Single‐cell transcriptome analysis reveals intratumoral heterogeneity in lung adenocarcinoma

Author:

Xu Hong1,Jiang Lin2,Qin Lingshan3ORCID,Shi Ping4,Xu Ping5,Liu Changyu6

Affiliation:

1. Department of Thoracic and Cardiovascular Surgery, Yiling Hospital China Three Gorges University Yichang China

2. Department of Gastroenterology, Yiling Hospital China Three Gorges University Yichang China

3. Department of clinical medicne China medical university Shenyang China

4. Department of Oncology, Tongji Hospital, Tongji Medical College Huazhong University of Science and Technology Shenyang China

5. Department of Pathology, Guangzhou Women and Children’s Medical Center Guangzhou Medical University, Guangzhou, China Guangzhou China

6. Department of Thoracic Surgery Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China Guangzhou China

Abstract

AbstractIntroductionLung adenocarcinoma (LUAD) is a major health concern worldwide. Single‐cell RNA‐sequencing (scRNA‐seq) provides a valuable platform for exploring the intratumoral heterogeneity in LUAD and holds great potential for facilitating the development and application of personalized therapeutic approaches.MethodsThe TCGA‐LUAD (n = 503), GSE68465 (n = 442), GSE72094 (n = 398), and GSE26939 (n = 115) datasets were retrieved for prognostic assessment. Subgroup analysis was performed for the epithelial cells, endothelial cells, immune cells, and fibroblasts, and the transcription factors and tumor‐related pathways enriched in each subgroup were analyzed using PROGENy and DoRothEA package. The InferCNV software was used to calculate the copy number variations (CNVs) in tumor cell subgroups with normal epithelial cells as the reference. The association between the annotated cell types and survival was analyzed using the Scissor software.ResultsWe identified eight major cell types in LUAD, namely epithelial cells, NK cells, T and B cells, endothelial cells, mast cells, myeloid cells, and fibroblasts, of which the epithelial cells and B cells showed a marked increase in the tumor samples. In addition, we also detected an intense signal transduction network from the cancer‐associated fibroblasts (CAFs) to malignant cells, mainly involving the DCN/MET, COLA1/DDR1, COL1A1/SDC1, and COL1A2/SDC1 pathways. The tumor differentiation trajectory consisted of state 1 and state 2, which were enriched in HIF1A, and state 4. Furthermore, only a few B cells originated from the normal tissue, suggesting significant recruitment and infiltration of B cells in LUAD. Based on differentially upregulated genes in the cells positively and negatively associated with survival, we established a prognostic model that showed satisfactory predictive performance in three different cohorts. States 3 and 2 of epithelial cells included the majority of cells with KRAS mutation, whereas state 2 showed high frequency of EGFR mutations.ConclusionWe analyzed intra‐tumor heterogeneity of LUAD at the single‐cell level and developed a prognostic index that was highly effective across multiple cohorts.

Publisher

Wiley

Subject

Health, Toxicology and Mutagenesis,Management, Monitoring, Policy and Law,Toxicology,General Medicine

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