OTEH-11. Single Cell RNA Sequencing to identify cellular heterogeneity with in Pituitary Adenomas

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise approximately 15% of brain neoplasms. Most PA are histologically benign, but can cause significant morbidity. Previous studies utilized whole genome and exome sequencing to identify a few somatic variants, but no recurrent mutations were observed. Further studies are warranted to identify driver mutations occurring at low frequencies. We used single-cell RNA sequencing (10X Genomics) to investigate cellular heterogeneity in 12 non-functioning pituitary adenomas. Our analysis identified discrete clusters of cells associated with specific functional pathways. One of these clusters corresponded to cells expressing genes related to metabolic pathways, primarily lipid metabolism. Another cluster consistent amongst the three patients comprised cells involved in antigen presentation and processing. In addition, the copy number variation analysis highlighted distinct chromosomal alterations within our samples. Interestingly, we were able to identify clonal variations within each tumor based on chromosomal aberrations. For example, in our first patient we observed a gain of chromosome 19 and loss of chromosome 2. Our analysis showed three different clonal populations within this tumor. All three populations harbored the loss of chromosome 2, one population exhibited gain of chromosome 19, while a third population exhibited loss of chromosome 19. These early results indicate the loss of chromosome 2 as an early event in tumorigenesis and gain/loss of chromosome 19 as late events. We are currently in a process of identifying somatic variations within these tumors by variant calling. Currently we are expanding our analysis to 20 non-functional PA. Mapping the single-cell gene expression profiles with mutational phylogeny will reveal the differences in clonal evolution within the tumor subtypes. This study will help us define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized in the clinic for better management of these tumors.

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EPCO-37. USING SINGLE-CELL RNA SEQUENCING TO IDENTIFY CELLULAR HETEROGENEITY WITHIN NON-FUNCTIONING PITUITARY ADENOMAS

Neuro-Oncology ◽

10.1093/neuonc/noaa215.316 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii77-ii77

Author(s):

Saket Jain ◽

Husam Babikir ◽

Karin Shamardani ◽

Francisca CatalanSaavedra ◽

Aaron Diaz ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Pituitary Adenomas ◽

Expression Profiles ◽

Cellular Heterogeneity ◽

Chromosome 2 ◽

Chromosome 19 ◽

Recurrent Mutations ◽

Single Cell Rna Sequencing ◽

Non Functioning Pituitary Adenomas

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise approximately 15% of brain neoplasms. Most PA are histologically benign but can cause significant morbidity. Previous studies utilized whole-genome and exome sequencing to identify a few somatic variants, but no recurrent mutations were observed. Further studies are warranted to identify driver mutations occurring at low frequencies. We used single-cell RNA sequencing (10X Genomics) to investigate cellular heterogeneity in three non-functioning pituitary adenomas. Our analysis identified discrete clusters of cells associated with specific functional pathways. One of these clusters corresponded to cells expressing genes related to metabolic pathways, primarily lipid metabolism. Another cluster consistent amongst the three patients comprised of cells involved in antigen presentation and processing. In addition, the copy number variation analysis highlighted distinct chromosomal alterations within our samples. Interestingly, we were able to identify clonal variations within each tumor based on chromosomal aberrations. For example, in our first patient, we observed a gain of chromosome 19 and loss of chromosome 2. Our analysis showed three different clonal populations within this tumor. All three populations harbored the loss of chromosome 2, one population exhibited gain of chromosome 19, while a third population exhibited loss of chromosome 19. These early results indicate the loss of chromosome 2 as an early event in tumorigenesis and gain/loss of chromosome 19 as late events. We are currently in a process of identifying somatic variations within these tumors by variant calling. Currently we are expanding our analysis to 20 non-functional PA. Mapping the single-cell gene expression profiles with mutational phylogeny will reveal the differences in clonal evolution within the tumor subtypes. This study will help us define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized in the clinic for better management of these tumors.

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Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing

Gut ◽

10.1136/gutjnl-2019-320368 ◽

2020 ◽

pp. gutjnl-2019-320368 ◽

Cited By ~ 1

Author(s):

Min Zhang ◽

Shuofeng Hu ◽

Min Min ◽

Yanli Ni ◽

Zheng Lu ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Gastric Adenocarcinoma ◽

Expression Profiles ◽

Chief Cell ◽

The Other ◽

Cellular Heterogeneity ◽

Fundic Gland ◽

Tumour Heterogeneity ◽

Single Cell Rna Sequencing

ObjectiveTumour heterogeneity represents a major obstacle to accurate diagnosis and treatment in gastric adenocarcinoma (GA). Here, we report a systematic transcriptional atlas to delineate molecular and cellular heterogeneity in GA using single-cell RNA sequencing (scRNA-seq).DesignWe performed unbiased transcriptome-wide scRNA-seq analysis on 27 677 cells from 9 tumour and 3 non-tumour samples. Analysis results were validated using large-scale histological assays and bulk transcriptomic datasets.ResultsOur integrative analysis of tumour cells identified five cell subgroups with distinct expression profiles. A panel of differentiation-related genes reveals a high diversity of differentiation degrees within and between tumours. Low differentiation degrees can predict poor prognosis in GA. Among them, three subgroups exhibited different differentiation grade which corresponded well to histopathological features of Lauren’s subtypes. Interestingly, the other two subgroups displayed unique transcriptome features. One subgroup expressing chief-cell markers (eg, LIPF and PGC) and RNF43 with Wnt/β-catenin signalling pathway activated is consistent with the previously described entity fundic gland-type GA (chief cell-predominant, GA-FG-CCP). We further confirmed the presence of GA-FG-CCP in two public bulk datasets using transcriptomic profiles and histological images. The other subgroup specifically expressed immune-related signature genes (eg, LY6K and major histocompatibility complex class II) with the infection of Epstein-Barr virus. In addition, we also analysed non-malignant epithelium and provided molecular evidences for potential transition from gastric chief cells into MUC6+TFF2+ spasmolytic polypeptide expressing metaplasia.ConclusionAltogether, our study offers valuable resource for deciphering gastric tumour heterogeneity, which will provide assistance for precision diagnosis and prognosis.

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Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

Genome Medicine ◽

10.1186/s13073-021-00885-z ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Sunny Z. Wu ◽

Daniel L. Roden ◽

Ghamdan Al-Eryani ◽

Nenad Bartonicek ◽

Kate Harvey ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Single Cells ◽

Cellular Heterogeneity ◽

Tumour Heterogeneity ◽

Fresh Tissue ◽

Human Cancers ◽

Cryopreserved Cell ◽

Single Cell Rna Sequencing

Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

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MBRS-46. CHARTING NEOPLASTIC AND IMMUNE CELL HETEROGENEITY IN HUMAN AND GEM MODELS OF MEDULLOBLASTOMA USING scRNAseq

Neuro-Oncology ◽

10.1093/neuonc/noaa222.555 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii406-iii406

Author(s):

Andrew Donson ◽

Kent Riemondy ◽

Sujatha Venkataraman ◽

Ahmed Gilani ◽

Bridget Sanford ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Immune Cell ◽

Genetically Engineered ◽

Cellular Heterogeneity ◽

Cell Heterogeneity ◽

Transcriptomic Data ◽

Single Cell Rna Sequencing ◽

Transcript Profiles

Abstract We explored cellular heterogeneity in medulloblastoma using single-cell RNA sequencing (scRNAseq), immunohistochemistry and deconvolution of bulk transcriptomic data. Over 45,000 cells from 31 patients from all main subgroups of medulloblastoma (2 WNT, 10 SHH, 9 GP3, 11 GP4 and 1 GP3/4) were clustered using Harmony alignment to identify conserved subpopulations. Each subgroup contained subpopulations exhibiting mitotic, undifferentiated and neuronal differentiated transcript profiles, corroborating other recent medulloblastoma scRNAseq studies. The magnitude of our present study builds on the findings of existing studies, providing further characterization of conserved neoplastic subpopulations, including identification of a photoreceptor-differentiated subpopulation that was predominantly, but not exclusively, found in GP3 medulloblastoma. Deconvolution of MAGIC transcriptomic cohort data showed that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. In both GP3 and GP4, higher proportions of undifferentiated subpopulations is associated with shorter survival and conversely, differentiated subpopulation is associated with longer survival. This scRNAseq dataset also afforded unique insights into the immune landscape of medulloblastoma, and revealed an M2-polarized myeloid subpopulation that was restricted to SHH medulloblastoma. Additionally, we performed scRNAseq on 16,000 cells from genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models showed a level of fidelity with corresponding human subgroup-specific neoplastic and immune subpopulations. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.

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Single-cell RNA sequencing of cultured human endometrial CD140b+CD146+ perivascular cells highlights the importance of in vivo microenvironment

Stem Cell Research & Therapy ◽

10.1186/s13287-021-02354-1 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Dandan Cao ◽

Rachel W. S. Chan ◽

Ernest H. Y. Ng ◽

Kristina Gemzell-Danielsson ◽

William S. B. Yeung

Keyword(s):

Stem Cells ◽

Single Cell ◽

Rna Sequencing ◽

Marker Gene ◽

Cellular Heterogeneity ◽

Stromal Fibroblast ◽

Perivascular Cells ◽

Endometrial Cells ◽

Single Cell Rna Sequencing

Abstract Background Endometrial mesenchymal-like stromal/stem cells (eMSCs) have been proposed as adult stem cells contributing to endometrial regeneration. One set of perivascular markers (CD140b&CD146) has been widely used to enrich eMSCs. Although eMSCs are easily accessible for regenerative medicine and have long been studied, their cellular heterogeneity, relationship to primary counterpart, remains largely unclear. Methods In this study, we applied 10X genomics single-cell RNA sequencing (scRNA-seq) to cultured human CD140b+CD146+ endometrial perivascular cells (ePCs) from menstrual and secretory endometrium. We also analyzed publicly available scRNA-seq data of primary endometrium and performed transcriptome comparison between cultured ePCs and primary ePCs at single-cell level. Results Transcriptomic expression-based clustering revealed limited heterogeneity within cultured menstrual and secretory ePCs. A main subpopulation and a small stress-induced subpopulation were identified in secretory and menstrual ePCs. Cell identity analysis demonstrated the similar cellular composition in secretory and menstrual ePCs. Marker gene expression analysis showed that the main subpopulations identified from cultured secretory and menstrual ePCs simultaneously expressed genes marking mesenchymal stem cell (MSC), perivascular cell, smooth muscle cell, and stromal fibroblast. GO enrichment analysis revealed that genes upregulated in the main subpopulation enriched in actin filament organization, cellular division, etc., while genes upregulated in the small subpopulation enriched in extracellular matrix disassembly, stress response, etc. By comparing subpopulations of cultured ePCs to the publicly available primary endometrial cells, it was found that the main subpopulation identified from cultured ePCs was culture-unique which was unlike primary ePCs or primary endometrial stromal fibroblast cells. Conclusion In summary, these data for the first time provides a single-cell atlas of the cultured human CD140b+CD146+ ePCs. The identification of culture-unique relatively homogenous cell population of CD140b+CD146+ ePCs underscores the importance of in vivo microenvironment in maintaining cellular identity.

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Single-Cell RNA-Sequencing Identifies Infrapatellar Fat Pad Macrophage Polarization in Acute Synovitis/Fat Pad Fibrosis and Cell Therapy

Bioengineering ◽

10.3390/bioengineering8110166 ◽

2021 ◽

Vol 8 (11) ◽

pp. 166

Author(s):

Dimitrios Kouroupis ◽

Thomas M. Best ◽

Lee D. Kaplan ◽

Diego Correa ◽

Anthony J. Griswold

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Transcriptional Profiling ◽

Macrophage Polarization ◽

Myeloid Cells ◽

Cellular Heterogeneity ◽

Joint Disease ◽

Infrapatellar Fat Pad ◽

Fat Pad ◽

Single Cell Rna Sequencing

The pathogenesis and progression of knee inflammatory pathologies is modulated partly by residing macrophages in the infrapatellar fat pad (IFP), thus, macrophage polarization towards pro-inflammatory (M1) or anti-inflammatory (M2) phenotypes is important in joint disease pathologies. Alteration of M1/M2 balance contributes to the initiation and progression of joint inflammation and can be potentially altered with mesenchymal stem cell (MSC) therapy. In an acute synovial/IFP inflammation rat model a single intra-articular injection of IFP-MSC was performed, having as controls (1) diseased rats not receiving IFP-MSC and (2) non-diseased rats. After 4 days, cell specific transcriptional profiling via single-cell RNA-sequencing was performed on isolated IFP tissue from each group. Eight transcriptomically distinct cell populations were identified within the IFP across all three treatment groups with a noted difference in the proportion of myeloid cells across the groups. Largely myeloid cells consisted of macrophages (>90%); one M1 sub-cluster highly expressing pro-inflammatory markers and two M2 sub-clusters with one of them expressing higher levels of canonical M2 markers. Notably, the diseased samples (11.9%) had the lowest proportion of cells expressing M2 markers relative to healthy (14.8%) and MSC treated (19.4%) samples. These results suggest a phenotypic polarization of IFP macrophages towards the pro-inflammatory M1 phenotype in an acute model of inflammation, which are alleviated by IFP-MSC therapy inducing a switch towards an alternate M2 status. Understanding the IFP cellular heterogeneity and associated transcriptional programs may offer insights into novel therapeutic strategies for disabling joint disease pathologies.

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Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing

Cephalalgia ◽

10.1177/0333102418762476 ◽

2018 ◽

Vol 38 (13) ◽

pp. 1976-1983 ◽

Cited By ~ 5

Author(s):

William Renthal

Keyword(s):

Human Brain ◽

Single Cell ◽

Rna Sequencing ◽

Expression Profiles ◽

Cell Types ◽

Susceptibility Genes ◽

Brain Cell ◽

Cell Type ◽

Single Cell Rna Sequencing ◽

Brain Cell Types

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

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EPCO-28. SINGLE-CELL RNA SEQUENCING IDENTIFIES INTRATUMORAL HETEROGENEITY AND ACTIVATION OF PRO-INVASIVE PATHWAYS IN NON-FUNCTIONING PITUITARY ADENOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.027 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi8-vi8

Author(s):

Saket Jain ◽

Elaina Wang ◽

Husam Babikir ◽

Karin Shamardani ◽

Aaron Diaz ◽

...

Keyword(s):

Copy Number Variation ◽

Wnt Signaling ◽

Single Cell ◽

Rna Sequencing ◽

Pituitary Adenomas ◽

Copy Number ◽

Variation Analysis ◽

Copy Number Variation Analysis ◽

Single Cell Rna Sequencing ◽

Number Variation

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise 15% of brain neoplasms. Most PAs are histologically benign but can cause significant morbidity. The genetic profile of PAs is poorly understood. We used single-cell RNA sequencing using the 10X genomic platform to investigate cellular heterogeneity in twelve non-functioning pituitary adenoma samples from nine patients including site-specific (core vs edge) samples from three patients. Our analysis identified discrete clusters of cells associated with activation of specific functional pathways including lipid metabolism, angiogenic, and antigen presentation and processing pathways regardless of location within the tumor. MALT1, a lncRNA associated with increased proliferation and metastasis was ubiquitously expressed amongst these samples. Analysis of the core vs edge samples showed two specific clusters with activated invasion-promoting pathways including PI3k/AKT signaling, Wnt signaling (Wnt6 and FZD4), and epithelial-mesenchymal transition (TGFB1, SMAD1, ZEB1, and SNAI2) in the edge of the tumors. The activated Wnt signaling cascade drove a proinflammatory tumor microenvironment induced by the expression of IL-1, IL-17, and Toll-like receptors (TLR6 and TLR7/8) resulting in suppression of Tregs. Copy number variation analysis using the CONICS-CNV algorithm highlighted distinct chromosomal alterations within our samples that led to insight into clonal variations within each tumor with loss of chromosome 2 an early event in tumorigenesis and gain/loss of chromosome 19 as late events. Mapping the copy number variation analysis with the somatic variant analysis using the Vartrix algorithm identified novel driver mutations within these tumors. These findings help define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized for better management of these tumors.

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Microbial single-cell RNA sequencing by split-pool barcoding

Science ◽

10.1126/science.aba5257 ◽

2020 ◽

Vol 371 (6531) ◽

pp. eaba5257 ◽

Cited By ~ 2

Author(s):

Anna Kuchina ◽

Leandra M. Brettner ◽

Luana Paleologu ◽

Charles M. Roco ◽

Alexander B. Rosenberg ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Single Cell Analysis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Growth Stages ◽

High Throughput Analysis ◽

Single Cell Rna Sequencing

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

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