Prognosis Of Ovarian Cancer Research Articles

Identification and validation of immunity- and disulfidptosis-related genes signature for predicting prognosis in ovarian cancer

BackgroundOvarian cancer (OC) ranks as the fifth most prevalent neoplasm in women and exhibits an unfavorable prognosis. To improve the OC patient's prognosis, a pioneering risk signature was formulated by amalgamating disulfidptosis-related genes. MethodsA comparative analysis of OC tissues and normal tissues was carried out, and differentially expressed disulfidptosis-related genes (DRGs) were found using the criteria of |log2 (fold change) | > 0.585 and adjusted P-value <0.05. Subsequently, the TCGA training set was utilized to create a prognostic risk signature, which was validated by employing both the TCGA testing set and the GEO dataset. Moreover, the immune cell infiltration, mutational load, response to chemotherapy, and response to immunotherapy were analyzed. To further validate these findings, QRT-PCR analysis was conducted on ovarian tumor cell lines. ResultsA risk signature was created using fourteen differentially expressed genes (DEGs) associated with disulfidptosis, enabling the classification of ovarian cancer (OC) patients into high-risk group (HRG) and low-risk group (LRG). The HRG exhibited a lower overall survival (OS) compared to the LRG. In addition, the risk score remained an independent predictor even after incorporating clinical factors. Furthermore, the LRG displayed lower stromal, immune, and estimated scores compared to the HRG, suggesting a possible connection between the risk signature, immune cell infiltration, and mutational load. Finally, the QRT-PCR experiments revealed that eight genes were upregulated in the human OC cell line SKOV3 compared with the human normal OC line IOSE80, while six genes were down-regulated. ConclusionsA fourteen-biomarker signature composed of disulfidptosis-related genes could serve as a valuable risk stratification tool in OC, facilitating the identification of patients who may benefit from individualized treatment and follow-up management.

A phase I/II study of maplirpacept in combination with pegylated liposomal doxorubicin (PLD) in patients with platinum-resistant ovarian cancer (OC): Phase 1 results.

e17546 Background: CD47, an overexpressed factor correlated with poor clinical characteristics and prognosis in OC, is an innate immune checkpoint that binds signal regulatory protein alpha (SIRPα) and delivers a signal to suppress macrophage phagocytosis. Maplirpacept (PF-07901801) is a fusion protein consisting of the CD47-binding domain of human SIRPα linked to the Fc region of human IgG4, enhancing phagocytosis by blocking CD47. Blockade of CD47, both alone and combined with doxorubicin, has shown anti-tumor activity in vitro and in vivo in xenograft animal models. PLD 40mg/m2 conveyed poor efficacy (PFS 4 months; ORR 8%), as did bevacizumab + PLD (PFS 5 months; ORR 14%) (AURELIA), highlighting the need for new treatments for platinum-resistant OC. C4971002 [NCT05261490] is an open label, multicenter dose-escalation and expansion study evaluating the safety, preliminary anti-tumor activity, pharmacokinetics and -dynamics of maplirpacept in combination with PLD in patients with platinum-resistant recurrent OC. Methods: The study included adults with platinum-resistant recurrent epithelial OC (PD ≤6 months after platinum-based therapy or unable/unwilling to receive platinum-based therapy). PLD while platinum-resistant or directly prior to study was not permitted. Patients received maplirpacept (12mg/kg Dose Level [DL] 1; 24mg/kg DL2; 48mg/kg DL3) weekly in Cycle 1 and every 2 weeks in Cycle 2+, and PLD (40mg/m2) on Day 1 of each 4-week cycle. Assessments of adverse events (AEs) were based on CTCAE v5.0. Response assessments (RECIST v1.1) were performed every 8 weeks. Results of the Phase I portion, aiming to evaluate the DLTs, the MTD and the RP2D, are presented as of 18 December 2023, after all patients completed the 28-day DLT assessment period. Results: 10 patients were treated (DL1 n=3; DL2 n=3; DL3 n=4) with a median (min, max) age of 69 (53, 77) years, 80% ECOG 1, 60% serous adenocarcinoma. Median (min, max) treatment duration was 14 (8, 32) weeks. Most common adverse events are shown in the table. No DLTs occurred in the assessment period. 1 serious AE (gait disturbance &amp; muscle weakness) related to maplirpacept was reported (DL3). 2 deaths occurred &gt;120 days after 1st dose, both due to disease. 5 (50%) patients had a best response of stable disease, 2 of which were treated into at least Cycle 6. Conclusions: Despite immature anti-tumor activity, maplirpacept + PLD was tolerable at all dose levels, not reaching the MTD. The encouragingly tolerable dose of 48mg/kg thus represents the RP2D which could support further development for this population. Clinical trial information: NCT05261490 . [Table: see text]

CT-based radiomics predicts CD38 expression and indirectly reflects clinical prognosis in epithelial ovarian cancer

BackgroundCluster of differentiation 38 (CD38) has been found to be highly expressed in various solid tumours, and its expression level may be associated with patient prognosis and survival. This study aimed to evaluate the prognostic value of CD38 expression for patients with epithelial ovarian cancer (EOC) and construct two computed tomography (CT)-based radiomics models for predicting CD38 expression. MethodsA total of 333 cases of EOC were enrolled from The Cancer Genome Atlas (TCGA) database for CD38-related bioinformatics and survival analysis. A total of 56 intersection cases from TCGA and The Cancer Imaging Archive (TCIA) databases were selected for radiomics feature extraction and model construction. Logistic regression (LR) and support vector machine (SVM) models were constructed and internally validated using 5-fold cross-validation to assess the performance of the models for CD38 expression levels. ResultsHigh CD38 expression was an independent protective factor (HR = 0.540) for overall survival (OS) in EOC patients. Five radiomics features based on CT images were selected to build models for the prediction of CD38 expression. In the training and internal validation sets, for the receiver operating characteristic (ROC) curve, the LR model reached an area under the curve (AUC) of 0.739 and 0.732, while the SVM model achieved AUC values of 0.741 and 0.700, respectively. For the precision-recall (PR) curve, the LR and SVM models demonstrated an AUC of 0.760 and 0.721. The calibration curves and decision curve analysis (DCA) provided evidence supporting the fitness and net benefit of the models. ConclusionsHigh levels of CD38 expression can improve OS in EOC patients. CT-based radiomics models can be a new predictive tool for CD38 expression, offering possibilities for individualised survival assessment for patients with EOC.

A novel lactylation-related gene signature for effectively distinguishing and predicting the prognosis of ovarian cancer.

Lactylation has been found to regulate several types of biological processes in cancer. However, there is limited research on lactylation-related genes in predicting the prognosis of ovarian cancer (OC). This study aimed to explore the functional roles of lactylation-related genes in OC. Based on TCGA database, we obtained RNA sequencing data and clinical characteristics of patients with OC. Fourteen lactylation-related genes were screened for bioinformatic analysis in OC. Tumor classification of OC was constructed via a consistency cluster analysis. We examined the prognosis, immune-cell infiltration, and immunotherapy in relation to a lactylation-related model for OC. A total of 707 prognostic genes and 14 key lactylation-related genes (SNRPA1, MPHOSPH6, POLDIP3, RB1, AHNAK, MAGOHB, CALM1, EP300, HDAC1, HDAC2, HDAC3, SIRT1, SIRT2, and SIRT3) were identified in TCGA-OC patients. Based on 14 genes involved in lactylation, TCGA-OC patients were split into low-risk (G1) and high-risk (G2) groups. Downregulated differentially expressed genes (DEGs) in the low-risk G1 group were associated with thermogenesis, oxidative phosphorylation, neutrophil extracellular trap formation, and interleukin 17 (IL-17) signaling pathway, whereas upregulated DEGs were associated with proteoglycans in cancer, focal adhesion, Wnt signaling pathway, extracellular matrix (ECM)-receptor interaction, and the adherens junction. The immune activity of the low-risk G1 group was lower than that of the high-risk G2 group. Gemcitabine, bleomycin, and doxorubicin had lower half-maximal inhibitory concentration (IC50) values in the high-risk G2 patients with OC, while cisplatin and paclitaxel had higher IC50 values compared to the low-risk G1 patients. The prognosis of patients with OC was also predicted with the help of an eight-lactylation-related gene prognostic model, comprising SNRPA1, MPHOSPH6, POLDIP3, RB1, HDAC1, CALM1, HDAC2, and SIRT2. The lactylation-related genes are closely related to tumor classification and immunity in patients with OC. There was good prognostic predictive performance for OC based on a lactylation-related signature. Our findings may offer new insights into the diagnosis and treatment of OC.

Identification of the biological functions and chemo-therapeutic responses of ITGB superfamily in ovarian cancer

BackgroundPatients with ovarian cancer (OC) tend to face a poor prognosis due to a lack of typical symptoms and a high rate of recurrence and chemo-resistance. Therefore, identifying representative and reliable biomarkers for early diagnosis and prediction of chemo-therapeutic responses is vital for improving the prognosis of OC.MethodsExpression levels, IHC staining, and subcellular distribution of eight ITGBs were analyzed using The Cancer Genome Atlas (TCGA)-Ovarian Serous Cystadenocarcinoma (OV) database, GEO DataSets, and the HPA website. PrognoScan and Univariate Cox were used for prognostic analysis. TIDE database, TIMER database, and GSCA database were used to analyze the correlation between immune functions and ITGBs. Consensus clustering analysis was performed to subtype OC patients in the TCGA database. LASSO regression was used to construct the predictive model. The Cytoscape software was used for identifying hub genes. The ‘pRRophetic’ R package was applied to predict chemo-therapeutic responses of ITGBs.ResultsITGBs were upregulated in OC tissues except ITGB1 and ITGB3. High expression of ITGBs correlated with an unfavorable prognosis of OC except ITGB2. In OC, there was a strong correlation between immune responses and ITGB2, 6, and 7. In addition, the expression matrix of eight ITGBs divided the TCGA-OV database into two subgroups. Subgroup A showed upregulation of eight ITGBs. The predictive model distinguishes OC patients from favorable prognosis to poor prognosis. Chemo-therapeutic responses showed that ITGBs were able to predict responses of common chemo-therapeutic drugs for patients with OC.ConclusionsThis article provides evidence for predicting prognosis, immuno-, and chemo-therapeutic responses of ITGBs in OC and reveals related biological functions of ITGBs in OC.

Epigenetic editing of BRCA1 promoter increases cisplatin and olaparib sensitivity of ovarian cancer cells

ABSTRACT Drug resistance is the primary contributor to the high mortality rate of ovarian cancer (OC). The loss of BRCA1/2 function is linked to drug sensitivity in OC cells. The aim of this study is to enhance the drug sensitivity of OC cells by inducing BRCA1 dysfunction through promoter epigenetic editing. Epigenetic regulatory regions within the BRCA1 promoter, affecting gene expression, were initially discerned through analysis of clinical samples. Subsequently, we designed and rigorously validated epigenetic editing tools. Ultimately, we evaluated the cisplatin and olaparib sensitivity of the OC cells after editing. The BRCA1 promoter contains two CpG-rich regions, with methylation of the region covering the transcription start site (TSS) strongly correlating with transcription and influencing OC development, prognosis, and homologous recombination (HR) defects. Targeting this region in OC cells using our designed epigenetic editing tools led to substantial and persistent DNA methylation changes, accompanied by significant reductions in H3K27ac histone modifications. This resulted in a notable suppression of BRCA1 expression and a decrease in HR repair capacity. Consequently, edited OC cells exhibited heightened sensitivity to cisplatin and olaparib, leading to increased apoptosis rates. Epigenetic inactivation of the BRCA1 promoter can enhance cisplatin and olaparib sensitivity of OC cells through a reduction in HR repair capacity, indicating the potential utility of epigenetic editing technology in sensitization therapy for OC.

Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer

Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes—C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)—emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.

P27Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer.

The biological function of p27Kip1 largely depends on its subcellular localization and phosphorylation status. Different subcellular localizations and phosphorylation statuses of p27Kip1 may represent distinct clinical values, which are unclear in ovarian cancer. This study aimed to elucidate different subcellular localizations of p27Kip1 and pSer10p27 in predicting prognosis and chemotherapy response in ovarian cancer. Meta-analyses were executed to evaluate the association of p27Kip1 and phosphorylated p27Kip1 with the prognosis of ovarian cancer patients. The expression levels and patterns of p27Kip1 and pSer10p27 were evaluated by immunohistochemistry. The correlations between different p27Kip1 states, clinicopathological features, and prognosis were analyzed. p27Kip1 and pSer10p27 expression levels in cisplatin-sensitive and cisplatin-resistant ovarian cancer cell lines were detected using WB. KEGG analysis and WB were performed to evaluate the pathways in which p27Kip1 was involved. Meta-analyses showed that p27Kip1 was associated with significantly better overall survival (OS) in ovarian cancer (HR=2.14; 95% CI [1.71-2.68]) and pSer10p27 was associated with significantly poor OS in mixed solid tumors (HR=2.56; 95% CI [1.76-3.73]). In our cohort of ovarian cancer patients, low total p27Kip1 remained independent risk factors of OS (HR=2.097; 95% CI [1.121-3.922], P=0.021) and PFS (HR=2.483; 95% CI [1.364-4.518], P=0.003), while low cytoplasmic pSer10p27 had independent protective effects in terms of OS (HR=0.472; 95% CI [0.248-0.898], P=0.022) and PFS (HR=0.488; 95% CI [0.261-0.910], P=0.024). Patients with low total p27Kip1/pSer10p27 and low nuclear p27Kip1 had worse chemotherapy responses, while patients with low cytoplasmic pSer10p27 expression had better chemotherapy responses. The protein levels of p27Kip1 and pSer10p27 were significantly reduced in the cisplatin-resistant cell lines SKOV3-cDDP and A2780-cDDP, and the level of p27Kip1/pSer10p27 was subjective to Akt activation. The present study demonstrates that p27Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer.

Development of a Prognostic Risk Model Based on Oxidative StressRelated Genes for Platinum-Resistant Ovarian Cancer Patients.

Ovarian Cancer (OC) is a heterogeneous malignancy with poor outcomes. Oxidative stress plays a crucial role in developing drug resistance. However, the relationships between Oxidative Stress-related Genes (OSRGs) and the prognosis of platinum-resistant OC remain unclear. This study aimed to develop an OSRGs-based prognostic risk model for platinum-resistant OC patients. Gene Set Enrichment Analysis (GSEA) was performed to determine the expression difference of OSRGs between platinum-resistant and -sensitive OC patients. Cox regression analyses were used to identify the prognostic OSRGs and establish a risk score model. The model was validated by using an external dataset. Machine learning was used to determine the prognostic OSRGs associated with platinum resistance. Finally, the biological functions of selected OSRG were determined via in vitro cellular experiments. Three gene sets associated with oxidative stress-related pathways were enriched (p < 0.05), and 105 OSRGs were found to be differentially expressed between platinum-resistant and - sensitive OC (p < 0.05). Twenty prognosis-associated OSRGs were identified (HR: 0:562-5.437; 95% CI: 0.319-20.148; p < 0.005), and seven independent OSRGs were used to construct a prognostic risk score model, which accurately predicted the survival of OC patients (1-, 3-, and 5-year AUC=0.69, 0.75, and 0.67, respectively). The prognostic potential of this model was confirmed in the validation cohort. Machine learning showed five prognostic OSRGs (SPHK1, PXDNL, C1QA, WRN, and SETX) to be strongly correlated with platinum resistance in OC patients. Cellular experiments showed that WRN significantly promoted the malignancy and platinum resistance of OC cells. The OSRGs-based risk score model can efficiently predict the prognosis and platinum resistance of OC patients. This model may improve the risk stratification of OC patients in the clinic.

Association of low Angiomotin-p130 and high YAP1 nuclear expression with adverse prognosis in epithelial ovarian cancer.

The aim of our study was to examine the association of Angiomotin (Amot-p130) and Yes-associated protein 1 (YAP1) expressions and their prognostic significance in epithelial ovarian cancer (EOC). A total of 100 primary EOC samples were obtained for immunohistochemical analysis of Amot-p130 and YAP1 expressions. Correlation analysis was performed between Amot-p130 or YAP1 and clinical factors. The overall survival time was calculated. Low Amot-p130 and high YAP1 nuclear expression were identified in 34 and 56 of 100 EOC tissues, respectively. Both low Amot-p130 and high YAP1 nuclear expression were associated with advanced tumor stage, high-grade carcinoma, and non-response to chemotherapy (p<0.05). They were also associated with shorter overall survival time (p<0.05) by log-rank test. A marker of low Amot-p130 and high YAP1 expression was associated with high-grade ovarian carcinoma, late-stage disease, non-response to chemotherapy, and shorter overall survival time (p<0.05). Low Amot-p130 and high YAP1 nuclear expression can provide additional prognostic information for patients with EOC. A marker of low Amot-p130 and high YAP1 expression may be a potent predictor of poor prognosis in patients with epithelial ovarian cancer.

Heterogeneous treatment effect of dose-dense paclitaxel plus carboplatin therapy for advanced ovarian cancer.

A Japanese clinical trial (JGOG3016) showed that dose-dense weekly paclitaxel in combination with carboplatin extensively prolonged overall survival (OS) in patients with advanced ovarian cancer. However, in other clinical trials, dose-dense paclitaxel regimens were not superior to triweekly paclitaxel regimens. In this study, causal tree analysis was applied to explore subpopulations with different treatment effects of dose-dense paclitaxel in a data-driven approach. The 587 participants with stage II-IV ovarian cancer in the JGOG3016 trial were used for model development. The primary endpoint was treatment effect in terms of 3-year OS in patients receiving dose-dense vs. conventional paclitaxel therapies. In patients <50 years, the 3-year OS was similar in both groups; however, it was higher in the dose-dense group in patients ≥50 years. Dose-dense paclitaxel showed strong positive treatment effects in patients ≥50 years with stage II/III disease, BMI <23 kg/m2, non-CC/MC, and residual tumor ≥1 cm. In contrast, although there was no significant difference in OS; the 3-year OS rate was 23% lower in dose-dense paclitaxel than conventional paclitaxel in patients ≥60 years with stage IV cancer. Patients in this group had a particularly lower performance status than other groups. Our causal tree analysis suggested that poor prognosis groups represented by residual tumor tissue ≥1 cm benefit from dose-dense paclitaxel, whereas elderly patients with advanced disease and low-performance status are negatively impacted by dose-dense paclitaxel. These subpopulations will be of interest to future validation studies. Personalized treatments based on clinical features are expected to improve advanced ovarian cancer prognosis.

Prognostic factors and the role of primary debulking in operable stage IVB ovarian cancer with supraclavicular lymph node metastasis: a retrospective study in Chinese patients

BackgroundRecent studies showed heterogeneity in stage IVB patients. However, few studies focused on the prognosis of supraclavicular metastatic ovarian cancer. This study aimed to explore the prognostic factors and the role of primary debulking in IVB ovarian cancer patients with supraclavicular lymph node metastasis.MethodsWe retrospectively analyzed patients newly diagnosed as primary epithelial ovarian cancer with supraclavicular lymph node metastasis from January 2015 to July 2020. Supraclavicular lymph node metastasis was defined as either the pathological diagnosis by supraclavicular lymph node biopsy, or the radiological diagnosis by positron emission tomography-computed tomography (PET-CT).ResultsIn 51 patients, 37 was diagnosed with metastatic supraclavicular lymph nodes by histology, 46 by PET-CT, and 32 by both methods. Forty-four (86.3%) with simultaneous metastatic paraaortic lymph nodes (PALNs) by imaging before surgery or neoadjuvant chemotherapy were defined as “continuous-metastasis type”, while the other 7 (13.7%) defined as “skip-metastasis type”. Nineteen patients were confirmed with metastatic PALNs by histology. Thirty-four patients were investigated for BRCA mutation, 17 had germline or somatic BRCA1/2 mutations (g/sBRCAm). With a median follow-up of 30.0 months (6.3–63.4 m), 16 patients (31.4%) died. The median PFS and OS of the cohort were 17.3 and 48.9 months. Survival analysis showed that “continuous-metastasis type” had longer OS and PFS than “skip-metastasis type” (OS: 50.0/26.6 months, PFS: 18.5/7.2months, p=0.005/0.002). BRCA mutation carriers also had longer OS and PFS than noncarriers (OS: 57.4 /38.5 m, p=0.031; PFS: 23.6/15.2m, p=0.005). Multivariate analysis revealed only metastatic PALNs was independent prognostic factor for OS (p=0.040). Among “continuous-metastasis type” patients, 22 (50.0%) achieved R0 abdominopelvic debulking, who had significantly longer OS (55.3/42.3 months, p =0.034) than those with residual abdominopelvic tumors.ConclusionsIn stage IVB ovarian cancer patients with supraclavicular lymph nodes metastasis, those defined as “continuous-metastasis type” with positive PALNs had better prognosis. For them, optimal abdominopelvic debulking had prognostic benefit, although metastatic supraclavicular lymph nodes were not resected. Higher BRCA mutation rate than the general population of ovarian cancer patients was observed in patients with IVB supraclavicular lymph node metastasis, leading to better survival as expected.

A cuproptosis-related signature predicts prognosis and indicates cross-talk with immunocyte in ovarian cancer

PurposeCuproptosis, programmed cell death by intracellular copper-mediated lipoylated protein aggregation, is involved in various tumorigenesis and drug resistance abilities by mediating the tumor microenvironment. Previous studies have demonstrated that serum copper levels are higher in OC patients than in normal subjects. However, the exact relationship between cuproptosis and ovarian cancer progression remains to be further elucidated.MethodsThe Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) datasets were utilized to establish a cuproptosis-related prognostic signature in ovarian cancer. Subsequently, the bulk RNA-seq analysis and single-cell RNA-seq analysis were used to identify the relationship between signature with immune cell infiltration, chemotherapy, and cuproptosis-related scoring (CuRS) system. Finally, the potential biological functional roles of target genes in cuproptosis were validated in vitro.ResultsBy using LASSO-Cox regression analysis to establish the cuproptosis-related prognostic model, our works demonstrated the accuracy and efficiency of our model in the TCGA (583 OC patients) and GEO (260 OC patients) OC cohorts, and the high-scoring groups showed worse survival outcomes. Notably, there were substantial differences between the high and low-risk groups in extensive respects, such as the activating transcription factors, cell pseudotime features, cell intercommunication patterns, immunocytes infiltration, chemotherapy response, and potential drug resistance. KIF26B was selected to construct a prognostic model from the identified 33 prognosis-related genes, and high expression of KIF26B predicted poorer prognosis in ovarian cancer. Ultimately, further in vitro experiments demonstrated that KIF26B participated in the proliferation and cisplatin resistance of OC cells. Knockdown of KIF26B increased the sensitivity of OC cells to elesclomol, a cuproptosis agonists.ConclusionThis study constructed a new cuproptosis-related gene signature that has a good prognostic capacity in assessing the outcome of OC patients. This study enhances our understanding of cuproptosis associated with ovarian cancer aggressiveness, cross-talk with immunocytes, and serves as a novel chemotherapy strategy.

Identification of PDZD11 as a Potential Biomarker Associated with Immune Infiltration for Diagnosis and Prognosis in Epithelial Ovarian Cancer.

Evidence has indicated that PDZD11 is involved in regulating adherens junction. However, the distinct effect of its aberrant expression on epithelial ovarian cancer (EOC) awaits clarification. In this study, public databases (Gene Expression Omnibus, The Cancer Genome Atlas, and The Genotype-Tissue Expression), online analysis tools (Kaplan-Meier plotter and TIMER), and data analysis methods (Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and the CIBERSORT algorithm) were fully utilized to analyze the differential expression, diagnostic efficiency, prognostic significance, potential function, and correlation with immune infiltration of PDZD11. The differential expression of PDZD11 was tested by immunohistochemistry in EOC tissues (78 cases) and control tissues (37 cases). Our results indicate that PDZD11 was remarkably overexpressed in EOC, which was associated with advanced cancer stages, no lymphatic metastasis status, and poor prognosis. Moreover, PDZD11 played a role in cell adhesion, cell proliferation, and immune responses. Also, PDZD11 was significantly related to the abundances of infiltrating immune cells in EOC, including neutrophils, macrophages, dendritic cells, CD8+ T cells, and CD4+ T cells, and its expression was positively co-expressed with well-known immune checkpoints, including TIGIT, TIM3, LAG3, CTLA4, and PD-1. These results suggest that PDZD11 could be a potential diagnostic and prognostic biomarker associated with immune infiltration in EOC, and our findings might help elucidate the function of PDZD11 in carcinogenesis.

Identification of MAD2L1 and BUB1B as Potential Biomarkers Associated with Progression and Prognosis of Ovarian Cancer.

Ovarian cancer develops insidiously and is frequently diagnosed at advanced stages. Screening for ovarian cancer is an effective strategy for reducing mortality. This study aimed to investigate the molecular mechanisms underlying the development of ovarian cancer and identify novel tumor biomarkers for the diagnosis and prognosis of ovarian cancer. Three databases containing gene expression profiles specific to serous ovarian cancer (GSE18520, GSE12470, and GSE26712) were acquired. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were analyzed for the differentially expressed gene (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING database. The pivotal genes in the PPI network were screened using the Cytoscape software. Survival curve analysis was performed using a Kaplan-Meier Plotter. The cancer genome atlas and Gene Expression Omnibus databases were used to find the relationship between Hub gene and serous ovarian cancer. PCR and immunohistochemistry were used to detect the expression of Hub gene in serous ovarian cancer tissues and cells. Downstream pathways of the candidate tumor marker genes were predicted using Gene Set Enrichment Analysis. In this study, 252 DEGs were screened for pathway enrichment. 20 Hub genes were identified. Survival analysis suggested that Aurka, Bub1b, Cenpf, Cks1b, Kif20a, Mad2l1, Racgap1, and Ube2c were associated with the survival of patients with serous ovarian cancer. MAD2L1 and BUB1B levels were significantly different in serous ovarian cancer at different stages. Finally, Mad2l1 was found to play a role in the cell cycle, oocyte meiosis, and ubiquitin-mediated proteolysis. Meanwhile, Bub1b may play a role in the cell cycle, ubiquitin-mediated proteolysis, and spliceosome processes. Mad2l1 and Bub1b could be used as markers to predict ovarian carcinogenesis and prognosis, providing candidate targets for the diagnosis and treatment of serous ovarian cancer.

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer.

This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis. SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses. Our analysis revealed that 48 DEPCDGs are significantly correlated with apoptotic signaling and oxidative stress pathways and identified seven key DEPCDGs (CASP3, GADD45B, GNA15, GZMB, IL1B, ISG20, and RHOB) through survival analysis. Furthermore, eight distinct cell subtypes were characterized using scRNA-seq. It was found that G protein subunit alpha 15 (GNA15) exhibited low expression across these subtypes and a strong association with immune cells. Based on the DEGs identified by the GNA15 high- and low-expression groups, a prognostic model comprising eight genes with significant prognostic value was constructed, effectively predicting patient overall survival. Additionally, a nomogram incorporating the RS signature, age, grade, and stage was developed and validated using two large SOC datasets. GNA15 emerged as an independent and excellent prognostic marker for SOC patients. This study provides valuable insights into the prognostic potential of DEPCDGs in SOC, presenting new avenues for personalized treatment strategies.

Research progress in endometriosis-associated ovarian cancer.

Endometriosis-associated ovarian cancer (EAOC) is a unique subtype of ovarian malignant tumor originating from endometriosis (EMS) malignant transformation, which has gradually become one of the hot topics in clinical and basic research in recent years. According to clinicopathological and epidemiological findings, precancerous lesions of ovarian clear cell carcinoma (OCCC) and ovarian endometrioid carcinoma (OEC) are considered as EMS. Given the large number of patients with endometriosis and its long time window for malignant transformation, sufficient attention should be paid to EAOC. At present, the pathogenesis of EAOC has not been clarified, no reliable biomarkers have been found in the diagnosis, and there is still a lack of basis and targets for stratified management and precise treatment in the treatment. At the same time, due to the long medical history of patients, the fast growth rate of cancer cells, and the possibility of eliminating the earliest endometriosis-associated ovarian cancer, it is difficult to find the corresponding histological evidence. As a result, few patients are finally diagnosed with EAOC, which increases the difficulty of in-depth study of EAOC. This article reviews the epidemiology, pathogenesis, risk factors, clinical diagnosis, new treatment strategies and prognosis of endometriosis-associated ovarian cancer, and prospects the future direction of basic research and clinical transformation, in order to achieve stratified management and personalized treatment of ovarian cancer patients.

TCEB3 initiates ovarian cancer apoptosis by mediating ubiquitination and degradation of MCL-1.

Platinum resistance remains a major contributor to the poor prognosis of ovarian cancer. Anti-apoptotic protein myeloid cell leukemia-1 (MCL-1) has emerged as a promising target for overcoming drug resistance, but different cancer cells utilize distinct protein degradation pathways to alter MCL-1 level. We systematically investigated E3 ligases to identify novel candidates that mediate platinum resistance in ovarian cancer. Transcription Elongation Factor B (TCEB3) has been identified as a novel E3 ligase recognition subunit that targets MCL-1 in the cytoplasm during platinum treatment other than its traditional function of targeting the Pol II in the nuclear compartment. TCEB3 expression is downregulated in platinum-resistant cell lines and this low expression is associated with poor prognosis. The ubiquitination of MCL-1 induced by TCEB3 leads to cell death in ovarian cancer. Moreover, platinum treatment increased the cytoplasm proportion of TCEB3, and the cytoplasm localization of TCEB3 is important for its targeting of MCL-1. This study emphasizes the dual function of TCEB3 in homeostasis maintenance and in cell fate determination under different conditions, and provides a new insight into drug resistance in ovarian cancer.

Alteration of glucose metabolism and expression of glucose transporters in ovarian cancer.

Aerobic glycolysis also known as the Warburg effect, remains a hallmark of various cancers, including ovarian cancer. Cancer cells undergo metabolic changes to sustain their tumorigenic properties and adapt to environmental conditions, such as hypoxia and nutrient starvation. Altered metabolic pathways not only facilitate ovarian cancer cells' survival and proliferation but also endow them to metastasize, develop resistance to chemotherapy, maintain cancer stem cell phenotype, and escape anti-tumor immune responses. Glucose transporters (GLUTs), which play a pivotal role as the rate-limiting step in glycolysis, are frequently overexpressed in a variety of tumors, including ovarian cancer. Multiple oncoproteins can regulate GLUT proteins, promoting tumor proliferation, migration, and metastasis, either dependent or independent of glycolysis. This review examines the alteration of GLUT proteins, particularly GLUT1, in ovarian cancer and its impact on cancer initiation, progression, and resistance to treatment. Additionally, it highlights the role of these proteins as biomarkers for diagnosis and prognosis in ovarian cancer, and delves into novel therapeutic strategies currently under development that target GLUT isoforms.

Profiling of Tumour-Infiltrating Lymphocytes and Tumour-Associated Macrophages in Ovarian Epithelial Cancer-Relation to Tumour Characteristics and Impact on Prognosis.

Early evidence suggests a strong impact of tumour-infiltrating lymphocytes (TILs) on both the prognosis and clinical behaviour of ovarian cancer. Proven associations, however, have not yet translated to successful immunotherapies and further work in the field is urgently needed. We aimed to analyse the tumour microenvironment of a well-characterised cohort of ovarian cancer samples. Tumour markers were selected owing to their comparative underrepresentation in the current literature. Paraffin-embedded, formalin-fixed tumour tissue blocks of 138 patients representative of the population and including early stage disease were identified, stained for CD3, CD20, CD68 and CD163 and analysed for both the stromal and intertumoral components. Data were statistically analysed in relation to clinical details, histological subtype, borderline vs. malignant status, survival and management received. Mean stromal CD3, total CD3 count, mean stromal CD20 and total CD20 count all correlated negatively with survival. Malignant ovarian tumours consistently demonstrated significantly higher infiltration of all analysed immune cells than borderline tumours. Assessment of the stromal compartment produced a considerably higher proportion of significant results when compared to the intra-tumoural infiltrates. Customary assessment of solely intra-tumoural cells in advanced stage disease patients undergoing primary debulking surgery should be challenged, with recommendations for future scoring systems provided.