REVIEW ARTICLE
Open Access

Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer

Marco Rossi1, Giulia Bianchi, Alessandro Conti ORCID 

1Thoracic Oncology Unit, European Institute of Oncology (IEO), Milan, Italy
DOI: 10.18081/ajbm.2026.1.1

Publication History: Received 02 November, Revised 30 December 2025, Accepted 03 January 2026, Available online 19 January 2026
Copyright: © 2026 Conti, et al. This is an open-access article under a Creative Commons license (CC BY 4.0).
Crossmark logo

ABSTRACT

Background

Immune checkpoint inhibitors have transformed the treatment landscape of non-small cell lung cancer (NSCLC); however, primary and acquired resistance remain major clinical challenges. Immune evasion in NSCLC is increasingly recognized as a complex, dynamic process driven by tumor heterogeneity and adaptive remodeling of the tumor microenvironment. Conventional bulk profiling approaches are limited in resolving this complexity, underscoring the need for higher-resolution methodologies.

Objective
This review aims to synthesize current evidence on how single-cell transcriptomic approaches have advanced the understanding of immune evasion mechanisms in treatment-resistant NSCLC, with a focus on tumor-intrinsic programs, immune cell dysfunction, and intercellular communication networks.

Methods

A structured narrative review with systematic elements was conducted, analyzing peer-reviewed studies employing single-cell RNA sequencing and related single-cell technologies in human NSCLC. Studies were evaluated for their insights into immune escape pathways, resistance to immunotherapy, and translational relevance.

Results

Single-cell transcriptomic analyses reveal profound intratumoral and immune heterogeneity in treatment-resistant NSCLC. Resistant tumors harbor distinct malignant cell states characterized by impaired antigen presentation, dysregulated interferon signaling, and lineage plasticity. Within the immune compartment, hierarchical T-cell exhaustion, depletion of progenitor-like exhausted T cells, and expansion of immunosuppressive myeloid populations—particularly tumor-associated macrophages—emerge as dominant features of resistance. Ligand–receptor interaction analyses further demonstrate coordinated immunosuppressive communication networks that sustain immune escape at a systems level. Several single-cell–defined cellular states correlate with poor response to immune checkpoint blockade and adverse clinical outcomes.

Conclusion

Single-cell transcriptomics has fundamentally reshaped the conceptual framework of immune resistance in NSCLC, redefining it as a multicellular, dynamic ecosystem rather than a single-pathway phenomenon. These insights provide a strong biological rationale for developing biomarker strategies and rational combination therapies that target both tumor-intrinsic adaptations and the immunosuppressive microenvironment. Continued integration of single-cell technologies into translational and clinical research is essential to overcome immunotherapy resistance and improve patient outcomes in NSCLC.

Keywords: Non-small cell lung cancer; Single-cell RNA sequencing; Immune evasion; Immunotherapy resistance; Tumor microenvironment

Recommended Citation

Zhang W, Chen L. Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer. Advanced Journal of Biomedicine & Medicine. 2026;14(1):1-17. doi:10.18081/ajbm.2026.4.1

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

References

  1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. doi:10.3322/caac.21660
  2. Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer. 2018;553(7689):446-454. doi:10.1038/nature25183
  3. Reck M, Rodríguez-Abreu D, Robinson AG, et al. Pembrolizumab versus chemotherapy for PD-L1–positive NSCLC. N Engl J Med. 2016;375(19):1823-1833. doi:10.1056/NEJMoa1606774
  4. Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A. Primary, adaptive, and acquired resistance to cancer immunotherapy. 2017;168(4):707-723. doi:10.1016/j.cell.2017.01.017
  5. Topalian SL, Taube JM, Anders RA, Pardoll DM. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat Rev Cancer. 2016;16(5):275-287. doi:10.1038/nrc.2016.36
  6. Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. 2018;359(6382):1350-1355. doi:10.1126/science.aar4060
  7. McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present, and the future. 2017;168(4):613-628. doi:10.1016/j.cell.2017.01.018
  8. Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol. 2018;18(1):35-45. doi:10.1038/nri.2017.76
  9. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. 2011;144(5):646-674. doi:10.1016/j.cell.2011.02.013
  10. Chen DS, Mellman I. Elements of cancer immunity and the cancer–immune set point. 2017;541(7637):321-330. doi:10.1038/nature21349
  11. Gettinger S, Choi J, Hastings K, et al. Impaired HLA class I antigen processing and presentation as a mechanism of acquired resistance to immune checkpoint inhibitors in lung cancer. Cancer Discov. 2017;7(12):1420-1435. doi:10.1158/2159-8290.CD-17-0593
  12. Rosenthal R, Cadieux EL, Salgado R, et al. Neoantigen-directed immune escape in lung cancer evolution. 2019;567(7749):479-485. doi:10.1038/s41586-019-1032-7
  13. Wherry EJ, Kurachi M. Molecular and cellular insights into T cell exhaustion. Nat Rev Immunol. 2015;15(8):486-499. doi:10.1038/nri3862
  14. Sade-Feldman M, Yizhak K, Bjorgaard SL, et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. 2018;175(4):998-1013.e20. doi:10.1016/j.cell.2018.10.038
  15. Guo X, Zhang Y, Zheng L, et al. Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing. Nat Med. 2018;24(7):978-985. doi:10.1038/s41591-018-0045-3
  16. Lavin Y, Kobayashi S, Leader A, et al. Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. 2017;169(4):750-765.e17. doi:10.1016/j.cell.2017.04.014
  17. Lambrechts D, Wauters E, Boeckx B, et al. Phenotype molding of stromal cells in the lung tumor microenvironment. Nat Med. 2018;24(8):1277-1289. doi:10.1038/s41591-018-0096-5
  18. Zilionis R, Engblom C, Pfirschke C, et al. Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations. 2019;50(5):1317-1334.e10. doi:10.1016/j.immuni.2019.03.009
  19. Binnewies M, Roberts EW, Kersten K, et al. Understanding the tumor immune microenvironment. Nat Med. 2018;24(5):541-550. doi:10.1038/s41591-018-0014-x
  20. Gubin MM, Esaulova E, Ward JP, et al. High-dimensional analysis delineates myeloid and lymphoid compartment remodeling during successful immune checkpoint cancer therapy. 2018;175(4):1014-1030.e19. doi:10.1016/j.cell.2018.09.030
  21. Fridman WH, Zitvogel L, Sautès-Fridman C, Kroemer G. The immune contexture in cancer prognosis and treatment. Nat Rev Clin Oncol. 2017;14(12):717-734. doi:10.1038/nrclinonc.2017.101
  22. Keren L, Bosse M, Thompson S, et al. MIBI-TOF: a multiplexed imaging platform relates cellular phenotypes and tissue structure. Sci Adv. 2019;5(10):eaax5851. doi:10.1126/sciadv.aax5851
  23. Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol. 2015;33(5):495-502. doi:10.1038/nbt.3192
  24. Stuart T, Butler A, Hoffman P, et al. Comprehensive integration of single-cell data. 2019;177(7):1888-1902.e21. doi:10.1016/j.cell.2019.05.031
  25. Kalluri R. The biology and function of fibroblasts in cancer. Nat Rev Cancer. 2016;16(9):582-598. doi:10.1038/nrc.2016.73
  26. Joyce JA, Fearon DT. T cell exclusion, immune privilege, and the tumor microenvironment. 2015;348(6230):74-80. doi:10.1126/science.aaa6204
  27. Mariathasan S, Turley SJ, Nickles D, et al. TGF-β attenuates tumor response to PD-L1 blockade by contributing to exclusion of T cells. 2018;554(7693):544-548. doi:10.1038/nature25501
  28. Sanmamed MF, Chen L. A paradigm shift in cancer immunotherapy: from enhancement to normalization. 2018;175(2):313-326. doi:10.1016/j.cell.2018.09.035
  29. Yost KE, Satpathy AT, Wells DK, et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat Med. 2019;25(8):1251-1259. doi:10.1038/s41591-019-0522-3
  30. Franklin RA, Liao W, Sarkar A, et al. The cellular and molecular origin of tumor-associated macrophages. 2014;344(6186):921-925. doi:10.1126/science.1252510
  31. Broz ML, Binnewies M, Boldajipour B, et al. Dissecting the tumor myeloid compartment reveals rare activating antigen-presenting cells critical for T cell immunity. Cancer Cell. 2014;26(5):638-652. doi:10.1016/j.ccell.2014.09.007
  32. Chen G, Ning B, Shi T. Single-cell RNA-seq technologies and related computational data analysis. Front Genet. 2019;10:317. doi:10.3389/fgene.2019.00317
  33. Wagner J, Rapsomaniki MA, Chevrier S, et al. A single-cell atlas of the tumor and immune ecosystem of human breast cancer. 2019;177(5):1330-1345.e18. doi:10.1016/j.cell.2019.03.005
  34. Cristescu R, Mogg R, Ayers M, et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy. 2018;362(6411):eaar3593. doi:10.1126/science.aar3593
  35. McGinnis CS, Murrow LM, Gartner ZJ. DoubletFinder: doublet detection in single-cell RNA sequencing data. Cell Syst. 2019;8(4):329-337.e4. doi:10.1016/j.cels.2019.03.003
  36. Wolf FA, Angerer P, Theis FJ. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 2018;19(1):15. doi:10.1186/s13059-017-1382-0
  37. Finotello F, Trajanoski Z. Quantifying tumor-infiltrating immune cells from transcriptomics data. Cancer Immunol Immunother. 2018;67(7):1031-1040. doi:10.1007/s00262-018-2150-z
  38. Newman AM, Steen CB, Liu CL, et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat Biotechnol. 2019;37(7):773-782. doi:10.1038/s41587-019-0114-2
  39. Hegde PS, Chen DS. Top 10 challenges in cancer immunotherapy. 2020;52(1):17-35. doi:10.1016/j.immuni.2019.12.011
  40. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology: mutational landscape determines sensitivity to PD-1 blockade in NSCLC. 2015;348(6230):124-128. doi:10.1126/science.aaa1348
  41. Thorsson V, Gibbs DL, Brown SD, et al. The immune landscape of cancer. 2018;48(4):812-830.e14. doi:10.1016/j.immuni.2018.03.023
  42. Paik PK, Felip E, Veillon R, et al. Tepotinib in non–small-cell lung cancer with MET exon 14 skipping mutations. N Engl J Med. 2020;383(10):931-943. doi:10.1056/NEJMoa2004407
  43. Zhou Y, Yang D, Yang Q, et al. Single-cell RNA landscape of intratumoral heterogeneity and immunosuppressive microenvironment in advanced NSCLC. Nat Commun. 2020;11:2540. doi:10.1038/s41467-020-16342-7
  44. Wu TD, Madireddi S, de Almeida PE, et al. Peripheral T cell expansion predicts tumour infiltration and clinical response. 2020;579(7798):274-278. doi:10.1038/s41586-020-2056-8

2026 Vol 14, Issue 1 Pages 1-17

Download article

PDF Download: 215

PDF (639.5 KB) XML (4.7 KB)

Cite this article

Rossi M, Bianchi G, Conti A (2026). Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> . Advanced Journal of Biomedicine & Medicine, 14(1), 1-17. https://doi.org/10.18081/ajbm.2026.1.1
Rossi M, Bianchi G, Conti A. "Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> ." Advanced Journal of Biomedicine & Medicine, vol. 14, no. 1, 2026, pp. 1-17. DOI: 10.18081/ajbm.2026.1.1.
Rossi M, Bianchi G, Conti A. Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> . AJBM. 2026;14(1):1-17. DOI: 10.18081/ajbm.2026.1.1. PMID: .
Rossi M, Bianchi G, Conti A 2026, "Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> ", Advanced Journal of Biomedicine & Medicine, vol. 14, no. 1, pp. 1-17.
@article{rossi2026, title={Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> }, author={Rossi M, Bianchi G, Conti A}, journal={Advanced Journal of Biomedicine & Medicine}, volume={14}, number={1}, pages={1-17}, year={2026}, doi={10.18081/ajbm.2026.1.1} }
TY - JOUR AU - Rossi M, Bianchi G, Conti A TI - Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> JO - American Journal of Biomedicine VL - 14 IS - 1 SP - 1-17 PY - 2026 DO - 10.18081/ajbm.2026.1.1 ER -
%0 Journal Article %A Rossi M, Bianchi G, Conti A %T Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> %J American Journal of Biomedicine %V 14 %N 1 %P 1-17 %D 2026 %R 10.18081/ajbm.2026.1.1 %M
Rossi M, Bianchi G, Conti A (2026). Single-Cell Transcriptomic Mapping of Immune Evasion Pathways in Treatment-Resistant Non-Small Cell Lung Cancer<br /> . Advanced Journal of Biomedicine & Medicine, 14(1), 1-17. https://doi.org/10.18081/ajbm.2026.1.1

PlumX Metrics