D9a1d5a9-d284-4c6b-b30d-543bdbbdd1b1 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008835 | EGA |
REPOSITORIES: EGA
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2019-06-12 | PXD007841 | Pride
Project description:Over one million prostate biopsies are performed in the U.S. every year. However, pathology examination is not definitive in a significant percentage of cases due limited diagnostic tumor. We have observed that the microenvironment of prostate tumor cells exhibits numerous differential gene expression changes and have asked whether such information can be used to distinguish “tumor” from “nontumor”. We initially compared expression analysis data (Affymetrix U133plus2) from 18 volunteer biopsy specimens to 17 specimens containing largely tumor-adjacent stroma and identified 964 significant (p_adj < 0.01 and B > 0) expression changes. These genes were filtered to eliminate possible aging-related genes and genes expressed in tumor cells > 10% of the stroma cell expression level leading to 23 candidate genes (28 Affymetrix probe sets). A classifier based on the 28 probe sets was tested on 289 independent cases, including 195 tumor-bearing cases, 99 nontumor cases (normal biopsies, normal autopsies, remote stroma as well as pure tumor adjacent stroma) all with accuracies >85%, sensitivities >90% and specificities >85%. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorization as “tumor” and “nontumor”. For inquires please contact dmercola@uci.edu. Experiment Overall Design: Prostate cancer gene expression profiles were studied in this project. Total RNA from 154 prostate sample with various amount of different cell types were hybridized to Affymetrix U133Plus2 array. The percentage of different cell types were determined by a pathologist.
2009-09-11 | E-GEOD-17951 | biostudies-arrayexpress
Project description:A DIA-MS dataset of 106 samples including 14 healthy liver tissues, 46 pairs of tumor and adjacent-to-tumor samples.
2022-08-12 | PXD036048 |
Project description:Over one million prostate biopsies are performed in the U.S. every year. However, pathology examination is not definitive in a significant percentage of cases due limited diagnostic tumor. We have observed that the microenvironment of prostate tumor cells exhibits numerous differential gene expression changes and have asked whether such information can be used to distinguish “tumor” from “nontumor”. We initially compared expression analysis data (Affymetrix U133plus2) from 18 volunteer biopsy specimens to 17 specimens containing largely tumor-adjacent stroma and identified 964 significant (p_adj < 0.01 and B > 0) expression changes. These genes were filtered to eliminate possible aging-related genes and genes expressed in tumor cells > 10% of the stroma cell expression level leading to 23 candidate genes (28 Affymetrix probe sets). A classifier based on the 28 probe sets was tested on 289 independent cases, including 195 tumor-bearing cases, 99 nontumor cases (normal biopsies, normal autopsies, remote stroma as well as pure tumor adjacent stroma) all with accuracies >85%, sensitivities >90% and specificities >85%. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorization as “tumor” and “nontumor”. For inquires please contact dmercola@uci.edu.
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Project description:<p>Cancer-associated fibroblasts (CAFs) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we employ single-cell RNA-sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human PDAC tumors. Six human PDAC tumor specimens from six patients were collected, and processed for single-cell RNA-sequencing analysis. Adjacent-normal pancreas tissue was also collected from two of the patients. Tumor samples were digested, and fluorescence-activated cell sorting was used to isolate viable cells. For one tumor sample, viable, CD45-negative, CD31-negative, and EpCAM-negative cells were also isolated to enrich for CAFs. The 10X Chromium platform was then used to isolate single cells for RNA-sequencing analysis. This work has demonstrated the differences in immune cell populations between adjacent-normal and tumor tissues, and identified subpopulations of epithelial cells and CAFs present in PDAC tumors. This high-throughput analysis is a resource to better understand the cell populations present in PDAC, and may ultimately aid in the development of more effective therapies for this deadly malignancy.</p>
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Project description:The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total).
Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.
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