Prognostic Significance of CCDC8 in Bladder Cancer: Insights from Bioinformatics and Immunohistochemical Analysis

Abstract

Background: Pro-apoptotic coiled-coil domain containing 8 (CCDC8) has been linked to tumor progression and metastasis, yet its prognostic significance and underlying molecular mechanisms in bladder cancer remain to be elucidated. Materials and methods: This study utilized raw data from public databases along with a single-center retrospective case series. We performed bioinformatics analysis and immunohistochemistry to investigate the biological landscape of CCDC8 in various tumors, with a particular focus on bladder cancer. This involved examining its expression characteristics and prognostic value. Gene function enrichment analysis was conducted to perform functional annotation, evaluate the association between bladder cancer molecular subtypes and mutation spectra, and analyze the tumor immune microenvironment to predict treatment response sensitivity. Results: Our study identified CCDC8 as a novel prognostic marker for bladder cancer. We observed that high CCDC8 expression correlates with poor prognosis and a suboptimal response to immunotherapy in bladder cancer. CCDC8 was implicated in regulating tumor immune status, metabolic activity, and cell cycle-related signaling pathways, thereby influencing the biological behavior of tumor cells. Additionally, CCDC8 contributed to the suppression of the immune microenvironment, diminishing anti-tumor immune responses. Comprehensive characterization of CCDC8 was applied to prognostic prediction in bladder cancer, indicating that targeting CCDC8 may be a potential therapeutic strategy. Conclusions: These findings suggest that CCDC8 serves as an independent biomarker for predicting prognosis and immunotherapy efficacy for bladder cancer. Further investigation into its specific molecular mechanisms may offer new therapeutic strategies for treating bladder cancer.

Keywords: bladder cancer; computational biology and bioinformatics; pro-apoptotic coiled-coil domain containing 8 (CCDC8); tumor microenvironment.

Figure 1

Expression, prognostic value, and mutation characteristics of CCDC8 in Pan-cancer. (A) CCDC8 expression across 34 cancer types compared to normal tissues, as analyzed using TCGA data. (B) Forest plot illustrating the associations between CCDC8 expression and overall survival in various cancer types (pan-cancer). (C) Map position of CCDC8 mutations in pan-cancer, highlighting mutation frequency and locations within the gene. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Figure 2

Prognostic value of the CCDC8 expression in Bladder Cancer. (A-C) CCDC8 expression in different (A) Age, (B) Sex and (C) Stage in cohort1. (D-F) CCDC8 expression in different (D) Age, (E) Sex and (F) Stage in cohort2. (G) Representative immunohistochemistry images for CCDC8 in bladder cancer (100X, bar=500uM and 400X,bar=100uM). (H-J) OS for CCDC8 in (H) cohort1 and (I) cohort3, RFS for CCDC8 in (J) cohort2.

Figure 3

Functional annotation of differentially expressed genes. (A-C) Functional enrichment analysis of upregulated DEGs: (A) Gene Ontology (GO) terms, (B) KEGG pathways, and (C) Hallmark gene sets. (D-F) Functional enrichment analysis of downregulated DEGs: (D) Gene Ontology (GO) terms, (E) KEGG pathways, and (F) Hallmark gene sets.

Figure 4

Association of CCDC8 with molecular subtypes and differentiation pathways in Bladder Cancer. Differential expression of bladder cancer-related signatures between high and low CCDC8 expression groups in (A) cohort 1 and (B) cohort 3. *P < 0.05, ***P < 0.001, and ****P < 0.0001.

Figure 5

The relationship between CCDC8 expression and the tumor immune microenvironment in cohort1. (A) Heatmap showing the distribution of immune cells between high and low CCDC8 expression groups. (B-C) Correlation violin plots depicting the differences between high and low CCDC8 expression groups in (B) the immune cycle and (C) immune checkpoints. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Figure 6

The relationship between CCDC8 expression and the tumor immune microenvironment in cohort 3. Heatmap showing the distribution of immune cells between high and low CCDC8 expression groups. (B-C) Correlation violin plots depicting the differences between high and low CCDC8 expression groups in (B) the immune cycle and (C) immune checkpoints. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Figure 7

CCDC8 predicts immunotherapy response. (A) relationship between CCDC8 and immune response-related pathways in cohort1 and(B) cohort3. (C-G) CCDC8 expression in patients with (C) different clinical response of tumor immunotherapy, (D) immune cell infiltration types, (E) enrollment IC, (F) IC levels and (G) TC levels. **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Figure 8

The relationship between CCDC8 expression and the signature of radiotherapy, chemotherapy, and targeted therapy in cohort 1. (A-C) Differential expression of therapeutic signatures between high and low CCDC8 groups: (A) targeted therapy and radiotherapy, (B) IC50 values for gemcitabine and cisplatin therapy, (C) drug-target genes. **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Figure 9

The relationship between CCDC8 expression and the signature of radiotherapy, chemotherapy, and targeted therapy in cohort 3. (A-C) Differential expression of therapeutic signatures between high and low CCDC8 groups: (A) targeted therapy and radiotherapy, (B) IC50 values for gemcitabine and cisplatin therapy, (C) drug-target genes. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Figure 10

The mutation profile in CCDC8 high and low groups. Comparison of the mutational landscape between CCDC8 high group and CCDC8 low group. *P < 0.05 and **P < 0.01 and ****P < 0.0001.