Skip to main content
Log in

Genomic Profiling Reveals Immune-Related Gene Differences in Lung Cancer Patients Stratified by PD1/PDL1 Expression: Implications for Immunotherapy Efficacy

  • Human Genetics • Original Paper
  • Published:
Journal of Applied Genetics Aims and scope Submit manuscript

Abstract

Lung cancer remains a leading cause of global cancer-related mortality, and the exploration of innovative therapeutic approaches, such as PD1/PDL1 immunotherapy, is critical. This study leverages comprehensive data from the Cancer Genome Atlas (TCGA) to investigate the differential expression of PD1/PDL1 in lung cancer patients and explores its implications. Clinical data, RNA expression, somatic mutations, and copy number variations of 1017 lung cancer patients were obtained from TCGA. Patients were categorized into high (HE) and low (LE) PD1/PDL1 expression groups based on mRNA levels. Analyses included differential gene expression, functional enrichment, protein-protein interaction networks, and mutational landscape exploration. The study identified 391 differentially expressed genes, with CD4 and PTPRC among the upregulated genes in the HE group. Although overall survival did not significantly differ between HE and LE groups, enrichment analysis revealed a strong association with immunoregulatory signaling pathways, emphasizing the relevance of PD1/PDL1 in immune response modulation. Notably, TP53 mutations were significantly correlated with high PD1/PDL1 expression. This study provides a comprehensive analysis of PD1/PDL1 expression in lung cancer, uncovering potential biomarkers and highlighting the intricate interplay between PD1/PDL1 and the immune response. The identified upregulated genes, including CD4 and PTPRC, warrant further investigation for their roles in the context of lung cancer and immunotherapy. The study underscores the importance of considering molecular heterogeneity in shaping personalized treatment strategies for lung cancer patients. Limitations, such as the retrospective nature of TCGA data, should be acknowledged.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

All data are provided in this study and raw data can be requested to the corresponding author.

References

  • Bade BC, Dela Cruz CS (2020) Lung Cancer 2020: epidemiology, etiology, and prevention. Clin Chest Med 41(1):1–24

    Article  PubMed  Google Scholar 

  • Bolandi N, Derakhshani A, Hemmat N, Baghbanzadeh A, Asadzadeh Z, Afrashteh Nour M, Brunetti O, Bernardini R, Silvestris N, Baradaran B (2021) The positive and negative immunoregulatory role of B7 family: promising novel targets in gastric cancer treatment. Int J Mol Sci 22(19):10719

  • Burova E, Hermann A, Waite J et al (2017) Characterization of the anti-PD-1 antibody REGN2810 and its antitumor activity in human PD-1 knock-in mice. Mol Cancer Ther 16(5):861–870

    Article  CAS  PubMed  Google Scholar 

  • Cha JH, Chan LC, Li CW et al (2019) Mechanisms controlling PD-L1 expression in cancer. Mol Cell 76(3):359–370

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chen EJ, Chen S, Zhou FL (2021) Mechanism of TRIM27 promoting inflammatory response in lung cancer cells. Zhonghua Zhong Liu Za Zhi 43(10):1076–1081

    CAS  PubMed  Google Scholar 

  • Dong ZY, Zhong WZ, Zhang XC et al (2017) Potential predictive value of TP53 and KRAS mutation status for response to PD-1 blockade immunotherapy in lung adenocarcinoma. Clin Cancer Res 23(12):3012–3024

    Article  CAS  PubMed  Google Scholar 

  • Ferlay J, Colombet M, Soerjomataram I et al (2019) Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer 144(8):1941–1953

    Article  CAS  PubMed  Google Scholar 

  • Gómez-Henao W, Tenorio EP, Sanchez FRC et al (2021) Relevance of glycans in the interaction between T lymphocyte and the antigen presenting cell. Int Rev Immunol 40(4):274–288

    Article  PubMed  Google Scholar 

  • Herbst RS, Morgensztern D, Boshoff C (2018) The biology and management of non-small cell lung cancer. Nature 553(7689):446–454

    Article  CAS  PubMed  ADS  Google Scholar 

  • Hughes PE, Caenepeel S, Wu LC (2016) Targeted therapy and checkpoint immunotherapy combinations for the treatment of cancer. Trends Immunol 37(7):462–476

  • Lagou V, Garcia-Perez JE, Smets I et al (2018) Genetic architecture of adaptive immune system identifies key immune regulators. Cell Rep 25(3):798–810.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Leng C, Li Y, Qin J et al (2016) Relationship between expression of PD-L1 and PD-L2 on esophageal squamous cell carcinoma and the antitumor effects of CD8+ T cells. Oncol Rep 35(2):699–708

    Article  CAS  PubMed  Google Scholar 

  • Liu C, Zheng S, Jin R et al (2020) The superior efficacy of anti-PD-1/PD-L1 immunotherapy in KRAS-mutant non-small cell lung cancer that correlates with an inflammatory phenotype and increased immunogenicity. Cancer Lett 470:95–105

    Article  CAS  PubMed  Google Scholar 

  • McDermott DF, Atkins MB (2013) PD-1 as a potential target in cancer therapy. Cancer Medicine 2(5):662–673

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mezzadra R, Sun C, Jae LT et al (2017) Identification of CMTM6 and CMTM4 as PD-L1 protein regulators. Nature 549(7670):106–110

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  • Mogi A, Kuwano H (2011) TP53 mutations in nonsmall cell lung cancer. J Biomed Biotechnol 2011:583929

    Article  PubMed  PubMed Central  Google Scholar 

  • Raphael I, Joern RR, Forsthuber TG (2020) Memory CD4+ T cells in immunity and autoimmune diseases. Cells 9(3):531

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ritchie ME, Phipson B, Wu D et al (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47

    Article  PubMed  PubMed Central  Google Scholar 

  • Roulleaux Dugage M, Nassif EF, Italiano A et al (2021) Improving immunotherapy efficacy in soft-tissue sarcomas: a biomarker driven and histotype tailored review. Front Immunol 12:775761

    Article  PubMed  PubMed Central  Google Scholar 

  • Salmaninejad A, Valilou SF, Shabgah AG et al (2019) PD-1/PD-L1 pathway: basic biology and role in cancer immunotherapy. J Cell Physiol 234(10):16824–16837

    Article  CAS  PubMed  Google Scholar 

  • Singh AK, Stock P, Akbari O (2011) Role of PD-L1 and PD-L2 in allergic diseases and asthma. Allergy 66(2):155–162

    Article  CAS  PubMed  Google Scholar 

  • Sun Y, Jiang L, Wen T et al (2021) Trends in the research into immune checkpoint blockade by anti-PD1/PDL1 antibodies in cancer immunotherapy: a bibliometric study. Front Pharmacol 12:670900

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Toumazis I, Bastani M, Han SS et al (2020) Risk-based lung cancer screening: a systematic review. Lung Cancer 147:154–186

    Article  PubMed  Google Scholar 

  • Tumeh PC, Harview CL, Yearley JH et al (2014) PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515(7528):568–571

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  • Watza D, Lusk CM, Dyson G et al (2018) Prognostic modeling of the immune-centric transcriptome reveals interleukin signaling candidates contributing to differential patient outcomes. Carcinogenesis 39(12):1447–1454

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wei W, Zeng H, Zheng R et al (2020) Cancer registration in China and its role in cancer prevention and control. Lancet Oncol 21(7):e342–e3e9

    Article  PubMed  Google Scholar 

  • Xu F, Lin H, He P et al (2020) A TP53-associated gene signature for prediction of prognosis and therapeutic responses in lung squamous cell carcinoma. Oncoimmunology 9(1):1731943

    Article  PubMed  PubMed Central  Google Scholar 

  • Yu G, Wang LG, Han Y et al (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16(5):284–287

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhou J, Zhang D, Zhang W (2023) Cross-view enhancement network for underwater images. Eng Appl Artif Intel 121:105952

    Article  Google Scholar 

Download references

Funding

This study did not receive any funding in any form.

Author information

Authors and Affiliations

Authors

Contributions

ZY, TH, & LW: concepts, design, data analysis, statistical analysis, manuscript preparation, manuscript review, guarantor; ZY, KH, HZ, LH, & LW: definition of intellectual content, literature search, experimental studies, data acquisition, manuscript editing

Corresponding author

Correspondence to Lu Wang.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Communicated by: Ewa Ziętkiewicz

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ye, Z., Huang, T., Hu, K. et al. Genomic Profiling Reveals Immune-Related Gene Differences in Lung Cancer Patients Stratified by PD1/PDL1 Expression: Implications for Immunotherapy Efficacy. J Appl Genetics (2024). https://doi.org/10.1007/s13353-024-00841-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13353-024-00841-8

Keywords

Navigation