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Journal of Peking University (Health Sciences) ›› 2023, Vol. 55 ›› Issue (5): 793-801. doi: 10.19723/j.issn.1671-167X.2023.05.004

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Risk modeling based on HER-2 related genes for bladder cancer survival prognosis assessment

Huan-rui LIU1,Xiang PENG1,2,Sen-lin LI1,Xin GOU1,*()   

  1. 1. Department of Urology, The First Hospital of Chongqing Medical University, Chongqing 400016, China
    2. Chongqing Key Laboratory of Molecular Tumor and Epigenetics, Chongqing 400016, China
  • Received:2023-03-20 Online:2023-10-18 Published:2023-10-09
  • Contact: Xin GOU E-mail:gouxincq@163.com

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Abstract:

Objective: To investigate the correlation between the human epidermal growth factor receptor-2-related genes (HRGs) and survival prognosis of bladder cancer and to construct a predictive model for survival prognosis of bladder cancer patients based on HRGs. Methods: HRGs in bladder cancer were found by downloading bladder tumor tissue mRNA sequencing data and clinical data from the cancer genome atlas (TCGA), downloading HER-2 related genes from the molecular signatures database (MsigDB), and crossing the two databases. Further identifying HRGs associated with bladder cancer survival (P < 0.05) by using single and multi-factor Cox regression analysis and constructing HRGs risk score model (HRSM), the bladder cancer patients were categorized into high-risk and low-risk groups accor-ding to the median risk score. Survival analysis of the patients in high- and low-risk groups was conducted using R language and correlation of HRGs with clinical characteristics. A multi-factor Cox regression analysis was used to verify the independent factors affecting the prognosis of the patients with bladder cancer. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) of HRSM was calculated, and a nomogram was constructed for survival prediction of the bladder cancer patients. Analysis of HRSM and patient immune cell infiltration correlation was made using the TIMER database. Results: A total of 13 HRGs associated with patient survival were identified in this study. Five genes (BTC, CDC37, EGF, PTPRR and EREG) were selected for HRSM by multi-factor Cox regression analysis. The 5-year survival rate of the bladder cancer patients in the high-risk group was significantly lower than that of the patients in the low-risk group. High expression of PTPRR was found to be significantly and negatively correlated with tumor grade and stage by clinical correlation analysis, while EREG was found to be the opposite; Increased expression of EGF was associated with high grade, however, the high expression ofCDC37showed the opposite result. And no significant correlation was found between BTC expression and clinical features. Correlation analysis of HRSM with immune cells revealed a positive correlation between risk score and infiltration of dendritic cells, CD8+T cells, CD4+T cells, neutrophils and macrophages. Conclusion: HRGs have an important role in the prognosis of bladder cancer patients and may serve as new predictive biomarkers and potential targets for treatment.

Key words: Bladder cancer, HER-2 related genes, Risk model, Prognosis, Immune cell infiltration

CLC Number: 

  • R737.1

Table 1

General clinical characteristics of patients with bladder cancer in the TCGA database"

CharacteristicsValue, n(%)
Age/year
  ≤65141 (37.7)
  >65233 (62.3)
Gender
  Female96 (25.7)
  Male278 (74.3)
Grade
  High354 (94.7)
  Low20 (5.3)
Clinical stage
  Ⅰ2 (0.5)
  Ⅱ105 (28.1)
  Ⅲ138 (36.9)
  Ⅳ129 (34.5)
T stage
  T01 (0.3)
  T13 (0.8)
  T2118 (31.6)
  T3194 (51.9)
  T458 (15.5)
N stage
  N0222 (59.4)
  N1-3126 (33.7)
  Nx26 (7.0)
M stage
  M0178 (47.6)
  M18 (2.1)
  Mx188 (50.3)

Figure 1

Single-factor Cox regression analysis of 13 HRGs associated with patient survival HRGs, HER-2 related genes."

Figure 2

Construction of HRSM for survival analysis A, distribution of patients based on risk scores; B, survival status for each patient (low risk, left side of the dashed line; high risk, right side of the dashed line); C, heat map of HRGs between low-risk groups (red) and high-risk groups (blue) (green, low expression level; red, high expression level); D, Kaplan-Meier survival curves for patients in the low-risk and high-risk groups. HRGs, HER-2 related genes; HRSM, HRGs risk score model."

Figure 3

Multi-factor Cox regression analysis of risk scores"

Figure 4

Correlation between HRGs and clinical A, relationship between the gene expression of HRSM and clinical stage of bladder cancer (the horizontal line inside the box plot indicates the median of gene expression); B, C, D, relationship between the gene expression of HRSM and TNM stage; E, relationship between the gene expression of HRSM and pathologic grade of bladder cancer. HRSM, HRGs risk score model; HRGs, HER-2 related genes; HG, high grade; LG, low grade. *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant."

Figure 5

ROC curves for HRSM and general clinical features HRSM, HRGs risk score model; HRGs, HER-2 related genes; AUC, area under the curve; ROC, receiver operating characteristic curve."

Figure 6

Construction of a prognostic nomogram for bladder cancer patients based on HRGs HRGs, HER-2 related genes."

Figure 7

Calibration curves for prognostic nomograms The gray line indicates the idealized model, and the better the match with the gray line, the better the prediction ability. OS, overall survival."

Figure 8

Graph of the relationship between risk score and immune cell infiltration The closer the correlation value is to 1 or-1, the stronger the positive or negative correlation is. cor, correlation."

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