RNA结合蛋白HuR通过调控ITGB1促进非小细胞肺癌进展的生物信息学分析及验证

doi:10.3969/j.issn.1674-8115.2026.04.005

摘要/Abstract

摘要：

目的·系统鉴定RNA结合蛋白人类抗原R（human antigen R，HuR）在非小细胞肺癌（non-small cell lung cancer，NSCLC）中的下游关键靶基因，并阐明其通过调控该靶点影响肿瘤进展的分子机制。方法·基于癌症基因组图谱（The Cancer Genome Atlas，TCGA）数据库、基因型-组织表达项目（Genotype-Tissue Expression，GTEx）数据库及临床蛋白质组学肿瘤分析联盟（Clinical Proteomic Tumor Analysis Consortium，CPTAC）数据库，分析HuR在NSCLC及癌旁组织中的表达差异；通过免疫组织化学法检测HuR蛋白水平，并利用GSE19188数据集进行验证。基于TCGA数据，分析HuR表达与临床病理参数间关系，进行生存分析，并通过单因素与多因素Cox回归评估预后因素，构建列线图模型预测生存率。利用ESTIMATE包及CIBERSORT算法分析HuR表达与免疫微环境的相关性。采用Transwell实验检测HuR敲低后A549细胞迁移与侵袭能力变化。通过RNA测序筛选差异表达基因（differentially expressed genes，DEGs），结合蛋白质相互作用（protein-protein interaction，PPI）网络鉴定枢纽基因，并利用基因本体论（Gene Ontology，GO）与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes，KEGG）进行富集分析。采用RNA免疫沉淀（RNA immunoprecipitation，RIP）验证HuR与整合素β1（integrin β 1，ITGB1） mRNA的直接结合，并通过实时定量PCR（RT-qPCR）和Western blotting分别检测HuR敲低后ITGB1在mRNA和蛋白水平的表达变化。结果·HuR在肺癌组织中显著高表达，与不良预后独立相关（P=0.045），且其表达与免疫抑制性微环境特征呈负相关。功能实验表明敲低HuR可显著抑制肺癌细胞的迁移（P<0.001）与侵袭（P=0.002）能力。生物信息学分析将ITGB1锁定为HuR下游的核心枢纽基因，富集分析显示其参与细胞外基质受体相互作用等通路。RIP实验证实HuR可直接结合ITGB1 mRNA；进一步的RT-qPCR与Western blotting结果表明，敲低HuR导致ITGB1在mRNA和蛋白水平均显著下调，提示HuR主要通过维持ITGB1 mRNA稳定性发挥转录后调控作用。结论·HuR通过直接结合并稳定ITGB1 mRNA，激活下游信号通路，促进NSCLC进展。HuR-ITGB1调控轴的发现不仅为深入理解肺癌的发病机制提供了新视角，也为预后判断和靶向治疗提供了潜在新靶点。

关键词: 非小细胞肺癌, 人类抗原R, 生物信息学分析, 枢纽基因, 免疫细胞浸润, 预测模型

Abstract:

Objective ·To systematically identify the key downstream target genes of the RNA-binding protein human antigen R (HuR) in non-small cell lung cancer (NSCLC) and to elucidate the molecular mechanisms through which HuR influences tumor progression by regulating this target. Methods ·Based on the The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, the differential expression of HuR in NSCLC and adjacent tissues was analyzed. HuR protein levels were detected via immunohistochemistry and validated by using the GSE19188 dataset. Using TCGA data, the relationship between HuR expression and clinicopathological parameters was analyzed; survival analysis was performed, and univariate and multivariate Cox regression analyses were conducted to assess prognostic factors, followed by the construction of a nomogram model to predict survival rates. The ESTIMATE package and CIBERSORT algorithm were used to analyze the correlation between HuR expression and the tumor immune microenvironment. A Transwell assay was employed to detect changes in the migration and invasion capabilities of A549 cells after HuR knockdown. RNA-seq was used to screen for differentially expressed genes (DEGs), and hub genes were identified by combining protein-protein interaction (PPI) network analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for functional enrichment. Mechanistically, RNA immunoprecipitation (RIP) was used to validate the direct binding between HuR and integrin β 1 (ITGB1) mRNA. Furthermore, real-time quantitative PCR (RT-qPCR) and Western blotting were performed to detect the expression changes of ITGB1 at the mRNA and protein levels, respectively, after HuR knockdown. Results ·HuR was significantly overexpressed in lung cancer tissues, independently associated with poor prognosis (P=0.045), and negatively correlated with characteristics of an immunosuppressive microenvironment. Functional experiments demonstrated that HuR knockdown significantly inhibited the migration (P<0.001) and invasion (P=0.002) capabilities of lung cancer cells. Bioinformatic analysis identified ITGB1 as the core hub gene downstream of HuR, and enrichment analysis revealed its significant involvement in pathways such as the extracellular matrix (ECM)-receptor interaction. RIP assays confirmed that HuR directly binds to ITGB1 mRNA. Further RT-qPCR and Western blotting results indicated that HuR knockdown led to significant downregulation of ITGB1 at both the mRNA (P=0.001) and protein levels, suggesting that HuR primarily exerts its post-transcriptional regulatory role by maintaining ITGB1 mRNA stability. Conclusion ·HuR promotes NSCLC progression by directly binding to and stabilizing ITGB1 mRNA, thereby activating downstream signaling pathways. The discovery of the HuR-ITGB1 regulatory axis not only provides a novel perspective for understanding the pathogenesis of lung cancer but also offers a potential target for prognosis assessment and targeted therapy.

Key words: non-small cell lung cancer (NSCLC), human antigen R (HuR), bioinformatic analysis, hub gene, immune cell infiltration, predictive model

中图分类号:

R734.2

彭倩倩, 宋璟涵, 徐杏怡, 肖辉. RNA结合蛋白HuR通过调控ITGB1促进非小细胞肺癌进展的生物信息学分析及验证[J]. 上海交通大学学报（医学版）, 2026, 46(4): 451-466.

Peng Qianqian, Song Jinghan, Xu Xingyi, Xiao Hui. Bioinformatic analysis and validation of the RNA-binding protein HuR promoting non-small cell lung cancer progression via ITGB1[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2026, 46(4): 451-466.

图/表 11

表1 TCGA与GTEx数据集肿瘤及正常组织样本数

Tab 1 Sample counts of tumor and normal tissues from TCGA and GTEx datasets

TCGA	Detail	Tumor/n	Normal/n	GTEx	Normal/n
ACC	Adrenocortical carcinoma	79	‒	Adrenal gland	128
BLCA	Bladder urothelial carcinoma	408	19	Bladder	9
BRCA	Breast invasive carcinoma	1 093	112	Breast	179
CESC	Cervical squamous cell carcinoma and endocervical adenocarcinoma	304	3	Cervix uteri	10
CHOL	Cholangio carcinoma	36	9	‒	‒
COAD	Colon adenocarcinoma	457	41	Colon	308
DLBC	Lymphoid neoplasm diffuse large B-cell lymphoma	48	‒	Blood	337
ESCA	Esophageal carcinoma	184	11	Esophagus	273
GBM	Glioblastoma multiforme	153	5	Brain	207
HNSC	Head and neck squamous cell carcinoma	520	44	‒	‒
KICH	Kidney chromophobe	66	25	Kidney	28
KIRC	Kidney renal clear cell carcinoma	533	72	Kidney	28
KIRP	Kidney renal papillary cell carcinoma	290	32	Kidney	28
LAML	Acute myeloid leukemia	173	‒	Bone marrow	70
LGG	Brain lower grade glioma	516	‒	Brain	207
LIHC	Liver hepatocellular carcinoma	371	50	Liver	110
LUAD	Lung adenocarcinoma	515	59	Lung	288
LUSC	Lung squamous cell carcinoma	501	50	Lung	288
MESO	Mesothelioma	87	‒	‒	‒
OV	Ovarian serous cystadenocarcinoma	303	‒	Ovary	88
PAAD	Pancreatic adenocarcinoma	178	4	Pancreas	167
PCPG	Pheochromocytoma and paraganglioma	179	3	‒	‒
PRAD	Prostate adenocarcinoma	497	52	Prostate	100
READ	Rectum adenocarcinoma	166	10	Colon	308
SARC	Sarcoma	259	2	‒	‒
SKCM	Skin cutaneous melanoma	103	‒	Skin	557
STAD	Stomach adenocarcinoma	415	35	Stomach	175
TGCT	Testicular germ cell tumor	150	‒	Testis	165
THCA	Thyroid carcinoma	501	59	Thyroid	278
THYM	Thymoma	120	‒	Blood	337
UCEC	Uterine corpus endometrial carcinoma	545	35	Uterus	78
UCS	Uterine carcinosarcoma	57	‒	Uterus	78
UVM	Uveal melanoma	80	‒	‒	‒
Total		9 887	732		3 555

表2 CPTAC数据集肿瘤与配对正常组织样本数

Tab 2 Sample counts of tumor and matched normal tissues from the CPTAC dataset

CPTAC	Detail	Tumor/n	Normal/n
BRCA	Breast cancer	126	18
CCRCC	Clear cell renal cell carcinoma	117	84
COAD	Colon adenocarcinoma	101	96
GBM	Glioblastoma	156	5
HNSC	Head and neck squamous cell carcinoma	110	68
NSCLC	Non-small cell lung cancer	217	199
OV	Ovarian serous cystadenocarcinoma	93	10
UCEC	Uterine corpus endometrial carcinoma	104	30
PAAD	Pancreatic adenocarcinoma	137	74
LIHC	Liver hepatocellular carcinoma	128	106
Total		1 289	690

表3 RT-qPCR引物序列

Tab 3 Primer sequences for RT-qPCR

Gene	Forward (5'→3')	Reverse (5'→3')
HuR	TAATCGCCATAGCCTTCCTAA	GGCGTCTGCAAATGGTTGTA
β-actin	ATCAAGATCATTGCTCCTCCTGAG	CTGCTTGCTGATCCACATCTG
ITGB1	ATCCCAGAGGCTCCAAGAT	CCCCTGATCTTAATCGCAA

图1 肺癌组织中 HuR 的上调表达Note： A/B. Expression of HuR in 33 cancer types compared with normal tissues based on TCGA (A) and TCGA combined with the GTEx (B) datasets, with only statistically significant comparisons displayed. C. Differential expression of HuR between tumor and matched normal tissues across 10 cancer types from the CTPAC database. D. Representative immunohistochemistry images of HuR protein in lung cancer and adjacent normal tissues. E. Immunoreactivity scores of HuR in lung cancer versus normal tissues. F/G. Validation of HuR overexpression in lung cancer using TCGA (F) and GSE19188 (G) datasets. ACC—adrenocortical carcinoma; BLCA—bladder urothelial carcinoma; BRCA—breast invasive carcinoma; CESC—cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL—cholangiocarcinoma; COAD—colon adenocarcinoma; DLBC—lymphoid neoplasm diffuse large B-cell lymphoma; ESCA—esophageal carcinoma; GBM—glioblastoma multiforme; HNSC—head and neck squamous cell carcinoma; KIRP—kidney renal papillary cell carcinoma; LAML—acute myeloid leukemia; LGG—brain lower grade glioma; LIHC—liver hepatocellular carcinoma; LUAD—lung adenocarcinoma; LUSC—lung squamous cell carcinoma; OV—ovarian serous cystadenocarcinoma; PAAD—pancreatic adenocarcinoma; PCPG—pheochromocytoma and paraganglioma; PRAD—prostate adenocarcinoma; READ—rectum adenocarcinoma; STAD—stomach adenocarcinoma; TGCT—testicular germ cell tumor; THCA—thyroid carcinoma; THYM—thymoma; UCEC—Uterine corpus endometrial carcinoma; UCS—uterine carcinosarcoma; CCRCC—clear cell renal cell carcinoma.

Fig 1 Up-regulated expression of HuR in lung cancer tissues

图2 HuR 表达对肺癌的诊断与预后价值Note： A. ROC curve showing the diagnostic potential of HuR in lung cancer. B‒D. Kaplan-Meier survival analyses comparing high and low HuR expression groups: overall survival (OS) in all patients (B); DSS in all patients (C); OS in stage Ⅲ‒Ⅳ patients (D). E‒I. Associations between HuR expression and T stage (E), N stage (F), M stage (G), histologic grade (H), and smoking status (I) in lung cancer patients.

Fig 2 Diagnostic and prognostic value of HuR expression in lung cancer

图3 肺癌预后影响因素分析及预后模型构建Note： A/B. Forest plots of univariate (A) and multivariate (B) Cox regression analyses of clinicopathological characteristics in lung cancer patients. C. Prognostic nomogram integrating clinical variables and HuR expression for predicting 1-, 3-, and 5-year OS in lung cancer patients. D. Calibration curves of the prognostic model.

Fig 3 Analysis of prognostic factors and construction of a prognostic model in lung cancer

图4 HuR表达与肿瘤免疫微环境的负相关性Note： A. Heatmaps showing correlations between HuR expression and ImmuneScore, StromalScore, and ESTIMATEScore across 33 cancer types. B. Lollipop plot depicting the correlation between HuR expression and the infiltration levels of 24 immune cell types in lung cancer. C. Scatter plots illustrating the correlations between HuR expression and specific immune cell infiltration levels. D. Comparison of immune infiltration scores for 24 immune cell types between HuR high- and low-expression groups in lung cancer. Cor—correlation. NK cells—natural killer cells; Tgd—γδT cells; Tcm—central memory T cells; TReg—regulatory T cells; Tem—effector memory T cells; TFH—follicular helper T cells; DC—dendritic cells; aDC—activated dendritic cells; iDC—immature dendritic cells; pDC—plasmacytoid dendritic cells.

Fig 4 Negative correlation between HuR expression and the tumor immune microenvironment in lung cancer

图5 HuR 敲低对A549细胞迁移与侵袭的抑制效果Note： A. Western blotting analysis of A549 wild-type (WT) cells, negative-control (NC) cells, and A549 HuR-KD cells. B. Relative mRNA expression of HuR in Lipofectamine 2000-treated NC cells and A549 HuR-KD cells. C‒F. Representative images (C, D) and quantitative analyses (E, F) of migration (C, E) and invasion (D, F) assays in A549 HuR-KD vs NC cells.

Fig 5 Inhibitory effect of HuR knockdown on the migration and invasion of A549 cells

图6 HuR 敲低诱导的转录组重编程与 ITGB1 下调Note： A. PCA plot of RNA-seq samples from HuR-KD and A549 WT cells. B/C. Volcano plot (B) and heatmap (C) of DEGs between HuR-KD and A549 WT cells. D. PPI network of identified DEGs. Nodes represent DEGs; edges indicate functional interactions between nodes. FC—fold change.

Fig 6 Transcriptional reprogramming and ITGB1 downregulation induced by HuR knockdown

图7 功能富集分析揭示HuR通过ITGB1调控肺癌微环境的潜在机制Note： A. Bubble plot of GO enrichment analysis of DEGs after HuR-KD in lung cancer cells. B. Chord plot visualizing GSEA results. ES—Enrichment score. C. Bubble plot of KEGG pathway enrichment analysis. D. Circle plot displaying KEGG functional enrichment. E. Circle plot displaying GO functional enrichment.

Fig 7 Functional enrichment analysis reveals the potential mechanism of HuR in regulating the lung cancer microenvironment via ITGB1

图8 HuR与ITGB1的分子相互作用及表达调控验证Note： A. Western blotting analysis of target protein HuR after RIP, showing the expression levels in the Input, IgG control, and IP (anti-HuR antibody) groups. B. RIP-qPCR analysis of the binding between HuR protein and ITGB1 mRNA in A549 cells. RNA-protein complexes were immunoprecipitated using an anti-HuR antibody, and the enrichment of ITGB1 was detected by qPCR. C/D. Western blotting (C) and RT-qPCR (D) analyses showing that knockdown of HuR led to a decrease in both mRNA and protein levels of ITGB1 in A549 cells.

Fig 8 Validation of the molecular interaction and expression regulation between HuR and ITGB1

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