Biology subjects

Deutsch, E.

Publications and source records attributed to Deutsch, E..

7 recordsLinked to original sources

bioRxiv2026

ACB1801 enhances tumor immunogenicity by targeting glycolysis/ferroptosis vulnerability and activating STAT1-signaling to overcome anti-PD-1 resistance in MSS colorectal cancer

BackgroundImmune checkpoint blockade (ICB) therapies demonstrate low efficacy in microsatellite stable (MSS) colorectal cancer (CRC) due to an immune-desert tumor microenvironment (TME) characterized by low antigen presentation and limited tumor-infiltrating lymphocytes (TILs). Harmine, a natural small-molecule and its promising derivatives ACB1801 have shown anti-tumor potential in preclinical models; however, their potential to reprogram the TME and overcome ICB resistance in MSS CRC remains unexplored. This study investigates whether and how ACB1801 can reshape TME to sensitize MSS CRC to ICB therapies. MethodsWe used the CT26 MSS colorectal cancer mouse model to evaluate the ability of the harmine derivative ACB1801 to enhance the efficacy of anti-PD-1 therapy. To characterize its mode of action, we performed immune landscape analysis and transcriptomic profiling of both CD45- and CD45+ tumor-derived cells. In parallel, mechanistic studies were conducted in vitro using mouse and human MSS CRC cell lines. ResultsWe demonstrate that the harmine derivative ACB1801 enhances the effectiveness of anti-PD-1 therapy in an MSS CRC mouse model. Combination therapy significantly increased CD8+ T cell infiltration and reduced regulatory T-cell (Treg) density in the TME. Transcriptomic profiling of CRC cells isolated from tumors treated with either anti-PD-1 alone or in combination with ACB1801 revealed significant enrichment of metabolic pathways in the combination group, characterized by reduced glycolysis and enhanced ferroptosis signatures. These findings were supported by in vitro data showing that ACB1801 reduces tumor cell glycolytic activity and promotes ferroptotic vulnerability. Mechanistically, ACB1801 induced STAT1 signaling, promoted CXCL10 release, and enhanced major histocompatibility complex class I (MHC-I)-dependent antigen presentation on tumor cells, thereby increasing tumor susceptibility to anti-PD-1 therapy. ConclusionCollectively, our findings indicate that combination therapy with harmine derivatives and ICBs represents a promising strategy for treating MSS CRC patients.

cancer biology↗

bioRxiv2023

Phosphorylation in the Plasmodium falciparum proteome: A meta-analysis of publicly available data sets

Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to human, of which P. falciparum is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signalling and hence, regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics datasets, to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 28,495 phosphorylated sites on P. falciparum proteins at 5% false localisation rate (FLR) and, of those, 18,100 at 1% FLR. We identified significant sequence motifs, likely indicative of different groups of kinases, responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved, and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We were also able to identify over 180,000 phosphosites within Plasmodium species beyond falciparum, based on orthologue mapping. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signalling, and thus warranting further study for their roles in host- pathogen interactions. All data has made available via UniProtKB, PRIDE and PeptideAtlas, with visualisation interfaces for exploring phosphosites in the context of other data on Plasmodium proteins. Author SummaryPlasmodium parasites continue to pose a significant global health threat, with a high proportion of the world at risk of malaria. It is imperative to gain new insights into cell signalling and regulation of biological processes in these parasites to develop effective treatments. This study focused on post- translational modifications (PTMs) of proteins, specifically phosphorylation. We conducted a meta- analysis of 11 publicly available phosphoproteomics datasets, identifying over 28,000 phosphorylated sites on P. falciparum proteins, using very rigorous statistics to avoid reporting false positives, and mapping to over 180,000 phosphorylation sites on other species of Plasmodium. The analysis revealed distinct sequence motifs associated with different groups of phosphosites (and likely indicative of different upstream kinases), and differences in the downstream pathways regulated. Conservation analysis highlighted clusters of phosphoproteins evolving at different rates within the Plasmodium genus. Notably, phosphorylation was enriched in regions of proteins lacking distinct structural elements, known as intrinsically disordered regions (IDRs), which are poorly conserved across the genus - we speculate that they are important for modulating protein interactions. The findings provide valuable insights into the molecular mechanisms of P. falciparum, with potential implications for understanding host-pathogen interactions. The comprehensive dataset generated is now publicly accessible, serving as a valuable resource for the scientific community through UniProtKB, PRIDE, and PeptideAtlas.

bioinformatics↗

bioRxiv2022

TGFβ receptor inhibition unleashes interferon-β production by tumor-associated macrophages and enhances radiotherapy efficacy

BackgroundTransforming growth factor-beta (TGF{beta}) can limit the efficacy of cancer treatments, including radiotherapy (RT), by inducing an immunosuppressive tumor environment. The association of TGF{beta} with impaired T cell infiltration and antitumor immunity is known, but the mechanisms by which TGF{beta} participates in immune cell exclusion and limits the efficacy of antitumor therapies warrant further investigations. MethodsWe used the clinically relevant TGF{beta} receptor 2 (TGF{beta}R2)-neutralizing antibody MT1 and the small molecule TGF{beta}R1 inhibitor LY3200882 and evaluated their efficacy in combination with RT against murine orthotopic models of head and neck and lung cancer. ResultsWe demonstrated that TGF{beta} pathway inhibition strongly increased the efficacy of RT. TGF{beta}R2 antibody upregulated interferon beta (IFN{beta}) expression in tumor-associated macrophages (TAMs) within the irradiated tumors and favored T cell infiltration at the periphery and within the core of the tumor lesions. We highlighted that both the antitumor efficacy and inhibition of immune exclusion observed with the combination of MT1 and RT were dependent on type I interferon signaling. ConclusionsThese data shed new light on the role of TGF{beta} in limiting the efficacy of RT, identifying a novel mechanism involving the inhibition of macrophage-derived type I interferon production, and fostering the use of TGF{beta}R inhibition in combination with RT in therapeutic strategies for the management of head and neck and lung cancer.

cancer biology↗

bioRxiv2020

Low doses of radiation therapy increase the immunosuppressive profile of lung macrophages via IL-10 production and IFNγ/IL-6 suppression: a therapeutic strategy to counteract lung inflammation?

Severe pneumonia and acute respiratory distress syndrome (ARDS) have been described in patients with severe COVID-19. Recently, early clinical data reported the efficacy of low doses of radiation therapy (RT) in the treatment of ARDS in patients with severe COVID-19. However, the involved mechanisms remained unknown. Here, we used airways-instilled lipopolysaccharide (LPS) and influenza virus (H1N1) as murine models of pneumonia, and Tolllike receptor (TLR)-3 stimulation in human lung macrophages. Low doses RT (0.5-1 Gy) decreased LPS induced pneumonia, and increased the percentage of Nerve- and Airway-associated Macrophages (NAMs) producing IL-10. During H1N1 viral infection, we observed decreased lung tissue damage and immune cell infiltration in irradiated animals. Low doses RT increased IL-10 production by infiltrating immune cells into the lung. Irradiation of TLR-3 ligand-stimulated human lung macrophages ex vivo increased IL-10 secretion and decreased IFN{gamma} production in the culture supernatant. The percentage of human lung macrophages producing IL-6 was also decreased. Our data highlight one of the mechanisms by which low doses RT regulate lung inflammation and skew lung macrophages towards an anti-inflammatory profile. These data provide the preclinical rationale for the use and for the optimization of low doses RT in situations such as COVID-19-induced ARDS.

immunology↗

bioRxiv2019

Mass Spectrometry-based Plasma Proteomics: Considerations from Sample Collection to Achieving Translatable Data

The proteomic analyses of human blood and blood-derived products (e.g. plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g. inter-individual variability), analysis of biospecimen (e.g. sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest whilst enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=51 SRC=\"FIGDIR/small/716563v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@1faf719org.highwire.dtl.DTLVardef@174c1b1org.highwire.dtl.DTLVardef@5860baorg.highwire.dtl.DTLVardef@366c21_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2019

Fast dose fractionation using ultra-short laser accelerated proton pulses can increase cancer cell mortality, which relies on functional PARP1 protein

Radiotherapy is a cornerstone of cancer management. The improvement of spatial dose distribution in the tumor volume by minimizing the dose deposited in the healthy tissues have been a major concern during the last decades. Temporal aspects of dose deposition are yet to be investigated. Laser-plasma-based particle accelerators are able to emit pulsed-proton beams at extremely high peak dose rates (~109 Gy/s) during several nanoseconds. The impact of such dose rates on resistant glioblastoma cell lines, SF763 and U87-MG, was compared to conventionally accelerated protons and X-rays. No difference was observed in DNA double-strand breaks generation and cells killing. The variation of the repetition rate of the proton bunches produced an oscillation of the radio-induced cell susceptibility in HCT116 cells, which appeared to be related to the presence of the PARP1 protein and an efficient parylation process. Interestingly, when laser-driven proton bunches were applied at 0.5 Hz, survival of the radioresistant HCT116 p53-/- cells equaled that of its radiosensitive counterpart, HCT116 WT, which was also similar to cells treated with the PARP1 inhibitor Olaparib. Altogether, these results suggest that the application modality of ultrashort bunches of particles could provide a great therapeutic potential in radiotherapy.

cancer biology↗

bioRxiv2018

BDQC: a general-purpose analytics tool for domain-blind validation of Big Data

Translational biomedical research is generating exponentially more data: thousands of whole-genome sequences (WGS) are now available; brain data are doubling every two years. Analyses of Big Data, including imaging, genomic, phenotypic, and clinical data, present qualitatively new challenges as well as opportunities. Among the challenges is a proliferation in ways analyses can fail, due largely to the increasing length and complexity of processing pipelines. Anomalies in input data, runtime resource exhaustion or node failure in a distributed computation can all cause pipeline hiccups that are not necessarily obvious in the output. Flaws that can taint results may persist undetected in complex pipelines, a danger amplified by the fact that research is often concurrent with the development of the software on which it depends. On the positive side, the huge sample sizes increase statistical power, which in turn can shed new insight and motivate innovative analytic approaches. We have developed a framework for Big Data Quality Control (BDQC) including an extensible set of heuristic and statistical analyses that identify deviations in data without regard to its meaning (domain-blind analyses). BDQC takes advantage of large sample sizes to classify the samples, estimate distributions and identify outliers. Such outliers may be symptoms of technology failure (e.g., truncated output of one step of a pipeline for a single genome) or may reveal unsuspected \" signal\" in the data (e.g., evidence of aneuploidy in a genome). We have applied the framework to validate real-world WGS analysis pipelines. BDQC successfully identified data outliers representing various failure classes, including genome analyses missing a whole chromosome or part thereof, hidden among thousands of intermediary output files. These failures could then be resolved by reanalyzing the affected samples. BDQC both identified hidden flaws as well as yielded new insights into the data. BDQC is designed to complement quality software development practices. There are multiple benefits from the application of BDQC at all pipeline stages. By verifying input correctness, it can help avoid expensive computations on flawed data. Analysis of intermediary and final results facilitates recovery from aberrant termination of processes. All these computationally inexpensive verifications reduce cryptic analytical artifacts that could seriously preclude clinical-grade genome interpretation. BDQC is available at https://github.com/ini-bdds/bdqc.

bioinformatics↗