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Hematopoietic stem cells (HSCs) provide all types of blood cells during the entire life of the organism. HSCs are mainly quiescent and can eventually enter the cell cycle to differentiate. HSCs are maintained and tightly regulated in a particular environment. The stem cell niche regulates dormancy and awakening. Deregulations of this interplay can lead to hematopoietic failure and diseases. In this paper, we present a Boolean network model that recapitulates HSC regulation in virtue of external signals coming from the niche. This Boolean network integrates and summarizes the current knowledge of HSC regulation and is based on extensive literature research. Furthermore, dynamic simulations suggest a novel systemic regulation of TP53 in homeostasis. Thereby, our model indicates that TP53 activity is balanced depending on external stimulations, engaging a regulatory mechanism involving ROS regulators and RAS activated transcription factors. Finally, we investigated different mouse models and compared them to knockout simulations. Here, the model could recapitulate observed behaviors and thus sustains our results.
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http://dx.doi.org/10.3389/fphys.2020.00848 | DOI Listing |
Annu Rev Pathol
September 2025
3Department of Pathology, Stanford University, Stanford, California, USA;
Clonal hematopoiesis, originally identified as a precursor to hematologic malignancies, has emerged as a significant factor in various nonmalignant diseases. Recent research highlights how somatic mutations in hematopoietic stem cells lead to the expansion of circulating mutated immune cells that exert profound effects on organ function and disease progression. These mutated clones display altered inflammatory profiles and tissue-specific functional consequences, contributing to various diseases including atherosclerotic cardiovascular disease, osteoporosis, heart failure, and neurodegenerative conditions.
View Article and Find Full Text PDFFam Cancer
September 2025
School of Social Policy and Practice, University of Pennsylvania, Philadelphia, USA.
Li-Fraumeni syndrome (LFS) is an early-onset cancer syndrome caused by pathogenic germline TP53 variants. Adolescents and young adults (AYAs) with LFS may have challenges navigating new romantic partnerships given the significant effects of LFS on multiple life domains that also affect partners (e.g.
View Article and Find Full Text PDFUrologia
September 2025
UROGIV Research Group, School of Medicine, Universidad Del Valle, Cali, Colombia.
Background And Objective: Bladder cancer (BC) is the sixth most common cancer in the U.S., with risk factors such as smoking, older age, and male sex.
View Article and Find Full Text PDFSignal Transduct Target Ther
September 2025
State Key Laboratory of Molecular Oncology & Department of Medical Oncology & Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Small-cell lung cancer (SCLC), an aggressive neuroendocrine tumor strongly associated with exposure to tobacco carcinogens, is characterized by early dissemination and dismal prognosis with a five-year overall survival of less than 7%. High-frequency gain-of-function mutations in oncogenes are rarely reported, and intratumor heterogeneity (ITH) remains to be determined in SCLC. Here, via multiomics analyses of 314 SCLCs, we found that the ASCL1/MKI67 and ASCL1/CRIP2 clusters accounted for 74.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.
Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.