CCDC134 as a Prognostic-Related Biomarker in Breast Cancer Correlating With Immune Infiltrates

Zhijian Huang; Linhui Yang; Jian Chen; Shixiong Li; Jing Huang; Yijie Chen; Jingbo Liu; Hongyan Wang; Hui Yu

doi:10.3389/fonc.2022.858487

CCDC134 as a Prognostic-Related Biomarker in Breast Cancer Correlating With Immune Infiltrates

Front Oncol. 2022 Mar 3:12:858487. doi: 10.3389/fonc.2022.858487. eCollection 2022.

Authors

Zhijian Huang^{1

2}, Linhui Yang¹, Jian Chen¹, Shixiong Li¹, Jing Huang³, Yijie Chen⁴, Jingbo Liu⁵, Hongyan Wang⁶, Hui Yu³

Affiliations

¹ Department of Breast Surgical Oncology, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China.
² The Graduate School of Fujian Medical University, Fuzhou, China.
³ Department of Pharmacy, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China.
⁴ Department of Ultrasound, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China.
⁵ Pathology Department, Daqing Longnan Hospital, The Fifth Affiliated Hospital of Qiqihar Medical College, Daqing, China.
⁶ Department of Pathology, Daqing Oilfield General Hospital, Daqing, China.

Abstract

Background: The expression of Coiled-Coil Domain Containing 134(CCDC134) is up-regulated in different pan-cancer species. However, its prognostic value and correlation with immune infiltration in breast cancer are unclear. Therefore, we evaluated the prognostic role of CCDC134 in breast cancer and its correlation with immune invasion.

Methods: We downloaded the transcription profile of CCDC134 between breast cancer and normal tissues from the Cancer Genome Atlas (TCGA). CCDC134 protein expression was assessed by the Clinical Proteomic Cancer Analysis Consortium (CPTAC) and the Human Protein Atlas. Gene set enrichment analysis (GSEA) was also used for pathway analysis. Receiver operating characteristic (ROC) curve was used to differentiate breast cancer from adjacent normal tissues. Kaplan-Meier method was used to evaluate the effect of CCDC134 on survival rate. The protein-protein interaction (PPI) network is built from STRING. Function expansion analysis is performed using the ClusterProfiler package. Through tumor Immune Estimation Resource (TIMER) and tumor Immune System Interaction database (TISIDB) to determine the relationship between CCDC134 expression level and immune infiltration. CTD database is used to predict drugs that inhibit CCDC134 and PubChem database is used to determine the molecular structure of identified drugs.

Results: The expression of CCDC134 in breast cancer tissues was significantly higher than that of CCDC134 mRNA expression in adjacent normal tissues. ROC curve analysis showed that the AUC value of CCDC134 was 0.663. Kaplan-meier survival analysis showed that patients with high CCDC134 had a lower prognosis (57.27 months vs 36.96 months, P = 2.0E-6). Correlation analysis showed that CCDC134 mRNA expression was associated with tumor purity immune invasion. In addition, CTD database analysis identified abrine, Benzo (A) Pyrene, bisphenol A, Soman, Sunitinib, Tetrachloroethylene, Valproic Acid as seven targeted therapy drugs that may be effective treatments for seven targeted therapeutics. It may be an effective treatment for inhibiting CCDC134.

Conclusion: In breast cancer, upregulated CCDC134 is significantly associated with lower survival and immune infiltrates invasion. Our study suggests that CCDC134 can serve as a biomarker of poor prognosis and a potential immunotherapy target in breast cancer. Seven drugs with significant potential to inhibit CCDC134 were identified.

Keywords: CCDC134; biomarker; breast cancer; immune infiltration; prognosis.