Sequencing of the whole transcriptome of papillary thyroid cancer and lymph node metastases
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE202413 | GEO | 2023/05/31
REPOSITORIES: GEO
Similar Datasets
Project description:Metastasis via the lymphatics is a major risk factor in squamous cell carcinoma of the oral cavity (OSCC). We sought to determine whether the presence of metastasis in the regional lymph node could be predicted by a gene expression signature of the primary tumor. A total of 18 OSCCs were characterized for gene expression by hybridizing RNA to Affymetrix U133A gene chips. Genes with differential expression were identified using a permutation technique and verified by quantitative RT-PCR and immunohistochemistry. A predictive rule was built using a support vector machine, and the accuracy of the rule was evaluated using crossvalidation on the original data set and prediction of an independent set of four patients. Metastatic primary tumors could be differentiated from nonmetastatic primary tumors by a signature gene set of 116 genes. This signature gene set correctly predicted the four independent patients as well as associating five lymph node metastases from the original patient set with the metastatic primary tumor group. We concluded that lymph node metastasis could be predicted by gene expression profiles of primary oral cavity squamous cell carcinomas. The presence of a gene expression signature for lymph node metastasis indicates that clinical testing to assess risk for lymph node metastasis should be possible.
2007-08-25 | E-GEOD-2280 | biostudies-arrayexpress
Project description:Metastasis via the lymphatics is a major risk factor in squamous cell carcinoma of the oral cavity (OSCC). We sought to determine whether the presence of metastasis in the regional lymph node could be predicted by a gene expression signature of the primary tumor. A total of 18 OSCCs were characterized for gene expression by hybridizing RNA to Affymetrix U133A gene chips. Genes with differential expression were identified using a permutation technique and verified by quantitative RT-PCR and immunohistochemistry. A predictive rule was built using a support vector machine, and the accuracy of the rule was evaluated using crossvalidation on the original data set and prediction of an independent set of four patients. Metastatic primary tumors could be differentiated from nonmetastatic primary tumors by a signature gene set of 116 genes. This signature gene set correctly predicted the four independent patients as well as associating five lymph node metastases from the original patient set with the metastatic primary tumor group. We concluded that lymph node metastasis could be predicted by gene expression profiles of primary oral cavity squamous cell carcinomas. The presence of a gene expression signature for lymph node metastasis indicates that clinical testing to assess risk for lymph node metastasis should be possible. Keywords = oral carcinoma lymphatic metastasis predict Keywords: repeat sample
2005-02-19 | GSE2280 | GEO
Project description:We performed oligonucleotide microarray analysis to assess the genetic expression alteration wich affected on lateral neck node metastasis of thyroid papillary microcarcinoma(PTMC). We performed microarray analysis in three PTMCs without cervical lymph-node metastases (N0), and five PTMCs with lateral neck-node metastasis (N1b) at initial diagnosis, using an Illumina HumanHT-12 v4.0 Expression BeadChip.
2019-11-12 | GSE129562 | GEO
Project description:Lymph node involvement is the most important prognostic factor in breast cancer, but little is known about the underlying molecular changes. First, to identify a molecular signature associated with nodal metastasis, gene expression analysis was performed on a homogeneous group of 96 primary breast tumors, balanced for lymph node involvement. Each tumor was diagnosed as a poorly differentiated, estrogen positive, her2-neu negative invasive ductal cancer. (Affymetrix Human U133 Plus 2.0 microarray chips). A model, including 241 genes was built and validated on an internal and external dataset performed with Affymetrix technology. All samples used for validation had the same characteristics as the initial tumors. The area under the ROC curve (AUC) for the internal dataset was 0.646 and 0.651 for the external datasets. Thus, the molecular profile of a breast tumor reveals information about lymph node involvement, even in a homogeneous group of tumors. However, an AUC of 0.65 indicates only a weak correlation. Our model includes multiple kinases, apoptosis related and zinc ion binding genes. Pathway analysis using the Molecular Signatures Database revealed relevant gene sets (BAF57, Van 't Veer). Next, miRNA profiling was performed on 82/96 tumors using Human MiRNA microarray chips (Illumina). Eight miRNAs were significantly differentially expressed according to lymph node status at a significance level of 0.05, without correcting for multiple testing. The analysis of the inverse correlation between a miRNA and its computationally predicted targets point to general deregulation of the miRNA machinery potentially responsible for lymph node invasion. In conclusion, our results provide evidence that lymph node involvement in breast cancer is not a random process. Gene expression profiling: A training set of 96 patients and an independent internal dataset of 20 patients balanced for lymph node involvement was selected from the multidisciplinary breast centre database miRNA profiling not provided in this Series.
2011-02-04 | E-GEOD-23177 | biostudies-arrayexpress
Project description:Lymph node involvement is the most important prognostic factor in breast cancer, but little is known about the underlying molecular changes. First, to identify a molecular signature associated with nodal metastasis, gene expression analysis was performed on a homogeneous group of 96 primary breast tumors, balanced for lymph node involvement. Each tumor was diagnosed as a poorly differentiated, estrogen positive, her2-neu negative invasive ductal cancer. (Affymetrix Human U133 Plus 2.0 microarray chips). A model, including 241 genes was built and validated on an internal and external dataset performed with Affymetrix technology. All samples used for validation had the same characteristics as the initial tumors. The area under the ROC curve (AUC) for the internal dataset was 0.646 and 0.651 for the external datasets. Thus, the molecular profile of a breast tumor reveals information about lymph node involvement, even in a homogeneous group of tumors. However, an AUC of 0.65 indicates only a weak correlation. Our model includes multiple kinases, apoptosis related and zinc ion binding genes. Pathway analysis using the Molecular Signatures Database revealed relevant gene sets (BAF57, Van 't Veer). Next, miRNA profiling was performed on 82/96 tumors using Human MiRNA microarray chips (Illumina). Eight miRNAs were significantly differentially expressed according to lymph node status at a significance level of 0.05, without correcting for multiple testing. The analysis of the inverse correlation between a miRNA and its computationally predicted targets point to general deregulation of the miRNA machinery potentially responsible for lymph node invasion. In conclusion, our results provide evidence that lymph node involvement in breast cancer is not a random process.
2011-02-04 | GSE23177 | GEO
Project description:Secreted extracellular vesicles are known to influence the tumor microenvironment and promote metastasis. In this work, we have analyzed the involvement of extracellular vesicles in establishing the lymph node pre-metastatic niche by melanoma cells. We found that small extracellular vesicles (sEVs) derived from highly metastatic melanoma cell lines spread broadly through the lymphatic system and are taken up by lymphatic endothelial cells reinforcing lymph node metastasis. Melanoma-derived sEVs induce lymphangiogenesis, a hallmark of pre-metastatic niche formation, in vitro and in lymphoreporter mice in vivo. Analysis of involved factors demonstrated that the neural growth factor receptor (NGFR) is secreted in melanoma-derived small extracellular vesicles and shuttled to lymphatic endothelial cells inducing lymphangiogenesis and tumor cell adhesion through the activation of ERK and NF-B pathways and ICAM1 expression. Importantly, ablation or inhibition of NGFR in sEVs reversed the lymphangiogenic phenotype, decreased melanoma lymph node metastasis and extended mice survival. Importantly, analysis of NGFR expression in lymph node metastases and matched primary tumors shows that levels of MITF+NGFR+ lymph node metastatic cells are correlated with disease outcome. Our data support that NGFR is secreted in sEVs favoring lymph node pre-metastatic niche formation and lymph node metastasis in melanoma.
2021-07-16 | PXD024108 | Pride
Project description:Secreted extracellular vesicles are known to influence the tumor microenvironment and promote metastasis. In this work, we have analyzed the involvement of extracellular vesicles in the establishment of lymph node pre-metastatic niches by melanoma cells. We found that small extracellular vesicles (sEVs) derived from highly metastatic melanoma cell lines spread broadly through the lymphatic system and were taken up by lymphatic endothelial cells, reinforcing lymph node metastasis. Melanoma-derived sEVs induce lymphangiogenesis, a hallmark of pre-metastatic niche formation, in vitro and in lymphoreporter mice in vivo. We found that neural growth factor receptor (NGFR) is secreted in melanoma-derived small extracellular vesicles and shuttled to lymphatic endothelial cells, inducing lymphangiogenesis and tumor cell adhesion through the activation of ERK and NF-B pathways and ICAM1 expression. Importantly, ablation or inhibition of NGFR in sEVs reversed the lymphangiogenic phenotype, decreased melanoma lymph node metastasis and extended the survival. Importantly, analysis of NGFR expression in lymph node metastases and matched primary tumors shows that levels of MITF+NGFR+ lymph node metastatic cells are correlated with disease outcome. Our data support the idea that NGFR secreted in sEVs favors lymph node pre-metastatic niche formation and lymph node metastasis in melanoma
2021-08-05 | PXD024852 | Pride
Project description:Deep proteomic analysis of larvae, pupae and 15 adult tissues using high resolution Fourier transform mass spectrometry provided peptide evidence for ~9,000 computationally predicted genes accounting for 82% of total protein-coding genes in An. stephensi. Transcriptomic profiling of 4 tissues provided transcript evidence for 7,504 computationally predicted gene models and resulted in identification of 3,797 novel transcripts. We also identified protein level evidence for several novel alternative transcripts, SNPs and tissue restricted expression patterns of several proteins in An. stephensi
2016-09-26 | PXD001128 | Pride
Project description:A genome wide microarray platform containing the predicted coding sequences (putative genes) for the ciliated protozoan Tetrahymena thermophila is described, validated and used to study gene expression in growing, starved and conjugating cells. Of the ~27,400 predicted open reading frames in Tetrahymena, transcripts homologous to 5876 are not detectable in one or more of these life cycle stages, indicating that this organism does indeed contain a large number of functional genes. Transcripts from over 5000 predicted genes are expressed at levels 5X background and 95 genes are expressed at 250X background in all stages. Transcripts homologous to 94 predicted genes are specifically expressed and 155 more are highly up-regulated in growing cells, and 90 are specifically expressed and 616 are up-regulated during starvation. Strikingly, transcripts homologous to 1073 predicted genes are specifically expressed and 1753 are significantly up-regulated during conjugation. The patterns of gene expression during conjugation correlate well with the previously described developmental stages of meiosis, nuclear differentiation and DNA elimination. Genes encoding proteins known to be complexed show similar expression patterns, indicating that co-ordinate expression with putative genes of known function should identify new genes with related functions. Keywords: growth (three cell densities); Starvation (seven time points); Conjugation (ten time points)
2008-10-01 | GSE11300 | GEO
Project description:Background Breast cancer patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and metastasis to this lymph node is crucial for the staging of cancer and the quality of surgical intervention. Sentinel Lymph Node Biopsy (SLNB) that is currently used to assess lymph node metastasis is neither sensitive, nor specific, is time-consuming, thereby necessitating the identification of novel biomarkers that can flag sentinel lymph node metastasis. Methods Breast cancer patients were screened, and those with early stage were recruited in the study. Surgical resection of the breast was followed by identification of sentinel lymph nodes by methylene fluorescent technique. Histo-pathology of fresh frozen section biopsy was used as the gold standard to assign the clinical phenotypes of metastatic (SLNM+) and non-metastatic sentinel lymph nodes (SLNM-). Discovery phase of the experiment included isobaric Tags for Relative and Absolute Quantitation (iTRAQ) technique comprising of six comparative experiments coupled with mass spectrometric analysis on Orbitrap Fusion to identify differentially expressed proteins on Proteome Discoverer 2.4. Functional enrichment and pathway analyses of differentially regulated genes was carried out in DAVID functional annotation tool. Validation was done by ELISA and protein concentrations were used to estimate the ROC for computing diagnostic parameters. Results Based on MS/MS spectra there were 2396 unique protein groups and 81 differentially expressed proteins comparing SLNB + and SLNB -. Nineteen proteins up-regulated, and eight proteins that were down regulated in SLNB+ as compared to SLNB-. Bioinformatic analysis showed the implication of extra cellular matrix proteins and ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed the up-regulation of caveolin 1, collagen α-1, desmin, fibrillin-1, and microfibrillar associated glycoprotein 4 in metastatic, as compared to non-metastatic lymph nodes. These proteins are known to be integral in tumorogenesis, cell proliferation, invasion, cell survival and anti-apoptosis. These proteins have 80%-100%, of sensitivity and specificity to differentiate the two clinical phenotypes. Conclusion Identified extra cellular matrix protein biomarkers have requisite diagnostic parameters to be developed as a translational tool to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical therapy of axillary lymph nodes in early breast oncology.
2022-05-01 | PXD027668 | Pride