Holliday junction recognition protein (HJURP) could reflect the clinical outcomes of lung adenocarcinoma patients, and impact the choice of precision therapy

Abstract

Background: Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer (NSCLC), characterized by poor prognosis and a high mortality rate. Identifying reliable prognostic biomarkers and potential therapeutic targets is crucial for improving patient outcomes.

Methods: We conducted a comprehensive analysis of HJURP expression in LUAD using data from four cohorts: TCGA-LUAD (n = 453), GSE31210 (n = 226), GSE68465 (n = 442), and GSE72094 (n = 386). Univariate Cox regression analysis was employed to identify prognostic genes, with Kaplan-Meier survival analysis used to assess the predictive power of HJURP. Functional enrichment analyses were performed using MetaScape and FGSEA, and spatial transcriptomics and single-cell sequencing data were analyzed to explore HJURP's distribution and potential functions. Additionally, correlations between HJURP expression and genetic alterations, immune cell infiltration, and potential therapeutic responses were evaluated.

Results: HJURP was identified as a significant prognostic biomarker in all four cohorts, with high expression associated with increased risk of overall survival (OS) death (TCGA-LUAD: HR = 1.93, 95% CI: 1.321-2.815, P < 0.001; GSE31210: HR = 2.75, 95% CI: 1.319-5.735, P = 0.007; GSE68465: HR = 1.57, 95% CI: 1.215-2.038, P < 0.001; GSE72094: HR = 2.2, 95% CI: 1.485-3.27, P < 0.001). Functional analyses indicated that HJURP is involved in DNA metabolic processes, cell cycle regulation, and mitotic processes, with significant activation of pathways related to MYC targets, G2M checkpoint, and DNA repair. High HJURP expression was associated with higher mutation frequencies in TP53, CSMD3, TTN, and MUC16, and positively correlated with pro-inflammatory immune cell infiltration and several immune checkpoints, including PD-L1 and PD-L2. Chemotherapeutic agents such as gefitinib and sorafenib were predicted to be effective against high HJURP-expressing tumors.

Conclusion: HJURP is a pivotal biomarker for LUAD, consistently associated with poor prognosis and advanced disease stages. Its high expression correlates with specific genetic alterations and immune profiles, highlighting its potential as a therapeutic target. Future studies should validate these findings in larger cohorts.

Keywords: HJURP; genetic alterations; immune infiltration; lung adenocarcinoma; prognosis.

FIGURE 1

Identification of Prognostic Genes in Four Cohorts Using Univariate Cox Regression Analysis (A–D). Univariate cox regression analysis across TCGA-LUAD (A), GSE31210 (B), GSE68465 (C), and GSE72094 (D); (E). Merged analysis of the risk genes identified across the four cohorts by Venn plot; (F). Pan-cancer analysis of HJURP expression among tumor and normal tissues across 18 types of tumors. BLCA: Bladder Urothelial Carcinoma; BRCA: Breast invasive carcinoma; COAD: Colon adenocarcinoma; ESCA: Esophageal carcinoma; HNSC: Head and Neck squamous cell carcinoma; KICH: Kidney Chromophobe; KIRC: Kidney renal clear cell carcinoma; KIRP: Kidney renal papillary cell carcinoma; LIHC: Liver hepatocellular carcinoma; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; PAAD: Pancreatic adenocarcinoma; PCPG: Pheochromocytoma and Paraganglioma; PRAD: Prostate adenocarcinoma; READ: Rectum adenocarcinoma; STAD: Stomach adenocarcinoma; THCA: Thyroid carcinoma; UCEC: Uterine Corpus Endometrial Carcinoma.

FIGURE 2

Kaplan-Meier Survival Analysis of HJURP Gene Expression Across Different Cohorts. (A–D). Kaplan-Meier showing the prognostic value of HJURP across TCGA-LUAD (A), GSE31210 (B), GSE68465 (C), and GSE72094 (D); (E). Meta-analysis of HJURP gene expression impact on clinical outcomes.

FIGURE 3

HJURP Expression Analysis Across Pan-Cancer, TCGA, and Validation Cohorts. (A) HJURP expression in TCGA-LUAD tumors and paired adjacent normal samples; (B) Validation of HJURP expression in GSE40791 and GSE31547 cohorts; (C) HJURP expression comparing by gender subgroup in TCGA-LUAD, GSE31210, and GSE68465 cohorts; (D) HJURP expression comparing by smoking status in TCGA-LUAD and GSE31210 cohorts; (E) HJURP expression comparing by race in the GSE68465 cohort.

FIGURE 4

HJURP Expression Analysis by Tumor Stage, Differentiation, and Treatment Outcome. (A) HJURP expression comparing by tumor stage in TCGA-LUAD, GSE31210, GSE68465, and GSE72094 cohorts; (B) HJURP expression comparing by differentiation grade in TCGA-LUAD samples; (C) HJURP expression comparing by treatment outcome in the TCGA-LUAD cohort. (D) Immunofluorescent staining picture shows that HJURP mostly localized in the nucleoplasm and nucleoli.

FIGURE 5

Spatial Transcriptomics and Single-Cell Sequencing Analysis of HJURP Expression in LUAD Tumor Tissues. (A) Spatial distribution of tumor cells in LUAD tissues; (B) Spatial distribution of HJURP expression in LUAD tissues; (C) Spatial distribution of immune cells in LUAD tissues; (D) Correlation analysis of HJURP expression with various cell types in LUAD tissues; (E) HJURP mRNA levels in different cell lineages in lung cancer tissues by single-cell sequencing data; (F) UMAP visualization of HJURP expression in single-cell sequencing data; (G) UMAP visualization of different cell types in single-cell sequencing data; (H) Proportion of cell types with positive HJURP expression in lung cancer tissues.

FIGURE 6

Correlation and Functional Enrichment Analysis of HJURP Expression in LUAD. (A) Correlation between HJURP expression and over 20,000 other genes; (B) Biological function enrichment analysis of the top 200 genes most correlated with HJURP expression; (C) Pathway activation analysis in patients with high versus low HJURP expression using the FGSEA algorithm; (D) Correlation of HJURP expression with the activation levels of 14 tumor development-related signaling pathways.

FIGURE 7

HJURP Expression, Gene Mutations, and Immune Cell Infiltration in LUAD (A) Expression of HJURP in wild-type and mutated HJURP samples; (B) HJURP expression in TCGA-LUAD samples with mutations in various genes; (C) Survival curve comparing overall survival between mutant and wild-type HJURP patients; (D) Validation of HJURP expression in TP53-mutated samples in GSE26339 and GSE72094 cohorts; (E) Validation of HJURP expression in EGFR-mutated samples in GSE72094 cohort; (F) Correlation of HJURP expression with immune cell infiltration in LUAD; (G) Distribution of HJURP expression groups in six immune subtypes of LUAD.

FIGURE 8

Correlation of HJURP Expression with Immune Checkpoints and Drug Sensitivity. (A) Correlation of HJURP expression with various immune checkpoint genes across multiple cohorts; (B) HJURP expression in responders (R) and non-responders (NR) to anti-PD-L1 treatment in the IMvigor210 cohort (2018); (C) HJURP expression in responders (R) and non-responders (NR) to anti-PD-L1 treatment in the Wolf cohort (2021); (D) Correlation of HJURP expression with drug sensitivity in the GDSC1 database; (E) Correlation of HJURP expression with drug sensitivity in the CTRP database.