Genomic classification and identification of the cell of origin of pediatric mixed phenotype acute leukemia
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA448174 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Molecular classification of histological origin of NSCLC
| PRJNA707488 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-10-18 | GSE112561 | GEO
Project description:Lung cancer is one of the most common malignant tumors in the world. The latest edition of WHO classifies lung cancer on the basis of histological morphology and molecular typing, which is a relatively complete pathological classification of lung cancer at present. However, in clinical practice, it is difficult to make accurate subtype classification of NSCLC only by using morphological structure and immunohistochemical characteristics, and the degree of coincidence with gene mutation and clinicopathological parameters is poor, which has limited guiding effect on clinical diagnosis and treatment. In this study, we proposed Molecular Pathological Classification Model of NSCLC Tissue Origin.
2022-04-01 | GSE168466 | GEO
Project description:Mixed phenotype (MP) in acute leukemias poses unique classification and management dilemmas and can be seen in entities other than de novo mixed phenotype acute leukemia (MPAL). Although WHO classification empirically recommends excluding AML with myelodysplasia related changes (AML-MRC) and therapy related AML (t-AML) with mixed phenotype (referred to as “AML-MP”) from MPAL, there is lack of studies investigating the clinical, genetic, and biologic features of AML-MP. We report the first cohort of AML-MP integrating their clinical, immunophenotypic, genomic and transcriptomic features with comparison to MPAL and AML without MP. Patients with AML-MP share similar clinical and genetic features to its AML counterpart but differs from MPAL. AML-MP harbors more frequent RUNX1 mutations than AML without MP and MPAL. RUNX1 mutations or complex karyotypes did not impact the survival of MPAL patients. Unsupervised hierarchal clustering based on immunophenotype identified biologically distinct clusters with phenotype/genotype correlation and outcome differences. Furthermore, transcriptomic analysis showed an enrichment for stemness signature in AML-MP and AML without MP as compared to MPAL. Lastly, MPAL but not AML-MP often switched to lymphoid only immunophenotype after treatment. Expression of transcription factors critical for lymphoid differentiation were upregulated only in MPAL, but not in AML-MP. Our study for the first time demonstrates that AML-MP clinically and biologically resembles its AML counterpart without MP and differs from MPAL, supporting the recommendation to exclude these patients from the diagnosis of MPAL. Future studies are needed to elucidate the molecular mechanism of mixed phenotype in AML.
2024-08-28 | GSE275859 | GEO
Project description:We examined if pediatric AMLs rank-ordered according to C/EBPδ expression showed the activation of similar pathways. AML samples were dichotomized into groups including the upper quartile (Q1) and the lower three quartiles (Q2-4) according to their C/EBPδ expression values. Moreover, AML samples were associated to French-American-British (FAB) classification.
2016-06-21 | GSE75461 | GEO
Project description:In this study gene expression profiles for 307 cases of advanced bladder cancers were compared to molecular phenotype at the tumor cell level. TUR-B tissue for RNA extraction was macrodissected from the close vicinity of the tissue sampled for immunohistochemistry to ensure high-quality sampling and to minimize the effects of intra-tumor heterogeneity. Despite excellent agreement between gene expression values and IHC-score at the single marker level, broad differences emerge when samples are clustered at the global mRNA versus tumor cell (IHC) levels. Classification at the different levels give different results in a systematic fashion, which implicates that analysis at both levels is required for optimal subtype-classification of bladder cancer.
2017-03-13 | GSE83586 | GEO
Project description:RNA sequencing analysis was performed from bone marrow samples of 24 adult mixed phenotype acute leukemia (MPAL) patients
2018-04-25 | GSE113601 | GEO
Project description:Cavitating ultrasonic aspirator devices are frequently used in pediatric neurosurgery for efficient microsurgical resection of brain tumours while minimizing tissue damage to surrounding healthy brain. Within this study molecular diagnostics using methylation-based classification of ultrasonic aspirated samples was performed and performance against routine microarray diagnostics was assessed.
2024-02-08 | GSE255044 | GEO
Project description:Carcinomas of unknown primary origin constitute 3-5% of all newly diagnosed metastatic cancers, of which the primary source is difficult to classify with current histological methods. Effective cancer treatment depends on early and accurate identification of the tumor, which is why patients with metastases of unknown origin have poor prognosis and short survival. Because microRNA expression is highly tissue specific, the microRNA profile of a metastasis may be used to identify its origin. As a first step to realize this goal, we evaluated the potential of microRNA profiling for identification of the primary tumor of known metastases. 208 formalin-fixed paraffin-embedded samples representing 15 different histologies were profiled on an LNA-enhanced microarray platform, which allows for highly sensitive and specific detection of microRNA. Based on these data, we developed and cross-validated a novel classification algorithm, LASSO (Least Absolute Shrinkage and Selection Operator), which had an overall accuracy of 85%. When the classifier was applied on an independent test set of 48 metastases, the primary site was correctly identified in 42 cases (88% accuracy). Our findings suggest that microRNA expression profiling on paraffin tissue can efficiently predict the primary origin of a tumor, and may provide pathologists with a molecular diagnostic tool that can improve their capability to correctly identify the origin of hitherto unidentifiable metastatic tumors, and eventually, enable tailored therapy. 94 samples
2013-12-01 | E-GEOD-50890 | biostudies-arrayexpress
Project description:Carcinomas of unknown primary origin constitute 3-5% of all newly diagnosed metastatic cancers, of which the primary source is difficult to classify with current histological methods. Effective cancer treatment depends on early and accurate identification of the tumor, which is why patients with metastases of unknown origin have poor prognosis and short survival. Because microRNA expression is highly tissue specific, the microRNA profile of a metastasis may be used to identify its origin. As a first step to realize this goal, we evaluated the potential of microRNA profiling for identification of the primary tumor of known metastases. 208 formalin-fixed paraffin-embedded samples representing 15 different histologies were profiled on an LNA-enhanced microarray platform, which allows for highly sensitive and specific detection of microRNA. Based on these data, we developed and cross-validated a novel classification algorithm, LASSO (Least Absolute Shrinkage and Selection Operator), which had an overall accuracy of 85%. When the classifier was applied on an independent test set of 48 metastases, the primary site was correctly identified in 42 cases (88% accuracy). Our findings suggest that microRNA expression profiling on paraffin tissue can efficiently predict the primary origin of a tumor, and may provide pathologists with a molecular diagnostic tool that can improve their capability to correctly identify the origin of hitherto unidentifiable metastatic tumors, and eventually, enable tailored therapy.
2013-12-01 | GSE50890 | GEO