroup of ALL-Tcell samples. Overall, we find that the gene shaving method produces gene clusters at great speed; allows variable cluster sizes and can incorporate partial or full supervision; and finds clusters of genes in which the gene expression varies greatly over the tissue samples while maintaining a high level of coherence between the gene expression profiles. The intent of the EMMIX-GENE method is to cluster the tissue samples. It performs a filtering step that results in a subset of relevant genes, followed by gene clustering, and then tissue clustering, and is favorable in its accuracy of ranking the clusters produced.

scholarly journals Comparison of Accuracy of Whole-Exome Sequencing with Formalin-Fixed Paraffin-Embedded and Fresh Frozen Tissue Samples

PLoS ONE ◽  
2015 ◽  
Vol 10 (12) ◽  
pp. e0144162 ◽  
Author(s):  
Ensel Oh ◽  
Yoon-La Choi ◽  
Mi Jeong Kwon ◽  
Ryong Nam Kim ◽  
Yu Jin Kim ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Tissue Samples ◽  
Whole Exome ◽  
Formalin Fixed Paraffin ◽  
Frozen Tissue ◽  
Formalin Fixed Paraffin Embedded ◽  
Fresh Frozen ◽  
Formalin Fixed

Standard operating procedure for the collection of fresh frozen tissue samples

2007 ◽  
Vol 43 (5) ◽  
pp. 828-834 ◽  
Author(s):  
S.R. Mager ◽  
M.H.A. Oomen ◽  
M.M. Morente ◽  
C. Ratcliffe ◽  
K. Knox ◽  
...  
Keyword(s):  
Operating Procedure ◽  
Standard Operating Procedure ◽  
Tissue Samples ◽  
Frozen Tissue ◽  
Standard Operating ◽  
Fresh Frozen

scholarly journals Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues

Gut ◽  
2017 ◽  
Vol 67 (3) ◽  
pp. 521-533 ◽  
Author(s):  
Mingfeng Zhang ◽  
Soren Lykke-Andersen ◽  
Bin Zhu ◽  
Wenming Xiao ◽  
Jason W Hoskins ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Cancer Risk ◽  
Regulatory Element ◽  
Pancreatic Tissue ◽  
The Cancer Genome Atlas ◽  
Eqtl Analysis ◽  
Data Set ◽  
Tissue Samples ◽  
Pancreatic Cancer Risk

ObjectiveTo elucidate the genetic architecture of gene expression in pancreatic tissues.DesignWe performed expression quantitative trait locus (eQTL) analysis in histologically normal pancreatic tissue samples (n=95) using RNA sequencing and the corresponding 1000 genomes imputed germline genotypes. Data from pancreatic tumour-derived tissue samples (n=115) from The Cancer Genome Atlas were included for comparison.ResultsWe identified 38 615 cis-eQTLs (in 484 genes) in histologically normal tissues and 39 713 cis-eQTL (in 237 genes) in tumour-derived tissues (false discovery rate <0.1), with the strongest effects seen near transcriptional start sites. Approximately 23% and 42% of genes with significant cis-eQTLs appeared to be specific for tumour-derived and normal-derived tissues, respectively. Significant enrichment of cis-eQTL variants was noted in non-coding regulatory regions, in particular for pancreatic tissues (1.53-fold to 3.12-fold, p≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 (rs687289) was associated with ABO expression in histologically normal (p=5.8×10−8) and tumour-derived (p=8.3×10−5) tissues. The high linkage disequilibrium between this variant and the O blood group generating deletion variant in ABO (exon 6) suggested that nonsense-mediated decay (NMD) of the ‘O’ mRNA might explain this finding. However, knockdown of crucial NMD regulators did not influence decay of the ABO ‘O’ mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL.ConclusionsWe have identified cis-eQTLs representing potential functional regulatory variants in the pancreas and generated a rich data set for further studies on gene expression and its regulation in pancreatic tissues.

scholarly journals Prognostic And Immunological Implications of BTK Expression In Pan-Cancer

2021 ◽  
Author(s):  
Tao Yang ◽  
Lizheng Hao ◽  
Jian Chen ◽  
Xueying Zhu ◽  
Keyi Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
B Cell Lymphoma ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Cox Analysis ◽  
Pan Cancer

Abstract Background: Cancer poses a serious threat to human health. Clarifying the potential significance of Bruton's tyrosine kinase (BTK)in cancer has potential clinical value. This study examined the prognostic and immunological value of BTK gene expression in pan-cancer.Methods: We evaluated the gene expression of BTK in tumor tissues and normal tissues in different cancers. Survival analysis, including Kaplan–Meier analysis and Cox analysis, were performed to explore the prognostic value of BTK for pan-cancer based on survival data from The Cancer Genome Atlas (TCGA) database. Spearman’s method was conducted to analyze the interrelation between BTK gene expression and tumor mutational burden (TMB)and microsatellite instability (MSI). We explored the association of BTK expression with the tumor microenvironment based on Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm. Co-expression analysis of BTK expression and immune-related genes was performed. We used Gene Set Enrichment Analysis (GSEA) to examine the molecular mechanisms and pathways of BTK in pan-cancer.Results: High BTK expression in cervical squamous cell carcinoma and endocervical adenocarcinoma (CSEC), head and neck squamous cell carcinoma (HNSC), lung adenocarcinoma (LUAD) and skin cutaneous melanoma (SKCM) was positively correlated with patient prognosis, while high expression of BTK in lymphoid neoplasm diffuse large B cell lymphoma (DLBC), brain lower grade glioma (LGG) and esophageal carcinoma (ESCA) corresponded with a worse prognosis. Cox analysis showed that BTK was closely associated to the prognosis of HNSC, LGG, SKCM and LUAD. BTK expression was correlated with clinical stage, TMB and MSI of 10 types of tumors. In HNSC, LGG, LUAD and SKCM, the expression of BTK was positive correlated with immune and stromal scores. Conclusion: BTK expression can act as a prognostic factor in various cancers, especially in HNSC, LGG, LUAD and SKCM, and this may be from its close association with TMB, MSI and immune cell infiltration.

scholarly journals Identification of COPA as a potential prognostic biomarker and pharmacological intervention target of cervical cancer by quantitative proteomics and experimental verification

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Huiqiong Bao ◽  
Xiaobin Li ◽  
Zhixing Cao ◽  
Zhihong Huang ◽  
Li Chen ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Quantitative Proteomics ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Cell Counting ◽  
Pharmacological Intervention ◽  
Tissue Samples ◽  
Frozen Tissue ◽  
Fresh Frozen

Abstract Background Cervical cancer is the most fatal gynecological carcinoma in the world. It is urgent to explore novel prognostic biomarkers and intervention targets for cervical cancer. Methods Through integrated quantitative proteomic strategy, we investigated the protein expression profiles of cervical cancer; 28 fresh frozen tissue samples (11 adenocarcinoma (AC), 12 squamous cell carcinoma (SCC) and 5 normal cervixes (HC)) were included in discover cohort; 45 fresh frozen tissue samples (19 AC, 18 SCC and 8 HC) were included in verification cohort; 140 paraffin-embedded tissues samples of cervical cancer (85 AC and 55 SCC) were used for immunohistochemical evaluation (IHC) of coatomer protein subunit alpha (COPA) as a prognostic biomarker for cervical cancer; how deficiency of COPA affects cell viability and tumorigenic ability of cervical cancer cells (SiHa cells and HeLa cells) were evaluated by cell counting kit-8 and clone formation in vitro. Results We identified COPA is a potential prognostic biomarker for cervical cancer in quantitative proteomics analysis. By retrospective IHC analysis, we additionally verified the proteomics results and demonstrated moderate or strong IHC staining for COPA is an unfavourable independent prognostic factor for cervical cancer. We also identified COPA is a potential pharmacological intervention target of cervical cancer by a series of in vitro experiments. Conclusion This study is the first to demonstrate that COPA may contribute to progression of cervical cancer. It can serve as a potential prognostic biomarker and promising intervention target for cervical cancer.

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