整合单细胞与转录组学解析头颈鳞癌坏死性凋亡异质性及预后预测模型构建

Integrated single-cell and transcriptomic analysis reveals necroptosis heterogeneity and constructs a prognostic model in head and neck squamous cell carcinoma

摘要

目的 头颈鳞状细胞癌(head and neck squamous cell carcinoma, HNSCC)治疗耐药与凋亡抵抗密切相关，坏死性凋亡作为一种可绕过凋亡缺陷的替代性细胞死亡方式，其在HNSCC肿瘤微环境重塑及预后中的单细胞层面特征尚缺乏系统解析。本研究旨在整合单细胞与批量转录组数据，揭示HNSCC中坏死性凋亡的细胞异质性特征，并构建预后预测模型。方法 从GEO和TCGA数据库获取HNSCC的单细胞RNA测序(scRNA-seq)及批量转录组数据。采用Seurat、AUCell算法进行单细胞分析，量化不同细胞亚群的坏死性凋亡活性。通过差异分析、Cox回归及LASSO回归筛选关键基因，构建预后列线图模型，并利用CIBERSORT及CellMiner数据库分别评估模型基因与免疫细胞浸润及药物敏感性的关联。结果 单细胞图谱解析揭示了恶性细胞、巨噬细胞和肥大细胞具有最高的坏死性凋亡活性，角蛋白家族基因在恶性细胞中与坏死性凋亡活性高度相关。通过整合分析，构建了一个由LAT、KRT6A、APP和DUSP5组成的四基因预后模型。高风险组患者预后显著较差，并呈现出以CD8⁺T细胞和活化CD4⁺记忆T细胞浸润减少、静息态树突状细胞增多为特征的“免疫荒漠”表型。此外，模型基因表达与奈拉滨、Bcl-2抑制剂等多种药物的敏感性存在统计学相关性，为后续实验提供初步线索。需明确指出，因公共数据库限制，本研究未能纳入HPV状态信息，目前结论的普适性尚待HPV分层分析验证。结论 本研究系统解析了HNSCC坏死性凋亡相关分子特征，所构建的四基因模型具有一定的风险分层潜力，并为理解坏死性凋亡可能参与驱动免疫抑制微环境形成及指导个体化治疗提供了新的分子靶点。

Abstract

Objective Treatment resistance in head and neck squamous cell carcinoma (HNSCC) is closely associated with apoptotic defects. Necroptosis is an alternative regulated cell death modality that can bypass apoptotic deficiencies; however, its role in tumor microenvironment (TME) remodeling and prognosis in HNSCC remains insufficiently characterized at the single-cell level. This study aimed to integrate single-cell and bulk transcriptomic data to elucidate the cellular heterogeneity of necroptosis-related features in HNSCC, and to construct a prognostic prediction model. Methods We obtained single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data of HNSCC were obtained from the GEO and TCGA databases. Single-cell analysis was performed using the Seurat package and the AUCell algorithm to quantify necroptosis activity across distinct cell subpopulations. Key genes were identified through differential expression analysis, as well as Cox and LASSO regression, in order to construct a prognostic nomogram model. The associations of the model genes with immune cell infiltration and drug sensitivity were then evaluated using CIBERSORT and the CellMiner database, respectively. Results Single-cell profiling revealed that malignant cells, macrophages, and mast cells exhibited the highest levels of necroptosis activity. Keratin family genes were found to be highly correlated with necroptosis activity in malignant cells. An integrative analysis was performed to construct a four-gene prognostic model comprising LAT, KRT6A, APP, and DUSP5. Patients in the high-risk group had significantly worse prognosis and exhibited an “immune desert” phenotype characterized by reduced infiltration of CD8⁺ T cells and activated CD4⁺ memory T cells, accompanied by increased resting dendritic cells. Furthermore, the gene expression in the model correlates with sensitivity to multiple drugs, including nelarabine and Bcl-2 inhibitors. This offers preliminary insights for subsequent experiments. It should be clearly noted that, due to limitations of public databases, HPV status information was not included in this study due to limitations of public databases. Consequently, the generalizability of the current conclusions remains to be validated by HPV-stratified analyses. Conclusion This study systematically elucidates the molecular features of necroptosis in HNSCC at a single-cell level. The established four-gene model enables effective risk stratification and provides novel molecular targets for understanding the formation of necroptosis-driven immunosuppressive TME driven by necroptosis, as well as for guiding individualized therapy.

关键词

头颈鳞状细胞癌 / 坏死性凋亡 / 预后模型 / 肿瘤微环境 / 免疫治疗

Key words

Head and neck squamous cell carcinoma / Necroptosis / Prognostic model / Tumor microenvironment / Immunotherapy

参考文献

[1] Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263. DOI: 10.3322/caac.21834

[2] Li QF, Tie Y, Alu A, et al. Targeted therapy for head and neck cancer: signaling pathways and clinical studies[J]. Signal Transduct Target Ther, 2023, 8: 31. DOI: 10.1038/s41392-022-01297-0

[3] Saba NF, Chaudhary R, Kirtane K, et al. Pembrolizumab and cabozantinib in recurrent and/or metastatic head and neck squamous cell carcinoma: long-term survival update with a biomarker analysis[J]. Clin Cancer Res, 2024, 30(20): 4601-4608. DOI: 10.1158/1078-0432.CCR-24-1202

[4] Kishita S, Umemura N, Miyazaki H, et al. Induction of immunogenic necroptosis by shikonin in drug-resistant head and neck squamous cell carcinoma cells[J]. Oncol Rep, 2025, 54(6): 1-12. DOI: 10.3892/or.2025.8996

[5] Gong YT, Fan ZY, Luo GP, et al. The role of necroptosis in cancer biology and therapy[J]. Mol Cancer, 2019, 18(1): 100. DOI: 10.1186/s12943-019-1029-8

[6] Wang SZ, Jiang JJ, Xing M, et al. Deciphering the prognostic potential of a necroptosis-related gene signature in head and neck squamous cell carcinoma: a bioinformatic analysis[J]. Transl Cancer Res, 2025, 14(1): 340-353. DOI: 10.21037/tcr-24-743

[7] Huang J, Lu R, Zhong DT, et al. A novel necroptosis-associated IncRNA signature for prognosis of head and neck squamous cell carcinoma[J]. Front Genet, 2022, 13: 907392. DOI: 10.3389/fgene.2022.907392

[8] Gao WT, Wang XY, Zhou Y, et al. Autophagy, ferroptosis, pyroptosis, and necroptosis in tumor immunotherapy[J]. Sig Transduct Target Ther, 2022, 7: 196. DOI: 10.1038/s41392-022-01046-3

[9] Zhang T, Yin CR, Fedorov A, et al. ADAR1 masks the cancer immunotherapeutic promise of ZBP1-driven necroptosis[J]. Nature, 2022, 606(7914): 594-602. DOI: 10.1038/s41586-022-04753-7

[10] Huang J, Huo HQ, Lu R. A novel signature of necroptosis-associated genes as a potential prognostic tool for head and neck squamous cell carcinoma[J]. Front Genet, 2022, 13: 907985. DOI: 10.3389/fgene.2022.907985

[11] Huang JT, Xu ZQ, Teh BM, et al. Construction of a necroptosis-related lnRNA signature to predict the prognosis and immune microenvironment of head and neck squamous cell carcinoma[J]. J Clin Lab Anal, 2022, 36(6): e24480. DOI: 10.1002/jcla.24480

[12] Abugeessa I, Kasukawa T. Practical Guide to Life Science Databases[M]. Singapore: Springer Nature Singapore, 2021: 27-56. DOI: 10.1007/978-981-16-5812-9

[13] Liberzon A, Birger C, Thorvaldsdóttir H, et al. The molecular signatures database hallmark gene set collection[J]. Cell Syst, 2015, 1(6): 417-425. DOI: 10.1016/j.cels.2015.12.004

[14] Reinhold WC, Sunshine M, Liu HF, et al. CellMiner: a web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set[J]. Cancer Res, 2012, 72(14): 3499-3511. DOI: 10.1158/0008-5472.can-12-1370

[15] Shankavaram UT, Varma S, Kane D, et al. CellMiner: a relational database and query tool for the NCI-60 cancer cell lines[J]. BMC Genom, 2009, 10(1): 277. DOI: 10.1186/1471-2164-10-277

[16] Puram SV, Tirosh I, Parikh AS, et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer[J]. Cell, 2017, 171(7): 1611-1624.e24. DOI: 10.1016/j.cell.2017.10.044

[17] Li YN, Sun YM, Yu K, et al. Keratin: a potential driver of tumor metastasis[J]. Int J Biol Macromol, 2025, 307: 141752. DOI: 10.1016/j.ijbiomac.2025.141752

[18] Han SX, Fan HN, Zhong GX, et al. Nuclear KRT19 is a transcriptional corepressor promoting histone deacetylation and liver tumorigenesis[J]. Hepatology, 2025, 81(3): 808-822. DOI: 10.1097/hep.0000000000000875

[19] Kiss M, Vande Walle L, Saavedra PHV, et al. IL1β promotes immune suppression in the tumor microenvironment independent of the inflammasome and gasdermin D[J]. Cancer Immunol Res, 2021, 9(3): 309-323. DOI: 10.1158/2326-6066.CIR-20-0431

[20] Han Y, Zhang YY, Pan YQ, et al. IL-1β-associated NNT acetylation orchestrates iron-sulfur cluster maintenance and cancer immunotherapy resistance[J]. Mol Cell, 2023, 83(11): 1887-1902.e8. DOI: 10.1016/j.molcel.2023.05.011

[21] Gu ZW, Wang L, Dong Q, et al. Aberrant LYZ expression in tumor cells serves as the potential biomarker and target for HCC and promotes tumor progression via csGRP78[J]. Proc Natl Acad Sci USA, 2023, 120(29): e2215744120. DOI: 10.1073/pnas.2215744120

[22] Hänggi K, Li J, Gangadharan A, et al. Interleukin-1α released during necrotic-like cell death generates myeloid-driven immunosuppression that restricts anti-tumor immunity[J]. Cancer Cell, 2024, 42(12): 2015-2031.e11. DOI: 10.1016/j.ccell.2024.10.014

[23] 宁艳萍, 陈柳燕, 周素芳. 坏死性凋亡在肿瘤治疗中的作用机制[J]. 中国生物化学与分子生物学报, 2025, 41(11): 1622-1632. DOI: 10.13865/j.cnki.cjbmb.2025.07.1169

[24] 张振雄, 秦仁义. 胰腺癌细胞死亡与肿瘤微环境相互影响研究现状及展望[J]. 中华实验外科杂志, 2024, 41(11): 2435-2439. DOI: 10.3760/cma.j.cn421213-20240508-01097

[25] Cai ZM, Tang BJ, Chen L, et al. Mast cell marker gene signature in head and neck squamous cell carcinoma[J]. BMC Cancer, 2022, 22(1): 577. DOI: 10.1186/s12885-022-09673-3

[26] Li SY, Wang W, Yu HH, et al. Characterization of genomic instability-related genes predicts survival and therapeutic response in lung adenocarcinoma[J]. BMC Cancer, 2023, 23(1): 1115. DOI: 10.1186/s12885-023-11580-0

[27] 张展瑞, 赵文浩, 胡子轩, 等. 基于铁死亡相关基因构建肺腺癌预后模型及验证[J]. 中国肺癌杂志, 2025, 28(1): 22-32. DOI: 10.3779/j.issn.1009-3419.2025.102.04

[28] Orobet KS, Karamyshev AL. Amyloid precursor protein and Alzheimer̓s disease[J]. Int J Mol Sci, 2023, 24(19): 14794. DOI: 10.3390/ijms241914794

[29] Fan WN, Xing Y, Yan S, et al. DUSP5 regulated by YTHDF1-mediated m6A modification promotes epithelial-mesenchymal transition and EGFR-TKI resistance via the TGF-β/Smad signaling pathway in lung adenocarcinoma[J]. Cancer Cell Int, 2024, 24(1): 208. DOI: 10.1186/s12935-024-03382-6

[30] Markovits E, Klymyshyn D, Froumine R, et al. Spatial profiling of HPV-stratified head and neck squamous cell carcinoma reveals distinct immune niches and microenvironmental architectures[J]. J Transl Med, 2025, 23(1): 1304. DOI: 10.1186/s12967-025-07280-x

[31] Ou D, Garberis I, Adam J, et al. Prognostic value of tissue necrosis, hypoxia-related markers and correlation with HPV status in head and neck cancer patients treated with bio-chemo-radiotherapy[J]. Radiother Oncol, 2018, 126(1): 116-124. DOI: 10.1016/j.radonc.2017.10.007

基金资助

北京市自然科学基金(7264256)