Biology subjects

Doultsinos, D.

Publications and source records attributed to Doultsinos, D..

6 recordsLinked to original sources

bioRxiv2025

IRE1 activity regulates tumour and microenvironment cell lineage states while stratifying localised and metastatic prostate cancer.

Prostate cancer (PCa) is an androgen receptor (AR) driven, high-incidence disease significantly contributing to cancer mortality. PCa is in need of better risk stratification at diagnosis and treatment outcomes in patients at high risk of metastasis. The unfolded protein response (UPR) is an AR-dependent process. However, the impact of the UPR transducer IRE1 on AR-dependent biology and treatment resistance has not been defined. We use diverse pre-clinical models of stress response to describe IRE1 activity impact on multiple disease stages and demonstrate its involvement with poor prognosis (RB1 loss), and cell lineage determination (club phenotypes). Integrating clinical transcriptomic datasets, we chart IRE1 activity throughout PCa evolution by developing a PCa-specific, IRE1 activity gene set (IRE1_18) reflecting both tumoral and micro-environmental niches. IRE1_18 can determine tumoral identity, inform androgen deprivation treatment suitability, prognosticate localised and metastatic disease independently from AR activity, and guide IRE1 modulation as a novel combination therapeutic. Graphical Abstract created using Biorender.com O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/643042v3_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@18edd6aorg.highwire.dtl.DTLVardef@6a759eorg.highwire.dtl.DTLVardef@14ff3fborg.highwire.dtl.DTLVardef@1ae77d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

IGFs regulate cancer cell immune evasion in prostate cancer

Insulin-like growth factor-1 (IGF-1) promotes prostate cancer (PCa) development and lethality, with immunosuppressive properties in other disease models. These studies investigated the tumor-intrinsic immune effects of IGF-1 in PCa to understand mechanisms underlying its poor immunotherapy response. Transcriptional profiling of human (DU145, 22Rv1) and murine (Myc-CaP) PCa cells revealed, through pathway enrichment, that cytokine signalling, antigen processing and presentation, and other immune regulatory pathways, were most suppressed by IGF-1. We went on to investigate changes in the expression of components of two key pathways responsible for cancer cell recognition by immune cells and immune evasion: antigen processing and presentation, and PD-L1 checkpoint expression. These pathways are crucial for determining immunotherapy response. IGF-1 downregulated transporters associated with antigen processing (TAPs), endoplasmic reticulum aminopeptidase-1 (ERAP-1), and Class I component {beta}2-microglobulin, without major changes in Class I allele expression. These effects were associated with reduced presentation of Class I complexes on the Myc-CaP cell surface suggesting altered peptide transport, processing, and/or presentation. In contrast, IGF-1 upregulated immune checkpoint CD274 (PD-L1) via IGF receptor/AKT/ERK-dependent signaling. Analysis of public data (TCGA Firehose Legacy PCa) revealed increased CD274 expression in PCa with high endogenous IGF1 and IGFBP5, markers of high IGF axis activity. Additionally, in primary PCa (n=32), multiplex immunofluorescence revealed higher PD-L1 expression in the central tumor of men with high serum IGF-1 promoting cancer cell immune evasion in PCa. These findings indicate a novel mechanism by which IGF-1 mediates immunosuppressive effects in malignant prostate epithelium, potentially explaining the poor responsiveness of PCa to immunotherapy and highlighting the complex interplay between IGF signaling and immune evasion.

cancer biology↗

bioRxiv2023

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of heterogeneity on genomic signature scoring

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx(R), Decipher(R), Prostadiag(R)) using a step-wise approach increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses. Patient summaryProstate cancers are very variable, including within a single tumour. Current genetic scoring systems, which are sometimes used to make decisions for how to treat patients with prostate cancer, are based on sampling methods which do not reflect these variations. We found, using state-of-the-art spatial genetic technology to simulate accurate assessment of variation in biopsies, that the current approaches miss important details which could negatively impact clinical decisions. Take home messageVirtual biopsies from spatial transcriptomic analysis of a whole prostate reveal that current genomic risk scores potentially deliver misleading results as they are based on bulk analysis of prostate biopsies and ignore tumour heterogeneity.

genomics↗

bioRxiv2023

Clonal phylogenies inferred from bulk, single cell, and spatial transcriptomic analysis of cancer

Epithelial cancers are typically heterogeneous with primary prostate cancer being a typical example of histological and genomic variation. Prostate cancer is the second most common male cancer in western industrialized countries. Prior studies of primary prostate cancer tumor genetics revealed extensive inter and intra-patient tumor heterogeneity. Recent advances have enabled extensive single-cell and spatial transcriptomic profiling of tissue specimens. The ability to resolve accurate prostate cancer tumor phylogenies at high spatial resolution would provide tools to address questions in tumorigenesis, disease progression, and metastasis. Recent advances in machine learning have enabled the inference of ground-truth genomic single-nucleotide and copy number variant status from transcript data. The inferred SNV and CNV states can be used to resolve clonal phylogenies, however, it is still unknown how faithfully transcript-based tumor phylogenies reconstruct ground truth DNA-based tumor phylogenies. We sought to study the accuracy of inferred-transcript to recapitulate DNA-based tumor phylogenies. We first performed in-silico comparisons of inferred and directly resolved SNV and CNV status, from single cancer cells, from three different cell lines. We found that inferred SNV phylogenies accurately recapitulate DNA phylogenies (entanglement = 0.097). We observed similar results in iCNV and CNV based phylogenies (entanglement = 0.11). Analysis of published prostate cancer DNA phylogenies and inferred CNV, SNV and transcript based phylogenies demonstrated phylogenetic concordance. Finally, a comparison of pseudo-bulked spatial transcriptomic data to adjacent sections with WGS data also demonstrated recapitulation of ground truth (entanglement = 0.35). These results suggest that transcript-based inferred phylogenies recapitulate conventional genomic phylogenies. Further work will need to be done to increase accuracy, genomic, and spatial resolution.

bioinformatics↗

bioRxiv2021

Accelerating manufacturing to start large-scale supply of a new adenovirus-vectored vaccine within 100 days

The Coalition for Epidemic Preparedness Innovations 100-day moonshot aspires to launch a new vaccine within 100 days of pathogen identification. Here, we describe work to optimize adenovirus vector manufacturing for rapid response, by minimizing time to clinical trial and first large-scale supply, and maximizing the output from the available manufacturing footprint. We describe a rapid viral seed expansion workflow that allows vaccine release to clinical trials within 60 days of antigen sequence identification, followed by vaccine release from globally distributed sites within a further 40 days. We also describe a new perfusion-based upstream production process, designed to maximize output while retaining simplicity and suitability for existing manufacturing facilities. This improves upstream volumetric productivity of ChAdOx1 nCoV-19 by around four-fold and remains compatible with the existing downstream process, yielding drug substance sufficient for 10000 doses from each liter of bioreactor capacity. Transition to a new production process across a large manufacturing network is a major task. In the short term, the rapid seed generation workflow could be used with the existing production process. We also use techno-economic modelling to show that, if linear scale-up were achieved, a single cleanroom containing two 2000 L bioreactors running our new perfusion-based process could supply bulk drug substance for around 120 million doses each month, costing <0.20 EUR/dose. We estimate that a manufacturing network with 32000 L of bioreactor capacity could release around 1 billion doses of a new vaccine within 130 days of genomic sequencing of a new pathogen, in a hypothetical surge campaign with suitable prior preparation and resources, including adequate fill-and-finish capacity. This accelerated manufacturing process, along with other advantages such as thermal stability, supports the ongoing value of adenovirus-vectored vaccines as a rapidly adaptable and deployable platform for emergency response.

bioengineering↗

bioRxiv2019

Constitutive IRE1α signaling maintains glioblastoma cell differentiation

Endoplasmic Reticulum (ER) proteostasis control and the Unfolded Protein Response (UPRER) have been shown to contribute to tumor development and aggressiveness. As such, the UPRER sensor IRE1 (referred to as IRE1 hereafter) is a major regulator of glioblastoma (GBM) development and is an appealing therapeutic target. To document IRE1 suitability as an antineoplastic pharmacological target, we investigated how this protein contributed to GBM cell reprogramming, a property involved in treatment resistance and disease recurrence. Probing the IRE1 activity molecular signature on transcriptome datasets of human tumors, showed that high IRE1 activity correlated with low expression of the main GBM stemness transcription factors SOX2, SALL2, POU3F2 and OLIG2. Henceforth, this phenotype was pharmacologically and genetically recapitulated in immortalized and primary GBM cell lines as well as in mouse models. We demonstrated that constitutive activation of the IRE1/XBP1/miR148a signaling axis repressed the expression of SOX2 and led to maintenance of a differentiation phenotype in GBM cells. Our results describe a novel role for IRE1 signaling in maintaining differentiated tumor cell state and highlight opportunities of informed IRE1 modulation utility in GBM therapy.

cancer biology↗