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A novel 12-gene signature as independent prognostic model in stage IA and IB lung squamous cell carcinoma patients

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Abstract

Background

There is currently no formal consensus on the administration of adjuvant chemotherapy to stage I lung squamous cell carcinoma (LUSC) patients despite the poor prognosis. The side effects of adjuvant chemotherapy need to be balanced against the risk of tumour recurrence. Prognostic markers are thus needed to identify those at higher risks and recommend individualised treatment regimens.

Methods

Clinical and sequencing data of stage I patients were retrieved from the Lung Squamous Cell Carcinoma project of the Cancer Genome Atlas (TCGA) and three tissue microarray datasets. In a novel K-resample gene selection algorithm, gene-wise Cox proportional hazard regressions were repeated for 50 iterations with random resamples from the TCGA training dataset. The top 200 genes with the best predictive power for survival were chosen to undergo an L1-penalised Cox regression for further gene selection.

Results

A total of 602 samples of LUSC were included, of which 42.2% came from female patients, 45.3% were stage IA cancer. From an initial pool of 11,212 genes in the TCGA training dataset, a final set of 12 genes were selected to construct the multivariate Cox prognostic model. Among the 12 selected genes, 5 genes, STAU1, ADGRF1, ATF7IP2, MALL and KRT23, were adverse prognostic factors for patients, while seven genes, NDUFB1, CNPY2, ZNF394, PIN4, FZD8, NBPF26 and EPYC, were positive prognostic factors. An equation for risk score was thus constructed from the final multivariate Cox model. The model performance was tested in the sequestered TCGA testing dataset and validated in external tissue microarray datasets (GSE4573, GSE31210 and GSE50081), demonstrating its efficacy in stratifying patients into high- and low-risk groups with significant survival difference both in the whole set (including stage IA and IB) and in the stage IA only subgroup of each set. The prognostic power remains significant after adjusting for standard clinical factors. When benchmarked against other prominent gene-signature based prognostic models, the model outperformed the rest in the TCGA testing dataset and in predicting long-term risk at eight years in all three validation datasets.

Conclusion

The 12-gene prognostic model may serve as a useful complementary clinical risk-stratification tool for stage I and especially stage IA lung squamous cell carcinoma patients to guide clinical decision making.

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Data availability

All data used in the study were downloaded from publicly available sources, see the methods section for their corresponding index numbers.

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Funding

This study was supported by the National Natural Science Foundation of China (81573178). The study was also supported by Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

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Author notes

  1. K. Wang and Y. Li contributed equally to the manuscript.

Authors and Affiliations

  1. School of Clinical Medicine, The University of Cambridge, Cambridge, UK

    K. Wang

  2. School of Medicine, The University of Leeds, Leeds, UK

    K. Wang

  3. School of Medicine, The University of Manchester, Manchester, UK

    Y. Li

  4. School of Public Health, Medical College of Soochow University, 199 Renai Rd., Suzhou, 215123, Jiangsu, China

    J. Wang & J. Li

  5. Respiratory Department, The Second Affiliated Hospital of the Soochow University, Suzhou, 215004, China

    R. Chen

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Contributions

(1) Conception and design: KW, YL and JL; (2) administrative support: JL and RC; (3) provision of study materials or patients: JL and RC; (4) collection and assembly of data: KW, YL and JW; (5) data analysis and interpretation: KW, YL and JW; (6) manuscript writing: all authors; (7) final approval of manuscript: all authors.

Corresponding authors

Correspondence to R. Chen or J. Li.

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All authors have completed the ICMJE uniform disclosure form. The authors have no conflicts of interest to declare.

Ethical statement

The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. There was no need for ethical approval as all data in this study were downloaded from public databases (TCGA), and the data processing met the TCGA publication guidelines (https://cancergenome.nih.gov/publications/guidelines).

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Wang, K., Li, Y., Wang, J. et al. A novel 12-gene signature as independent prognostic model in stage IA and IB lung squamous cell carcinoma patients. Clin Transl Oncol 23, 2368–2381 (2021). https://doi.org/10.1007/s12094-021-02638-1

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  • DOI: https://doi.org/10.1007/s12094-021-02638-1

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