Single Sequence Research Articles

Single nuclear RNA sequencing of terminal ileum in patients with cirrhosis demonstrates multi-faceted alterations in the intestinal barrier

Patients with cirrhosis have intestinal barrier dysfunction but the role of the individual cell types in human small intestine is unclear. We performed single-nuclear RNA sequencing (snRNAseq) in the pinch biopsies of terminal ileum of four age-matched men [56 years, healthy control, compensated, early (ascites and lactulose use) and advanced decompensated cirrhosis (ascites and rifaximin use)]. Cell type proportions, differential gene expressions, cell-type specific pathway analysis using IPA, and cellular crosstalk dynamics were compared. Stem cells, enterocytes and Paneth cells were lowest in advanced decompensation. Immune cells like naive CD4 + T cells were lowest while ITGAE + cells were highest in advanced decompensation patients. MECOM had lowest expression in stem cells in advanced decompensation. Defensin and mucin sulfation gene (PAPSS2) which can stabilize the mucus barrier expression were lowest while IL1, IL6 and TNF-related genes were significantly upregulated in the enterocytes, goblet, and Paneth cells in decompensated subjects. IPA analysis showed higher inflammatory pathways in enterocytes, stem, goblet, and Paneth cells in decompensated patients. Cellular crosstalk analysis showed that desmosome, protease-activated receptors, and cadherin-catenin complex interactions were most perturbed in decompensated patients. In summary, the snRNAseq of the human terminal ileum in 4 subjects (1 control and three cirrhosis) identified multidimensional alteration in the intestinal barrier with lower stem cells and altered gene expression focused on inflammation, mucin sulfation and cell–cell interactions with cirrhosis decompensation.

A complete workflow for single cell mtDNAseq in CHO cells, from cell culture to bioinformatic analysis.

Chinese hamster ovary (CHO) cells have a long history in the biopharmaceutical industry and currently produce the vast majority of recombinant therapeutic proteins. A key step in controlling the process and product consistency is the development of a producer cell line derived from a single cell clone. However, it is recognized that genetic and phenotypic heterogeneity between individual cells in a clonal CHO population tends to arise over time. Previous bulk analysis of CHO cell populations revealed considerable variation within the mtDNA sequence (heteroplasmy), which could have implications for the performance of the cell line. By analyzing the heteroplasmy of single cells within the same population, this heterogeneity can be characterized with greater resolution. Such analysis may identify heterogeneity in the mitochondrial genome, which impacts the overall phenotypic performance of a producer cell population, and potentially reveal routes for genetic engineering. A critical first step is the development of robust experimental and computational methods to enable single cell mtDNA sequencing (termed scmtDNAseq). Here, we present a protocol from cell culture to bioinformatic analysis and provide preliminary evidence of significant mtDNA heteroplasmy across a small panel of single CHO cells.

Analyzing single cell RNA sequencing with topological nonnegative matrix factorization

Single-cell RNA sequencing (scRNA-seq) is a relatively new technology that has stimulated enormous interest in statistics, data science, and computational biology due to the high dimensionality, complexity, and large scale associated with scRNA-seq data. Nonnegative matrix factorization (NMF) offers a unique approach due to its meta-gene interpretation of resulting low-dimensional components. However, NMF approaches suffer from the lack of multiscale analysis. This work introduces two persistent Laplacian regularized NMF methods, namely, topological NMF (TNMF) and robust topological NMF (rTNMF). By employing a total of 12 datasets, we demonstrate that the proposed TNMF and rTNMF significantly outperform all other NMF-based methods. We have also utilized TNMF and rTNMF for the visualization of popular Uniform Manifold Approximation and Projection (UMAP) and t-distributed stochastic neighbor embedding (t-SNE).

Fructose regulates the pentose phosphate pathway and induces an inflammatory and resolution phenotype in Kupffer cells

Over-consumption of fructose in adults and children has been linked to increased risk of non-alcoholic fatty liver disease (NAFLD). Recent studies have highlighted the effect of fructose on liver inflammation, fibrosis, and immune cell activation. However, little work summarizes the direct impact of fructose on macrophage infiltration, phenotype, and function within the liver. We demonstrate that chronic fructose diet decreased Kupffer cell populations while increasing transitioning monocytes. In addition, fructose increased fibrotic gene expression of collagen 1 alpha 1 (Col1a1) and tissue metallopeptidase inhibitor 1 (Timp1) as well as inflammatory gene expression of tumor necrosis factor alpha (Tnfa) and expression of transmembrane glycoprotein NMB (Gpnmb) in liver tissue compared to glucose and control diets. Single cell RNA sequencing (scRNAseq) revealed fructose elevated expression of matrix metallopeptidase 12 (Mmp12), interleukin 1 receptor antagonist (Il1rn), and radical S-adenosyl methionine domain (Rsad2) in liver and hepatic macrophages. In vitro studies using IMKC and J774.1 cells demonstrated decreased viability when exposed to fructose. Additionally, fructose increased Gpnmb, Tnfa, Mmp12, Il1rn, and Rsad2 in unpolarized IMKC. By mass spectrometry, C13 fructose tracing detected fructose metabolites in glycolysis and the pentose phosphate pathway (PPP). Inhibition of the PPP further increased fructose induced Il6, Gpnmb, Mmp12, Il1rn, and Rsad2 in nonpolarized IMKC. Taken together, fructose decreases cell viability while upregulating resolution and anti-inflammatory associated genes in Kupffer cells.

MGMT promoter methylation prediction based on multiparametric MRI via vision graph neural network.

Glioblastoma (GBM) is aggressive and malignant. The methylation status of the -methylguanine-DNA methyltransferase (MGMT) promoter in GBM tissue is considered an important biomarker for developing the most effective treatment plan. Although the standard method for assessing the MGMT promoter methylation status is via bisulfite modification and deoxyribonucleic acid (DNA) sequencing of biopsy or surgical specimens, a secondary automated method based on medical imaging may improve the efficiency and accuracy of those tests. We propose a deep vision graph neural network (ViG) using multiparametric magnetic resonance imaging (MRI) to predict the MGMT promoter methylation status noninvasively. Our model was compared to the RSNA radiogenomic classification winners. The dataset includes 583 usable patient cases. Combinations of MRI sequences were compared. Our multi-sequence fusion strategy was compared with those using single MR sequences. Our best model [Fluid Attenuated Inversion Recovery (FLAIR), T1-weighted pre-contrast (T1w), T2-weighted (T2)] outperformed the winning models with a test area under the curve (AUC) of 0.628, an accuracy of 0.632, a precision of 0.646, a recall of 0.677, a specificity of 0.581, and an F1 score of 0.661. Compared to the winning models with single MR sequences, our ViG utilizing fused-MRI showed a significant improvement statistically in AUC scores, which are FLAIR (), T1w (), T1wCE (), and T2 (). Our model is superior to challenge champions. A graph representation of the medical images enabled good handling of complexity and irregularity. Our work provides an automatic secondary check pipeline to ensure the correctness of MGMT methylation status prediction.

CnnImpute: missing value recovery for single cell RNA sequencing data

The advent of single-cell RNA sequencing (scRNA-seq) technology has revolutionized our ability to explore cellular diversity and unravel the complexities of intricate diseases. However, due to the inherently low signal-to-noise ratio and the presence of an excessive number of missing values, scRNA-seq data analysis encounters unique challenges. Here, we present cnnImpute, a novel convolutional neural network (CNN) based method designed to address the issue of missing data in scRNA-seq. Our approach starts by estimating missing probabilities, followed by constructing a CNN-based model to recover expression values with a high likelihood of being missing. Through comprehensive evaluations, cnnImpute demonstrates its effectiveness in accurately imputing missing values while preserving the integrity of cell clusters in scRNA-seq data analysis. It achieved superior performance in various benchmarking experiments. cnnImpute offers an accurate and scalable method for recovering missing values, providing a useful resource for scRNA-seq data analysis.

Clusterin knockdown has effects on intracellular and secreted von Willebrand factor in human umbilical vein endothelial cells.

Alterations in von Willebrand factor (VWF) have an important role in human health and disease. Deficiency of VWF is associated with symptoms of bleeding and excesses of VWF are associated with thrombotic outcomes. Understanding the mechanisms that drive VWF regulation can lead to a better understanding of modulation of VWF levels in humans. We identified clusterin (CLU) as a potential candidate regulator of VWF based on a single cell RNA sequencing (scRNA-seq) analysis in control endothelial cells (ECs) and von Willebrand disease (VWD) endothelial colony-forming-cells (ECFCs). We found that patients with deficiencies of VWF (von Willebrand disease, VWD) had decreased CLU expression and ECs with low VWF expression also had low CLU expression. Based on these findings, we sought to evaluate the role of CLU in the regulation of VWF, specifically as it relates to VWD. As CLU is primarily thought to be a golgi protein involved in protein chaperoning, we hypothesized that knockdown of CLU would lead to decreases in VWF and alterations in Weibel-Palade bodies (WPBs). We used both siRNA- and CRISPR-Cas9-based approaches to modulate CLU in human umbilical vein endothelial cells (HUVECs) and evaluated VWF protein levels, VWF mRNA copy number, and WPB quantity and size. We demonstrated that siRNA-based knockdown of CLU resulted in decreases in VWF content in cellular lysates and supernatants, but no significant change in WPB quantity or size. A CRISPR-Cas9-based knockdown of CLU demonstrated similar findings of decreases in intracellular VWF content but no significant change in WPB quantity or size. Our data suggests that CLU knockdown is associated with decreases in cellular VWF content but does not affect VWF mRNA levels or WPB quantity or size.

A195 IL-13 DRIVES CROHN’S DISEASE ASSOCIATED-INTESTINAL FIBROSIS IN SHIP DEFICIENT MICE

Abstract Background Crohn’s disease (CD) is an immune-mediated disease characterized by chronic, relapsing and remitting, or progressive inflammation of the digestive tract. One in 3 people with CD will develop intestinal fibrosis requiring surgery within 10 years of diagnosis. Biological therapy is effective at reducing inflammation in CD and early and aggressive treatment with biologics will reduce the incidence of fibrosis. However, in children, for whom a step-up approach to therapy is used, and populations that are refractory to biological therapy; fibrosis remains a serious concern. Treatments are urgently needed as currently there are no treatments that target intestinal fibrosis directly in CD. Mice deficient in the Src homology 2 domain-containing inositolpolyphosphate 5’-phosphatase (SHIP-/-) develop spontaneous CD-like ileal inflammation and fibrosis. Fibrosis is dependent on PI3Kp110δ activity. IL-4 and IL-13 lead to downstream activation of PI3Kp110δ. Recent work in our lab has shown through pharmacological inhibition that the development of fibrosis in SHIP-/- mice is dependenet on IL-13 signaling, but not IL-4. Aims Aim 1: To determine whether genetic ablation of IL-13 prevents ileal fibrosis in SHIP-/- mice Aim 2: To determine the cellular source of IL-13 in the distal ileum of SHIP-/- mice Aim 3: To determine the cellular source of IL-13 in the distal ileum of individuals with CD Methods SHIP-/- mice were crossed with IL-13 deficient mice (IL13-/-) to generate SHIP+/+IL13+/+, SHIP+/+IL13-/-, SHIP-/-IL13+/+, and SHIP-/-IL13-/- mice. Measurements of ileal fibrosis included gross and histopathology, muscle thickening, and collagen accumulation (Masson’s trichrome staining for fibrosis). Single cell RNA sequencing (snRNA-seq) was performed on the distal ileum of SHIP-/- mice to determine the cellular source of IL-13. Previously published scRNA-seq data were analyzed to determine the cellular source of IL-13 in individuals with CD. Results Genetic ablation of IL-13 in SHIP-/- mice (SHIP-/-IL13-/-) reduced the development of ileal fibrosis. Analysis of single cell RNA sequencing data (scRNA seq) has revealed mast cells as the cellular source of IL-13 in the distal ileum of people with CD. Conclusions Mast cell derived IL-13 may be driving the development of intestinal fibrosis in CD. Our data suggest that an antibody-based biologic targeting IL-13 may be an effective strategy to prevent fibrosis in people with Crohn’s Disease. Funding Agencies CAG, CIHR

A single sequence of intermittent hypoxia does not alter stretch reflex excitability in able-bodied individuals.

Spasticity attributable to exaggerated stretch reflex pathways, particularly affecting the ankle plantar flexors, often impairs overground walking in persons with incomplete spinal cord injury. Compelling evidence from rodent models underscores how exposure to acute intermittent hypoxia (AIH) can provide a unique medium to induce spinal plasticity in key inhibitory pathways mediating stretch reflex excitability and potentially affect spasticity. In this study, we quantify the effects of a single exposure to AIH on the stretch reflex in able-bodied individuals. We hypothesized that a single sequence of AIH will increase the stretch reflex excitability of the soleus muscle during ramp-and-hold angular perturbations applied to the ankle joint while participants perform passive and volitionally matched contractions. Our results revealed that a single AIH exposure did not significantly change the stretch reflex excitability during both passive and active matching conditions. Furthermore, we found that able-bodied individuals increased their stretch reflex response from passive to active matching conditions after both sham and AIH exposures. Together, these findings suggest that a single AIH exposure might not engage inhibitory pathways sufficiently to alter stretch reflex responses in able-bodied persons. However, the generalizability of our present findings requires further examination during repetitive exposures to AIH along with potential reflex modulation during functional movements, such as overground walking.

Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease

Single cell and spatially resolved ‘omic’ techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome ‘spot’ on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNAseq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Single cell mapping of the spatial transcriptome using paired snRNAseq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell–cell interactions predicted using ligand–receptor analysis of snRNAseq data poorly correlated with cellular relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell–cell interactions in biobanked clinical samples with advanced liver disease.

Co-occurrence of blaNDM-1 and blaOXA-23 in carbapenemase-producing Acinetobacter baumannii belonging to high-risk lineages isolated from burn patients in Tunisia.

Carbapenem-resistant Acinetobacter baumannii (CR-Ab) is an important cause of infections in burn patients. This study aimed to characterize the antimicrobial susceptibility pattern of CR-Ab isolated from burns in Burn Intensive Care Unit (BICU) of the Trauma and Burn Centre of Ben Arous, to determine the prevalence of β-lactamase-encoding genes and to search eventual genetic relatedness of CR-Ab strains. From 15 December 2016 to 2 April 2017, all nonduplicated CR-Ab isolated in burn patients in the BICU were screened by simplex Polymerase Chain Reaction (PCR) for the class A, B, C, and D β-lactamase genes. Sequencing was performed for NDM gene only. Genetic relatedness was determined by using pulsed field gel electrophoresis (PFGE) and by multilocus sequence typing. During the study period, 34 strains of CR-Ab were isolated in burns, mainly in blood culture (n=14) and central vascular catheter (n=10). CR-Ab strains were susceptible to colistin but resistant to amikacin (91%), ciprofloxacin (100%), rifampicin (97%), and trimethoprim-sulfamethoxazole (100%). All strains harbored blaOXA-51-like and blaOXA-23 genes, only or associated to blaGES (n=26; 76%), blaADC (n=20; 59%), blaPER-1 (n=6; 18%) or/and blaNDM-1 (n=3; 9%). PFGE identified 16 different clusters and revealed that most strains belonged to one major cluster A (n=15; 44.1%). Among NDM-1 isolates, two were clonally related in PFGE and belonged to two single locus variant sequence type ST-6 and ST-85. This is the first description of clonally related NDM-1 and OXA-23-producing A. baumannii strains in the largest Tunisian BICU associated with two single locus variant sequence types ST6 and ST85.

Predicting proximal tubule failed repair drivers through regularized regression analysis of single cell multiomic sequencing

Renal proximal tubule epithelial cells have considerable intrinsic repair capacity following injury. However, a fraction of injured proximal tubule cells fails to undergo normal repair and assumes a proinflammatory and profibrotic phenotype that may promote fibrosis and chronic kidney disease. The healthy to failed repair change is marked by cell state-specific transcriptomic and epigenomic changes. Single nucleus joint RNA- and ATAC-seq sequencing offers an opportunity to study the gene regulatory networks underpinning these changes in order to identify key regulatory drivers. We develop a regularized regression approach to construct genome-wide parametric gene regulatory networks using multiomic datasets. We generate a single nucleus multiomic dataset from seven adult human kidney samples and apply our method to study drivers of a failed injury response associated with kidney disease. We demonstrate that our approach is a highly effective tool for predicting key cis- and trans-regulatory elements underpinning the healthy to failed repair transition and use it to identify NFAT5 as a driver of the maladaptive proximal tubule state.

Comprehensive analysis of single cell and bulk data develops a promising prognostic signature for improving immunotherapy responses in ovarian cancer.

The tumor heterogeneity is an important cause of clinical therapy failure and yields distinct prognosis in ovarian cancer (OV). Using the advantages of integrated single cell RNA sequencing (scRNA-seq) and bulk data to decode tumor heterogeneity remains largely unexplored. Four public datasets were enrolled in this study, including E-MTAB-8107, TCGA-OV, GSE63885, and GSE26193 cohorts. Random forest algorithm was employed to construct a multi-gene prognostic panel and further evaluated by receiver operator characteristic (ROC), calibration curve, and Cox regression. Subsequently, molecular characteristics were deciphered, and treatments strategies were explored to deliver precise therapy. The landscape of cell subpopulations and functional characteristics, as well as the dynamic of macrophage cells were detailly depicted at single cell level, and then screened prognostic candidate genes. Based on the expression of candidate genes, a stable and robust cell characterized gene associated prognosis signature (CCIS) was developed, which harbored excellent performance at prognosis assessment and patient stratification. The ROC and calibration curves, and Cox regression analysis elucidated CCIS could serve as serve as an independent factor for predicting prognosis. Moreover, a promising clinical tool nomogram was also constructed according to stage and CCIS. Through comprehensive investigations, patients in low-risk group were charactered by favorable prognosis, elevated genomic variations, higher immune cell infiltrations, and superior antigen presentation. For individualized treatment, patients in low-risk group were inclined to better immunotherapy responses. This study dissected tumor heterogeneity and afforded a promising prognostic signature, which was conducive to facilitating clinical outcomes for patients with OV.

Potent and broadly neutralizing antibodies against sarbecoviruses induced by sequential COVID-19 vaccination

The current SARS-CoV-2 variants strikingly evade all authorized monoclonal antibodies and threaten the efficacy of serum-neutralizing activity elicited by vaccination or prior infection, urging the need to develop antivirals against SARS-CoV-2 and related sarbecoviruses. Here, we identified both potent and broadly neutralizing antibodies from a five-dose vaccinated donor who exhibited cross-reactive serum-neutralizing activity against diverse coronaviruses. Through single B-cell sorting and sequencing followed by a tailor-made computational pipeline, we successfully selected 86 antibodies with potential cross-neutralizing ability from 684 antibody sequences. Among them, PW5-570 potently neutralized all SARS-CoV-2 variants that arose prior to Omicron BA.5, and the other three could broadly neutralize all current SARS-CoV-2 variants of concern, SARS-CoV and their related sarbecoviruses (Pangolin-GD, RaTG13, WIV-1, and SHC014). Cryo-EM analysis demonstrates that these antibodies have diverse neutralization mechanisms, such as disassembling spike trimers, or binding to RBM or SD1 to affect ACE2 binding. In addition, prophylactic administration of these antibodies significantly protects nasal turbinate and lung infections against BA.1, XBB.1, and SARS-CoV viral challenge in golden Syrian hamsters, respectively. Importantly, post-exposure treatment with PW5-5 and PW5-535 also markedly protects against XBB.1 challenge in these models. This study reveals the potential utility of computational process to assist screening cross-reactive antibodies, as well as the potency of vaccine-induced broadly neutralizing antibodies against current SARS-CoV-2 variants and related sarbecoviruses, offering promising avenues for the development of broad therapeutic antibody drugs.

(058) Detection and Transcriptional Profiling of Mesenchymal Stem Cells in Peyronie’s Plaque Explants

Abstract Introduction The mechanisms behind the pathogenesis of Peyronie’s disease largely remain a mystery. Plaques have largely been thought to be derived from epithelial to mesenchymal transformation of fibroblasts to myofibroblasts. Objective We sought to transcriptomically profile explanted cells from Peyronie’s plaques and evaluate their profiles with transforming growth factor B (TGF-B) stimulation. Methods Peyronie’s plaque were excised from 3 patients undergoing penile incision and grafting surgery. Cells were explanted from biopsy tissue and propagated. Cells were profiled using single cell RNA sequencing (scRNAseq). These cells were then exposed to TGF-□ to simulate the active phase of Peyronie’s disease, and profiled with scRNAseq at baseline and 24 hours following TGF-□□ stimulation. We used principle component analysis (PCA) to reduce the dimension of data and built the nearest-neighbors graph using PCA weights. We performed clustering over the nearest-neighbor graph and visualized the clusters using UMAP algorithm. Differential gene expression and pathway analyses were performed using the top 50 genes with increased expression between 0- and 24-hour time points. Multi-channel flow cytometry and immunofluorescence were used for mesenchymal stem cell (MSC) phenotypic validation. Results Assessment of cell clustering identified profiles of fibroblasts, myofibroblasts, smooth muscle, and mesenchymal stem-like cells. We further confirmed rare presence of mesenchymal stem cells using multi-channel flow cytometry in our cultured cells and plaque biopsies. Differential gene expression of the 50 genes showing the greatest induction showed that genes involved in cellular binding and catalytic activity were most commonly upregulated following introduction of TGF-B. Conclusions This analysis provides unique insight into the expression profiles of Peyronie’s plaque cell populations explanted in culture and stimulated via TGF-B to activate myofibroblasts akin to the active phase of Peyronie’s disease. Using the information gained from this single-cell RNA sequencing analysis ongoing efforts can be performed to identify therapeutic targets for active phase Peyronie’s disease. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Coloplast; Boston; Teumo Health Technologies.

Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.

Background: Collagen represents a prominent constituent of the tumor's extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions. Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer. Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells. Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.

A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI

PurposeTo explore a subregion-based RadioFusionOmics (RFO) model for discrimination between adult-type grade 4 astrocytoma and glioblastoma according to the 2021 WHO CNS5 classification.Methods329 patients (40 grade 4 astrocytomas and 289 glioblastomas) with histologic diagnosis was retrospectively collected from our local institution and The Cancer Imaging Archive (TCIA). The volumes of interests (VOIs) were obtained from four multiparametric MRI sequences (T1WI, T1WI + C, T2WI, T2-FLAIR) using (1) manual segmentation of the non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE), and (2) K-means clustering of four habitats (H1: high T1WI + C, high T2-FLAIR; (2) H2: high T1WI + C, low T2-FLAIR; (3) H3: low T1WI + C, high T2-FLAIR; and (4) H4: low T1WI + C, low T2-FLAIR). The optimal VOI and best MRI sequence combination were determined. The performance of the RFO model was evaluated using the area under the precision-recall curve (AUPRC) and the best signatures were identified.ResultsThe two best VOIs were manual VOI3 (putative peritumoral edema) and clustering H34 (low T1WI + C, high T2-FLAIR (H3) combined with low T1WI + C and low T2-FLAIR (H4)). Features fused from four MRI sequences (Fseq1,2,3,4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${F}_{seq}^{\\mathrm{1,2},\\mathrm{3,4}}$$\\end{document}) outperformed those from either a single sequence or other sequence combinations. The RFO model that was trained using fused features Fseq1,2,3,4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${F}_{seq}^{\\mathrm{1,2},\\mathrm{3,4}}$$\\end{document} achieved the AUPRC of 0.972 (VOI3) and 0.976 (H34) in the primary cohort (p = 0.905), and 0.971 (VOI3) and 0.974 (H34) in the testing cohort (p = 0.402).ConclusionThe performance of subregions defined by clustering was comparable to that of subregions that were manually defined. Fusion of features from the edematous subregions of multiple MRI sequences by the RFO model resulted in differentiation between grade 4 astrocytoma and glioblastoma.

Vasculogenic mimicry regulates immune infiltration and mutational status of the tumor microenvironment in breast cancer to influence tumor prognosis.

Vasculogenic mimicry (VM) refers to the direct formation of microcirculatory ducts by invasive malignant tumors via cellular phenotypic transformation. However, there is a lack of VM-based biomarkers for breast cancer. We obtained transcriptomic expression data, single cell sequencing data, and clinical data of patients from The Cancer Genome Atlas Program (TCGA) database and GEO database, performed single cell analysis to obtain specific type annotations of breast cancer cells and analyzed their spatial expression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analyses as well as Gene Set Enrichment Analysis (GSEA) analyses were performed to clarify the biological pathways and tumor functional enrichment relationships of the major expressed genes of VM in the breast cancer bulk data specimens. VM biomarkers were constructed. Meanwhile, the relationship between VM scores and tumor immune infiltration in breast cancer was analyzed using MCPcounter and ssGSEA methods. In addition, we assessed the specific relationship between NDRG1, a key VM gene in breast cancer, and tumor colonization, adhesion and invasion by biological experiments in breast cancer cell lines. The main cell types of breast cancer (BRCA) samples were annotated by single cell transcriptome analysis. Most of the VM-high group was present in epithelial cells, whereas the VM-low group was present in immune and stromal cells. Multiple tumor pathways such as TGFβ p53 and MAPK were closely associated with VM-mediated breast cancer infiltration and invasion. A prognostic model of breast cancer based on VM key genes was constituted. Prognostic stratification of breast cancer was successfully achieved for the TCGA-BRCA and GSE58812 datasets. Through immune infiltration analysis, we found that differential expression of VM markers was associated with multiple immune cell regulation. In MDA-MB-231 and MDA-MB-453 cell lines, we found that the NDRG1 gene significantly promoted colony formation of breast cancer cells. Our constructed VM-related gene-based model of breast cancer biology holds promise for prognostic prediction and patient stratification of breast cancer. This may provide a potentially clinically valuable aid in promoting a deeper understanding of the biological regulation of VM in breast cancer and exploring the specific mechanisms of tumor angiogenesis and breast cancer development.

Abstract IA15: Single cell origins and targeting of genomic instability in breast cancers

Abstract Early whole genome sequencing studies have emphasised the different modes by which breast cancers can evolve. However, bulk NGS tissue analysis obscures mutations that are contemporaneous and/or lead to negative selection, and does not resolve clone specific metrics such as replication rate and fitness. We have developed single cell genome sequencing methods (Laks et al., Cell 2019) to identify large scale copy number-structural (CNA-SV) mutational processes that result in genomic shuffling through the duplication or deletion of chromosomal regions, obscured by bulk tissue analysis. This has revealed the existence and activity of distinct “foreground” mutational processes, i.e. mutational events in single mitoses that are observed directly, before the effects of purifying selection. We discovered that foreground processes are preferentially associated with background patterns of genome instability (Funnell et al., Nature 2022). We also discovered that CNA-SV mutational patterns are associated with relative sensitivity or resistance to platinum, a commonly used DNA targeting agent in TNBC and HGSOC. Our second recent discovery has been the association of CNA-SV mutations with clonal resistance to platinum in TNBC (Salehi et al., Nature 2021). Taken together, we now understand that ongoing CNA-SV mutations contribute to the evolution of fitness landscapes for DNA targeting therapeutics. In parallel work (Xu et al Nat. comms 2017) we have discovered stabilisers of folded DNA guanine stacked bases, G-quadruplexes (G4), to be synthetically lethal in contexts including HR and TMEJ that are underpinned by the single cell processes identified through single genome sequencing. To this end we have recently observed G4-ligand clinical activity in BRCA2 and PALB2 mutated cancers in a phase 1 trial (Hilton et al, Nature communication 2022). Citation Format: Samuel Aparicio. Single cell origins and targeting of genomic instability in breast cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr IA15.

Abstract A060: Organoid Culture as a Unique Resource for Studying Aggressive Triple Negative Breast Cancer in African American

Abstract Introduction Triple negative breast cancer (TNBC) among women with African ancestry has been shown to be more aggressive than in women of European ancestry. However, the root cause for this disparity is not fully understood. In our previous studies, we show that the gene expression in the breast cancer stem cells of TNBC tumors was differential based on Western sub-Saharan ancestry. To study the role of African ancestry in the biology of TNBC, we have developed patient-derived organoids (PDO) from African (Ghanaian) and African American tumors that will be available for research. Organoid culture has the capacity to mimic the physiological tissue organization and functionality and has been used as an invaluable tool for disease modeling and drug discovery. Objective The objective is to develop and characterize PDOs based on African TNBC that will serve as a renewable source of African tumors for breast cancer research. Methods Through our international collaboration called Precision Medicine for Aggressive Breast Cancers (PMABC), we obtained fresh patient tumors from continental Africa (Ghana) and African American tumors from Henry Ford Health. PDOs were developed form both primary tumors and patient-derived xenografts (PDX). Tissues were processed using the Miltenyi Gentle Mac. The cells were seeded in a 12-well plate coated with Matrigel. Developed organoids are characterized using single cell RNA sequencing as well as 10X spatial sequencing Results We have successfully developed organoids using frozen tissues from both West African and African American breast patients. We have successfully established four (4) organoid lines from individual primary breast cancer tissues and one PDX. The organoids are passaged after every 7-14 days, and the highest passage so far is passage number 12 for the organoids from primary tissues and passage number 15 for the PDXs. We are in the process of characterizing the developed organoids using single-cell assay in comparisons to their primary tumor of origin. Conclusion Establishment of organoids has helped us have a renewable source of tumor for studying the aggressive TNBC among Women with African ancestry. We aim to use the organoids to identify tumor biomarkers for treating aggressive TNBC that disproportionately affects women of western sub Saharan ancestry. Citation Format: Moses Kamita, Kurt Fernando, Sylvester Antwi, Forster Amponsah-Manu, Josephine Nsaful, Kafui Akakpo, Jessica Bensenhaver, Kwabena Agbedinu, Michael Nortey, Nelson Affram, Mohammed Sheriff, Cassandra Mills, Alex Mremi, Jieoma Aja, Moses Dokurugu, Haythem Ali, Eleanor Walker, Max Wicha, Evelyn Jiagge. Organoid Culture as a Unique Resource for Studying Aggressive Triple Negative Breast Cancer in African American [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A060.