Features Of Ovarian Cancer Research Articles

STAU1-mediated CNBP mRNA degradation by LINC00665 alters stem cell characteristics in ovarian cancer

BackgroundTo investigate the role of lncRNA LINC00665 in modulating ovarian cancer stemness and its influence on treatment resistance and cancer development.MethodsWe isolated ovarian cancer stem cells (OCSCs) from the COC1 cell line using a combination of chemotherapeutic agents and growth factors, and verified their stemness through western blotting and immunofluorescence for stem cell markers. Employing bioinformatics, we identified lncRNAs associated with ovarian cancer, with a focus on LINC00665 and its interaction with the CNBP mRNA. In situ hybridization, immunohistochemistry, and qPCR were utilized to examine their expression and localization, alongside functional assays to determine the effects of LINC00665 on CNBP.ResultsLINC00665 employs its Alu elements to interact with the 3’-UTR of CNBP mRNA, targeting it for degradation. This molecular crosstalk enhances stemness by promoting the STAU1-mediated decay of CNBP mRNA, thereby modulating the Wnt and Notch signaling cascades that are pivotal for maintaining CSC characteristics and driving tumor progression. These mechanistic insights were corroborated by a series of in vitro assays and validated in vivo using tumor xenograft models. Furthermore, we established a positive correlation between elevated CNBP levels and increased disease-free survival in patients with ovarian cancer, underscoring the prognostic value of CNBP in this context.ConclusionslncRNA LINC00665 enhances stemness in ovarian cancer by mediating the degradation of CNBP mRNA, thereby identifying LINC00665 as a potential therapeutic target to counteract drug resistance and tumor recurrence associated with CSCs.

Expression of human dCTP pyrophosphatase 1 (DCTPP1) and its association with cisplatin resistance characteristics in ovarian cancer.

Cisplatin (DDP) resistance is a major challenge in treating ovarian cancer patients. A recently discovered enzyme called dCTP pyrophosphatase 1 (DCTPP1) has been implicated in regulating cancer characteristics, including drug responses. In this study, we aimed to understand the role of DCTPP1 in cancer progression and cisplatin response. Using publicly available databases, we analysed the expression and clinical significance of DCTPP1 in ovarian cancer. Our bioinformatics analysis confirmed that DCTPP1 is significantly overexpressed in ovarian cancer and is closely associated with tumour progression and poor prognosis after cisplatin treatment. We also found that DCTPP1 located in oxidoreductase complex and may be involved in various biological processes related to cisplatin resistance, including pyrimidine nucleotide metabolism, the P53 signalling pathway and cell cycle signalling pathways. We observed higher expression of DCTPP1 in cisplatin-resistant cells (SKOV3/DDP) and samples compared to their sensitive counterparts. Additionally, we found that DCTPP1 expression was only enhanced in SKOV3/S cells when treated with cisplatin, indicating different expression patterns of DCTPP1 in cisplatin-sensitive and cisplatin-resistant cancer cells. Our study further supports the notion that cisplatin induces intracellular reactive oxygen species (ROS) and triggers cancer cell death through excessive oxidative stress. Knocking out DCTPP1 reversed the drug resistance of ovarian cancer cells by enhancing the intracellular antioxidant stress response and accumulating ROS. Based on our research findings, we conclude that DCTPP1 has prognostic value for ovarian cancer patients, and targeting DCTPP1 may be clinically significant in overcoming cisplatin resistance in ovarian cancer.

Disulfidptosis-related signature elucidates the prognostic, immunologic, and therapeutic characteristics in ovarian cancer.

Ovarian cancer (OC) is the deadliest malignancy in gynecology, but the mechanism of its initiation and progression is poorly elucidated. Disulfidptosis is a novel discovered type of regulatory cell death. This study aimed to develop a novel disulfidptosis-related prognostic signature (DRPS) for OC and explore the effects and potential treatment by disulfidptosis-related risk stratification. The disulfidptosis-related genes were first analyzed in bulk RNA-Seq and a prognostic nomogram was developed and validated by LASSO algorithm and multivariate cox regression. Then we systematically assessed the clinicopathological and mutational characteristics, pathway enrichment analysis, immune cell infiltration, single-cell-level expression, and drug sensitivity according to DRPS. The DRPS was established with 6 genes (MYL6, PDLIM1, ACTN4, FLNB, SLC7A11, and CD2AP) and the corresponding prognostic nomogram was constructed based on the DRPS, FIGO stage, grade, and residual disease. Stratified by the risk score derived from DRPS, patients in high-risk group tended to have worse prognosis, lower level of disulfidptosis, activated oncogenic pathways, inhibitory tumor immune microenvironment, and higher sensitivity to specific drugs including epirubicin, stauroporine, navitoclax, and tamoxifen. Single-cell transcriptomic analysis revealed the expression level of genes in the DRPS significantly varied in different cell types between tumor and normal tissues. The protein-level expression of genes in the DRPS was validated by the immunohistochemical staining analysis. In this study, the DRPS and corresponding prognostic nomogram for OC were developed, which was important for OC prognostic assessment, tumor microenvironment modification, drug sensitivity prediction, and exploration of potential mechanisms in tumor development.

Incidence and characteristics of ovarian cancer following endometrial cancer in the emerging era of conservative management of endometrial cancer-Implications for counseling-A SEER analysis.

To assess the ovarian cancer (OC) risk following endometrial cancer (EC) in patients who underwent ovarian preservation as part of the EC staging. With permission of the Surveillance, Epidemiology and End Results (SEER) program of the United States National Cancer Institute, clinicopathological information of women diagnosed with EC and following OC were analyzed. Incidence of OC and survival according to the surgical approach were studied. Primary analysis was conducted in women up to and including the age of 49 years. A total of 116 patients up to the age of 49 years were diagnosed with EC and following OC. In this group of patients, no differences in incidence (IRR 0.9, CI 0.56-1.49, p = 0.66) or survival rates (p = 0.71) were found comparing ovarian preservation and bilateral salpingo-oophorectomy (BSO) performance. In an overall analysis of women diagnosed with EC and following OC at any age, incidence of OC did not differ between groups (IRR 1.07, CI 0.83-1.39, p = 0.59) yet when including patients older than 49 years old survival rates were shorter in ovarian preservation patients compared to patients with BSO performed as part of their EC treatment. Ovarian preservation in EC patients under the age of 49 years may be considered safe, with no impact on OC incidence or survival, benefiting longer natural hormonal status.

Factors predicting BRCA1/2 pathogenic variants in patients with ovarian cancer: a systematic review with meta-analysis

AimTo provide accurate figures of the frequency of specific clinical features in ovarian cancer (OC) associated with germline BRCA1/2 pathogenic variants and to define their relevance in predicting the presence...

Abstract 5446: Immune phenotypes classified by deep learning-based H&E tissue analyzer demonstrate distinct immune landscape and transcriptomic features in ovarian cancer

Abstract Introduction: Deep learning-based H&E slide analyzer, Lunit-SCOPE IO can classify the tumor microenvironment as three immune phenotypes (IPs): inflamed, immune-excluded and immune-desert. In our previous study, the IPs demonstrated distinct survival outcome and immunologic landscape in endometrial cancer. To further explore the application of IPs in other type of cancer, we applied Lunit-SCOPE in ovarian cancer (OV) and compared tumor microenvironments based on the IPs. Methods: H&E slide images, RNA-sequencing data, and clinical data were obtained from TCGA OV cohort. Lunit-SCOPE IO is a H&E slide analyzer using deep learning algorithm and was trained with 1,824 H&E slides of advanced NSCLC. We used the analyzer to classify H&E slide images from TCGA OV cohort to three IPs. Cibersort was used to assess immune cell infiltration across the IPs. The cytolytic activity score was obtained from geometric mean of GZMA and PRF1 RNA expression. We further assessed transcriptomic characteristics across IPs via differentially expressed genes analysis and gene set enrichment analysis (GSEA). Additionally, we compared CD274 gene expression across IPs. Finally, survival analysis was performed to evaluate survival outcome based on IPs. We used Mann-Whitney method to compare non-parametric variables between the IPs. Results: The proportion of inflamed, immune-excluded and immune-desert group in TCGA OV were 7 (10.2%), 13 (18.8%), and 49 (71%), respectively. Inflamed group showed significantly higher proportion of M1 macrophage compared with immune-desert group (6.6% vs. 2%, P=.012). We observed higher cytolytic activity score in inflamed group compared to immune-desert group (7.21 vs. 5.27, P=.016). In GSEA, inflamed group is significantly enriched in IL6 JAK STAT3 signaling, interferon gamma response, KRAS signaling up, and inflammatory response pathway (NES 2.19; adjusted P=.021, NES 1.70; adjusted P=.021, NES 1.62; adjusted P=.037, and NES 1.52; adjusted P=.037, respectively). Immune-desert is related to upregulated MYC target V2 pathway (NES -1.95; adjusted P=.037). Inflamed group did not show significant difference in CD274 expression, compared with others (Inflamed vs. immune-excluded, 4.97 vs. 4.19, P=.115 and Inflamed vs. immune-desert, 4.97 vs. 3.95, P=.058). Inflamed group did not show any significant difference in overall survival, compared with non-inflamed group (Inflamed vs. non-inflamed, HR 0.98; 95% CI 0.45 - 2.14; P=.958). Conclusion: Deep learning-based H&E slide analyzer can be used to classify tumor H&E slide images with OV into three IPs. In this study, the classification demonstrated distinct immunologic traits and transcriptomic characteristics in tumor microenvironment. The enrichment of interferon gamma response pathway in inflamed OV group may indicate opportunities for targeted immunotherapy. Citation Format: Horyun Choi, Youjin Oh, Chan-Young Ock, Kyunghyun Paeng, Young Kwang Chae. Immune phenotypes classified by deep learning-based H&E tissue analyzer demonstrate distinct immune landscape and transcriptomic features in ovarian cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5446.

Crosstalk of RNA Adenosine Modification-Related Subtypes, Establishment of a Prognostic Model, and Immune Infiltration Characteristics in Ovarian Cancer.

BackgroundFour RNA adenosine modifications, including m6A, m1A, alternative polyadenylation, and adenosine-to-inosine RNA editing, have been identified as potentially valuable in influencing colorectal carcinogenesis, immune infiltration, and response to drug therapy. However, the regulatory mechanisms and clinical significance of these four RNA modifications in ovarian cancer (OC) remain unknown.MethodsWe comprehensively described the transcriptional and genetic modifications of 26 RNA modification “writers” in OC and assessed the expression patterns. We identified two RNA modification subtypes using an unsupervised clustering approach. Subsequently, using differentially expressed genes (DEGs) in both subtypes, we calculated RNA modification “writer” scores (RMW scores) to characterize the RNA modifications of single OC patients. RMW score-related gene expression was investigated by qRT-PCR. We explored the correlation between RMW score and clinical features, immune infiltration, and drug sensitivity. We drew a nomogram to more intuitively and accurately describe the application value of the RMW score.ResultsWe found that molecular alterations in “writers” are strongly related to prognostic and immune-infiltrating features in OC patients. We identified two different clusters of RNA modifications. According to the immune infiltration characteristics in the two RNA modification isoforms, cluster A and cluster B can correspond to “hot” and “cold” tumors, respectively. With the median RMW score, we classified the patients into high- and low-score subgroups. A low RMW score was associated with good patient prognosis and lower immune infiltration. In addition, a low RMW score equated with a higher cancer stem cell index and a lower tumor mutation burden, which to some extent affected the sensitivity of patients to therapeutic drugs. Seven RMW score-related gene expressions were investigated by qRT-PCR in three OC cell lines. Compared to previously known models, our established RMW score has higher accuracy in predicting patient survival.ConclusionA comprehensive analysis of four RNA modification patterns in OC reveals their potential value in OC prognosis, immune microenvironment, and drug sensitivity. These results could deepen our knowledge of RNA modification and yield fresh insights for new personalized therapeutic strategies.

The Comprehensive Analysis of Interferon-Related Prognostic Signature with regard to Immune Features in Ovarian Cancer.

Interferon plays an important role in immune response of ovarian cancer. However, the expression pattern of interferon in ovarian cancer remains unclear. This study is aimed at exploring the expression profile of interferon-relate genes and constructing an interferon-based prognostic signature in ovarian cancer. The ovarian cancer samples collected from TCGA database were viewed as the training set, and ovarian cancer samples collected from GEO datasets were used as the independent validation sets. Univariate Cox regression analysis and multivariate Cox regression analysis were used to construct interferon-related signature, which worked as independent prognostic factor. Bioinformatics based on David software, GSEA, and R software were used to investigate the relationship between immune status and the signature in ovarian cancer. The signature showed close correlation with the status for ovarian cancer immune microenvironment, which might provide the possibility for clinical targeted therapy.

Genomic characteristics of homologous recombination deficiency in ovarian cancer.

e17575 Background: HRD score correlates with sensitivity to PARP inhibitors (PARPi). BRCA1/2 mutations are well-known causes of HRD, but other genetic abnormalities of the homologous recombination repair (HRR) pathway could also cause HRD, although no consensus has been reached. We aimed to analyze HRD score and its relationship with genetic characteristics in ovarian cancer, particularly the HRR-related genes mutations. Methods: Matched tumor/normal DNA from Chinese patients with ovarian cancer (N = 181) were analyzed by Acornmed panel with 98 cancer-related genes. The HRD score is the sum of these scar signature scores, namely, the loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transitions (LST). HRR genes mutations and clinical outcomes from the TCGA cohort were included. Results: In our cohort, 44.2% patients exhibited HRR genes mutations, yielded an increment of 12.2% than BRCA mutants. The most frequently mutated HRR genes were BRCA1 (25.0%), BRCA2 (8.0%), CDK12 (4.0%), and RAD51D (4.0%). Chinese cohort contained frequently somatic mutation of HRR genes compared with TCGA cohort (22.7% vs 13.6%, p < 0.010). Germline mutations of HRR genes and non-HRR genes occurred in 21.5% and 2.8% of cases detected, respectively. HRD score in HRR-related genes wildtype was lower than tumors with BRCA1/2 mutation and HRR genes mutation without BRCA1/2 carriers (median HRD score 33, 72 and 64; p < 0.001). Interestingly, no difference was observed in HRD scores between patients with somatic BRCA-mut and germline- BRCA mutants. The median HRD score in our cohort was 65 (range from 0 to 96), and 58.6% patients were HRD-high with the cutoff of HRD score ≥ 42. The HRD-high patients covered 89.7% of the BRCA-positive cases, besides, approximately 77.3% of the BRCA-wt/HRR-mut patients also harbored high HRD scores. Six mutated genes were significantly different between HRD-high and HRD-low group. ARID1A was frequently mutated in patients with HRD-low, while significantly more mutations in TP53 were identified among HRD-high patients. Interestingly, in the TCGA cohort, patients with TP53-mut (p = 0.024) and individuals without ARID1A mutation (p < 0.001) had remarkably high survival rates, as compared with the rest of these patients.Furthermore, tumors with HRD-high had a bit higher TMB (median TMB 4.56 vs 2.91, p = 0.018). Conclusions: Our data suggest that HRR genes mutations strongly affect HRD score, which may increase the number of patients who may benefit from PARPi treatment, and combining gene mutations and HRD score could optimize prognosis stratification in ovarian cancer. In addition, the molecular features of HRD provide new opportunities to predict the tumor response to multiple treatments.

Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.

PurposeThe hypoxic microenvironment is involved in the tumorigenesis of ovarian cancer (OC). Therefore, we aim to develop a non-invasive radiogenomics approach to identify a hypoxia pattern with potential application in patient prognostication.MethodsSpecific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. Meanwhile, multiple hypoxia-related subtypes were identified by unsupervised consensus analysis and LASSO–Cox regression analysis. Subsequently, diversified bioinformatics algorithms were used to explore the immune microenvironment, prognosis, biological pathway alteration, and drug sensitivity among different subtypes. Finally, optimal radiogenomics biomarkers for predicting the risk status of patients were developed by machine learning algorithms.ResultsOne hundred forty sHRGs and three types of hypoxia-related subtypes were identified. Among them, hypoxia-cluster-B, gene-cluster-B, and high-risk subtypes had poor survival outcomes. The subtypes were closely related to each other, and hypoxia-cluster-B and gene-cluster-B had higher hypoxia risk scores. Notably, the low-risk subtype had an active immune microenvironment and may benefit from immunotherapy. Finally, a four-feature radiogenomics model was constructed to reveal hypoxia risk status, and the model achieved area under the curve (AUC) values of 0.900 and 0.703 for the training and testing cohorts, respectively.ConclusionAs a non-invasive approach, computed tomography-based radiogenomics biomarkers may enable the pretreatment prediction of the hypoxia pattern, prognosis, therapeutic effect, and immune microenvironment in patients with OC.

A Survey of the Awareness and Educational Needs of Nurses in Nagasaki Prefecture Regarding Hereditary Breast and Ovarian Cancer

The aim of this study was to evaluate the knowledge and educational needs with regard to hereditary breast and ovarian cancer among nurses working in breast cancer care in the Nagasaki Prefecture. In breast cancer care, the identification of patients at risk for hereditary breast and ovarian cancer is necessary for the implementation of genetic testing and counseling. Nurses should be involved in this process, since they play a crucial role in the care of patients with breast cancer. However, the knowledge regarding hereditary breast and ovarian cancer among nurses working in oncology care in Japan has not been assessed. The design of this study is cross-sectional design. We distributed 597 surveys to nurses working in breast cancer care. The surveys assessed the nurses’ demographic data, their current knowledge and practices regarding cancer genetics and hereditary breast and ovarian cancer, and their attitude and preferences regarding learning about the condition. We received 317 valid replies. Nurses had limited knowledge about hereditary breast and ovarian cancer characteristics: 41.6% reported that they do not know about the condition, whereas less than 10% knew its characteristics. However, nurses were aware of hereditary breast and ovarian cancer significance and were willing to learn about it: 91% wished to learn about the condition, and 88.6% wanted to participate in study group meetings. Further, nurses’ preferences regarding educational programs were clarified. Overall, our results show that educational programs should be implemented to advance nurses’ knowledge of hereditary breast and ovarian cancer characteristics.

HIF-1α Is a Rational Target for Future Ovarian Cancer Therapies.

Ovarian cancer is the eighth most commonly diagnosed cancer among women worldwide. Even with the development of novel drugs, nearly one-half of the patients with ovarian cancer die within five years of diagnosis. These situations indicate the need for novel therapeutic agents for ovarian cancer. Increasing evidence has shown that hypoxia-inducible factor-1α(HIF-1α) plays an important role in promoting malignant cell chemoresistance, tumour metastasis, angiogenesis, immunosuppression and intercellular interactions. The unique microenvironment, crosstalk and/or interaction between cells and other characteristics of ovarian cancer can influence therapeutic efficiency or promote the disease progression. Inhibition of the expression or activity of HIF-1α can directly or indirectly enhance the therapeutic responsiveness of tumour cells. Therefore, it is reasonable to consider HIF-1α as a potential therapeutic target for ovarian cancer. In this paper, we summarize the latest research on the role of HIF-1α and molecules which can inhibit HIF-1α expression directly or indirectly in ovarian cancer, and drug clinical trials about the HIF-1α inhibitors in ovarian cancer or other solid malignant tumours.

OVARIAN CANCER BURDEN IN GEORGIA

Goal 1. To determine the incidence and death rates and features of ovarian cancer in the female population of Georgia in 2015-2019 using standardized rates and to create epidemiological maps. 2. To study the risks of cancer progression, recurrence and metastasis in oncogynecologic patients in the posttreatment period. 3. Study of 3-year survival rates of ovarian cancer. 4. To determine the burden of gynecologic cancer in the female population . 5. To develop preventive recommendations for oncogynecology patient advocacy. METHODS The following gross and standardized rates were calculated: Crude Morbidity and Mortality Rate (CrudeRate); AgeSpecific Rate (Age-Specific Rate); Age-Standardized Rate (ASR); 95% confidence interval of Age-standardized Rate (95% CI ASR); Truncated Age Standardized Rate (TASR); 95% confidence interval of Truncated Age Standardized Rate (95% CI TASR); Age-Adjusted Rate (AAR); 95% confidence interval of age-adjusted rate (95% CI AAR); Standardized Rate Ratio (SRR); 95% confidence interval of standardized ratio ratios (95% CI SRR); Cumulative risk indicator (Cumulative Risk-CR , CR ,); 95% confidence interval of cumulative risk indicator (95% CI CR); Proportional Incidence 64 74 Ratio (PIR); 95% confidence interval of proportional incidence ratios (95% CI PIR); Standardized Incidence Ratio (SIR); 95% confidence interval of standardized incidence ratio (95% CI SIR). 3-year survival rates for ovarian cancer were studied using SPSS, Kaplan-Maier curves, and Cox multifactorial analysis were used. Disability-adjusted life years (DALYs) in patients with gynecologic cancer were studied. RESULTS 1. In the overall structure of cancer incidence in women, according to age standardized (ASR) rates per 100 000 women, in 2015-2019, the third most common site for gynecologic cancer in Georgia was cervical cancer (ASR = 13,4; 95% CI ASR = 12,8-14,1) , the fourth – uterine cancer (ASR = 11,3; 95% CI ASR = 10,8-11,9), and sixth - ovarian (ASR = 9,8; 95% CI ASR = 9,3-10.3) cancer. 2. In the overall structure of cancer incidence in women, by age-adjusted (AAR) rates per 100 000 women (Georgian Standard 2014), in 2015-2019, the fourth most common gynecologic cancer in Georgia was cervical cancer (AAR = 18,6; 95% CI AAR = 18,0-19,3), uterine cancer was the fifth (AAR = 18,5; 95% CI AAR = 18,0-19,1), and ovarian cancer the sixth (AAR = 15,1; 95% CI AAR = 14,6 -15 6). 3. In Georgia, the risks of recurrence and/or development of metastases and disease progression after the period of treatment and remission of cervical and uterine cancer are not statistically significantly different from each other (OR = 1,0, 95% CI OR = 0,7-1,4), while compared to the cervical and uterine cancer, the risk of ovarian cancer progression is 2,9 times higher (OR = 2,9, 95% CI OR = 2,1-3,9).The risk of recurrence and / or development of metastases and disease progression post-therapy and remission is 2,3 times higher for uterine cancer compared to cervical cancer in Tbilisi (OR = 2,3, 95% CI OR = 1,4-3,9). At the same time, compared to cervical and uterine cancers, the risk of ovarian cancer progression is 4,1 times and 1,8 times higher, respectively (OR = 4,1, 95% CI OR = 2,4-6,8; OR = 1 , 8, 95% CI OR = 1 2-2 7). 4. In Tbilisi (the capital city of Georgia), the 3-year survival rate of gynecologic cancer with Kaplan-Meyer curves averaged 70,5%. Better 3-year survival rates among gynecologic cancer localizations were observed in cases of uterine cancer (78,7%) and cervical cancer (75,2%). The 3-year survival rate for ovarian cancer was 55,2%. 5. According to the DALYs index of gynecologic cancer in Georgia and Tbilisi, 39 459,1 women/year were lost due to gynecologic cancer in Georgia in 2015-2019, each patient lost an average of 7,3 years, and in Tbilisi, respectively 11 521,3 women/year is lost, each patient lost an average of 5,8 years.

Comprehensive of N1-Methyladenosine Modifications Patterns and Immunological Characteristics in Ovarian Cancer.

Backgroundrecently, many researches have concentrated on the relevance between N1-methyladenosine (m1A) methylation modifications and tumor progression and prognosis. However, it remains unknown whether m1A modification has an effect in the prognosis of ovarian cancer (OC) and its immune infiltration.MethodsBased on 10 m1A modulators, we comprehensively assessed m1A modification patterns in 474 OC patients and linked them to TME immune infiltration characteristics. m1Ascore computed with principal component analysis algorithm was applied to quantify m1A modification pattern in OC patients. m1A regulators protein and mRNA expression were respectively obtained by HPA website and RT-PCR in clinical OC and normal samples.ResultsWe finally identified three different m1A modification patterns. The immune infiltration features of these m1A modification patterns correspond to three tumor immune phenotypes, including immune-desert, immune-inflamed and immune-excluded phenotypes. The results demonstrate individual tumor m1A modification patterns can predict patient survival, stage and grade. The m1Ascore was calculated to quantify individual OC patient’s m1A modification pattern. A high m1Ascore is usually accompanied by a better survival advantage and a lower mutational load. Research on m1Ascore in the treatment of OC patients showed that patients with high m1Ascore showed marked therapeutic benefits and clinical outcomes in terms of chemotherapy and immunotherapy. Lastly, we obtained four small molecule drugs that may potentially ameliorate prognosis.ConclusionThis research demonstrates that m1A methylation modification makes an essential function in the prognosis of OC and in shaping the immune microenvironment. Comprehensive evaluation of m1A modifications improves our knowledge of immune infiltration profile and provides a more efficient individualized immunotherapy strategy for OC patients.

Identification of CXCL10-Relevant Tumor Microenvironment Characterization and Clinical Outcome in Ovarian Cancer.

BackgroundChemokines are implicated in tumor microenvironment (TME) cell infiltration. Development of ovarian cancer involves heterologous cells together with the adjacent microenvironment. Nonetheless, our understanding of the chemokine-related TME characteristics in ovarian cancer remains obscure.MethodsIn this large-scale multi-platform study of 10 microarray datasets consisting of 1,673 ovarian cancer patients, we comprehensively evaluated CXCL10 and CXCL9 expression risk classifications for predicting overall survival (OS) and TME immune characteristics. The cross-validation between a standard cohort (TCGA: The Cancer Genome Atlas) and three test cohorts (GEO: Gene-Expression Omnibus) was applied. We investigated differences in the biological functions and the underlying mechanisms between high- and low-risk classifications.ResultsWe identified that evaluation of CXCL10 expression could predict the tumor development, immune cell infiltration, TME signature, genetic alteration, and patient prognosis in ovarian cancer. Low-risk classification was characterized by high CXCL10 expression and prolonged prognosis, which was positively associated with specific immune cell infiltration (i.e., T cells, DCs, aDC, and Th2 cells) and TME immune-relevant signatures. Meanwhile, the high-risk classification was defined by lower CXCL10/CXCL9 expression and relevant poor prognosis and immune infiltrations. The CXCL10-based low-risk classification was also linked to antitumor biological function of specific immune gene sets, such as IL2-STAT5 signaling. Additionally, a mutational pattern featured by enrichment of C > T transition was further identified to be associated with immune cell infiltration.ConclusionsThis work proposed a promising biomarker for evaluating TME immune characteristics and clinical outcomes in patients with ovarian cancer. Estimation of CXCL10 risk pattern sheds a novel insight on ovarian cancer TME immune characteristics and provides strategies for ovarian cancer immunotherapy.

Identification of 5-methylcytosine-related signature for predicting prognosis in ovarian cancer

BackgroundOvarian cancer is one of the most common malignancies often resulting in a poor prognosis. 5-methylcytosine (m5C) is a common epigenetic modification with roles in eukaryotes. However, the expression and function of m5C regulatory factors in ovarian cancer remained unclear.ResultsTwo molecular subtypes with different prognostic and clinicopathological features were identified based on m5C regulatory factors. Meanwhile, functional annotation showed that in the two subtypes, 452 differentially expressed genes were significantly related to the malignant progression of ovarian cancer. Subsequently, four m5C genes were screened to construct a risk marker predictive of overall survival and indicative of clinicopathological features of ovarian cancer, also the robustness of the risk marker was verified in external dataset and internal validation set. multifactorial cox regression analysis and nomogram demonstrated that risk score was an independent prognostic factor for ovarian cancer prognosis.ConclusionIn conclusion, our results revealed that m5C-related genes play a critical role in tumor progression in ovarian cancer. Further detection of m5C methylation could provide a novel targeted therapy for treating ovarian cancer.

Diagnostic Value of International Ovarian Tumor Analysis Simple Rules (IOTA-SR) In Iranian Patients with Ovarian Mass

Background: Among gynecologic malignancies, ovarian cancer has the highest mortality rate per case. The most important prognostic feature of ovarian cancer is an early diagnosis. The IOTA-SR is an ultrasound exam criterion for classifying benign or malignant ovarian tumors, which could be used effectively by an inexperienced radiologist. This study aimed to evaluate the diagnostic value of IOTA-SR in Iranian patients with ovarian tumors. Methods: In this cross-sectional study, considering inclusion and exclusion criteria, 60 females enrolled (from 2019-1 to 2019-12). Patients were evaluated with ultrasound by an experienced radiologist. Tumors were classified, as benign or malignant according to the IOTA-SR criteria. After laparotomy, histological and ultrasond examination findings were compared. Results: According to histopathologic results, the prevalence of malignancy was 63.3% (38 malignant and 22 benign tumors). The IOTA-SR could be applied in all the participants as 21 tumors (35%) were classified as benign and 39 (65%) as malignant. Compared with histopathologic results, the IOTA-SR yielded 36 true positives, three false positives, 19 true negatives, and two false negatives. Thus, assessing ovarian mass using IOTA-SR achieved a sensitivity of 94.7%, a specificity of 86.3%, a positive predictive value of 92.3%, a negative predictive value of 90.47%, positive likelihood ratio of 6.91, negative likelihood ratio of 0.091, overall accuracy of 91.6%, and kappa coefficient of 0.819 (P<0.001). Conclusions: IOTA-SR criteria have a high diagnostic value in differentiation of the malignant and benign ovarian tumors and can be applied in daily practice.

EIF4E Overexpression Is Associated with Poor Prognoses of Ovarian Cancer.

Aim Ovarian cancer is a common malignant tumor of the gynecological oncology worldwide, with a high incidence and mortality rate and poor prognosis. Searching for new diagnostic molecular biomarkers for ovarian cancer is extremely significant. Methods Here, we analyzed the expression rates of eIF4E and cyclin D1 proteins in 123 cases of cancer tissue samples and 38 cases of paracancerous tissue samples and studied the connection between the expression rates of eIF4E and cyclin D1 proteins by immunohistochemistry and statistically correlated with clinicopathological features in ovarian cancer. Results The results showed that the expression rates of eIF4E and cyclin D1 proteins in ovarian cancer tissues were significantly higher than those in noncancerous epithelial ovarian tissues (P = 0.001 and P = 0.032, respectively). Additionally, the results revealed that a higher expression rate of eIF4E (P = 0.008) was found in the advanced stage (stage III/IV), and also patients with cervical lymph node metastasis displayed higher expression of eIF4E (P < 0.001) and cyclin D1 (P = 0.033) than those without lymph node metastasis. Spearman's rank correlation test showed that there was a significant positive correlation between the eIF4E and cyclin D1 proteins in ovarian cancer. The Kaplan-Meier method showed that patients with lower expression of eIF4E had marginally better survival than those with high expression of eIF4E (P = 0.012). Multivariate Cox regression analysis further identified that positive expression of eIF4E was an independent prognostic factor. Conclusion In ovarian cancer, eIF4E might be a valuable biomarker to predict poor prognoses and a potential therapeutic target to develop valid treatment strategies.

Expression of ACAP1 Is Associated with Tumor Immune Infiltration and Clinical Outcome of Ovarian Cancer.

ADP-ribosylation factor (Arf) GTPase-activating protein (GAP) with coiled-coil, ankyrin repeat and PH domains 1 (ACAP1) is an Arf6 GAP that regulates membrane trafficking and is critical for the migratory potential of cells. However, the roles of ACAP1 have not been fully explored and its association with clinicopathological features in ovarian cancer is still unknown. In this study, we systematically analyzed multiple databases, including TISIDB, Tumor Immune Estimation Resource (TIMER2.0), Gene Expression Omnibus (GEO), CORTECON, Kaplan-Meier Plotter and LinkedOmics platforms to reveal the clinical significance and function of ACAP1 in ovarian cancer. We found that the expression of ACAP1 was upregulated in ovarian cancer and high ACAP1 expression predicted poor prognosis. Our data demonstrated that the expression and methylation status of ACAP1 were strongly correlated with immune infiltration levels, immunomodulators, and chemokines. Gene set enrichment analysis (GSEA) analysis also showed that the mechanism of ACAP1 in regulating ovarian cancer was related to a variety of immune-related pathways. In addition, we also revealed that the expression of ACAP1 was altered during cell differentiation and associated with cancer cell stemness markers. Our study highlights the clinical significance of ACAP1 in ovarian cancer and provides insight into the novel function of ACAP1 in regulation of tumor immune microenvironment and cancer cell stemness.

Prognostic impact of platinum sensitivity in ovarian carcinoma patients with brain metastasis

BackgroundBrain metastasis (BM) is a rare event in ovarian cancer patients. The current prognostic scores that have been used for other tumors do not account for specific characteristics of ovarian cancer, such as platinum sensitivity.MethodsThis retrospective cohort study examined patients with ovarian carcinoma and BM who were treated at a single institution from January 2007 to December 2017. Clinical data on the diagnosis of BM and follow-up were collected. Cox regression was used to evaluate prognostic factors for overall survival (OS).ResultsOf 560 patients, 26 presented with BM. Eight patients were treated with surgery, 15 with whole-brain radiotherapy (RT), and 5 with stereotactic RT, and 4 patients received systemic treatment at the diagnosis of BM. The median OS was 10.8 months. The following factors were associated with OS: platinum-sensitive recurrence (HR 0.34, 95% CI 0.12–0.99; p = 0.049), higher number of previous treatment lines (HR 1.57, 95% CI 1.12–2.19; p = 0.008), ECOG performance status (HR 2.52, 95% CI 1.24–5.09; p = 0.010), and longer interval from initial diagnosis to BM (p = 0.025). Notably, the number of brain metastasis, the largest tumor size, and progression outside of the CNS were not related to survival. Platinum sensitivity was not associated with any of the classic prognostic factors in brain metastasis patients such as number or size of brain metastasis or disease progression outside the CNS strengthening the hypothesis of the importance of platinum sensitivity to the prognosis of ovarian cancer patients with BM.ConclusionsThe factors related to the biological behavior of the ovarian cancer such as platinum sensitivity at the time of BM diagnosis, fewer number of previous treatment lines and interval from initial diagnosis were associated with survival in ovarian cancer patients with BM, while factors that are usually related to survival in BM in other cancers were not associated with survival in this cohort of ovarian cancer patients. The small number of patients did not allow us to exclude the prognostic role of these former factors that were not associated with survival in the present cohort.