HER2 Expression Associated with Clinical Characteristics and Prognosis of Urothelial Carcinoma in a Chinese Population.

BACKGROUND: The frequency of HER2 overexpression in bladder cancer is reported as 9%-61%. HER2 alteration correlates with aggressive disease in bladder cancer. Traditional anti-HER2 targeted therapy has failed to show clinical benefits in patients with advanced urothelial carcinoma . METHODS: The information on pathologically proven patients with urothelial carcinoma with detected HER2 status was collected from the database of Peking University Cancer Hospital. The HER2 expression, as well as its association with clinical characteristics and prognosis, was analyzed. RESULTS: A total of 284 consecutive patients with urothelial carcinoma were enrolled. HER2 was positive (IHC 2+/3+) in 44% of urothelial carcinoma. HER2 positivity was found more frequent in UCB than in UTUC (51% vs. 38%). Stage, radical surgery, and histological variant were associated with survival (P < .05). For metastatic patients, multivariate analysis shows that 3 indicators, including liver metastasis, the number of involved organs, and anemia, are independent risk factors of prognosis. Receiving immunotherapy or disitamab vedotin (DV) treatment is an independent protecting factor. The survival of patients with low HER2 expression was also significantly improved by the treatment of DV (P < .001). HER2 expression (IHC 1+, 2+, 3+) was associated with a better prognosis in this population. CONCLUSION: DV has improved the survival of patients with urothelial carcinoma in the real world. With the new-generation anti-HER2 ADC treatment, HER2 expression is no longer a poor prognostic factor.

Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis.

BACKGROUND: Gastric cancer is one of the most common malignant cancers worldwide. Despite substantial developments in therapeutic strategies, the five-year survival rate remains low. Therefore, novel biomarkers and therapeutic targets involved in the progression of gastric tumors need to be identified. METHODS: We obtained the mRNA microarray datasets GSE65801, GSE54129 and GSE79973 from the Gene Expression Omnibus database to acquire differentially expressed genes (DEGs). We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to analyze DEG pathways and functions, and the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape to obtain the protein-protein interaction (PPI) network. Next, we validated the hub gene expression levels using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA), and conducted stage expression and survival analysis. RESULTS: From the three microarray datasets, we identified nine major hub genes: COL1A1, COL1A2, COL3A1, COL5A2, COL4A1, FN1, COL5A1, COL4A2, and COL6A3. CONCLUSION: Our study identified COL1A1 and COL1A2 as potential gastric cancer prognostic biomarkers.