Biology subjects

Lehtio, J.

Publications and source records attributed to Lehtio, J..

7 recordsLinked to original sources

bioRxiv2025

Recognition of Ovarian Tumor-Derived Non-canonical Peptide Induces Memory-Like Features in Natural Killer Cells

Immune cell-based immunotherapy has emerged as a promising strategy for both hematologic malignancies and solid tumors. The adaptive properties of T and B cells, namely, antigen specificity and long-term immune memory, form the foundation of approaches such as chimeric antigen receptor (CAR) T-cell therapy and tumor vaccines. In contrast, natural killer (NK) cells, traditionally classified as innate lymphocytes, have been appreciated primarily for their immediate cytotoxicity against tumor cells, but not for long-term memory-like responses. Recent evidence has revealed a subset of NK cells defined as adaptive NK cells (aNK) capable of developing adaptive features, particularly in response to cytomegalovirus (CMV) primarily, and more recently, to ovarian tumor-derived antigens. However, whether tumor-derived peptides can specifically induce NK cell memory, and the corresponding interaction patterns, remains largely unexplored. In this study, we employed a proteogenomic approach combining RNA sequencing (RNA-seq) with HLA-E immunoprecipitation to identify both canonical and non-canonical peptides presented by primary ovarian tumor cells. Among four tumor-derived neo-antigenic peptides, the 9-mer peptide APAPAPAPL demonstrated the strongest binding affinity to HLA-E and engagement with the NK receptors NKG2C/A. Functional in vitro assays confirmed that this peptide could induce memory-like NK cell responses, including antigen-specific recall activity and enhanced tumor cytotoxicity. Furthermore, structural modeling using AutoDock Vina and Rosetta Dock illustrated that peptides with similar binding capacity shared conserved interaction patterns and docking orientations. Together, this systemic study highlights a novel mechanism for inducing NK cell memory through tumor-derived neoantigens. It also paves the way for the development of NK cell-targeted cancer vaccines, representing a new direction in tumor immunotherapy beyond conventional T cell-centered strategies.

immunology↗

bioRxiv2025

Mitochondrial Dysfunction Induces Hepatic Lipid Accumulation and Inflammatory Responses in mtDNA Mutator Mice

BackgroundNon-Alcoholic Fatty Liver Disease (NAFLD), now referred to as Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), is a widespread and complex health issue characterized by the accumulation of lipids in liver cells, not linked to alcohol consumption or other known liver problems. Despite its strong association with insulin resistance and obesity, a notable proportion of lean individuals develop NAFLD, suggesting the involvement of additional factors. Mitochondrial dysfunction has emerged as a potential contributor, given its role in lipid homeostasis and the generation of reactive oxidative species (ROS). MethodsIn this study, we took advantage of the mtDNA mutator mouse model, characterized by oxidative phosphorylation deficiency due to accelerated accumulation of mitochondrial DNA (mtDNA) mutations, to investigate how mitochondrial dysfunction affects liver homeostasis triggering fat accumulation. ResultsWe found that mitochondrial dysfunction induces liver steatosis and inflammation in this mouse model at a young age, independent of obesity. Using quantitative mass spectrometry, we reveal that mitochondrial dysfunction alters the levels of multiple proteins involved in lipid metabolism, cholesterol homeostasis, and inflammation. In vitro data show a shift in cellular metabolism toward the glycolytic pathway and confirm the upregulation of inflammatory genes. These changes are associated with oxidative stress and occur independently of mtDNA molecule release into the cytoplasm. ConclusionOur findings demonstrate that liver steatosis might develop as result of mitochondrial dysfunction without obesity and insulin resistance, underscoring the importance of mitochondrial dysfunction in NAFLD development in lean individuals and providing valuable insights into the molecular mechanisms underlying this complex metabolic disorder. This mouse model offers a unique platform for further investigations aimed at unraveling the intricacies of NAFLD pathogenesis and potential therapeutic targets beyond conventional risk factors.

cell biology↗

bioRxiv2021

A novel immunopeptidomic-based pipeline for the generation of personalized oncolytic cancer vaccines

Beside the isolation and identification of MHC-I restricted peptides from the surface of cancer cells, one of the challenges is eliciting an effective anti-tumor CD8+ T cell mediated response as part of therapeutic cancer vaccine. Therefore, the establishment of a solid pipeline for the downstream selection of clinically relevant peptides and the subsequent creation of therapeutic cancer vaccines are of utmost importance. Indeed, the use of peptides for eliciting specific anti-tumor adaptive immunity is hindered by two main limitations: the efficient selection of the most optimal candidate peptides and the use of a highly immunogenic platform to combine with the peptides to induce effective tumor-specific adaptive immune responses. Here, we describe for the first time a streamlined pipeline for the generation of personalized cancer vaccines starting from the isolation and selection of the most immunogenic peptide candidates expressed on the tumor cells and ending in the generation of efficient therapeutic oncolytic cancer vaccines. This immunopeptidomics-based pipeline was carefully validated in a murine colon tumor model CT26. Specifically, we used state-of-the-art immunoprecipitation and mass spectrometric methodologies to isolate >8000 peptide targets from the CT26 tumor cell line. The selection of the target candidates was then based on two separate approaches: RNAseq analysis and the HEX software. The latter is a tool previously developed by Chiaro et al. (1), able to identify tumor antigens similar to pathogen antigens, in order to exploit molecular mimicry and tumor pathogen cross-reactive T-cells in cancer vaccine development. The generated list of candidates (twenty-six in total) was further tested in a functional characterization assay using interferon-{gamma} ELISpot (Enzyme-Linked Immunospot), reducing the number of candidates to six. These peptides were then tested in our previously described oncolytic cancer vaccine platform PeptiCRAd, a vaccine platform that combines an immunogenic oncolytic adenovirus (OAd) coated with tumor antigen peptides. In our work, PeptiCRAd was successfully used for the treatment of mice bearing CT26, controlling the primary malignant lesion and most importantly a secondary, non-treated, cancer lesion. These results confirmed the feasibility of applying the described pipeline for the selection of peptide candidates and generation of therapeutic oncolytic cancer vaccine, filling a gap in the field of cancer immunotherapy, and paving the way to translate our pipeline into human therapeutic approach.

cancer biology↗

bioRxiv2021

Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides.

SummaryWe have implemented the pypgatk package and the pgdb workflow to create proteogenomics databases based on ENSEMBL resources. The tools allow the generation of protein sequences from novel protein-coding transcripts by performing a three-frame translation of pseudogenes, lncRNAs, and other non-canonical transcripts, such as those produced by alternative splicing events. It also includes exonic out-of-frame translation from otherwise canonical protein-coding mRNAs. Moreover, the tool enables the generation of variant protein sequences from multiple sources of genomic variants including COSMIC, cBioportal, gnomAD, and mutations detected from sequencing of patient samples. pypgatk and pgdb provide multiple functionalities for database handling, notably optimized target/decoy generation by the algorithm DecoyPyrat. Finally, we perform a reanalysis of four public datasets in PRIDE by generating cell-type specific databases for 65 cell lines using the pypgatk and pgdb workflow, revealing a wealth of non-canonical or cryptic peptides amounting to more than 10% of the total number of peptides identified (43,501 out of 402,512). AvailabilityThe software is freely available. pypgatk: (https://github.com/bigbio/py-pgatk/), and pgdb: (https://github.com/nf-core/pgdb) ContactYasset Perez-Riverol (yperez@ebi.ac.uk), Rui Branca (rui.mamede-branca@ki.se) Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2018

The Viral protein Corona Directs Viral Pathogenesis and Amyloid Aggregation

Artificial nanoparticles accumulate a protein corona layer in biological fluids, which significantly influences their bioactivity. As nanosized obligate intracellular parasites, viruses share many biophysical properties with artificial nanoparticles in extracellular environments and here we show that respiratory syncytial virus (RSV) and herpes simplex virus 1 (HSV-1) accumulate a rich and distinctive protein corona in different biological fluids. Moreover, we show that corona pre-coating differentially affects viral infectivity and immune cell activation. Additionally, we demonstrate that viruses bind amyloidogenic peptides in their corona and catalyze amyloid formation via surface-assisted heterogeneous nucleation. Importantly, we show that HSV-1 catalyzes the aggregation of the amyloid beta peptide (A{beta}42), a major constituent of amyloid plaques in Alzheimers disease, in-vitro and in animal models. Our results highlight the viral protein corona as an acquired structural layer that is critical for viral-host interactions and illustrate a mechanistic convergence between viral and amyloid pathologies.

microbiology↗

bioRxiv2017

A small core set of transcription factors bind strongly to DNA in different cell types

It is well established that transcription factors (TFs) play crucial roles in determining cell identity, and that a large fraction of all TFs are expressed in most cell types. In order to globally characterize activities of TFs in cells, we have developed a novel massively parallel protein activity assay, Active TF Identification (ATI) that measures DNA-binding activity of all TFs from any species or tissue type. In contrast to previous studies based on mRNA expression or protein abundance, we found that a set of TFs binding to only around ten distinct motifs display strong DNA-binding activity in any given cell or tissue type. Mass spectrometric identification of TFs revealed that within these highly active TFs, there were both housekeeping TFs, which were universally found in all cell types, and specific TFs, which were highly enriched in known factors that determine the fate of the analyzed tissue or cell type. The importance of a small subset of TFs for determining the overall accessible chromatin landscape of a cell suggests that gene regulatory logic may be simpler than what has previously been appreciated.

cell biology↗

bioRxiv2017

Mass spectrometry based qualification ofantibodies for plasma proteomics.

There is a strong need for procedures that enable context and application dependent validation of antibodies. Here we describe the foundation for a resource aiding more detailed assessment antibody selectivity for capturing endogenous proteins from human plasma. In 414 immunoprecipitation (IP) experiments with EDTA plasma, data was generated by mass spectrometry (LC-MS) with 157 antibodies (targeting 120 unique proteins). Out of a total of 1,313 unique proteins, 426 proteins (33%) were detected in > 20% of the assays and indicate a background comprised of mainly proteins from the complement system. For all proteins identified either in heat-treated or untreated EDTA plasma, frequencies of occurrence were derived. We determined z-scores for each IP as a measure of enrichment to annotate the antibodies into four categories (ON-target, CO-target, OFF-target and NO-target). For 45% (70/157) of the tested antibodies, the expected target proteins were enriched (z-score [≥]3) above background. There were 84% (59/70) of binders that co-enriched other proteins beside the intended target, either due to OFF-target binding or predicted interactions. Comparing several antibodies raised against IGFBP2, the established library allowed us to describe protein complexes in plasma, and we employed multiplexed sandwich immunoassays to confirm these. In summary, the generated resource of plasma enrichment profiles and background proteins adds a very useful and yet lacking starting point for the assessment of antibody selectivity in this clinically important body fluid. The provided insights will contribute to a more informed use of validated affinity reagents and may lead to further advancements of plasma proteomics assays.

biochemistry↗