SynthesisInternational journal of molecular sciences2023
Systemic Alterations of Cancer Cells and Their Boost by Polyploidization: Unicellular Attractor (UCA) Model.
Synthesis in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Inflamed Yet Immune-Evasive? A Transcriptomic Meta-Analysis Identifies Conserved Inflammatory, Developmental, and Neuronal Signatures Associated with Polyploid Giant Cancer Cells.International journal of molecular sciences · 2026Pooled it
- Polyploid giant cancer cells (PGCC): short-term return to multicellularity.Biological research · 2025Article
- Transcriptome-Wide Insights: Neonatal Lactose Intolerance Promotes Telomere Damage, Senescence, and Cardiomyopathy in Adult Rat Heart.International journal of molecular sciences · 2025Article
- Polyploidy Promotes Hypertranscription, Apoptosis Resistance, and Ciliogenesis in Cancer Cells and Mesenchymal Stem Cells of Various Origins: Comparative Transcriptome In Silico Study.International journal of molecular sciences · 2024Article
- Review
- Special Issue "Advances in Genome Regulation in Cancer".International journal of molecular sciences · 2023Article
- Tetraploidization Increases the Motility and Invasiveness of Cancer Cells.International journal of molecular sciences · 2023Article
- The Price of Human Evolution: Cancer-Testis Antigens, the Decline in Male Fertility and the Increase in Cancer.International journal of molecular sciences · 2023Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Using meta-analyses, we introduce a unicellular attractor (UCA) model integrating essential features of the 'atavistic reversal', 'cancer attractor', 'somatic mutation', 'genome chaos', and 'tissue organization field' theories. The 'atavistic reversal' theory is taken as a keystone. We propose a possible mechanism of this reversal, its refinement called 'gradual atavism', and evidence for the 'serial atavism' model. We showed the gradual core-to-periphery evolutionary growth of the human interactome resulting in the higher protein interaction density and global interactome centrality in the UC center. In addition, we revealed that UC genes are more actively expressed even in normal cells. The modeling of random walk along protein interaction trajectories demonstrated that random alterations in cellular networks, caused by genetic and epigenetic changes, can result in a further gradual activation of the UC center. These changes can be induced and accelerated by cellular stress that additionally activates UC genes (especially during cell proliferation), because the genes involved in cellular stress response and cell cycle are mostly of UC origin. The functional enrichment analysis showed that cancer cells demonstrate the hyperactivation of energetics and the suppression of multicellular genes involved in communication with the extracellular environment (especially immune surveillance). Collectively, these events can unleash selfish cell behavior aimed at survival at all means. All these changes are boosted by polyploidization. The UCA model may facilitate an understanding of oncogenesis and promote the development of therapeutic strategies.
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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.