Ovarian Serous Cystadenocarcinoma Research Articles

Inferences of carboplatin response-related signature by integrating multiomics data in ovarian serous cystadenocarcinoma.

Platinum-based chemotherapy, especially carboplatin, is the primary measure to treat patients with ovarian cancer (OC). However, OC patients still have an adverse prognosis due to emergency of chemotherapy resistance. Ovarian serous cystadenocarcinoma (OSC) is the most common histological subtype of OC. Therefore, identifying the key factors that affect chemotherapy resistance and searching novel treatments had become a top priority. In this study, we analyzed carboplatin response-related mRNA, miRNA, DNA methylation, and alternative splicing (AS) and established a drug-resistant signature for carboplatin in OSC. This drug-resistant signature was obviously higher in resistant group than in non-resistant group and had accuracy predictive performance, which demonstrated that this signature could be considered as a superior indicator for OSC patients with carboplatin resistance. Furthermore, we selected three potential small molecule drugs including liranaftate, siguazodan, and tramiprostate to inhibit carboplatin resistance of OSC. In addition, we also identified ZINC00000205417, ZINC00000140928, and ZINC00021908260 were potential small molecule compounds for SLC17A7 based on Molecular Operating Environment (MOE) virtual screening. Finally, we confirmed the drug-like properties of these small molecule drugs via evaluating absorption, distribution, metabolism, elimination, and toxicity (ADMET) property. In summary, the signature could be used as biomarker for carboplatin resistance and small molecule drugs targeting these genes could improve clinical treatment for OSC in the future.

A pan-cancer analysis of the oncogenic role of secreted phosphoprotein 1 (SPP1) in human cancers.

BackgroundEmerging evidence suggests that secreted phosphoprotein 1 (SPP1) is involved in tumor cell progression in multiple cancer types. However, the role of SPP1 in different cancers is still not clear.MethodsWe used data from The Cancer Genome Atlas (TCGA) to analyze the multiomic roles of SPP1, including RNA expression, DNA methylation, protein phosphorylation, immune infiltration, and overall survival (OS) in 33 tumor types.ResultsSPP1 is highly expressed in most cancer types, and its methylation variability and mRNA expression level are both correlated with prognosis in multiple cancer types. A higher S234 phosphorylation level was observed in 4 types of tumors, including colon adenocarcinoma (COAD) and lung adenocarcinoma (LUAD). SPP1 expression level was positively associated with the infiltration level of dendritic cells, neutrophils, and macrophages in multiple cancer types. It was also significantly positively correlated with hepatitis A virus cellular receptor 2 (HAVCR2), which was observed in most tumor types, including brain lower grade glioma (LGG) and ovarian serous cystadenocarcinoma (OV). Moreover, myeloid cell differentiation and leukocyte migration were observed in the enrichment analysis, suggesting that SPP1 might induce immune escape.ConclusionsPan-cancer analysis using a multiomic approach offered a comprehensive overview of SPP1. This protein plays an important role in most of the analyzed tumor types and could be a valuable prognostic marker across different types of cancer.

Clinical Significance of TET2 in Female Cancers.

Female cancers refer to malignant tumors of the female reproductive system and breasts, which severely affect the physical and mental health of women. Although emerging experiment-based studies have indicated a potential correlation between ten-eleven translocation methylcytosine dioxygenase (TET2) and female cancers, no comprehensive studies have been conducted. Therefore, this study aimed to summarize the clinical value and underlying oncogenic functions of TET2 in female cancers, such as breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), ovarian serous cystadenocarcinoma (OV), uterine corpus endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS), based on the data obtained from The Cancer Genome Atlas. The expression of TET2 was decreased in most female cancers, and its high expression was distinctly associated with the favorable prognosis of most female cancers. Furthermore, CD8+ T-cell infiltration was not correlated with TET2 in OV, UCEC, and UCS, whereas tumor-associated fibroblast infiltration was significantly correlated with TET2 in BRCA, CESC, and OV. TET2 was co-expressed with the immune checkpoint molecules ADORA2A, CD160, CD200, CD200R1, CD44, CD80, NRP1 TNFSF4, and TNFSF15 in most female cancers. Enrichment analysis revealed that some signaling pathways involving TET2 and related genes were related to tumorigenesis. Immunohistochemical and immunofluorescence staining confirmed the results of cancer immune infiltration analysis in BRCA tissues. Therefore, this study provides evidence for the oncogenic functions and clinical value of TET2 in female cancers.

ANXA2P2: A Potential Immunological and Prognostic Signature in Ovarian Serous Cystadenocarcinoma via Pan-Carcinoma Synthesis.

BackgroundAlthough the effect of pseudogene ANXA2P2 on some tumors has been reported in a few literatures, the therapeutic potential and prognostic value of ANXA2P2 in ovarian serous cystadenocarcinoma (OV) have not been elucidated.MethodsThe correlation for ANXA2P2 expression patterns to prognostic characteristics, tumor immune microenvironment, immune cell infiltration level, tumor mutation burden (TMB), tumor microsatellite instability (MSI), drug sensitivity, and pathway function enrichment were investigated in pan-carcinoma via TCGA and GTEx databases. Subsequently, the role of ANXA2P2 expression levels in the pathway enrichments and prognosis prediction in OV were further explored using weighted correlation network analysis (WGCNA) analysis, gene mutation analysis, and risk-independent prognostic analysis.ResultsANXA2P2 was frequently overexpressed in a variety of tumors compared with normal tissues. The correlation analysis for prognostic characteristics, tumor immune microenvironment, immune cell infiltration level, TMB, MSI, drug sensitivity, and pathway function enrichment revealed that ANXA2P2 expression patterns might deal a significant impact on the pathogenesis, development, and prognosis of various tumors. Then, GSVA, GSEA, WGCNA, gene mutation, and independent prognostic analysis for OV have indicated that high expression in ANXA2P2 could be mostly enriched in TNF-α signaling-via-NF-κB, epithelial-mesenchymal transition, apical junction, IL-6-JAK STAT3 signaling, etc., which were also proved to act as crucial factors on tumorigenesis, development, invasion, and metastasis. The mutation of TP53 (94%), TTN (24%), and CSMD3 (9%) in the biological process of tumor had been confirmed by relevant studies. Finally, the independent prognostic analysis demonstrated that ANXA2P2 expression in OV contributes greatly to the dependability of 3- and 5-year survival prediction.ConclusionIn summary, our findings might provide a helpful foundation for prospective explorative researches, afford new strategies for the clinical treatment, deal prognosis prediction, and give new hope for OV patients.

Prognostic Implication and Oncogenic Role of PNPO in Pan-Cancer.

Objective: Pyridoxine 5′-phosphate oxidase (PNPO) is a key enzyme in the metabolism of vitamin B6 and affects the tumorigenesis of ovarian and breast cancers. However, the roles of PNPO in other types of cancer remain unknown. Methods: The expression of PNPO was interpreted by The Cancer Genome Atlas (TCGA) database and Genotype Tissue-Expression (GTEX) database. Analysis of PNPO genomic alterations and protein expression in human organic tissues was analyzed by the cBioPortal database and human multiple organ tissue arrays. PNPO with drug sensitivity analysis was performed from the CellMiner database. The correlations between PNPO expression and survival outcomes, clinical features, DNA mismatch repair system (MMR), microsatellite instability (MSI), tumor mutation burden (TMB), and immune-associated cell infiltration were analyzed using the TCGA, ESTIMATE algorithm, and TIMER databases. Gene Set Enrichment Analysis (GSEA) was applied to elucidate the biological function of PNPO in pan-cancer. Results: The differential analysis showed that the level of PNPO mRNA expression was upregulated in 21 tumor types compared with normal tissues, which was consistent with its protein expression in most cancer types. The abnormal expression of PNPO could predict the survival outcome of patients with esophageal carcinoma (ESCA), kidney renal clear cell carcinoma (KIRC), prostate adenocarcinoma (PRAD), ovarian serous cystadenocarcinoma (OV), and uveal melanoma (UVM). Furthermore, the most frequent mutation type of PNPO genomic was amplified. Moreover, the aberrant PNPO expression was related to MMR, MSI, TMB, and drug sensitivity in various types of cancer. The expression of PNPO was related to the infiltration levels of various immune-associated cells in pan-cancer by ESTIMATE algorithm and TIMER database mining. Conclusion: Our results suggest that PNPO is a potential molecular biomarker for predicting patient prognosis, drug sensitivity, and immunoreaction in pan-cancer.

Comprehensive characterization of 11 prognostic alternative splicing events in ovarian cancer interacted with the immune microenvironment

Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of ovarian cancer patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1472 AS events that were associated with survival of ovarian serous cystadenocarcinoma (OC) and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and developed the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OC patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OC. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OC. AS events that were correlated with the immune system might be potential therapeutic targets.

Comprehensive Analysis of the Expression and Clinical Significance of a Ferroptosis-Related Genome in Ovarian Serous Cystadenocarcinoma: A Study Based on TCGA Data

Background: Epithelial ovarian cancer (EOC) is the deadliest malignancy among the gynecologic tumors, and ovarian serous cystadenocarcinoma (OV) is the dominant histological type. Ferroptosis is a novel iron-dependent, programmed form of cell death, and agents that trigger ferroptosis may constitute potential anti-cancer therapies. Materials and Methods: We herein extracted the genes that participate in the process of ferroptosis from the online FerrDb database to create a ferroptosis-related genome (FRG), and then comprehensively analyzed the relationship between the mRNA expression of each gene and the clinicopathologic features of The Cancer Genome Atlas (TCGA)-OV cohort. Results: We found that most of the FRG genes were differently expressed between OV and normal ovarian tissue and were significantly related to the prognosis of OV. In addition, gene ontology (GO) analysis revealed that the candidate genes of the FRG were primarily associated with responses to nutrient levels, oxidative stress, oxygen levels, and neuronal death. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that candidate genes of the FRG were primarily associated with ferroptosis, hepatitis B, mitophagy, prostate cancer, and bladder cancer. The protein–protein interaction (PPI) network exhibited 132 nodes, 565 edges, an average node degree of 9.94, and an average local clustering coefficient of 0.539, indicating that the proteins were closely interrelated with one another and constitute a biological cluster. A comprehensive analysis of the top 5 genes involved in promoting and preventing ferroptosis revealed that these genes were differently expressed between OV and normal ovarian tissue, were significantly related to the prognosis of OV, reflected excellent diagnostic value, and were significantly correlated with immune cell infiltration in the tumor microenvironment (TME), polarization of macrophages, and with immune checkpoints. The protein levels of top 5 genes involved in promoting ferroptosis were differentially expressed between OV and normal ovarian tissue, and the top 5 genes involved in preventing ferroptosis were constitutively expressed in most of the normal tissues and tumors. Conclusions: We herein ascertained that the majority of the FRG was differentially expressed between OV and normal ovarian tissue, that the genes were significantly related to prognosis, and that the dysregulation of ferroptosis appeared to influence the development and progression of OV. The FRG showed an excellent diagnostic value for OV, and we postulate that it is significantly correlated with immune cell infiltration and immune checkpoints in the TME. We posit that targeting ferroptosis might comprise a novel anti-cancer therapy in OV.

Systemic characterization of alternative splicing related to prognosis, immune infiltration, and drug sensitivity analysis in ovarian cancer.

BackgroundAlternative splicing (AS) plays an essential role in tumorigenesis and progression. This study intended to construct an innovative prognostic model based on AS events to gain more precise survival prediction and search for potential therapeutic targets in ovarian cancer.MethodsSeven types of AS events in ovarian serous cystadenocarcinoma (OV) patients with RNA-seq were obtained using The Cancer Genome Atlas (TCGA) SpliceSeq tool and database. Cox and Kaplan-Meier curve analyses were employed to establish the prognostic models. Relying on drug sensitivity data from the CellMiner database, Genomics of Drug Sensitivity (GDS) was adopted to estimate the platinum-sensitive analysis. Furthermore, a prognostic splicing factor (SF)-AS network was constructed using Cytoscape. Finally, in order to explore the influence of the tumor microenvironment on the prognosis of OV patients, we first combined a similar network fusion and consensus clustering (SNF-CC) algorithm to identify three OV subtypes based on survival-related AS events and then utilized single-sample Gene Set Enrichment Analysis (ssGSEA) method to perform immune cell infiltration analysis.ResultsA total of 48,049 AS events and 21,841 related genes were selected from 318 OV samples, and 2,206 AS events associated with disease-free survival (DFS) were identified. Multivariate Cox and Kaplan-Meier curve analyses were then employed to establish the prognostic models. Receiver operating characteristic (ROC) analysis from 0.59 to 0.75 showed that these models were highly efficient in distinguishing patient survival. GDS was adopted with the CellMiner database to provide some insights for platinum-sensitive analysis of OV. Furthermore, a prognostic SF-AS network, which discovered a significant connection between SFs and prognostic AS genes, was constructed using Cytoscape. The combined SNF-CC algorithm revealed three distinct OV subtypes based on the prognostic AS events, and the associations between this novel molecular classification and immune cell infiltration were further explored.ConclusionsWe developed a powerful prognostic AS signature for OV and provided a deeper understanding of SF-AS network regulatory mechanisms, as well as platinum-sensitive and cancer immune microenvironments. These results revealed various candidate biomarkers and potential targets for OV treatment strategies.

Immunohistochemical evaluation of forkhead box A1 and EphA5 markers in serous ovarian carcinomas, and their impact on the clinical outcome of patients.

Ovarian cancer is the most lethal gynaecological neoplasm in females. In ovarian cancer, forkhead box A1 (FOXA1) aids transcription of YAP-associated protein mediated by the cyclic adenosine monophosphate response element-binding protein. As aresult, cellular proliferation and migration increased. The roles of erythropoietin-producing human hepatocellular carcinoma cell (Eph) receptors and ephrin ligands in cell adhesion, migration, cell proliferation regulation in various cancers, and angiogenesis are well characterized. This study included formalin-fixed, paraffin-embedded tissue specimens from 41 patients with ovarian serous cystadenocarcinoma, including both low- and high-grade tumours. For each case, aparaffin block with tumour tissue was chosen for an immunohistochemical procedure using primary antibodies against EphA5 and FOXA1. By the end of 2017, patients finished their chemotherapy and were followed for the next 3 years. Positive FOXA1 and EphA5 results were presented in 68.3% and 39% of patients, respectively. Astatistically significant correlation was detected between FOXA1 expression and each of CA-125 level, tumour stage, tumour grade, and the presence of lymph node metastasis. In our work, the overall survival was positively correlated with EphA5 expression and inversely correlated to FOXA1 immunoreactivity. The estimated disease-free survival (DFS) and EphA5 immunoreactivity had asignificant positive association, whereas DFS and FOXA1 protein expression had asignificant inverse link. FOXA1 and EphA5 expression play arole in ovarian cancer progression and prognosis prediction.

Race-Specific Genetic Profiles of Homologous Recombination Deficiency in Multiple Cancers.

Homologous recombination deficiency (HRD) has been used to predict both cancer prognosis and the response to DNA-damaging therapies in many cancer types. HRD has diverse manifestations in different cancers and even in different populations. Many screening strategies have been designed for detecting the sensitivity of a patient’s HRD status to targeted therapies. However, these approaches suffer from low sensitivity, and are not specific to each cancer type and population group. Therefore, identifying race-specific and targetable HRD-related genes is of clinical importance. Here, we conducted analyses using genomic sequencing data that was generated by the Pan-Cancer Atlas. Collapsing non-synonymous variants with functional damage to HRD-related genes, we analyzed the association between these genes and race within cancer types using the optimal sequencing kernel association test (SKAT-O). We have identified race-specific mutational patterns of curated HRD-related genes across cancers. Overall, more significant mutation sites were found in ATM, BRCA2, POLE, and TOP2B in both the ‘White’ and ‘Asian’ populations, whereas PTEN, EGFG, and RIF1 mutations were observed in both the ‘White’ and ‘African American/Black’ populations. Furthermore, supported by pathogenic tendency databases and previous reports, in the ‘African American/Black’ population, several associations, including BLM with breast invasive carcinoma, ERCC5 with ovarian serous cystadenocarcinoma, as well as PTEN with stomach adenocarcinoma, were newly described here. Although several HRD-related genes are common across cancers, many of them were found to be specific to race. Further studies, using a larger cohort of diverse populations, are necessary to identify HRD-related genes that are specific to race, for guiding gene testing methods.

The circular RNA expression profile in ovarian serous cystadenocarcinoma reveals a complex circRNA\u2013miRNA regulatory network

BackgroundOvarian serous cystadenocarcinoma is one of the most serious gynecological malignancies. Circular RNA (circRNA) is a type of noncoding RNA with a covalently closed continuous loop structure. Abnormal circRNA expression might be associated with tumorigenesis because of its complex biological mechanisms by, for example, functioning as a microRNA (miRNA) sponge. However, the circRNA expression profile in ovarian serous cystadenocarcinoma and their associations with other RNAs have not yet been characterized. The main purpose of this study was to reveal the circRNA expression profile in ovarian serous cystadenocarcinoma.MethodsWe collected six specimens from three patients with ovarian serous cystadenocarcinoma and adjacent normal tissues. After RNA sequencing, we analyzed the expression of circRNAs with relevant mRNAs and miRNAs to characterize potential function.Results15,092 unique circRNAs were identified in six specimens. Approximately 46% of these circRNAs were not recorded in public databases. We then reported 353 differentially expressed circRNAs with oncogenes and tumor-suppressor genes. Furthermore, a conjoint analysis with relevant mRNAs revealed consistent changes between circRNAs and their homologous mRNAs. Overall, construction of a circRNA–miRNA network suggested that 4 special circRNAs could be used as potential biomarkers.ConclusionsOur study revealed the circRNA expression profile in the tissues of patients with ovarian serous cystadenocarcinoma. The differential expression of circRNAs was thought to be associated with ovarian serous cystadenocarcinoma in the enrichment analysis, and co-expression analysis with relevant mRNAs and miRNAs illustrated the latent regulatory network. We also constructed a complex circRNA–miRNA interaction network and then demonstrated the potential function of certain circRNAs to aid future diagnosis and treatment.

Predictive modeling of gene expression regulation

BackgroundIn-depth analysis of regulation networks of genes aberrantly expressed in cancer is essential for better understanding tumors and identifying key genes that could be therapeutically targeted.ResultsWe developed a quantitative analysis approach to investigate the main biological relationships among different regulatory elements and target genes; we applied it to Ovarian Serous Cystadenocarcinoma and 177 target genes belonging to three main pathways (DNA REPAIR, STEM CELLS and GLUCOSE METABOLISM) relevant for this tumor. Combining data from ENCODE and TCGA datasets, we built a predictive linear model for the regulation of each target gene, assessing the relationships between its expression, promoter methylation, expression of genes in the same or in the other pathways and of putative transcription factors. We proved the reliability and significance of our approach in a similar tumor type (basal-like Breast cancer) and using a different existing algorithm (ARACNe), and we obtained experimental confirmations on potentially interesting results.ConclusionsThe analysis of the proposed models allowed disclosing the relations between a gene and its related biological processes, the interconnections between the different gene sets, and the evaluation of the relevant regulatory elements at single gene level. This led to the identification of already known regulators and/or gene correlations and to unveil a set of still unknown and potentially interesting biological relationships for their pharmacological and clinical use.

Development and identification of a prognostic nomogram model for patients with mixed cell adenocarcinoma of the ovary

BackgroundMixed cell ovarian adenocarcinoma (MCOA) is a malignant gynecologic tumor consisting of serous, mucous, and papillary tumor cells. However, the clinical features and prognosis of MCOA patients are unclear.MethodsIn this study, univariate and multivariate Cox proportional risk models were performed to identify independent prognostic factors. The Kaplan–Meier method was used to assess the relationship between clinical characteristics and patient survival. Finally, a nomogram was constructed and validated to predict patient survival time, and the C-index was used to evaluate the efficacy of the nomogram.ResultsA total of 2,818 patients diagnosed with MCOA were identified, and the 5-year survival rate was 62%. Univariate and multivariate Cox models suggested that age (HR=1.28, 95% CI[1.15,1.44]), grade (HR=1.26, 95% CI[1.12,1.41]), SEER stage (HR=1.63, 95% CI[1.25,2.13]) and AJCC (American Joint Committee on Cancer) stage (HR=1.59, 95% CI[1.36,1.86]) were independent prognostic factors for MCOA patients. After propensity score matching for age, grade, SEER stage, and AJCC stage, the 5-year survival rate was 69.7% for ovarian serous cystadenocarcinoma and 62.9% for ovarian papillary serous cystadenocarcinoma. These results mean that serous adenocarcinoma had the best prognosis of the three pathologic types of ovarian carcinoma (p<0.0001), with no significant difference between papillary serous cystadenocarcinoma and MCOA (p=0.712). Finally, a nomogram consisting of age, grade, SEER stage, and AJCC stage was established and validated to predict the survival time, with C-indices of 0.743 and 0.731, respectively.ConclusionsIn summary, MCOA is uncommon, and age, grade, SEER stage, and AJCC stage are independent prognostic factors. Compared with other common malignant ovarian tumors, MCOA has a poor prognosis.

A FZD7-specific Antibody-Drug Conjugate Induces Ovarian Tumor Regression in Preclinical Models.

Although WNT signaling is frequently dysregulated in solid tumors, drugging this pathway has been challenging due to off-tumor effects. Current clinical pan-WNT inhibitors are nonspecific and lead to adverse effects, highlighting the urgent need for more specific WNT pathway-targeting strategies. We identified elevated expression of the WNT receptor Frizzled class receptor 7 (FZD7) in multiple solid cancers in The Cancer Genome Atlas, particularly in the mesenchymal and proliferative subtypes of ovarian serous cystadenocarcinoma, which correlate with poorer median patient survival. Moreover, we observed increased FZD7 protein expression in ovarian tumors compared with normal ovarian tissue, indicating that FZD7 may be a tumor-specific antigen. We therefore developed a novel antibody-drug conjugate, septuximab vedotin (F7-ADC), which is composed of a chimeric human-mouse antibody to human FZD7 conjugated to the microtubule-inhibiting drug monomethyl auristatin E (MMAE). F7-ADC selectively binds human FZD7, potently kills ovarian cancer cells in vitro, and induces regression of ovarian tumor xenografts in murine models. To evaluate F7-ADC toxicity in vivo, we generated mice harboring a modified Fzd7 gene where the resulting Fzd7 protein is reactive with the human-targeting F7-ADC. F7-ADC treatment of these mice did not induce acute toxicities, indicating a potentially favorable safety profile in patients. Overall, our data suggest that the antibody-drug conjugate approach may be a powerful strategy to combat FZD7-expressing ovarian cancers in the clinic.

Long non-coding RNA FOXP4-AS1 is a prognostic biomarker and associated with immune infiltrates in ovarian serous cystadenocarcinoma.

Background:FOXP4-AS1 expression participates in multiple signal pathways and has been previously reported in colorectal cancer, cervical cancer, and other cancer cells. However, its role on prognosis and immune infiltrates in ovarian serous cystadenocarcinoma (OVs) remains unclear. The purpose of our study was to investigate the expression of FOXP4-AS1 in OVs and its association with immune infiltrates, and determined its prognostic roles in OVs.Methods:Using The Cancer Genome Atlas (TCGA) database, we retrieved FOXP4-AS1 expression and clinical information for 376 patients with OVs. Wilcoxon rank sum test was used to compare the expression of FOXP4-AS1 in OVs and normal ovarian tissue. Logistic regression was used to analyze the relationship between clinicopathologic features and FOXP4-AS1. Gene Set Enrichment Analysis (GSEA), and single sample Gene Set Enrichment Analysis (ssGSEA) was conducted to investigate the enrich pathways and functions and quantify the extent of immune cells infiltration for FOXP4-AS1. Kaplan–Meier method was used to generate survival curves, and Cox regression was used to analyze the relationship between FOXP4-AS1 and survival rate.Results:High FOXP4-AS1 expression was significantly correlated with tumor FIGO stage (P = .026). Multivariate survival analysis showed that FOXP4-AS1was an independent prognostic marker for overall survival (OS; hazard ratio [HR]: 0.638; 95% confidence interval [CI]:0.467–0.871; P = .001) and disease-specific survival (DSS; HR: 0.649; CI: 0.476–0.885; P = .006). GSEA showed that High FOXP4-AS1 expression may active programmed cell death 1 (PD-1) signaling, the cytotoxic T lymphocyte-associated antigen-4 (CTLA4) pathway, the B cell receptor signaling pathway, apoptosis, fibroblast growth factor receptor (FGFR) signaling, and the Janus-activated kinase signal transducers and activators of transcription (JAK-STAT) signaling pathway. FOXP4-AS1 expression was negatively correlated with markers of immune cells, including aDC, cytotoxic cells and neutrophils.Conclusion:High FOXP4-AS1 expression has the potential to be a prognostic molecular marker of favorable survival in OVs.

Upregulated Expression of CYBRD1 Predicts Poor Prognosis of Patients with Ovarian Cancer.

Cytochrome b reductase 1 (CYBRD1) promotes the development of ovarian serous cystadenocarcinoma (OV). We assessed the function of CYBRD1 in OV underlying The Cancer Genome Atlas (TCGA) database. The correlation between clinicopathological characteristics and CYBRD1 expression was estimated. The Cox proportional hazards regression model and the Kaplan–Meier method were applied to identify clinical features related to overall survival and disease-specific survival. Gene set enrichment analysis (GSEA) was applied to identify the relationship between CYBRD1 expression and immune infiltration. CYBRD1 expression in OV was significantly associated with poor outcomes of primary therapy and FIGO stage. Patients with high levels of CYBRD1 expression were prone to the development of a poorly differentiated tumor and experience of an unfavorable outcome. CYBRD1 expression had significant association with shorter OS and acts as an independent predictor of poor outcome. Moreover, enhanced CYBRD1 expression was positively associated with Tem, NK cells, and mast cells but negatively associated with CD56 bright NK cells and Th2 cells. CYBRD1 expression may serve as a diagnostic and prognostic indicator of OV patients. The mechanisms of poor prognosis of CYBRD1-mediated OV may include increased iron uptake, regulation of immune microenvironment, ferroptosis related pathway, and ERK signaling pathway, among which ferroptosis and ERK signaling pathway may be important pathways of CYBRD1-mediated OV. Furthermore, we verified that CYBRD1 was upregulated in OV and significant correlated with lymph nodes metastasis, advanced stage, poor-differentiated tumor, and poor clinical prognosis in East Hospital cohort. The results of this study may provide guidance for the development of optimal treatment strategies for OV.

Role of Transabdominal Ultrasound in Characterization of the Ovarian Mass

The use of grey-scale ultrasound morphology to characterize a pelvic mass may also be called ‘pattern recognition’. The grey-scale ultrasound image provides as much information as that obtained by the surgeon or pathologist when they cut a surgical specimen to see what it looks like inside. Aim of our study is to characterize the ovarian mass by ultrasound. The study was conducted in Department of Radiology and Imaging, College of Medical Sciences, Bharatpur. Patients with suspected ovarian mass in Gynecology OPD were included in our study. A prospective cross-sectional study was conducted on 60 patients in college of medical science, Bharatpur, over the period of one year (from November 2019 to October 2020). Present study showed benign ovarian (90.0%) pathology are the most commonly encountered ovarian mass. Ovarian mass is most common in adult female of age 15-30 years and malignant ovarian mass was most common among the age group of 30-60 years. Among benign pathology of ovary simple follicular cysts are most common (39.0%), followed by hemorrhagic cyst (31.0%), dermoid cyst (17.0%), chocolate cyst (9.0%) and ectopic pregnancy (4.0%). Among the malignant ovarian mass serous cystadenocarcinoma and mucinous cystadenocarcinoma showed similar frequency (33.0% each) and followed by immature teratoma and krukenberg tumor (17.0% each). Ultrasound parameters like size, septal thickness, solid component and spectral doppler (RI ans PI) are very helpful for determination of malignant pathology. In this study the sensitivity and specificity of size parameter is least (40.3% and 60.2%) and highest in solid component and spectral Doppler parameter (PI) being (82.0% and 92.0%). Combined study of grey scaleand spectral Doppler study plays crucial role in characterization of ovarian mass to differentiate between benign and malignant pathology.

Pan-Cancer Prognostic Role and Targeting Potential of the Estrogen-Progesterone Axis.

IntroductionEstrogen receptors (ESRs) and progesterone receptors (PGRs) are associated with the development and progression of various tumors. The feasibility of ESRs and PGRs as prognostic markers and therapeutic targets for multiple cancers was evaluated via pan-cancer analysis.MethodsThe pan-cancer mRNA expression levels, genetic variations, and prognostic values of ESR1, ESR2, and PGR were analyzed using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and cBioPortal. The expression levels of ERa, ERb, and PGR proteins were detected by immunohistochemical staining using paraffin-embedded tissue specimens of ovarian serous cystadenocarcinoma (OV) and uterine endometrioid adenocarcinoma (UTEA). Correlation between immunomodulators and immune cells was determined based on the Tumor and Immune System Interaction Database (TISIDB).Results ESR1, ESR2, and PGR mRNAs were found to be differentially expressed in different cancer types, and were associated with tumor progression and clinical prognosis. ERa, ERb, and PGR proteins were further determined to be significantly differentially expressed in OV and UTEA via immunohistochemical staining. The expression of ERa protein was positively correlated with a high tumor stage, whereas the expression of PGR protein was conversely associated with a high tumor stage in patients with OV. In patients with UTEA, the expression levels of both ERa and PGR proteins were conversely associated with tumor grade and stage. In addition, the expression levels of ESR1, ESR2, and PGR mRNAs were significantly associated with the expression of immunomodulators and immune cells.Conclusion ESR1, ESR2, and PGR are potential prognostic markers and therapeutic targets, as well as important factors for the prediction, evaluation, and individualized treatment in several cancer types.

Abstract 160: LASSO-based protein signatures for survival prediction in human cancer cohorts

Abstract Background: Large-scale multi-omics data characterizing human tumors are increasingly available and can be leveraged to develop a deeper understanding of biological processes and predict clinical outcomes. Reverse-phase protein array (RPPA) is a high-throughput, antibody-based method that provides a more direct assessment of cellular activity compared to DNA and RNA sequencing, which generate data that do not always correlate with protein expression. Multiple studies have demonstrated the prognostic value of RPPA data. Some of these studies have used pathway-driven approaches, relying on prior knowledge from the literature to group proteins into biological pathways, to develop prognostic signatures or predictors of treatment response. Methods: We obtained normalized RPPA data for up to 258 total, cleaved, acetylated, or phosphorylated protein species from The Cancer Proteome Atlas (TCPA). Starting from a published RPPA-based seven-protein signature of receptor tyrosine kinase (RTK) pathway activity in the form of an unweighted sum of the seven protein measurements, shown to have prognostic value in a 445-patient renal clear cell carcinoma cohort (TCGA-KIRC), we demonstrated that strong stratification of patients into high and low risk groups can be achieved by using a statistical approach—LASSO regression—with no a priori biological knowledge, to select from the 233 proteins and optimally combine their RPPA measurements into a weighted risk score. Method performance was assessed using two unbiased approaches: 1) 10 iterations of 3-fold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan-Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Results: For the first evaluation approach, the median hazard ratio between high and low risk groups across the held-out folds in the cross-validation based on the 7-protein RTK score was 2.4, compared to 3.3 when using the risk score derived by LASSO applied to the training data folds. Furthermore, the median difference in overall survival probability at 5 years based on the LASSO-derived risk score was 32.8%, compared to 25.2% when using the 7-protein RTK score. The permutation test p values were 5.0e-4 for both the RTK pathway-driven and the LASSO data-driven approaches. Finally, we demonstrated the applicability and performance of our approach for overall survival prediction in additional TCGA cohorts; namely, ovarian serous cystadenocarcinoma (TCGA-OVCA), sarcoma (TCGA-SARC), and cutaneous melanoma (TCGA-SKCM). Conclusions: The data-driven nature of our LASSO-based approach makes it versatile and particularly well-suited for the discovery of unexplored protein/disease associations that could aid in therapeutic discovery. Citation Format: Mariam M. Konaté, Ming-Chung Li, Lisa McShane, Yingdong Zhao. LASSO-based protein signatures for survival prediction in human cancer cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 160.

Abstract 2982: Utility of S. cerevisiae genetic interactions in the mechanistic validation and therapeutic potential of highly conserved targets for drug discovery

Abstract Use of chemo-genetic interaction mediated synthetic lethality represents a strategy for mechanistic validation of targets and gene-based patient stratification for clinical development. Given that core pathways supporting cancer development and progression (cell cycle regulation, genome integrity, metabolism) are highly conserved, orthogonal model organisms represent powerful systems in which to identify synthetic lethal pairs for highly conserved human drug targets. BPM42522 is an enzyme in the ubiquitin proteasome system whose anti-cancer potential has been validated through genetic and pharmacologic modulation. The S. cerevisiae homolog of BPM42522 (yBPM42522) is a critical cell cycle-regulatory gene with 273 genetic interactions affecting fitness (Costanzo 2016). Negative genetic interactors regulate cellular processes validated for therapeutic intervention in oncology such as DNA replication and repair, protein turnover, and mitosis. Thus, mapping yBPM42522 negative genetic interactors to their human homologs and curating tumors in which they are altered may aid in identification of clinical contexts more susceptible to pharmacologic inhibition of BPM42522. To this end, conservation analysis of genetic interactors of yBPM42522 was performed, and coding mutations and deletion events were then characterized using The Cancer Genome Atlas (TCGA) tumor data. The most frequently altered genetic interactors across human tumors were reviewed for the direction and strength of the genetic interaction between their yeast homologs and yBPM42522, and mutations were curated by their likelihood to result in a loss of function. Those with strong negative genetic interactions with yBPM42522 and frequent mutation or deletion in its human homolog were prioritized. The resulting candidates included tumor suppressors (FBXW7, NF1), cell cycle regulators (CCNB1, CCNB3, BUB1B), and the NIMA kinase and GTPase-activating protein families (NEK3, NEK4, RASA1, RASAL2). TCGA database was used to determine if alterations in these candidate genes were prevalent in specific tumor types and whether they co-occurred with alterations in established cancer driver genes. Several candidate genetic interactors identified were frequently mutated or deleted in specific tumor types including uterine carcinosarcoma, uterine corpus endometrial carcinoma, ovarian serous cystadenocarcinoma, and mesothelioma. Moreover, these alterations were mutually exclusive with 96 reported cancer driver genes. Validation of the candidate genetic interactors for synthetic lethality with BPM42522 and their role in specific cancer types highlights the approach for rapid identification of synthetic lethality and its potential use to stratify patient populations most likely to benefit from therapeutic agents targeting highly conserved drug targets. Citation Format: Anne R. Diers, Kris Richardson, Leonardo O. Rodrigues, Rangaprasad Sarangarajan, Niven R. Narain, Jennifer A. Benanti, Stephane Gesta. Utility of S. cerevisiae genetic interactions in the mechanistic validation and therapeutic potential of highly conserved targets for drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2982.