ArticleFrontiers in immunology2022
Immune and non-immune cell subtypes identify novel targets for prognostic and therapeutic strategy: A study based on intratumoral heterogenicity analysis of multicenter scRNA-seq datasets in lung adenocarcinoma.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 7 citations in OpenAlex.
- Bibliometric analysis of single-cell RNA sequencing in tumor microenvironment.Discover oncology · 2026Review
- Single-cell transcriptomic analysis reveals cellular and molecular changes in EGFR-positive lung adenocarcinoma before and after Furmonertinib treatment.Genes & genomics · 2026Review
- Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study.Cancer cell international · 2025Article
- Unveiling the power of Treg.Sig: a novel machine-learning derived signature for predicting ICI response in melanoma.Frontiers in immunology · 2025Article
- Lung adenocarcinoma size as a predictor of distant metastasis: A CT scan-based measurement.Narra J · 2024Article
- Construction of an immune-related gene prognostic model with experimental validation and analysis of immune cell infiltration in lung adenocarcinoma.Oncology letters · 2024Article
- Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing.Therapeutic advances in medical oncology · 2024Review
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13 authors at 5 institutions in 2 countries.
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Abstract
Lung adenocarcinoma (LUAD) is the most common type of lung cancer and the leading cause of cancer incidence and mortality worldwide. Despite the improvement of traditional and immunological therapies, the clinical outcome of LUAD is still far from satisfactory. Patients given the same treatment regimen had different responses and clinical outcomes due to the heterogeneity of LUAD. How to identify the targets based on heterogeneity analysis is crucial for treatment strategies. Recently, the single-cell RNA-sequencing (scRNA-seq) technology has been used to investigate the tumor microenvironment (TME) based on cell-specific changes and shows prominently valuable for biomarker prediction. In this study, we systematically analyzed a meta-dataset from the multiple LUAD scRNA-seq datasets in LUAD, identified 15 main types of cells and 57 cell subgroups, and revealed a series of potential biomarkers in M2b, exhausted CD8
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