Biology subjects

Medina-Acosta, E.

Publications and source records attributed to Medina-Acosta, E..

8 recordsLinked to original sources

bioRxiv2026

RCDome: A Multi-Database Human Gene Atlas of Regulated Cell Death

Introduction: Regulated cell death (RCD) governs tissue homeostasis, development, and disease, and is executed or regulated by specific genes. Yet for the researcher asking which genes execute or regulate a given RCD form, the answer is rarely simple: gene lists for the same form rarely agree across databases, many associations carry no traceable source, and most have never been systematically checked against primary literature. We built RCDome to answer the most basic question a researcher can ask: where did this gene-RCD association come from, and what is the evidence? Methods: RCDome is a multi-database human gene atlas built through a staged architecture integrating multi-source compilation, literature validation and evidence recovery, mechanistic classification, human-governed ontological adjudication, and web deployment. Five complementary evidence channels (PubMed Boolean search, curated databases, AI-assisted screening, manual curation, and Elicit systematic review) were integrated from 20 public databases into a unified matrix. Sixty-two original name strings were canonicalized into 53 RCD-related entities with curator-adjudicated operational definitions and ontological levels. Gene-RCD associations were systematically evaluated through an independent DeepSeek two-call LLM validation, Europe PMC full-text recovery and deep evidence extraction, an independent Consensus literature-search channel, and GPT-4o arbitration of disagreements. Source-grounding controls rejected extracted evidence not found verbatim in the source document, while the governance contract was enforced as executable code. Results: The compendium holds 22,473 association rows spanning 9,265 unique HGNC-validated genes (21,568 unique gene-RCD pairs). Evidence-first adjudication resolved 5,138 pairs (23.8%) as mechanistically involved; across the 4,775 role-resolved pairs, 225 (4.7%) are executors, 4,455 (93.3%) are regulators, and 95 are markers, revealing a small death-executing core embedded in a vast regulatory network. Under a separate seven-class mechanistic criterion applied to all 22,473 rows, only 3,063 (13.6%) were mechanistically confirmed and 286 (1.3%) were database-only with no verifiable paper trail. Conclusion: RCDome makes the RCD evidence landscape measurable and traceable, showing that AI-assisted curation can be verifiable, human-governed, and explicit about uncertainty. It is delivered as a Shiny web application that lets any researcher query the atlas and inspect the evidence behind each association. Availability: RCDome is freely available at https://rcdome.org/ (source code and data at https://github.com/BioCancerInformatics/RCDome).

cell biology↗

bioRxiv2026

A Pan-Cancer Multi-Omic SuperLearner for Regulated Cell Death Survival Topologies

IntroductionRegulated cell death (RCD) pathways profoundly influence tumor progression and immune modulation. In prior work, we constructed a comprehensive database mapping 25 forms of RCD across seven multi-omic layers encompassing 33 tumor types (CancerRCDShiny). Despite their robust ability to identify risk populations, translating these prognostic signatures into personalized clinical workflows requires a shift from generalized cohort stratification to individualized risk mapping. This necessitates mapping the complex geometric landscape of patient risk--Survival Topologies--to accurately capture the non-linear dynamics of RCD signatures. MethodsWe engineered a Pan-Cancer Multi-Omic SuperLearner pipeline evaluating 33 cancer types. Phase I performed zero-leakage data harmonization and groupwise imputation to prevent cross-cohort amalgamation. Phase II utilized Elastic Net-regularized Cox (CoxNet) regression as an audit-compliant CANARY diagnostic to map mathematical proportional-hazards failures. Admissible strata enforcing a rigid 35% topological missingness barrier entered Phase III, deploying an advanced non-linear Quadripartite Base-Learner Ensemble (Random Survival Forests (RSF), Extreme Gradient Boosting (XGBoost), insulated Survival-Boruta, and Multi-Task Logistic Regression (MTLR))--fused within an Elastic Net Multi-View Meta-Learner (MVL)--with local interpretability guaranteed via post-hoc SHAPley Additive exPlanations (TreeSHAP) and Local Interpretable Model-agnostic Explanations (LIME). ResultsThe CANARY diagnostic empirically proved the structural invalidity of pan-cancer geometric proportional-hazards. Advancing 96 verified matrices into the Quadripartite Machine Learning Ensemble, Phase III executed a structural algorithmic displacement: dense continuous multi-omic topologies computationally suppressed static genomic mutations and Copy Number Variations (CNVs) during multidimensional competition (85.7% vs 0.0% apex retention). Furthermore, the MVL stabilized global predictions against extreme biological variance, while surrogate LIME validations (R{superscript 2} < 0.10) confirmed the absolute failure of linear interpretative proxies. Extracting N-dimensional TreeSHAP interactions natively bypassed generalized risk parameters, mapping exact Survival Topologies. This dynamically exposed multi-omic synergistic (lethal peaks) and antagonistic (protective valleys) rescue trajectories invisible to additive models. We integrated this architecture into CancerRCDPredictor, a Shiny application operating as a digital tumor board. ConclusionDeploying a Pan-Cancer Multi-Omic SuperLearner to bypass linear topological failures, this study advances beyond generalized cohort stratifications, establishing a deterministically mapped architecture for predicting RCD-related Survival Topologies. Through the CancerRCDPredictor interface, we directly translate multi-omic insights into individualized precision oncology interception.

bioinformatics↗

bioRxiv2026

Geometric Multidimensional Representation of Omic Signatures

Multi-omic signatures are widely used in biomarker discovery, precision oncology, and systems biology, yet they are typically treated as vectors or composite scores that collapse intrinsically multidimensional biological organization into one-dimensional summaries. As a result, their internal structure, contextual dependencies, and mechanistic coherence remain largely inaccessible. Here, we introduce a geometric framework that reconceptualizes omic signatures as multidimensional informational entities whose biological meaning arises from structural organization rather than molecular membership alone. Each signature is embedded in a shared latent space integrating regulatory, phenotypic, microenvironmental, immune, and clinical constraints, and represented as a convex polytope. This representation preserves internal organization and enables intrinsic geometric measurements--including barycenter distance, volume, anisotropy, and asymmetry--that quantify concordance, divergence, and latent complexity. We apply this framework to 24,796 metabolic regulatory circuitries reconstructed across 32 TCGA cancer types, encoded as paired regulatory and metabolic signatures in an 18-dimensional latent space. Geometric analysis shows that discordance predominates: most circuitries occupy strong or extreme discordance regimes and display high-dimensional, frequently asymmetric geometries, whereas fully concordant circuitries are rare and structurally constrained. These geometric phenotypes stratify metabolic pathways and superfamilies in reproducible, non-uniform patterns that are not detectable with vector- or network-based representations. By transforming omic signatures into measurable geometric objects, this framework enables principled comparison, de-redundancy, and mechanistic interpretation of multi-omic biomarkers, providing a scalable approach for analyzing complex regulatory systems across cancer and beyond. All geometric representations and derived descriptors are available through the SigPolytope Shiny application (https://sigpolytope.shinyapps.io/geometricatlas/).

bioinformatics↗

bioRxiv2025

A Multi-Omic Atlas of Convergent and Divergent Metabolic Regulatory Circuitries in Cancer

Metabolic reprogramming underlies tumor progression, immune evasion, and resistance to regulated cell death, yet the higher-order regulatory logic that coordinates these processes across molecular layers remains poorly defined. We developed OncoMetabolismGPS, a multi-omic analytical framework that reconstructs a Pan-Cancer atlas of convergent and divergent metabolic regulatory circuitries. From 463,433 significant multi-omic and phenotypic associations across 33 tumor types, we derived 241,415 omic-specific metabolic signatures, each integrating metabolic pathway context with phenotypic, prognostic, and immune features. By mapping shared upstream regulators of these signatures, we identified 24,796 metabolic regulatory circuitries--classified as convergent when regulators and signatures act in the same biological direction, or divergent when they exhibit opposing associations. Divergent circuitry predominated, especially in immunosuppressive (cold) tumor contexts, revealing context-dependent regulatory compensation across metabolic, phenotypic, and clinical axes. The accompanying OncoMetabolismGPS Shiny application implements this atlas as an interactive platform that positions each signature and circuitry within a multidimensional coordinate space defined by molecular, phenotypic, immune, and clinical attributes, enabling systematic navigation of metabolic regulatory behavior in cancer. Together, this study establishes the first multi-omic atlas of metabolic regulatory circuitries, providing a conceptual and computational framework for dissecting metabolic plasticity, pathway dependencies, and therapeutic vulnerabilities across human cancers.

bioinformatics↗

bioRxiv2022

A Sexual Bias in mitochondrial protein-coding gene expression across different tissues and the prognostic value in multiple cancers

Mitochondria in mammalian cells provide ATP through oxidative phosphorylation. The overproduction of reactive oxygen species (ROS) in mitochondrial cells promotes cancer by modifying gene expression or function. Mating introduces competing mitochondrial (mtDNA) and nuclear DNA (nDNA) gene products, leading to biological differences between males and females for diseases and disorders such as cancer. There is a significant sex bias in aging-related conditions. We aimed to investigate whether sex and age affect mitochondrial protein-coding gene expression in cancer and, if so, to determine the prognosis value in survival outcomes, stemness, and immune cell infiltrates. We compared normal versus primary tumor transcriptomes (bulk RNA-Seq) from The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) projects to test these hypotheses. Correlations between gene expression, survival, protective or risk factor, stemness, and immune cell infiltrate were performed in RStudio using UCSC Xena Shiny. Eleven mitochondrial protein-coding genes were altered in brain cancer (MT-ND2, MT-ND1, MT-ATP8, MT-ATP6, MT-CO2, MT-CYB, MT-CO3, MT-ND4L, MT-ND4, MT-ND3, MT-CO1). MT-ND5 and MT-ND6 are disproportionately expressed in female brain tissues. Mitochondrial global polymorphic expression sites of variation were more significant in the 50-59 and 60-79-year-old age groups than in the 20-49-year-old age groups. Pan-cancer survival analysis revealed a 4-component gene signature (MT-CO1, MT-CO2, MT-ND5, and MT-ND6) downregulated in low-grade glioma (LGG). This gene signature increased LGG overall survival, disease-specific survival, and progression-free interval without sex-specific association. However, the correlation with disease-free interval survival was female-specific. The 4-component gene signature was protective in LGG but risky in thymoma cancer and uterine corpus endometrial carcinoma. In LGG, the 4-component gene signature positively correlated with immune monocyte, NK, and B cell infiltrates and negatively correlated with T cell CD4+ Th2, macrophage M1 and M2, myeloid dendritic cell, and neutrophil. We identified a 13-component mitochondrial protein-coding gene signature associated with stemness in kidney chromophobe. A sex-biased effect was observed in mitochondrial protein-coding for brain tissues, with a female bias. However, an aging effect with higher polymorphic site expression was observed in male tissues. We conclude that the differentially expressed mitochondrial protein-coding genes provide new insights into carcinogenesis, helping to identify new prognostic markers. The overexpression of the 4-component gene signature is associated with a better prognosis in LGG, with positive and negative correlations with immune cell infiltrates.

genomics↗

bioRxiv2022

Differential haplotype expression in class I MHC genes during SARS-CoV-2 infection of human lung cell lines

Cell entry of SARS-CoV-2 causes genome-wide disruption of the transcriptional profiles of genes and biological pathways involved in the pathogenesis of COVID-19. Expression allelic imbalance is characterized by a deviation from the Mendelian expected 1:1 expression ratio and is an important source of allele-specific heterogeneity. Expression allelic imbalance can be measured by allele-specific expression analysis (ASE) across heterozygous informative expressed single nucleotide variants (eSNVs). ASE reflects many regulatory biological phenomena that can be assessed by combining genome and transcriptome information. ASE contributes to the interindividual variability associated with disease. We aim to estimate the transcriptome-wide impact of SARS-CoV-2 infection by analyzing eSNVs. We compared ASE profiles in the human lung cell lines Calu-3, A459, and H522 before and after infection with SARS-CoV-2 using RNA-Seq experiments. We identified 34 differential ASE (DASE) sites in 13 genes (HLA-A, HLA-B, HLA-C, BRD2, EHD2, GFM2, GSPT1, HAVCR1, MAT2A, NQO2, SUPT6H, TNFRSF11A, UMPS), all of which are enriched in protein binding functions and play a role in COVID-19. Most DASE sites were assigned to the MHC class I locus and were predominantly upregulated upon infection. DASE sites in the MHC class I locus also occur in iPSC-derived airway epithelium basal cells infected with SARS-CoV-2. Using an RNA-Seq haplotype reconstruction approach, we found DASE sites and adjacent eSNVs in phase (i.e., predicted on the same DNA strand), demonstrating differential haplotype expression upon infection. We found a bias towards the expression of the HLA alleles with a higher binding affinity to SARS-CoV-2 epitopes. Independent of gene expression compensation, SARS-CoV-2 infection of human lung cell lines induces transcriptional allelic switching at the MHC loci. This suggests a response mechanism to SARS-CoV-2 infection that swaps HLA alleles with poor epitope binding affinity, an expectation supported by publicly available proteome data.

genomics↗

bioRxiv2019

An Exclusively Skewed Distribution of Pediatric Immune Reconstitution Inflammatory Syndrome Towards the Female Sex is Associated with Advanced Acquired Immune Deficiency Syndrome

In human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) patients with very low CD4 cell counts, there is a temporal relationship between administration of antiretroviral therapy (ART) and an increased inflammatory response state known as the immune reconstitution inflammatory syndrome (IRIS). The predominant clinical presentation of IRIS is an infectious disease that can be life-threatening. IRIS-related infectious events are distributed similarly between adult males and females, albeit a few studies have shown a skewing towards the male sex in pediatric IRIS. Here, we assessed sex-specific differences in the causes and extent of IRIS infectious events in HIV-infected pediatric patients on ART. We carried out a prospective clinical analysis (from 2000 to 2018) of IRIS-related infectious events after ART in a cohort of 82 Brazilian children and adolescents infected with HIV-1 through mother-to-child transmission as well as a comprehensive cross-referencing with public records on IRIS-related infectious causes in pediatric HIV/AIDS. Twelve events fulfilling the criteria of IRIS occurred exclusively in eleven females in our cohort. The median age at IRIS events was 3.6 years. The infectious causes included Mycobacterium bovis, varicella-zoster virus, molluscum contagiosum virus, human papillomavirus, cytomegalovirus, and Mycobacterium tuberculosis. In one female, there was regional bacillus Calmette-Guerin dissemination and cytomegalovirus esophagitis. There was complete health recovery after ten IRIS events without the use of corticosteroids or ART interruption. One case of IRIS-associated miliary tuberculosis was fatal. The biological female sex was a significant risk factor for IRIS events (odds ratio: 23.67; 95% confidence interval 95%: 1.341 - 417.7; P = 0.0016). We observed an effect of the advanced HIV/AIDS variable in IRIS females as compared with non-IRIS females (mean CD4+ T cell percentage 13.36% versus 18.63%; P = 0.0489), underpinning the exclusively skewed distribution towards the female sex of this cohort. Moreover, the IRIS females in our cohort had higher mean CD4+ T cell percentages before (13.36%) and after IRIS (26.56%) than those of the IRIS females (before IRIS, 4.978%; after IRIS, 13.81%) in previous studies conducted worldwide. We concluded that the exclusively skewed distribution of pediatric IRIS towards females is associated with more advanced AIDS.

epidemiology↗

bioRxiv2019

A Differentially Methylated CpG Site in the IL4 Gene Associated with Anti-FVIII Inhibitor Antibody Development in Hemophilia A

Hemophilia A is the most common clotting disorder in humans. It affects one in five thousand live-born children. Mutations in the X-chromosome linked F8 gene lead to the deficiency of circulating factor VIII (FVIII). The defect is characterized by severe bleeding. The standard therapy is to replace the deficient factor intravenously. The main adverse event of the therapy is the development of anti-FVIII inhibitor antibodies that impair coagulation and result in increased complications and risk of death. Several risk factors have been described for the development of inhibitor antibodies, among them age, type of FVIII administered, ethnicity, and variant alleles in immune response genes. Epigenetic risks factors have not yet been explored. This work aimed to evaluate the methylation statuses at thirteen CpG sites (5meCpG) in regulatory regions of the IL1B, IL2, IL4, IL6, IL10, TNF, IFNG, CTLA4, CD28, and CST7 immune regulation genes in hemophilia A affected males on replacement therapy who develop or do not develop inhibitor antibodies. At each of the thirteen specific CpG sites, we observed one of three possible statuses: hypermethylated, hypomethylated or intermediate methylated. We found a statistically significant (p = 0.04) decrease in the methylation level at one CpG site in the IL4 intron 1 (CpG-3) in the affected group of patients presenting with anti-FVIII inhibitors as compared with the group of patients without inhibitors. The differential 5meCpG-3 maps within a predicted enhancer region in IL4 intron 1 that overlaps DNase I hypersensitive chromatin region of the Th2 IL5, IL13, and IL4 cytokine gene cluster and, therefore, permissive for gene expression. Six-bp upstream of the differentially 5meCpG-3 is the rs2227282 cis expression quantitative trait locus that influences the transcript levels of the PDLIM4, SLC22A4, SLC22A5, RAD50, IL4, KIF3A, SEPT8 genes. We consider the IL4 (CpG-3) site a promising lead epigenetic mark, the potential value of which must be appraised in a larger group of patients. The methodology employed also allowed to evaluate the distribution of the IL6 rs35081782 insertion/deletion variant, associated with white blood cell count traits in genome-wide association studies, and which showed no difference in distribution between the groups of patients.

genetics↗