Long-read sequencing of clear cell renal cell carcinoma
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ABSTRACT:
PROVIDER: PRJEB35219 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Whole genome expression of 39 clear-cell renal cell carcinomas tumors 39 frozen tissue from recent nephrectomies for clear-cell renal cell carcinoma; association with clinical characteristics
2011-05-28 | E-GEOD-29609 | biostudies-arrayexpress
Project description:Whole genome expression of 39 clear-cell renal cell carcinomas tumors
2011-05-28 | GSE29609 | GEO
Project description:CTSP Kidney Renal Clear Cell Carcinoma E2805T6
| PRJNA562745 | ENA
Project description:Background: Clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) can usually be distinguished by histologic characteristics. Occasionally, diagnosis proves challenging and diagnostic difficulty will likely increase as needle biopsies of renal lesions become more common. Method: To identify markers that aid in differentiating ccRCC from chRCC, we used gene expression profiles to identify candidate markers that correlate with histology. 39 antisera and antibodies, including 35 for transcripts identified from gene expression profiling, were evaluated. Promising markers were tested on a tissue microarray (TMA) containing 428 renal neoplasms. Strength of staining of each core on the TMA was formally scored and the distribution of staining across different types of renal neoplasms was analyzed. Results: Based on results from initial immunohistochemical staining of multitissue titer arrays, 23 of the antisera and antibodies were selected for staining of the TMA. For 7 of these markers, strength of staining of each core on the TMA was formally scored. Vimentin (positive in ccRCC) and CD9 (positive in chRCC) best distinguished ccRCC from chRCC. The combination of vimentin negativity and CD9 positivity was found to distinguish chRCC from ccRCC with a sensitivity of 100.0% and a specificity of 95.2%. Conclusions: Based on gene expression analysis, we identify CD9 and vimentin as candidate markers for distinguishing between ccRCC and chRCC. In difficult cases and particularly when the amount of diagnostic tissue is limited, vimentin and CD9 staining could serve as a useful adjunct in the differential diagnosis of ccRCC and chRCC. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Stage of Clear Cell renal cell carcinoma (I - V)) disease_state_design
2010-08-20 | E-GEOD-17746 | biostudies-arrayexpress
Project description:The understanding of metastatic spread is limited and molecular mechanisms causing particular characteristics of metastasis, like varying dormancy periods of Mets originating from the same primary tumor entity or the differing number of Mets in patients with the same primary tumor, are largely unknown. Knowing the molecular fundamentals of these phenomena would support the prognosis of patients´ outcome and facilitate the decision for an appropriate therapy regime. We analyzed the transcriptome-wide expression profiles of 20 pulmonary metastases of renal cell carcinoma in order to identify expression patterns associated with two important prognostic factors in RCC: the disease-free interval after nephrectomy (DFI) and the number of Mets per patient. Keywords: comparison of pulmonary metastases from patients with different clinical characteristics metastases manifested early or late after nephrectomy (DFI less than or equal to 9 vs. greater than or equal to 60 months) metastases derived from patients with only few or multiple pulmonary metastases (less than or equal to 8 vs. greater than or equal to 16)
2009-01-13 | E-GEOD-14378 | biostudies-arrayexpress
Project description:Genomic characterization of Chinese clear cell renal cell carcinoma
| PRJNA523858 | ENA
Project description:Side Population Analysis in Clear Cell Renal Cell Carcinoma
| PRJNA779732 | ENA
Project description:Background: Clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) can usually be distinguished by histologic characteristics. Occasionally, diagnosis proves challenging and diagnostic difficulty will likely increase as needle biopsies of renal lesions become more common. Method: To identify markers that aid in differentiating ccRCC from chRCC, we used gene expression profiles to identify candidate markers that correlate with histology. 39 antisera and antibodies, including 35 for transcripts identified from gene expression profiling, were evaluated. Promising markers were tested on a tissue microarray (TMA) containing 428 renal neoplasms. Strength of staining of each core on the TMA was formally scored and the distribution of staining across different types of renal neoplasms was analyzed. Results: Based on results from initial immunohistochemical staining of multitissue titer arrays, 23 of the antisera and antibodies were selected for staining of the TMA. For 7 of these markers, strength of staining of each core on the TMA was formally scored. Vimentin (positive in ccRCC) and CD9 (positive in chRCC) best distinguished ccRCC from chRCC. The combination of vimentin negativity and CD9 positivity was found to distinguish chRCC from ccRCC with a sensitivity of 100.0% and a specificity of 95.2%. Conclusions: Based on gene expression analysis, we identify CD9 and vimentin as candidate markers for distinguishing between ccRCC and chRCC. In difficult cases and particularly when the amount of diagnostic tissue is limited, vimentin and CD9 staining could serve as a useful adjunct in the differential diagnosis of ccRCC and chRCC. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: Stage of Clear Cell renal cell carcinoma (I - V))
2010-08-20 | GSE17746 | GEO
Project description:The understanding of metastatic spread is limited and molecular mechanisms causing particular characteristics of metastasis, like varying dormancy periods of Mets originating from the same primary tumor entity or the differing number of Mets in patients with the same primary tumor, are largely unknown. Knowing the molecular fundamentals of these phenomena would support the prognosis of patients´ outcome and facilitate the decision for an appropriate therapy regime. We analyzed the transcriptome-wide expression profiles of 20 pulmonary metastases of renal cell carcinoma in order to identify expression patterns associated with two important prognostic factors in RCC: the disease-free interval after nephrectomy (DFI) and the number of Mets per patient. Keywords: comparison of pulmonary metastases from patients with different clinical characteristics
2009-01-13 | GSE14378 | GEO
Project description:Study of non-clear cell renal cell carcinoma
| EGAS00001000926 | EGA