Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview

Slovin, Shaked; Carissimo, Annamaria; Panariello, Francesco; Grimaldi, Antonio; Bouché, Valentina; Gambardella, Gennaro; Cacchiarelli, Davide

doi:10.1007/978-1-0716-1307-8_19

Cited by 111 publications

(99 citation statements)

References 90 publications

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“…We first used "NormalizeData" to standardize the data, then used "RunPCA" for principal component analysis. Finally, single-cell samples were clustered using the k-nearest neighbor classification (KNN) algorithm through "FindNeighbors" and "FindClusters" [ 10 ].…”

Section: Methodsmentioning

confidence: 99%

Single-cell sequencing analysis reveals gastric cancer microenvironment cells respond vastly different to oxidative stress

Chen

Yan

et al. 2022

J Transl Med

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Gastric cancer is a common type of gastrointestinal malignant tumor in China. The mechanism of the development and progression of gastric cancer remains the continuing research focus. The tumor microenvironment plays an important role in the development and progression of tumors. The present study used single-cell sequencing data to characterize the microenvironment of gastric cancer, investigate the effects of oxidative stress on gastric cancer microenvironmental cells through the comparison between cancer tissue and normal tissue, and identify the key genes associated with gastric cancer patients’ survival. The results showed that compared with normal gastric tissue, gastric cancer tissue had a decreased oxidative stress response, weaker oxidative detoxification ability, and increased oxidative stress-induced cell death. In the different types of single cells of gastric cancer microenvironment, the oxidative stress response of T cell was increased, the ability of oxidative detoxification was enhanced, and the oxidative stress-induced cell death was exacerbate. Mucous cell showed the same trend as gastric cancer cells: decreased oxidative stress response, weak oxidative detoxification ability, and weakened oxidative stress-induced cell death. Moreover, TRIM62, MET, and HBA1, which were significantly associated with oxidative stress, may be biomarkers for the prognosis of gastric cancer. High expression of TRIM62 indicated a good prognosis, while MET and HBA1 indicated a poor prognosis, which will be confirmed by further clinical studies.

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Section: Methodsmentioning

confidence: 99%

Single-cell sequencing analysis reveals gastric cancer microenvironment cells respond vastly different to oxidative stress

Chen

Yan

et al. 2022

J Transl Med

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“…Highly dimensional scRNA-Seq data were analyzed using the SeqGeq software (FlowJo) for visualization, clustering by Phenograph algorithm [ 23 ] and differential expression analysis. The workflow based on the SCANPY software was also applied [ 24 , 25 ]. The count matrices of various single-cell experiments were read using the Pandas Python library and cells from different experiments were concatenated in a single data frame, keeping track of the sample group origin (COVID or control), the counts for different genes and cell type.…”

Section: Methodsmentioning

confidence: 99%

COVID-19 Specific Immune Markers Revealed by Single Cell Phenotypic Profiling

et al. 2021

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COVID-19 is a viral infection, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and characterized by a complex inflammatory process and clinical immunophenotypes. Nowadays, several alterations of immune response within the respiratory tracts as well as at the level of the peripheral blood have been well documented. Nonetheless, their effects on COVID-19-related cell heterogeneity and disease progression are less defined. Here, we performed a single-cell RNA sequencing of about 400 transcripts relevant to immune cell function including surface markers, in mononuclear cells (PBMCs) from the peripheral blood of 50 subjects, infected with SARS-CoV-2 at the diagnosis and 27 healthy blood donors as control. We found that patients with COVID-19 exhibited an increase in COVID-specific surface markers in different subsets of immune cell composition. Interestingly, the expression of cell receptors, such as IFNGR1 and CXCR4, was reduced in response to the viral infection and associated with the inhibition of the related signaling pathways and immune functions. These results highlight novel immunoreceptors, selectively expressed in COVID-19 patients, which affect the immune functionality and are correlated with clinical outcomes.

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“…Single cells expression profiles were normalized using GF-ICF (Gene Frequency – Inverse Cell Frequency) normalization using the gficf package 65,66 for R statistical environment (https://github.com/dibbelab/gficf). GF-ICF is based on a data transformation model called term frequency-inverse document frequency (TF-IDF) that has been extensively used in the field of text mining.…”

Section: Methodsmentioning

confidence: 99%

A single-cell atlas of breast cancer cell lines to study tumour heterogeneity and drug response

Gambardella

Viscido

Tumaini³

et al. 2021

Preprint

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Brest Cancer (BC) patient stratification is mainly driven by receptor status and histological grading and subtyping, with about twenty percent of patients for which absence of any actionable biomarkers results in no clear therapeutic intervention to apply. Here, we evaluated the potentiality of single-cell transcriptomics for automated diagnosis and drug treatment of breast cancer. We transcriptionally profiled 35,276 individual cells from 33 BC cell-lines covering all main BC subtypes to yield a Breast Cancer Single Cell Atlas. We show that single cell transcriptomics can successfully detect clinically relevant BC biomarkers and that atlas can be used to automatically predict cancer subtype and composition from a patient's tumour biopsy. We found that BC cell lines arbour a high degree of heterogeneity in the expression of clinically relevant BC biomarkers and that such heterogeneity enables cells with differential drug sensitivity to co-exist even within a genomically stable isogenic cell line. Finally, we developed a novel bioinformatics approach named DREEP (DRug Estimation from Expression Profiles) to automatically predict responses to more than 450 anticancer agents starting from single-cell transcriptional profiles. We validated DREEP both in-silico and in-vitro by selectively inhibiting the growth of the HER2-deficient subpopulation in the MDAMB361 cell line. Our work shows transcriptional heterogeneity is common, dynamic and plays a relevant role in determining drug sensitivity. Moreover, our Breast Cancer Single Cell Atlas and DREEP approach are a unique resource for the BC research community and to advance the use of single-cell sequencing in the clinics.

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Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview

Cited by 111 publications

References 90 publications

Single-cell sequencing analysis reveals gastric cancer microenvironment cells respond vastly different to oxidative stress

Single-cell sequencing analysis reveals gastric cancer microenvironment cells respond vastly different to oxidative stress

COVID-19 Specific Immune Markers Revealed by Single Cell Phenotypic Profiling

A single-cell atlas of breast cancer cell lines to study tumour heterogeneity and drug response

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