Identification of Myeloma-Initiating Cells By Single-Cell RNA Sequencing

Abstract Background: The outcomes of patients with multiple myeloma (MM) have improved due to treatment advances. However, some patients still experience rapid progression, multiple drug resistance or recurrent relapse. Tumor-initiating cells, also known as cancer stem cells (CSC) in some cancer types, have been speculated to induce recurrence of the disease. The aim of this study is to infer the identity of myeloma-initiating cells (MICs) utilizing single-cell transcriptome analysis and explore the unique biological characteristics relating with high-risk and drug-resistance. Method: We applied single cell RNA sequencing to fresh bone marrow mononuclear cell samples collecting from 7 healthy donors and 12 newly diagnosed MM patients utilizing 10x Chromium platform. Results: Firstly, we segregated the patients by tumor cell infiltration at single cell resolution and found that Myc pathway was significantly enriched in patients with high tumor burden (HTB). Next, we performed clustering analysis to tumor cells and identified 13 tumor subpopulations in total. Surprisingly, the distribution pattern of tumor subpopulations presented similarity among HTB patients, whereas we did not find the uniform subpopulation composition among the patients with low (LTB) or medium tumor burden (MTB). Via the tumor subpopulation analysis, we clarified the divergence in biological characteristics of these 13 malignant subpopulations. We identified plasmablasts as displaying high expression of B-cell gene signatures (CD19, CD27, MS4A1 and CD79B) and relatively low expression of plasma cell gene signatures (SDC1 and BCMA). Additionally, we also noted that they showed high level of CD24, which has been validated to be the marker gene for MICs. We next examined proliferative capability and utilized the 70 high-risk gene model and 56 drug resistance-related gene model to further distinguish subpopulations with the most malignant gene expression features. Notably, we found that plasmablasts possessed characteristics of high proliferation, drug-resistance and high-risk gene profiling, indicating their role as the root of myeloma, namely MIC subpopulation. Gene enrichment analysis also implicated that Wnt pathway, Notch pathway, stem cell differentiation pathway and Hedgehog pathway were enriched in MIC subpopulation which were associated with the proliferation, migration and drug resistance of MM. Differentially expressed gene (DEG) analysis showed that common driver genes in myeloma, such as CCND2, ITGB7 and CD74, were upregulated in MIC subpopulation comparing with other subpopulations. Conclusion: Our work presents an integral profiling for tumor cells in myeloma at single cell resolution. We uncovered divergence in the distribution of malignant subclusters across patients and distinct heterogeneity in gene expression across malignant subclusters as well. Plasmablasts expressing high level of CD24, CD27 and dim CD138 presented as the MICs with characteristics of higher proliferation, drug-resistance and high-risk gene profiling. Disclosures No relevant conflicts of interest to declare.

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GnRH and gpcr: laser-captured single cell gene profiling

Fish Physiology and Biochemistry ◽

10.1007/s10695-006-0018-1 ◽

2005 ◽

Vol 31 (2-3) ◽

pp. 153-156 ◽

Cited By ~ 6

Author(s):

Ishwar S. Parhar

Keyword(s):

Single Cell ◽

Gene Profiling ◽

Cell Gene

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Single-cell gene profiling defines differential progenitor subclasses in mammalian neurogenesis

Development ◽

10.1242/dev.022616 ◽

2008 ◽

Vol 135 (18) ◽

pp. 3113-3124 ◽

Cited By ~ 129

Author(s):

A. Kawaguchi ◽

T. Ikawa ◽

T. Kasukawa ◽

H. R. Ueda ◽

K. Kurimoto ◽

...

Keyword(s):

Single Cell ◽

Gene Profiling ◽

Cell Gene

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Single Cell Gene Transcriptome Analysis of Ovarian Mature Teratomas

Pathology & Oncology Research ◽

10.3389/pore.2021.604228 ◽

2021 ◽

Vol 27 ◽

Author(s):

Sun Shin ◽

Youn Jin Choi ◽

Seung-Hyun Jung ◽

Yeun-Jun Chung ◽

Sug Hyung Lee

Keyword(s):

Single Cell ◽

Germ Cells ◽

Expression Profiles ◽

Cell Types ◽

Cell Tumor ◽

Single Cell Level ◽

Cell Level ◽

Normal Cells ◽

Single Cell Rna Sequencing ◽

Cell Gene

Teratoma is a type of germ cell tumor that originates from totipotential germ cells that are present in gonads, which can differentiate into any of the cell types found in adult tissues. Ovarian teratomas are usually mature cystic teratomas (OMCTs, also known as dermoid cysts). Chromosome studies in OMCTs show that the chromosomes are uniformly homozygous with karyotype of 46, XX, indicating that they may be parthenogenic tumors that arise from a single ovum after thefirst meiotic division. However, the tissues in OMCTs have been known to be morphologically and immunophenotypically identical to the orthotopic tissues. Currently, expression profiles of tissue components in OMCTs are not known. To identify whether OMCT tissues are expressionally similar to or different from the orthotopic tissues, we adopted single-cell RNA-sequencing (scRNA-seq), and analyzed transcriptomes of individual cells in heterogenous tissues of two OMCTs. We found that transcriptome profiles of the OMCTs at single cell level were not significantly different from those of normal cells in orthotopic locations. The present data suggest that parthenogeneticlly altered OMCTs may not alter expression profiles of inrivirual tissue components in OMCTs.

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Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.729485 ◽

2022 ◽

Vol 9 ◽

Author(s):

Tianying Tong ◽

Jie Zhang ◽

Xiaoqiang Zhu ◽

Pingping Hui ◽

Zhimin Wang ◽

...

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Single Cell ◽

Rna Sequencing ◽

Immune Checkpoint ◽

Risk Model ◽

Risk Group ◽

High Risk Group ◽

Related Model ◽

Single Cell Rna Sequencing

Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencing, an autophagy-related risk model was identified. The model was capable of distinguishing the worse prognosis of patients with gastric cancer (GC), which was validated in TCGA and two independent Gene Expression Omnibus cohorts utilizing the survival analysis, and was also independent of other clinical covariates evaluated by multivariable Cox regression. The clinical value of this model was further assessed using a receiver operating characteristic (ROC) and nomogram analysis. Investigation of single-cell RNA sequencing uncovered that this model might act as an indicator of the dysfunctional characteristics of T cells in the high-risk group. Moreover, the high-risk group exhibited the lower expression of immune checkpoint markers (PDCD1 and CTLA4) than the low-risk group, which indicated the potential predictive power to the current immunotherapy response in patients with GC. In conclusion, this autophagy-associated risk model may be a useful tool for prognostic evaluation and will facilitate the potential application of this model as an indicator of the predictive immune checkpoint biomarkers.

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Single-cell gene profiling and lineage tracing analyses revealed novel mechanisms of endothelial repair by progenitors

Cellular and Molecular Life Sciences ◽

10.1007/s00018-020-03480-4 ◽

2020 ◽

Vol 77 (24) ◽

pp. 5299-5320

Author(s):

Jiacheng Deng ◽

Zhichao Ni ◽

Wenduo Gu ◽

Qishan Chen ◽

Witold Norbert Nowak ◽

...

Keyword(s):

Single Cell ◽

Lineage Tracing ◽

Gene Profiling ◽

Endothelial Repair ◽

Cell Gene

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Single-cell gene profiling of planarian stem cells using fluorescent activated cell sorting and its “index sorting” function for stem cell research

Development Growth & Differentiation ◽

10.1111/j.1440-169x.2009.01157.x ◽

2010 ◽

Vol 52 (1) ◽

pp. 131-144 ◽

Cited By ~ 76

Author(s):

Tetsutaro Hayashi ◽

Norito Shibata ◽

Ryo Okumura ◽

Tomomi Kudome ◽

Osamu Nishimura ◽

...

Keyword(s):

Stem Cells ◽

Stem Cell ◽

Single Cell ◽

Stem Cell Research ◽

Cell Sorting ◽

Gene Profiling ◽

Cell Gene ◽

Index Sorting

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Single Cell Gene Profiling Revealed Heterogeneity of Paracrine Effects of Bone Marrow Cells in Mouse Infarcted Hearts

PLoS ONE ◽

10.1371/journal.pone.0068270 ◽

2013 ◽

Vol 8 (7) ◽

pp. e68270 ◽

Cited By ~ 3

Author(s):

Yanhua Li ◽

Xinhong Guo ◽

Qiao Xue ◽

Mei Zhu ◽

Lei Gao ◽

...

Keyword(s):

Bone Marrow ◽

Single Cell ◽

Bone Marrow Cells ◽

Gene Profiling ◽

Paracrine Effects ◽

Cell Gene ◽

Marrow Cells

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Circulating immune cell phenotype dynamics reflect the strength of tumor-immune cell interactions in patients during immunotherapy

10.1101/2020.03.24.993923 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jason I Griffiths ◽

Pierre Wallet ◽

Lance T. Pflieger ◽

David Stenehjem ◽

Xuan Liu ◽

...

Keyword(s):

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Cell Interaction ◽

Tumor Burden ◽

Predator Prey ◽

Cell Abundance ◽

Single Cell Rna Sequencing ◽

Peripheral Immune Cell ◽

Cell Phenotypes

AbstractThe extent that immune cell phenotypes in the peripheral blood reflect within-tumor immune activity prior to and early in cancer therapy is unclear. To address this question, we studied the population dynamics of tumor and immune cells, and immune phenotypic changes, using clinical tumor and immune cell measurements and single cell genomic analyses. These samples were serially obtained from a cohort of advanced gastrointestinal cancer patients enrolled on a trial with chemotherapy and immunotherapy. Using an ecological population model, fitted to clinical tumor burden and immune cell abundance data from each patient, we find evidence of a strong tumor-circulating immune cell interaction in responder patients, but not those patients that progress on treatment. Upon initiation of therapy, immune cell abundance increased rapidly in responsive patients, and once the peak level is reached, tumor burden decreases, similar to models of predator-prey interactions; these dynamic patterns were absent in non-responder patients. To interrogate phenotype dynamics of circulating immune cells, we performed single cell RNA sequencing at serial time points during treatment. These data show that peripheral immune cell phenotypes were linked to the increased strength of patients’ tumor-immune cell interaction, including increased cytotoxic differentiation and strong activation of interferon signaling in peripheral T-cells in responder patients. Joint modeling of clinical and genomic data highlights the interactions between tumor and immune cell populations and reveals how variation in patient responsiveness can be explained by differences in peripheral immune cell signaling and differentiation soon after the initiation of immunotherapy.One sentence summaryPeripheral immune cell differentiation and signaling, upon initiation of immunotherapy, reflects tumor attacking ability and patient response.Significance statementThe evolution of peripheral immune cell abundance and signaling over time, as well as how these immune cells interact with the tumor, may impact a cancer patient’s response to therapy. By developing an ecological population model, we provide evidence of a dynamic predator-prey like relationship between circulating immune cell abundance and tumor size in patients that respond to immunotherapy. This relationship is not found either in patients that are non-responsive to immunotherapy or during chemotherapy. Single cell RNA-sequencing (scRNAseq) of serial peripheral blood samples from patients show that the strength of tumor-immune cell interactions is reflected in T-cells interferon activation and differentiation early in treatment. Thus, circulating immune cell dynamics reflect a tumor’s response to immunotherapy.

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