Identification of prognostic biomarkers for cervical cancer based on programmed cell death-related genes and assessment of their immune profile and response to drug therapy

IF 3.2 4区医学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Journal of Gene Medicine Pub Date : 2023-12-04 DOI:10.1002/jgm.3643

Sijie Feng, Zhenhui Wang, Huizhen Zhang, Baohua Hou, Yanjun Xu, Shuangying Hao, Yunkun Lu

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Abstract

Background

Programmed cell death (PCD) has been widely investigated in various human diseases. The present study aimed to identify a novel PCD-related genetic signature in cervical squamous cell carcinoma (CESC) to provide clues for survival, immunotherapy and drug sensitization prediction.

Methods

Single-sample gene set enrichment analysis (ssGSEA) was used to quantify the PCD score and assess the distribution of PCD in clinicopathological characteristics in The Cancer Genome Atlas (TCGA)-CESC samples. Then, the ConsensusClusterPlus method was used to identify molecular subtypes in the TCGA-CESC database. Genomic mutation analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment, as well as tumor microenvironment (TME) infiltration analysis, were performed for each molecular subtype group. Finally, a prognostic model by Uni-Cox and least absolute shrinkage and selection operator-Cox analysis was established based on differentially expressed genes from molecular subtypes. ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) and ssGSEA were performed to assess the correlation between the model and TME. Drug sensitization prediction was carried out with the oncoPredict package.

Results

Preliminary analysis indicated that PCD had a potential association clinical characteristics of the TCGA-CESC cohort, and PCD-related genes mutated in 289 (70.59%) CESC patients. Next, four groups of CESC molecular typing were clustered based on 63 significantly prognostic PCD-related genes. Among four subtypes, C1 group displayed the worst prognosis combined with over expressed PCD genes and enriched cell cycle-related pathways. C4 group exhibited the best prognosis accompanied with high degree of immune infiltration. Finally, a five-gene (SERPINE1, TNF, CA9, CX3CL1 and JAK3) prognostic model was constructed. Patients in the high-risk group displayed unfavorable survival. Immune infiltration analysis found that the low-risk group had significantly higher levels of immune cell infiltration such as T cells, Macrophages_M1, relative to the high-risk group, and were significantly enriched in apoptosis-associated pathways, which predicted a higher level of immunity. Drug sensitivity correlation analysis revealed that the high-risk group was resistant to conventional chemotherapeutic drugs and sensitive to the Food and Drug Administration-approved drugs BI.2536_1086 and SCH772984_1564.

Conclusions

In the present study, we first found that PCD-related gene expression patterns were correlated with clinical features of CESC patients, which predicts the feasibility of subsequent mining of prognostic features based on these genes. The five-PCD-associated-gene prognostic model showed good assessment ability in predicting patient prognosis, immune response and drug-sensitive response, and provided guidance for the elucidation of the mechanism by which PCD affects CESC, as well as for the clinical targeting of drugs.

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基于程序性细胞死亡相关基因的宫颈癌预后生物标志物鉴定及其免疫特征和对药物治疗反应的评估

背景:程序性细胞死亡(PCD)在各种人类疾病中得到了广泛的研究。本研究旨在发现宫颈鳞状细胞癌(CESC)中一个新的与pcd相关的遗传特征，为生存、免疫治疗和药物致敏预测提供线索。方法:采用单样本基因集富集分析(ssGSEA)定量PCD评分，评估PCD在the Cancer Genome Atlas (TCGA)-CESC样本临床病理特征中的分布。然后，使用ConsensusClusterPlus方法在TCGA-CESC数据库中识别分子亚型。对每个分子亚型组进行基因组突变分析、基因本体和京都基因与基因组百科全书功能富集分析以及肿瘤微环境(TME)浸润分析。最后，基于分子亚型差异表达基因，通过Uni-Cox、最小绝对收缩和选择算子- cox分析建立预后模型。通过ESTIMATE(即利用表达数据估计恶性肿瘤中的基质细胞和免疫细胞)和ssGSEA来评估模型与TME之间的相关性。使用oncoppredict包进行药物致敏预测。结果:初步分析显示PCD与TCGA-CESC队列有潜在的关联临床特征，289例(70.59%)CESC患者出现PCD相关基因突变。接下来，根据63个与pcd预后相关的基因对四组CESC分子分型进行聚类。4种亚型中，C1组预后最差，PCD基因过表达，细胞周期相关通路富集。C4组预后最好，且免疫浸润程度高。最后，构建五基因(SERPINE1、TNF、CA9、CX3CL1和JAK3)预后模型。高危组患者生存率较低。免疫浸润分析发现，与高危组相比，低危组T细胞、巨噬ges_m1等免疫细胞浸润水平显著升高，凋亡相关通路显著富集，预示着较高的免疫水平。药物敏感性相关分析显示，高危组对常规化疗药物耐药，对fda批准的药物BI.2536_1086和SCH772984_1564敏感。结论:在本研究中，我们首次发现pcd相关基因表达模式与CESC患者的临床特征相关，这预示了后续基于这些基因挖掘预后特征的可行性。PCD- 5相关基因预后模型在预测患者预后、免疫反应和药物敏感反应方面具有较好的评估能力，为阐明PCD影响CESC的机制及临床药物靶向治疗提供指导。

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来源期刊

Journal of Gene Medicine 医学-生物工程与应用微生物

CiteScore

6.40

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The aims and scope of The Journal of Gene Medicine include cutting-edge science of gene transfer and its applications in gene and cell therapy, genome editing with precision nucleases, epigenetic modifications of host genome by small molecules, siRNA, microRNA and other noncoding RNAs as therapeutic gene-modulating agents or targets, biomarkers for precision medicine, and gene-based prognostic/diagnostic studies. Key areas of interest are the design of novel synthetic and viral vectors, novel therapeutic nucleic acids such as mRNA, modified microRNAs and siRNAs, antagomirs, aptamers, antisense and exon-skipping agents, refined genome editing tools using nucleic acid /protein combinations, physically or biologically targeted delivery and gene modulation, ex vivo or in vivo pharmacological studies including animal models, and human clinical trials. Papers presenting research into the mechanisms underlying transfer and action of gene medicines, the application of the new technologies for stem cell modification or nucleic acid based vaccines, the identification of new genetic or epigenetic variations as biomarkers to direct precision medicine, and the preclinical/clinical development of gene/expression signatures indicative of diagnosis or predictive of prognosis are also encouraged.