ArticleBMC research notes2011
Computational analysis of expression of human embryonic stem cell-associated signatures in tumors.
Article in BMC research notes, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Classification of lung adenocarcinoma based on stemness scores in bulk and single cell transcriptomes.Computational and structural biotechnology journal · 2022Article
- Transcriptome analysis reveals high tumor heterogeneity with respect to re-activation of stemness and proliferation programs.PloS one · 2022Article
- Article
- MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis.The Journal of clinical investigation · 2014Article
- Computational analysis of transcriptional circuitries in human embryonic stem cells reveals multiple and independent networks.BioMed research international · 2014Article
- Discovery of molecular associations among aging, stem cells, and cancer based on gene expression profiling.Chinese journal of cancer · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe cancer stem cell model has been proposed based on the linkage between human embryonic stem cells and human cancer cells. However, the evidences supporting the cancer stem cell model remain to be collected. In this study, we extensively examined the expression of human embryonic stem cell-associated signatures including core genes, transcription factors, pathways and microRNAs in various cancers using the computational biology approach.
resultsWe used the class comparison analysis and survival analysis algorithms to identify differentially expressed genes and their associated transcription factors, pathways and microRNAs among normal vs. tumor or good prognosis vs. poor prognosis phenotypes classes based on numerous human cancer gene expression data. We found that most of the human embryonic stem cell- associated signatures were frequently identified in the analysis, suggesting a strong linkage between human embryonic stem cells and cancer cells.
conclusionsThe present study revealed the close linkage between the human embryonic stem cell associated gene expression profiles and cancer-associated gene expression profiles, and therefore offered an indirect support for the cancer stem cell theory. However, many interest issues remain to be addressed further.
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.