Yi Li

Multi-omics analysis reveals that ALYREF-mediated m5C modification promotes platinum resistance in ovarian cancer via the NSUN2/ALYREF/LGR4 axis

Abstract Platinum resistance remains a major obstacle to effective treatment and improved prognosis in ovarian cancer. Although 5-methylcytosine (m 5 C) RNA modification has been implicated in chemoresistance, its precise functional role in ovarian cancer remains unclear. In this study, we integrated RNA-Seq and single-cell transcriptomic data from cisplatin-resistant ovarian cancer cell lines and patient samples, identifying the m 5 C reader protein ALYREF as a key regulator of platinum resistance. Functional studies using ALYREF and NSUN2 knockdown, overexpression, and mutant constructs—combined with multi-omics analyses (RNA-Seq, m 5 C-BIS-Seq, and RIP-Seq)—revealed that ALYREF binds to m 5 C-modified LGR4 mRNA, enhancing its stability and promoting activation of the Wnt/β-catenin signaling pathway. Critically, this regulatory mechanism is dependent on NSUN2-mediated m 5 C modification of LGR4 mRNA. Together, our findings demonstrate that the NSUN2/ALYREF/LGR4 axis mediates platinum resistance through m 5 C-dependent stabilization of LGR4 and downstream Wnt signaling activation. Thus, targeting ALYREF may represent a promising strategy to overcome platinum resistance in ovarian cancer.

Prognostic Value and Immune-Infiltration Pattern of KIF4A in Patients with Endometrial Carcinoma

Background. With the development of sequencing technology, an increasing number of biomarkers has been identified in endometrial carcinoma (EC). However, there have been few comprehensive analyses of the KIF4A gene in patients with EC. Methods. Based on raw data in public databases, the KIF4A gene and protein expression in EC were validated. Logistic regression analysis was conducted to analyze the correlations between clinical characteristics and the KIF4A expression. Kaplan-Meier analysis was used to explore the difference in survival in clinical subgroups. Meanwhile, we used meta-analysis in multiple datasets to investigate the prognostic value of KIF4A. In addition, Cox regression analysis was used to confirm the independent prognostic value of KIF4A, and we constructed a nomogram based on KIF4A expression. Subsequently, we used ESTIMATE and ssGSEA algorithms to excavate the correlation between KIF4A, tumour-infiltrating immune cells, and related gene markers of immune cells. Moreover, the potential biological functions of KIF4A were investigated by gene function annotation. Finally, we identified the hub genes interacting with KIF4A by constructing a protein-protein interaction (PPI) network and screening differential genes (DEGs). Results. In the pan-cancer analysis, KIF4A was upregulated in most tumors (21/33). Similarly, the overexpression of KIF4A in EC patients was confirmed in the TCGA cohort, the GEO cohort, and immunohistochemistry. In addition, upregulated KIF4A is associated with age, survival status, grade, FIGO stage, histological type, tumour invasion, and TCGA molecular subtypes ( p < 0.05 ). KIF4A overexpression was correlated with the grade, histological type, and pathological stage according to logistic regression analysis ( p < 0.05 ). Meanwhile, survival analysis and meta-analysis revealed that KIF4A was associated with a poor prognosis and acted as an independent prognostic marker in EC patients ( p < 0.05 ). KIF4A is associated to immune response and may have a function in controlling immune cell infiltration in EC (20/24, p < 0.05 ). This is noteworthy given that gene enrichment analysis suggested KIF4A may be involved in the neuroactive ligand-receptor interaction pathway, etc. Finally, we identified transcription factors which have a potential interaction with KIF4A. Conclusion. We provided robust evidences that KIF4A is an indicator of poor prognosis and a potential target for immunotherapy in patients with EC.

Independent predictive value of blood inflammatory composite markers in ovarian cancer: recent clinical evidence and perspective focusing on NLR and PLR

AbstractOvarian cancer (OC) is one of the deadliest malignant tumors affecting women worldwide. The predictive value of some blood inflammatory composite markers in OC has been extensively reported. They can be used for early detection and differential diagnosis of OC and can be used for predicting survival, treatment response, and recurrence in the affected patients. Here, we reviewed the predictive values of composite inflammatory markers based on complete blood count, namely neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio, and systemic inflammation index and markers based on blood protein, namely C-reactive protein-to-albumin ratio and prognostic nutritional index in OC, with a focus on NLR and PLR. We referred to the clinical studies on these six markers, reviewed the patient population, and summarized the marker cut-off values, significance, and limitations of these studies. All these studies were retrospective and most of them were single-center clinical studies with small sample sizes. We found that the cut-off values of these markers have not been unified, and methods used to determine these values varied among studies. The predictive value of these markers on survival was mainly reflected in the postoperative patients of multiple subtypes of ovarian cancer including epithelial OC, high-grade serous ovarian carcinoma, and ovarian clear cell carcinoma. We focused on NLR and PLR and calculated their pooled hazard ratios. NLR and PLR were reliable in predicting overall and progression-free survivals in patients with OC. Therefore, it is necessary to adjust important confounding factors and conduct a long-term follow-up prospective cohort study to further clarify the cut-off values of NLR and PLR and their clinical applications.

Preoperative low hematocrit is an adverse prognostic biomarker in ovarian cancer

The study aimed to investigate the prognostic value of preoperative hematocrit (HCT) on the survival of epithelial ovarian cancer (EOC) patients. Patients who underwent primary debulking surgery (PDS) in our institution, from January 2010 to December 2015, were enrolled. The preoperative HCT, hemoglobin (Hb), tumor stage, ascites volume, age, albumin, BMI, ASA score, diabetes and other factors were collected and analyzed to find the risk factors for poor prognosis of EOC patients using Cox regression. Survival analysis was conducted with Kaplan-Meier method and log-rank test. 192 patients met the inclusion criteria. HCT < 35% (P = 0.031, HR: 1.715, 95% CI 1.050-2.802) was an independent risk factor for poor overall survival in patients. The mean survival time was 83.7 months in patients with preoperative HCT ≥ 35% and 61.7 months in patients with HCT < 35% (P = 0.002). Patients with low HCT (< 35%) had a poor prognosis compared with patients with normal HCT, specifically in the patients of stage III/IV, age ≥ 65 years, BMI ≥ 25.0 kg/m Preoperative low HCT was a valuable predictor for EOC patients' poor prognosis, specifically in obese, nondiabetic, elder, advanced stage but having relatively good performance status patients.

Near‐infrared dye‐labeled antibody COC183B2 enables detection of tiny metastatic ovarian cancer and optimizes fluorescence‐guided surgery

AbstractObjectiveWe aimed to evaluate the ability of the fluorescent monoclonal antibody probe COC183B2‐Cy7 (Cy7‐conjugated COC183B2 antibody) to detect tiny metastatic lesions of ovarian cancer and thus guide precise tumor resection.MethodsThe expression of the tumor‐associated antigen OC183B2 in lymph nodes and SKOV3‐Luc cells was detected using immunohistochemistry and immunofluorescence. A subcutaneous mouse tumor model and an intraperitoneal ovarian cancer metastasis model were constructed using SKOV3‐Luc cells. Near‐infrared fluorescence (NIRF) imaging was performed to determine the imaging parameters and evaluate the ability of COC183B2‐Cy7 to detect tiny metastatic lesions.ResultsOC183B2 was expressed in metastatic lymph nodes and SKOV3‐Luc cells. NIRF imaging of the subcutaneous mouse tumor model showed that the tumor background ratio was significantly higher in the COC183B2‐Cy7 group than in the control group at different time points postinjection. Biodistribution study showed that COC183B2‐Cy7 did not accumulate in other organs. COC183B2‐Cy7 can detect tiny metastatic lesions of ovarian cancer. The smallest intraperitoneal metastatic tumor detected by COC183B2‐Cy7 was approximately 1 mm.ConclusionsCOC183B2‐Cy7 probe has relatively high specificity and sensitivity. Our study suggests that COC183B2‐Cy7 probe is a promising diagnostic tool for the complete and accurate resection of malignant lesions in fluorescence‐guided surgery.

Prognostic value of site-specific metastasis and the treatment effect of surgery for FIGO stage IVB ovarian cancer: A population-based study

Single-Cell Dissection of the Multiomic Landscape of High-Grade Serous Ovarian Cancer

Abstract High-grade serous cancer (HGSC) is the most common subtype of ovarian cancer. HGSC is highly aggressive with poor patient outcomes, and a deeper understanding of HGSC tumorigenesis could help guide future treatment development. To systematically characterize the underlying pathologic mechanisms and intratumoral heterogeneity in human HGSC, we used an optimized single-cell multiomics sequencing technology to simultaneously analyze somatic copy-number alterations (SCNA), DNA methylation, chromatin accessibility, and transcriptome in individual cancer cells. Genes associated with interferon signaling, metallothioneins, and metabolism were commonly upregulated in ovarian cancer cells. Integrated multiomics analyses revealed that upregulation of interferon signaling and metallothioneins was influenced by both demethylation of their promoters and hypomethylation of satellites and LINE1, and potential key transcription factors regulating glycolysis using chromatin accessibility data were uncovered. In addition, gene expression and DNA methylation displayed similar patterns in matched primary and abdominal metastatic tumor cells of the same genetic lineage, suggesting that metastatic cells potentially preexist in the subclones of primary tumors. Finally, the lineages of cancer cells with higher residual DNA methylation levels and upregulated expression of CCN1 and HSP90AA1 presented greater metastatic potential. This study characterizes the critical genetic, epigenetic, and transcriptomic features and their mutual regulatory relationships in ovarian cancer, providing valuable resources for identifying new molecular mechanisms and potential therapeutic targets for HGSC. Significance: Integrated analysis of multiomic changes and epigenetic regulation in high-grade serous ovarian cancer provides insights into the molecular characteristics of this disease, which could help improve diagnosis and treatment.