ABSTRACT
BACKGROUND: Pelvic lipomatosis (PL) is a rare benign condition with characteristic overgrowth of histologically benign fat and invasion and compression of pelvic organs, often leading to non-specific lower urinary tract symptoms (LUTS). Approximately 40% of patients with PL have cystitis glandularis (CG). The cause of PL combined with CG is poorly understood, and there is currently no effective treatment. Refractory CG with upper urinary tract obstruction even requires partial or radical bladder resection. CASE SUMMARY: In this case, a patient suffering from PL with CG was treated by transurethral resection of bladder tumour (TUR-BT) and oral administration of celecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor. The LUTS were alleviated, and the cystoscopy results improved significantly. Immunohistochemistry showed up-regulated COX-2 expression in the epithelium of TUR-BT samples, suggesting that COX-2 may participate in the pathophysiological process of PL combined with CG. CONCLUSION: We report for the first time that celecoxib may be an effective treatment strategy for PL combined with refractory CG.
ABSTRACT
Backgrounds: Colorectal cancer (CRC) with high incidence, has the third highest mortality of tumors. DNA damage and repair influence a variety of tumors. However, the role of these genes in colon cancer prognosis has been less systematically investigated. Here, we aim to establish a corresponding prognostic signature providing new therapeutic opportunities for CRC. Method: After related genes were collected from GSEA, univariate Cox regression was performed to evaluate each gene's prognostic relevance through the TCGA-COAD dataset. Stepwise COX regression was used to establish a risk prediction model through the training sets randomly separated from the TCGA cohort and validated in the remaining testing sets and two GEO datasets (GSE17538 and GSE38832). A 12-DNA-damage-and-repair-related gene-based signature able to classify COAD patients into high and low-risk groups was developed. The predictive ability of the risk model or nomogram were evaluated by different bioinformatics- methods. Gene functional enrichment analysis was performed to analyze the co-expressed genes of the risk-based genes. Result: A 12-gene based prognostic signature established within 160 significant survival-related genes from DNA damage and repair related gene sets performed well with an AUC of ROC 0.80 for 5 years in the TCGA-CODA dataset. The signature includes CCNB3, ISY1, CDC25C, SMC1B, MC1R, LSP1P4, RIN2, TPM1, ELL3, POLG, CD36, and NEK4. Kaplan-Meier survival curves showed that the prognosis of the risk status owns more significant differences than T, M, N, and stage prognostic parameters. A nomogram was constructed by LASSO regression analysis with T, M, N, age, and risk as prognostic parameters. ROC curve, C-index, Calibration analysis, and Decision Curve Analysis showed the risk module and nomogram performed best in years 1, 3, and 5. KEGG, GO, and GSEA enrichment analyses suggest the risk involved in a variety of important biological processes and well-known cancer-related pathways. These differences may be the key factors affecting the final prognosis. Conclusion: The established gene signature for CRC prognosis provides a new molecular tool for clinical evaluation of prognosis, individualized diagnosis, and treatment. Therapies based on targeted DNA damage and repair mechanisms may formulate more sensitive and potential chemotherapy regimens, thereby expanding treatment options and potentially improving the clinical outcome of CRC patients.