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Rodrígo Mora

Hospital for Tropical Diseases

ORCID: 0000-0001-7964-3575

Publishes on Adenosine and Purinergic Signaling, RNA modifications and cancer, COVID-19 Clinical Research Studies. 125 papers and 2.3k citations.

125Publications
2.3kTotal Citations

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Persistence of SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC) up to 15 Months Post-Infection
Bruce K. Patterson, Edgar B. Francisco, Ram Yogendra et al.|Frontiers in Immunology|2022
Cited by 286Open Access

The recent COVID-19 pandemic is a treatment challenge in the acute infection stage but the recognition of chronic COVID-19 symptoms termed post-acute sequelae SARS-CoV-2 infection (PASC) may affect up to 30% of all infected individuals. The underlying mechanism and source of this distinct immunologic condition three months or more after initial infection remains elusive. Here, we investigated the presence of SARS-CoV-2 S1 protein in 46 individuals. We analyzed T-cell, B-cell, and monocytic subsets in both severe COVID-19 patients and in patients with post-acute sequelae of COVID-19 (PASC). The levels of both intermediate (CD14+, CD16+) and non-classical monocyte (CD14Lo, CD16+) were significantly elevated in PASC patients up to 15 months post-acute infection compared to healthy controls (P=0.002 and P=0.01, respectively). A statistically significant number of non-classical monocytes contained SARS-CoV-2 S1 protein in both severe (P=0.004) and PASC patients (P=0.02) out to 15 months post-infection. Non-classical monocytes were sorted from PASC patients using flow cytometric sorting and the SARS-CoV-2 S1 protein was confirmed by mass spectrometry. Cells from 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients contained ddPCR+ peripheral blood mononuclear cells, however, only fragmented SARS-CoV-2 RNA was found in PASC patients. No full length sequences were identified, and no sequences that could account for the observed S1 protein were identified in any patient. That non-classical monocytes may be a source of inflammation in PASC warrants further study.

Artesunate Activates Mitochondrial Apoptosis in Breast Cancer Cells via Iron-catalyzed Lysosomal Reactive Oxygen Species Production
Anne Hamacher‐Brady, Henning Stein, Simon Turschner et al.|Journal of Biological Chemistry|2010
Cited by 225Open Access

The antimalarial agent artesunate (ART) activates programmed cell death (PCD) in cancer cells in a manner dependent on the presence of iron and the generation of reactive oxygen species. In malaria parasites, ART cytotoxicity originates from interactions with heme-derived iron within the food vacuole. The analogous digestive compartment of mammalian cells, the lysosome, similarly contains high levels of redox-active iron and in response to specific stimuli can initiate mitochondrial apoptosis. We thus investigated the role of lysosomes in ART-induced PCD and determined that in MCF-7 breast cancer cells ART activates lysosome-dependent mitochondrial outer membrane permeabilization. ART impacted endolysosomal and autophagosomal compartments, inhibiting autophagosome turnover and causing perinuclear clustering of autophagosomes, early and late endosomes, and lysosomes. Lysosomal iron chelation blocked all measured parameters of ART-induced PCD, whereas lysosomal iron loading enhanced death, thus identifying lysosomal iron as the lethal source of reactive oxygen species upstream of mitochondrial outer membrane permeabilization. Moreover, lysosomal inhibitors chloroquine and bafilomycin A1 reduced ART-activated PCD, evidencing a requirement for lysosomal function during PCD signaling. ART killing did not involve activation of the BH3-only protein, Bid, yet ART enhanced TNF-mediated Bid cleavage. We additionally demonstrated the lysosomal PCD pathway in T47D and MDA-MB-231 breast cancer cells. Importantly, non-tumorigenic MCF-10A cells resisted ART-induced PCD. Together, our data suggest that ART triggers PCD via engagement of distinct, interconnected PCD pathways, with hierarchical signaling from lysosomes to mitochondria, suggesting a potential clinical use of ART for targeting lysosomes in cancer treatment.

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning
Bruce K. Patterson, José Guevara-Coto, Ram Yogendra et al.|Frontiers in Immunology|2021
Cited by 203Open Access

Expression of CCR5 and its cognate ligands have been implicated in COVID-19 pathogenesis, consequently therapeutics directed against CCR5 are being investigated. Here, we explored the role of CCR5 and its ligands across the immunologic spectrum of COVID-19. We used a bioinformatics approach to predict and model the immunologic phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 224 individuals including healthy controls and patients spanning the COVID-19 disease continuum. We assessed the plasma and isolated peripheral blood mononuclear cells (PBMCs) from 29 healthy controls, 26 Mild-Moderate COVID-19 individuals, 48 Severe COVID-19 individuals, and 121 individuals with post-acute sequelae of COVID-19 (PASC) symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients from each group. B-cells were significantly elevated compared to healthy control individuals (P<0.001) as was the CD14+, CD16+, CCR5+ monocytic subset (P<0.001). CD4 and CD8 positive T-cells expressing PD-1 as well as T-regulatory cells were significantly lower than healthy controls (P<0.001 and P=0.01 respectively). CCL5/RANTES, IL-2, IL-4, CCL3, IL-6, IL-10, IFN-γ, and VEGF were all significantly elevated compared to healthy controls (all P<0.001). Conversely GM-CSF and CCL4 were in significantly lower levels than healthy controls (P=0.01). Data were further analyzed and the classes were balanced using SMOTE. With a balanced working dataset, we constructed 3 random forest classifiers: a multi-class predictor, a Severe disease group binary classifier and a PASC binary classifier. Models were also analyzed for feature importance to identify relevant cytokines to generate a disease score. Multi-class models generated a score specific for the PASC patients and defined as S1 = (IFN-γ + IL-2)/CCL4-MIP-1β. Second, a score for the Severe COVID-19 patients was defined as S2 = (IL-6+sCD40L/1000 + VEGF/10 + 10*IL-10)/(IL-2 + IL-8). Severe COVID-19 patients are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While PASC patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells.

miRNA-130a Targets <i>ATG2B</i> and <i>DICER1</i> to Inhibit Autophagy and Trigger Killing of Chronic Lymphocytic Leukemia Cells
Valentina Kovaleva, Rodrígo Mora, Yoon Jung Park et al.|Cancer Research|2012
Cited by 201

Toxicity and relapses from the immunochemotherapy used to treat chronic lymphocytic leukemia (CLL) prompt continued interest in gentle but effective targeted treatment options for the mainly elderly population suffering from this disease. Here, we report the definition of critical CLL cell survival pathways that can be targeted by ectopic reexpression of the miRNA genes miR-130a and miR-143 which are widely downregulated in CLL. Notably, miR-130a inhibited autophagy by reducing autophagosome formation, an effect mediated by downregulation of the genes ATG2B and DICER1, the latter of which is a major component of the miRNA silencing machinery. In support of the concept of a fundamental connection between miRNA disregulation and altered autophagic flux in this cancer, we showed that RNA interference-mediated knockdown of DICER1 expression was sufficient to reduce autophagy in primary or established cultures of CLL cells. Together, our findings show that miR-130a modulates cell survival programs by regulating autophagic flux, and they define roles for miR-130a and Dicer1 in a regulatory feedback loop that mediates CLL cell survival.

Where good ideas come from: The natural history of innovation
Rodrígo Mora|Repositorio Institucional UN - Biblioteca Digital|2011
Cited by 132Open Access

El autor cede los derechos de publicación a la Escuela de Administración de Empresas y Contaduría Pública de la Facultad de Ciencias Económicas de la Universidad Nacional de Colombia. El artículo no puede aparecer en ningún medio masivo de comunicación sin la autorización expresa de la Escuela de Administración de Empresas y Contaduría Pública. NOTA: El envío de los artículos no obliga al comité editorial de INNOVAR a realizar su publicación. Revista INNOVAR, Facultad de Ciencias Económicas, edificio 238, aula 06, Ciudad Universitaria. Correo electrónico: revinnova_bog@unal.edu.co