Signatures of malignant cells and novel therapeutic targets revealed by single‐cell sequencing in lung adenocarcinoma

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 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.

Vascularized patient-derived tumoroids supplemented with immune cells to predict response towards treatment for lung cancer patients

“…2B). Among TTF-1, EPCAM, CK7 (or KRT7) and MUC1, more genes of the cytokeratin's family were found either in the tumoral primary cells or in the PDTs (KRT6A, KRT8, KRT18 and KRTCAP3) 27 . Genes such as NAPSA and S100P were observed in our Vasc-PDT in accordance with the tumoral primary cells.…”

A Novel Prognostic Signature Revealed the Interaction of Immune Cells in Tumor Microenvironment Based on Single-Cell RNA Sequencing for Lung Adenocarcinoma

“…Subsequent analysis validated the independent predicted value and well performance in immunotherapy response and revealed the crucial role of immune cells within the TME in tumor progression and metastasis. Since the rapid development and accessibility of scRNAseq in cancer research, promising findings in cancer evolu-tion, metastasis, and TME have been reached [21,22]. Previous studies have demonstrated that single-cell transcriptome analysis could apply specific signature genes to estimate cell type abundances of bulk transcriptome [23].…”

Characterization of Infiltrating Immune Cells and Secretory or Membrane-Associated Proteins in KRAS Lung Adenocarcinoma

“…Patient records lacking survival information were removed ( n = 22). The Human Protein Atlas ( https://www.proteinatlas.org ) [ 19 , 20 ] data on gene localization was retrieved. Gene locations, including their main location, additional location, and extracellular location, are all included in the data that was retrieved from the database.…”