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pmid:37091977
An integrated bioinformatic analysis of bulk and single-cell sequencing clarifies immune microenvironment and metabolic profiles of lung adenocarcinoma to predict immunotherapy efficacy.
Mengling Li · Baosen Zhou · Chang Zheng
Frontiers in cell and developmental biology · 2023 doi:10.3389/fcell.2023.1163314
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Experiment
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Complete file
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However, few studies have addressed the efficacy of immunotherapy for LUAD. Here, a novel method for predicting immunotherapy efficacy has been proposed, which combines single-cell and bulk sequencing to characterize the immune microenvironment and metabolic profile of LUAD. TCGA bulk dataset was used to cluster two immune subtypes: C1 with \"cold\" tumor characteristics and C2 with \"hot\" tumor characteristics, with different prognosis. The Scissor algorithm, which is based on these two immune subtypes, identified GSE131907 single cell dataset into two groups of epithelial cells, labeled as Scissor_C1 and Scissor_C2. The enrichment revealed that Scissor_C1 was characterized by hypoxia, and a hypoxic microenvironment is a potential inducing factor for tumor invasion, metastasis, and immune therapy non-response. Furthermore, single cell analysis was performed to investigate the molecular mechanism of hypoxic microenvironment-induced invasion, metastasis, and immune therapy non-response in LUAD. Notably, Scissor_C1 cells significantly interacted with T cells and cancer-associated fibroblasts (CAF), and exhibited epithelial-mesenchymal transition and immunosuppressive features. CellChat analysis revealed that a hypoxic microenvironment in Scissor_C1elevated TGFβ signaling and induced ANGPTL4 and SEMA3C secretion. Interaction with endothelial cells with ANGPTL4, which increases vascular permeability and achieves distant metastasis across the vascular endothelium. Additionally, interaction of tumor-associated macrophages (TAM) and Scissor_C1 via the EREG/EFGR pathway induces tyrosine kinase inhibitor drug-resistance in patients with LAUD. Thereafter, a subgroup of CAF cells that exhibited same features as those of Scissor_C1 that exert immunosuppressive functions in the tumor microenvironment were identified. Moreover, the key genes (EPHB2 and COL1A1) in the Scissor_C1 gene network were explored and their expressions were verified using immunohistochemistry. Finally, the metabolism dysfunction in cells crosstalk was determined, which is characterized by glutamine secretion by TAM and uptake by Scissor_C1 via SLC38A2 transporter, which may induce glutamine addiction in LUAD cells. Overall, single-cell sequencing clarifies how the tumor microenvironment affects immunotherapy efficacy via molecular mechanisms and biological processes, whereas bulk sequencing explains immunotherapy efficacy based on clinical information.", "claims": [{"id": "claim-method", "statement": "Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37091977", "locator": "sections[6] \"2.4 Scissor algorithm for identifying phenotypically related cells\" paragraph 2", "quote": "Bulk sequencing from TCGA-LUAD patients was correlated with single-cell data using the Scissor algorithm (Sun et al., 2022)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37091977", "locator": "sections[26] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37091977", "locator": "sections[16] \"3.2 Integrated scRNA-seq analysis to dissect and cluster immune-related epithelial cell populations in LUAD\" paragraph 2", "quote": "The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively (Figures 4A, B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The Scissor algorithm identified 562 and 1,082 epithelial cells most associated with the C1 and C2 subtypes, respectively.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:37091977"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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