Biology subjects

Coto-Llerena, M.

Publications and source records attributed to Coto-Llerena, M..

7 recordsLinked to original sources

bioRxiv2026

Organoid-based colorectal tumor microenvironment model for immuno-oncology research

The development of cancer immunotherapies is hindered by the lack of human-relevant models that accurately translate to patient outcomes. We combine patient-derived colorectal tumor organoids (PDOs) and cancer-associated fibroblasts (CAFs) into floating extracellular matrix drops to form miniature colorectal tumors. These SHaking Organoid CO-cultures (SHOCOs) reproducibly capture key features of the tumor microenvironment (TME), including physiologically relevant ECM, hypoxic regions, and a diversified stromal compartment that captures primary CAF states. Compared with traditional PDO-based co-culture models, SHOCOs maintain immune cells in numbers, states and functional interactions that more closely reflect the physiological tumor microenvironment. The modularity of the system allowed controlled simulation of diverse patient tumor archetypes, and defining how TME components shape therapy response. Immune-rich SHOCOs treated with T-cell bispecific antibodies exhibited robust anti-tumor responses that were stronger and more rapid than their PDO-based counterparts. Stroma-rich tumors, on the other hand, diminished therapy responses by physically hindering both immune cell recruitment and limiting antibody penetration. Thus, SHOCOs enable the construction of modular tumor microenvironments, providing a versatile platform to dissect immune and stromal tumor biology and to catalyze the discovery of novel therapeutic approaches.

cancer biology↗

bioRxiv2026

Ribosome profiling reveals extensive translational alterations in steatohepatitis-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one the most lethal cancer types. While infections with hepatitis B or hepatitis C viruses remain the primary risk factors for HCC development worldwide, metabolic disease-associated steatohepatitis has become the fastest growing etiology of HCC, particularly in the West. Our study characterizes, for the first time, the remodeling of the translation landscape in steatohepatitis-associated HCC using ribosome profiling and mass spectrometry techniques. In striking contrast with the transcriptional alterations, which do not show strong dependence on associated co-morbidity, translational alterations are broader in the steatohepatitis compared to the viral background. These alterations affect hundreds of genes, whose products are often involved in subcellular protein localization. By quantifying the relationship between the ribosome occupancy of upstream or downstream open reading frames (uORFs or dORFs) and coding regions (CDSs), we provide evidence of uORFs attenuating the translation efficiency of CDSs in HCC. We also identify numerous novel translated regions, including from RNAs currently annotated as non-coding, some yielding peptides that can be reproducibly identified in mass spectrometry datasets. Our study thus provides novel molecular data on HCC with a focus on the steatohepatitis etiology, reveals unexpectedly extensive translational control in this co-morbidity, and gives multiple hints and candidate targets for follow-up experiments.

systems biology↗

bioRxiv2023

Ribosomal protein RPL39L is an efficiency factor in the cotranslational folding ofproteins with alpha helical domains

Increasingly many studies reveal how ribosome composition can be tuned to optimally translate the transcriptome of individual cell types. In this study, we investigated the expression pattern, structure within the ribosome and effect on protein synthesis of the ribosomal protein paralog 39L (RPL39L). With a novel mass spectrometric approach we have quantified the expression of RPL39L in human pluripotent cells, cancer cell lines and tissue samples, and in mouse germ cells. We generated RPL39L knock-out mouse embryonic stem cell (mESC) lines and demonstrated that RPL39L impacts the dynamics of translation, to support the pluripotency and differentiation, spontaneous and along the germ cell lineage. Most differences in protein abundance between WT and RPL39L KO lines were explained by widespread proteasomal activity. By CryoEM analysis of purified RPL39 and RPL39L-containing ribosomes we found that, unlike RPL39, RPL39L has two distinct conformations in the exposed segment of the nascent peptide exit tunnel, creating a distinct hydrophobic patch that has been predicted to support the efficient co-translational folding of alpha helices. Our study shows that ribosomal protein paralogs provide switchable modular components that can tune translation to the protein production needs of individual cell types.

molecular biology↗

bioRxiv2022

Elevated arginine levels in liver tumors promote metabolic reprogramming and tumor growth

Arginine auxotropy, due to reduced expression of urea cycle genes, is common in cancer. However, little is known about the levels of arginine in these cancers. Here, we report that arginine levels are elevated in hepatocellular carcinoma (HCC) despite reduced expression of urea cycle enzymes. Liver tumors accumulate high levels specifically of arginine via increased uptake and, more importantly, via suppression of arginine-to-polyamine conversion due to reduced arginase 1 (ARG1) and agmatinase (AGMAT) expression. Furthermore, the high levels of arginine are required for tumor growth. Mechanistically, high levels of arginine promote tumorigenesis via transcriptional regulation of metabolic genes, including upregulation of asparagine synthetase (ASNS). ASNS-derived asparagine further enhances arginine uptake, creating a positive feedback loop to sustain high arginine levels and oncogenic metabolism. Thus, arginine is a novel second messenger-like molecule that reprograms metabolism to promote tumor growth.

cancer biology↗

bioRxiv2021

Proteogenomic characterization of hepatocellular carcinoma

We performed a proteogenomic analysis of hepatocellular carcinomas (HCCs) across clinical stages and etiologies. We identified pathways differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. These pathways are involved in the organization of cellular components, cell cycle control, signaling pathways, transcriptional and translational control and metabolism. Analyses of CNA-mRNA and mRNA-protein correlations identified candidate driver genes involved in epithelial-to-mesenchymal transition, the Wnt-{beta}-catenin pathway, transcriptional control, cholesterol biosynthesis and sphingolipid metabolism. The activity of targetable kinases aurora kinase A and CDKs was upregulated. We found that CTNNB1 mutations are associated with altered phosphorylation of proteins involved in actin filament organization, whereas TP53 mutations are associated with elevated CDK1/2/5 activity and altered phosphorylation of proteins involved in lipid and mRNA metabolism. Integrative clustering identified HCC subgroups with distinct regulation of biological processes, metabolic reprogramming and kinase activation. Our analysis provides insights into the molecular processes underlying HCCs.

genomics↗

bioRxiv2019

APSiC: Analysis of Perturbation Screens for the Identification of Novel Cancer Genes

BackgroundSystematic perturbation screens provide comprehensive resources for the elucidation of cancer driver genes, including rarely mutated genes that are missed by approaches focused on frequently mutated genes and driver genes for which the basis for oncogenicity is non-genetic. The perturbation of many genes in relatively few cell lines in such functional screens necessitates the development of specialized computational tools with sufficient statistical power. ResultsHere we developed APSiC (Analysis of Perturbation Screens for identifying novel Cancer genes) that can identify genetic and non-genetic drivers even with a limited number of samples. Applying APSiC to the large-scale deep shRNA screen Project DRIVE, APSiC identified well-known, pan-cancer genetic drivers, novel putative genetic drivers known to be dysregulated in specific cancer types and the context dependency of mRNA-splicing between cancer types. Additionally, APSiC discovered a median of 28 and 35 putative non-genetic oncogenes and tumor suppressor genes, respectively, for individual cancer types, including genes involved in genome stability maintenance and cell cycle. We functionally demonstrated that LRRC4B, a putative non-genetic tumor suppressor gene that has not previously been associated with carcinogenesis, suppresses proliferation by delaying cell cycle and modulates apoptosis in breast cancer. ConclusionWe demonstrate APSiC is a robust statistical framework for discovery of novel cancer genes through analysis of large-scale perturbation screens. The analysis of DRIVE using APSiC is provided as a web portal and represents a valuable resource for the discovery of novel cancer genes.

genomics↗

bioRxiv2019

Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens

Despite the progress in precision oncology, development of cancer therapies is limited by the dearth of suitable drug targets1. Novel candidate drug targets can be identified based on the concept of synthetic lethality (SL), which refers to pairs of genes for which an aberration in either gene alone is non-lethal, but co-occurrence of the aberrations is lethal to the cell. We developed SLIdR (Synthetic Lethal Identification in R), a statistical framework for identifying SL pairs from large-scale perturbation screens. SLIdR successfully predicts SL pairs even with small sample sizes while minimizing the number of false positive targets. We applied SLIdR to Project DRIVE data2 and found both established and novel pan-cancer and cancer type-specific SL pairs. We identified and experimentally validated a novel SL interaction between AXIN1 and URI1 in hepatocellular carcinoma, thus corroborating the potential of SLIdR to identify new SL-based drug targets.

bioinformatics↗