Prognostic Factor In Ovarian Cancer Research Articles

Association of Chemotherapy Response Score with Multidrug Resistance 1 and CA125 ELIMination Rate Constant K in Patients with Advanced Ovarian Cancer Treated with Neoadjuvant Chemotherapy.

The relationship between chemotherapy response score (CRS), a widely used response predictor of neoadjuvant chemotherapy-interval debulking surgery (NAC-IDS), and multidrug resistance 1 (MDR1) and CA125 ELIMination rate constant K (KELIM), is undetermined. We evaluated CRS in advanced ovarian cancer patients undergoing NAC and looked for associations between CRS and MDR1 and CA125 KELIM. Our aim was to predict the therapeutic effect of NAC before interval debulking surgery (IDS) by examining its association with CRS. This retrospective cohort study included patients who underwent NAC-IDS (first-line treatment) at Kurume University Hospital, Japan, between 2004 and 2017. CRS association with MDR1 and CA125 KELIM was examined using Cox proportional hazard regression analyses. Survival curves used Kaplan-Meier method, and survival differences between groups used log-rank test. Overall, 55 patients were classified into CRS1 (n=22), CRS2 (n=19), and CRS3 (n=14). The CRS3 group had a significantly better prognosis than the CRS1 or CRS2 group. CRS, age, and IDS status were clinical prognostic factors for ovarian cancer. MDR1 positivity for excision repair cross-complementing group 1, β-tubulin, and Y-box binding protein-1 occurred in 15, 17, and 11 patients, respectively, but these were not associated with CRS. CA125 KELIM was <0.5 (n=8), 0.5-1.0 (n=30), and ≥ 1.0 (n=17) but not associated with CRS. CRS is reconfirmed as a treatment response predictor for NAC-IDS, but its association with drug resistance factors remains unconfirmed.

Serum high-density lipoprotein level and prognosis of ovarian cancer.

This study aimed to investigate the prognostic value of serum high-density lipoprotein (HDL) level in patients with ovarian cancer. This study enrolled 152 patients diagnosed with ovarian cancer and 119 patients with benign ovarian tumors. The associations of patient characteristics and disease with survival were determined using Cox regression analysis, t tests, analysis of variance for multiple-group comparisons, and chi-square tests. The potential association between HDL levels and the clinical characteristics of the disease was also analyzed. The diagnostic value of HDL was estimated using receiver operating characteristic curve analysis and calculation of the area under the curve. Progression-free survival and overall survival were determined using the Kaplan-Meier method, and their associations with patient and pathological variables, including HDL, were determined using the log-rank test. The median serum HDL was 1.15 mm measured in 152 patients with ovarian cancer and 1.30 mm in 119 patients with benign ovarian tumors (P = .000054). The receiver operating characteristic curve analysis yielded an area under the curve of 0.735 for serum HDL levels. Serum HDL levels were significantly associated with tumor pathological types (non-serous vs serous, P < .05). No association was observed between serum HDL levels and patient age, age at menarche or marriage, number of children, tumor grade, or clinical stage (P > .05). Patients with high serum HDL levels had a longer progression-free survival and overall survival than those with low serum HDL levels. Serum HDL levels are an independent prognostic factor for ovarian cancer.

Minimally Invasive Staging of Early-Stage Epithelial Ovarian Cancer versus Open Surgery in Terms of Feasibility and Safety: A Systematic Review and Meta-Analysis.

Epithelial ovarian cancer is women's fourth most common oncological cause of death. One of the main prognostic factors in ovarian cancer is the tumor stage. For instance, surgical staging of the disease is focal when choosing the best therapeutic option for each case. Although open surgery is the prevalent approach for staging and treating ovarian cancer, the use of minimally invasive surgery (MIS) has found recent application in staging or restaging cases of early disease. Our work compares oncological outcomes after MIS staging for FIGO I epithelial ovarian cancer with the laparotomic approach. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement recommendations, we systematically searched the Pub Med and Scopus databases in February 2023. No temporal nor geographical limitation was made. We included the articles containing data about Disease-Free Survival (DFS) and Overall Survival (OS), Recurrence Rates (RR), and Upstaging Rates (UpR). We used comparative studies for the meta-analysis. After the database search and article selection, 19 works matched the inclusion criteria for the systematic review. Eleven of these were comparative studies between MIS and Open Surgical Staging (OSS) approaches for ovarian cancer staging and were included in the meta-analysis. The meta-analysis did not show a statistically significant difference between the MIS and the OSS group concerning DFS, OS, and RR. Only Upstaging Rate ≥ FIGO Stage II was statistically significative higher in the OSS group. Likewise, MIS is confirmed to be an approach with a lower profile of surgical complications. In conclusion, our study did not show one approach to be safer than the other. However, the lack of dedicated studies limits the evidence of our study. For instance, we recommend adequately selecting the specimen, minimizing the risk of spillage, and optimizing surgical staging.

PM2.5 exposure and its interaction of oxidative balance score on ovarian cancer survival: A prospective cohort study

Recent evidence advises particles with a diameter of 2.5 µm or less (PM2.5) might be a prognostic factor for ovarian cancer (OC) survival. The oxidative balance score (OBS) incorporates diet-lifestyle factors to estimate individuals’ anti-oxidant exposure status which may be relevant to cancer prognosis. We aimed to investigate the roles of PM2.5, and OBS and their interaction in OC prognosis. 663 patients with OC were enrolled in the current study. Satellite-derived annual average exposures to PM2.5 based on patients’ residential locations. The OBS was calculated based on 16 different diet-lifestyle components derived using an acknowledged self-reported questionnaire. The Cox regression model was performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival (OS). We also assessed the effect of modification between PM2.5 and OS by OBS via interaction terms. During a median follow-up of 37.57 (interquartile:35.27–40.17) months, 123 patients died. Compared to low-concentration PM2.5 exposure, high PM2.5 during 1 year before diagnosis was associated with worse OC survival (HR= 1.19, 95% CI = 1.01–1.42). We observed an improved OS with the highest compared with the lowest OBS (HR = 0.46, 95% CI = 0.27–0.79, P for trend < 0.05). Notably, we also found an additive interaction between low OBS and high exposure to PM2.5, with the corresponding associations of PM2.5 being more pronounced among participants with lower OBS (HR = 1.42, 95% CI = 1.09–1.86). PM2.5 may blunt OC survival, but high OBS represented an antioxidative performance that could alleviate the adverse association of PM2.5 and OS.

49P First report on pan-immune-inflammation value as a new prognostic factor in ovarian cancer: A biomarker analysis of OVANORDEST-1 study

Inflammation is a hallmark of cancer. In our recent Umbrella systematic review of systematic reviews, we demonstrated that inflammatory biomarkers based on peripheral blood count impact both progression-free survival and overall survival (OS) in ovarian cancer. Pan-Immune-Inflammation Value (PIIV) is a new prognostic factor that was studied in breast cancer and other malignancies, but never in ovarian cancer. In this study, we provide the first results of the prognostic value of PIIV in a Moroccan cohort of ovarian cancer patients based on a biomarker-analysis of OVANORDEST-1 study. An exploratory biomarker set from our OVANORDEST-1 database was included in the final analysis with OS as a primary endpoint. PIIV was calculated as previously described: (neutrophil count × platelet count × monocyte count)/lymphocyte count. Receiver operating characteristic (ROC) was used to evaluate the optimal cut-off of PIIV. Cox proportional hazard model was used for multivariable analysis and Kaplan-Meier method to estimate OS. A total number of 158 patients treated for epithelial ovarian cancer with a median age of 55 years were included in the survival analysis. A ROC-based cut off of 991.7 of PIIV was used for patients’ stratification. Survival analysis using Log rank test showed a significant association of PIIV with OS (p<0.0001). Women with high PIIV had the worst outcomes as compared to those with low PIIV (median OS: 16 months versus 35.4 months, respectively). On Cox proportional hazard model, PIIV was an independent predictor of OS (HR=2.38, CI:1.47-3.85; p<0.0001). High PIIV is associated with an increased risk of death in women with epithelial ovarian cancer. A validation set of this study is ongoing and a prospective enrollment to develop a nomogram based on PIIV is being planned.

Actin-like Protein 6A Expression Correlates with Cancer Stem Cell-like Features and Poor Prognosis in Ovarian Cancer.

Ovarian cancer has the highest mortality rate among gynecological cancers, often diagnosed at the late stage and lacking an effective targeted therapy. Although the study of malignant features of cancer, considered to be cancer stem cells (CSCs), is emerging, the aim of this study was to predict and explore the possible mechanism and clinical value of genetic markers in the development of ovarian cancer from a combined database with CSCs features. The common differentially expressed genes (DEGs) were selected in GSE185833 and GSE176246 datasets from the Gene Expression Omnibus (GEO). The GSE185833 dataset was created to reveal gene expression profiles of peritoneal metastasis tissues using single-cell sequencing, and the GSE176246 dataset was determined from gene expression profiles of chemotherapy-refractory ovarian cancer cell lines compared with ovarian cancer cell lines by RNA-seq analysis. By analyzing the correlation between common DEGs and prognosis of ovarian cancer and its possible pathways and functions were predicted by The Cancer Genome Atlas (TCGA) database. The expression levels of 11 genetic markers were significantly elevated in highly invasive and chemoresistant ovarian cancer. The expression of Actin-like protein 6A (ACTL6A) was found to be correlated with survival prognosis, and the total survival time of the patients with high expression of ACTL6A was shorter than those with low expression. Gene set enrichment analysis (GSEA) showed that ACTL6A positively enriched the gene set of 'Cell cycle' and ACTL6A negatively enriched the gene set of focal adhesion. CP724714, a human epidermal growth factor receptor 2 (HER2) inhibitor, could serve as a therapeutic option when ACTL6A levels are high in ovarian cancer cells. The high expression of ACTL6A is a poor prognostic factor in ovarian cancer and may serve as an effective biomarker for predicting treatment-refractory, metastasis, and prognosis of patients with ovarian cancer. The use of HER2 inhibitors is a promising therapeutic strategy against chemoresistant ovarian cancer.

Establishment, immunological analysis, and drug prediction of a prognostic signature of ovarian cancer related to histone acetylation.

In recent years, epigenetic modifications have been increasingly regarded as an important hallmark of cancer. Histone acetylation, as an important part of epigenetic modification, plays a key role in the progress, treatment, and prognosis of many cancers. In this study, based on the TCGA database, we performed LASSO regression and the Cox algorithm to establish a prognostic signature of ovarian cancer associated with histone acetylation modulator genes and verified it externally in the GEO database. Subsequently, we performed an immunological bioinformatics analysis of the model from multiple perspectives using the CIBERSORT algorithm, ESTIMATE algorithm, and TIDE algorithm to verify the accuracy of the model. Based on the prognostic model, we divided ovarian cancer patients into high-risk and low-risk groups, and assessed survival and the efficacy of accepting immunosuppressive therapy. In addition, based on the analysis of characteristics of the model, we also screened targeted drugs for high-risk patients and predicted potential drugs that inhibit platinum resistance through the connectivity map method. We ultimately constructed a histone acetylation modulator-related signature containing 10 histone acetylation modulators, among which HDAC1, HDAC10, and KAT7 can act as independent prognostic factors for ovarian cancer and are related to poor prognosis. In the analysis of the tumor microenvironment, the proportion of the B-infiltrating cells and the macrophages was significantly different between the high- and low-risk groups. Also, the samples with high-risk scores had higher tumor purity and lower immune scores. In terms of treatment, patients in the high-risk group who received immunotherapy had a higher likelihood of immune escape or rejection and were less likely to respond to platinum/paclitaxel therapy. Finally, we screened 20 potential drugs that could target the model for reference.

SNORA70E promotes the occurrence and development of ovarian cancer through pseudouridylation modification of RAP1B and alternative splicing of PARPBP

The present study demonstrated for the first time that SNORA70E, which belongs to box H/ACA small nucleolar noncoding RNAs (snoRNAs) who could bind and induce pseudouridylation of RNAs, was significantly elevated in ovarian cancer tissues and was an unfavourable prognostic factor of ovarian cancer. The over‐expression of SNORA70E showed increased cell proliferation, invasion and migration in vitro and induced tumour growth in vivo. Further research found that SNORA70E regulates RAS‐Related Protein 1B (RAP1B) mRNA through pseudouracil modification by combing with the pyrimidine synthase Dyskerin Pseudouridine Synthase 1 (DKC1) and increase RAP1B protein level. What's more, the silencing of DKC1/RAP1B in SNORA70E overexpression cells both inhibited cell proliferation, migration and invasion through reducing β‐catenin, PI3K, AKT1, mTOR, and MMP9 protein levels. Besides, RNA‐Seq results revealed that SNORA70E regulates the alternative splicing of PARP‐1 binding protein (PARPBP), leading to the 4th exon‐skipping in PARPBP‐88, forming a new transcript PARPBP‐15, which promoted cell invasion, migration and proliferation. Finally, ASO‐mediated silencing of SNORA70E could inhibit ovarian cancer cell proliferation, invasion, migration ability in vitro and inhibit tumorigenicity in vivo. In conclusion, SNORA70E promotes the occurrence and development of ovarian cancer through pseudouridylation modification of RAP1B and alternative splicing of PARPBP. Our results demonstrated that SNORA70E may be a new diagnostic and therapeutic target for ovarian cancer.

The Significance of Peritoneal Washing as a Prognostic Indicator for Ovarian Cancer Patients

Background/Aim: During ovarian cancer (OC) debulking surgery, the surgeon can examine the peritoneal cavity for malignant cancer cells with peritoneal washing (PW) cytology. The goal of this study was to examine the significance of peritoneal washing as a prognostic indicator for ovarian cancer patients. Patients and Methods: Information considering the prognostic factors of OC and their impact in PW’s result was collected, compared, and combined. Results: Omental metastasis, tumor type, tumor invasion, tumor size, tumor grade/ stage, tumor’s cytoreduction, and recurrence affect both the peritoneal washing result and the patient’s prognosis. The correlation that most of the above factors have with a positive PW and dismal prognosis, led us to the assumption that PW has a significance as a prognostic indicator. Conclusion: The significance of PW as a prognostic indicator remains an assumption.

Mast cells and M2 macrophages in ovarian cancer

The objectives of this study were to investigate the immunohistochemical expression of markers of mast cells and M2 macrophages in benign and malignant ovarian neoplasms and to examine the prognostic value of this expression in ovarian cancer. The study was performed with samples from 32 patients, divided into benign (n = 16) and malignant (n = 16) neoplasm groups. Samples obtained by surgical resection were submitted to immunohistochemical analysis. Higher proportions of M2 macrophages (p = .041) and mast cells (p = .0054) were present in malignant than benign ovarian neoplasms. Histological grade 2/3 was related to higher proportions of M2 macrophages compared with grade 1 (p = .0102). Stages II-IV were also related to higher proportions of M2 macrophages (p = .0102). Logistic regression revealed that M2 macrophages predicted malignancy [odds ratio (OR) = 1.017; 95% confidence interval (CI), 1.003–1.037; p = .017], but that mastocytes had greater predictive value for this outcome (OR = 1.127; 95% CI, 1.018–1.105; p = .013). M2 macrophages predicted more advanced histological grades (OR = 1.060; 95% CI, 1.010–1.218; p = .003). The proportions of M2 macrophages and mast cells were greater in malignant than in benign ovarian neoplasms. Larger proportions of cells expressing M2 macrophages were related to more advanced histological grades and disease stages, and thus to worse prognoses for ovarian cancer. Impact Statement What is already known on this subject? Concentrations of mast cells and M2 macrophages have been observed in several tumour types, but their significance remains uncertain. What do the results of this study add? The proportions of M2 macrophages and mast cells were greater in malignant than in benign ovarian neoplasms. Larger proportions of cells expressing M2 macrophages were related to higher histological grades and more advanced stages of the disease. What are the implications of these findings for clinical practice and/or further research? Larger proportions of cells expressing M2 macrophages were related to worse prognoses for malignant ovarian neoplasia. The discovery of new prognostic factors in ovarian cancer may be the target of studies on new treatments and immunotherapies for this disease. In addition, it can help guide the oncologist towards more aggressive treatments for patients with worse prognostic factors.

Identification Of key prognostic genes in ovarian cancer using WGCNA and LASSO analysis

Ovarian cancer (OC) is the fifth leading cause of death in females. This study aims to identify new prognostic genes of OC through bioinformatics analysis. Based on two datasets from the NCBI GEO public database, we constructed two WGCNA networks. We then selected and intersected two key modules and 177 key genes were identified. The GO, KEGG and PPI network were determined based on the screened genes. According to the LASSO analysis and KM plotter, three hub genes were associated with the overall survival. GEPIA and IHC staining showed that CCDC80 expression level was lower while FBXO16 expression level was higher in OC tissues than in normal ovarian tissues. The relationship between hub genes and clinical characteristics was evaluated and the prognostic significance was validated in 60 clinical patients with OC. CIBERSORT shows that both CCDC80 and FBXO16 were significantly correlated with the immune cell content. Drug sensitivity analysis shows that CCDC80 affected the IC50 value of Gefitinib, and FBXO16 affected the IC50 value of Cisplatin and Docetaxel. CCDC80 and FBXO16 were identified as two robust prognostic factors in OC that could be explored further with respect to the diagnosis and treatment of OC patients.

Association between miR-196a-2 Gene Polymorphism and Ovarian Cancer Prognosis in Egyptian Females.

Background:Ovarian cancer is the fifth leading cause of cancer-related deaths among women worldwide. Unfortunately, early detection tests are relatively lacking. Diagnosis in the late stages of the disease carries a poor prognosis. Objective:To evaluate the relationship between miR-196a-2 rs11614913 polymorphism and ovarian cancer risk and prognosis in Egyptian females. Methods: In this case-control study, the participants were classified into 2 groups. Group A is the control group which included 50 healthy females. Group B included 50 patients newly diagnosed with ovarian carcinoma confirmed by histopathological analysis. Immunohistochemistry for P53 and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) for miR-196a-2 genotypes detection were performed. Results:There was a statistically significant difference among ovarian cancer cases and controls regarding genotypes (P = 0.003). However, the distribution of the T and C alleles in both studied groups showed no significant difference (P = 0.17). There was a statistically significant increase of CA 125 levels among CT and CC genotypes carriers of ovarian cancer cases (p = 0.04). Besides, there was a statistically significant correlation between miR-196a-2 polymorphism and each of tumor grade (P <0.001), p53 immunohistochemical expression (P= 0.002), and Figo classification (P <0.001). Conclusion:There was a statistically significant increase of CA 125 levels among C allele carriers of ovarian cancer cases. Besides, there was a statistically significant association between the miR-196a-2 polymorphism and each of tumor grade, p53 immunohistochemical expression, and Figo classification. So, miR-196a-2 polymorphism can be a possible prognostic factor in ovarian cancer.

Women With Ovarian Cancer and With Fertility Preservation: A Survival Analysis Using the Surveillance, Epidemiology, and End Results Database and Construction of Nomograms to Predict Cancer-Specific Survival.

ObjectiveThis study aimed to determine the risk and prognostic factors of ovarian cancer (OC) in women having fertility-sparing surgery, as well as survival outcomes of those with stage I epithelial ovarian cancer (EOC). We also determined the effect of chemotherapy in OC treatment and used multiple independent risk factors to establish a prognostic nomogram model for patients with stage I EOC.Patients and MethodsIndividuals with OC and with fertility-sparing surgery (FSS) between 1998 and 2016 were identified in the SEER database. Univariate and multivariate logistic regression was performed to identify the distributions of patient characteristics according to chemotherapy. Cancer-specific survival (CSS) was assessed using Kaplan–Meier curves and log-rank tests. Univariate and multivariate Cox regression was conducted to determine the independent prognostic factors for CSS. Cox analysis was used to construct a nomogram model. The C-index and calibration plots showed the performance evaluation results.ResultsA total of 1,839 women with OC with FSS were identified in the SEER database. Factors associated with significantly higher odds of undergoing chemotherapy included younger age, being unmarried, having grades 2–4, stages II–III, or clear cell and non-epithelial histologic type following a multivariate logistic regression analysis. Multivariate Cox regression analysis confirmed that age, marital status, chemotherapy, histologic type, grade, and the International Federation of Gynecology and Obstetrics (FIGO) stage were independent prognostic factors for CSS. In stage I EOC, the prognosis in patients with stage IA/IB-grade 3 (5-year CSS 85.3%) or stage IC (5-year CSS 80.6%) was worse than that in those with stage IA/IB-grade 1 (5-year CSS 95.2%), or stage IA/IB-grade 2 (5-year CSS 94.7%). However, chemotherapy improved the survival of patients with stage IA/IB-grade 3 (5-year CSS 78.1% vs. 94.6%, p = 0.024) or stage IC (5-year CSS 75.1% vs. 86.7%, p = 0.170).DiscussionThe study provided population-based estimates of risk factors and prognoses in patients with OC and with FSS as well as the survival outcomes of patients with stage I EOC and the effect of chemotherapy. The constructed nomograms exhibited superior prognostic discrimination and survival prediction for patients with stage I EOC.

KDF1 Promoted Proliferation and Metastasis of Epithelial Ovarian Cancer via Wnt/Beta-Catenin Pathway: TCGA-Based Data Mining and Experimental Validation.

Objectives: It has been reported that keratinocyte differentiation factor 1 (KDF1) was related to proliferation, differentiation, and cell cycle. However, the role of KDF1 has not been reported in ovarian cancer. The present study investigated the function and the potential mechanism of KDF1 in ovarian cancer. Methods: We evaluated the prognostic value in ovarian cancer based on data from the Cancer Genome Atlas (TCGA) database. The Kruskal–Wallis test, Wilcoxon signed-rank test, and logistic regression were used to evaluate the relationship between KDF1 expression and clinicopathologic features. The Cox regression and the Kaplan–Meier method were adopted to evaluate prognosis-related factors. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) gene enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were performed to identify the key biological process related to KDF1. Then the expression of KDF1 in ovarian cancer tissues was validated by streptavidin–peroxidase (SP) immunohistochemistry. The proliferation and invasion ability of KDF1 were determined by EdU and Transwell assay, respectively, with KDF1 gene silencing and overexpression. The mRNA expression of KDF1 was determined by qPCR. The protein expression of KDF1 was determined using the Western blot. Methods: By performing differential expression analysis on the ovarian cancer data of the TCGA database, it was found that KDF1 is highly expressed in ovarian cancer patients and associated with poorer overall survival (OS) and progression-free survival (PFS) of ovarian cancer patients. The highly expressed KDF1 may reduce cell adhesion according to GO, KEGG, and GSEA results. After analysis combining the relevant clinical features, we found that the high expression of KDF1 is an independent prognostic factor of ovarian cancer and associated with platinum resistance and tumor metastasis in ovarian cancer. At the same time, the BioGRID database showed that there might be protein–protein interaction between KDF1 and E-cadherin. Then we further validated that the high expression of KDF1 had a close correlation with the stage and grade of ovarian cancer in ovarian cancer tissue chips. Silencing KDF1 inhibited the proliferation and invasion ability of SKOV3 cells. By contrast, ectopic expression of KDF1 promoted the proliferation and invasion ability of A2780 cells. We also found that KDF1 can interact with E-cadherin and regulate the expression of Wnt5A and β-catenin, hence activating Wnt/β-catenin pathway via in vitro and vivo experiments. Conclusions: Based on the bioinformatics analysis, in vitro experiments, and an in vivo study, it is indicated that KDF1 played an important role in ovarian cancer progression and might be a therapeutic target for patients with ovarian cancer.

Clinical Significance of BTLA, CD27, CD70, CD28 and CD80 as Diagnostic and Prognostic Markers in Ovarian Cancer.

It is very important to find new diagnostic and prognostic biomarkers. A total of 79 patients were enrolled in the study. The study group consisted of 37 patients with epithelial ovarian cancer, and the control group consisted of 42 patients with benign ovarian lesions. Five proteins involved in the immune response were studied: BTLA, CD27, CD70, CD28, CD80. The study material was serum and peritoneal fluid. The ROC curve was plotted, and the area under the curve was calculated to characterize the sensitivity and specificity of the studied parameters. Univariate and multivariate analyses were performed simultaneously using the Cox regression model. The cut-off level of CD27 was 120.6 pg/mL, with the sensitivity and specificity of 66 and 84% (p = 0.014). Unfavorable prognostic factors determined in serum were: CD27 (for PFS: HR 1.26, 95% CI 1.21–1.29, p = 0.047; for OS: HR 1.20, 95% CI 1.15–1.22, p = 0.014). Unfavorable prognostic factors determined in peritoneal fluid were: BTLA (for OS: HR 1.26, 95% CI 1.25–1.31, p = 0.033). We conclude that CD27 should be considered as a potential biomarker in the diagnosis of ovarian cancer. BTLA and CD27 are unfavorable prognostic factors for ovarian cancer.

Clinical Relevance of Soluble Forms of Immune Checkpoint Molecules sPD-1, sPD-L1, and sCTLA-4 in the Diagnosis and Prognosis of Ovarian Cancer

It is crucial to find new diagnostic and prognostic biomarkers. A total of 80 patients were enrolled in the study. The study group consisted of 37 patients with epithelial ovarian cancer, and the control group consisted of 43 patients with benign ovarian cystic lesions. Three proteins involved in the immune response were studied: PD-1, PD-L1, and CTLA-4. The study material was serum and peritoneal fluid. The ROC curve was plotted, and the area under the curve was calculated to characterize the sensitivity and specificity of the studied parameters. Univariate and multivariate analyses were performed simultaneously using the Cox regression model. The cut-off level of CTLA-4 was 0.595 pg/mL, with the sensitivity and specificity of 70.3% and 90.7% (p = 0.000004). Unfavorable prognostic factors determined in serum were: PD-L1 (for PFS: HR 1.18, 95% CI 1.11–1.21, p = 0.016; for OS: HR 1.17, 95% CI 1.14–1.19, p = 0.048) and PD-1 (for PFS: HR 1.01, 95% CI 0.91–1.06, p = 0.035). Unfavorable prognostic factors determined in peritoneal fluid were: PD-L1 (for PFS: HR 1.08, 95% CI 1.01–1.11, p = 0.049; for OS: HR 1.14, 95% CI 1.10–1.17, p = 0.045) and PD-1 (for PFS: HR 1.21, 95% CI 1.19–1.26, p = 0.044). We conclude that CTLA-4 should be considered as a potential biomarker in the diagnosis of ovarian cancer. PD-L1 and PD-1 concentrations are unfavorable prognostic factors for ovarian cancer.

Multiple genetic variants predict the progression-free survival of bevacizumab plus chemotherapy in advanced ovarian cancer: A retrospective study.

Bevacizumab (BV) plus chemotherapy is broadly used in advanced ovarian cancer (OC). However, the efficacy of BV-based regimens for advanced OC patients is not satisfactory. Therefore, it is urgent to explore the predictive genetic biomarkers for BV.Tumor tissues from advanced OC patients receiving BV-based regimens were analyzed with a 150-gene targeted panel for next generation sequencing. The associations between gene alterations or clinicopathology features and progression-free survival (PFS) were analyzed by Kaplan–Meier curves or Cox regression. The association of the genetic alteration in potential predictive genes and expressions of 11 vascular endothelial growth factor-related genes were analyzed in The Cancer Genome Atlas cohort using 292 OC cases.Sixty two Chinese advanced OC patients treated with BV-based therapy were included. The median PFS of was 6.9 months, and objective response rate was 14.5%. In multivariate Cox regression analysis, the status of endothelial growth factor receptor (EGFR) (hazard ratio = 6.39, 95% confidence interval [CI] 2.25–18.13, P < .001) and human epidermal growth factor receptor 2 (HER2) (hazard ratio = 3.58, 95% CI 1.27–10.08, P = .016) were significantly correlated with PFS. MYC Proto-Oncogene amplification seemed to have a positive trend (hazard ratio = 0.21, 95% CI 0.05–1.02, P = .052). Moreover, EGFR and HER2 alterations were not prognostic factors of overall survival for OC in The Cancer Genome Atlas OC cohort. The vascular endothelial growth factor-related signature analysis indicated vascular endothelial factor A expression was upregulated with EGFR alterations (P = .034) which may be involved in BV resistance, and HER2 alterations were associated with hypoxia inducible factor 1 subunit alpha overexpression significantly (P = .029).EGFR or HER2 alterations are negative predictors of PFS for OC patient treated with BV plus chemotherapy. Therefore, the clinicians may consider to use alternative regimens such as anti-EGFR or anti-HER2 targeted therapy instead of BV-based regimens on these patients when standard care fail.

Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value.

BackgroundOvarian cancer is one of the most common malignant tumors in female genital organs, and its incidence rate is high. However, the pathogenesis and prognostic markers of ovarian cancer are unclear. This study sought to screen potential markers of ovarian cancer and to explore their prognostic value.MethodsThe Cancer Genome Atlas, Gene Expression Omnibus, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used in this study. The least absolute shrinkage and selection operator (LASSO), multivariate Cox regression and stepwise regression analysis were chosen to screen genes and construct risk model. Gene Set Enrichment Analysis (GSEA) and an immune-infiltration analysis were performed.ResultsOne hundred thirty two co-expressed genes were found. They involved in metabolism, protein phosphorylation, mitochondria, and immune signaling pathways. Twelve genes significantly related to the survival of ovarian cancer were identified. Eight risk genes (i.e., CACNB1, FAM120B, HOXB2, MED19, PTPN2, SMU1, WAC.AS1, and BCL2L11) were further screened and used to construct the risk model. The risk status might be an independent prognostic factor of ovarian cancer, and most of the biological functions of genes expressed in high-risk ovarian cancer were related to synapse, adhesion, and immune-related functions. The clusters of CD4+ T cells and M2 macrophages were high in high-risk status samples.ConclusionsIn ovarian cancer, the abnormal expression of 8 genes, including CACNB1, FAM120B, HOXB2, MED19, PTPN2, SMU1, WAC.AS1, and BCL2L11, is closely related to ovarian cancer progression, and these genes can serve as independent prognosis markers of ovarian cancer.

Comprehensive Analysis of the Expression and Prognosis for Laminin Genes in Ovarian Cancer.

Survival is low in ovarian cancer (OC). Most OC patients demonstrate advanced metastases, and recurrence is common. Dysregulation of laminin interactions is associated with cancer development. However, it is unknown whether laminin subunits can be considered as biomarkers for OC diagnosis, prognosis, and treatment. We used cBioPortal, GEO, ONCOMINE, GEPIA, Human Protein Atlas, Kaplan-Meier Plotter, TIMER, and Metascape to determine the associations among laminin expression, prognosis, and immune cell infiltration in OC. LAMA5, LAMB3, and LAMC2 mRNAs and LAMA3, LAMB1/B2/B3, and LAMC1/C2 proteins were overexpressed in OC tissues compared with normal ovaries. LAMA4, LAMB1, and LAMC1 mRNA upregulation was positively correlated with worse overall survival (OS) and progression-free survival (PFS) in OC. Elevated LAMA2 and LAMC2 mRNA expression levels were related to better PFS or OS, respectively. The results speculated that LAMA5 could potentially be a good prognostic factor in OC. Its expression proves valuable for predicting OS in patients diagnosed with stage Ⅳ and grade 3 OC and PFS in patients diagnosed with all OC stages or grades. LAMB3 and LAMC2 expression was correlated with platinum resistance development. ROC analysis of laminins in OC sets revealed that LAMA2/A4/A5, LAMB1/B2/B3, and LAMC2 could be used to differentiate between malignant tumors and non-neoplastic tissues. LAMA1/A5 and LAMC1 were significantly and negatively correlated with various tumor immune infiltrates (TILs), especially with dendritic cells, CD8+ T cells or neutrophil. LAMA4 and LAMB1 might be associated with tumor purity in OC. Overall, LAMA5 and LAMC1 could help predict OC survival and diagnosis and might be deemed important OC oncogenes.

A Potential Immune-Related Long Non-coding RNA Prognostic Signature for Ovarian Cancer.

Ovarian cancer (OC), the most lethal gynecologic malignancy, ranks fifth in cancer deaths among women, largely because of late diagnosis. Recent studies suggest that the expression levels of immune-related long non-coding RNAs (lncRNAs) play a significant role in the prognosis of OC; however, the potential of immune-related lncRNAs as prognostic factors in OC remains unexplored. In this study, we aimed to identify a potential immune-related lncRNA prognostic signature for OC patients. We used RNA sequencing and clinical data from The Cancer Genome Atlas and the Gene Expression Omnibus database to identify immune-related lncRNAs that could serve as useful biomarkers for OC diagnosis and prognosis. Univariate Cox regression analysis was used to identify the immune-related lncRNAs with prognostic value. Functional annotation of the data was performed through the GenCLiP310 website. Seven differentially expressed lncRNAs (AC007406.4, AC008750.1, AL022341.2, AL133351.1, FAM74A7, LINC02229, and HOXB-AS2) were found to be independent prognostic factors for OC patients. The Kaplan-Meier curve indicated that patients in the high-risk group had a poorer survival outcome than those in the low-risk group. The receiver operating characteristic curve revealed that the predictive potential of the immune-related lncRNA signature for OC was robust. The prognostic signature of the seven lncRNAs was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the signature of the seven lncRNAs was an independent prognostic factor for OC patients. Finally, we constructed a nomogram model and a competing endogenous RNA network related to the lncRNA prognostic signature. In conclusion, our study reveals novel immune-related lncRNAs that may serve as independent prognostic factors in OC.