Biology subjects

Rad, R.

Publications and source records attributed to Rad, R..

28 records · Page 2Linked to original sources

bioRxiv2022

eIF3 mRNA selectivity profiling reveals eIF3k as a cancer-relevant regulator of ribosome content

eIF3, whose subunits are frequently overexpressed in cancer, regulates mRNA translation from initiation to termination, but mRNA-selective functions of individual subunits remain poorly defined. Using multi-omic profiling upon acute depletion of eIF3 subunits, we observed that while eIF3a, b, e, and f markedly differed in their impact on eIF3 holo-complex formation and translation, they were each required for cancer cell proliferation and tumor growth. Remarkably, eIF3k showed the opposite pattern with depletion promoting global translation, cell proliferation, tumor growth, and stress resistance through repressing the synthesis of ribosomal proteins, especially RPS15A. Whereas ectopic expression of RPS15A mimicked the anabolic effects of eIF3k depletion, disruption of eIF3 binding to the 5-UTR of RSP15A mRNA negated them. Supported by mathematical modeling, our data uncovers eIF3k-l as a mRNA-specific module which, through controlling RPS15A translation, serves as a rheostat of ribosome content to secure spare translational capacity that can be mobilized during stress.

cell biology↗

bioRxiv2021

Cancer tolerance to chromosomal instability is driven by Stat1 inactivation in vivo

Chromosomal instability is a hallmark of cancer, but also an instigator of aneuploidy-induced stress, reducing cellular fitness. To better understand how cells with CIN adjust to aneuploidy and adopt a malignant fate in vivo, we performed a genome-wide mutagenesis screen in mice. We find that specifically aneuploid tumors inactivate Stat1 signaling in combination with increased Myc activity. By contrast, loss of p53 is common, but not enriched in CIN tumors. Validation in another tissue type confirmed that CIN promotes immune cell infiltration, which is alleviated by Stat1 loss combined with Myc activation, but not with p53 inactivation, or Myc activation alone. Importantly, we find that this mechanism is preserved in human aneuploid cancers. We conclude that aneuploid cancers inactivate Stat1 signaling to circumvent immune surveillance.

cancer biology↗

bioRxiv2021

Spatial and temporal plasticity of neoantigen-specific T-cell responses bases on characteristics associated to antigen and TCR

Neoantigens derived from somatic mutations have been demonstrated to correlate with therapeutic responses mediated by treatment with immune checkpoint inhibitors. Neoantigens are therefore highly attractive targets for the development of personalized medicine approaches although their quality and associated immune responses is not yet well understood. In a case study of metastatic malignant melanoma, we performed an in-depth characterization of neoantigens and respective T-cell responses in the context of immunotherapy with Ipilimumab. Three neoantigens identified either by immunopeptidomics or in silico prediction were investigated using binding affinity analyses and structural simulations. We isolated seven T-cell receptors (TCRs) from the patient immune repertoire recognizing these antigens. TCRs were compared in-vitro and in-vivo with multi-parametric analyses. Identified immunogenic peptides showed similar binding affinities to the human leukocyte antigen (HLA) complex and comparable differences to their wildtype counterparts in molecular dynamic simulations. Nevertheless, isolated TCRs differed substantially in functionality and frequency. In fact, TCRs with comparably lower functional avidity and higher potential for cross-reactivity provided at least equal anti-tumor immune responses in vivo. Of note, these TCRs showed a reduced activation pattern upon primary in vitro stimulation. Exploration of the TCR-{beta} repertoire in blood and in different tumor-related tissues over three years, offered insights on the high frequency and particular long-term persistence of low-avidity TCRs. These data indicate that qualitative differences of neoantigen-specific TCRs and their impact on function and longevity need to be considered for neoantigen targeting by adoptive T-cell therapy using TCR-transgenic T cells. Statement of translational relevanceImmunotherapy has demonstrated high efficacy in diverse malignancies. Neoantigens derived from mutations provide promising targets for safe and highly tumor-specific therapeutic approaches. Yet, single determinants of an effective and enduring T-cell mediated tumor rejection are still not well understood. We analyzed in detail seven neoantigen-specific T-cell receptors (TCRs) derived from a melanoma patient targeting three different altered peptide ligands identified by mass spectrometry and prediction analyses. Functional characterization of these TCRs revealed potent anti-tumor reactivity of all TCRs. Of special interest, TCRs with comparably lower affinity demonstrated effective in vivo activity as well as dominant spatial and temporal distribution in blood and tissue. Functional differences of TCR may require further T-cell and/or TCR engineering and should be considered for future clinical trial designs.

immunology↗

bioRxiv2020

Precise Estimation of In Vivo Protein Turnover Rates

Isotopic labeling with deuterium oxide (D2O) is a common technique for estimating in vivo protein turnover, but its use has been limited by two long-standing problems: (1) identifying non-monoisotopic peptides; and (2) estimating protein turnover rates in the presence of dynamic amino acid enrichment. In this paper, we present a novel experimental and analytical framework for solving these two problems. Peptides with high probabilities of labeling in many amino acids present fragmentation spectra that frequently do not match the theoretical spectra used in standard identification algorithms. We resolve this difficulty using a modified search algorithm we call Conditional Ion Distribution Search (CIDS). Increased identifications from CIDS along with direct measurement of amino acid enrichment and statistical modeling that accounts for heterogeneous information across peptides, dramatically improves the accuracy and precision of half-life estimates. We benchmark the approach in cells, where near-complete labeling is possible, and conduct an in vivo experiment revealing, for the first time, differences in protein turnover between mice and naked mole-rats commensurate with their disparate longevity.

bioinformatics↗

bioRxiv2020

Targeting the ubiquitin-proteasome system in a pancreatic cancer subtype with hyperactive MYC

Purpose The myelocytomatosis oncogene (MYC) is an important driver in a subtype of pancreatic ductal adenocarcinoma (PDAC). However, MYC remains a challenging therapeutic target, therefore identifying druggable synthetic lethal interactions in MYC-active PDAC may lead to novel precise therapies.Methods Cluster analysis using direct MYC target genes was used to identify PDAC with active MYC. We profiled the transcriptome of established human cell lines, murine primary PDAC cell lines and also accessed public available repositories for transcriptomic profiling. Networks active in MYC hyperactive subtypes were analyzed by gene set enrichment analysis. An unbiased pharmacological drug screen with FDA-approved anti-cancer drugs was conducted to define MYC-associated vulnerabilities, which were validated by analysis of drug response repositories and genetic gain- and loss-of-function experiments.Results In an unbiased pharmacological drug screen with FDA-approved anti-cancer drugs we detected that the proteasome inhibitor bortezomib triggers a MYC-associated vulnerability. By integrating publicly available data sets we found the unfolded protein response as a signature connected to MYC. Furthermore, the increased sensitivity of MYC hyperactive PDACs to bortezomib was validated in genetically modified PDAC cells.Conclusions In sum, we provide evidence that perturbing the ubiquitin proteasome system might be an option to target MYC hyperactive PDAC cells and our data provide the rationale to further develop precise targeting of the ubiquitin-proteasome system as a subtype-specific therapeutic approach.Competing Interest StatementThe authors have declared no competing interest.Abbrevations4-OHT4-hydoxytamoxifenATF4activating transcription factor 4BETbromodomain and extra terminal motifCNVcopy number variationCTD2cancer target discovery and development networkdepmapdependency mapDoRothEAdiscriminant regulon expression analysisGSEAgene set enrichment analysisICGCinternational cancer gene consortiumMYCmyelocytomatosis oncogenePDACpancreatic ductal adenocarcinomaPERKproteinkinase RNA-activated-like ER kinaseSUMOsmall-ubiquitin-like modifierTCGAthe cancer genome atlasUPRunfolded protein responseUPSubiquitin proteasome systemView Full Text

cancer biology↗

bioRxiv2020

Multi-level proteomics reveals host-perturbation strategies of SARS-CoV-2 and SARS-CoV

The global emergence of SARS-CoV-2 urgently requires an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1-10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. We therefore conducted a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactome of both viruses, as well as their influence on transcriptome, proteome, ubiquitinome and phosphoproteome in a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon SARS-CoV-2 and SARS-CoV infections at different layers and identified unique and common molecular mechanisms of these closely related coronaviruses. The TGF-{beta} pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org) highlights many hotspots that can be targeted by existing drugs and it can guide rational design of virus- and host-directed therapies, which we exemplify by identifying kinase and MMPs inhibitors with potent antiviral effects against SARS-CoV-2.

systems biology↗

bioRxiv2020

Improved Monoisotopic Mass Estimation for Deeper Proteome Coverage

Accurate assignment of monoisotopic peaks is essential for the identification of peptides in bottom-up proteomics. Misassignment or inaccurate attribution of peptidic ions leads to lower sensitivity and fewer total peptide identifications. In the present work we present a performant, open-source, cross-platform algorithm, Monocle, for the rapid reassignment of instrument assigned precursor peaks to monoisotopic peptide assignments. We demonstrate that the present algorithm can be integrated into many common proteomics pipelines and provides rapid conversion from multiple data source types. Finally, we show that our monoisotopic peak assignment results in up to a two-fold increase in total peptide identifications compared to analyses lacking monoisotopic correction and a 44% improvement over previous monoisotopic peak correction algorithms.

bioinformatics↗

bioRxiv2020

A GATA6-centered gene regulatory network involving HNFs and ΔNp63 controls plasticity and immune escape in pancreatic cancer

ObjectiveMolecular taxonomy of tumors is the foundation of personalized medicine and is becoming of paramount importance for therapeutic purposes. Four transcriptomics-based classification systems of pancreatic ductal adenocarcinoma (PDAC) exist, which consistently identified a subtype of highly aggressive PDACs with basal-like features, including {Delta}Np63 expression and loss of the epithelial master regulator GATA6. We investigated the precise molecular events driving PDAC progression and the emergence of the basal program. DesignWe combined the analysis of patient-derived transcriptomics datasets and tissue samples with mechanistic experiments using a novel dual-recombinase mouse model for Gata6 deletion at late stages of KRasG12D-driven pancreatic tumorigenesis (Gata6LateKO). ResultsThis comprehensive human-to-mouse approach allowed us to show that GATA6 loss is necessary, but not sufficient, for the expression of a basal program in patients and in mice. The concomitant loss of HNF1A and HNF4A, likely through epigenetic silencing, is required for the full phenotype switch. Moreover, Gata6 deletion in mice dramatically increased the metastatic rate, with a propensity for lung metastases. Through RNA-Seq analysis of primary cells isolated from mouse tumors, we show that Gata6 inhibits tumor cell plasticity and immune evasion, suggesting that it works as a barrier for acquiring the fully developed basal and metastatic phenotype. ConclusionsOur work provides both a mechanistic molecular link between the basal phenotype and metastasis and a valuable preclinical tool to investigate the most aggressive subtype of PDAC. These data, therefore, are important for understanding the pathobiological features underlying the heterogeneity of pancreatic cancer in both mice and human. What is already known about this subject?O_LIMultiple transcriptomics-based studies have identified a basal-like subtype of pancreatic ductal adenocarcinoma (PDAC) with especially poor prognosis. C_LIO_LILoss of GATA6 in PDAC cells is associated with altered differentiation, including ectopic expression of basal markers such as KRT14. C_LIO_LIAberrant expression of the {Delta}Np63 transcription factor can drive the expression of the basal transcriptional program. C_LI What are the new findings?O_LILoss of GATA6 expression is necessary but not sufficient for the expression of {Delta}Np63 and the basal phenotype. C_LIO_LIConcomitant silencing of HNF4A and HNF1A, possibly through epigenetic mechanisms, is required for the full-blown phenotype. C_LIO_LIGata6 deletion in established murine tumors favors the basal and metastatic phenotype, with a lung tropism, in a next-generation model of KRasG12D-driven PDAC. C_LIO_LILoss of GATA6 expression is associated with features of immune escape in mouse and human PDAC cells. C_LI How might it impact on clinical practice in the foreseeable future?O_LIThe combined analysis of GATA6, HNFs, and TP63 expression in patient-derived samples will provide a more precise classification of PDAC. C_LIO_LIRestoration of the classical PDAC phenotype may not only reduce metastatic potential but also increase immune recognition of tumor cells. C_LI

cancer biology↗

bioRxiv2020

Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins - half the proteome - in 293T cells and includes 118,162 interactions among 14,586 proteins; the second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome at unprecedented scale, encoding protein function, localization, and complex membership. Their comparison validates thousands of interactions and reveals extensive customization of each network. While shared interactions reside in core complexes and involve essential proteins, cell-specific interactions bridge conserved complexes, likely rewiring each cells interactome. Interactions are gained and lost in tandem among proteins of shared function as the proteome remodels to produce each cells phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

systems biology↗

bioRxiv2019

Full-featured, real-time database searching platform enables fast and accurate multiplexed quantitative proteomics.

Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 methods longer duty cycles. RTS with Orbiter enables the elimination of SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiters online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 milliseconds. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiters RTS was able to quantify more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 hours for RTS, 36 hours for SPS-MS3).

cell biology↗