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Immunotherapy and senolytics in head and neck squamous cell carcinoma: phase 2 trial results

Nature Medicine volume 31, pages 3047–3061 (2025)Cite this article

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Abstract

Recent advancements in cancer immunotherapy have improved patient outcomes, yet responses to immunotherapy remain moderate. Immunosenescence has been shown to contribute to the development and progression of various diseases; however, its specific role in solid tumors has not been fully delineated. Here we conducted a phase 2 clinical trial involving 51 patients with cancer undergoing neoadjuvant chemoimmunotherapy and applied single-cell RNA as well as TCR and BCR sequencing on tumor and blood samples to elucidate the immune cell perturbations. Our findings associate poor response with reduced levels of CCR7+ CD4+ naive T cells and CD27+ memory B cells, as well as higher expression of immunosenescence-related genes in T and B cell subsets. Using naturally aged mice and Ercc1-deficient mice (premature aging), we found that senolytics enhance the therapeutic efficacy of immunotherapy in multiple solid tumors by mitigating immunosenescence. Notably, we launched a phase 2 clinical trial (COIS-01) investigating the combination of senolytics with anti-PD-1 therapy. The results showed that the combination therapy achieved a 33.3% (95% confidence interval 16.6–54.7%) major pathological response rate with a low incidence of grade 3–4 adverse events (4.2%). These findings underscore the pivotal role of immunosenescence characteristics in influencing the effectiveness of immunotherapy and suggest a promising therapeutic efficacy along with a favorable safety for the combination of senolytics with anti-PD-1 therapy. ClinicalTrials.gov Identifier: OOC-001(NCT04718415) and COIS-01(NCT05724329).

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Fig. 1: The results of the phase 2 clinical trial (OOC-001) and scRNA-seq data indicate that MPR patients demonstrate increased diversity in immune response-related cell subtypes and exhibit decreased expression of senescence markers.
Fig. 2: Patient responses to immunotherapy are associated with the expression of IAGs in both T and B cell subsets, as well as the interaction of IGF1+ Mφ with T and B cells.
Fig. 3: The combination of dasatinib and quercetin with αPD-1 enhances therapeutic efficacy in a chemically induced HNSCC mouse model by alleviating immunosenescence.
Fig. 4: Senolytics combined αPD-1 improve the efficacy of solid tumors in Ercc1+/− mice by reducing SASP and increasing tumor-infiltrating CD4+ naive T cells.
Fig. 5: ATAC-seq and RNA-seq analyses of CD4+ naive T cells provide evidence for the potential of αPD-1 + DQ in the regulation of immunosenescence.
Fig. 6: The phase 2 clinical trial COIS-01 validated the safety and efficacy of combining senolytic drugs with anti-PD-1 therapy.

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Data availability

All data associated with this study are present in the Article or its Supplementary Information. The raw sequence data including single-cell sequencing, TCR and BCR sequencing of human, and RNA and ATAC sequencing of CD4+ naive T cell datasets generated and analyzed during the current study have been deposited in Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) with accession code PRJCA027702 (https://ngdc.cncb.ac.cn/bioproject/browse/PRJCA027702) and PRJCA028161 (https://ngdc.cncb.ac.cn/bioproject/browse/PRJCA028161). Source data are provided with this paper.

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Acknowledgements

We thank all patients and their families for participation during sample collection. We are grateful to the support of the Clinical Research Design Division and Clinical Research Center at Sun Yat-sen Memorial Hospital, Sun Yat-sen University. S. Ferrone sadly passed away on 10 January 2023, at the age of 82. He was the supervisor of S. Fan during S. Fan’s postdoctoral work in his laboratory at Massachusetts General Hospital (MGH). Due to his constantly invaluable guidance and suggestions, which greatly helped improve and organize this study, all contributing authors agree to keep him as a co-author of this Article. We thank all the members of the Fan lab for valuable discussions and help with experimental techniques and analysis of the manuscript. This work was supported by the Joint Funds of the National Natural Science Foundation of China (grant no. U21A20381, S. Fan), the General Funds of the National Natural Science Foundation of China (grant no. 82373452, S. Fan), the Guangdong Natural Science Funds for Distinguished Young Scholar (grant no. 2022B1515020061, S. Fan), the Guangdong Basic and Applied Basic Research Foundation (grant no. 2021A1515220138, S. Fan), the Guangzhou Basic Research Program Jointly Funded by Municipal Schools (Institutes) (grant no. 202201020367, S. Fan), the General Funds of the National Natural Science Foundation of China (grant no. 32071451, X.F.), the Guangdong Provincial Pearl River Talents Program (grant no. 2021QN02Y747, X.F.), the Guangdong Special Support Program (grant no. 2023TQ07A494, F.X.), the Shenzhen Science and Technology Program (grant no. RCYX20210706092100003, F.X.) and by the Shenzhen Medical Research Funds grant (grant no. A2303005, F.X.).

Author information

Author notes

  1. These authors contributed equally: Niu Liu, Jiaying Wu, Enze Deng, Jianglong Zhong, Bin Wei, Tingting Cai.

  2. These authors jointly supervised this work: Song Fan, Xiaoying Fan, Fang Xu, Xinhui Wang.

  3. Deceased: Soldano Ferrone.

Authors and Affiliations

  1. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Guangzhou, China

    Niu Liu, Jiaying Wu, Jianglong Zhong, Bin Wei, Tingting Cai, Zhijun Xie, Kezhi Huang, Peilin Zhuang, Yunsheng Chen, Lizao Zhang, Hsinyu Lin, Qunxing Li, Peichia Lu, Jiahao Miao & Song Fan

  2. Department of Oral and Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Niu Liu, Jiaying Wu, Jianglong Zhong, Bin Wei, Tingting Cai, Zhijun Xie, Peilin Zhuang, Yunsheng Chen, Lizao Zhang, Hsinyu Lin, Qunxing Li, Peichia Lu, Jiahao Miao & Song Fan

  3. Interdisciplinary Center for Brain Information, Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Niu Liu, Yunsheng Chen, Jiahao Miao & Fang Xu

  4. Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, China

    Enze Deng, Qingpei Huang & Xiaoying Fan

  5. MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China

    Enze Deng

  6. Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Xiaohui Duan

  7. Department of Cellular and Molecular Diagnostics Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Sha Fu

  8. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    David O. Osei-Hwedieh & Sylvan C. Baca

  9. Department of Hematology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, JieYang, China

    Kezhi Huang

  10. Internal Medicine Ward I, JieXi People’s Hospital, JieYang, China

    Kezhi Huang

  11. School of Dentistry, Shenzhen University Medical School, Shenzhen, China

    Ou Sha

  12. Jiangxi Key Laboratory of Oncology, The Third Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China

    Xiaobin Lv

  13. Clinical Research Design Division, Clinical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Yingying Zhu

  14. Lecturer, Department of Gastroenterological Surgery, Faculty of Medicine, Fukuoka University, Fukuoka, Japan

    Teppei Yamada

  15. Institute of Hepatopancreatobiliary Surgery, Chongqing General Hospital, Chongqing University, Chongqing, China

    Lei Cai

  16. Cancer Institute, Xuzhou Medical University, Xuzhou, China

    Hongwei Du

  17. Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Xinhui Wang

  18. Faculty of Life and Health Sciences, Shenzhen University of Advanced Technology, Shenzhen, China

    Fang Xu

  19. GMU-GIBH Joint School of Life Sciences, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China

    Xiaoying Fan

Authors
  1. Niu Liu
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  2. Jiaying Wu
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  3. Enze Deng
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  4. Jianglong Zhong
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  5. Bin Wei
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  6. Tingting Cai
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  7. Zhijun Xie
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  8. Xiaohui Duan
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  9. Sha Fu
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  10. David O. Osei-Hwedieh
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  11. Kezhi Huang
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  12. Peilin Zhuang
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  13. Ou Sha
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  14. Yunsheng Chen
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  15. Xiaobin Lv
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  16. Yingying Zhu
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  17. Lizao Zhang
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  18. Hsinyu Lin
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  19. Qunxing Li
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  20. Peichia Lu
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  21. Jiahao Miao
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  22. Teppei Yamada
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  23. Lei Cai
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  24. Hongwei Du
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  25. Sylvan C. Baca
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  26. Qingpei Huang
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  27. Soldano Ferrone
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  28. Xinhui Wang
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  29. Fang Xu
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  30. Xiaoying Fan
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  31. Song Fan
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X.W., S.F., X.F., F.X., N.L., J.W. and E.D. designed the study and wrote the manuscript. S.F., X.F., F.X. and X.W. supervised the study. Single-cell RNA, TCR and BCR sequencing, RNA-seq and ATAC-seq involved library preparation and data analysis by N.L., J.W., E.D., T.C., Q.L. and J.Z. B.W., J.W., E.D., X.D., S.F., T.C., Z.X., P.Z., K.H. and Y.Z. collected patient samples and analyzed clinical data. S.F., N.L., J.W. and E.D. performed experiments and interpreted the data. All authors critically revised the paper.

Corresponding authors

Correspondence to Xinhui Wang, Fang Xu, Xiaoying Fan or Song Fan.

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The authors declare no competing interests.

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Nature Medicine thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Ulrike Harjes, in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1 The trial design and outcomes of OOC-001.

a, Trial flow diagram. b, Representative pre- and post-treatment intraoral photographs, H&E staining, and MRI images for MPR and noMPR patients. Scale bar = 50 μm. c, The changes and proportional statistics of TNM staging after treatment for lymph nodes in different patients. d, Scatter plot depicts the pathological response and radiographic response of the primary tumor after neoadjuvant treatment in the same patient (left), and the radiographic response of the primary tumor and lymph node metastasis in the same patient after neoadjuvant treatment (right). e, Pathological response of the primary tumor in patients treated with different cycles during neoadjuvant therapy (left), radiographic response of the primary tumor in patients treated with different cycles during neoadjuvant therapy (middle), and all remission include primary tumor and lymph node metastasis in patients treated with different cycles during neoadjuvant therapy (right). Sample sizes by treatment cycle: 2 cycles (n = 25), 3 cycles (n = 22), 4 cycles (n = 4). f, The rates of MPR for patients after 2 cycles, 3 cycles, and 4 cycles of treatment, as well as the rates of Grade 1-2 adverse events and Grade 3-4 adverse events. g, Survival curves for patients in this clinical trial at the 24-month follow-up. h, Disease-free survival (DFS) and OS curves for patients in this clinical trial at the 24-month follow-up. Boxes represent interquartile range (IQR, 25th–75th percentile), horizontal lines within boxes indicate medians, whiskers extend to 1.5×IQR.

Extended Data Fig. 2 Dynamic characterization of TCR landscape.

a, TCR sequencing of tumor (pre-treatment), pre- (P0) and post-treatment (P1) blood T cells (patients SH1-SH7, top-bottom). Top 10 differential blood clonotypes shown in serial blood (left) and tumor (right). b, Longitudinal changes in dominant tumor/blood clonotypes (circle size = clonal frequency; bright = persistent clones). MPR patients maintained pretreatment-dominant clones post-treatment. c, Grantham distance-based similarity of top 50 intratumoral TCR CDR3b clones. Red highlights maximally expanded clones. d, Bar plot of TCR and BCR clonotypes across all T cells and B cells in MPR or noMPR groups from P0, P1 and tumors. One clonotype consists strictly of one paired α-/β-chain V(D)J TCR. e, Pie chart of the antigen specificity of detected TCRs when considering α-, β-, and paired strands. CMV, cytomegalovirus; EBV, Epstein-Barr virus; InfluenzaA, influenza A virus; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; HS, Homo sapiens antigen; HIV-1, human immunodeficiency virus 1; HCV, hepatitis C virus; YFV, yellow fever virus; DEV, dengue virus. f, Representative immunofluorescence images of senescent markers P16 and P21 on paraffin sections from MPR and noMPR patients in two patient cohorts (Cohort1 n = 50, Cohort2 n = 61).

Extended Data Fig. 3 Development and validation of IAGs.

a, Representative immunofluorescence staining results of the entire tumor paraffin section, with DAPI labeling cell nuclei (blue), P16 as a senescence marker (green), CD3 as a T cell marker (purple), and Pan-CK as a tumor marker (red). Scale bar = 100 μm. b, Human immune cell samples from multiple data sets were used for single-cell RNA sequencing analysis to construct the IAGs. A representative panoramic slide from all immunofluorescence staining procedures is presented, showcasing the distribution of immune cells and senescent cells within the tumor region. c, The IAGs significantly enriched in B cells (middle) and T cells (right) in peripheral blood of frail elderly people (GSE157007). d, The IAGs is significantly enriched in B cells (middle) and T cells (right) in the peripheral blood of elderly women (PRJCA002856). e, The IAGs is significantly enriched in all immune cells in bone marrow of older women (GSE141595). f, Violin plot of expression of the different all cells IAGs score in HNSCC tumors between MPR and noMPR groups (left), and in TNBC tumors between PR and SD groups (right). Black lines with different lengths indicate which two groups were compared. Wilcoxon signed-rank test.

Extended Data Fig. 4 Anti-tumor reactivity and immunosenescence features of T cell subtypes.

a, Violin plot of expression of all T cells IAGs score in HNSCC tumors between MPR and noMPR groups. Black lines with different lengths indicate which two groups were compared. Wilcoxon signed-rank test. b, Gene Venn diagram of differential genes of T cell subtypes in tumors between MPR and noMPR groups. c, UMAP shows the distribution of T cell and B cell subtypes in TNBC. d, Box plot of the percentage of the T cell clusters in TNBC tumors between PR and SD groups. The boxed plot on the left of each T cell cluster is the PR group, and on the right is SD group. Box middle lines, median; box limits, upper and lower quartiles. Black lines with different lengths indicate which two groups were compared. Wilcoxon signed-rank test. e, Violin plot of expression of all T cells IAGs score in TNBC tumors between PR and SD groups. Black lines with different lengths indicate which two groups were compared. Wilcoxon signed-rank test. f, The Ridge plot of IAGs score analysis for T cells clusters in TNBC. g, Dot plot of intersection genes of TNBC T cell DEGs and IAGs between PR and SD groups. h, DEGs (Log2Foldchages > 0.5) of CCR7 + CD4 naïve T cells and CXCL13 CD4 T helper cells between MPR and noMPR enriched GO terms in tumors. Log-rank test (two-sided). *P < 0.05, **P < 0.01, ***P < 0.001. Boxes represent interquartile range (IQR, 25th–75th percentile), horizontal lines within boxes indicate medians, whiskers extend to 1.5×IQR.

Extended Data Fig. 5 The effect of senolytics combined with αPD-1 on TIME of 4-NQO mice.

a, Representative images of tongue sections from mice, fed with 4-nitroquinoline-1-oxide (4-NQO)-containing drinking water for 12, 20, and 28 weeks, stained with hematoxylin and eosin (HE). Scale bar, 50μm. n = 3 mice per timepoint. For each mouse, 5 random fields of view (FOV) were imaged from distinct tissue sections. b, Images of tongue of mice after receiving Isotype, αPD-1, αPD-1 + CP or αPD-1 + DQ treatment (n = 6 each group). Red arrows indicate tumor-like nodules. c, Line graph illustrating the change in mouse body weight over time after receiving Isotype, αPD-1, αPD-1 + CP or αPD-1 + DQ treatment (n = 6 per group). d, Flow cytometry gating strategy for assessing the proportions of CD4+, CD8+, as well as T cell subtypes. e-g, Flow cytometry immunophenotyping of splenic cells, bone marrow Cells and blood showing the frequencies of CD4+, CD8+ and B220+ cells in mice after receiving Isotype, αPD-1, αPD-1 + CP or αPD-1 + DQ treatment (n = 6 each group). h, Senescence markers p16 and p21 expression in CD8+ TILs from the mice treated with Isotype, αPD-1, αPD-1 + CP or αPD-1 + DQ (n = 6 per group).

Source data

Extended Data Fig. 6 Transcriptomic and epigenetic dynamics of CD4 naive T cells following the αPD-1 + DQ therapy.

a, Volcano plot of differentially expressed genes between αPD-1 + DQ and Isotype groups (left), αPD-1 and Isotype groups (middle), αPD-1 + DQ and αPD-1 groups (right). b, DEGs (Log2Foldchanges > 0.5) of CD4 naïve T cells in tumors between αPD-1 and Isotype groups enriched GO terms. c, Proportions of the ATAC-seq peak regions representing various genome annotations identified in Isotype, αPD-1 + DQ and αPD-1 groups. d, The heatmap of different annotated genes in Isotype, αPD-1 and αPD-1 + DQ groups from ATAC-seq. e, Venn diagram of peaks of CD4 naïve T cells in Isotype, αPD-1 and αPD-1 + DQ groups. f, ATAC-seq tracks showing the representative genes chromatin accessibility in the Lck, Cfd, and Slfn2 loci for CD4 naïve T cells in Isotype, αPD-1 + DQ and anti-PD-1 groups. g, RNA-seq and ATAC-seq detected GO terms that were simultaneously enriched in the αPD-1 group and Isotype group (left) and GO terms that were enriched in open chromatin regions unique to the αPD-1 + DQ group and αPD-1group (right).

Extended Data Table 1 Demographic and clinical characteristics of OOC-001
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Extended Data Table 2 Treatment-related adverse events of OOC-001 (n = 51)
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Extended Data Table 3 Demographic and clinical characteristics of COIS-01
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Extended Data Table 4 Treatment-related adverse events of COIS-01 (n = 24)
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Supplementary information

Supplementary Information

Supplementary Figs. 1–10 and primer sequence information.

Reporting Summary

Supplementary Tables 1–9

Supplementary Table 1a. Demographic and clinical characteristics of OOC-001, related to Fig. 1. Supplementary Table 1b. Demographic and clinical characteristics of seven patients with HNSCC, related to Fig. 2. Supplementary Table 2. TRAEs of OOC-001. Supplementary Table 3a. DEGs of CXCL13-CD4 T helper in tumors between MPR and noMPR. Supplementary Table 3b. DEGs of CCR7+ CD4+ naive T cells in tumors between MPR and noMPR. Supplementary Table 3c. DEG of CD27+ memory B cells in tumors between MPR and noMPR. Supplementary Table 4. Immunosenescence-related genes (IAGs). Supplementary Table 5. Luminex assay. Supplementary Table 6a. DEGs of CD4+ naive T cells between anti-PD-1 + DQ and control groups, related to Fig. 5. Supplementary Table 6b. DEGs of CD4+ naive T cells between anti-PD-1 and control groups. Supplementary Table 6c. DEGs of CD4+ naive T cells between anti-PD-1 and anti-PD-1 + DQ groups. Supplementary Table 7a. Signature peaks and chromatin dynamics of CD4+ naove T cells, related to Fig. 5. Supplementary Table 7b. Signature peaks and chromatin dynamics of T cell clusters, related to Fig. 5. Supplementary Table 8. Demographic and clinical characteristics of COIS-01. Supplementary Table 9. TRAEs of COIS-01.

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Liu, N., Wu, J., Deng, E. et al. Immunotherapy and senolytics in head and neck squamous cell carcinoma: phase 2 trial results. Nat Med 31, 3047–3061 (2025). https://doi.org/10.1038/s41591-025-03873-7

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