Biology subjects

Trajanoski, Z.

Publications and source records attributed to Trajanoski, Z..

At least 19 recordsLinked to original sources

bioRxiv2025

Escherichia-Shigella expansion and metabolite dysregulation in type 3c diabetes

Emerging evidence supports a bidirectional gut-pancreas axis in which microbial dysbiosis, barrier dysfunction, and altered metabolite fluxes contribute to pancreatogenic diabetes (T3cDM). Whether gut microbial changes reflect systemic metabolic disturbances or primarily arise from exocrine pancreatic insufficiency (EPI) remains unclear. We profiled the gut microbiome of 48 outpatients with T3cDM, type 1 diabetes (T1DM), and healthy controls. Genus-level 16S rRNA data were analysed using cross-validated LASSO logistic regression and patient-specific community metabolic models. T3cDM showed reduced -diversity and distinct {beta}-diversity compared with T1DM and controls. Key compositional shifts included enrichment of Enterobacteriaceae (notably Escherichia-Shigella) and Streptococcaceae in T3cDM. LASSO models discriminated T3cDM from T1DM (AUC 0.867; accuracy 0.818), highlighting Blautia, Escherichia-Shigella, Streptococcus, Clostridium, and Faecalibacterium as predictors. Metabolic modelling indicated elevated Escherichia-Shigella growth in T3cDM and disease-specific metabolite fluxes. Gut microbial shifts in T3cDM predominantly reflect EPI rather than systemic metabolic disturbances characteristic of T1DM, underscoring the central role of exocrine pancreatic dysfunction in shaping the gut microbiome and its metabolic activity.

microbiology↗

bioRxiv2025

Optimised dissociation and multimodal profiling of prostate cancer stroma reveal fibromuscular cell heterogeneity with clinical correlates

BackgroundDynamic remodelling of the tumour microenvironment (TME) plays a central role in prostate cancer (PCa) progression, immune evasion and therapy resistance. However, the co-existence of both tumour-promoting and tumour-restraining stromal elements necessitates extensive characterisation of the TME for effective targeting. Fibromuscular cell heterogeneity in PCa remains poorly characterised, in part due to challenges in isolating cells embedded within the desmoplastic stroma. This study therefore aimed to better characterise fibroblast and smooth muscle cell (SMC) populations as the major tissue-resident stromal cell subtypes within the PCa TME. MethodsA PCa single-cell RNA sequencing (scRNA-seq) dataset was re-analysed to define fibromuscular subtypes. Due to low fibroblast yields, an optimised tissue dissociation protocol was developed and benchmarked against two commercial kits via flow cytometry, immunostaining of clinical specimens and ex vivo culture. Dimensionality reduction and clustering were applied to the CD31- stromal fraction using a multiparameter surface marker panel. Annotation of the resulting clusters based on their surface marker profile was supported by integrating scRNA-seq and immuno-histological findings. ResultsThe optimised protocol yielded over twice the viable cells/mg tissue compared to two commercial kits, preserved surface marker integrity, enhanced successful cultivation of mesenchymal cells and recovered diverse stromal subpopulations from benign and malignant samples. Dimensionality reduction and clustering of flow cytometry counts identified 11 distinct CD31- stromal populations. Integration with transcriptomic data and immunofluorescence of clinical specimens identified spatially- and prognostically-distinct fibroblast subtypes, including inflammatory and myofibroblastic cancer-associated fibroblasts, pericytes linked to poor prognosis and a novel SMC subset associated with stromal activation. ConclusionThis study presents a robust workflow for improved isolation and characterisation of fibromuscular stromal cells in PCa. The multimodal approach enabled refined characterisation of phenotypically distinct and clinically-relevant stromal subpopulations within their spatial context providing a foundation for future TME-targeted therapies.

cancer biology↗

bioRxiv2025

Coordinated IFN-γ/TNF Axis Drives Selective Loss of Activated Enteric Glia in Inflammatory Bowel Diseases

BackgroundEnteric glial cells (EGC) play a crucial role in maintaining gut homeostasis, but their dysregulation in inflammatory bowel diseases (IBD) remains poorly understood. Emerging preclinical data suggests activated EGC have beneficial roles in controlling gut pathophysiology. ObjectiveUnderstanding EGC activation and adaptation during experimental and clinical IBD. DesignWe provide the first highly integrated approach to identify EGC activation signature in IBD. Profiling 390 samples from IBD patients via bulk and single-nucleus (sn) transcriptomics and replicate the findings on publicly available bulk and single-cell (sc) datasets from 1160 patients and 19,000 single EGC. Preclinical modelling of Th1/Th17 inflammation, reporter-assisted EGC sorting, analysis of regulated cell death, and Casp8 ablation in EGC was performed ResultsWe identified novel IBD type and sampling associated EGC activation signature. Specific EGC activation markers were shared in biopsies and resection specimens, and were divergent between Crohns disease and Ulcerative colitis. Preclinical modelling of intestinal inflammation identified combinatorial TNF and IFN-{gamma}-driven activation of EGC, associated with elevated necroptosis, and negatively impacting gut motility. Genetic-reporter-enabled sorting and downstream analyses confirmed TNF and IFN-{gamma}-driven EGC necroptosis, potentiated by Casp8 deficiency. Furthermore, snRNA-Seq from IBD patient samples confirmed elevated cell death signature in activated but not in rare neuroglia progenitor-like cluster. ConclusionOur findings identify IBD type-associated activated EGC markers involved in immune and epithelial homeoastasis. We uncover necroptosis of activated EGCs as a constituent of intestinal inflammation. Advancing our understanding of activated EGC survival is pivotal in elucidating their complex roles in maintaining gut immune-epithelial homeostasis. What is already known on this topicActivated EGC have emerged as important contributors in maintaining epithelial, immune and neuronal homeostasis. Increasing evidence from mouse studies points to the role of activated EGC in epithelial regeneration, tolerogenic T-cell activation, relaying psychological stress to the enteric nervous system, post-injury neurogenesis, and helminth clearance. Nevertheless, no consensus has emerged on what might define activated EGC in the context of IBD and how EGC turnover is affected in gut inflammation, limiting translation of their disease associated roles. What this study addsBy combining bulk with single cell and single nucleus transcriptomes from IBD patients we identified new IBD type- and location-associated EGC activation signatures. Some of these are conserved with mouse EGC in gut inflammation models. We identified osteopontin an immunomodulator and Wnt6 an epithelial morphogen elevated in IBD EGC. We also identified IBD-associated EGC cell clusters, which display higher expression of cell death pathway transcripts. To investigate EGC turnover, we utilized preclinical models and found rapid EGC activation upon Th1/Th17 inflammation. This was associated with elevated EGC activation and caspase-independent necroptotic cell death. Ex vivo experiments showed a combinatorial requirement of IFN-{gamma} and TNF in mediating EGC necroptosis. Our findings were replicated on multiple publicly available sc-RNA sequencing datasets from IBD patients. How this study might affect research, practice or policyExpanding on the available repertoire of EGC activation markers in IBD, both shared and unique to sampling procedure, disease type, and location will provide researchers with tools to identify EGC homeostasis during IBD. Moreover, the nature of the identified markers will stimulate research into specific EGC pathways triggered in inflammation. Adding to this, the rapid induction in pathological death of activated but not naive EGC upon IFN-{gamma} and TNF stimulation will shed light on EGC adaptation and turnover. Our identification of markers of activated EGC with immuno-modulatory and epithelial-regenerative properties, including osteopontin and wingless family of morphogenes will stimulate further research in EGC-immune and EGC-epithelial communication in the context of IBD.

neuroscience↗

bioRxiv2025

IBDome: An integrated molecular, histopathological, and clinical atlas of inflammatory bowel diseases

Multi-omic and multimodal datasets with detailed clinical annotations offer significant potential to advance our understanding of inflammatory bowel diseases (IBD), refine diagnostics, and enable personalized therapeutic strategies. In this multi-cohort study, we performed an extensive multi-omic and multimodal analysis of 1,002 clinically annotated patients with IBD and non-IBD controls, incorporating whole-exome and RNA sequencing of normal and inflamed gut tissues, serum proteomics, and histopathological assessments from images of H&E-stained tissue sections. Transcriptomic profiles of normal and inflamed tissues revealed distinct site-specific inflammatory signatures in Crohns disease (CD) and ulcerative colitis (UC). Leveraging serum proteomics, we developed an inflammatory protein severity signature that reflects underlying intestinal molecular inflammation. Furthermore, foundation model-based deep learning accurately predicted histologic disease activity scores from images of H&E-stained intestinal tissue sections, offering a robust tool for clinical evaluation. Our integrative analysis highlights the potential of combining multi-omics and advanced computational approaches to improve our understanding and management of IBD.

molecular biology↗

bioRxiv2025

Unraveling the YAP1-TGFβ1 axis: a key driver of androgen receptor loss in prostate cancer-associated fibroblasts

Due to their pivotal roles in tumor progression and therapy resistance, cancer-associated fibroblasts (CAF) are considered key therapeutic targets with loss of stromal androgen receptor (AR) a poorly understood hallmark of aggressive prostate cancer (PCa). A paucity of pre-clinical models however has hampered functional studies of CAF heterogeneity. We demonstrate that our newly-generated CAF biobank contains three FAP+-fibroblast subtypes, each with unique molecular and functional traits. Cultures with an early-activated phenotype expressed the highest levels of AR and exhibited AR-dependent growth. Consistently, stromal cells expressing early-activation markers co-expressed nuclear AR in clinical specimens and were enriched in pre-neoplastic lesions/low-grade PCa. Conversely, myofibroblastic CAF (myCAF), which expressed low AR levels in vitro and in vivo and were proliferatively-insensitive to AR signaling modulation, constituted the predominant CAF subpopulation in stromogenic high-grade PCa and castration-resistant LACP9 patient-derived xenografts. Exacerbation of the myCAF state upon castration of LAPC9-bearing hosts underscored these findings. Mechanistically, AR loss in myCAF was driven by an NF{kappa}B-TGF{beta}1-YAP1 axis, whose combined targeting synergistically repressed myofibroblastic hallmarks and impaired autophagic flux, effects that were potentiated by enzalutamide resulting in myCAF cell death. Collectively, these findings provide a mechanistic rationale for adjuvant targeting of the YAP1-TGF{beta} signaling axis to improve patient outcomes.

cancer biology↗

bioRxiv2024

Eosinophils restrict CRC metastasis by inhibiting pro-tumorigenic SPP1+ macrophage differentiation

Eosinophils, traditionally associated with allergic responses, have emerged as critical immune modulators in colorectal cancer (CRC). Here, we reveal that eosinophils actively shape the tumor microenvironment and influence metastatic progression. Using comprehensive transcriptomics analysis of human CRC and a murine orthotopic tumor model, we identify a conserved tumor-specific eosinophil signature and activation profile. Despite their declining presence in advanced CRC, eosinophils suppress metastatic dissemination by counteracting the pro-tumorigenic functions of SPP1+ macrophages - a subset linked to immune exclusion and tumor metastasis. Mechanistically, eosinophils respond to tumor-derived signals and inhibit macrophage differentiation into SPP1+ cells. Eosinophil depletion exacerbates peritoneal tumor spread. These findings highlight the pivotal role of eosinophils in restraining late-stage CRC progression and unveil a novel eosinophil-macrophage axis as potential therapeutic targets.

cancer biology↗

bioRxiv2024

NovumRNA: accurate prediction of non-canonical tumor antigens from RNA sequencing data

Non-canonical tumor-specific antigens (ncTSAs) can expand the pool of targets for cancer immunotherapy, but require robust and comprehensive computational pipelines for their prediction. Here, we present NovumRNA, a fully-automated Nextflow pipeline for predicting different classes of ncTSAs from patients RNA sequencing data. We extensively validated NovumRNA using publicly-available and newly-generated datasets, demonstrating the robustness of its analytical modules and predictions. NovumRNA analysis of colorectal cancer organoid data revealed comparable ncTSA potential for microsatellite stable and unstable tumors and candidate therapeutic targets for patients with low tumor mutational burden. Finally, our investigation of glioblastoma cell lines demonstrated increased ncTSAs burden upon indisulam treatment, and detection by NovumRNA of therapy-induced ncTSAs, which we could validate experimentally. These findings underscore the potential of NovumRNA for identifying synergistic drugs and novel therapeutic targets for immunotherapy, which could ultimately extend its benefit to a broader patient population.

bioinformatics↗

bioRxiv2024

Dissecting heterogeneity of tumor microenvironment in colorectal cancer using high-resolution single-cell atlas

The immune composition of the tumor microenvironment (TME) has a major impact on the therapeutic response and clinical outcome in patients with colorectal cancer (CRC). Here, we comprehensively characterize the TME at the single-cell level by first building a large-scale atlas that integrates 4.27 million single cells from 1,670 patient samples. We then complemented the atlas with single-cell profiles from four CRC cohorts with 266 patients, including cells with low mRNA content, spatial transcriptional profiles from 3.7 million cells, and protein profiles from 0.7 million cells. The analysis of the atlas allows refined tumor classification into four immune phenotypes: immune desert, B cell enriched, T cell enriched, and myeloid cell enriched subtypes. Within the myeloid compartment we uncover distinct subpopulations of neutrophils that acquire new functional properties in blood and in the TME, including anti-tumorigenic capabilities. Further, spatial multimodal single-cell profiling reveals that neutrophils are organized in clusters within distinct functional niches. Finally, using an orthotopic mouse model we show that cancer-derived systemic signals modify neutrophil production in the bone marrow, providing evidence for tumor-induced granulopoiesis. Our study provides a big data resource for the CRC and suggests novel therapeutic strategies targeting neutrophils.

bioinformatics↗

bioRxiv2024

Conventional therapy induces tumor immunoediting and modulates the immune contexture in colorectal cancer

BackgroundCancer immunotherapies for patients with colorectal cancer (CRC) continue to lag behind other solid cancer types with the exception of 4% of patients with microsatellite-instable tumors. Thus, there is an urgent need to broaden the clinical benefit of checkpoint blockers to CRC by combining conventional therapies to sensitise tumors to immunotherapy. However, the impact of conventional drugs on immunoediting, potentially promoting the positive selection of less immunogenic variants, and on the tumor immune contexture in CRC, remain elusive. MethodsWe performed comprehensive multimodal profiling using longitudinal samples from metastatic CRC patients undergoing neoadjuvant therapy with mFOLFOX6 and Bevacizumab. Exome-sequencing, RNA-sequencing and multiplexed immunofluorescence imaging was carried out on tumor samples obtained before and after therapy and the data was analysed using established methods. The results of the analysis were extrapolated to publicly available datasets (TCGA and CPTAC). In order to identify a surrogate marker, an explainable artificial intelligence method was developed using a transformer-based analytical pipeline for the identification of features in Hematoxylin and Eosin (H&E) images associated with specific biological processes, followed by manual evaluation of highly informative tiles by a pathologist. ResultsMutational profiles were highly modified and the level of genetic intertumoral heterogeneity between patients varied following treatment. Evolutionary analysis indicated eradication of some clones and dominant clonal prevalence of others, supporting the notion of pharmacologically-induced cancer immunoeditin. Post treatment samples showed upregulation of HLA class II genes, activation of differentiation and stemness pathways, and changes in the consensus molecular subtypes. The tumor immune contexture was characterised by increased densities of CD8+ and CD4+ T cells, but reduced T cell-tumor cell interactions (and increased T cell exhaustion. The AI-guided analyses of the H&E images pinpointed extracellular mucin deposits associated with stemness genes, suggesting a surrogate marker for routine pathological evaluation. ConclusionsConventional therapy induces immunoediting and modulates the immune contexture in metastatic CRC patients.

cancer biology↗

bioRxiv2024

Integrated multi-model analysis of intestinal inflammation exposes key molecular features of preclinical and clinical IBD

BackgroundInflammatory bowel disease (IBD) is a chronic inflammatory condition of the intestine with a complex and multifaceted pathogenesis. While various animal models exist to study specific disease mechanisms relevant to human IBD, a comprehensive comparative framework linking these to IBD pathophysiology is lacking. ObjectiveIn our study, we aimed at providing a framework that delineates common and unique features encountered in 13 widely used mouse models comparing them with human IBD to identify translatable pathways in model-cohort pairs. Another aim of our study was to provide an explorable resource for looking up gene and pathway level changes in mouse models assisting in hypothesis testing and minimizing animal burden abiding by the 3R principals. DesignWe employed comparative transcriptomic analyses with curated and a priori statistical correlative methods between mouse models versus established as well as own patient datasets at both bulk and single cell levels. ResultsWe identify IBD-related pathways, ontologies, and cellular processes that are translatable between mouse models and patient cohorts. Moreover, we identify, known and novel IBD-associated subcellular mechanisms and how they are recapitulated in specific mouse models. ConclusionOur findings provide a valuable resource for selecting the most appropriate experimental paradigm to model unique features of IBD pathomechanisms, allowing analysis at the tissue, cellular, and subcellular levels. What is already known on this topicPreclinical modelling of IBD is key to the discovery of pathomechanisms and the evaluation of therapeutic approaches. However, individual models do not recapitulate the complexity of the disease and comprehensive studies comparing modelling paradigms with human IBD are lacking. What this study addsOur study provides a comparative analysis of thirteen commonly used intestinal inflammation models, identifying core-conserved pathways between mouse models and IBD patient cohorts. In addition, our study shows how specific pathways involved in IBD are recapitulated in specific mouse models and introduces a web tool to analyse the models. How this study might affect research, practice or policyBy identifying conserved and discrepant pathways between specific mouse models and IBD patient cohorts, our analysis platform provides an invaluable resource for translational IBD research.

systems biology↗

bioRxiv2023

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion

The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomic data. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through the analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability that explains the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses: activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME, and ultimately to determine its unfolding and fate during immunotherapy with immune checkpoint blockers.

bioinformatics↗

bioRxiv2023

Multimodal profiling of peripheral blood identifies proliferating circulating effector CD4+ T cells as predictors for response to integrin α4β7-blocking therapy in patients with inflammatory bowel disease

Despite the success of biological therapies in inflammatory bowel disease (IBD), patient management remains challenging due to a lack of therapy response predictors. Here we prospectively sampled two cohorts of IBD patient cohorts receiving the anti-integrin 4{beta}7 antibody vedolizumab. Samples were subjected to mass cytometry, single-cell RNA sequencing, single-cell V(D)J sequencing, serum proteomics, and multidimensional flow cytometry to comprehensively assess vedolizumab-induced immunological changes in the peripheral blood and their potential associations with treatment response. Vedolizumab induced changes in the abundance of both circulating innate and adaptive immune cell compartments and modified the T cell receptor diversity of circulating gut-homing CD4+ memory T cells. Through integration of multimodal parameters and machine learning, we identify that pretreatment activated proliferating CD4+ memory T cell abundance is associated with treatment failure, independent of clinical variables, thereby providing a reliable predictive classifier with significant implications for the personalized management of IBD patients.

immunology↗

bioRxiv2023

Comparative Analysis of Whole Transcriptome Single-Cell Sequencing Technologies in Complex Tissues

The development of single-cell omics tools has enabled scientists to study the tumor microenvironment (TME) in unprecedented detail. However, each of the different techniques may have its unique strengths and limitations. Here we directly compared two commercially available high-throughput single-cell RNA sequencing (scRNA-seq) technologies - droplet-based 10X Chromium vs. microwell-based BD Rhapsody - using paired samples from patients with localized prostate cancer (PCa) undergoing a radical prostatectomy. Although high technical consistency was observed in unraveling the whole transcriptome, the relative abundance of cell populations differed. Cells with low-mRNA content such as T cells were underrepresented in the droplet-based system, at least partly due to lower RNA capture rates. In contrast, microwell based scRNA-seq recovered less cells of epithelial origin. Moreover, we discovered platform-dependent variabilities in mRNA quantification and cell-type marker annotation. Overall, our study provides important information for selection of the appropriate scRNA-seq platform and for the interpretation of published results. SYNOPSISO_LIComparison of scRNA-seq protocols uncovers disparities in RNA-to-library conversion C_LIO_LIMicrowell-based scRNA-seq technology excels in capturing low-mRNA content cells C_LIO_LIBiased transcriptomes due to gene specific RNA detection efficacies by both platforms C_LIO_LIThe study guides in informed scRNA-seq platform selection and data interpretation C_LI

cancer biology↗

bioRxiv2023

13C tracer analysis reveals the landscape of metabolic checkpoints in human CD8+ T cell differentiation

Naive T cells remain in an actively maintained state of quiescence until activation by antigenic signals, upon which they start proliferation and generation of effector cells to initiate a functional immune response. Metabolic reprogramming is essential to meet the biosynthetic demands of the differentiation process, and failure to do so can promote the development of hypofunctional exhausted T cells. Here we used 13C metabolomics and transcriptomics to study the metabolic dynamics of CD8+ T cells in their complete course of differentiation from naive over stem-like memory to effector cells. The quiescence of naive T cells was evident in a profound suppression of glucose oxidation and a decreased expression of ENO1, downstream of which no glycolytic flux was detectable. Moreover, TCA cycle activity was low in naive T cells and associated with a downregulation of SDH subunits. Upon stimulation and exit from quiescence, the initiation of cell growth and proliferation was accompanied by differential expression of T cell regulatory genes and metabolic reprogramming towards aerobic glycolysis with high rates of nutrient uptake, respiration and lactate production. High flux in anabolic pathways imposed a strain on NADH homeostasis, which coincided with engagement of the proline cycle for mitochondrial redox shuttling. With acquisition of effector functions, cells increasingly relied on glycolysis as opposed to oxidative phosphorylation, which paradoxically was not linked to changes in mitochondrial abundance. We further investigated the metabolic phenotype of exhausted T cells, finding that decreased effector function concurred with a reduction in mitochondrial metabolism, glycolysis and amino acid import, and an upregulation of suppressive and quiescence-associated genes, including TXNIP and KLF2. Thus, these results identify multiple features critical for the metabolic reprogramming that supports quiescence, proliferation and effector function of CD8+ T cells during differentiation. Further, an impairment of the same processes in exhaustion suggests that targeting these control points may be useful for both modulation of differentiation and prevention of exhaustion.

immunology↗

bioRxiv2022

Functional precision profiling reveals non-mutational rewiring of kinase signaling networks in colorectal cancer

BackgroundDespite major advances in the development of targeted therapies, precision (immuno)oncology approaches for patients with colorectal cancer continue to lag behind other solid cancers. Functional precision oncology - a strategy that is based on perturbing primary tumor cells from cancer patients with drugs - could provide an alternate road forward to personalize treatment. MethodsWe extend here the functional precision oncology paradigm to measuring phosphoproteome landscapes using patient-derived organoids (PDOs). We first employed steady-state multi-omics (exome sequencing, RNA sequencing, and proteomics) and single-cell characterization of the PDOs. The PDOs were then perturbed with kinase inhibitors (MEKi, PI3Ki, mTORi, TBKi, BRAFi, and TAKi), and large-scale phosphoproteomics profiling using data-independent acquisition was carried out. Further, we used imaging mass-cytometry-based single-cell proteomic profiling of the primary tumors to characterize cellular composition of the tumor-microenvironment (TME) and to quantify heterocellular signaling crosstalk. ResultsWe show that kinase inhibitors induce profound off-target effects resulting in a crosstalk with oncogenic and immune-related pathways. Reconstruction of the topologies of the kinase networks revealed that the patient-specific rewiring of the central EGFR-RAS-MAPK network is unaffected by mutations. Moreover, we show non-genetic heterogeneity of the PDOs and patient- and inhibitor-specific upregulation of stemness and differentiation genes by kinase inhibitors. We complemented our functional profiling by spatial proteomics profiling of the primary tumors using imaging mass cytometry. We quantify spatial heterocellular crosstalk and tumor-immune cell interactions, showing an avoidance of PD1+ immune cells and PD-L1+ tumor cells. ConclusionsCollectively, we provide a multi-modal framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno)-oncology in colorectal cancer.

cancer biology↗

bioRxiv2022

High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is characterized by molecular heterogeneity with diverse immune cell infiltration patterns, which has been linked to both, therapy sensitivity and resistance. However, full understanding of how immune cell phenotypes vary across different patient and tumor subgroups is lacking. Here, we dissect the NSCLC tumor microenvironment at high resolution by integrating 1,212,463 single-cells from 538 samples and 309 patients across 29 datasets, including our own dataset capturing cells with low mRNA content. Based on the cellular composition we stratified patients into immune deserted, B cell, T cell, and myeloid cell subtypes. Using bulk samples with genomic and clinical information, we identified specific cellular components associated with tumor histology and genotypes. Analysis of cells with low mRNA content uncovered distinct subpopulations of tissue-resident neutrophils (TRNs) that acquire new functional properties in the tissue microenvironment, providing evidence for the plasticity of TRNs. TRN-derived gene signature was associated with anti-PD-L1 treatment failure in a large NSCLC cohort. In briefSalcher, Sturm, Horvath et al. integrate single-cell datasets to generate the largest transcriptome atlas in NSCLC, refining patient stratification based on tumor immune phenotypes, and revealing associations of histological subtypes and genotypes with specific cellular composition patterns. Coverage of cells with low mRNA content by single-cell sequencing identifies distinct tissue-resident neutrophil subpopulations, which acquire new properties within the tumor microenvironment. Gene signature from tissue-resident neutrophils is associated with immune checkpoint inhibitor treatment failure. The integrated atlas is publicly available online (https://luca.icbi.at), allowing the dissection of tumor-immune cell interactions in NSCLC. HighlightsO_LIHigh-resolution single-cell atlas of the tumor microenvironment (TME) in NSCLC. C_LIO_LIHistological tumor subtypes and driver genes imprint specific cellular TME patterns. C_LIO_LIscRNA-seq of cells with low transcript count identifies distinct tissue-resident neutrophil (TRN) subpopulations and non-canonical functional properties in the TME niche. C_LIO_LITRN gene signature identifies patients who are refractory to treatment with PD-L1 inhibitors. C_LI O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/491204v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1050b6aorg.highwire.dtl.DTLVardef@3088c8org.highwire.dtl.DTLVardef@6408b8org.highwire.dtl.DTLVardef@1788c22_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data

SummaryAdvances in single-cell technologies have enabled the investigation of T cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses in cancer, but also in infectious diseases like COVID-19. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T cell receptors. Here we propose Scirpy, a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data. Availability and implementationScirpy source code and documentation are available at https://github.com/icbi-lab/scirpy.

bioinformatics↗

bioRxiv2017

quanTIseq: quantifying immune contexture of human tumors

The immune contexture has a prognostic value in several cancers and the study of its pharmacological modulation could identify drugs acting synergistically with immune checkpoint blockers. However, the quantification of the immune contexture is hampered by the lack of simple and efficient methods. We developed quanTIseq, a deconvolution method that quantifies the densities of ten immune cell types from bulk RNA sequencing data and tissue imaging data. We performed extensive validation using simulated data, flow cytometry data, and immunohistochemistry data from three cancer cohorts.\n\nAnalysis of 8,000 samples showed that the activation of the CXCR3/CXCL9 axis, rather than the mutational load is associated with cytotoxic T cell infiltration. We also show the prognostic value of deconvolution-based immunoscore and T cell/B cell score in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture, and we suggest that it might have predictive value for immunotherapy.

bioinformatics↗