Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA194525 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Profiling of three leiomyosarcoma molecular subtypes with RNA-sequencing
| PRJNA264379 | ENA
Project description:Leiomyosarcoma (LMS) is a malignant neoplasm of smooth muscle and is an aggressive soft tissue tumor, have complex genetic abnormalities and could be defined as three molecular subtypes. Since that the molecular heterogeneity of LMS, the pathogenesis analysis per subtype will be highly necessary and helpful to understand the etiology of this more common sarcoma. Within this study, we collected four Myometrium, three Leiomyoma, three LMS cell lines and 99 LMSs (GSE45510), performed the system-wide gene expression profiling by 3'end RNA Sequencing, and found that there are significant different molecular pathways along the pathogenesis for those three molecular subtypes.
2015-05-19 | E-GEOD-54511 | biostudies-arrayexpress
Project description:'Precision medicine' is a concept that by utilizing modern molecular diagnostics, an effective therapy is accurately applied for each cancer patient to improve their survival rates. The aim of this study was to compare the molecular subtypes of triple negative breast cancer (TNBC) between Taiwanese and other datasets.
2017-06-13 | GSE95700 | GEO
Project description:Different molecular pathways along with pathogenesis of three subtypes of Leiomyosarcoma
| PRJNA236775 | ENA
Project description:In the present work, we aimed to carry out a pipeline based on quantitative proteomics tools to discover, verify and validate circulating proteins that are associated with the presence in serum of RF and ACPA and may therefore have potential for the stratification of RA patients and the application of precision medicine strategies based on these molecular signatures.
2023-03-11 | PXD037386 | Pride
Project description:Leiomyosarcoma (LMS) is a malignant neoplasm with smooth muscle differentiation, and there are three molecular subtypes of LMS which have been defined previously by our lab. To further validate these subtypes and identify potential therapeutic targets in each subtype, we profiled the LMS cases from each subtype with RNA-Seq technology.
2015-12-25 | GSE62544 | GEO
Project description:The molecular etiology of uterine leiomyosarcoma (ULMS) is poorly understood, which accounts for the wide disparity in outcomes among women with this disease. We examined and compared the molecular profiles of ULMS, fibroids, and normal myometrium (NL) to identify clinically relevant molecular subtypes. RNA was hybridized to Affymetrix U133A 2.0 transcription microarrays. Differentially expressed genes and pathways were identified using standard methods.
2015-01-08 | GSE64763 | GEO
Project description:One challenge of cancer precision medicine is the heterogeneity of genetic and non-genetic alterations that result in dysfunctional molecular pathways. As an emerging drug discovery effort, dysregulation in Hippo pathway signaling is known to drive oncogenesis across numerous cancer types but lacks recurrent mutation(s) that are often found in other canonical signaling pathways. Here, we use first principles approach to develop a machine-learning framework to identify a robust, lineage-independent gene expression signature to quantify Hippo pathway dependency in cancers. Through integrating data from multi-omics platforms, this data-driven approach has enabled identifying a proposed combination with MAPK inhibition for direct targeting of Hippo pathway dependent cancers for which we then elucidate the underlying molecular mechanism. The results underscore how a multifaceted approach, computational models combined with laboratory efforts, can accelerate precision medicine efforts toward co-targeting Hippo and MAPK pathways, an approach that can be generalized to other key cancer signaling pathways to define therapeutic strategies.
2021-01-26 | GSE161018 | GEO
Project description:One challenge of cancer precision medicine is the heterogeneity of genetic and non-genetic alterations that result in dysfunctional molecular pathways. As an emerging drug discovery effort, dysregulation in Hippo pathway signaling is known to drive oncogenesis across numerous cancer types but lacks recurrent mutation(s) that are often found in other canonical signaling pathways. Here, we use first principles approach to develop a machine-learning framework to identify a robust, lineage-independent gene expression signature to quantify Hippo pathway dependency in cancers. Through integrating data from multi-omics platforms, this data-driven approach has enabled identifying a proposed combination with MAPK inhibition for direct targeting of Hippo pathway dependent cancers for which we then elucidate the underlying molecular mechanism. The results underscore how a multifaceted approach, computational models combined with laboratory efforts, can accelerate precision medicine efforts toward co-targeting Hippo and MAPK pathways, an approach that can be generalized to other key cancer signaling pathways to define therapeutic strategies.
2021-01-26 | GSE161010 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here we construct a high-resolution molecular landscape of the multicellular subtypes and spatial communities that compose PAC using single-nucleus RNA-seq and whole-transcriptome digital spatial profiling (SP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment-naïve. We uncovered expression programs across malignant cells and fibroblasts, including a newly-identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities: classical, squamoid-basaloid, and treatment-enriched. Our refined molecular and cellular taxonomy can advance precision oncology in PAC through stratification in clinical trials and as roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.
2022-05-18 | GSE202051 | GEO