Signatures of malignant cells and novel therapeutic targets revealed by single‐cell sequencing in lung adenocarcinoma. (31st January 2022)
- Record Type:
- Journal Article
- Title:
- Signatures of malignant cells and novel therapeutic targets revealed by single‐cell sequencing in lung adenocarcinoma. (31st January 2022)
- Main Title:
- Signatures of malignant cells and novel therapeutic targets revealed by single‐cell sequencing in lung adenocarcinoma
- Authors:
- Liang, Jiaqi
Chen, Zhencong
Huang, Yiwei
Bi, Guoshu
Bian, Yunyi
Jin, Xing
Zhang, Huan
Sui, Qihai
Zhan, Cheng
Wang, Qun - Abstract:
- Abstract: Background: Single‐cell transcriptomics has been used to investigate various tumors to elucidate the molecular distinction of all cell type compositions of a complex mix. Aims: This study aimed to investigate malignant‐cell‐specific genes to explore diagnostic and therapeutic biomarkers using single‐cell transcriptomic data of lung adenocarcinoma. Materials & Methods: 10X single‐cell RNA‐seq data of fourteen patients with lung adenocarcinoma were analyzed. Genes that expressed differentially and those with higher confidence to distinguish tumor cells from normal cells were picked out using the ROC curves. The LASSO regression method was used to select most markedly correlated genes to predict the malignancy of every single cell within a model. We also conducted further experiments to determine their roles in lung cancer in vitro. Results: Twenty two thousand four hundred and ninety one tumor and 181 666 normal single cells were analyzed where 369 genes were found to be specifically expressed in single malignant cells. Seventy of them, encoding secreted or membrane‐bound proteins, showed involvement in cell‐to‐cell communications in tumor biology. KRT18 and the other six genes were identified as predictors to distinguish single malignant cells and were integrated to construct an accurate (96.1%) predicting model. Notably, IRX2, SPINK13, and CAPN8 outperformed the other four genes. Further experiments confirmed the upregulation of them in lung adenocarcinoma at bothAbstract: Background: Single‐cell transcriptomics has been used to investigate various tumors to elucidate the molecular distinction of all cell type compositions of a complex mix. Aims: This study aimed to investigate malignant‐cell‐specific genes to explore diagnostic and therapeutic biomarkers using single‐cell transcriptomic data of lung adenocarcinoma. Materials & Methods: 10X single‐cell RNA‐seq data of fourteen patients with lung adenocarcinoma were analyzed. Genes that expressed differentially and those with higher confidence to distinguish tumor cells from normal cells were picked out using the ROC curves. The LASSO regression method was used to select most markedly correlated genes to predict the malignancy of every single cell within a model. We also conducted further experiments to determine their roles in lung cancer in vitro. Results: Twenty two thousand four hundred and ninety one tumor and 181 666 normal single cells were analyzed where 369 genes were found to be specifically expressed in single malignant cells. Seventy of them, encoding secreted or membrane‐bound proteins, showed involvement in cell‐to‐cell communications in tumor biology. KRT18 and the other six genes were identified as predictors to distinguish single malignant cells and were integrated to construct an accurate (96.1%) predicting model. Notably, IRX2, SPINK13, and CAPN8 outperformed the other four genes. Further experiments confirmed the upregulation of them in lung adenocarcinoma at both tissue and cell levels. Proliferative capacities of lung adenocarcinoma cells were attenuated by knocking‐down of either of them. However, targeting CAPN8, IRX2, or SPINK13 hardly exerted a cytotoxic effect on these cells. Discussion: Apart from the current model, similar tools were still warranted using single‐cell RNA‐seq data of more types of tumors. The three genes identified as potential therapeutic targets in the present study still need to be validated in more in lung cancer. Conclusion: Our model can aid the analyses of single‐cell sequencing data. CAPN8, IRX2, and SPINK13 may serve as novel targets of targeted and immune‐based therapies in lung adenocarcinoma. Abstract : This study identified several tumor‐related genes that were scarcely revealed through analyses of bulk data provided with an effective approach to distinguish tumor cells from normal cells in single‐cell transcriptomic data. Several valuable genes used for promising targets in anticancer therapies in lung adenocarcinoma were discovered and validated in this work. … (more)
- Is Part Of:
- Cancer medicine. Volume 11:Number 11(2022)
- Journal:
- Cancer medicine
- Issue:
- Volume 11:Number 11(2022)
- Issue Display:
- Volume 11, Issue 11 (2022)
- Year:
- 2022
- Volume:
- 11
- Issue:
- 11
- Issue Sort Value:
- 2022-0011-0011-0000
- Page Start:
- 2244
- Page End:
- 2258
- Publication Date:
- 2022-01-31
- Subjects:
- lung adenocarcinoma -- single‐cell transcriptomics -- therapeutic targets
616.994005 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2045-7634 ↗ - DOI:
- 10.1002/cam4.4547 ↗
- Languages:
- English
- ISSNs:
- 2045-7634
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21778.xml