Gene expression based profiling of pleomorphic xanthoastrocytoma highlights two prognostic subgroups
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PROVIDER: PRJNA714538 | ENA |
REPOSITORIES: ENA
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Project description:First comprehensive analysis highlighting distinct molecular subgroups of PXA. The DEGs between two clusters may potentially be used for developing histology independent classification scheme, prognostication and suggest prospective therapeutic targets
2021-12-14 | GSE168904 | GEO
Project description:BackgroundPleomorphic xanthoastrocytomas (PXAs) are rare, accounting for less than 1% of astrocytomas, and commonly occur in young patients. The majority are WHO grade II. A fraction of tumors that present or recur with malignant change are classified as anaplastic (APXA, grade III). Limited data are available on their molecular characteristics.MethodologyGenome-wide expression profiling of 14 PXA and 6 APXAs was performed by microarray. Among differentially expressed genes (DEGs), Cyclin-Dependent Kinase 14 (CDK14) and Mitochondrial Fission Process 1 (MTFP1) were validated by qRT PCR.ResultUnsupervised hierarchical clustering revealed two distinct molecular clusters (Cluster 1: 10 PXA, 3 APXA and Cluster 2: 4 PXA, 3 APXA) with grade II and III tumors distributed in both highlighting molecular heterogeneity within the same grade. There was an insignificant difference in age, sex, immunohistochemical profile, frequency of BRAF mutation, or CDKN2A deletion among the two clusters. Significantly, worse progression-free survival was observed in cluster 2 (P=0.003). mRNA profiling-based prediction of recurrence was superior to and independent of histological grade, BRAF mutation, or CDKN2A deletion status. A total of 10 upregulated and 418 downregulated genes were identified between the PXA clusters. qRT-PCR validation of CDK14 (upregulated in cluster 2) and MTFP1 (upregulated in cluster 1) showed strong concordance with expression array data.ConclusionThis is the first comprehensive study highlighting distinct molecular subgroups of PXA. The differentially expressed genes between two clusters may potentially be used for developing histology independent classification schemes, prognostication and may serve as prospective therapeutic targets for PXA patients.
| S-EPMC8902531 | biostudies-literature
Project description:Medullary breast cancers (MBC) display a basal profile, but a favorable prognosis. We hypothesized that a previously published 368-gene expression signature associated with MBC might serve to define a prognostic classifier in basal cancers. We collected public gene expression and histoclinical data of 2145 invasive early breast adenocarcinomas. We developed a Support Vector Machine (SVM) classifier based on this 368-gene list in a learning set, and tested its predictive performances in an independent validation set. Then, we assessed its prognostic value and that of six prognostic signatures for disease-free survival (DFS) in the remaining 2034 samples. The SVM model accurately classified all MBC samples in the learning and validation sets. A total of 466 cases were basal across other sets. The SVM classifier separated them into two subgroups, subgroup 1 (resembling MBC) and subgroup 2 (not resembling MBC). Subgroup 1 exhibited 71% 5-year DFS, whereas subgroup 2 exhibited 50% (p=9.93E-05). The classifier outperformed the classical prognostic variables in multivariate analysis, conferring lesser risk for relapse in subgroup 1 (HR=0.52, p=3.9E-04). This prognostic value was specific to the basal subtype, in which none of the other prognostic signatures was informative.
2010-05-05 | GSE21653 | GEO
Project description:Medulloblastoma in adults: Cytogenetic phenotypes identify prognostic subgroups
| PRJNA704366 | ENA
Project description:Soft tissue sarcoma diagnostics and prognostics are challenging, particularly in highly malignant and pleomorphic subtypes such as undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS). We applied 32K BAC-arrays and gene expression profiling to 18 extremity soft tissue LMS and 31 extremity soft tissue UPS with the aim to identify molecular subtype signatures and genomic prognostic markers. Both the gains/losses and gene expression signatures revealed striking similarities between UPS and LMS, which were indistinguishable using unsupervised hierarchical cluster analysis and significance analysis for microarrays. Gene expression analysis revealed just 9 genes, among them Tropomyosin beta, that were differentially expressed. Loss of 4q31 (encompassing the SMAD1 locus), loss of 18q22 and tumor necrosis were identified as independent predictors of metastasis in multivariate stepwise Cox regression analysis. Combined analysis applying loss of 4q31 and 18q22 and presence of necrosis improved the area under receiver operating characteristic curve for metastasis prediction from 0.64 to 0.86. The extensive genetic similarities between extremity soft tissue UPS and LMS suggest a shared lineage of these STS subtypes and the new and independent genetic prognosticators identified hold promise for refined prognostic determination in high-grade, genetically complex STS. Genomic DNA was extracted from a total of 49 samples, 31 Undifferentiated pleomorphic Sarcomas and 18 Leiomyosarcomas. The DNA was labeled using Bioprime array CGH labeling kit (Invitrogen). Promega pooled male DNA was used as reference. Labeled DNA was hybridized onto BAC arrays containing ~32 000 BAC clones printed in singlets. BAC arrays were produced at the SWEGENE DNA Microarray Facility at Lund University.
2010-10-08 | E-GEOD-13775 | biostudies-arrayexpress
Project description:Integrative Analysis Defines Distinct Prognostic Subgroups of Intrahepatic Cholangiocarcinoma
| PRJNA830481 | ENA
Project description:Medullary breast cancers (MBC) display a basal profile, but a favorable prognosis. We hypothesized that a previously published 368-gene expression signature associated with MBC might serve to define a prognostic classifier in basal cancers. We collected public gene expression and histoclinical data of 2145 invasive early breast adenocarcinomas. We developed a Support Vector Machine (SVM) classifier based on this 368-gene list in a learning set, and tested its predictive performances in an independent validation set. Then, we assessed its prognostic value and that of six prognostic signatures for disease-free survival (DFS) in the remaining 2034 samples. The SVM model accurately classified all MBC samples in the learning and validation sets. A total of 466 cases were basal across other sets. The SVM classifier separated them into two subgroups, subgroup 1 (resembling MBC) and subgroup 2 (not resembling MBC). Subgroup 1 exhibited 71% 5-year DFS, whereas subgroup 2 exhibited 50% (p=9.93E-05). The classifier outperformed the classical prognostic variables in multivariate analysis, conferring lesser risk for relapse in subgroup 1 (HR=0.52, p=3.9E-04). This prognostic value was specific to the basal subtype, in which none of the other prognostic signatures was informative. The IPC series contained frozen tumor samples obtained from 266 early breast cancer patients who underwent initial surgery in our institution between 1992 and 2004. They included 227 cases previously reported {Finetti, 2008 #1758} and 39 additional cases, all similarly profiled using Affymetrix U133 Plus 2.0 human oligonucleotide microarrays as previously described {Finetti, 2008 #1758}. The study was approved by the IPC review board, and informed consent was available for each case. Gene expression data of 266 BCs were quantified by using whole-genome DNA microarrays (HG-U133 plus 2.0, Affymetrix).
2010-05-05 | E-GEOD-21653 | biostudies-arrayexpress
Project description:Soft tissue sarcoma diagnostics and prognostics are challenging, particularly in highly malignant and pleomorphic subtypes such as undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS). We applied 32K BAC-arrays and gene expression profiling to 18 extremity soft tissue LMS and 31 extremity soft tissue UPS with the aim to identify molecular subtype signatures and genomic prognostic markers. Both the gains/losses and gene expression signatures revealed striking similarities between UPS and LMS, which were indistinguishable using unsupervised hierarchical cluster analysis and significance analysis for microarrays. Gene expression analysis revealed just 9 genes, among them Tropomyosin beta, that were differentially expressed. Loss of 4q31 (encompassing the SMAD1 locus), loss of 18q22 and tumor necrosis were identified as independent predictors of metastasis in multivariate stepwise Cox regression analysis. Combined analysis applying loss of 4q31 and 18q22 and presence of necrosis improved the area under receiver operating characteristic curve for metastasis prediction from 0.64 to 0.86. The extensive genetic similarities between extremity soft tissue UPS and LMS suggest a shared lineage of these STS subtypes and the new and independent genetic prognosticators identified hold promise for refined prognostic determination in high-grade, genetically complex STS.
2009-03-24 | GSE13775 | GEO
Project description:Undifferentiated pleomorphic sarcoma (UPS) and related tumors are the most common type of soft tissue sarcoma. However, this spectrum of tumors has different etiologies with varying rates of metastasis and survival. Two dermal-based neoplasms in this class of pleomorphic sarcomas, atypical fibroxanthoma (AFX) and pleomorphic dermal sarcoma (PDS), are challenging to differentiate at initial biopsy but vary significantly in prognosis. We performed single-cell transcriptomics on five AFX and PDS biopsy specimens as well as both single-cell and spatial transcriptomics on one PDS excision specimen to better characterize these tumors. The top differential genes between AFX and PDS were predictive of overall survival in 17 other cancers included in the Human Protein Atlas. Of these genes, COL6A3 and BGN predicted overall survival and metastasis-free survival in independent cohorts of 46 and 38 UPS tumors, respectively. COL6A3 was most predictive of overall survival in UPS patients and outperformed an established sarcoma prognostic gene panel at predicting metastasis in UPS.
2024-11-10 | GSE281529 | GEO
Project description:Undifferentiated pleomorphic sarcoma (UPS) and related tumors are the most common type of soft tissue sarcoma. However, this spectrum of tumors has different etiologies with varying rates of metastasis and survival. Two dermal-based neoplasms in this class of pleomorphic sarcomas, atypical fibroxanthoma (AFX) and pleomorphic dermal sarcoma (PDS), are challenging to differentiate at initial biopsy but vary significantly in prognosis. We performed single-cell transcriptomics on five AFX and PDS biopsy specimens as well as both single-cell and spatial transcriptomics on one PDS excision specimen to better characterize these tumors. The top differential genes between AFX and PDS were predictive of overall survival in 17 other cancers included in the Human Protein Atlas. Of these genes, COL6A3 and BGN predicted overall survival and metastasis-free survival in independent cohorts of 46 and 38 UPS tumors, respectively. COL6A3 was most predictive of overall survival in UPS patients and outperformed an established sarcoma prognostic gene panel at predicting metastasis in UPS.
2024-11-08 | GSE281096 | GEO