Cell-specific Signatures Research Articles

Understanding the Foreign Body Response via Single-Cell Meta-Analysis.

Foreign body response (FBR) is a universal reaction to implanted biomaterial that can affect the function and longevity of the implant. A few studies have attempted to identify targets for treating FBR through the use of single-cell RNA sequencing (scRNA-seq), though the generalizability of these findings from an individual study may be limited. In our study, we perform a meta-analysis of scRNA-seq data from all available FBR mouse studies and integrate these data to identify gene signatures specific to FBR across different models and anatomic locations. We identify subclusters of fibroblasts and macrophages that emerge in response to foreign bodies and characterize their signaling pathways, gene ontology terms, and downstream mediators. The fibroblast subpopulations enriched in the setting of FBR demonstrated significant signaling interactions in the transforming growth factor-beta (TGF-β) signaling pathway, with known pro-fibrotic mediators identified as top expressed genes in these FBR-derived fibroblasts. In contrast, FBR-enriched macrophage subclusters highly expressed pro-fibrotic and pro-inflammatory mediators downstream of tumor necrosis factor (TNF) signaling. Cell-cell interactions were additionally interrogated using CellChat, with identification of key signaling interactions enriched between fibroblasts and macrophages in FBR. By combining multiple FBR datasets, our meta-analysis study identifies common cell-specific gene signatures enriched in foreign body reactions, providing potential therapeutic targets for patients requiring medical implants across a myriad of devices and indications.

Tissue gene expression profiles and communication networks inform candidate blood biomarker identification in psoriasis and atopic dermatitis

Overlapping clinical and pathomechanistic features can complicate the diagnosis and treatment of inflammatory skin diseases, including psoriasis and atopic dermatitis (AD). Spatial transcriptomics allows the identification of disease- and cell-specific molecular signatures that may advance biomarker development and future treatments.This study identified transcriptional signatures in keratinocytes and sub-basal CD4+ and CD8+ T lymphocytes from patients with psoriasis and AD. In silico prediction of ligand:receptor interactions delivered key signalling pathways (interferon, effector T cells, stroma cell and matrix biology, neuronal development, etc.). Targeted validation of selected transcripts, including CCL22, RELB, and JUND, in peripheral blood T cells suggests the chosen approach as a promising tool also in other inflammatory diseases.Psoriasis and AD are characterized by transcriptional dysregulation in T cells and keratinocytes that may be targeted therapeutically. Spatial transcriptomics is a valuable tool in the search for molecular signatures that can be used as biomarkers and/or therapeutic targets.

Aging atlas reveals cell-type-specific effects of pro-longevity strategies

Organismal aging involves functional declines in both somatic and reproductive tissues. Multiple strategies have been discovered to extend lifespan across species. However, how age-related molecular changes differ among various tissues and how those lifespan-extending strategies slow tissue aging in distinct manners remain unclear. Here we generated the transcriptomic Cell Atlas of Worm Aging (CAWA, http://mengwanglab.org/atlas) of wild-type and long-lived strains. We discovered cell-specific, age-related molecular and functional signatures across all somatic and germ cell types. We developed transcriptomic aging clocks for different tissues and quantitatively determined how three different pro-longevity strategies slow tissue aging distinctively. Furthermore, through genome-wide profiling of alternative polyadenylation (APA) events in different tissues, we discovered cell-type-specific APA changes during aging and revealed how these changes are differentially affected by the pro-longevity strategies. Together, this study offers fundamental molecular insights into both somatic and reproductive aging and provides a valuable resource for in-depth understanding of the diversity of pro-longevity mechanisms.

Gene expression meta-analysis reveals aging and cellular senescence signatures in scleroderma-associated interstitial lung disease.

Aging and cellular senescence are increasingly recognized as key contributors to pulmonary fibrosis. However, our understanding in the context of scleroderma-associated interstitial lung disease (SSc-ILD) is limited. To investigate, we leveraged previously established lung aging- and cell-specific senescence signatures to determine their presence and potential relevance to SSc-ILD. We performed a gene expression meta-analysis of lung tissues from 38 SSc-ILD and 18 healthy controls and found that markers (GDF15, COMP, and CDKN2A) and pathways (p53) of senescence were significantly increased in SSc-ILD. When probing the established aging and cellular senescence signatures, we found that epithelial and fibroblast senescence signatures had a 3.6- and 3.7-fold enrichment, respectively, in the lung tissue of SSc-ILD and that lung aging genes (CDKN2A, FRZB, PDE1A, and NAPI12) were increased in SSc-ILD. These signatures were also enriched in SSc skin and associated with degree of skin involvement (limited vs. diffuse cutaneous). To further support these findings, we examined telomere length (TL), a surrogate for aging, in the lung tissue and found that, independent of age, SSc-ILD had significantly shorter telomeres than controls in type II alveolar cells in the lung. TL in SSc-ILD was comparable to idiopathic pulmonary fibrosis, a disease of known aberrant aging. Taken together, this study provides novel insight into the possible mechanistic effects of accelerated aging and aberrant cellular senescence in SSc-ILD pathogenesis.

Schizophrenia endothelial cells exhibit higher permeability and altered angiogenesis patterns in patient-derived organoids

Schizophrenia (SCZ) is a complex neurodevelopmental disorder characterized by the manifestation of psychiatric symptoms in early adulthood. While many research avenues into the origins of SCZ during brain development have been explored, the contribution of endothelial/vascular dysfunction to the disease remains largely elusive. To model the neuropathology of SCZ during early critical periods of brain development, we utilized patient-derived induced pluripotent stem cells (iPSCs) to generate 3D cerebral organoids and define cell-specific signatures of disease. Single-cell RNA sequencing revealed that while SCZ organoids were similar in their macromolecular diversity to organoids generated from healthy controls (CTRL), SCZ organoids exhibited a higher percentage of endothelial cells when normalized to total cell numbers. Additionally, when compared to CTRL, differential gene expression analysis revealed a significant enrichment in genes that function in vessel formation, vascular regulation, and inflammatory response in SCZ endothelial cells. In line with these findings, data from 23 donors demonstrated that PECAM1+ microvascular vessel-like structures were increased in length and number in SCZ organoids in comparison to CTRL organoids. Furthermore, we report that patient-derived endothelial cells displayed higher paracellular permeability, implicating elevated vascular activity. Collectively, our data identified altered gene expression patterns, vessel-like structural changes, and enhanced permeability of endothelial cells in patient-derived models of SCZ. Hence, brain microvascular cells could play a role in the etiology of SCZ by modulating the permeability of the developing blood brain barrier (BBB).

DNA Methylation Changes in Nucleated Red Blood Cells from Patients with Sickle Cell Disease: A Potential Marker of Engraftment after Stem Cell Transplantation

Hematopoietic cell transplant (HCT) is the only established cure for sickle cell disease (SCD). Engraftment (chimerism) of donor red blood cells (RBCs) determines HCT success but current methods measure only white blood cell chimerism and may be inaccurate or fail to indicate graft rejection in a timely manner. Measurement of differentially methylated regions (DMRs) in nucleated red blood cells (nRBCs) to distinguish individuals with sickle cell anemia (genotype HbSS) nRBCs from HbAA and HbAS nRBCs to quantify RBC chimerism could improve post-HCT monitoring by increasing sensitivity to detect rejection and allow for early intervention. Cell-free DNA derived from nRBCs represents a potential method to specifically measure RBC chimerism. Methylation of cytosine nucleotides that are followed by a guanine (methylated CpG sites) is a major means of cell-specific gene expression, and measuring regions of multiple differentially methylated cytosines (DMRs) enables the identification of cell-of-origin of DNA fragments. Cell-free DNA is released into the circulation from all body tissues and cells, including nRBCs, and retains their cell-specific methylation signatures (figure 1). We hypothesized that DMRs unique to healthy and/or SCD nRBC DNA could be identified and later quantified to assess RBC donor chimerism. We generated genome-wide methylomes of nRBC DNA from pediatric SCD (n=2) and non-SCD control (n=3) patients using enzymatic methyl-sequencing (figure 2). From these 5 novel nRBC methylomes and publicly available methylomes and hydroxymethylomes from 35 different tissues and hematopoietic cells we computationally identified 105 DMRs uniquely found in nRBCs compared to other tissues and cells. There were 34 DMRs that specifically distinguished control nRBCs from SCD nRBCs. The 105 DMRs unique to nRBCs were all relatively hypomethylated. These DMRs were intergenic and not associated with CpG islands or shores. DMRs that distinguished SCD nRBCs from control nRBCs were predominantly hypermethylated (76%) in SCD nRBCs and were commonly (21%-24%) located at promoter, exon or intron sequences while 47% were intergenic. 24% were in CpG islands and 5% were in CpG shores. The most significant gene ontology terms in SCD-specific nRBC DMRs were cardiac-related, including heart contraction and conduction. Other highly significant terms were related to cell signaling, transmembrane transporters, and ion channels. Enriched pathway analysis identified terms related to cell signaling, though these were associated with neuronal and immune signaling pathways. To validate our in silico findings, we amplified 8 DMRs from genomic DNA isolated from 23 different cells and tissues and compared methylation patterns. Four DMRs were relatively hypomethylated in control nRBCs compared to SCD nRBCs and other tissues and cells. Amplification of these DMRs from cell-free DNA in patient plasma before and after HCT will validate them as potential unique markers of successful RBC chimerism. Quantification in recipients with HbAA and HbAS donors will be performed. The successful identification of nRBC-specific DMRs in plasma cell-free DNA will enable novel methodology for the quantification of RBC chimerism after HCT for SCD that can be compared to conventional methods of chimerism measurement in future clinical trials.

EPCO-29. SEXUALLY DIMORPHIC EFFECT OF H-FERRITIN GENETIC MANIPULATION ON SURVIVAL AND IMMUNE CELL INFILTRATION IN A MOUSE MODEL OF GLIOBLASTOMA

Abstract Iron plays a crucial role in promoting tumor growth. Recent research has shown that H-ferritin (FTH1), traditionally recognized as an iron storage protein, can transport iron to GBM cancer stem cells, reducing their invasion activity. Moreover, binding of extracellular FTH1 to human GBM tissues, and brain iron delivery in general, has been found to have a sex bias. This raises questions addressed in this study about whether H-ferritin levels extrinsic to the tumor can affect tumor cell pathways and if this impact is sex-specific. Systemic Fth1+/- mice were orthotopically implanted with mouse GBM cells (GL261). Littermate Fth1 +/+ mice were controls. Survival was evaluated and the tumors were subjected to next-generation sequencing protocols. We analyzed resulting data utilizing murine Microenvironment Cell Population (mMCP) method. mMCP estimates abundance of tissue infiltrating immune and stromal populations based on cell-specific gene signatures. Female Fth1+/- mice had significantly poorer survival than control females. Fth1 genetic status had no effect on survival in males. mMCP analysis revealed a significant reduction in T cells and CD8+ T cell infiltration tumors of Fth1+/- females as compared to Fth1+/+. Mast and fibroblast cell infiltration was increased in females and males with Fth1+/- background, respectively, compared to Fth1+/+ mice. Genetic manipulation of Fth1 which leads to reduced systemic levels of FTH1 protein had a sexually dimorphic impact on survival. Fth1+/- significantly worsened survival in females but not in male GBMs. Furthermore, genetic manipulation of Fth1 significantly affected tumor infiltration of T-cells, CD8+ T cells, fibroblasts, and mast cells in a sexually dimorphic manner. These results demonstrate a role for FTH1 and presumably iron status in establishing the tumor cellular landscape that ultimately impacts survival and further reveals a sex bias that may inform the population studies showing a sex effect on the prevalence of brain tumors.

Immune cell-specific and common molecular signatures in rheumatoid arthritis through molecular network approaches

Rheumatoid arthritis (RA) is an autoimmune disorder and common symptom of RA is chronic synovial inflammation. The pathogenesis of RA is not fully understood. Therefore, we aimed to identify underlying common and distinct molecular signatures and pathways among ten types of tissue and cells obtained from patients with RA. In this study, transcriptomic data including synovial tissues, macrophages, blood, T cells, CD4+T cells, CD8+T cells, natural killer T (NKT), cells natural killer (NK) cells, neutrophils, and monocyte cells were analyzed with an integrative and comparative network biology perspective. Each dataset yielded a list of differentially expressed genes as well as a reconstruction of the tissue-specific protein-protein interaction (PPI) network. Molecular signatures were identified by a statistical test using the hypergeometric probability density function by employing the interactions of transcriptional regulators and PPI. Reporter metabolites of each dataset were determined by using genome-scale metabolic networks. It was defined as the common hub proteins, novel molecular signatures, and metabolites in two or more tissue types while immune cell-specific molecular signatures were identified, too. Importantly, miR-155-5p is found as a common miRNA in all tissues. Moreover, NCOA3, PRKDC and miR-3160 might be novel molecular signatures for RA. Our results establish a novel approach for identifying immune cell-specific molecular signatures of RA and provide insights into the role of common tissue-specific genes, miRNAs, TFs, receptors, and reporter metabolites. Experimental research should be used to validate the corresponding genes, miRNAs, and metabolites.

Using LLMs and Explainable ML to Analyze Biomarkers at Single-Cell Level for Improved Understanding of Diseases.

Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our understanding of the diversity of cells and how this diversity is implicated in diseases. Yet, translating these findings across various scRNA-seq datasets poses challenges due to technical variability and dataset-specific biases. To overcome this, we present a novel approach that employs both an LLM-based framework and explainable machine learning to facilitate generalization across single-cell datasets and identify gene signatures to capture disease-driven transcriptional changes. Our approach uses scBERT, which harnesses shared transcriptomic features among cell types to establish consistent cell-type annotations across multiple scRNA-seq datasets. Additionally, we employed a symbolic regression algorithm to pinpoint highly relevant, yet minimally redundant models and features for inferring a cell type's disease state based on its transcriptomic profile. We ascertained the versatility of these cell-specific gene signatures across datasets, showcasing their resilience as molecular markers to pinpoint and characterize disease-associated cell types. The validation was carried out using four publicly available scRNA-seq datasets from both healthy individuals and those suffering from ulcerative colitis (UC). This demonstrates our approach's efficacy in bridging disparities specific to different datasets, fostering comparative analyses. Notably, the simplicity and symbolic nature of the retrieved gene signatures facilitate their interpretability, allowing us to elucidate underlying molecular disease mechanisms using these models.

Single-Cell Integration of BMD GWAS Results Prioritize Candidate Genes Influencing Age-Related Bone Loss.

The regulation of bone mineral density (BMD) is highly influenced by genetics and age. Although genome-wide association studies (GWAS) for BMD have uncovered many genes through their proximity to associated variants (variant nearest-neighbor [VNN] genes), the cell-specific mechanisms of each VNN gene remain unclear. This is primarily due to the inability to prioritize these genes by cell type and age-related expression. Using age-related transcriptomics, we found that the expression of many VNN genes was upregulated in the bone and marrow from aged mice. Candidate genes from GWAS were investigated using single-cell RNA-sequencing (scRNA-seq) datasets to enrich for cell-specific expression signatures. VNN candidate genes are highly enriched in osteo-lineage cells, osteocytes, hypertrophic chondrocytes, and Lepr+ mesenchymal stem cells. These data were used to generate a "blueprint" for Cre-loxp mouse line selection for functional validation of candidate genes and further investigation of their role in BMD maintenance throughout aging. In VNN-gene-enriched cells, Sparc, encoding the extracellular matrix (ECM) protein osteonectin, was robustly expressed. This, along with expression of numerous other ECM genes, indicates that many VNN genes likely have roles in ECM deposition by osteoblasts. Overall, we provide data supporting streamlined translation of GWAS candidate genes to potential novel therapeutic targets for the treatment of osteoporosis. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

217-LB: Heterogeneity of Single Cells Obtained from Peripheral Blood Mononuclear Cells Collected from Youth with Recent-Onset Type 1 Diabetes

Whole blood bulk RNA sequencing has been used to guide T1D clinical trial design and assess response to disease modifying interventions, whereas it is with limited information about cell specific gene expression changes. Here, we aimed to apply computational strategies to deconvolute cell type composition using cell specific gene expression references. Single-cell RNA sequencing (scRNA-seq) was conducted to profile 108,795 peripheral blood mononuclear cells obtained from 5 youth within 48 hrs of Stage 3 T1D onset (avg age 11.4; 3M;2F) and 5 age- and sex-matched controls and identified 31 distinct cell clusters. In T1D, the proportion of CD4+ T central memory (TCM) cells was increased (P = 0.018), while plasmacytoid dendritic cells (pDC), platelets, and hematopoietic stem and progenitor cells (HSPC) proportions were reduced (P = 0.021, 0.012 and 0.017 respectively) compared to controls. The most robust transcriptomic changes were observed in CD14+ and CD16+ monocyte populations and CD1C+ conventional type-2 dendritic (cDC2) cells. Using this scRNA-seq reference dataset, we ran computational algorithms CIBERSORTx and our in-house reference-free method ICTD to deconvolute cell proportions using public clinical trial data testing the anti-CD20 monoclonal antibody rituximab (n=37) vs. placebo (n=17). Strong correlation was observed between the methods for cell proportion estimates (P < 2.2*10-16). It showed that B cell subsets were reduced by rituximab. At baseline, non-responders had a higher proportion of CD8+ T cells (P = 0.04), and responders had higher proportions of neutrophils (P =0.04). These data suggest that deconvolution approaches can be utilized for secondary analysis of existing clinical trial bulk RNA-seq data, to link cell specific immune signatures associated with drug responder status. Disclosure W. Wu: None. C. Parks-schenck: None. T. Guo: None. C. Zhang: None. R. G. Mirmira: None. C. Evans-molina: Advisory Panel; Provention Bio, Inc., DiogenX, Avotres Inc., Neurodon, MaiCell Therapeutics, Other Relationship; Isla Technology, Bristol-Myers Squibb Company, Nimbus Therapeutics, Research Support; Lilly, Astellas Pharma Inc. Funding dkNET; Indiana University Center for Diabetes and Metabolic Diseases; National Institutes of Health (U01DK127786)

Abstract A52: IDS and SETBP1 is highly prognostic in myelodysplastic neoplasms and is a candidate stem cell signature

Abstract Myelodysplastic neoplasms (MDS) are heterogenous blood disorders that arise from dysfunctional hematopoietic stem cells (HSCs) and progenitor cells (HSPCs). According to the cancer stem cell (CSC) model, MDS is organized as a cellular hierarchy that arises from the malignant transformation of HSPCs into rare CSCs. MDS-CSCs are thought to persist during treatment and regenerate disease during relapse. Prior studies have linked MDS-CSCs to MDS-HSPC (Woll et al. Cancer Cell 2014, Pang et al, PNAS 2013, Will et al, Blood 2012), however, a specific cell type has not been isolated and purified as the MDS-CSC. Prognostic gene expression signatures in MDS have also been linked to immature HSPCs (Shiozawa et al, Blood 2017), however, a cell specific signature has not been identified. There is a need to characterize a cell specific gene signature for MDS-CSCs in order to study these cells. To address this need, we performed iterative statistical analyses on MDS gene expression data in order to identify a candidate CSC signature. We hypothesized that by analyzing genes specifically up-regulated in MDS-HSPCs, we can derive a CSC specific gene signature that is not only associated with poor outcomes in MDS, but also marks a subset of cells in MDS with stem cell programs. Up-regulated genes in MDS-HSPCs compared to healthy controls were derived by re-analyzing 73 sorted samples (Woll et al, Cancer Cell 2014) using the limma (Ritchie et al, Nucleic Acids Res 2015). Using these genes, we subsequently analyzed their association with survival in a cohort of 244 MDS patients (Shiozawa et al, Blood 2017, Gerstung et al, Nat Commun 2015, Tyner et al, Nature 2018). We performed iterative Cox proportional hazard models on a training data (n=146), using single and multiple gene combinations. A 2 gene score (i.e., MDS2), comprising IDS and SETBP1, was identified as the most significantly associated feature with decreased survival in MDS compared to Age, Sex, Cytogenetic Risk, and an established MDS score (Shiozawa et al, Blood 2017). Single cell expression of MDS2 was evaluated in MDS scRNA-seq samples (Dussiau et al, BMC Biol2022), and rare cells were identified expressing high levels of MDS2, i.e., MDS2 cells. These cells were integrated with healthy HSPCs. MDS2 cells reside primarily between HSCs and MPPs on a diffusion map, following a differentiation trajectory towards GMPs and monocyte precursors. These observations are consistent with prior studies, as MDS-CSCs were shown to be enriched in HSCs and GMPs (Pang et al, PNAS 2013, Woll et al, Cancer Cell 2014). Analysis of upregulated genes in MDS2 cells revealed that antigen processing, assembly and presentation were the most enriched processes. This analysis supports our approach for identifying a cell specific gene signature, and future work will focus on further single cell analyses and evaluation of CSC content and function of MDS2 cells. Citation Format: Asiri Ediriwickrema, Andrew Gentles, Ravindra Majeti. IDS and SETBP1 is highly prognostic in myelodysplastic neoplasms and is a candidate stem cell signature [abstract]. In: Proceedings of the AACR Special Conference: Acute Myeloid Leukemia and Myelodysplastic Syndrome; 2023 Jan 23-25; Austin, TX. Philadelphia (PA): AACR; Blood Cancer Discov 2023;4(3_Suppl):Abstract nr A52.

Abstract 109: A Spatial Transcriptomic Approach to Understanding Coronary Atherosclerotic Plaque Stability

Introduction: Classically, vulnerable plaques at risk for acute coronary syndrome (ACS) have been defined by cellular architecture. However, contemporary imaging studies have shed light into new mechanisms of ACS (e.g., plaque erosion), challenging plaque rupture as the sole mechanism of disease. Furthermore, mechanisms within the vascular microenvironment that may modulate these disease phenotypes are poorly understood. Our objective was to examine differential programming of smooth muscle and macrophage cells amongst patients with stable and unstable plaques using spatial transcriptomics. Methods: Autopsy-derived coronary arteries were reviewed by an independent pathologist and segregated into stable (N=8) and unstable (defined by the presence of CD68+ cells and a large lipid core, N=8) plaques for spatial profiling. In combination with immunofluorescent histology, our approach enabled cell-specific, spatially resolved transcriptional profiling of plaques with mapping of cell populations via gene expression patterns. Results: We observed unique spatial and cell-specific transcriptional signatures for stable and unstable plaques including regional differences in the tunica intima and media. These regions differentially expressed pro-inflammatory (e.g., IFN-gamma, MHC Class II, pro-inflammatory cytokines) and pro-thrombotic signaling pathways. Cell-type-specific expression analysis using spatial deconvolution revealed heterogeneous CD68+ cell populations which shared gene signatures with endothelial, smooth muscle, and myeloid cells. Conclusion: Our results highlight cell-specific and regional pro-inflammatory and coagulation transcriptional changes within unstable coronary arterial plaques and supports the idea of cellular dedifferentiation and intra-plaque plasticity as a contributor to plaque instability. These findings may help to identify novel mediators of ACS and potential therapeutic targets.

Defining cardiac functional recovery in end-stage heart failure at single-cell resolution.

Recovery of cardiac function is the holy grail of heart failure therapy yet is infrequently observed and remains poorly understood. In this study, we performed single-nucleus RNA sequencing from patients with heart failure who recovered left ventricular systolic function after left ventricular assist device implantation, patients who did not recover and non-diseased donors. We identified cell-specific transcriptional signatures of recovery, most prominently in macrophages and fibroblasts. Within these cell types, inflammatory signatures were negative predictors of recovery, and downregulation of RUNX1 was associated with recovery. In silico perturbation of RUNX1 in macrophages and fibroblasts recapitulated the transcriptional state of recovery. Cardiac recovery mediated by BET inhibition in mice led to decreased macrophage and fibroblast Runx1 expression and diminished chromatin accessibility within a Runx1 intronic peak and acquisition of human recovery signatures. These findings suggest that cardiac recovery is a unique biological state and identify RUNX1 as a possible therapeutic target to facilitate cardiac recovery.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers.

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

Abstract 5945: Transcriptional analysis of TME in MC38 colon carcinoma model following checkpoint inhibition

Abstract Colorectal cancer (CRC) is one of the most common cancers with 200,000 US cases per year. Adenocarcinoma is the most common type of CRC, making up 95 percent of all CRC cases. Checkpoint inhibitors used for CRC have shown efficacy for a specific subset of patients. MC38 is a very popular tumor model due to its characteristics as an immunologically warm tumor and response to some immunotherapies. To identify underlying factors that influence differences in treatment response, the tumor microenvironment (TME) of the MC38 model was analyzed following the treatment with anti-programmed cell death protein 1 (PD-1) and anti-cytotoxic T lymphocyte associated protein 4 (CTLA-4). The minimal tumor growth inhibition was observed in MC38 tumors treated with anti-PD-1 or anti-CTLA-4. The NanoString® nCounter system and flow cytometry were used to provide gene and cell-specific signatures of TME in response to immunomodulatory agents. NanoString® nCounter and flow cytometry analyses were complementary and demonstrated evidence of T cell recruitment and upregulation of genes associated with several immune-related pathways following treatment. Cytotoxic CD8+ T cells, CD4+ T cells, and NK cells in MC38 tumors following treatment with anti-PD-1, suggesting activation of an immune response. With treatment of anti-CTLA-4, tumors did not have demonstrable alterations to immune cell subset distribution which supports evidence that anti-CTLA-4 treatment show minimal activation of the immune system in MC38 tumors. Further, transcriptome analysis with NanoString® nCounter system revealed that the immune pathways related to signatures such as interferon signaling, cytotoxicity, antigen presentation, cytokine signaling, and chemokine signaling were upregulated with anti-PD-1 treatment compared to control or anti-CTLA-4 treatment of MC38 tumors. The transcriptome analysis also demonstrated 2-5-fold increases of interferon, cytotoxicity, cytokine, and chemokine genes such as, Gbp2, Gbp3, Irf1, Irf7, Irf8, Ifit1, Ifit2, Ifit3, Tnfsf10, Ccl2, Ccl5, Ccl7, Ccl12, Cxcl9, Cxcl10, and Cxcl11 over control in the case of anti-PD-1 treatment. In summary, anti-PD-1 treatment increased T cell recruitment into the tumor and upregulated genes in TME. Anti-CTLA-4 treatment known to enable combination activity with anti-PD-1, but not enough to show notable monotherapy activity. Immune cell subset distribution in TME and relative gene expression are two potential types of analyses to predict anti-tumor response. These data can be used mechanistically as well as to inform rational combination strategies for checkpoint inhibitors in colon adenocarcinoma. Citation Format: Priyanka Singh, Dan Saims, David Draper, Sheri Barnes. Transcriptional analysis of TME in MC38 colon carcinoma model following checkpoint inhibition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5945.

Longitudinal DNA methylation profiling of the rectal mucosa identifies cell-specific signatures of disease status, severity and clinical outcomes in ulcerative colitis cell-specific DNA methylation signatures of UC

BackgroundIn peripheral blood, DNA methylation (DNAm) patterns in inflammatory bowel disease patients reflect inflammatory status rather than disease status. Here, we examined DNAm in diseased rectal mucosa from ulcerative colitis (UC) patients, focusing on constituent cell types with the goal of identifying therapeutic targets for UC other than the immune system. We profiled DNAm of rectal mucosal biopsies of pediatric UC at diagnosis (n = 211) and non-IBD control (n = 85) patients and performed epigenome-wide association studies (EWAS) of specific cell types to understand DNAm changes in epithelial, immune and fibroblast cells across disease states, course, and clinical outcomes. We also examined longitudinal analysis on follow-up samples (n = 73), and comparisons were made among patients with clinical outcomes including those undergoing colectomy versus those who did not. Additionally, we included RNA-seq from the same subjects to assess the impact of CpG sites on the transcription of nearby genes during the disease course.ResultsAt diagnosis, UC rectal mucosa exhibited a lower proportion of epithelial cells and fibroblasts, and higher proportion of immune cells, in conjunction with variation in the DNAm pattern. While treatment had significant effects on the methylation signature of immune cells, its effects on fibroblasts and epithelial cells were attenuated. Individuals who required colectomy exhibited cell composition and DNAm patterns at follow-up more similar to disease onset than patients who did not require colectomy. Combining these results with gene expression profiles, we identify CpG sites whose methylation patterns are most consistent with a contribution to poor disease outcomes and could thus be potential therapeutic targets.ConclusionsCell-specific epigenetic changes in the rectal mucosa in UC are associated with disease severity and outcome. Current therapeutics may more effectively target the immune than the epithelial and fibroblast compartments.Graphical abstract

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing

The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.

Thrombospondin-1, CD47, and SIRPα display cell-specific molecular signatures in human islets and pancreata.

Thrombospondin-1 (TSP1) is a secreted protein minimally expressed in health but increased in disease and age. TSP1 binds to the cell membrane receptor CD47, which itself engages signal regulatory protein α (SIRPα), and the latter creates a checkpoint for immune activation. Individuals with cancer administered checkpoint-blocking molecules developed insulin-dependent diabetes. Relevant to this, CD47 blocking antibodies and SIRPα fusion proteins are in clinical trials. We characterized the molecular signature of TSP1, CD47, and SIRPα in human islets and pancreata. Fresh islets and pancreatic tissue from nondiabetic individuals were obtained. The expression of THBS1, CD47, and SIRPA was determined using single-cell mRNA sequencing, immunofluorescence microscopy, Western blot, and flow cytometry. Islets were exposed to diabetes-affiliated inflammatory cytokines and changes in protein expression were determined. CD47 mRNA was expressed in all islet cell types. THBS1 mRNA was restricted primarily to endothelial and mesenchymal cells, whereas SIRPA mRNA was found mostly in macrophages. Immunofluorescence staining showed CD47 protein expressed by β cells and present in the exocrine pancreas. TSP1 and SIRPα proteins were not seen in islets or the exocrine pancreas. Western blot and flow cytometry confirmed immunofluorescent expression patterns. Importantly, human islets produced substantial quantities of secreted TSP1. Human pancreatic exocrine and endocrine tissue expressed CD47, whereas fresh islets displayed cell surface CD47 and secreted TSP1 at baseline and in inflammation. These findings suggest unexpected effects on islets from agents that intersect TSP1-CD47-SIRPα.NEW & NOTEWORTHY CD47 is a cell surface receptor with two primary ligands, soluble thrombospondin-1 (TSP1) and cell surface signal regulatory protein alpha (SIRPα). Both interactions provide checkpoints for immune cell activity. We determined that fresh human islets display CD47 and secrete TSP1. However, human islet endocrine cells lack SIRPα. These gene signatures are likely important given the increasing use of CD47 and SIRPα blocking molecules in individuals with cancer.

Longitudinal Effects of 1-Year Smoking Cessation on Human Bronchial Epithelial Transcriptome

Longitudinal Effects of 1-Year Smoking Cessation on Human Bronchial Epithelial Transcriptome