Browsing by Author "Bernal, Yanara"

Now showing 1 - 7 of 7
  • Thumbnail Image
    Publication
    A Comprehensive Analysis of the Effect of A>I(G) RNA-Editing Sites on Genotoxic Drug Response and Progression in Breast Cancer
    (2024) Bernal, Yanara; Blanco, Alejandro; Sagredo, Eduardo; Oróstica, Karen; Alfaro, Ivan; Marcelain, Katherine; Armisén, Ricardo
    Dysregulated A>I(G) RNA editing, which is mainly catalyzed by ADAR1 and is a type of post-transcriptional modification, has been linked to cancer. A low response to therapy in breast cancer (BC) is a significant contributor to mortality. However, it remains unclear if there is an association between A>I(G) RNA-edited sites and sensitivity to genotoxic drugs. To address this issue, we employed a stringent bioinformatics approach to identify differentially RNA-edited sites (DESs) associated with low or high sensitivity (FDR 0.1, log2 fold change 2.5) according to the IC50 of PARP inhibitors, anthracyclines, and alkylating agents using WGS/RNA-seq data in BC cell lines. We then validated these findings in patients with basal subtype BC. These DESs are mainly located in non-coding regions, but a lesser proportion in coding regions showed predicted deleterious consequences. Notably, some of these DESs are previously reported as oncogenic variants, and in genes related to DNA damage repair, drug metabolism, gene regulation, the cell cycle, and immune response. In patients with BC, we uncovered DESs predominantly in immune response genes, and a subset with a significant association (log-rank test p < 0.05) between RNA editing level in LSR, SMPDL3B, HTRA4, and LL22NC03-80A10.6 genes, and progression-free survival. Our findings provide a landscape of RNA-edited sites that may be involved in drug response mechanisms, highlighting the value of A>I(G) RNA editing in clinical outcomes for BC.
  • Thumbnail Image
    Publication
    ADAR-Mediated A>I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer
    (2024) Bernal, Yanara; Durán, Eduardo; Solar, Isidora; Sagredo, Eduardo; Armisén, Ricardo
    Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.
  • Thumbnail Image
    Publication
    Advances in machine learning for tumour classification in cancer of unknown primary: A mini-review
    (2024) Oróstica, Karen; Mardones, Felipe; Bernal, Yanara; Molina, Samuel; Orchard, Marcos; Verdugo, Ricardo; Carvajal-Hausdorf, Daniel; Marcelain, Katherine; Contreras, Seba; Armisen, Ricardo
    Cancers of unknown primary (CUP) are a heterogeneous group of aggressive metastatic cancers where standardised diagnostic techniques fail to identify the organ where it originated, resulting in a poor prognosis and resistance to treatment. Recent advances in large-scale sequencing techniques have enabled the identification of mutational signatures specific to particular tumour subtypes, even from liquid biopsy samples such as blood. This breakthrough paves the way for the development of new cost-effective diagnostic strategies. This mini-review explores recent advancements in Machine Learning (ML) and its application to tumour classification methods for CUP patients, identifying its weaknesses and strengths when classifying the tumour type. In the era of multi-omics, integrating several sources of information (e.g., imaging, molecular biomarkers, and family history) requires important theoretical advancements: increasing the dimensionality of the problem can result in lowering the predictive accuracy and robustness when data is scarce. Here, we review and discuss different architectures and strategies for incorporating cutting-edge machine learning into CUP diagnosis, aiming to bridge the gap between theory and clinical practice.
  • Thumbnail Image
    Publication
    Beyond tobacco: genomic disparities in lung cancer between smokers and never-smokers
    (2024) Garrido, Javiera; Bernal, Yanara; González, Evelin; Blanco, Alejandro; Sepúlveda, Gonzalo; Freire, Matías; Oróstica, Karen; Rivas, Solange; Marcelain, Katherine; Owen, Gareth; Ibañez, Carolina; Corvalan, Alejandro; Garrido, Marcelo; Assar, Rodrigo; Lizana, Rodrigo; Cáceres, Javier; Ampuero, Diego; Ramos, Liliana; Pérez, Paola; Aren, Osvaldo; Chernilo, Sara; Fernández, Cristina; Spencer, María; Flores, Jacqueline; Bernal, Giuliano; Ahumada, Mónica; Rasse, Germán; Sánchez, Carolina; De Amorim, Maria; Bartelli, Thais; Noronha, Diana; Dias, Emmanuel; Freitas, Helano; Armisén, Ricardo
    Background: Tobacco use is one of the main risk factors for Lung Cancer (LC) development. However, about 10-20% of those diagnosed with the disease are never-smokers. For Non-Small Cell Lung Cancer (NSCLC) there are clear differences in both the clinical presentation and the tumor genomic profiles between smokers and never-smokers. For example, the Lung Adenocarcinoma (LUAD) histological subtype in never-smokers is predominately found in young women of European, North American, and Asian descent. While the clinical presentation and tumor genomic profiles of smokers have been widely examined, never-smokers are usually underrepresented, especially those of a Latin American (LA) background. In this work, we characterize, for the first time, the difference in the genomic profiles between smokers and never-smokers LC patients from Chile. Methods: We conduct a comparison by smoking status in the frequencies of genomic alterations (GAs) including somatic mutations and structural variants (fusions) in a total of 10 clinically relevant genes, including the eight most common actionable genes for LC (EGFR, KRAS, ALK, MET, BRAF, RET, ERBB2, and ROS1) and two established driver genes for malignancies other than LC (PIK3CA and MAP2K1). Study participants were grouped as either smokers (current and former, n = 473) or never-smokers (n = 200) according to self-report tobacco use at enrollment. Results: Our findings indicate a higher overall GA frequency for never-smokers compared to smokers (58 vs. 45.7, p-value < 0.01) with the genes EGFR, KRAS, and PIK3CA displaying the highest prevalence while ERBB2, RET, and ROS1 the lowest. Never-smokers present higher frequencies in seven out of the 10 genes; however, smokers harbor a more complex genomic profile. The clearest differences between groups are seen for EGFR (15.6 vs. 21.5, p-value: < 0.01), PIK3CA (6.8 vs 9.5) and ALK (3.2 vs 7.5) in favor of never-smokers, and KRAS (16.3 vs. 11.5) and MAP2K1 (6.6 vs. 3.5) in favor of smokers. Alterations in these genes are comprised almost exclusively by somatic mutations in EGFR and mainly by fusions in ALK, and only by mutations in PIK3CA, KRAS and MAP2K1. Conclusions: We found clear differences in the genomic landscape by smoking status in LUAD patients from Chile, with potential implications for clinical management in these limited-resource settings.
  • Thumbnail Image
    Publication
    Chronic Stress and Ovulatory Dysfunction: Implications in Times of COVID-19
    (2022) Vigil, Pilar; Meléndez, Jaime; Soto, Hugo; Petkovic, Grace; Bernal, Yanara; Molina, Santiago
    Stress is known to be associated with adverse health outcomes. The COVID-19 pandemic and its associated lockdowns are examples of chronic stressors. Lockdown measures inadvertently caused significant psychological distress and became a powerful source of anxiety/stress, sleep disturbances, nutritional changes and weight gain. Stress is known to impact women's health specifically, through hypothalamic-pituitary-gonadal (HPG) axis dysfunction and resultant ovulatory dysfunction. Such dysfunction may manifest in menstrual irregularities and/or infertility due to hypothalamic hypogonadism. Here, we review the key physiological mediators of stress and associated ovulatory dysfunction. The kisspeptinergic system is comprised of sets of neurons located in the hypothalamus, the rostral periventricular region of the third ventricle (RP3V) and the arcuate nucleus (ARC). This system links nutrition, reproductive signals and stress. It plays a key role in the function of the HPG axis. During chronic stress, the kisspeptinergic system affects the HPG axis, GnRH pulsatility, and, therefore, ovulation. Leptin, insulin and corticotrophin-releasing hormone (CRH) are thought to be additional key modulators in the behavioral responses to chronic stress and may contribute to stress-related ovulatory dysfunction. This mini-review also summarizes and appraises the available evidence on the negative impact of chronic stress as a result of the COVID-19 pandemic lockdowns. It proposes physiological mechanisms to explain the observed effects on women's reproductive health and well-being. The review suggests areas for future research.
  • Thumbnail Image
    Publication
    Determinants of COVID-19 and non-COVID-19 vaccine confidence in low- and middle-income countries: A systematic review of qualitative evidence and thematic synthesis
    (2025) Blukacz, Alice; Obach, Alexandra; Vásquez, Paola; Campaña, Carla; Huerta, Catalina; Bernal, Yanara; Cabieses, Báltica
    Background: The COVID-19 pandemic has shown the immediate risk for global and public health posed by vaccination inequities worldwide. The regions most affected are low- and middle-income countries (LMICs). In addition to systemic challenges, vaccine hesitancy driven by low vaccine confidence has been identified as a threat to vaccine uptake. The aim of this systematic review of qualitative literature is to explore the determinants of COVID-19 and non-COVID-19 vaccine confidence in LMICs. Methods: A systematic review was conducted following the PRISMA and ENTREQ guidelines. The electronic databases Cinahl, Embase, Pubmed, Scopus and Web of Science were searched for qualitative studies focusing on the topic of interest in LMICs published between 2013 and 2023. The quality of the studies was assessed using the Joanna Briggs Institute’s Checklist for Qualitative Research. A thematic synthesis was conducted. The study was registered on the Open Science Framework platform. Findings: 66 studies were included in the review. Three main determinants of vaccine confidence were identified: (1) General perceptions of the safety and efficacy of vaccines; (2) Information and experience; (3) Trust in healthcare providers, institutions, and systems. General perceptions of vaccine safety and efficacy were similar between COVID-19 and non-COVID-19 vaccines, and doubts regarding vaccine safety were neither new nor exclusive to the COVID-19 vaccine, indicating a persisting challenge. Furthermore, low vaccine confidence was partly determined by broader dynamics of mistrust towards Western countries and institutions, which was reflected for both vaccine groups. While conspiracy theories have been persisting determinants of low confidence, low COVID-19 vaccine confidence was partly determined by what was perceived as a lack of specific information. Conclusion: Persistent challenges to vaccine confidence were identified, rooted in colonial legacies and global health inequities, as well as limited intercultural approaches to building trust with regards to vaccines.
  • Thumbnail Image
    Publication

Implementado por OpenGeek Services