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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Cancer Immunity and Immunotherapy

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1654573

This article is part of the Research TopicImmune Predictive and Prognostic Biomarkers in Immuno-Oncology: Refining the Immunological Landscape of CancerView all 39 articles

Immunoproteasome Components LMP2, PSME1, and PSME2 as Novel Tissue Biomarkers Predicting Response and Survival in Neoadjuvant Chemoimmunotherapy for Resectable NSCLC

Provisionally accepted
  • 1Shandong First Medical University, Jinan, China
  • 2Shandong First Medical University Cancer Hospital, Jinan, China
  • 3Shandong Academy of Medical Sciences (SDAMS), Jinan, China

The final, formatted version of the article will be published soon.

Background: While neoadjuvant chemoimmunotherapy (NACI) improves outcomes in resectable non-small cell lung cancer (NSCLC), a significant subset of patients exhibits innate resistance. Biomarkers predicting response are urgently needed. Given the central role of antigen processing in immunotherapy efficacy, we investigated key immunoproteasome components—LMP2 (PSMB9), PSME1, and PSME2—as potential tissue-based biomarkers for NACI response and survival. Methods: Potential biomarker genes were identified through systematic literature review of NSCLC immunotherapy transcriptomic datasets. Candidate genes underwent validation in public databases (GEO, TCGA) via differential expression and Kaplan-Meier survival analysis. Protein expression of LMP2, PSME1, and PSME2 was assessed by immunohistochemistry (IHC) in pre-treatment tumor biopsies from a retrospective cohort of 50 resectable NSCLC patients treated with NACI (platinum-based chemotherapy + anti-PD-1/PD-L1). Pathologic response was categorized as major pathologic response (MPR, ≤10% residual viable tumor) or incomplete pathologic response (IPR). Associations with MPR, overall survival (OS), and independent prognostic value were evaluated. Results: Bioinformatic analysis identified LMP2, PSME1, and PSME2 as immunoproteasome subunits linked to antigen presentation pathways. In the clinical cohort, low pre-treatment intratumoral expression of LMP2, PSME1, and PSME2 (by IHC) significantly predicted MPR (P < 0.05). This is a provisional file, not the final typeset article Specifically, IPR patients exhibited higher median IHC scores for all three proteins compared to MPR patients. Kaplan-Meier analysis demonstrated that high pre-treatment LMP2 expression was associated with significantly improved OS (median OS: Not Reached vs. 40.0 months, P <0.0104). Post-NACI pathological stage (ypTNM III-IV) correlated with worse OS (P = 0.0027). Multivariate Cox analysis confirmed MPR status (HR=8.709, P = 0.003), and high pre-treatment LMP2 (HR=0.051, P = 0.007) as independent prognostic factors for OS. Conclusion: Low pre-treatment expression of immunoproteasome subunits LMP2, PSME1, and PSME2 predicts favorable pathologic response to NACI in resectable NSCLC. High baseline LMP2 expression, along with MPR achievement, independently associates with improved survival. These findings nominate LMP2/PSME1/PSME2 as novel, IHC-detectable biomarkers for stratifying NACI response and prognosis, highlighting the critical role of antigen processing machinery in modulating treatment efficacy. Validation in larger prospective cohorts is warranted.

Keywords: neoadjuvant immunotherapy combined with chemotherapy 1, predictive markers 2, NSCLC 3, LMP24, PSME15, PSME26

Received: 26 Jun 2025; Accepted: 30 Aug 2025.

Copyright: © 2025 Xie, Zhai, Yu and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Jinming Yu, Shandong First Medical University Cancer Hospital, Jinan, China
Miaoqing Zhao, Shandong Academy of Medical Sciences (SDAMS), Jinan, China

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