J Cancer 2024; 15(3):796-808. doi:10.7150/jca.90768 This issue Cite

Research Paper

Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer

Junkai Zhu1,*, Junluo Yang1,*, Xinyi Chen1,*, Yang Wang2,*, Xin Wang1, Mengmeng Zhao1, Guanjie Li1, Yuhang Wang1, Yuyao Zhu1, Fangrong Yan1,✉, Tiantian Liu1,✉, Liyun Jiang1,✉

1. Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing 210009, P.R. China.
2. Department of Radiology, Zhujiang Hospital, Southern Medical University, 253 Gongye Middle Avenue, Haizhu District, Guangzhou, Guangdong, 510282, P.R. China.
* These authors contributed equally to the work.

Citation:
Zhu J, Yang J, Chen X, Wang Y, Wang X, Zhao M, Li G, Wang Y, Zhu Y, Yan F, Liu T, Jiang L. Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer. J Cancer 2024; 15(3):796-808. doi:10.7150/jca.90768. https://www.jcancer.org/v15p0796.htm
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Abstract

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Background: Most of the current research on prognostic model construction for non-small cell lung cancer (NSCLC) only involves in bulk RNA-seq data without integration of single-cell RNA-seq (scRNA-seq) data. Besides, most of the prognostic models are constructed by predictive genes, ignoring other predictive variables such as clinical features.

Methods: We obtained scRNA-seq data from GEO database and bulk RNA-seq data from TCGA database. We construct a prognostic model through the Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression. Furthermore, we performed ESTIMATE, CIBERSORT, immune checkpoint-related analyses and compared drug sensitivity using pRRophetic method judged by IC50 between different risk groups.

Results: 14 tumor-related genes were extracted for model construction. The AUC for 1-, 3-, and 5 years overall survival prediction in TCGA and three validation cohorts were almost higher than 0.65, some of which were even higher than 0.7, even 0.8. Besides, calibration curves suggested no departure between model prediction and perfect fit. Additionally, immune-related and drug sensitivity results revealed potential targets and strategies for treatment, which can provide clinical guidance.

Conclusion: We integrated traditional bulk RNA-seq and scRNA-seq data, along with predictive clinical features to develop a prognostic model for patients with NSCLC. According to the constructed model, patients in different groups can follow precise and individual therapeutic schedules based on immune characteristics as well as drug sensitivity.

Keywords: non-small cell lung cancer, scRNA-seq, prognostic model, immunotherapy, drug sensitivity


Citation styles

APA
Zhu, J., Yang, J., Chen, X., Wang, Y., Wang, X., Zhao, M., Li, G., Wang, Y., Zhu, Y., Yan, F., Liu, T., Jiang, L. (2024). Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer. Journal of Cancer, 15(3), 796-808. https://doi.org/10.7150/jca.90768.

ACS
Zhu, J.; Yang, J.; Chen, X.; Wang, Y.; Wang, X.; Zhao, M.; Li, G.; Wang, Y.; Zhu, Y.; Yan, F.; Liu, T.; Jiang, L. Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer. J. Cancer 2024, 15 (3), 796-808. DOI: 10.7150/jca.90768.

NLM
Zhu J, Yang J, Chen X, Wang Y, Wang X, Zhao M, Li G, Wang Y, Zhu Y, Yan F, Liu T, Jiang L. Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer. J Cancer 2024; 15(3):796-808. doi:10.7150/jca.90768. https://www.jcancer.org/v15p0796.htm

CSE
Zhu J, Yang J, Chen X, Wang Y, Wang X, Zhao M, Li G, Wang Y, Zhu Y, Yan F, Liu T, Jiang L. 2024. Integrated Bulk and Single-cell RNA Sequencing Data Constructs and Validates a Prognostic Model for Non-small Cell Lung Cancer. J Cancer. 15(3):796-808.

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