ArticleScientific data2023
An integrated single-cell transcriptomic dataset for non-small cell lung cancer.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From tumor microenvironment orchestrators to actionable targets: a systematic review of TAM-targeted therapies in triple-negative breast cancer.International journal of clinical oncology · 2026Pooled it
- Lineage identity governs oncogene dependence in mouse NSCLC models of KRAS inhibitor resistance.Nature genetics · 2026Article
- ANGPTL4 contributes to osimertinib resistance through NDRG1-associated extracellular matrix remodeling in EGFR-mutant NSCLC organoid models.Cancer cell international · 2026Article
- Establishing human immune system mice: application, opportunity, and challenges.Experimental & molecular medicine · 2026Review
- Targeting the HMGB1-IL32 pathway to alleviate T cell exhaustion in epithelial ovarian cancer.GeroScience · 2026Article
- YY1-mediated NDUFA9 upregulation promotes NSCLC cell growth through mitochondrial and Akt-mTOR pathway modulation.Cell death & disease · 2026Article
- Cortisol-resistant CAR-NK cells overcome steroid-induced immunosuppression in lung cancer.Signal transduction and targeted therapy · 2026Article
- A single-nucleus RNA-seq dataset of the colon in Pink1-deficient and wild-type mice.Scientific data · 2026Article
- Integrated single-cell transcriptomic atlas of human gastric and colorectal tissues across diverse phenotypes.Scientific data · 2026Article
- Tumors located in the brain impair the frequency and phenotype of dendritic cells in blood and tumor.iScience · 2026Article
- A highly resolved integrated single-cell atlas of HPV-negative head and neck cancer.Communications medicine · 2026Article
- An integrative spatial multi-omic workflow for unified analysis of tumor tissue.Cell reports methods · 2026Article
- Single-cell spatial analysis identifies ID1-high endothelial cells in tertiary lymphoid structures as predictors of durable response to immunotherapy in non-small cell lung cancer.Cancer cell international · 2026Article
- Deciphering immune heterogeneity in lung adenocarcinoma via machine learning-based Differential Phenotype Immune Score: TPX2 as a key biomarker for immunotherapy resistance.Frontiers in immunology · 2026Article
- MRPL17 is a critical regulator of mitochondrial function and a novel therapeutic target in non-small cell lung cancer.Cell death & disease · 2025Article
- Harnessing plasma transcriptomics for non-invasive cancer biomarker identification: a comprehensive review.Discover oncology · 2025Review
- Article
- IPGCA: A Comprehensive Single Cell Atlas of 1 074 127 Porcine Intestinal Cells Revealing Cellular Dynamics, Genetic Regulation, and Cross-Species Conservation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Comprehensive Single-Cell Transcriptomic Atlas of the Mouse Pons and Medulla.Scientific data · 2025Article
- Exploring mitochondrial ribosomal protein S12 as a novel target for non-small cell lung cancer.NPJ precision oncology · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
As single-cell RNA sequencing (scRNA-seq) has emerged as a great tool for studying cellular heterogeneity within the past decade, the number of available scRNA-seq datasets also rapidly increased. However, reuse of such data is often problematic due to a small cohort size, limited cell types, and insufficient information on cell type classification. Here, we present a large integrated scRNA-seq dataset containing 224,611 cells from human primary non-small cell lung cancer (NSCLC) tumors. Using publicly available resources, we pre-processed and integrated seven independent scRNA-seq datasets using an anchor-based approach, with five datasets utilized as reference and the remaining two, as validation. We created two levels of annotation based on cell type-specific markers conserved across the datasets. To demonstrate usability of the integrated dataset, we created annotation predictions for the two validation datasets using our integrated reference. Additionally, we conducted a trajectory analysis on subsets of T cells and lung cancer cells. This integrated data may serve as a resource for studying NSCLC transcriptome at the single cell level.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.