Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA236747 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication.
2014-08-18 | GSE54467 | GEO
Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication. Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. We previously analyzed the distribution of survival times in these samples and identified more favorable and less favorable groups as patients having time from surgery to death from melanoma greater than 4 years with no sign of relapse (n=25) or less than 1 year (n=22), respectively (Mann et al. 2013, PMID: 22931913). Since that publication, survival data have been re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset. The current survival data are considered to be more accurate. MRNA expression profiling and somatic mutation profiling, were performed as previously described in Mann et al. 2013 (PMID: 22931913).
2014-08-18 | E-GEOD-54467 | biostudies-arrayexpress
Project description:microRNA expression profiling and its integration with mRNA in metastatic melanoma reveal associations with BRAF mutation status and patient prognosis
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Project description:Liquid biopsies are becoming imperative on early patient diagnosis, prognosis and evaluation of residual disease. The use of circulating extracellular vesicles (EVs) as surrogate markers of tumor progression could be a powerful tool in the clinical setting. EVs in plasma have emerged as a non-invasive option to detect metastatic outcome, however sensitivity is low. Here we have characterized the lymph obtained after postoperative lymphadenectomy as a novel biological fluid enriched in EVs. Our proteomic profiling and BRAFV600E/K status determination demonstrate for the first time that EVs from the lymph of melanoma patients are enriched in melanoma-associated proteins and are useful for BRAF mutations detection. Melanoma oncogenic pathways, immunomodulation and platelet activating proteins are enriched in lymph-derived exosomes from patients with distal lymph node spread compared to local/early spreading. Furthermore, patients positive for BRAFV600E mutation on lymph-circulating vesicles had a shorter time of relapse. These data encourage the analysis of lymph-circulating EVs for detection of residual disease and recurrence.
2019-03-13 | PXD012042 | Pride
Project description:Immunotherapy and targeted therapy dramatically changed the treatment of metastatic melanoma. Yet, many patients do not respond to these treatments and improve the understanding of response and resistance is an urgent need. Thus, we utilized mass spectrometry-based proteomic analysis of 185 metastatic melanoma samples. Metastases from different sites demonstrate differences in cellular processes such as immune, metabolism, translation and proliferation. Complementary epidemiology analysis uncovers prognosis variance between different metastases locations after treated with anti-PD1. Examination of lung melanoma metastases reveals clinical and molecular heterogeneity that mainly reflected in immune-related processes. Analysis of BRAF mutation status and prior treatments with MAPK inhibitors also indicate differences in immune and metabolic processes and suggest a molecular basis for the combination of immunotherapy and targeted therapy. These results shed new light into biology and therapeutic resistant mechanisms and the pathogenesis of metastatic melanoma.
2020-12-23 | PXD020618 | Pride
Project description:The identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes. The molecular genetic alterations contributing to the pathogenesis of melanoma are incompletely defined and few independent prognostic features have been identified beyond the pathologic characteristics of the primary tumor. Early stage melanoma is frequently curable, in contrast to the inferior prognosis of melanomas with regional lymph nodes involvement and the incurability of distant metastatic disease. The identification of novel tumor-specific markers may improve our understanding of melanoma progression and prognostic accuracy. To find differentially expressed genes that can distinguish melanoma from normal tissue, we performed a whole genome expression profiling of 46 primary melanoma samples, 12 regional or distant metastases, and 16 normal skin samples using Affymetrix U133 2.0 Plus array. Our study generated lists of differentially expressed genes in melanoma and identified novel prognostic marker HMGA2. It is a novel, highly overexpressed melanoma gene associated with poor prognosis. The overexpression of HMGA2 is strongly associated with regional and distant metastases and serves as an independent predictor of disease-free survival and overall survival in melanoma. Melanoma samples were obtained through an IRB-approved protocol using informed consent at the University of Michigan Multidisciplinary Melanoma Clinic. A portion of pigmented lesions clinically suspicious for melanoma and known melanoma were sampled by punch biopsy at the time of excision. The punch biopsy was bisected; half was sent to for clinical diagnosis and the other half along with adjacent normal skin when available immediately snap-frozen in liquid nitrogen. Snap-frozen tissue was embedded in OCT (TissueTek) followed by frozen sectioning and H&E slide preparation. The slides were evaluated by dermatopathologist who identified areas with greater than 70% tumor cellularity, which were sampled for RNA extraction. Primary melanomas and melanoma metastases were derived from different patients. Metastatic samples included lymph nodes (n=8), subcutaneous soft tissue (n=2), spleen (n=1), and small intestine (n=1).
2012-06-07 | E-GEOD-15605 | biostudies-arrayexpress
Project description:Liquid biopsies are becoming imperative on early patient diagnosis, prognosis and evaluation of residual disease. The use of circulating extracellular vesicles (EVs) as surrogate markers of tumor progression could be a powerful tool in the clinical setting. EVs in plasma have emerged as a non-invasive option to detect metastatic outcome, however sensitivity is low. Here we have characterized the lymph obtained after postoperative lymphadenectomy as a novel biological fluid enriched in EVs. Our proteomic profiling and BRAFV600E/K status determination demonstrate for the first time that EVs from the lymph of melanoma patients are enriched in melanoma-associated proteins and are useful for BRAF mutations detection. Melanoma oncogenic pathways, immunomodulation and platelet activating proteins are enriched in lymph-derived exosomes from patients with distal lymph node spread compared to local/early spreading. Furthermore, patients positive for BRAFV600E mutation on lymph-circulating vesicles had a shorter time of relapse. These data encourage the analysis of lymph-circulating EVs for detection of residual disease and recurrence.ADDENDUM: After the proper verification of the cell lines analysed in this dataset where it is written "SKMel103" or "SK103", it should be read as "SKMel147". This affects not only the raw files but also all the search results files. Sorry for the inconveniences.
2021-02-26 | PXD009505 | Pride
Project description:Assessment of mutation on expression levels Transcriptomic profile of a matched primary and metastatic acral melanoma One Primary and one metastatic acral melanoma transcript expression were assayed (no matched normal)
2011-12-13 | E-GEOD-28909 | biostudies-arrayexpress
Project description:The identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes. The molecular genetic alterations contributing to the pathogenesis of melanoma are incompletely defined and few independent prognostic features have been identified beyond the pathologic characteristics of the primary tumor. Early stage melanoma is frequently curable, in contrast to the inferior prognosis of melanomas with regional lymph nodes involvement and the incurability of distant metastatic disease. The identification of novel tumor-specific markers may improve our understanding of melanoma progression and prognostic accuracy. To find differentially expressed genes that can distinguish melanoma from normal tissue, we performed a whole genome expression profiling of 46 primary melanoma samples, 12 regional or distant metastases, and 16 normal skin samples using Affymetrix U133 2.0 Plus array. Our study generated lists of differentially expressed genes in melanoma and identified novel prognostic marker HMGA2. It is a novel, highly overexpressed melanoma gene associated with poor prognosis. The overexpression of HMGA2 is strongly associated with regional and distant metastases and serves as an independent predictor of disease-free survival and overall survival in melanoma.
2012-06-08 | GSE15605 | GEO
Project description:We performed cancer-immune gene expression analysis on a case series of glioblastoma second surgery samples due to novel enhancement following chemoradiation that were confirmed based on clinico-pathologic outcome as disease progression (PD) or pseudoprogression (psPD). This was accomplished using an nCounter Pancancer 360 IO panel. Our goals were to (1) determine if psPD events could be distinguished from PD events using differences in immune cell activation versus cancer cell proliferation and (2) examine whether samples stratified based on their molecular profile in the same way as documented clinico-pathologic diagnosis.
2023-12-04 | GSE231994 | GEO