Oxidative stress contributes significantly to cancer development. Recent studies have demonstrated that oxidative stress could alter the epigenome and, in particular, DNA methylation. This study aimed to explore the potential link between oxidative stress and uterine corpus endometrial carcinoma (UCEC). An analysis of RNA-seq data and relevant clinical information was conducted with data from The Cancer Genome Atlas (TCGA), and oxidative stress genes were obtained from Gene Set Enrichment Analysis (GSEA). Differentially expressed genes (DEGs) in normal and tumor groups of UCEC were analyzed using GO and KEGG enrichment analysis. As a result of survival analysis, Lasso regression analysis of DEGs, a risk score model of oxidative stress-related genes (OSRGs) was constructed. Moreover, this study demonstrated that OSRGs are associated with immune cell infiltration in UCEC, suggesting oxidative stress may play a role in UCEC development by activating immune cells. We discovered 136 oxidative stress-related DEGs in UCEC, from which we screened 25 prognostic genes significantly related to the overall survival of UCEC patients. BCL2A1, CASP6, GPX2, HIC1, IL19, MSX1, RNF183, SFN, TRPM2 and HIST1H3C are associated with a good prognosis while CDKN2A, CHAC1, E2F1, GSDME, HMGA1, ITGA7, MCM4, MYBL2, PPIF, S100A1, S100A9, STK26 and TRIB3 are involved in a poor prognosis in UCEC. A 7-OSRGs-based risk score (H3C1, CDKN2A, STK26, TRPM2, E2F1, CHAC1, MSX1) was generated by Lasso regression. Further, an association was found between H3C1, CDKN2A, STK26, TRPM2, E2F1, CHAC1 and MSX1 expression levels and the immune infiltrating cells, including CD8 T cells, NK cells, and mast cells in UCEC. NFYA and RFX5 were speculated as common transcription factors of CDKN2A, TRPM2, E2F1, CHAC1, and MSX1 in UCEC.

Objective: To investigate the prognostic value of immune cells within omental metastases originating from advanced epithelial ovarian cancer (EOC). Methods: We performed immunohistochemical analysis to determine the levels of CD4+/CD8+ tumor-infiltrating lymphocytes (TILs) and CD68+ tumor-associated microphages (TAMs) in omental specimens from 100 patients with advanced EOC. Significant prognostic factors, including immune cells and clinical parameters, were assessed by Kaplan–Meier survival analysis and Cox models. Results: Cox regression analysis showed that elevated levels of CD68+ TAMs and intra-islet CD4+ TILs in omental metastases were the main risk factors associated with worse survival outcomes for advanced EOC. Moreover, the survival analysis of relationships between omental immune cells and favorable clinical predictors revealed additional prognostic stratification information. Conclusion: Omental immune cells (TAMs and TILs) provide alternative prognostic factors in advanced EOC. In contrast to markers of the EOC tumor microenvironment at the primary site, elevated CD68+ TAMs and intra-islet CD4+ TILs in omental metastases serve as negative prognostic markers in advanced EOC and imply an unfavorable outcome.

Purpose: Programmed death-ligand 1 (PD-L1) has been widely used as a prognostic biomarker and an immunotherapeutic target in numerous cancers, but information on the clinical significance of its expression in endometrial serous carcinoma (ESC) is largely lacking. Here, we evaluate the predictive value of PD-L1 expression in ESC. Materials and Methods: A total of 79 cases of ESC accessioned between January 2003 and September 2015 were selected for further analysis. PD-L1 expression was evaluated in whole tissue sections of these cases by using the tumor proportion score (TPS, cut-off 1%) and combined positive score (CPS, cut-off 1) scoring methods. Results: Overall, there was a heterogeneous expression of PD-L1, focal or patchy, in ESCs. PD-L1 positivity was observed in 43.0% of ESCs by TPS and 73.4% of ESCs by CPS. Kaplan–Meier survival analysis showed that patients with PD-L1-positive tumors suffered significantly worse OS and PFS, when compared with PD-L1 negative tumors (log-rank p = 0.037 and p = 0.003, respectively). In contrast, PD-L1 positivity by CPS within the ESC cases showed no statistical significance for OS and PFS (log-rank p = 0.720 and p = 0.928, respectively). Multivariate Cox analysis showed that PD-L1 positivity by TPS was significantly associated with PFS (HR = 1.921, p = 0.039) but not OS (HR = 1.229, p = 0.631). Conclusion: PD-L1 expression is frequently found in ESC, suggesting a potential role of the PD-1/PD-L1 pathway as a potential therapeutic target for these tumors. PD-L1 expression by TPS also serves as a negative prognostic marker in ESC and implies an unfavorable outcome.

Objective: To investigate the risk factors for complications in breast cancer patients with totally implantable access ports (TIAPs). Methods: This retrospective case-control study involved 471 breast cancer (BC) patients who received TIAPs during chemotherapy. We compared the demographic and clinical characteristics of patients with complications to those without, analyzed independent risk factors using binary logistic regression, and identified differences in complication rates based on catheterization site. Results: The most frequent complication was catheter malposition, followed by infection, thrombosis, hemothorax, and port rotation. Complications were more common in right-side BC cases ( P = .026) and with left-side insertions ( P = .012). Binary logistic regression identified independent risk factors for complications: catheter tip location (OR = 0.599, P = .013), and catheterization site (OR = 0.319, P = .019). Notably, left-side insertion significantly increased the risk of overall complications and catheter malposition compared to right-side insertion (OR = 3.534, P = .008; OR = 5.624, P = .004, respectively). Conclusion: Catheter tip location and catheterization site independently affect complications and catheter malposition. For TIAPs implantation, particularly on the left side, a lower catheter tip location is advised to reduce complications and enhance safety.

Background: Current research on breast-conserving surgery (BCS) focuses on recurrence and survival but overlooks the issue of residual tumors post-excisional biopsy. These remnants, crucial for surgical planning, often necessitate additional excisions, impacting BCS success. Our 5-year study of excisional biopsy patients identifies risk factors for residual tumors, offering insights to improve surgical decisions. Methods: This study examined 233 breast cancer patients split into training and validation groups (2:1 ratio). Logistic regression models identified predictors of post-biopsy residual tumors status, leading to the creation and validation of a preoperative nomogram for residual risk. Results: In this study of 233 patients, 23.9% with BCS had residual tumors after biopsy, significantly less than those in the non-BCS group (P<0.001). Tumor size, biopsy method, and histopathological subtype were crucial in predicting residual tumors and were used to develop a nomogram, which showed strong predictive accuracy for preoperative residual tumor status. This tool enhances preoperative risk stratification and aids in the formulation of personalized surgical strategies by providing visual quantification of the probabilities associated with oncological clearance parameters. Conclusions: We developed a clinically practical nomogram for predicting residual tumor status following excisional biopsy, facilitating preoperative risk stratification and personalized surgical strategy. Further prospective studies are necessary to evaluate its generalizability and accuracy.

Background: Preoperative differentiation between uterine mesenchymal tumors and benign uterine fibroids remains challenging in postmenopausal women. This study aimed to develop an exploratory risk-stratification model for uterine mesenchymal tumors and to characterize complementary molecular features of uterine leiomyosarcoma using a public transcriptomic dataset. Methods: A retrospective case–control study was conducted in postmenopausal patients with uterine masses who underwent surgery between 2011 and 2021. A total of 23 uterine mesenchymal tumor cases and 92 frequency-matched fibroid controls were included. Clinical variables were analyzed using univariable and multivariable logistic regression to develop an exploratory risk-stratification model. Model performance was evaluated using ROC analysis, calibration analysis, decision curve analysis, and confusion matrix assessment. Exploratory transcriptomic analysis was performed using the GEO dataset GSE64763 to characterize molecular differences between uterine leiomyosarcoma and fibroid tissues. Results: Pelvic pressure, abnormal uterine bleeding, and tumor diameter were independently associated with uterine mesenchymal tumors. The model achieved an apparent AUC of 0.859 and an optimism-corrected AUC of 0.846 after 1000 bootstrap resamples. Exploratory transcriptomic analysis revealed distinct expression patterns and upregulation of proliferation-associated genes, including CCNB1, BUB1B, PRC1, TOP2A, and FOXM1, with enrichment of cell cycle–related pathways. Conclusions: An exploratory model based on routinely available preoperative variables demonstrated preliminary discriminatory ability within the development cohort. Independent external validation in representative prospective cohorts is required before any assessment of clinical utility.