Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB15979 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR483580_1.fastq.gz | Fastqsanger.gz | |||
| DRR483580_2.fastq.gz | Fastqsanger.gz | |||
| DRR483581_1.fastq.gz | Fastqsanger.gz | |||
| DRR483581_2.fastq.gz | Fastqsanger.gz | |||
| DRR483582_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 40 |
Similar Datasets
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
Project description:The lymph of normal rabbit lymph nodes and metastatic lymph nodes of breast cancer were extracted by contrast-enhanced ultrasound for proteomic analysis, and the differential proteins affecting metastasis were obtained.
2023-11-29 | PXD047360 |
Project description:The aim of our study was to identify a microRNA signature for metastatic CRC that could predict and differentiate metastatic target organ localization. Normal and cancer tissues of three different groups of CRC patients were analyzed. RNA microarray and TaqMan Array analysis were performed on 66 italian patients with or without lymph nodes and/or liver recurrences. Data obtained with the two assays, were analyzed separately and then intersected to identify a primary CRC metastatic signature. Five differentially expressed microRNAs (hsa-miR-21, -103, -93, -31 and -566) were validated by qRT-PCR on a second group of 16 american metastatic patients. In situ hybridization was performed on the 16 american patients as well as on three distinct commercial tissues microarray (TMA), containing normal adjacent colon, the primary adenocarcinoma, normal and metastatic lymph nodes and liver. Hsa-microRNA-31,-21,-93, and-103 upregulation together with hsa-miR-566 downregulation defined the CRC metastatic signature, while in situ hybridization data identified a lymphonodal invasion profile. 33 patients had colon cancer with lymph nodes metastasis only (Any T, Any N, M0) and 15 were diagnosed with colon cancer, lymph nodes and liver metastases (Any T, Any N, M1). Separate tumor samples from the primary tumor, the metastatic lymph nodes and the liver metastasis were collected.
2014-04-01 | E-GEOD-56350 | biostudies-arrayexpress
Project description:Background: Cervical lymph node metastasis is a potent prognostic factor in oral squamous cell carcinoma (OSCC). However, lymph nodes resected by sentinel node biopsy or neck dissection are usually diagnosed by examining only one or two sections of the maximal cut surface. Accurate diagnosis of the metastasis in lymph nodes is important but depends on a heavy workload of the pathologist. In this study, we have attempted to identify novel molecular markers to find the harboring cancer cells in the lymph node and establish rapid detection method. Methods: We determined the gene expression profiles of 7 metastatic lymph nodes from patients with OSCC and 1 normal lymph node and 5 salivary glands from non-cancerous patients by microarray analysis. We found the overexpression genes in all metastatic lymph nodes. Subsequently, we examined the expression of these genes in newly 23 metastatic lymph nodes and 9 normal lymph nodes by real-time quantitative RT-PCR (qRT-PCR) assay. Moreover, the rapid detection of lymph node metastasis by these genes was examined using the reverse transcription loop-mediated isothermal amplification (RT-LAMP) method. Result: Among the 4 genes identified by microarray analysis, annexin A8 (ANXA8) and desmoglein 3 (DSG3) were detected in all metastatic lymph nodes at a much higher level but not in normal lymph nodes at all by qRT-PCR. Furthermore, RT-LAMP method targeting ANXA8 rapidly detected almost lymph nodes with metastasis. Conclusions: ANXA8 could be a useful marker for detecting lymph node metastasis in OSCC. Using AB1700 system, we determined the gene expression profiles of lymph nodes with metastasis of OSCC. Normal lymph node and salivary gland tissues were used as control samples.
2015-12-21 | E-GEOD-70604 | biostudies-arrayexpress
Project description:The lungs are a frequent target of metastatic breast cancer cells, but the underlying molecular mechanisms are unclear. All existing data were obtained either using statistical association between gene expression measurements found in primary tumors and clinical outcome, or using experimentally derived signatures from mouse tumor models. Here, we describe a distinct approach that consists to utilize tissue surgically resected from lung metastatic lesions and compare their gene expression profiles with those from non-pulmonary sites, all coming from breast cancer patients. We demonstrate that the gene expression profiles of organ-specific metastatic lesions can be used to predict lung metastasis in breast cancer. We identified a set of 21 lung metastasis-associated genes. Using a cohort of 72 lymph node-negative breast cancer patients, we developed a six-gene prognostic classifier that discriminated breast primary cancers with a significantly higher risk of lung metastasis. We then validated the predictive ability of the six-gene signature in 3 independent cohorts of breast cancers consisting of a total of 721 patients. Finally, we demonstrated that the signature improves risk stratification independently of known standard clinical parameters and a previously established lung metastasis signature based on an experimental breast cancer metastasis model. Experiment Overall Design: We used microarrays to identify lung metastasis-related genes in a series of 23 patients with breast cancer metastases. No replicate, no reference sample.
2009-03-07 | E-GEOD-11078 | biostudies-arrayexpress
Project description:Background: Cervical lymph node metastasis is a potent prognostic factor in oral squamous cell carcinoma (OSCC). However, lymph nodes resected by sentinel node biopsy or neck dissection are usually diagnosed by examining only one or two sections of the maximal cut surface. Accurate diagnosis of the metastasis in lymph nodes is important but depends on a heavy workload of the pathologist. In this study, we have attempted to identify novel molecular markers to find the harboring cancer cells in the lymph node and establish rapid detection method. Methods: We determined the gene expression profiles of 7 metastatic lymph nodes from patients with OSCC and 1 normal lymph node and 5 salivary glands from non-cancerous patients by microarray analysis. We found the overexpression genes in all metastatic lymph nodes. Subsequently, we examined the expression of these genes in newly 23 metastatic lymph nodes and 9 normal lymph nodes by real-time quantitative RT-PCR (qRT-PCR) assay. Moreover, the rapid detection of lymph node metastasis by these genes was examined using the reverse transcription loop-mediated isothermal amplification (RT-LAMP) method. Result: Among the 4 genes identified by microarray analysis, annexin A8 (ANXA8) and desmoglein 3 (DSG3) were detected in all metastatic lymph nodes at a much higher level but not in normal lymph nodes at all by qRT-PCR. Furthermore, RT-LAMP method targeting ANXA8 rapidly detected almost lymph nodes with metastasis. Conclusions: ANXA8 could be a useful marker for detecting lymph node metastasis in OSCC.
2015-12-21 | GSE70604 | GEO
Project description:The project contains raw and result files from a proteomic profiling of a male breast cancer (MBC) case. Label-free quantification-mass spectrometry (LFQ-MS) and bioinformatics analysis were employed to investigate the differentially expressed proteins (DEPs) among distinct tissue samples: the primary breast tumor, axillary metastatic lymph nodes and the adjacent non-tumor breast tissue. An additional proteomic comparative analysis was performed with a primary breast tumor of a female patient. A number of Ingenuity® Pathway Analysis (IPA) (QIAGEN Inc.) and functional annotation tools were used to further analyze the DEPs. Altogether, our findings revealed deregulated proteins into signaling pathways involved in the cancer development and provided a landscape of proteomic data for the MBC research.
2021-09-08 | PXD012453 | Pride
Project description:To identify serum miRNAs as biomarkers for breast cancer, RNA from 7 serum pools (healthy volunteers: n=100, benign patients: n=100，cancer patients: n=94, Lymph nodes positive: n=36, lymph nodes negative: n=58, carcinoma in situ: n=25, infiltrating carcinoma: n=69) were screened by Affymetrix microarray 4.0.
2018-07-12 | E-MTAB-6652 | biostudies-arrayexpress
Project description:Metastasis remains the leading cause of death in breast cancer. However, little is known about the dynamic changes during the dissemination of breast cancer. Here, we generate single-cell RNA and spatial transcriptome of primary tumors and paired metastatic lymph nodes in 4 breast cancer patients. We identified a disseminated cancer cell cluster with high levels of oxidative phosphorylation (OXPHOS). We also noticed the transition between glycolysis and OXPHOS when dissemination initiates. Furthermore, this distinct cell cluster is distributed along the tumor’s leading edge.
2023-02-19 | GSE225600 | GEO
Project description:The lungs are a frequent target of metastatic breast cancer cells, but the underlying molecular mechanisms are unclear. All existing data were obtained either using statistical association between gene expression measurements found in primary tumors and clinical outcome, or using experimentally derived signatures from mouse tumor models. Here, we describe a distinct approach that consists to utilize tissue surgically resected from lung metastatic lesions and compare their gene expression profiles with those from non-pulmonary sites, all coming from breast cancer patients. We demonstrate that the gene expression profiles of organ-specific metastatic lesions can be used to predict lung metastasis in breast cancer. We identified a set of 21 lung metastasis-associated genes. Using a cohort of 72 lymph node-negative breast cancer patients, we developed a six-gene prognostic classifier that discriminated breast primary cancers with a significantly higher risk of lung metastasis. We then validated the predictive ability of the six-gene signature in 3 independent cohorts of breast cancers consisting of a total of 721 patients. Finally, we demonstrated that the signature improves risk stratification independently of known standard clinical parameters and a previously established lung metastasis signature based on an experimental breast cancer metastasis model. Keywords: Disease state analysis
2008-08-15 | GSE11078 | GEO