ArticleClinical Medicine Insights. Oncology2015
Transcriptome Analysis of Minimal Residual Disease in Subtypes of Pediatric B Cell Acute Lymphoblastic Leukemia.
Article in Clinical Medicine Insights. Oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Identification of Distinct Unmutated Chronic Lymphocytic Leukemia Subsets in Mice Based on Their T Cell Dependency.Frontiers in immunology · 2018Article
- Integrative Analysis of MicroRNA-Mediated Gene Signatures and Pathways Modulating White Blood Cell Count in Childhood Acute Lymphoblastic Leukemia.Biomarker insights · 2017Article
- Molecular Analysis of Central Nervous System Disease Spectrum in Childhood Acute Lymphoblastic Leukemia.Clinical Medicine Insights. Oncology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer and the leading cause of cancer-related death in children and adolescents. Minimal residual disease (MRD) is a strong, independent prognostic factor. The objective of this study was to identify molecular signatures distinguishing patients with positive MRD from those with negative MRD in different subtypes of ALL, and to identify molecular networks and biological pathways deregulated in response to positive MRD at day 46. We compared gene expression levels between patients with positive MRD and negative MRD in each subtype to identify differentially expressed genes. Hierarchical clustering was applied to determine their functional relationships. We identified subtype-specific gene signatures distinguishing patients with positive MRD from those with negative MRD. We identified the genes involved in cell cycle, apoptosis, transport, and DNA repair. We also identified molecular networks and biological pathways dysregulated in response to positive MRD, including Granzyme B, B-cell receptor, and PI3K signaling pathways.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.