Intratumor heterogeneity presents a major hurdle in cancer therapy. Most current research studies consider tumors as single entities and overlook molecular diversity between heterogeneous state(s) of different cells assumed to be homogenous. The present approach was designed for fluorescence-activated cell sorting-based resolution of heterogeneity arising from cancer stem cell (CSC) hierarchies and genetic instability in ovarian tumors, followed by microarray-based expression profiling of sorted fractions. Through weighted gene correlation network analyses, we could assign enriched modules of co-regulated genes to each fraction. Such gene modules often correlate with biological functions; one such specific association was the enrichment of CD53 expression in CSCs, functional validation indicated CD53 to be a tumor-initiating cell- rather than quiescent CSC-marker. Another association defined a state of poise for stress-induced metastases in aneuploid cells. Our results thus emphasize the need for studying cell-specific functionalities relevant to regeneration, drug resistance and disease progression in discrete tumor cell fractions.
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http://dx.doi.org/10.1038/srep25261 | DOI Listing |
In the current cybersecurity landscape, Distributed Denial of Service (DDoS) attacks have become a prevalent form of cybercrime. These attacks are relatively easy to execute but can cause significant disruption and damage to targeted systems and networks. Generally, attackers perform it to make reprisal but sometimes this issue can be authentic also.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Mathematics, Aswan University, Faculty of Science, Aswan, Egypt.
In this work, bridge network model with Rayleigh distribution lifetimes is used. Two main techniques are calculated to upgrade this model: reduction and redundancy techniques. In order to compare the effectiveness of the various approaches, the survival function, the mean time to failure and gamma-fractiles for the original and upgraded model are calculated.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Cancer Biology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
This study identifies microRNAs (miRNAs) with significant discriminatory power in distinguishing melanoma from nevus, notably hsa-miR-26a and hsa-miR-211, which have exhibited diagnostic potential with accuracy of 81% and 78% respectively. To enhance diagnostic accuracy, we integrated miRNAs into various machine-learning (ML) models. Incorporating miRNAs with AUC scores above 0.
View Article and Find Full Text PDFSTAR Protoc
January 2025
Department of Cell and Molecular Biology, SciLifeLab, Karolinska Institutet, 171 77 Stockholm, Sweden. Electronic address:
Drugs that target specific proteins often have off-target effects. We present a protocol using artificial neural networks to model cellular transcriptional responses to drugs, aiming to understand their mechanisms of action. We detail steps for predicting transcriptional activities, inferring drug-target interactions, and explaining the off-target mechanism of action.
View Article and Find Full Text PDFCancer Med
January 2025
Department of Respiratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, People's Republic of China.
Background: Lung adenocarcinoma (LUAD) exhibits molecular heterogeneity, with mitochondrial damage affecting progression. The relationship between mitochondrial damage and immune infiltration, and Weighted Gene Co-expression Network Analysis (WGCNA)-derived biomarkers for LUAD classification and prognosis, remains unexplored.
Aims: The objective of our research is to identify gene modules closely related to the clinical stages of LUAD using the WGCNA method.
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