Transcriptome-wide Gene Research Articles

FB5P-seq-mAbs: monoclonal antibody production from FB5P-seq libraries for integrative single-cell analysis of B cells

Parallel analysis of phenotype, transcriptome and antigen receptor sequence in single B cells is a useful method for tracking B cell activation and maturation during immune responses. However, in most cases, the specificity and affinity of the B cell antigen receptor cannot be inferred from its sequence. Antibody cloning and expression from single B cells is then required for functional assays. Here we propose a method that integrates FACS-based 5’-end single-cell RNA sequencing (FB5P-seq) and monoclonal antibody cloning for integrative analysis of single B cells. Starting from a cell suspension, single B cells are FACS-sorted into 96-well plates for reverse transcription, cDNA barcoding and amplification. A fraction of the single-cell cDNA is used for preparing 5’-end RNA-seq libraries that are sequenced for retrieving transcriptome-wide gene expression and paired BCR sequences. The archived cDNA of selected cells of interest is used as input for cloning heavy and light chain variable regions into antibody expression plasmid vectors. The corresponding monoclonal antibodies are produced by transient transfection of a eukaryotic producing cell line and purified for functional assays. We provide detailed step-by-step instructions and describe results obtained on ovalbumin-specific murine germinal center B cells after immunization. Our method is robust, flexible, cost-effective, and applicable to different B cell types and species. We anticipate it will be useful for mapping antigen specificity and affinity of rare B cell subsets characterized by defined gene expression and/or antigen receptor sequence.

EPCO-47. SEX-BIASED BRD4 ACTIVITY DRIVES TUMORIGENESIS IN GLIOBLASTOMA

Abstract Consistent sex differences in incidence and outcome have been reported in cancers including brain tumors. Glioblastoma (GBM), the most common and aggressive primary brain tumor, occurs with higher incidence and shorter survival in males compared to females. Brd4 is essential for regulating transcriptome-wide gene expression and specifying cell identity. Using an isogenic murine GBM model, we have reported correlated transcriptome-wide sex differences in gene expression, Brd4-bound enhancer usage, and Brd4 localization to oncogenic and tumor suppressor transcription factors binding sites in male and female GBM cells, respectively. Sex-biased gene expression patterns were also evident in human glioblastoma. Inhibiting Brd4 function abrogates sex differences in these transcriptional states and concomitant differences in tumorigenic phenotype. Thus, sex-biased Brd4 activity drives sex differences in GBM rendering males and females differentially sensitive to BET inhibitors. These data indicate that Brd4 can exhibit dual functions as an oncogene or tumor suppressor, dependent upon cellular sex. To better understand how to globally target Brd4, we interrogated the role played by master transcriptional Brd4 regulators in coordinating this dual phenotype in GBM. Motif-based analysis revealed that Brd4 co-localized with oncogenes such as Bach1, and Klf5 at male-biased enhancers whereas female-biased enhancers were co-occupied with tumor suppressors, such as Smad4 and p53. Knockdown of Bach1 decreased clonogenic frequency in males and females. Conversely, knockdown of Smad4 increased proliferation and clonogenicity in males, further inducing the male tumorigenic phenotype, while no change was observed in females. These results indicate that Smad4 might be necessary but not sufficient to provide females with resistance to transformation. Ongoing epitranscriptomics investigating Brd4 re-localization and enhancer usage in knockdown cells will increase our understanding of Brd4 mechanism in GBM. Targeting sex-biased Brd4 function will identify novel combinatorial sex-specific therapeutics for brain tumors and could have immediate impact on the clinical treatment of GBM patients.

FICTURE: scalable segmentation-free analysis of submicron-resolution spatial transcriptomics.

Spatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. However, analysis of high-resolution ST is often challenged by complex tissue structure, where existing cell segmentation methods struggle due to the irregular cell sizes and shapes, and by the absence of segmentation-free methods scalable to whole-transcriptome analysis. Here we present FICTURE (Factor Inference of Cartographic Transcriptome at Ultra-high REsolution), a segmentation-free spatial factorization method that can handle transcriptome-wide data labeled with billions of submicron-resolution spatial coordinates and is compatible with both sequencing-based and imaging-based ST data. FICTURE uses the multilayered Dirichlet model for stochastic variational inference of pixel-level spatial factors, and is orders of magnitude more efficient than existing methods. FICTURE reveals the microscopic ST architecture for challenging tissues, such as vascular, fibrotic, muscular and lipid-laden areas in real data where previous methods failed. FICTURE's cross-platform generality, scalability and precision make it a powerful tool for exploring high-resolution ST.

Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis.

Single-cell RNA sequencing (scRNA-seq) offers unprecedented insights into transcriptome-wide gene expression at the single-cell level. Cell clustering has been long established in the analysis of scRNA-seq data to identify the groups of cells with similar expression profiles. However, cell clustering is technically challenging, as raw scRNA-seq data have various analytical issues, including high dimensionality and dropout values. Existing research has developed deep learning models, such as graph machine learning models and contrastive learning-based models, for cell clustering using scRNA-seq data and has summarized the unsupervised learning of cell clustering into a human-interpretable format. While advances in cell clustering have been profound, we are no closer to finding a simple yet effective framework for learning high-quality representations necessary for robust clustering. In this study, we propose scSimGCL, a novel framework based on the graph contrastive learning paradigm for self-supervised pretraining of graph neural networks. This framework facilitates the generation of high-quality representations crucial for cell clustering. Our scSimGCL incorporates cell-cell graph structure and contrastive learning to enhance the performance of cell clustering. Extensive experimental results on simulated and real scRNA-seq datasets suggest the superiority of the proposed scSimGCL. Moreover, clustering assignment analysis confirms the general applicability of scSimGCL, including state-of-the-art clustering algorithms. Further, ablation study and hyperparameter analysis suggest the efficacy of our network architecture with the robustness of decisions in the self-supervised learning setting. The proposed scSimGCL can serve as a robust framework for practitioners developing tools for cell clustering. The source code of scSimGCL is publicly available at https://github.com/zhangzh1328/scSimGCL.

Changes in growth, lanthanide binding, and gene expression in Pseudomonas alloputida KT2440 in response to light and heavy lanthanides.

Pseudomonas alloputida KT2440 is a ubiquitous, soil-dwelling bacterium that metabolizes recalcitrant and volatile carbon sources. The latter is utilized by two redundant, Ca- and lanthanide (Ln)-dependent, pyrroloquinoline quinone-dependent alcohol dehydrogenases (PQQ ADH), PedE and PedH, whose expression is regulated by Ln availability. P. alloputida KT2440 is the best-studied non-methylotroph in the context of Ln-utilization. Combined with microfluidic cultivation and single-cell elemental analysis, we studied the impact of light and heavy Ln on transcriptome-wide gene expression when growing P. alloputida KT2440 with 2-phenylethanol as the carbon and energy source. Light Ln (La, Ce, and Nd) and a mixture of light and heavy Ln (La, Ce, Nd, Dy, Ho, Er, and Yb) had a positive effect on growth, whereas supplementation with heavy Ln (Dy, Ho, Er, and Yb) exerted fitness costs. These were likely a consequence of mismetallation and non-utilizable Ln interfering with Ln sensing and signaling. The measured amounts of cell-associated Ln varied between elements. Gene expression analysis suggested that the Ln sensing and signaling machinery, the two-component system PedS2R2 and PedH, responds differently to (non-)utilizable Ln. We expanded our understanding of the lanthanide (Ln) switch in P. alloputida KT2440, demonstrating that it adjusts the levels of pedE and pedH transcripts based on the availability of Ln. We propose that the usability of Ln influences the bacterium's response to different Ln elements.IMPORTANCEThe Ln switch, the inverse regulation of Ca- and Ln-dependent PQQ ADH in response to Ln availability in organisms featuring both, is central to our understanding of Ln utilization. Although the preference of bacteria for light Ln is well known, the effect of different Ln, light and heavy, on growth and gene expression has rarely been studied. We provide evidence for a fine-tuning mechanism of Ca- and Ln-dependent PQQ ADH in P. alloputida KT2440 on the transcriptome level. The response to (non-)utilizable Ln differs depending on the element. Ln commonly co-occur in nature. Our findings underline that Ln-utilizing microbes must be able to discriminate between Ln to use them effectively. Considering the prevalence of Ln-dependent proteins in many microbial taxa, more work addressing Ln sensing and signaling is needed. Ln availability likely necessitates different adaptations regarding Ln utilization.

Conserved 5-methyluridine tRNA modification modulates ribosome translocation

While the centrality of posttranscriptional modifications to RNA biology has long been acknowledged, the function of the vast majority of modified sites remains to be discovered. Illustrative of this, there is not yet a discrete biological role assigned for one of the most highly conserved modifications, 5-methyluridine at position 54 in tRNAs (m5U54). Here, we uncover contributions of m5U54 to both tRNA maturation and protein synthesis. Our mass spectrometry analyses demonstrate that cells lacking the enzyme that installs m5U in the T-loop (TrmA in Escherichia coli, Trm2 in Saccharomyces cerevisiae) exhibit altered tRNA modification patterns. Furthermore, m5U54-deficient tRNAs are desensitized to small molecules that prevent translocation in vitro. This finding is consistent with our observations that relative to wild-type cells, trm2Δ cell growth and transcriptome-wide gene expression are less perturbed by translocation inhibitors. Together our data suggest a model in which m5U54 acts as an important modulator of tRNA maturation and translocation of the ribosome during protein synthesis.

In vivo vitamin D targets reveal the upregulation of focal adhesion-related genes in primary immune cells of healthy individuals

Vitamin D modulates innate and adaptive immunity, the molecular mechanisms of which we aim to understand under human in vivo conditions. Therefore, we designed the study VitDHiD (NCT03537027) as a human investigation, in which 25 healthy individuals were supplemented with a single vitamin D3 bolus (80,000 IU). Transcriptome-wide differential gene expression analysis of peripheral blood mononuclear cells (PBMCs), which were isolated directly before and 24 h after supplementation, identified 452 genes significantly (FDR < 0.05) responding to vitamin D. In vitro studies using PBMCs from the same individuals confirmed 138 of these genes as targets of 1α,25-dihydroxyvitamin D3. A subset of the 91 most regulated in vivo vitamin D target genes indicated focal adhesion as the major pathway being upregulated by vitamin D3 supplementation of healthy individuals. Differences in the individual-specific responsiveness of in vivo vitamin D target genes in relation to the increase of the person’s vitamin D status allowed a segregation of the VitDHiD participants into 9 high, 12 mid and 4 low responders. The expression profile of nearly 600 genes elucidate the difference between high and low vitamin D responders, the most prominent of which is the HLA-C (major histocompatibility complex, class I, C) gene.

BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data.

Navigating the complex landscape of high-dimensional omics data with machine learning models presents a significant challenge. The integration of biological domain knowledge into these models has shown promise in creating more meaningful stratifications of predictor variables, leading to algorithms that are both more accurate and generalizable. However, the wider availability of machine learning tools capable of incorporating such biological knowledge remains limited. Addressing this gap, we introduce BioM2, a novel R package designed for biologically informed multistage machine learning. BioM2 uniquely leverages biological information to effectively stratify and aggregate high-dimensional biological data in the context of machine learning. Demonstrating its utility with genome-wide DNA methylation and transcriptome-wide gene expression data, BioM2 has shown to enhance predictive performance, surpassing traditional machine learning models that operate without the integration of biological knowledge. A key feature of BioM2 is its ability to rank predictor variables within biological categories, specifically Gene Ontology pathways. This functionality not only aids in the interpretability of the results but also enables a subsequent modular network analysis of these variables, shedding light on the intricate systems-level biology underpinning the predictive outcome. We have proposed a biologically informed multistage machine learning framework termed BioM2 for phenotype prediction based on omics data. BioM2 has been incorporated into the BioM2 CRAN package (https://cran.r-project.org/web/packages/BioM2/index.html).

Transcriptomic signature of CD4-expressing T-cell abundance developed in healthy peripheral blood predicts strong anti-retroviral therapeutic response in HIV-1: A retrospective and proof-of-concept study

CD4-expressing T-cells (CD4Ts) play a crucial role in maintaining the normal functioning of the mammalian immune system and overall systemic health. Diseased individuals, such as those infected with the human immunodeficiency virus type I (HIV-1), experience progressive and eventual depletion of CD4T leading to uncurable conditions and ultimate death if left untreated. Although much is known about the role of CD4T-mediated immunity, the understanding of CD4T-related transcriptomic patterns remains incomplete. This proof-of-concept study aims to identify a transcriptome-wide gene signature for CD4T abundance by Least Absolute Shrinkage and Selection Operator (LASSO) regression modeling in 340 healthy peripheral blood samples. The optimized LASSO model demonstrated computational robustness (tenfold average Pearson&amp;rsquo;s r = 0.89) and biological relevance evidenced by four significant Gene Ontology terms (all odds ratio [OR] &amp;ge; 4.5 and false discovery rate &amp;le;0.05). Subsequently, in an independent cohort with 24 HIV-1-infected men who received anti-retroviral therapies, there is a significant, positive association between the gene signature and a strong anti-retroviral response before (OR = 13.6, P &lt; 0.05) and after adjusting for subject age, sex, and race (OR = 14.4, P &lt; 0.05). Taken together, the gene expression pattern associated with CD4T abundance is predictable, generalizable, and biologically relevant, shedding new light on the importance of CD4T abundance.

GeneSurfer Enables Transcriptome-wide Exploration and Functional Annotation of Gene Co-expression Modules in 3D Spatial Transcriptomics Data.

Gene co-expression provides crucial insights into biological functions, however, there is a lack of exploratory analysis tools for localized gene co-expression in large-scale datasets. We present GeneSurfer, an interactive interface designed to explore localized transcriptome-wide gene co-expression patterns in the 3D spatial domain. Key features of GeneSurfer include transcriptome-wide gene filtering and gene clustering based on spatial local co-expression within transcriptomically similar cells, multi-slice 3D rendering of average expression of gene clusters, and on-the-fly Gene Ontology term annotation of co-expressed gene sets. Additionally, GeneSurfer offers multiple linked views for investigating individual genes or gene co-expression in the spatial domain at each exploration stage. Demonstrating its utility with both spatial transcriptomics and single-cell RNA sequencing data from the Allen Brain Cell Atlas, GeneSurfer effectively identifies and annotates localized transcriptome-wide co-expression, providing biological insights and facilitating hypothesis generation and validation.

Transcriptome analysis of avian livers reveals different molecular changes to three urban pollutants: Soot, artificial light at night and noise

Identifying key molecular pathways and genes involved in the response to urban pollutants is an important step in furthering our understanding of the impact of urbanisation on wildlife. The expansion of urban habitats and the associated human-introduced environmental changes are considered a global threat to the health and persistence of humans and wildlife. The present study experimentally investigates how short-term exposure to three urban-related pollutants -soot, artificial light at night (ALAN) and traffic noise-affects transcriptome-wide gene expression in livers from captive female zebra finches (Taeniopygia guttata). Compared to unexposed controls, 17, 52, and 28 genes were differentially expressed in soot, ALAN and noise-exposed birds, respectively. In soot-exposed birds, the enriched gene ontology (GO) terms were associated with a suppressed immune system such as interferon regulating genes (IRGs) and responses to external stimuli. For ALAN-exposed birds, enriched GO terms were instead based on downregulated genes associated with detoxification, redox, hormonal-, and metabolic processes. Noise exposure resulted in downregulation of genes associated with the GO terms: cellular responses to substances, catabolic and cytokine responses. Among the individually differentially expressed genes (DEGs), soot led to an increased expression of genes related to tumour progression. Likewise, ALAN revealed an upregulation of multiple genes linked to different cancer types. Both sensory pollutants (ALAN and noise) led to increased expression of genes linked to neuronal function. Interestingly, noise caused upregulation of genes associated with serotonin regulation and function (SLC6A4 and HTR7), which previous studies have shown to be under selection in urban birds. These outcomes indicate that short-term exposure to the three urban pollutants perturbate the liver transcriptome, but most often in different ways, which highlights future studies of multiple-stress exposure and their interactive effects, along with their long-term impacts for urban-dwelling wildlife.

Association of early menarche with breast tumor molecular features and recurrence

BackgroundEarly menarche is an established risk factor for breast cancer but its molecular contribution to tumor biology and prognosis remains unclear.MethodsWe profiled transcriptome-wide gene expression in breast tumors (N = 846) and tumor-adjacent normal tissues (N = 666) from women in the Nurses’ Health Studies (NHS) to investigate whether early menarche (age < 12) is associated with tumor molecular and prognostic features in women with breast cancer. Multivariable linear regression and pathway analyses using competitive gene set enrichment analysis were conducted in both tumor and adjacent-normal tissue and externally validated in TCGA (N = 116). Subgroup analyses stratified on ER-status based on the tumor were also performed. PAM50 signatures were used for tumor molecular subtyping and to generate proliferation and risk of recurrence scores. We created a gene expression score using LASSO regression to capture early menarche based on 28 genes from FDR-significant pathways in breast tumor tissue in NHS and tested its association with 10-year disease-free survival in both NHS (N = 836) and METABRIC (N = 952).ResultsEarly menarche was significantly associated with 369 individual genes in adjacent-normal tissues implicated in extracellular matrix, cell adhesion, and invasion (FDR ≤ 0.1). Early menarche was associated with upregulation of cancer hallmark pathways (18 significant pathways in tumor, 23 in tumor-adjacent normal, FDR ≤ 0.1) related to proliferation (e.g. Myc, PI3K/AKT/mTOR, cell cycle), oxidative stress (e.g. oxidative phosphorylation, unfolded protein response), and inflammation (e.g. pro-inflammatory cytokines IFNα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} and IFNγ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma$$\\end{document}). Replication in TCGA confirmed these trends. Early menarche was associated with significantly higher PAM50 proliferation scores (β = 0.082 [0.02–0.14]), odds of aggressive molecular tumor subtypes (basal-like, OR = 1.84 [1.18–2.85] and HER2-enriched, OR = 2.32 [1.46–3.69]), and PAM50 risk of recurrence score (β = 4.81 [1.71–7.92]). Our NHS-derived early menarche gene expression signature was significantly associated with worse 10-year disease-free survival in METABRIC (N = 952, HR = 1.58 [1.10–2.25]).ConclusionsEarly menarche is associated with more aggressive molecular tumor characteristics and its gene expression signature within tumors is associated with worse 10-year disease-free survival among women with breast cancer. As the age of onset of menarche continues to decline, understanding its relationship to breast tumor characteristics and prognosis may lead to novel secondary prevention strategies.

IL-1β + TGF-β2 dual-licensed mesenchymal stem cells have reduced major histocompatibility class I expression and positively modulate tenocyte migration, metabolism, and gene expression.

The study objectives were to 1) determine the mesenchymal stem cell (MSC) surface expression of major histocompatibility complex (MHC) class I and transcriptome-wide gene expression changes following IL-1β + TGF-β2 dual licensing and 2) evaluate if IL-1β + TGF-β2 dual-licensed MSCs had a greater ability to positively modulate tenocyte function compared to naive MSCs. Equine bone marrow-derived MSCs from 6 donors and equine superficial digital flexor tenocytes from 3 donors. Experiments were performed in vitro. Flow cytometry and bulk RNA sequencing were utilized to determine naive and dual-licensed MSC phenotype and transcriptome-wide changes in gene expression. Conditioned media were generated from MSCs and utilized in tenocyte cell culture assays as a method to determine the effect of MSC paracrine factors on tenocyte function. Dual-licensed MSCs have a reduced expression of MHC class I and exhibit enrichment in functional pathways associated with the extracellular matrix, cell signaling, and tissue development. Additionally, dual-licensed MSC-conditioned media significantly improved in vitro tenocyte migration and metabolism to a greater degree than naive MSC-conditioned media. In tenocytes exposed to IL-1β, dual-licensed conditioned media also positively modulated tenocyte gene expression. Our data indicate that conditioned media containing paracrine factors secreted from dual-licensed MSCs significantly modulates in vitro tenocyte function, which may confer benefits in vivo to healing tendons following injury. Additionally, due to reduced MHC class I expression in dual-licensed MSCs, this technique may also provide an avenue to provide an effective "off-the-shelf" allogenic source of MSCs.

Differentially co-expressed myofibre transcripts associated with abnormal myofibre proportion in chronic obstructive pulmonary disease.

Skeletal muscle dysfunction is a common extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD). Alterations in skeletal muscle myosin heavy chain expression, with reduced type I and increased type II myosin heavy chain expression, are associated with COPD severity when studied in largely male cohorts. The objectives of this study were (1) to define an abnormal myofibre proportion phenotype in both males and females with COPD and (2) to identify transcripts and transcriptional networks associated with abnormal myofibre proportion in COPD. Forty-six participants with COPD were assessed for body composition, strength, endurance and pulmonary function. Skeletal muscle biopsies from the vastus lateralis were assayed for fibre-type distribution and cross-sectional area via immunofluorescence microscopy and RNA-sequenced to generate transcriptome-wide gene expression data. Sex-stratified k-means clustering of type I and IIx/IIax fibre proportions was used to define abnormal myofibre proportion in participants with COPD and contrasted with previously defined criteria. Single transcripts and weighted co-expression network analysis modules were tested for correlation with the abnormal myofibre proportion phenotype. Abnormal myofibre proportion was defined in males with COPD (n=29) as <18% type I and/or >22% type IIx/IIax fibres and in females with COPD (n=17) as <36% type I and/or >12% type IIx/IIax fibres. Half of the participants with COPD were classified as having an abnormal myofibre proportion. Participants with COPD and an abnormal myofibre proportion had lower median handgrip strength (26.1 vs. 34.0kg, P=0.022), 6-min walk distance (300 vs. 353m, P=0.039) and forced expiratory volume in 1s-to-forced vital capacity ratio (0.42 vs. 0.48, P=0.041) compared with participants with COPD and normal myofibre proportions. Twenty-nine transcripts were associated with abnormal myofibre proportions in participants with COPD, with the upregulated NEB, TPM1 and TPM2 genes having the largest fold differences. Co-expression network analysis revealed that two transcript modules were significantly positively associated with the presence of abnormal myofibre proportions. One of these co-expression modules contained genes classically associated with muscle atrophy, as well as transcripts associated with both type I and type II myofibres, and was enriched for genetic loci associated with bone mineral density. Our findings indicate that there are significant transcriptional alterations associated with abnormal myofibre proportions in participants with COPD. Transcripts canonically associated with both type I and type IIa fibres were enriched in a co-expression network associated with abnormal myofibre proportion, suggesting altered transcriptional regulation across multiple fibre types.

Abstract 6235: Clinical and phenotypic consequences of HLA mediated antigen presentation deficiency in pancreatic adenocarcinoma at bulk and single-cell resolution

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal neoplasm of the pancreas characterized by a low survival rate and limited treatment options. Despite the success of immunotherapy in various cancer types, its efficacy in PDAC remains low. The underlying reasons for this discrepancy are not fully understood, despite PDAC exhibiting a moderate mutation burden. One possible determinant could be the loss of heterozygosity (LOH) at the human leukocyte antigen (HLA) loci, resulting in compromised antigen presentation. In this work, we aim to identify and validate HLA LOH events in two independent cohorts to gain insights into both their prevalence and clinical and phenotypic impact on PDAC. Methods: We applied LOHHLA, a specialized pipeline to identify HLA LOH events from paired whole genome sequencing to two independent cohorts comprising over 650 patients. We contextualized these results with the paired transcriptome-wide gene expression data and immunohistochemistry stains. In addition, we developed a machine learning classifier to predict HLA LOH from transcriptomic data. We transfer this classifier to single cell RNA sequencing data to identify the impact of (subclonal) HLA LOH on the tumor microenvironment. Results: HLA LOH events occur in approximately 30% of PDAC patients, with about 50% of these deletions being focal deletions. We find evidence that focal but not non-focal LOH is a driver of immune escape. Overall, we find that HLA LOH events are early genetic alterations and observe a significant association between HLA LOH and the Basal PDAC expression subtype. In addition, we find that HLA expression is the most important determinant of lymphocyte infiltration followed by an intact HLA locus. Moreover, our transcriptomic classifier allowed us to accurately identify HLA LOH events from RNA sequencing data, which we successfully validated in an independent cohort. Finally, we applied this classifier to single cell sequencing data and identified phenotypic differences in multiple compartments of the tumor microenvironment between samples with intact HLA and HLA LOH. Conclusions: In conclusion, our study provides the most in depth characterization of the consequences of altered antigen presentation in PDAC to date. We have demonstrated that HLA LOH occurs in a substantial proportion of patients. Overall, these findings contribute to a better understanding of the immune landscape in PDAC and may have implications for the development of immunotherapeutic strategies tailored to this challenging cancer type. Citation Format: Michael J. Geuenich, Barbara Gruenwald, Grainne O'Kane, Chengxin Yu, Tan Tiak Ju, Amy Zhang, Oumaima Hamza, Gun Ho Jang, Faiyaz Notta, Steven Gallinger, Kieran R. Campbell. Clinical and phenotypic consequences of HLA mediated antigen presentation deficiency in pancreatic adenocarcinoma at bulk and single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6235.

Transcriptome-wide gene expression outlier analysis pinpoints therapeutic vulnerabilities in colorectal cancer.

Multiple strategies are continuously being explored to expand the drug target repertoire in solid tumors. We devised a novel computational workflow for transcriptome-wide gene expression outlier analysis that allows the systematic identification of both overexpression and underexpression events in cancer cells. Here, it was applied to expression values obtained through RNA sequencing in 226 colorectal cancer (CRC) cell lines that were also characterized by whole-exome sequencing and microarray-based DNA methylation profiling. We found cell models displaying an abnormally high or low expression level for 3533 and 965 genes, respectively. Gene expression abnormalities that have been previously associated with clinically relevant features of CRC cell lines were confirmed. Moreover, by integrating multi-omics data, we identified both genetic and epigenetic alternations underlying outlier expression values. Importantly, our atlas of CRC gene expression outliers can guide the discovery of novel drug targets and biomarkers. As a proof of concept, we found that CRC cell lines lacking expression of the MTAP gene are sensitive to treatment with a PRMT5-MTA inhibitor (MRTX1719). Finally, other tumor types may also benefit from this approach.

Gene Signature of Regulatory T Cells Isolated from Children with Selective IgA Deficiency and Common Variable Immunodeficiency.

Selective IgA deficiency (SIgAD) is the most common form and common variable immunodeficiency (CVID) is the most symptomatic form of predominant antibody deficiency. Despite differences in the clinical picture, a similar genetic background is suggested. A common feature of both disorders is the occurrence of autoimmune conditions. Regulatory T cells (Tregs) are the major immune cell type that maintains autoimmune tolerance. As the different types of abnormalities of Treg cells have been associated with autoimmune disorders in primary immunodeficiency (PID) patients, in our study we aimed to analyze the gene expression profiles of Treg cells in CVID and SIgAD patients compared to age-matched healthy controls. The transcriptome-wide gene profiling was performed by microarray technology. As a result, we analyzed and visualized gene expression patterns of isolated population of Treg cells. We showed the differences at the gene level between patients with and without autoimmunizations. Our findings suggest that the gene signatures of Treg cells isolated from SIgAD and CVID patients differ from age-matched healthy controls and from each other, presenting transcriptional profiles enriched in innate immune or Th response, respectively. The occurrence of autoimmunity in both types of PID is associated with down-regulation of class I IFNs signaling pathways. In summary, our findings improve our understanding of Treg dysfunctions in patients with common PIDs and associated autoimmunity.

Tissue factor: A link between metastatic colorectal cancer and thrombosis in patients in the CALGB (Alliance)/SWOG 80405 trial.

198 Background: Tissue factor (TF) is a transmembrane protein that plays a crucial role in thrombosis. TF expression is elevated in various types of cancer, including colorectal cancer (CRC) and is associated with more aggressive disease and poor prognosis. The aim of this study was to evaluate TF expression in patients (pts) with metastatic CRC (mCRC) enrolled in the CALGB (Alliance)/SWOG 80405 clinical trial. Understanding the relationship between TF expression and mCRC will provide insights into the role of coagulation in the progression and prognosis of this disease and may have therapeutic implications, particularly in the setting of recent approval of a TF antibody drug conjugate for metastatic cervical cancer and other agents in the pipeline. Methods: 433 pts with mCRC treated with bevacizumab (Bev, n = 226) or cetuximab (Cet, n =207) in combination with first-line chemotherapy in CALGB/SWOG 80405 were included in the analysis. TF RNA was isolated from FFPE tumor samples and sequenced on the HiSeq 2500 (Illumina). Overall survival (OS) and progression-free survival (PFS) were compared between groups of pts categorized by tertiles of TF expression: high (H), medium (M) and low (L). Sensitivity analyses were conducted after stratifying by side. Logrank P-values describe differences without adjustment for pt characteristics. Transcriptome-wide gene association analysis was performed using linear regression, adjusting for age, sex, ethnicity, ECOG PS, location, number of metastases, KRAS, MSI status, treatment with FOLFOX or FOLFIRI, and the first 3 principal components from the RNA-seq data. Gene Ontology enrichment analysis was conducted with the top 100 TF-associated genes. Results: TF expression is associated with genes related to maintenance of epithelium, cell adhesion, and migration, immunoregulatory cytokine production, and metabolic, HER2, and MAP/Kinase pathways. TF-L showed significantly longer median (m)PFS (13.4 vs 10.1 vs 9.2 months (mo), p=0.0022) and mOS (35.4 vs 30.9 vs 25.2, p=0.0051) in the entire cohort. In Cet treated pts, TF-L had significantly longer mOS (41.3 vs 29.9 vs 26.1 mo, p=0.0013). In pts treated with FOLFOX, TF-L had significantly longer PFS (13.2 vs 10.9 vs 8.2 mo, p=0.0014) and OS (33.4 vs 30.9 vs 22.4 mo, p=0.0044). Pts with liver metastases and TF-H had worse PFS (9.2 vs 9.9 vs 13.5 mo, p=0.006) and OS (23.6 vs 29.9 vs 35.1 mo, p=0.016). Conclusions: Our results suggest that pts with TF-L tumors with liver metastases have improved prognosis compared to pts with TF-H and may benefit from FOLFOX and Cet-based treatment. Findings provide rationale for further evaluation of TF as a predictive biomarker and potential therapeutic target in CRC. Trial Identifier NCT00265850. Support: P30CA014089, U10CA180821, U10CA180882, U10CA180820 and UG1CA233277; UG1CA180830, U10CA180888; Pfizer, Genentech. https://acknowledgments.alliancefound.org.

Abstract A041: Characterizing antigen presentation associated immune escape mechanisms in pancreatic adenocarcinoma using an integrative computational approach

Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal neoplasm of the pancreas characterized by a low survival rate and limited treatment options. Despite the success of immunotherapy in various cancer types, its efficacy in PDAC remains low. The underlying reasons for this discrepancy are not fully understood, despite PDAC exhibiting a moderate mutation burden. One possible determinant could be the loss of heterozygosity (LOH) at the human leukocyte antigen (HLA) loci, resulting in compromised antigen presentation. In this work, we aim to identify and validate HLA LOH events in two independent cohorts to gain insights into both their prevalence and clinical and phenotypic impact on PDAC. Methods: We applied LOHHLA, a specialized pipeline to identify HLA LOH events from paired whole genome sequencing to two independent cohorts comprising over 650 patients. We contextualized these results with the paired transcriptome-wide gene expression data and immunohistochemistry stains. In addition, we developed a machine learning classifier to predict HLA LOH from transcriptomic data. We transfer this classifier to single cell RNA sequencing data to identify the impact of (subclonal) HLA LOH on the tumor microenvironment. Results: HLA LOH events occur in approximately 30% of PDAC patients, with about 50% of these deletions being focal deletions. These events are early genetic alterations and lead to a dosage compensation of the retained HLA genes. We observed a significant association between HLA LOH and the Basal PDAC expression subtype. In addition, we find that HLA expression is the most important determinant of lymphocyte infiltration followed by non-LOH at the HLA locus. Moreover, our transcriptomic classifier allowed us to accurately identify HLA LOH events from RNA sequencing data, which we successfully validated in an independent cohort. Finally, we applied this classifier to single cell sequencing data and identified phenotypic differences in multiple compartments of the tumor microenvironment between samples with intact HLA and HLA LOH. Conclusions: In conclusion, our study provides the most in depth characterization of the consequences of altered antigen presentation in PDAC to date. We have demonstrated that HLA LOH occurs in a substantial proportion of patients. Overall, these findings contribute to a better understanding of the immune landscape in PDAC and may have implications for the development of immunotherapeutic strategies tailored to this challenging cancer type. Citation Format: Michael J. Geuenich, Barbara Gruenwald, Amy Zhang, Oumaima Hamza, Gun Ho Jang, Grainne O’Kane, Faiyaz Notta, Steven Gallinger, Kieran R. Campbell. Characterizing antigen presentation associated immune escape mechanisms in pancreatic adenocarcinoma using an integrative computational approach [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A041.

Impact of plastic-related compounds on the gene expression signature of HepG2 cells transfected with CYP3A4

The presence of plastic and microplastic within the oceans as well as in marine flora and fauna have caused a multitude of problems that have been the topic of numerous investigations for many years. However, their impact on human health remains largely unknown. Such plastic and microplastic particles have been detected in blood and placenta, underlining their ability to enter the human body. Plastics also contain other compounds, such as plasticizers, antioxidants, or dyes, whose impact on human health is currently being studied. Critical enzymes within the metabolism of endogenous molecules, especially of xenobiotics, are the cytochrome P450 monooxygenases (CYPs). Although their importance in maintaining cellular balance has been confirmed, their interactions with plastics and related products are poorly understood. In this study, the possible relationship between different plastic-related compounds and CYP3A4 as one of the most important CYPs was analyzed using hepatic cells overexpressing this enzyme. Beginning with virtual compound screening and molecular docking of more than 1000 plastic-related compounds, several candidates were identified to interact with CYP3A4. In a second step, RNA-sequencing was used to study in detail the transcriptome-wide gene expression levels affected by the selected compounds. Three candidate molecules ((2,2′-methylenebis(6-tert-butyl-4-methylphenol), 1,1-bis(3,5-di-tert-butyl-2-hydroxyphenyl)ethane, and 2,2′-methylenebis(6-cyclohexyl-4-methylphenol)) had an excellent binding affinity to CYP3A4 in-silico as well as cytotoxic effects and interactions with several metabolic pathways in-vitro. We identified common pathways influenced by all three selected plastic-related compounds. In particular, the suppression of pathways related to mitosis and ‘DNA-templated DNA replication’ which were confirmed by cell cycle analysis and single-cell gel electrophoresis. Furthermore, several mis-regulated metabolic and inflammation-related pathways were identified, suggesting the induction of hepatotoxicity at different levels. These findings imply that these compounds may cause liver problems subsequently affecting the entire organism.