ArticlePloS one2015
Identification of Distinct Tumor Subpopulations in Lung Adenocarcinoma via Single-Cell RNA-seq.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
39 citing papers in PubMed, 60 citations in OpenAlex.
- Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer.Medicine · 2019Trial
- Monocarboxylate Transporter 2 (MCT2) Reduction Is Associated with Increased Lung Tumor Growth and Alterations in the Immune Microenvironment in a Subcutaneous Tumor Model.International journal of molecular sciences · 2026Article
- A pseudouridine-related prognostic model of colorectal cancer based on single-cell sequencing analysis and transcriptome analysis.Scientific reports · 2026Article
- The role of miR-21 in early-stage lung adenocarcinoma: clinical and bioinformatics insights.Scientific reports · 2025Article
- Single-cell spatial proteomics.Histology and histopathology · 2025Review
- Single-cell RNA-seq analysis to identify potential biomarkers for diagnosis, and prognosis of non-small cell lung cancer by using comprehensive bioinformatics approaches.Translational oncology · 2023Article
- Identification and validation of a seven-gene prognostic marker in colon cancer based on single-cell transcriptome analysis.IET systems biology · 2022Article
- Single-Cell Sequencing and Its Applications in Liver Cancer.Frontiers in oncology · 2022Review
- HLA-DR cancer cells expression correlates with T cell infiltration and is enriched in lung adenocarcinoma with indolent behavior.Scientific reports · 2021Article
- Dhaka: variational autoencoder for unmasking tumor heterogeneity from single cell genomic data.Bioinformatics (Oxford, England) · 2021Article
- Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy.Journal of the Chinese Medical Association : JCMA · 2021Review
- [Research Progress of Single Cell Sequencing in Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2021Review
- Deciphering the Immune-Tumor Interplay During Early-Stage Lung Cancer DevelopmentFrontiers in oncology · 2021Review
- The Single-Cell Sequencing: A Dazzling Light Shining on the Dark Corner of Cancer.Frontiers in oncology · 2021Review
- Single-Cell Transcriptomics Reveals the Complexity of the Tumor Microenvironment of Treatment-Naive Osteosarcoma.Frontiers in oncology · 2021Article
- Single-Cell Sequencing, an Advanced Technology in Lung Cancer Research.OncoTargets and therapy · 2021Review
- Article
- Breathing fresh air into respiratory research with single-cell RNA sequencing.European respiratory review : an official journal of the European Respiratory Society · 2020Review
- High accuracy gene expression profiling of sorted cell subpopulations from breast cancer PDX model tissue.PloS one · 2020Article
- Single-cell sequencing and its applications in head and neck cancer.Oral oncology · 2019Review
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell sequencing, which is used to detect clinically important tumor subpopulations, is necessary for understanding tumor heterogeneity. Here, we analyzed transcriptomic data obtained from 34 single cells from human lung adenocarcinoma (LADC) patient-derived xenografts (PDXs). To focus on the intrinsic transcriptomic signatures of these tumors, we filtered out genes that displayed extensive expression changes following xenografting and cell culture. Then, we performed clustering analysis using co-regulated gene modules rather than individual genes to minimize read drop-out errors associated with single-cell sequencing. This combined approach revealed two distinct intra-tumoral subgroups that were primarily distinguished by the gene module G64. The G64 module was predominantly composed of cell-cycle genes. E2F1 was found to be the transcription factor that most likely mediates the expression of the G64 module in single LADC cells. Interestingly, the G64 module also indicated inter-tumoral heterogeneity based on its association with patient survival and other clinical variables such as smoking status and tumor stage. Taken together, these results demonstrate the feasibility of single-cell RNA sequencing and the strength of our analytical pipeline for the identification of tumor subpopulations.
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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 OpenQuestion graph.