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Screening and validation of plasma cell-derived, purinergic, and calcium signalling-related genetic signature to predict prognosis and PD-L1/PD-1 blockade responses in lung adenocarcinoma

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Abstract

Background

This study aims at  screening and validation of prospective genetic signature for lung adenocarcinoma (LUAD) prognosis and treatment.

Methods

The immune-related genes (IRGs) were obtained from The Cancer Genome Atlas (TCGA) dataset where a total of 535 LUAD and 59 control samples were included. A risk model was then developed for the risk stratification of LUAD patients.  The immune cell infiltration, clinical outcomes, and the therapeutic efficacy of programmed cell death protein 1 (PD-1) and its ligand (PD-L1) blockade were compared between high and low-risk groups. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the biological processes and signalling pathways associated with the IRGs. Finally, IRGs mRNA levels were assayed by reverse transcription quantitative real-time PCR (RT-qPCR) in LUAD and relevant cell lines.

Results

Two IRGs, P2RX1 (purinergic receptor P2X 1) and PCP4 (Purkinje cell protein 4), were screened from a module that possesses the highest correlation with plasma cells. RT-qPCR verified the expression of the two IRGs in plasmacytoma cell RPMI 8226 but not in LUAD cells. A higher risk score is associated with a lower infiltration of immune cells. Kaplan–Meier and nomogram analysis showed that the high-risk group has a lower survival rate than the low-risk cohort. Furthermore, the high-risk group had a worse response rate to PD-L1/PD-1 blockade. GSVA and GSEA-GO results indicated that a lower risk score is linked to signalling pathways and biological functions promoting immune response and inflammation. In contrast, a higher risk score is associated with signalling cascades promoting tumour growth.

Conclusion

The immune-related prognostic model based on P2RX1 and PCP4 is conducive to predicting the therapeutic response of PD-L1/PD-1 blockade and clinical outcomes of LUAD.

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Availability of data and materials

The gene expression profiles and the clinical data of the subjects were downloaded from TCGA (The Cancer Genome Atlas Program-National Cancer Institute). The GSE30219 dataset was downloaded from the Gene Expression Omnibus (GEO) database (GEO-NCBI (nih.gov)).

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Funding

This study was supported by The Natural Science Foundation of Anhui Province (Grant No. 1808085MH229) and Key Research and Development Program of Anhui Province (Grant No. 202004j07020027).

Author information

Author notes

  1. Junfeng Huang and **ngyu Fan contributed equally to this work.

Authors and Affiliations

  1. Department of Laboratory Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China

    Junfeng Huang & Bingqi Hu

  2. Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China

    Junfeng Huang, Bingqi Hu & Liwen Chen

  3. Medicine Centre, Erasmus University, Rotterdam, The Netherlands

    **ngyu Fan

  4. Department of Blood Transfusion, The Second Affiliated Hospital of Anhui Medical University, Hefei, China

    Liwen Chen

Authors
  1. Junfeng Huang
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  2. **ngyu Fan
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Contributions

Junfeng Huang was involved in the project design; Bingqi Hu analysed the data; Bingqi Hu and **ngyu Fan contributed to the data visualization; Junfeng Huang contributed to writing—original draft; Liwen Chen assisted in writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Liwen Chen.

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The authors declare that they have no competing interests.

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All public datasets utilized were generated by others who obtained ethical approval; therefore, no ethical approval was required for this work.

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Supplementary Information

Below is the link to the electronic supplementary material.

432_2023_5153_MOESM1_ESM.tif

Supplementary file1 Supplementary Figure 1. Kaplan-Meier survival analysis based on stratified infiltration of PCs in LUAD. (TIF 5230 KB)

432_2023_5153_MOESM2_ESM.tif

Supplementary file2 Supplementary Figure 2. GO enrichment analysis by Metascape database. Bar graph (A) and network (B) of the functional enrichment for the 66 shared genes colored by P value (Top 17). (TIF 1472 KB)

432_2023_5153_MOESM3_ESM.tif

Supplementary file3 Supplementary Figure 3. Evaluation of the risk model's forecasting ability using the combined (GSE68465; GSE101929; GSE37745; GSE83845) GEO datasets. (A) Kaplan-Meier analyses of OS in the high- and low-risk groups. (B-D) The risk score distribution (B) survival status (C) and expression levels of P2RX1 and PCP4 (D) in the merged dataset's high-risk and low-risk cohorts. OS, overall survival. (TIF 255 KB)

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Huang, J., Fan, X., Hu, B. et al. Screening and validation of plasma cell-derived, purinergic, and calcium signalling-related genetic signature to predict prognosis and PD-L1/PD-1 blockade responses in lung adenocarcinoma. J Cancer Res Clin Oncol 149, 12931–12945 (2023). https://doi.org/10.1007/s00432-023-05153-8

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