Recent findings have identified competing endogenous RNAs (ceRNAs) as the drivers in many disease conditions, including cancers. The ceRNAs indirectly regulate each other by reducing the amount of microRNAs (miRNAs) available to target messenger RNAs (mRNAs). The ceRNA interactions mediated by miRNAs are modulated by a titration mechanism, i.e. large changes in the ceRNA expression levels either overcome, or relieve, the miRNA repression on competing RNAs; similarly, a very large miRNA overexpression may abolish competition. The ceRNAs are also called miRNA "decoys" or miRNA "sponges" and encompass different RNAs competing with each other to attract miRNAs for interactions: mRNA, long non-coding RNAs (lncRNAs), pseudogenes, or circular RNAs. Recently, we developed a computational method for identifying ceRNA-ceRNA interactions in breast invasive carcinoma. We were interested in unveiling which lncRNAs could exert the ceRNA activity. We found a drastic rewiring in the cross-talks between ceRNAs from the physiological to the pathological condition. The main actor of this dysregulated lncRNA-associated ceRNA network was the lncRNA PVT1, which revealed a net biding preference towards the miR-200 family members in normal breast tissues. Despite its up-regulation in breast cancer tissues, mimicked by the miR-200 family members, PVT1 stops working as ceRNA in the cancerous state. The specific conditions required for a ceRNA landscape to occur are still far from being determined. Here, we emphasized the importance of the relative concentration of the ceRNAs, and their related miRNAs. In particular, we focused on the withdrawal in breast cancer tissues of the PVT1 ceRNA activity and performed a gene expression and sequence analysis of its multiple isoforms. We found that the PVT1 isoform harbouring the binding site for a representative miRNA of the miR-200 family shows a drastic decrease in its relative concentration with respect to the miRNA abundance in breast cancer tissues, providing a plausibility argument to the breakdown of the sponge program orchestrated by the oncogene PVT1.
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J Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
Cien Saude Colet
January 2025
Universidade Federal do Ceará. R. Alexandre Baraúna 1115, Rodolfo Teófilo. 60430-160 Fortaleza CE Brasil.
Mammography is one of the main methods available for breast cancer screening in Brazil. However, differences in timely access and performance of the exam can be highlighted based on social determinants of health, considered relevant due to their influence on the health situation of a population. Thus, the present study aimed to identify the social determinants of health associated with access to and performance of mammography in Brazilian women.
View Article and Find Full Text PDFCien Saude Colet
January 2025
Instituto René Rachou, Fundação Oswaldo Cruz (Fiocruz Minas). Av. Augusto de Lima 1715, Barro Preto. 30190-002 Belo Horizonte MG Brasil.
This article aims to identify the relationship between material deprivation and mortality from breast, cervical, and prostate neoplasms in the Brazilian adult population and the relationship between ethnicity/skin color and material deprivation. This cross-sectional ecological study calculated the mean mortality rate per 100,000 inhabitants, and deaths were standardized by age and gender and redistributed per to ill-defined causes, stratified by age group and ethnicity/skin color. We applied the Negative Binomial model, containing the interaction between ethnicity/skin color and the Brazilian Deprivation Index (IBP).
View Article and Find Full Text PDFBrief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFCancer Res
January 2025
INSERM U1194, Montpellier Cedex 05, Occitanie, France.
BRCA1 deficiency is observed in approximately 25% of triple-negative breast cancer (TNBC). BRCA1, a key player of homologous recombination (HR) repair, is also involved in stalled DNA replication fork protection and repair. Here, we investigated the sensitivity of BRCA1-deficient TNBC models to the frequently used replication chain terminator gemcitabine, which does not directly induce DNA breaks.
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