Journal: medRxiv

Article Title: Loss of Y in regulatory T lymphocytes in the tumor micro-environment of primary colorectal cancers and liver metastases

doi: 10.1101/2023.06.17.23289722

Figure Lengend Snippet: Panel A: Computational analysis of two scRNA-seq datasets; Zhang et al., 2020 and Nieto et al., 2021. In the first step, CD4+ T cells from the tumor microenvironment (TME), uninvolved margin (UM) and blood samples obtained from four CRC patients (Zhang et al., 2020) were re-clustered and categorized into Th and Tregs. Next, LOY-cells were defined based on the lack of expression of MSY-specific genes. Subsequently, the status of selected immunosuppressive genes was investigated in LOY and non-LOY Tregs located in the UM and tumor sites. The results obtained from the Zhang et al., 2020 dataset and comprising the scRNA-seq were validated in the Nieto et al., 2021 dataset, the latter covering an atlas of CD45+ immune cells from eight types of cancer, including CRC. Panel B: Experimental design for analysis of cells obtained from TME of human CRCs (n = 10) and LM_CRCs (n = 10) tissues and blood samples collected from CRC (n = 49), LM_CRC (n = 13) and Ctrl (n = 19) patients showed in three consecutive steps. Suspensions of single cells were sorted by FACS, followed by DNA isolation, ddPCR analysis using TaqMan-probes. Parts of the figure were drawn by using pictures from Servier Medical Art. Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License ( https://creativecommons.org/licenses/by/3.0/ ). Abbreviations: TME – tumor microenvironment; UM – non-tumorous uninvolved margin tissue; CRC – colorectal cancer; LM_CRC – liver metastasis of CRC; Ctrl – control patients, Tregs – regulatory T cells; Th – helper T cells; CTL – CD8+ cytotoxic T cells; ddPCR – droplet digital PCR; scRNA-seq – single-cell RNA-seq.

Article Snippet: Granulocytes were sorted according to SSC/FSC parameters and CD45+ expression antigen (BD Bioscience).

Techniques: Expressing, DNA Extraction, Digital PCR, RNA Sequencing Assay

Journal: medRxiv

Article Title: Loss of Y in regulatory T lymphocytes in the tumor micro-environment of primary colorectal cancers and liver metastases

doi: 10.1101/2023.06.17.23289722

Figure Lengend Snippet: Panel A: Meta-analysis of the distribution of LOY in Tregs (n = 2, cells = 203), Th (n = 4, cells = 1818) and CTL (n = 3, cells = 1441) lymphocytes located in the uninvolved margin (UM) and Tregs (n = 4, cells = 498), Th (n = 4, cells = 1460) and CTL (n = 3, cells = 681) located in tumor of male patients with CRC. Panel B: Experimental analysis of the distribution of LOY in Regulatory T lymphocytes (Tregs), Helper T lymphocytes (Th) and CD8+ cytotoxic T cells (CTL) in blood samples collected from 49 CRC patients and 19 healthy controls. CRC – colorectal cancer, Ctrl – age-matched control patients without prior diagnoses of cancer and Alzheimer’s disease. Panel C: Meta-analysis of distribution of LOY in Tregs and Th in eight different cancer types: CRC -colorectal cancer (n = 10, cells = 3349); HCC – hepatocellular carcinoma (n = 9, cells = 8329); ICC – intrahepatic cholangiocarcinoma (n = 1, cells = 222); CM – cutaneous melanoma (n = 24, cells = 13306); PDAC – pancreatic ductal adenocarcinoma (n = 4, cells = 845); BCC – basal cell carcinoma (n = 8, cells = 14053); SCC – squamous-cell carcinomas (n = 8, cells = 13889); UvM – uveal melanoma (n = 1, cells = 248). Panel D: Meta-analysis of distribution of %LOY in CD45+ immune cells located in TME of different cancers. CRC – colorectal cancer (n = 10, cells = 11165), HCC – hepatocellular carcinoma (n = 16, cells = 21604), ICC – intrahepatic cholangiocarcinoma (n = 5, cells = 1497), CM – cutaneous melanoma (n = 33, cells = 41087), PDAC – pancreatic ductal adenocarcinoma (n = 11, cells = 4749), BCC – basal cell carcinoma (n = 8, cells = 35359), SCC – squamous-cell carcinomas (n = 4, cells = 25924), UvM – uveal melanoma (n = 4, cells = 5018).

Article Snippet: Granulocytes were sorted according to SSC/FSC parameters and CD45+ expression antigen (BD Bioscience).

Techniques:

Journal: medRxiv

Article Title: Loss of Y in regulatory T lymphocytes in the tumor micro-environment of primary colorectal cancers and liver metastases

doi: 10.1101/2023.06.17.23289722

Figure Lengend Snippet: Panel A: Distribution of LOY in five subpopulations of CD45+ blood leukocytes . LOY was analyzed in sorted B cells, Gran, Mono, NK, Tregs obtained from 49 male CRC patients, 13 LM_CRC patients and 19 healthy controls. CRC – colorectal cancer, LM_CRC – liver metastasis of CRC, Ctrl – control patients. Pairwise comparison (Wilcoxon test with Bonferroni correction) is shown only for Tregs vs. B cells and Tregs vs. NK cells. These subsets (B cells and NK cells) displayed the highest statistical significance upon comparison with Tregs. Panel B: Distribution of LOY in FACS sorted subpopulations of T lymphocytes . Analysis of the distribution of LOY in Tregs, Th and CTLs in blood samples collected from 13 LM_CRC patients.

Article Snippet: Granulocytes were sorted according to SSC/FSC parameters and CD45+ expression antigen (BD Bioscience).

Techniques:

Journal: Journal of Tissue Engineering

Article Title: Single-cell RNA-sequence analysis of human bone marrow reveals new targets for isolation of skeletal stem cells using spherical nucleic acids

doi: 10.1177/20417314231169375

Figure Lengend Snippet: ScRNA-seq of 17,102 human adult bone marrow cells reveals SPARCL1 as a candidate marker of skeletal progenitor populations. (a) Experiment overview. Heterogeneous bone marrow populations were isolated from human adult bone marrow and MACS was applied to enrich for a CD45−/CD146+ skeletal progenitor population, CD144+ endothelial cells and CD144−/CD106+ pericytes. Single cells were isolated and sequenced following the Drop-seq methodology. Unsupervised clustering was applied to reveal subpopulations, which were characterised by differential gene expression to identify lineage biomarkers. (b) Uniform Manifold Approximation and Projection (UMAP) was performed to reduce the dimensionality of, and visualise, the normalised gene expression, each point representative of a single cell. Cluster analysis revealed eight distinct groups corresponding to haematopoietic and non-haematopoietic cell types. (c) The sequenced population and (d) patient sample plots show the integration of data from distinct sources across the UMAP. (e) Heatmap of normalised expression of the top three differentially expressed genes from each cell type cluster in comparison to all other cells. Each cluster was down-sampled to 200 cells. (f) Violin plots of expression of top three most significant differentially expressed genes in the pericyte cluster; CXCL12, SPARCL1 and CP (for all targets, significance <0.001).

Article Snippet: Cells expressing CD45 (Miltenyi Biotec, 130-045-801), CD146 (Miltenyi Biotec, 130-093-596), CD144 (Miltenyi Biotec, 130-097-857), CD106 (Miltenyi Biotec, 130-104-123 and 130-048-102) were isolated using Large Separation (LS) columns (Miltenyi Biotec, 130-042-401) according to manufacturer’s instructions.

Techniques: Marker, Isolation, Gene Expression, Expressing, Comparison