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Chen DQ, Zhou EQ, Chen HF, Zhan Y, Ye CJ, Li Y, Dai SY, Wang JF, Chen L, Dong KR, Dong R. Deciphering pathological behavior of pediatric medullary thyroid cancer from single-cell perspective. PeerJ 2023; 11:e15546. [PMID: 37744240 PMCID: PMC10517655 DOI: 10.7717/peerj.15546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 05/22/2023] [Indexed: 09/26/2023] Open
Abstract
Background Pediatric medullary thyroid cancer (MTC) is one of the rare pediatric endocrine neoplasms. Derived from C cells of thyroid glands, MTC is more aggressive and more prompt to metastasis than other types of pediatric thyroid cancer. The mechanism remains unclear. Methods We performed single-cell transcriptome sequencing on the samples of the primary tumor and metastases lymph nodes from one patient diagnosed with MTC, and it is the first single-cell transcriptome sequencing data of pediatric MTC. In addition, whole exome sequencing was performed and peripheral blood was regarded as a normal reference. All cells that passed quality control were merged and analyzed in R to discover the association between tumor cells and their microenvironment as well as tumor pathogenesis. Results We first described the landscape of the single-cell atlas of MTC and studied the interaction between the tumor cell and its microenvironment. C cells, identified as tumor cells, and T cells, as the dominant participant in the tumor microenvironment, were particularly discussed in their development and interactions. In addition, the WES signature of tumor cells and their microenvironment were also described. Actively immune interactions were found, indicating B cells, T cells and myeloid cells were all actively participating in immune reaction in MTC. T cells, as the major components of the tumor microenvironment, proliferated in MTC and could be divided into clusters that expressed proliferation, immune effectiveness, and naive markers separately.
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Affiliation(s)
- De-qian Chen
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - En-qing Zhou
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Hui-fen Chen
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Yong Zhan
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Chun-Jing Ye
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Yi Li
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Shu-yang Dai
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Jun-feng Wang
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Lian Chen
- Department of Pathology, Children’s Hospital of Fudan University, Fudan University, Shanghai, China
| | - Kui-ran Dong
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
| | - Rui Dong
- Department of Pediatric Surgery, Children’s Hospital of Fudan University, and Shanghai Key Laboratory of Birth Defect, Fudan University, Shanghai, China
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Bruchelt G, Klose C, Lischka M, Brandes M, Handgretinger R, Brueckner R. Hybrid Molecules of Benzylguanidine and the Alkylating Group of Melphalan: Synthesis and Effects on Neuroblastoma Cells. J Clin Med 2023; 12:4469. [PMID: 37445504 DOI: 10.3390/jcm12134469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 06/15/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023] Open
Abstract
The therapy of neuroblastoma relies, amongst other things, on administering chemotherapeutics and radioactive compounds, e.g., the (meta-iodobenzyl)guanidine [131I]mIBG. For special applications (conditioning before stem cell transplantation), busulfan and melphalan (M) proved to be effective. However, both drugs are not used for normal chemotherapy in neuroblastoma because of their side effects. The alkylating drug melphalan contains a (Cl-CH2-CH2-)2N- group in the para-position of the phenyl moiety of the essential amino acid phenylalanine (Phe) and can, therefore, be taken up by virtually all kinds of cells by amino acid transporters. In contrast, mIBG isotopologs are taken up more selectively by neuroblastoma cells via the noradrenaline transporter (NAT). The present study aimed at synthesising and studying hybrid molecules of benzylguanidine (BG) and the alkylating motif of M. Such hybrids should combine the preferential uptake of BGs into neuroblastoma cells with the cytotoxicity of M. Besides the hybrid of BG with the dialkylating group (Cl-CH2-CH2-)2N- bound in the para-position as in M (pMBG), we also synthesised mMBG, which is BG meta-substituted by a (Cl-CH2-CH2-)2N- group. Furthermore, two monoalkylating hybrid molecules were synthesised: the BG para-substituted by a (Cl-CH2-CH2-)NH- group (pM*BG) and the BG meta-substituted by a (Cl-CH2-CH2-)NH- group (mM*BG). The effects of the four new compounds were studied with human neuroblastoma cell lines (SK-N-SH, Kelly, and LS) with regard to uptake, viability, and proliferation by standard test systems. The dialkylating hybrid molecules pMBG and mMBG were at least as effective as M, whereas the monoalkylating hybrid molecules pM*BG and mM*BG were more effective than M. Considering the preferred uptake via the noradrenaline transporter by neuroblastoma cells, we conclude that they might be well suited for therapy.
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Affiliation(s)
- Gernot Bruchelt
- Children's University Hospital, Hoppe-Seyler-Str. 1, D-72076 Tuebingen, Germany
| | - Chihab Klose
- Children's University Hospital, Hoppe-Seyler-Str. 1, D-72076 Tuebingen, Germany
| | - Matthias Lischka
- Institute of Organic Chemistry, Albert-Ludwigs-University, Albertstr. 21, D-79104 Freiburg, Germany
| | - Marietta Brandes
- Children's University Hospital, Hoppe-Seyler-Str. 1, D-72076 Tuebingen, Germany
| | | | - Reinhard Brueckner
- Institute of Organic Chemistry, Albert-Ludwigs-University, Albertstr. 21, D-79104 Freiburg, Germany
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A Review of the Regulatory Mechanisms of N-Myc on Cell Cycle. Molecules 2023; 28:molecules28031141. [PMID: 36770809 PMCID: PMC9920120 DOI: 10.3390/molecules28031141] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 12/25/2022] [Accepted: 01/11/2023] [Indexed: 01/26/2023] Open
Abstract
Neuroblastoma has obvious heterogeneity. It is one of the few undifferentiated malignant tumors that can spontaneously degenerate into completely benign tumors. However, for its high-risk type, even with various intensive treatment options, the prognosis is still unsatisfactory. At the same time, a large number of research data show that the abnormal amplification and high-level expression of the MYCN gene are positively correlated with the malignant progression, poor prognosis, and mortality of neuroblastoma. In this context, this article explores the role of the N-Myc, MYCN gene expression product on its target genes related to the cell cycle and reveals its regulatory network in promoting tumor proliferation and malignant progression. We hope it can provide ideas and direction for the research and development of drugs targeting N-Myc and its downstream target genes.
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Single-Cell Sequencing Identifies Master Regulators Affected by Panobinostat in Neuroblastoma Cells. Genes (Basel) 2022; 13:genes13122240. [PMID: 36553506 PMCID: PMC9778475 DOI: 10.3390/genes13122240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/17/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022] Open
Abstract
The molecular mechanisms and gene regulatory networks sustaining cell proliferation in neuroblastoma (NBL) cells are still not fully understood. In this tumor context, it has been proposed that anti-proliferative drugs, such as the pan-HDAC inhibitor panobinostat, could be tested to mitigate tumor progression. Here, we set out to investigate the effects of panobinostat treatment at the unprecedented resolution offered by single-cell sequencing. We identified a global senescence signature paired with reduction in proliferation in treated Kelly cells and more isolated transcriptional responses compatible with early neuronal differentiation. Using master regulator analysis, we identified BAZ1A, HCFC1, MAZ, and ZNF146 as the transcriptional regulators most significantly repressed by panobinostat. Experimental silencing of these transcription factors (TFs) confirmed their role in sustaining NBL cell proliferation in vitro.
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Mercatelli D, Cabrelle C, Veltri P, Giorgi FM, Guzzi PH. Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data. Brief Bioinform 2022; 23:6695270. [DOI: 10.1093/bib/bbac400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/28/2022] [Accepted: 08/17/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as ‘signaling hubs’. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called ‘SURFACER’. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.
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Affiliation(s)
- Daniele Mercatelli
- Department of Pharmacy and Biotechnology, University of Bologna , 40138 Bologna , Italy
| | - Chiara Cabrelle
- Department of Pharmacy and Biotechnology, University of Bologna , 40138 Bologna , Italy
| | - Pierangelo Veltri
- Department of Surgical and Medical Sciences, Magna Graecia University , 88100 Catanzaro , Italy
| | - Federico M Giorgi
- Department of Pharmacy and Biotechnology, University of Bologna , 40138 Bologna , Italy
| | - Pietro H Guzzi
- Department of Surgical and Medical Sciences, Magna Graecia University , 88100 Catanzaro , Italy
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Cao YH, Ding J, Tang QH, Zhang J, Huang ZY, Tang XM, Liu JB, Ma YS, Fu D. Deciphering cell-cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing. Bioengineered 2022; 13:14974-14986. [PMID: 37105769 DOI: 10.1080/21655979.2023.2185434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023] Open
Abstract
A tumor's heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heterogeneous cells, evaluate the clonal origin of cancer cells, and determine the selective evolution of different subpopulations of cancer cells. Researchers are able to trace a cell's mutation and identify different types of tumor cells by measuring the whole transcriptome with single-cell sequencing (scRNA-seq). This technology provides a better understanding of the molecular mechanisms driving tumor growth than that offered by traditional RNA sequencing methods. In addition, it has revealed changes in the mutations and functions of somatic cells as a tumor evolves; it has also clarified immune cell infiltration and activation. Research on scRNA-seq technology has recently advanced significantly, suggesting new strategies for the treatment of cancer. In short, cancer researchers have become increasingly dependent on scRNA-seq. This paper reviews the development, detection principles, and processes of scRNA-seq technology and their application in tumor research. It also considers potential clinical applications.
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Affiliation(s)
- Ya-Hong Cao
- Department of Respiratory, Nantong Traditional Chinese Medicine Hospital, Affiliated Nantong Traditional Chinese Medicine Hospital of Nantong University, Nantong, Jiangsu, China
| | - Jie Ding
- Department of Clinical Laboratory, Jingjiang Traditional Chinese Medicine Hospital, Jingjiang, Jiangsu, China
| | - Qing-Hai Tang
- Hunan Key Laboratory for Conservation and Utilization of Biological Resources in the Nanyue Mountainous Region and College of Life Sciences and Environment, Hengyang Normal University, Hengyang, Hunan, China
| | - Jie Zhang
- Department of Immunology, School of Medicine, Nantong University, Nantong, Jiangsu, China
| | - Zhong-Yan Huang
- Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, Huangpu, China
| | - Xiao-Mei Tang
- Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, Huangpu, China
| | - Ji-Bin Liu
- Institute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, Jiangsu, China
| | - Yu-Shui Ma
- Cancer Institute, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, Xuhui, China
| | - Da Fu
- Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, Huangpu, China
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The R Language: An Engine for Bioinformatics and Data Science. Life (Basel) 2022; 12:life12050648. [PMID: 35629316 PMCID: PMC9148156 DOI: 10.3390/life12050648] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 04/21/2022] [Accepted: 04/23/2022] [Indexed: 12/14/2022] Open
Abstract
The R programming language is approaching its 30th birthday, and in the last three decades it has achieved a prominent role in statistics, bioinformatics, and data science in general. It currently ranks among the top 10 most popular languages worldwide, and its community has produced tens of thousands of extensions and packages, with scopes ranging from machine learning to transcriptome data analysis. In this review, we provide an historical chronicle of how R became what it is today, describing all its current features and capabilities. We also illustrate the major tools of R, such as the current R editors and integrated development environments (IDEs), the R Shiny web server, the R methods for machine learning, and its relationship with other programming languages. We also discuss the role of R in science in general as a driver for reproducibility. Overall, we hope to provide both a complete snapshot of R today and a practical compendium of the major features and applications of this programming language.
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Mercatelli D, Formaggio F, Caprini M, Holding A, Giorgi F. Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach. Biosci Rep 2021; 41:BSR20212218. [PMID: 34750607 PMCID: PMC8655506 DOI: 10.1042/bsr20212218] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/29/2021] [Accepted: 11/08/2021] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patients with breast cancer, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed 'SURFACER'. METHODS Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA versus normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2 and Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity. RESULTS Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of five BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms. CONCLUSIONS BRCA patients can be stratified into five surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.
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Affiliation(s)
- Daniele Mercatelli
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy
| | - Francesco Formaggio
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy
| | - Marco Caprini
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy
| | - Andrew Holding
- York Biomedical Research Institute, University of York, Heslington, York, YO10 5DD, U.K
| | - Federico M. Giorgi
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy
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Dorado G, Gálvez S, Rosales TE, Vásquez VF, Hernández P. Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review. Biomolecules 2021; 11:1111. [PMID: 34439777 PMCID: PMC8393538 DOI: 10.3390/biom11081111] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/12/2021] [Accepted: 07/23/2021] [Indexed: 02/06/2023] Open
Abstract
Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.
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Affiliation(s)
- Gabriel Dorado
- Dep. Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba, 14071 Córdoba, Spain
| | - Sergio Gálvez
- Dep. Lenguajes y Ciencias de la Computación, Boulevard Louis Pasteur 35, Universidad de Málaga, 29071 Málaga, Spain;
| | - Teresa E. Rosales
- Laboratorio de Arqueobiología, Avda. Universitaria s/n, Universidad Nacional de Trujillo, 13011 Trujillo, Peru;
| | - Víctor F. Vásquez
- Centro de Investigaciones Arqueobiológicas y Paleoecológicas Andinas Arqueobios, Martínez de Companón 430-Bajo 100, Urbanización San Andres, 13088 Trujillo, Peru;
| | - Pilar Hernández
- Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, 14080 Córdoba, Spain;
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Mercatelli D, Balboni N, Giorgio FD, Aleo E, Garone C, Giorgi FM. The Transcriptome of SH-SY5Y at Single-Cell Resolution: A CITE-Seq Data Analysis Workflow. Methods Protoc 2021; 4:mps4020028. [PMID: 34066513 PMCID: PMC8163004 DOI: 10.3390/mps4020028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/03/2021] [Accepted: 05/04/2021] [Indexed: 12/15/2022] Open
Abstract
Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) is a recently established multimodal single cell analysis technique combining the immunophenotyping capabilities of antibody labeling and cell sorting with the resolution of single-cell RNA sequencing (scRNA-seq). By simply adding a 12-bp nucleotide barcode to antibodies (cell hashing), CITE-seq can be used to sequence antibody-bound tags alongside the cellular mRNA, thus reducing costs of scRNA-seq by performing it at the same time on multiple barcoded samples in a single run. Here, we illustrate an ideal CITE-seq data analysis workflow by characterizing the transcriptome of SH-SY5Y neuroblastoma cell line, a widely used model to study neuronal function and differentiation. We obtained transcriptomes from a total of 2879 single cells, measuring an average of 1600 genes/cell. Along with standard scRNA-seq data handling procedures, such as quality checks and cell filtering procedures, we performed exploratory analyses to identify most stable genes to be possibly used as reference housekeeping genes in qPCR experiments. We also illustrate how to use some popular R packages to investigate cell heterogeneity in scRNA-seq data, namely Seurat, Monocle, and slalom. Both the CITE-seq dataset and the code used to analyze it are freely shared and fully reusable for future research.
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Affiliation(s)
- Daniele Mercatelli
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy;
- Correspondence: (D.M.); (F.M.G.); Tel.: +39-05-12094521 (F.M.G.)
| | - Nicola Balboni
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy;
| | - Francesca De Giorgio
- Department of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy; (F.D.G.); (C.G.)
- Center for Applied Biomedical Research (CRBA), University of Bologna, 40138 Bologna, Italy
| | | | - Caterina Garone
- Department of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy; (F.D.G.); (C.G.)
- Center for Applied Biomedical Research (CRBA), University of Bologna, 40138 Bologna, Italy
| | - Federico Manuel Giorgi
- Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy;
- Correspondence: (D.M.); (F.M.G.); Tel.: +39-05-12094521 (F.M.G.)
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