Cell Transcriptomic Data Research Articles

SNCA correlates with immune infiltration and serves as a prognostic biomarker in lung adenocarcinoma

BackgroundThe SNCA gene is a critical gene in Parkinson’s disease (PD) pathology. Accumulating evidence indicates that SNCA is involved in tumorigenesis; however, the role of SNCA in lung adenocarcinoma (LUAD) remains unclear. This study aimed to explore the potential value of SNCA as a prognostic and diagnostic molecular marker in LUAD.MethodsIn this study, we explored the expression pattern, prognostic value, and promoter methylation status of SNCA in LUAD based on Oncomine, UALCAN, and Kaplan–Meier Plotter. Then, using TIMER, we investigated the correlation between SNCA expression and immune infiltration. And cBioPortal were used to analysis the correlation between SNCA expression and immune checkpoint. The transcriptome data of A549 cells overexpressing SNCA were used to further study the potential immune role of SNCA in LUAD. The effect of SNCA on proliferation of A549 cells were evaluated by CCK-8, EdU and colony formation. Finally, LUAD cell lines treated with 5-aza-dC were used to explore the correlation between increased promoter methylation and downregulated mRNA expression of SNCA.ResultsIn general, the expression level of SNCA in LUAD tissue was lower than that in normal tissue, and high expression of SNCA was related to better prognosis.There were significant positive correlations between SNCA expression and immune infiltrations, including CD8+ T cells, macrophages, neutrophils, dendritic cells, B cells, and CD4+ T cells, and immune checkpoints, suggesting that immune infiltration was one of the reasons for the influence of SNCA on prognosis in LUAD. The transcriptome data of A549 cells overexpressing SNCA were further used to screen the relevant immune-related genes regulated by SNCA. Enrichment analysis confirmed that SNCA participates in the PI3K-AKT signaling pathway and other key tumor signaling pathways and regulates the expression of MAPK3, SRC, PLCG1, and SHC1. Cellular proliferation assay showed that SNCA could inhabit the growth of A549 cells via inhibiting activity of PI3K/AKT/ mTOR pathway. Finally, analysis of the methylation level of SNCA promoter showed that the promoter methylation negatively correlated with mRNA level. The expression of SNCA in LUAD cell lines was significantly upregulated by treatment with 5-aza-dC.ConclusionHigh methylation of SNCA promoter in LUAD is one of the reasons for the downregulation of SNCA mRNA level. Given that SNCA could inhibit the proliferation of A549 cells and correlates with immune infiltrates, it may serve as a prognostic biomarker in LUAD.

β-Sitosterol Inhibits Rheumatoid Synovial Angiogenesis Through Suppressing VEGF Signaling Pathway.

Background: Rheumatoid arthritis (RA) is a chronic disabling inflammatory disease that causes synovial angiogenesis in an invasive manner and leads to joint destruction. Currently available pharmacotherapy for RA has unwanted side effects and limitations. Although anti-angiogenic therapy is regarded as a new potential treatment for RA, only a few anti-angiogenic drugs are available. An increasing number of studies have shown that β-sitosterol (BSS) may exert inhibitory effects against angiogenesis. However, the mechanisms involved are still unclear. Methods: Based on the results of the gene set enrichment analysis (GSEA) of the transcriptome data of endothelial cells from RA patients, we evaluated the pharmacological effects of BSS on the tube formation, cell proliferation, and migration of human umbilical vein endothelial cells (HUVECs). Furthermore, the effects of BSS treatment on vascular endothelial growth factor receptor 2 (VEGFR2) were determined using molecular docking and Western blotting. Additionally, in the presence or absence of BSS, synovial angiogenesis and joint destruction of the ankle were investigated in collagen-induced arthritis (CIA) mice. The effect of BSS treatment on VEGFR2/p-VEGFR2 expression was verified through immunohistochemical staining. Results: The immunohistochemistry results revealed that BSS treatment inhibited angiogenesis both in vitro and in vivo. In addition, the results of 5-ethynyl-2′-deoxyuridine and cell cycle analysis showed that BSS treatment suppressed the proliferation of HUVECs, while the Transwell migration and stress fiber assays demonstrated that BSS treatment inhibited the migration of HUVECs. Notably, the inhibitory effect of BSS treatment on VEGFR2/p-VEGFR2 was similar to that of axitinib. In CIA mice, BSS also exerted therapeutic effects on the ankles by reducing the degree of swelling, ameliorating bone and cartilage damage, preventing synovial angiogenesis, and inhibiting VEGFR2 and p-VEGFR2 expression. Conclusion: Therefore, our findings demonstrate that BSS exerts an inhibitory effect on synovial angiogenesis by suppressing the proliferation and migration of endothelial cells, thereby alleviating joint swelling and bone destruction in CIA mice. Furthermore, the underlying therapeutic mechanisms may involve the inhibition of VEGF signaling pathway activation.

T-cell dysfunction in the glioblastoma microenvironment is mediated by myeloid cells releasing interleukin-10

Despite recent advances in cancer immunotherapy, certain tumor types, such as Glioblastomas, are highly resistant due to their tumor microenvironment disabling the anti-tumor immune response. Here we show, by applying an in-silico multidimensional model integrating spatially resolved and single-cell gene expression data of 45,615 immune cells from 12 tumor samples, that a subset of Interleukin-10-releasing HMOX1+ myeloid cells, spatially localizing to mesenchymal-like tumor regions, drive T-cell exhaustion and thus contribute to the immunosuppressive tumor microenvironment. These findings are validated using a human ex-vivo neocortical glioblastoma model inoculated with patient derived peripheral T-cells to simulate the immune compartment. This model recapitulates the dysfunctional transformation of tumor infiltrating T-cells. Inhibition of the JAK/STAT pathway rescues T-cell functionality both in our model and in-vivo, providing further evidence of IL-10 release being an important driving force of tumor immune escape. Our results thus show that integrative modelling of single cell and spatial transcriptomics data is a valuable tool to interrogate the tumor immune microenvironment and might contribute to the development of successful immunotherapies.

A systems genetics approach delineates the role of Bcl2 in leukemia pathogenesis

Leukemia is a group of malignancies of the blood forming tissues, and is characterized by the uncontrolled proliferation of blood cells. In the United States, it accounts for approximately 3.5% and 4% of all cancer-related incidences and mortalities, respectively. The current study aimed to explore the role of Bcl2 and associated genes in leukemia pathogenesis using a systems genetics approach. The transcriptome data from BXD Recombinant Inbred (RI) mice was analyzed to identify the expression of Bcl2 in myeloid cells. eQTL mapping was performed to select the potential chromosomal region and subsequently identify the candidate gene modulating the expression of Bcl2. Furthermore, gene enrichment and protein-protein interaction (PPI) analyses of the Bcl2-coexpressed genes were performed to demonstrate the role of Bcl2 in leukemia pathogenesis. The Bcl2-coexpressed genes were found to be enriched in various hematopoietic system related functions, and multiple pathways related to signaling, immune response, and cancer. The PPI network analysis demonstrated direct interaction of hematopoietic function related genes, such as Bag3, Bak1, Bcl2l11, Bmf, Mapk9, Myc, Ppp2r5c, and Ppp3ca with Bcl2. The eQTL mapping identified a 4.5 Mb genomic region on chromosome 11, potentially regulating the expression of Bcl2. A multi-criteria filtering process identified Top2a, among the genes located in the mapped locus, as the best candidate upstream regulator for Bcl2 expression variation. Hence, the current study provides better insights into the role of Bcl2 in leukemia pathogenesis and demonstrates the significance of our approach in gaining new knowledge on leukemia. Furthermore, our findings from the PPI network analysis and eQTL mapping provide supporting evidence of leukemia-associated genes, which can be further explored for their functional importance in leukemia. Data availabilityThe myeloid cell transcriptomic data of the BXD mice used in this study can be accessed through our GeneNetwork (http://www.genenetwork.org) with the accession number of GN144.

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC.

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). However, patients afflicted with pancreatic ductal carcinoma (PDAC), one of the deadliest malignancies, overwhelmingly exhibit negative responses to checkpoint therapy. We sought to combine data analysis and machine learning to differentiate the putative mechanisms of BCC and PDAC non-response. We discover that increased MHC-I expression in malignant cells and suppression of MHC and PD-1/PD-L expression in CD8+ T cells is associated with nonresponse to treatment. Furthermore, we leverage machine learning to predict response to PD-1 blockade on a cellular level. We confirm divergent resistance mechanisms between BCC, PDAC, and melanoma and highlight the potential for rapid and affordable testing of gene expression in BCC patients to accurately predict response to checkpoint therapies. Our findings present an optimistic outlook for the use of quantitative cross-cancer analyses in characterizing immune responses and predicting immunotherapy outcomes.

Senescence as a dictator of patient outcomes and therapeutic efficacies in human gastric cancer

Senescence is believed to be a pivotal player in the onset and progression of tumors as well as cancer therapy. However, the guiding roles of senescence in clinical outcomes and therapy selection for patients with cancer remain obscure, largely due to the absence of a feasible senescence signature. Here, by integrative analysis of single cell and bulk transcriptome data from multiple datasets of gastric cancer patients, we uncovered senescence as a veiled tumor feature characterized by senescence gene signature enriched, unexpectedly, in the noncancerous cells, and further identified two distinct senescence-associated subtypes based on the unsupervised clustering. Patients with the senescence subtype had higher tumor mutation loads and better prognosis as compared with the aggressive subtype. By the machine learning, we constructed a scoring system termed as senescore based on six signature genes: ADH1B, IL1A, SERPINE1, SPARC, EZH2, and TNFAIP2. Higher senescore demonstrated robustly predictive capability for longer overall and recurrence-free survival in 2290 gastric cancer samples, which was independently validated by the multiplex staining analysis of gastric cancer samples on the tissue microarray. Remarkably, the senescore signature served as a reliable predictor of chemotherapeutic and immunotherapeutic efficacies, with high-senescore patients benefited from immunotherapy, while low-senescore patients were responsive to chemotherapy. Collectively, we report senescence as a heretofore unrecognized hallmark of gastric cancer that impacts patient outcomes and therapeutic efficacy.

ORIGINS: A protein network-based approach to quantify cell pluripotency from scRNA-seq data

Trajectory inference is a common application of scRNA-seq data. However, it is often necessary to previously determine the origin of the trajectories, the stem or progenitor cells. In this work, we propose a computational tool to quantify pluripotency from single cell transcriptomics data. This approach uses the protein-protein interaction (PPI) network associated with the differentiation process as a scaffold and the gene expression matrix to calculate a score that we call differentiation activity. This score reflects how active the differentiation network is in each cell. We benchmark the performance of our algorithm with two previously published tools, LandSCENT (Chen et al., 2019) and CytoTRACE (Gulati et al., 2020), for four healthy human data sets: breast, colon, hematopoietic and lung. We show that our algorithm is more efficient than LandSCENT and requires less RAM memory than the other programs. We also illustrate a complete workflow from the count matrix to trajectory inference using the breast data set.•ORIGINS is a methodology to quantify pluripotency from scRNA-seq data implemented as a freely available R package.•ORIGINS uses the protein-protein interaction network associated with differentiation and the data set expression matrix to calculate a score (differentiation activity) that quantifies pluripotency for each cell.

3239 – DETERMINING THE MECHANISM BY WHICH RUNX1 LOSS LEADS TO AN INFLAMMATORY RESPONSE IN HEMATOPOIETIC CELLS

The transcription factor RUNX1 is often mutated in acute myeloid leukemia. Familial platelet disorder with associated myeloid malignancy (FPDMM) is caused by mutations in RUNX1 and is associated with an increased risk of leukemia. Many FPDMM patients have heightened inflammation. Inflammation can promote malignancies and understanding how RUNX1 mutations increase inflammation is critical for determining how to halt leukemia progression. We created a pan hematopoietic RUNX1 knockout (KO) mouse model and found that RUNX1 KO neutrophils overproduced cytokines in response to toll-like receptor 4 (TLR4) stimulation with lipopolysaccharide (LPS). The hyper-responsiveness of RUNX1 KO neutrophils correlated with increased expression of several genes encoding proteins in the TLR4 pathway. To determine if RUNX1 regulates TLR4 signaling in neutrophils, we deleted RUNX1 specifically in neutrophils. Unexpectedly, RUNX1 deletion did not cause an inflammatory phenotype, indicating that alterations in the TLR4 signaling pathway are established in a neutrophil precursor. Single cell transcriptomic data suggests that RUNX1 deficiency dysregulates TLR4 signaling in a precursor of neutrophils, specifically the granulocyte-monocyte progenitor (GMP) population. We determined that RUNX1 loss in GMPs was sufficient to establish the inflammatory phenotype in neutrophils. We performed ATAC-seq and found that RUNX1 loss led to chromatin opening at key TLR signaling genes. We determined that the inflammatory phenotype driven by the IRF and STAT family of transcription factors. Together this data suggests that the dysregulated inflammatory response of neutrophils is a downstream consequence of RUNX1 deletion in GMPs and can be dampened by inhibiting either the TLR4 or JAK/STAT signaling pathways. The transcription factor RUNX1 is often mutated in acute myeloid leukemia. Familial platelet disorder with associated myeloid malignancy (FPDMM) is caused by mutations in RUNX1 and is associated with an increased risk of leukemia. Many FPDMM patients have heightened inflammation. Inflammation can promote malignancies and understanding how RUNX1 mutations increase inflammation is critical for determining how to halt leukemia progression. We created a pan hematopoietic RUNX1 knockout (KO) mouse model and found that RUNX1 KO neutrophils overproduced cytokines in response to toll-like receptor 4 (TLR4) stimulation with lipopolysaccharide (LPS). The hyper-responsiveness of RUNX1 KO neutrophils correlated with increased expression of several genes encoding proteins in the TLR4 pathway. To determine if RUNX1 regulates TLR4 signaling in neutrophils, we deleted RUNX1 specifically in neutrophils. Unexpectedly, RUNX1 deletion did not cause an inflammatory phenotype, indicating that alterations in the TLR4 signaling pathway are established in a neutrophil precursor. Single cell transcriptomic data suggests that RUNX1 deficiency dysregulates TLR4 signaling in a precursor of neutrophils, specifically the granulocyte-monocyte progenitor (GMP) population. We determined that RUNX1 loss in GMPs was sufficient to establish the inflammatory phenotype in neutrophils. We performed ATAC-seq and found that RUNX1 loss led to chromatin opening at key TLR signaling genes. We determined that the inflammatory phenotype driven by the IRF and STAT family of transcription factors. Together this data suggests that the dysregulated inflammatory response of neutrophils is a downstream consequence of RUNX1 deletion in GMPs and can be dampened by inhibiting either the TLR4 or JAK/STAT signaling pathways.

Detection of A-to-I RNA Editing in SARS-COV-2.

ADAR1-mediated deamination of adenosines in long double-stranded RNAs plays an important role in modulating the innate immune response. However, recent investigations based on metatranscriptomic samples of COVID-19 patients and SARS-COV-2-infected Vero cells have recovered contrasting findings. Using RNAseq data from time course experiments of infected human cell lines and transcriptome data from Vero cells and clinical samples, we prove that A-to-G changes observed in SARS-COV-2 genomes represent genuine RNA editing events, likely mediated by ADAR1. While the A-to-I editing rate is generally low, changes are distributed along the entire viral genome, are overrepresented in exonic regions, and are (in the majority of cases) nonsynonymous. The impact of RNA editing on virus–host interactions could be relevant to identify potential targets for therapeutic interventions.

A Role for CXCR3 Ligands as Biomarkers of Post-Operative Crohn's Disease Recurrence.

Crohn's disease [CD] recurrence following ileocolic resection [ICR] is common. We sought to identify blood-based biomarkers associated with CD recurrence. CD patients undergoing ICR were recruited across six centres. Serum samples were obtained at post-operative colonoscopy. A multiplex immunoassay was used to analyse 92 inflammation-related proteins [Olink Proteomics]. Bayesian analysis was used to identify proteins associated with increasing Rutgeerts score. Identified proteins were used in receiver operating characteristic [ROC] analysis to examine the ability to identify CD recurrence [Rutgeerts score ≥i2]. Existing single cell data were interrogated to further elucidate the role of the identified proteins. Data from 276 colonoscopies in 213 patients were available. Median time from surgery to first and second colonoscopy was 7 (interquartile range [IQR] 6-9) and 19 [IQR 16-23] months, respectively. Disease recurrence was evident at 60 [30%] first and 36 [49%] second colonoscopies. Of 14 proteins significantly associated with Rutgeerts score, the strongest signal was seen for CXCL9 and MMP1. Among patients on anti-tumour necrosis factor drugs, CXCL9 and CXCL11 were most strongly associated with Rutgeerts score. Both are CXCR3 ligands. Incorporation of identified proteins into ROC analysis improved the ability to identify disease recurrence as compared to C-reactive protein alone: area under the curve [AUC] 0.75 (95% confidence interval [CI]: 0.66-0.82] vs 0.64 [95% CI 0.56-0.72], p = 0.012. Single cell transcriptomic data provide evidence that innate immune cells are the primary source of the identified proteins. CXCR3 ligands are associated with CD recurrence following ICR. Incorporation of novel blood-based candidate biomarkers may aid in identification of CD recurrence.

249 C-FOS drives reversible basal to squamous cell carcinoma transition

While squamous transdifferentiation within subpopulations of adenocarcinomas represents an important drug resistance problem, its’ underlying mechanism remain poorly understood. Here, using surface markers of resistant skin basal cell carcinomas (BCC-RM) and patient single cell and bulk transcriptomic data, we uncover the dynamic epigenetic roadmap of basal to squamous cell carcinoma transition (BST). Experimentally induced BST identifies AP1 family members in regulating tumor plasticity, and we show that c-FOS plays a central role in BST by regulating the accessibility of distinct AP1 regulatory elements.

BMP-treated human embryonic stem cells transcriptionally resemble amnion cells in the monkey embryo.

ABSTRACTHuman embryonic stem cells (hESCs) possess an immense potential to generate clinically relevant cell types and unveil mechanisms underlying early human development. However, using hESCs for discovery or translation requires accurately identifying differentiated cell types through comparison with their in vivo counterparts. Here, we set out to determine the identity of much debated BMP-treated hESCs by comparing their transcriptome to recently published single cell transcriptomic data from early human embryos ( Xiang et al., 2020). Our analyses reveal several discrepancies in the published human embryo dataset, including misclassification of putative amnion, intermediate and inner cell mass cells. These misclassifications primarily resulted from similarities in pseudogene expression, highlighting the need to carefully consider gene lists when making comparisons between cell types. In the absence of a relevant human dataset, we utilized the recently published single cell transcriptome of the early post implantation monkey embryo to discern the identity of BMP-treated hESCs. Our results suggest that BMP-treated hESCs are transcriptionally more similar to amnion cells than trophectoderm cells in the monkey embryo. Together with prior studies, this result indicates that hESCs possess a unique ability to form mature trophectoderm subtypes via an amnion-like transcriptional state.This article has an associated First Person interview with the first author of the paper.

Abstract MP49: Single Cell Multiplex Immunophenotyping Using Mass Cytometry And CITE-Seq Reveals Decreases In Circulating PD-1 + CD8 + Memory T Cells With Features Of Exhaustion In Human Hypertension

Emerging evidence from animal models has demonstrated the importance of multiple innate and adaptive immune cells in hypertension. We hypothesized that the abundance and phenotype of circulating immune cell subsets are altered in human hypertension. To test this, we performed high dimensional single cell profiling of human peripheral blood mononuclear cells using mass cytometry. Unsupervised computational analysis revealed a 40% decrease in CD8 + memory T cells in hypertensive individuals. Using Phenograph to identify subsets of these cells revealed a selective 60% decrease in PD-1 + CD8 + memory T cells in hypertension. This observation was confirmed in a validation cohort using flow cytometry in which PD-1 + CD8 + memory T cells were significantly decreased 44% in hypertensive compared to control individuals. To determine the phenotype of these PD-1 + CD8 + memory T cells, we performed Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) on four control and four hypertensive individuals. Using antibodies to identify PD-1 + and PD-1 - CD8 + memory T cells, gene set enrichment analysis of the coordinate single cell transcriptomic data revealed that PD-1 + cells exhibit over-representation of features of both immunologically active effector T cells and hypofunctional exhausted T cells. Thus, clustering analysis of PD-1 + CD8 + memory T cells was performed which demonstrated 4 distinct subclusters. One of these subclusters was decreased in hypertension and exhibited selective expression of multiple inhibitory receptors characteristic of exhausted T cells. At the protein level, this subcluster was marked by expression of the inhibitory receptor LAG3 and low levels of CD57. Combining these markers to identify PD-1 + LAG3 + CD57 - CD8 + memory T cells permitted identification of exhausted cells which demonstrated a significant 35% decrease in hypertensive compared to control individuals using flow cytometry. Taken together, these results demonstrate novel and reproducible decreases in circulating PD-1 + CD8 + memory T cells with features of exhaustion in human hypertension. These findings provide new insights into the pathogenesis of human hypertension including loss and/or re-invigoration of exhausted T cells.

Follistatin-Like-1 (FSTL1) Is a Fibroblast-Derived Growth Factor That Contributes to Progression of Chronic Kidney Disease.

Our understanding of the mechanisms responsible for the progression of chronic kidney disease (CKD) is incomplete. Microarray analysis of kidneys at 4 and 7 weeks of age in Col4a3-/- mice, a model of progressive nephropathy characterized by proteinuria, interstitial fibrosis, and inflammation, revealed that Follistatin-like-1 (Fstl1) was one of only four genes significantly overexpressed at 4 weeks of age. mRNA levels for the Fstl1 receptors, Tlr4 and Dip2a, increased in both Col4a-/- mice and mice subjected to unilateral ureteral obstruction (UUO). RNAscope® (Advanced Cell Diagnostics, Newark CA, USA) localized Fstl1 to interstitial cells, and in silico analysis of single cell transcriptomic data from human kidneys showed Fstl1 confined to interstitial fibroblasts/myofibroblasts. In vitro, FSTL1 activated AP1 and NFκB, increased collagen I (COL1A1) and interleukin-6 (IL6) expression, and induced apoptosis in cultured kidney cells. FSTL1 expression in the NEPTUNE cohort of humans with focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), and IgA nephropathy (IgAN) was positively associated with age, eGFR, and proteinuria by multiple linear regression, as well as with interstitial fibrosis and tubular atrophy. Clinical disease progression, defined as dialysis or a 40 percent reduction in eGFR, was greater in patients with high baseline FSTL1 mRNA levels. FSTL1 is a fibroblast-derived cytokine linked to the progression of experimental and clinical CKD.

Single Cell Transcriptomic of Cartilage Reveals Variable Trajectory of CSPCs in the Progression of Osteoarthritis

Background: Osteoarthritis (OA) is characterized as cartilage destruction and lack of specific drugs. Cartilage-derived stem cells or progenitor cells (CSPCs) as multipotent cells play an essential role in cartilage renewal. However, alteration of CSPCs in the process of osteoarthritis remains elusive. Thus, understanding the changing patterns of CSPCs in the pathologic process of OA is greatly highlighted to provide a new insight on stem cell therapy in osteoarthritis (OA). Methods: We downloaded single cell transcriptomic data of patients with OA from GEO database and performed them on Unbiased clustering of the cells based on gene expression pattern by using Seurat package. By using specific cell markers, we identified CSPCs from all chondrocyte. We further explored the dynamics of CSPCs in the progression of OA and validated the scRNA-seq data in vitro with qPCR, immunofluorescence and western blotting. Findings: By using pan stem-cell markers, we traced CSPCs through whole stages. Specifically, we found that the heterogeneity of CSPCs was tightly associated with the progressing of OA. Our results indicates that CSPCs displayed significantly reduced differentiation capacity in the late stage of OA, while the proliferation capacity tends to increase. We also found that genes implicating in fibrosis, cell motility and extracellular matrix (ECM) remodeling were upregulated in CSPCs upon the progression of OA. Interpretation: Our study uncovers a dynamic of stem cell in progression of OA and may inform the development of stem cell therapy for OA. Funding Information: This work was supported by grants from the National Natural Science Foundation of China (81771651) and Xu Jun′s expert work station (202005AF150050). Declaration of Interests: The authors confirm that there are no conflicts of interest. Ethics Approval Statement: All of the animal experiments in this study were approved by the Animal Care and Use Committee of Tongji University School of Medicine.

Identifying sub-populations of cells in single cell transcriptomic data - a Bayesian mixture model approach to zero-inflation of counts

Identifying sub-populations of cells in single cell transcriptomic data - a Bayesian mixture model approach to zero-inflation of counts

PseudoGA: cell pseudotime reconstruction based on genetic algorithm.

Dynamic regulation of gene expression is often governed by progression through transient cell states. Bulk RNA-seq analysis can only detect average change in expression levels and is unable to identify this dynamics. Single cell RNA-seq presents an unprecedented opportunity that helps in placing the cells on a hypothetical time trajectory that reflects gradual transition of their transcriptomes. This continuum trajectory or ‘pseudotime’, may reveal the developmental pathway and provide us with information on dynamic transcriptomic changes and other biological processes. Existing approaches to build pseudotime heavily depend on reducing huge dimension to extremely low dimensional subspaces and may lead to loss of information. We propose PseudoGA, a genetic algorithm based approach to order cells assuming that gene expressions vary according to a smooth curve along the pseudotime trajectory. We observe superior accuracy of our method in simulated as well as benchmarking real datasets. Generality of the assumption behind PseudoGA and no dependence on dimensionality reduction technique make it a robust choice for pseudotime estimation from single cell transcriptome data. PseudoGA is also time efficient when applied to a large single cell RNA-seq data and adaptable to parallel computing. R code for PseudoGA is freely available at https://github.com/indranillab/pseudoga.

Abstract 129: An integrated multi-omic cellular atlas of human breast cancers

Abstract Breast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of the cellular composition and organization of breast cancer remains limited. We present a comprehensive single cell and spatially resolved transcriptomic atlas of human breast cancers. The 10X Genomics Chromium platform was used to generate single cell transcriptomic data (scRNA-Seq) from more than 120,000 cells sampled from 26 breast cancers. CITE-Seq was employed to simultaneously generate protein measurements using a panel of 157 antibodies against immune, stromal and epithelial cell surface markers and analysed using Seurat. Using single cell signatures, we estimated the cellular composition of more than 2000 breast cancers in the Metabric cohort using deconvolution methods. Spatial transcriptomics was conducted on 12 frozen tissues (Luminal, Her2+ and triple negative breast cancer (TNBC)) using the 10X genomics Visium solution. We also used a novel Spatial Whole Transcriptome Panel, targeting 18,000+ genes on the Nanostring GeoMX platform, to profile T cells and malignant cells across multiple tissue niches from 16 TNBC FFPE cases. Integrative scRNA-Seq analysis identifies recurrent gene modules driving neoplastic cell heterogeneity, including interferon signaling, estrogen receptor function and mutually exclusive patterns of proliferation versus EMT. We also develop a single cell classifier of intrinsic subtype (scSubtype) to reveal frequent intra-tumoral heterogeneity for breast cancer intrinsic subtypes. CITE-Seq revealed immune profiles at high resolution, leading to the identification of novel macrophage populations with high expression of PD-L1 and PD-L2 immune checkpoint ligands and associations with clinical outcome. We also observe enrichment of exhausted and proliferative CD8 T cells in TNBC, with unique patterns of cell-surface checkpoint protein expression when compared to other subtypes. Targeted analysis using the GeoMX revealed spatial segregation of T cell phenotypes, with exhausted and proliferative CD8 T cells forming small clusters adjacent to tumor cells with high interferon pathway activity. Analysis of scRNA-Seq data revealed that stromal cells generate diverse functions and cell surface protein expression through differentiation within 3 major lineages: fibroblast, endothelial and perivascular-like. Subsets of stromal cells had features associated with immune regulation and Visium data revealed that stromal-immune niches were spatially organized in tumors, offering insights into anti-tumor immune suppression by stromal cells. Finally, deconvolution stratified >2000 breast cancer cases in Metabric into nine clusters, termed ‘ecotypes', with distinct cellular compositions and clinical outcomes. This study provides a comprehensive atlas of the cellular architecture of breast cancer. Citation Format: Sunny Z. Wu, Daniel Roden, Ghamdan Al Eryani, Simon Junankar, Elgene Lim, Aatish Thennavan, Alma Andersson, Stephen Williams, Jingjing Gong, Robin Fropf, Kit Fuhrman, Joakim Lundeberg, Chuck Perou, Alexander Swarbrick. An integrated multi-omic cellular atlas of human breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 129.

The effect of stress on the transcriptomes of circulating immune cells in patients with Gulf War Illness

AimsIn an effort to gain further insight into the underlying mechanisms tied to disease onset and progression of Gulf War Illness (GWI), our team evaluated GWI patient response to stress utilizing RNA-Seq. Main MethodsThe protocol included blood collection before exercise challenge (baseline), at maximal exertion, and after exercise challenge (recovery – four hours post-exercise challenge). Peripheral blood mononuclear cell (PBMC) transcriptomics data were analyzed to understand why GWI patients process stressors differently from their healthy counterparts. Key findingsOur findings validate previously identified dysregulation of immune and inflammatory pathways among GWI patients as well as highlight novel immune and inflammatory markers of disease activity. These results provide a foundation for future research efforts in understanding GWI pathophysiology and creating targeted treatments. SignificanceGulf War Illness is a complex, chronic, and debilitating multi-system illness impacting 25%–30% of the U.S. troops deployed to the 1990–1991 Gulf War. The condition is characterized by medically unexplained fatigue and affects multiple organ systems. Because the underlying mechanisms are largely unknown, patients receive symptom-based treatment, rather than targeting fundamental biological processes. To the best of our knowledge, this is the first study that applies RNA-Seq to analyze the effect of GWI, and the response to stressors in GWI, on the transcriptomic changes in circulating immune cells.

Potential Networks of Nitrogen-Phosphorus-Potassium Channels and Transporters in Arabidopsis Roots at a Single Cell Resolution.

Nitrogen (N), phosphorus (P), and potassium (K) are three major macronutrients essential for plant life. These nutrients are acquired and transported by several large families of transporters expressed in plant roots. However, it remains largely unknown how these transporters are distributed in different cell-types that work together to transfer the nutrients from the soil to different layers of root cells and eventually reach vasculature for massive flow. Using the single cell transcriptomics data from Arabidopsis roots, we profiled the transcriptional patterns of putative nutrient transporters in different root cell-types. Such analyses identified a number of uncharacterized NPK transporters expressed in the root epidermis to mediate NPK uptake and distribution to the adjacent cells. Some transport genes showed cortex- and endodermis-specific expression to direct the nutrient flow toward the vasculature. For long-distance transport, a variety of transporters were shown to express and potentially function in the xylem and phloem. In the context of subcellular distribution of mineral nutrients, the NPK transporters at subcellular compartments were often found to show ubiquitous expression patterns, which suggests function in house-keeping processes. Overall, these single cell transcriptomic analyses provide working models of nutrient transport from the epidermis across the cortex to the vasculature, which can be further tested experimentally in the future.