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Predictive value of p53 and AXL immunostaining for the efficacy of immune checkpoint inhibitor-based therapy after osimertinib treatment in patients with epidermal growth factor-mutant non-small cell lung cancer

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Abstract

Background

Current evidence indicates that immune checkpoint inhibitors (ICIs) have a limited efficacy in patients with lung cancer harboring epidermal growth factor receptor (EGFR) mutations. However, there is a lack of data on the efficacy of ICIs after osimertinib treatment, and the predictors of ICI efficacy are unclear.

Methods

We retrospectively assessed consecutive patients with EGFR-mutant NSCLC who received ICI-based therapy after osimertinib treatment at 10 institutions in Japan, between March 2016 and March 2021. Immunohistochemical staining was used to evaluate the expression of p53 and AXL. The deletions of exon 19 and the exon 21 L858R point mutation in EGFR were defined as common mutations; other mutations were defined as uncommon mutations.

Results

A total of 36 patients with advanced or recurrent EGFR-mutant NSCLC were analyzed. In multivariate analysis, p53 expression in tumors was an independent predictor of PFS after ICI-based therapy (p = 0.002). In patients with common EGFR mutations, high AXL expression was a predictor of shorter PFS and overall survival after ICI-based therapy (log-rank test; p = 0.04 and p = 0.02, respectively).

Conclusion

The levels of p53 in pretreatment tumors may be a predictor of ICI-based therapy outcomes in patients with EGFR-mutant NSCLC after osimertinib treatment. High levels of AXL in tumors may also be a predictor of ICI-based therapy outcomes, specifically for patients with common EGFR mutations. Further prospective large-scale investigations on the predictors of ICI efficacy following osimertinib treatment are warranted.

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Data availability

The datasets generated during the current study are not publicly available because of ethical constraints but are available from the corresponding author upon reasonable request.

References

  1. Maemondo M, Inoue A, Kobayashi K et al (2010) Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N Engl J Med 362(25):2380–2388. https://doi.org/10.1056/NEJMoa0909530

    Article  CAS  PubMed  Google Scholar 

  2. Mitsudomi T, Morita S, Yatabe Y et al (2010) Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (WJTOG3405): an open label, randomised phase 3 trial. Lancet Oncol 11(2):121–128. https://doi.org/10.1016/S1470-2045(09)70364-X

    Article  CAS  PubMed  Google Scholar 

  3. Sequist LV, Yang JC, Yamamoto N et al (2013) Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J Clin Oncol 31(27):3327–3334. https://doi.org/10.1200/JCO.2012.44.2806

    Article  CAS  PubMed  Google Scholar 

  4. Soria JC, Ohe Y, Vansteenkiste J et al (2018) Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. N Engl J Med 378(2):113–125. https://doi.org/10.1056/NEJMoa1713137

    Article  CAS  PubMed  Google Scholar 

  5. Ramalingam SS, Vansteenkiste J, Planchard D et al (2020) Overall survival with osimertinib in untreated, EGFR-mutated advanced NSCLC. N Engl J Med 382(1):41–50. https://doi.org/10.1056/NEJMoa1913662

    Article  CAS  PubMed  Google Scholar 

  6. Passaro A, Leighl N, Blackhall F et al (2022) ESMO expert consensus statements on the management of EGFR mutant non-small-cell lung cancer. Ann Oncol S0923–7534:00112. https://doi.org/10.1016/j.annonc.2022.02.003

    Article  CAS  Google Scholar 

  7. Mazieres J, Drilon A, Lusque A et al (2019) Immune checkpoint inhibitors for patients with advanced lung cancer and oncogenic driver alterations: results from the IMMUNOTARGET registry. Ann Oncol 30:1321–1328. https://doi.org/10.1093/annonc/mdz167

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Morimoto K, Sawada R, Yamada T et al (2022) A real-world analysis of immune checkpoint inhibitor-based therapy after osimertinib treatment in EGFR-mutant non-small cell lung cancer patients. JTO Clin Res Rep 3(9):100388. https://doi.org/10.1016/j.jtocrr.2022.100388

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hong S, Gao F, Fu S et al (2018) Concomitant genetic alterations with response to treatment and epidermal growth factor receptor tyrosine kinase inhibitors in patients with EGFR-mutant advanced non-small cell lung cancer. JAMA Oncol 4(5):739–742. https://doi.org/10.1001/jamaoncol.2018.0049

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kim Y, Lee B, Shim JH et al (2019) Concurrent genetic alterations predict the progression to target therapy in EGFR-mutated advanced NSCLC. J Thorac Oncol 14(2):193–202. https://doi.org/10.1016/j.jtho.2018.10.150

    Article  CAS  PubMed  Google Scholar 

  11. Nahar R, Zhai W, Zhang T et al (2018) Elucidating the genomic architecture of Asian EGFR-mutant lung adenocarcinoma through multi-region exome sequencing. Nat Commun 9(1):216. https://doi.org/10.1038/s41467-017-02584-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Guo Y, Song J, Wang Y et al (2020) Concurrent genetic alterations and other biomarkers predict treatment efficacy of EGFR-TKIs in EGFR-mutant non-small cell lung cancer: a review. Front Oncol 10:610923. https://doi.org/10.3389/fonc.2020.610923

    Article  PubMed  PubMed Central  Google Scholar 

  13. Yoshimura A, Yamada T, Serizawa M et al (2022) High levels of AXL expression in untreated EGFR-mutated NSCLC negatively impacts the use of osimertinib. Cancer Sci. https://doi.org/10.1111/cas.15608. https://doi.org/10.1111/cas.15608. [published online ahead of print, 2022 Sep 28]

  14. Offin M, Chan JM, Tenet M et al (2019) Concurrent RB1 and TP53 alterations define a subset of EGFR-mutant lung cancers at risk for histologic transformation and inferior clinical outcomes. J Thorac Oncol 14(10):1784–1793. https://doi.org/10.1016/j.jtho.2019.06.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Singh N, Piskorz AM, Bosse T et al (2020) p53 immunohistochemistry is an accurate surrogate for TP53 mutational analysis in endometrial carcinoma biopsies. J Pathol 250(3):336–345. https://doi.org/10.1002/path.5375

    Article  CAS  PubMed  Google Scholar 

  16. Hwang HJ, Nam SK, Park H et al (2020) Prediction of TP53 mutations by p53 immunohistochemistry and their prognostic significance in gastric cancer. J Pathol Transl Med 54(5):378–386. https://doi.org/10.4132/jptm.2020.06.01

    Article  PubMed  PubMed Central  Google Scholar 

  17. Antony J, Huang RY (2017) AXL-driven EMT state as a targetable conduit in cancer. Cancer Res 77(14):3725–3732. https://doi.org/10.1158/0008-5472.CAN-17-0392

    Article  CAS  PubMed  Google Scholar 

  18. Graham DK, DeRyckere D, Davies KD, Earp HS (2014) The TAM family: phosphatidylserine sensing receptor tyrosine kinases gone awry in cancer. Nat Rev Cancer 14(12):769–785. https://doi.org/10.1038/nrc3847

    Article  CAS  PubMed  Google Scholar 

  19. Holland SJ, Powell MJ, Franci C et al (2005) Multiple roles for the receptor tyrosine kinase axl in tumor formation. Cancer Res 65(20):9294–9303. https://doi.org/10.1158/0008-5472.CAN-05-0993

    Article  CAS  PubMed  Google Scholar 

  20. Okura N, Nishioka N, Yamada T et al (2020) ONO-7475, a novel AXL inhibitor, suppresses the adaptive resistance to initial EGFR-TKI treatment in EGFR-mutated non-small cell lung cancer. Clin Cancer Res 26(9):2244–2256. https://doi.org/10.1158/1078-0432.CCR-19-2321

    Article  CAS  PubMed  Google Scholar 

  21. Taniguchi H, Yamada T, Wang R et al (2019) AXL confers intrinsic resistance to osimertinib and advances the emergence of tolerant cells. Nat Commun 10(1):259. https://doi.org/10.1038/s41467-018-08074-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kanda Y (2013) Investigation of the freely available easy-to-use software “EZR” for medical statistics. Bone Marrow Transplant 48(3):452–458. https://doi.org/10.1038/bmt.2012.244

    Article  CAS  PubMed  Google Scholar 

  23. Yamada T, Hirai S, Katayama Y et al (2019) Retrospective efficacy analysis of immune checkpoint inhibitors in patients with EGFR-mutated non-small cell lung cancer. Cancer Med 8(4):1521–1529. https://doi.org/10.1002/cam4.2037

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lin S, Li X, Lin M, Yue W (2021) Meta-analysis of P53 expression and sensitivity to platinum-based chemotherapy in patients with non-small cell lung cancer. Medicine 100(5):e24194

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. 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. https://doi.org/10.1158/1078-0432.CCR-16-2554

    Article  CAS  PubMed  Google Scholar 

  26. Assoun S, Theou-Anton N, Nguenang M et al (2019) Association of TP53 mutations with response and longer survival under immune checkpoint inhibitors in advanced non-small-cell lung cancer. Lung Cancer 132:65–71. https://doi.org/10.1016/j.lungcan.2019.04.005

    Article  PubMed  Google Scholar 

  27. Biton J, Mansuet-Lupo A, Pécuchet N et al (2018) TP53, STK11, and EGFR mutations predict tumor immune profile and the response to anti-PD-1 in lung adenocarcinoma. Clin Cancer Res 24(22):5710–5723. https://doi.org/10.1158/1078-0432.CCR-18-0163

    Article  CAS  PubMed  Google Scholar 

  28. Isomoto K, Haratani K, Hayashi H et al (2020) Impact of EGFR-TKI treatment on the tumor immune microenvironment in EGFR mutation-positive non-small cell lung cancer. Clin Cancer Res 26(8):2037–2046. https://doi.org/10.1158/1078-0432.CCR-19-2027

    Article  CAS  PubMed  Google Scholar 

  29. Köbel M, Piskorz AM, Lee S et al (2016) Optimized p53 immunohistochemistry is an accurate predictor of TP53 mutation in ovarian carcinoma. J Pathol Clin Res 2(4):247–258. https://doi.org/10.1002/cjp2.53

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Engelsen AST, Lotsberg ML, AbouKhouzam R et al (2022) Dissecting the role of AXL in cancer immune escape and resistance to immune checkpoint inhibition. Front Immunol 13:869676. https://doi.org/10.3389/fimmu.2022.869676

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lee W, Kim DK, Synn CB et al (2022) Incorporation of SKI-G-801, a novel AXL inhibitor, with anti-PD-1 plus chemotherapy improves anti-tumor activity and survival by enhancing T cell immunity. Front Oncol 12:821391. https://doi.org/10.3389/fonc.2022.821391

    Article  PubMed  PubMed Central  Google Scholar 

  32. Synn CB, Kim SE, Lee HK et al (2021) SKI-G-801, an AXL kinase inhibitor, blocks metastasis through inducing anti-tumor immune responses and potentiates anti-PD-1 therapy in mouse cancer models. Clin Transl Immunol 11(1):e1364. https://doi.org/10.1002/cti2.1364

    Article  CAS  Google Scholar 

  33. Goyette MA, Elkholi IE, Apcher C et al (2021) Targeting Axl favors an antitumorigenic microenvironment that enhances immunotherapy responses by decreasing Hif-1α levels. Proc Natl Acad Sci USA 118(29):e2023868118. https://doi.org/10.1073/pnas.2023868118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors sincerely appreciate the contributions of all the physicians and patients who participated in this study.

Funding

This research was conducted without any funding.

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Authors and Affiliations

Authors

Contributions

TY contributed to conceptualization, methodology, formal analysis, writing—original draft preparation, writing—review and editing, and supervision. KM was involved in methodology, investigation, formal analysis, writing—original draft preparation, writing—review and editing, project administration, data curation. RS contributed to methodology. KA, YG, TH, SS, NT, YC, TT, OH, IH, and ST were involved in Investigation. KT contributed to writing—original draft preparation, writing—review and editing, supervision. AY, YHK, MI and ST was involved in project administration and data curation.

Corresponding author

Correspondence to Tadaaki Yamada.

Ethics declarations

Conflict of interest

TY received grants from Pfizer, Ono Pharmaceutical, Janssen Pharmaceutical, and Takeda Pharmaceutical and personal fees from Eli Lilly. KA received personal fees from Ono Pharmaceutical, Chugai Pharmaceutical, AstraZeneca, MSD Oncology, and Bristol-Myers Squibb outside the submitted work. KT received grants from Chugai Pharmaceutical and Ono Pharmaceutical and personal fees from AstraZeneca, Chugai Pharmaceutical, MSD, Eli Lilly, Boehringer Ingelheim, and Daiichi Sankyo. The other authors have no further conflicts of interest to declare.

Ethics approval

The study protocol was approved by the ethics committee of each hospital, including the Kyoto Prefectural University of Medicine (Approval no. ERB-C-1918).

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Because this was a retrospective study, the need for informed consent was waived, and an official website was used as an opt-out method.

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Morimoto, K., Yamada, T., Sawada, R. et al. Predictive value of p53 and AXL immunostaining for the efficacy of immune checkpoint inhibitor-based therapy after osimertinib treatment in patients with epidermal growth factor-mutant non-small cell lung cancer. Cancer Immunol Immunother 72, 1699–1707 (2023). https://doi.org/10.1007/s00262-023-03370-1

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