Publisher Correction: The Extended Polydimensional Immunome Characterization (EPIC) web-based reference and discovery tool for cytometry data

Yeo, Joo Guan; Wasser, Martin; Kumar, Pavanish; Pan, Lu; Poh, Su Li; Ally, Fauziah; Arkachaisri, Thaschawee; Lim, Amanda Jin Mei; Leong, Jing Yao; Lai, Liyun; Yeo, Kee Thai; Lee, Elene Seck Choon; Chua, Camillus; Larbi, Anis; Nyunt, Ma Shwe Zin; Ng, Tze Pin; Chiesa, Sabrina; Gattorno, Marco; Martini, Alberto; Paleja, Bhairav; Dutertre, Charles–Antoine; Chen, Jinmiao; Yaung, Katherine Nay; Tang, Swee Ping; Ng, S. K.; Yung, Chee Fu; Tan, Angela Yun June; Lee, S.Y.; Ginhoux, Florent; Albani, Salvatore

doi:10.1038/s41587-020-0574-4

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“…These observations have led us to comprehensively investigate the general hypothesis that inappropriate, immunologically driven pro-inflammatory mechanisms contribute to the pathogenesis of DRE in humans, as in other brain inflammatory diseases such as MS and autoimmune encephalitis. In our previous study 8 , we employed a high-dimensionality mass cytometry, artificial intelligence-driven approach 32 to examine the peripheral blood immunome in DRE in comparison with an age-matched standard dataset. We found DRE-specific aberrations, with an imbalance toward pro-inflammatory T cell subsets and a marked IL-17 signature 8 as shown by another report 7 .…”

Section: Discussionmentioning

confidence: 99%

Single-cell transcriptomics and surface epitope detection in human brain epileptic lesions identifies pro-inflammatory signaling

et al. 2022

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Epileptogenic triggers are multifactorial and not well understood. Here we aimed to address the hypothesis that inappropriate pro-inflammatory mechanisms contribute to the pathogenesis of refractory epilepsy (non-responsiveness to antiepileptic drugs) in human patients. We used single-cell cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to reveal the immunotranscriptome of surgically resected epileptic lesion tissues. Our approach uncovered a pro-inflammatory microenvironment, including extensive activation of microglia and infiltration of other pro-inflammatory immune cells. These findings were supported by ligand–receptor (LR) interactome analysis, which demonstrated potential mechanisms of infiltration and evidence of direct physical interactions between microglia and T cells. Together, these data provide insight into the immune microenvironment in epileptic tissue, which may aid the development of new therapeutics.

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Section: Discussionmentioning

confidence: 99%

Single-cell transcriptomics and surface epitope detection in human brain epileptic lesions identifies pro-inflammatory signaling

et al. 2022

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“…First, we tested the relationship between TMB and SLC7A11 gene expression by Spearman correlation analysis. Next, we quantified the proportions of immune cells using the CIBERSORTx 29 and EPIC 30 algorithms, separately. Spearman correlation analysis was conducted for the relationships among TMB, Immune cell infiltration, and SLC7A11 expression in multiple tumor tissues.…”

Section: Methodsmentioning

confidence: 99%

Pan-Cancer Analyses Confirmed the Ferroptosis-Related Gene SLC7A11 as a Prognostic Biomarker for Cancer

Lin¹,

Dong²,

W³

et al. 2022

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Purpose Ferroptosis is an iron-dependent and reactive oxygen species (ROS)-reliant form of cell death, exhibiting cellular, molecular, and gene-level characteristics distinct from those of necrosis, autophagy, apoptosis, and pyroptosis. Solute carrier family 7 member 11 ( SLC7A11 ), which encodes a cystine/glutamate antiporter transmembrane protein, inhibits ferroptosis by importing cystine and promoting glutathione (GSH) biosynthesis and was found to be overexpressed in multiple human cancers. However, the specific role and underlying mechanism of SLC7A11 in cancers remains poorly characterized. This research aimed to identify the relationship between SLC7A11 expression and tumor microenvironment and visualize its prognostic value in pan-cancer. Patients and Methods Transcriptomic data for 6313 tumors and normal samples across 20 cancer types were acquired from The Cancer Genome Atlas (TCGA) database. Besides, we presented a novel bioinformatics pipeline that uncovered the impacts of SLC7A11 on cancer prognosis, tumor mutational burden (TMB), immune cell infiltration in tumor microenvironment, and drug responses. The Genotype-Tissue Expression (GTEx), cBioportal, TCGA and Connectivity Map (CMap) databases were used to explore the expression, genetic alterations, immune microenvironment, and drug responses of SLC7A11 . A series of deconvolution algorithms, including EPIC, CIBERSORT and GSEA, were utilized for multidimensional analyses of the cancer transcriptomic data. Results SLC7A11 was found to be highly expressed in the 20 types of cancer, especially in solid tumors. Survival analysis uncovered that most cancer patients with up-regulated expression of SLC7A11 showed poor prognosis, suggesting that SLC7A11 is a potential oncogene in most cancer types. Furthermore, the expression level of SLC7A11 was confirmed to be associated with immune cell infiltration in tumor microenvironment, TMB, and drug responses. Gene set enrichment analysis (GESA) revealed that dysregulation of SLC7A11 was associated with metabolic and immunity-related signaling pathways in the cancers. Conclusion The comprehensive pan-cancer analyses identified SLC7A11 as an attractive biomarker for immune infiltration and poor prognosis in cancers, shedding new light on the therapeutics of cancers.

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Publisher Correction: The Extended Polydimensional Immunome Characterization (EPIC) web-based reference and discovery tool for cytometry data

Cited by 2 publications

References 0 publications

Single-cell transcriptomics and surface epitope detection in human brain epileptic lesions identifies pro-inflammatory signaling

Single-cell transcriptomics and surface epitope detection in human brain epileptic lesions identifies pro-inflammatory signaling

Pan-Cancer Analyses Confirmed the Ferroptosis-Related Gene SLC7A11 as a Prognostic Biomarker for Cancer

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