Molecular classification of high grade endometrioid and clear cell ovarian cancer using TCGA gene expression signatures

Fertility-Sparing Surgery for Stage I Epithelial Ovarian Cancer

OBJECTIVE

To describe population-level utilization of fertility-sparing surgery and outcome of reproductive-aged patients with early epithelial ovarian cancer who underwent fertility-sparing surgery in the United States.

METHODS

This retrospective study queried the National Cancer Institute's Surveillance, Epidemiology, and End Result Program. The study included 3,027 patients younger than age 50 years with stage I epithelial ovarian cancer receiving primary surgical therapy from 2007 to 2020. Fertility-sparing surgery was defined as preservation of one ovary and the uterus for unilateral lesion and preservation of the uterus for bilateral lesions. Temporal trend of fertility-sparing surgery was assessed with linear segmented regression with log-transformation. Overall survival associated with fertility-sparing surgery was assessed with Cox proportional hazard regression model.

RESULTS

A total of 534 patients (17.6%) underwent fertility-sparing surgery. At the cohort level, the utilization of fertility-sparing surgery was 13.4% in 2007 and 21.8% in 2020 (P for trend=.009). Non-Hispanic White individuals (2.8-fold), those with high-grade serous histology (2.2-fold), and individuals with stage IC disease (2.3-fold) had a more than twofold increase in fertility-sparing surgery utilization during the study period (all P for trend<.05). After controlling for the measured clinicopathologic characteristics, patients who received fertility-sparing surgery had overall survival comparable with that of patients who had nonsparing surgery (5-year rates 93.6% vs 92.1%, adjusted hazard ratio 0.87, 95% CI, 0.57-1.35). This survival association was consistent in high-grade serous (5-year rates 92.9% vs 92.4%), low-grade serous (100% vs 92.2%), clear cell (97.5% vs 86.1%), mucinous (92.1% vs 86.6%), low-grade endometrioid (95.7% vs 97.7%), and mixed (93.3% vs 83.7%) histology (all P>.05). In high-grade endometrioid tumor, fertility-sparing surgery was associated with decreased overall survival (5-year rates 71.9% vs 93.8%, adjusted hazard ratio 2.90, 95% CI, 1.09-7.67). Among bilateral ovarian lesions, fertility-sparing surgery was not associated with overall survival (5-year rates 95.8% vs 92.5%, P=.364). Among 41,914 patients who had epithelial ovarian cancer with any age and stage, those younger than age 50 years with stage I disease increased from 8.6% to 10.9% during the study period (P for trend=.002).

CONCLUSION

Nearly one in five reproductive-aged patients with stage I epithelial ovarian cancer underwent fertility-sparing surgery in recent years in the United States. More than 90% of reproductive-aged patients with stage I epithelial ovarian cancer who underwent fertility-sparing surgery were alive at the 5-year timepoint, except for those with high-grade endometrioid tumors.

Machine learning-derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer

Clinical assessments relying on pathology classification demonstrate limited effectiveness in predicting clinical outcomes and providing optimal treatment for patients with ovarian cancer (OV). Consequently, there is an urgent requirement for an ideal biomarker to facilitate precision medicine. To address this issue, we selected 15 multicentre cohorts, comprising 12 OV cohorts and 3 immunotherapy cohorts. Initially, we identified a set of robust prognostic risk genes using data from the 12 OV cohorts. Subsequently, we employed a consensus cluster analysis to identify distinct clusters based on the expression profiles of the risk genes. Finally, a machine learning-derived prognostic signature (MLDPS) was developed based on differentially expressed genes and univariate Cox regression genes between the clusters by using 10 machine-learning algorithms (101 combinations). Patients with high MLDPS had unfavourable survival rates and have good prediction performance in all cohorts and in-house cohorts. The MLDPS exhibited robust and dramatically superior capability than 21 published signatures. Of note, low MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells. Additionally, patients suffering from OV with low MLDIS were more sensitive to immunotherapy. Meanwhile, patients with low MLDIS might benefit from chemotherapy, and 19 compounds that may be potential agents for patients with low MLDIS were identified. MLDIS presents an appealing instrument for the identification of patients at high/low risk. This could enhance the precision treatment, ultimately guiding the clinical management of OV.

LCK facilitates DNA damage repair by stabilizing RAD51 and BRCA1 in the nucleus of chemoresistant ovarian cancer

Poly-ADP Ribose Polymerase (PARP) targeted therapy is clinically approved for the treatment of homologous recombination (HR) repair deficient tumors. The remarkable success of this therapy in the treatment of HR repair deficient cancers has not translated to HR-proficient cancers. Our studies identify the novel role of non-receptor lymphocyte-specific protein tyrosine kinase (LCK) in the regulation of HR repair in endometrioid epithelial ovarian cancer (eEOC) model. We show that DNA damage leads to direct interaction of LCK with the HR repair proteins RAD51 and BRCA1 in a kinase dependent manner RAD51 and BRCA1 stabilization. LCK expression is induced and activated in the nucleus in response to DNA damage insult. Disruption of LCK expression attenuates RAD51, BRCA1, and BRCA2 protein expression by hampering there stability and results in inhibition of HR-mediated DNA repair including suppression of RAD51 foci formation, and augmentation of γH2AX foci formation. In contrast LCK overexpression leads to increased RAD51 and BRCA1 expression with a concomitant increase in HR DNA damage repair. Importantly, attenuation of LCK sensitizes HR-proficient eEOC cells to PARP inhibitor in cells and pre-clinical mouse studies. Collectively, our findings identify a novel therapeutic strategy to expand the utility of PARP targeted therapy in HR proficient ovarian cancer.

Clinical, pathological, and comprehensive molecular analysis of the uterine clear cell carcinoma: a retrospective national study from TMRG and GINECO network

BACKGROUND

Uterine clear cell carcinomas (CCC) represent less than 5% of uterine cancers. Their biological characteristics and clinical management remain uncertain. A multicenter study to explore both clinical and molecular features of these rare tumors was conducted.

METHODS

This multicenter retrospective national study was performed within the French TMRG (Rare Gynecologic Malignant Tumors) network. Clinical data and, when available, FFPE blocks were collected. Clinical features, treatments, and outcome (progression-free survival (PFS) and overall survival (OS)) were analyzed and correlated to the protein (tissue micro-array), RNA (Nanostring nCounter® technology), and DNA (array-Comparative Genomic hybridization and target-next generation sequencing) levels using the tumor samples available.

RESULTS

Sixty-eight patients with uterine CCC were enrolled, 61 from endometrial localization and 5 with cervix localization. Median age at diagnosis was 68.9 years old (range 19-89.7). Most tumors were diagnosed at an early stage (78% FIGO stage I-II). Hysterectomy (performed in 90%) and lymph node dissection (80%) were the most frequent surgical treatment. More than 70% of patients received external beam radiotherapy and 57% received brachytherapy. Nearly half (46%) of the patients received chemotherapy. After a median follow-up of 24.7 months, median PFS was 64.8 months (95 CI [5.3-124.4]) and median OS was 79.7 (IC95 [31.0-128.4]). Low hormone receptor expression (13% estrogen-receptor positive), frequent PI3K pathway alterations (58% PTEN loss, 50% PIK3CA mutations), and P53 abnormalities (41%) were observed. Mismatch repair deficiency was identified in 20%. P16 expression was associated with shorter PFS (HR = 5.88, 95 CI [1.56-25], p = 0.009). Transcriptomic analyzes revealed a specific transcriptomic profile notably with a high expression of immune response-associated genes in uterine CCC displaying a very good overall prognosis.

CONCLUSIONS

Uterine CCC reported to be potentially MSI high, hormone receptors negative, and sometimes TP53 mutated. However, some patients with immune response-associated features and better prognosis may be candidate to treatment de-escalation and immunotherapy.

A comprehensive molecular analysis of 113 primary ovarian clear cell carcinomas reveals common therapeutically significant aberrations

BACKGROUND

Molecular aberrations occurring in primary ovarian clear cell carcinoma (OCCC) can be of diagnostic, predictive, and prognostic significance. However, a complex molecular study including genomic and transcriptomic analysis of large number of OCCC has been lacking.

METHODS

113 pathologically confirmed primary OCCCs were analyzed using capture DNA NGS (100 cases; 727 solid cancer related genes) and RNA-Seq (105 cases; 147 genes) in order to describe spectra and frequency of genomic and transcriptomic alterations, as well as their prognostic and predictive significance.

RESULTS

The most frequent mutations were detected in genes ARID1A, PIK3CA, TERTp, KRAS, TP53, ATM, PPP2R1A, NF1, PTEN, and POLE (51,47,27,18,13,10,7,6,6, and 4%, respectively). TMB-High cases were detected in 9% of cases. Cases with POLE^mut and/or MSI-High had better relapse-free survival. RNA-Seq revealed gene fusions in 14/105 (13%) cases, and heterogeneous expression pattern. The majority of gene fusions affected tyrosine kinase receptors (6/14; four of those were MET fusions) or DNA repair genes (2/14). Based on the mRNA expression pattern, a cluster of 12 OCCCs characterized by overexpression of tyrosine kinase receptors (TKRs) AKT3, CTNNB1, DDR2, JAK2, KIT, or PDGFRA (p < 0.00001) was identified.

CONCLUSIONS

The current work has elucidated the complex genomic and transcriptomic molecular hallmarks of primary OCCCs. Our results confirmed the favorable outcomes of POLE^mut and MSI-High OCCC. Moreover, the molecular landscape of OCCC revealed several potential therapeutical targets. Molecular testing can provide the potential for targeted therapy in patients with recurrent or metastatic tumors.

Impact of the number of cycles of platinum-based chemotherapy for early stage ovarian clear cell carcinoma on survival: a retrospective study

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a unique subtype of ovarian epithelial ovarian cancer. The number of chemotherapy cycles for early-stage patients is still debated. This study aimed to evaluate whether at least 4 cycles of adjuvant platinum-based chemotherapy have better prognostic value than 1-3 cycles in early-stage OCCC.

METHODS

We retrospectively retrieved data from 102 patients with stage I-IIA OCCC between 2008 and 2017. All patients underwent complete surgical staging followed by adjuvant platinum-based chemotherapy. Kaplan-Meier curves and Multivariate Cox analysis were performed to estimate 5-year overall survival (OS) and progression-free (PFS) according to the number of chemotherapy cycles.

RESULTS

Among stage I-IIA disease, twenty (19.6%) patients received 1-3 cycles, and eighty-two (80.4%) patients received at least 4 cycles of adjuvant chemotherapy. Univariate analysis revealed that the patients in 1-3cycles group had not significantly improved 5-year OS and PFS than those in the ≥ 4 cycles group (5-year OS: hazard ratio [HR] 1.21; 95% confidence interval [CI] 0.25- 5.78, p = 0.1), and 5-year PFS: HR 0.79; 95% CI 0.26- 2.34, p = 0.1). In the multivariate analysis, there was no impact of 1-3 versus ≥ 4 cycles of chemotherapy on 5-year OS (HR 1.21, 95% CI 0.25-3.89, p = 0.8) or 5-year PFS (HR 0.94, 95% CI 0.32-2.71, p = 0.9). The potential independent risk factors associated with 5-year OS and PFS included the surgery approach and FIGO stage.

CONCLUSION

The number of cycles of platinum-based chemotherapy could not be associated with a survival benefit for patients with early-stage OCCC.

CD8 + T cell infiltration is associated with improved survival and negatively correlates with hypoxia in clear cell ovarian cancer

Unlike other histological types of epithelial ovarian carcinoma, clear cell ovarian carcinoma (CCOC) has poor response to therapy. In many other carcinomas, expression of the hypoxia-related enzyme Carbonic anhydrase IX (CAIX) by cancer cells is associated with poor prognosis, while the presence of CD8 + tumor-infiltrating lymphocytes (TIL) is positively prognostic. We employed [¹⁸F]EF5-PET/CT imaging, transcriptome profiling, and spatially-resolved histological analysis to evaluate relationships between CAIX, CD8, and survival in CCOC. Tissue microarrays (TMAs) were evaluated for 218 cases in the Canadian COEUR study. Non-spatial relationships between CAIX and CD8 were investigated using Spearman rank correlation, negative binomial regression and gene set enrichment analysis. Spatial relationships at the cell level were investigated using the cross K-function. Survival analysis was used to assess the relationship of CAIX and CD8 with patient survival for 154 cases. CD8 + T cell infiltration positively predicted survival with estimated hazard ratio 0.974 (95% CI 0.950, 1000). The negative binomial regression analysis found a strong TMA effect (p-value < 0.0001). It also indicated a negative association between CD8 and CAIX overall (p-value = 0.0171) and in stroma (p-value = 0.0050) but not in tumor (p-value = 0.173). Examination of the spatial association between the locations of CD8 + T cells and CAIX cells found a significant amount of heterogeneity in the first TMA, while in the second TMA there was a clear signal indicating negative spatial association in stromal regions. These results suggest that hypoxia may contribute to immune exclusion, primarily mediated by effects in stroma.

Ovarian clear cell carcinoma with or without endometriosis origin in a single institution cohort

BACKGROUND

As ovarian clear cell carcinoma (OCCC) has distinct clinical features, biology, genetic characteristics and mechanisms of pathogenesis, and whether the origin of endometriosis or not affects the prognosis of OCCC remains controversial.

METHODS

We retrospectively collected medical records and follow-up data of patients with OCCC treated at the Obstetrics and Gynecology Hospital of Fudan University from January 2009 to December 2019. Further, we divided patients into 2 groups. Group 1: non-endometriosis origin; Group 2: endometriosis origin. Clinicopathological characteristics and survival outcomes were compared between the 2 groups.

RESULTS

A total of one hundred and twenty-five patients with ovarian clear cell carcinoma were identified and included. In the overall patients' population, the 5 year overall survival was 84.8%, the mean overall survival was 85.9 months. The results of the stratified analysis showed that early stage (FIGO stage I/II) OCCC had a good prognosis. The results of univariate analyses indicated that a statistically significant relationship between overall survival (OS) and FIGO stage, lymph node metastasis, peritoneum metastasis, chemotherapy administration methods, Chinese herbal treatment, molecular target therapy. As for progression-free survival (PFS), a significant relationship between PFS and child-bearing history, largest residual tumor size, FIGO stage, tumor maximum diameter, lymph node metastasis was found, respectively. FIGO stage and lymph node metastasis are common poor prognostic factors affecting OS and PFS. The multivariate regression analysis revealed that FIGO stage (p = 0.028; HR, 1.944; 95% CI 1.073-3.52) and treatment by Chinese herbs (p = 0.018; HR, 0.141; 95% CI 0.028-0.716) were identified as influencing factors with regard to survival. The presence or absence of lymphadenectomy did not affect OS of 125 OCCC patients (p = 0.851; HR, 0.825; 95% CI 0.111-6.153). There was a trend towards a better prognosis for patients with OCCC of endometriosis origin than those with OCCC of non-endometriosis origin (p = 0.062; HR, 0.432; 95% CI 0.179-1.045). The two groups differed with respect to several clinicopathological factors. And the proportion of patients with disease relapse was higher in Group 1 (46.9%) than in Group 2 (25.0%), with a statistically significant difference (p = 0.048).

CONCLUSIONS

Surgical staging and treatment by Chinese herbs postoperatively are two independent prognostic factors affecting the OS of OCCC, early detection and Chinese herbal medicine combined with chemotherapy postoperatively may be a good choice. Tumor with endometriosis-origin was found less likely to relapse. While the non-necessity of lymphadenectomy in advanced ovarian cancer has been proven, the need for lymphadenectomy in the early stage ovarian cancer, including early stage OCCC, still deserved to be explored.

Targeting ATP Synthase by Bedaquiline as a Therapeutic Strategy to Sensitize Ovarian Cancer to Cisplatin

Cisplatin is a common chemotherapeutic drug for treating ovarian cancer, but its clinical efficacy is hampered by intrinsic and acquired resistance. Previous studies had shown inhibiting oxidative phosphorylation overcomes cisplatin resistance in ovarian cancer. Studies reveal that bedaquiline, a clinically available antimicrobial drug, inhibits cancer via targeting mitochondria. This study systematically assessed the efficacy of bedaquiline in ovarian cancer and its underlying mechanism. Using a panel of ovarian cancer cell lines and normal ovary cells, we demonstrated bedaquiline is selective for anti-ovarian cancer activities. Furthermore, the sensitivity varied among different ovarian cancer cell lines regardless of their sensitivity to cisplatin. Bedaquiline inhibited growth, survival and migration, through decreasing levels of ATP synthase subunit, complex V activity, mitochondrial respiration and ATP. We further found that ovarian cancer displayed increased levels of ATP, oxygen consumption rate (OCR), complex V activity and ATP synthase subunits compared to normal counterpart. Combination index analysis showed that bedaquiline and cisplatin is synergistic. Bedaquiline remarkably enhanced the efficacy of cisplatin in inhibiting ovarian cancer growth in mice. Our study provides evidence to repurpose bedaquiline for ovarian cancer treatment and suggests that ATP synthase is a selective target to overcome cisplatin resistance in ovarian cancer.

Poor-prognosis molecular subtypes in adenocarcinomas of pancreato-biliary and gynecological origin: A systematic review

Pancreato-biliary and gynecological adenocarcinomas need better tools to predict clinical outcome. Potential prognostic mesenchymal(-like) transcriptome-based subtypes have been identified in these cancers. In this systematic review, we include studies into molecular subtyping and summarize biological and clinical features of the subtypes within and across sites of origin, searching for suggestions to improve classification and prognostication. PubMed and Embase were searched for original research articles describing potential mesenchymal(-like) mRNA-based subtypes in pancreato-biliary or gynecological adenocarcinomas. Studies limited to supervised clustering were excluded. Fourty-four studies, discussing cholangiocarcinomas, gallbladder, ampullary, pancreatic, ovarian, and endometrial adenocarcinomas were included. There was overlap in molecular and clinical features in mesenchymal(-like) subtypes across all adenocarcinomas. Approaches including microdissection were more likely to identify prognosis-associating subtypes. To conclude, molecular subtypes in pancreato-biliary and gynecological adenocarcinomas share biological and clinical characteristics. Furthermore, separation of stromal and epithelial signals should be applied in future studies into biliary and gynecological adenocarcinomas.

Identification of the Subtypes of Renal Ischemia-Reperfusion Injury Based on Pyroptosis-Related Genes

Ischemia-reperfusion injury (IRI) often occurs in the process of kidney transplantation, which significantly impacts the subsequent treatment and prognosis of patients. The prognosis of patients with different subtypes of IRI is quite different. Therefore, in this paper, the gene expression data of multiple IRI samples were downloaded from the GEO database, and a double Laplacian orthogonal non-negative matrix factorization (DL-ONMF) algorithm was proposed to classify them. In this algorithm, various regularization constraints are added based on the non-negative matrix factorization algorithm, and the prior information is fused into the algorithm from different perspectives. The connectivity information between different samples and features is added to the algorithm by Laplacian regularization constraints on samples and features. In addition, orthogonality constraints on the basis matrix and coefficient matrix obtained by the algorithm decomposition are added to reduce the influence of redundant samples and redundant features on the results. Based on the DL-ONMF algorithm for clustering, two PRGs-related IRI isoforms were obtained in this paper. The results of immunoassays showed that the immune microenvironment was different among PRGS-related IRI types. Based on the differentially expressed PRGs between subtypes, we used LASSO and SVM-RFE algorithms to construct a diagnostic model related to renal transplantation. ROC analysis showed that the diagnostic model could predict the outcome of renal transplant patients with high accuracy. In conclusion, this paper presents an algorithm, DL-ONMF, which can identify subtypes with different disease characteristics. Comprehensive bioinformatic analysis showed that pyroptosis might affect the outcome of kidney transplantation by participating in the immune response of IRI.

Single-cell transcriptomic analysis of endometriosis

Endometriosis is a common condition in women that causes chronic pain and infertility and is associated with an elevated risk of ovarian cancer. We profiled transcriptomes of >370,000 individual cells from endometriomas (n = 8), endometriosis (n = 28), eutopic endometrium (n = 10), unaffected ovary (n = 4) and endometriosis-free peritoneum (n = 4), generating a cellular atlas of endometrial-type epithelial cells, stromal cells and microenvironmental cell populations across tissue sites. Cellular and molecular signatures of endometrial-type epithelium and stroma differed across tissue types, suggesting a role for cellular restructuring and transcriptional reprogramming in the disease. Epithelium, stroma and proximal mesothelial cells of endometriomas showed dysregulation of pro-inflammatory pathways and upregulation of complement proteins. Somatic ARID1A mutation in epithelial cells was associated with upregulation of pro-angiogenic and pro-lymphangiogenic factors and remodeling of the endothelial cell compartment, with enrichment of lymphatic endothelial cells. Finally, signatures of ciliated epithelial cells were enriched in ovarian cancers, reinforcing epidemiologic associations between these two diseases.

Integrative genomic and transcriptomic analysis reveals immune subtypes and prognostic markers in ovarian clear cell carcinoma

Background

We performed an integrative genomic and transcriptomic profiling to identify molecular subtypes and prognostic markers with special focus on immune-related pathways.

Methods

Totally, 50 Chinese patients were subjected to targeted next-generation sequencing and transcriptomic sequencing.

Results

Two distinct subgroups were identified as immune (22.0%) and non-immune (78.0%) based on the immune-pathway related hierarchical clustering. Surprisingly, patients with immune subtype had a significantly worse survival. The prognostic capacity was validated in external cohorts. The immune group had higher expression of genes involved in pro-inflammation and checkpoints. PD-1 signalling pathway was enriched in the immune subtype. Besides, the immune cluster presented enriched expression of genes involved in epithelial-mesenchymal transition, angiogenesis and PI3K-AKT-mTOR signalling, while the non-immune subtype had higher expression of metabolic pathways. The immune subtype had a higher mutation rate of PIK3CA though significance was not achieved. Lastly, we established a prognostic immune signature for overall survival. Interestingly, the immune signature could also be applied to renal clear cell carcinoma, but not to other histologic subtype of ovarian cancer.

Conclusions

An immune subtype of OCCC was identified with poor survival and enrichment of PD-1 and PI3K-AKT-mTOR signalling. We constructed and validated a robust prognostic immune signature of OCCC patients.

OSov: An Interactive Web Server to Evaluate Prognostic Biomarkers for Ovarian Cancer

Simple Summary

The OSov web server incorporates gene expression profiles with clinical risk factors to estimate the ovarian cancers patients’ survival, and provides a tool for multiple analysis, such as forest-plot, uni/multi-variate survival analysis, Kaplan-Meier plot and nomogram construction.

Abstract

Ovarian cancer is one of the most aggressive and highly lethal gynecological cancers. The purpose of our study is to build a free prognostic web server to help researchers discover potential prognostic biomarkers by integrating gene expression profiling data and clinical follow-up information of ovarian cancer. We construct a prognostic web server OSov (Online consensus Survival analysis for Ovarian cancer) based on RNA expression profiles. OSov is a user-friendly web server which could present a Kaplan–Meier plot, forest plot, nomogram and survival summary table of queried genes in each individual cohort to evaluate the prognostic potency of each queried gene. To assess the performance of OSov web server, 163 previously published prognostic biomarkers of ovarian cancer were tested and 72% of them had their prognostic values confirmed in OSov. It is a free and valuable prognostic web server to screen and assess survival-associated biomarkers for ovarian cancer.

Gene Expression Subtyping Reveals Immune alterations:TCGA Database for Prognosis in Ovarian Serous Cystadenocarcinoma

Serous ovarian cancer is the most common and primary death type in ovarian cancer. In recent studies, tumor microenvironment and tumor immune infiltration significantly affect the prognosis of ovarian cancer. This study analyzed the four gene expression types of ovarian cancer in TCGA database to extract differentially expressed genes and verify the prognostic significance. Meanwhile, functional enrichment and protein interaction network analysis exposed that these genes were related to immune response and immune infiltration. Subsequently, we proved these prognostic genes in an independent data set from the GEO database. Finally, multivariate cox regression analysis revealed the prognostic significance of TAP1 and CXCL13. The genetic alteration and interaction network of these two genes were shown. Then, we established a nomogram model related to the two genes and clinical risk factors. This model performed well in Calibration plot and Decision Curve Analysis. In conclusion, we have obtained a list of genes related to the immune microenvironment with a better prognosis for serous ovarian cancer, and based on this, we have tried to establish a clinical prognosis model.

Histological patterns and intra-tumor heterogeneity as prognostication tools in high grade serous ovarian cancers

OBJECTIVE

High grade serous ovarian carcinoma (HGSOC) is the most common type of malignant ovarian neoplasm and the main cause of ovarian cancer related deaths worldwide. Although novel biomarkers such as homologous recombination deficiency testing have been implemented into the clinical decision-making algorithm since diagnosis, morphological classification and immunohistochemistry analysis are essential for diagnostic purpose. This study aims at identifying histologic and clinical features that can be predictive of patients' prognosis.

METHODS

Morphological and architectural characterization including SET (Solid-Endometroid-Transitional)/Classic features was carried out in a cohort of 234 patients analyzing 695 slides. From each slide tumor infiltrating lymphocyte (TILs), the presence of necrosis, the number of mitoses, the presence of psammoma bodies, giant cells and atypical mitoses were recorded. Morphological heterogeneity was quantified by the Shannon's diversity index (SDI) considering the percentage of each architectural pattern per patient's slide.

RESULTS

The frequency of architectural patterns and morphological variables varied with respect of the surgical strategy (primary debulking surgery vs interval surgery after neoadjuvant chemotherapy). HGSOCs exhibiting SET features had a longer overall as well as progression free survival. Among SET features, pseudo-endometrioid and transitional like patterns had the best outcome, while it was heterogenous for solid pattern, that had better outcome for BRCA 1 negative and less heterogeneous tumors. In patients submitted to neoadjuvant chemotherapy a higher intratumor heterogeneity as defined by SDI was a negative independent prognostic factor.

CONCLUSIONS

A comprehensive histological examination considering architectural patterns and their heterogeneity can help in prognostication of HGSOCs.

Multiomics analysis identifies key genes and pathways related to N6-methyladenosine RNA modification in ovarian cancer

Aims: To explore the pathways and target genes related to N6-methyladenosine (m⁶A) methylation in ovarian cancer and their effect on patient prognosis. Methods & materials: The Cancer Genome Atlas was used to screen genes related to m⁶A regulators in terms of gene expression, mutation and copy number variation. These genes were subjected to pathway enrichment analysis. Prognosis-related genes were screened and involved in risk signature construction. Immunohistochemistry was used for verification. Results: We obtained 1408 genes dysregulated in parallel to m⁶A regulators, which were mainly involved in the platelet activation pathway. The m⁶A-related signature was constructed based on the expression of four prognosis-related genes (RPS6KA2, JUNB, HNF4A and P2RX1). Conclusion: This work provides new insights into the mechanism of m⁶A methylation in ovarian cancer.

Radiogenomics of gastroenterological cancer: The dawn of personalized medicine with artificial intelligence-based image analysis

Radiogenomics is a new field of medical science that integrates two omics, radiomics and genomics, and may bring a major paradigm shift in traditional personalized medicine strategies that require tumor tissue samples. In addition, the acquisition of the data does not require special imaging equipment or special imaging conditions, and it is possible to use image information from computed tomography, magnetic resonance imaging, positron emission tomography-computed tomography in clinical practice, so the versatility and cost-effectiveness of radiogenomics are expected. So far, the field of radiogenomics has developed, especially in the fields of brain tumors and breast cancer, but recently, reports of radiogenomic research on gastroenterological cancer are increasing. This review provides an overview of radiogenomic research methods and summarizes the current radiogenomic research in gastroenterological cancer. In addition, the application of artificial intelligence is considered to be indispensable for the integrated analysis of enormous omics information in the future, and the future direction of this research, including the latest technologies, will be discussed.

A Review of the Clinical Characteristics and Novel Molecular Subtypes of Endometrioid Ovarian Cancer

Ovarian cancer is one of the most common gynecologic cancers that has the highest mortality rate. Endometrioid ovarian cancer, a distinct subtype of epithelial ovarian cancer, is associated with endometriosis and Lynch syndrome, and is often accompanied by synchronous endometrial carcinoma. In recent years, dysbiosis of the microbiota within the female reproductive tract has been suggested to be involved in the pathogenesis of endometrial cancer and ovarian cancer, with some specific pathogens exhibiting oncogenic having been found to contribute to cancer development. It has been shown that dysregulation of the microenvironment and accumulation of mutations are stimulatory factors in the progression of endometrioid ovarian carcinoma. This would be a potential therapeutic target in the future. Simultaneously, multiple studies have demonstrated the role of four molecular subtypes of endometrioid ovarian cancer, which are of particular importance in the prediction of prognosis. This literature review aims to compile the potential mechanisms of endometrioid ovarian cancer, molecular characteristics, and molecular pathological types that could potentially play a role in the prediction of prognosis, and the novel therapeutic strategies, providing some guidance for the stratified management of ovarian cancer.

Combination of gene set signatures correlates with response to nivolumab in platinum-resistant ovarian cancer

Based on our previous phase II clinical trial of anti-programmed death-1 (PD-1) antibody nivolumab for platinum-resistant ovarian cancer (n = 19, UMIN000005714), we aimed to identify the biomarkers predictive of response. Tumor gene expression was evaluated by proliferative, mesenchymal, differentiated, and immunoreactive gene signatures derived from high-grade serous carcinomas and a signature established prior for ovarian clear cell carcinoma. Resulting signature scores were statistically assessed with both univariate and multivariate approaches for correlation to clinical response. Analyses were performed to identify pathways differentially expressed by either the complete response (CR) or progressive disease (PD) patient groups. The clear cell gene signature was scored significantly higher in the CR group, and the proliferative gene signature had significantly higher scores in the PD group where nivolumab was not effective (respective p values 0.005 and 0.026). Combinations of gene signatures improved correlation with response, where a visual projection of immunoreactive, proliferative, and clear cell signatures differentiated clinical response. An applicable clinical response prediction formula was derived. Ovarian cancer-specific gene signatures and related pathway scores provide a robust preliminary indicator for ovarian cancer patients prior to anti-PD-1 therapy decisions.

Gene expression profile association with poor prognosis in epithelial ovarian cancer patients

Ovarian cancer (OC) is the eighth most common type of cancer for women worldwide. The current diagnostic and prognostic routine available for OC management either lack specificity or are very costly. Gene expression profiling has shown to be a very effective tool in exploring new molecular markers for patients with OC, although association of such markers with patient survival and clinical outcome is still elusive. Here, we performed gene expression profiling of different subtypes of OC to evaluate its association with patient overall survival (OS) and aggressive forms of the disease. By global mRNA microarray profiling in a total of 196 epithelial OC patients (161 serous, 15 endometrioid, 11 mucinous, and 9 clear cell carcinomas), we found four candidates-HSPA1A, CD99, RAB3A and POM121L9P, which associated with OS and poor clinicopathological features. The overexpression of all combined was correlated with shorter OS and progression-free survival (PFS). Furthermore, the combination of at least two markers were further associated with advanced grade, chemotherapy resistance, and progressive disease. These results indicate that a panel comprised of a few predictors that associates with a more aggressive form of OC may be clinically relevant, presenting a better performance than one marker alone.

Updates of Pathogenesis, Diagnostic and Therapeutic Perspectives for Ovarian Clear Cell Carcinoma

Ovarian clear cell carcinoma (OCCC) is a special pathological type of epithelial ovarian carcinoma (EOC) and has a high prevalence in Asia without specific molecular subtype classification. Endometriosis is a recognized precancerous lesion that carries 3-fold increased risk of OCCC. Ovarian endometrioid carcinoma, which also originates from endometriosis, shares several features with OCCC, including platinum resistance and younger age at diagnosis. Patients with OCCC have about a 2.5 to 4 times greater risk of having a venous thromboembolism (VTE) compared with other EOC, and OCCC tends to metastasize through lymphatic vesicular and peritoneal spread as opposed to hematogenous metastasis. There is only mild elevation of the conventional biomarker CA125. Staging surgery or optimal cytoreduction combined with chemotherapy is a common therapeutic strategy for OCCC. However, platinum resistance commonly portends a poor prognosis, so novel treatments are urgently needed. Targeted therapy and immunotherapy are currently being studied, including PARP, EZH2, and ATR inhibitors combined with the synthetic lethality of ARID1A-dificiency, and MAPK/PI3K/HER2, VEGF/bFGF/PDGF, HNF1β, and PD-1/PD-L1 inhibitors. Advanced stage, suboptimal cytoreduction, platinum resistance, lymph node metastasis, and VTE are major prognostic predictors for OCCC. We focus on update pathogenesis, diagnostic methods and therapeutic approaches to provide future directions for clinical diagnosis and treatment of OCCC.

Increased Expression of UBE2T Predicting Poor Survival of Epithelial Ovarian Cancer: Based on Comprehensive Analysis of UBE2s, Clinical Samples, and the GEO Database

Ubiquitin-conjugating enzymes E2 (UBE2) have been reported in the microenvironment of various malignant tumors, but their correlation with ovarian cancer (OC) remains elusive. This study aimed to systematically analyze the expression patterns, prognostic value, genetic variation, and biological functions of 12 members of the UBE2 gene family in OC through the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, cBioPortal, and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) databases, respectively. We found that the mRNA levels of UBE2C, UBE2N, UBE2S, and UBE2T were significantly upregulated in OC compared with those in normal ovarian tissue. In patients with serous ovarian cancer (SOC), UBE2A, UBE2B, UBE2C, UBE2G, UBE2R2, and UBE2T upregulation were associated with poor overall survival. Moreover, UBE2A, UBE2N, UBE2R2, and UBE2T upregulation and UBE2G downregulation were associated with poor progression-free survival. UBE2T exhibited a strong correlation with OC and was thus further examined. We found that UBE2T has a high diagnostic accuracy (area under the receiver operating characteristic curve = 0.969) in epithelial ovarian cancer (EOC). Immunohistochemical assays and the Gene Expression Omnibus (GEO) database revealed that UBE2T was significantly upregulated in EOC compared with that in borderline tumors, benign tumors, and normal ovarian tissues, and its high expression was associated with poor prognosis. The Cox model showed that UBE2T upregulation was an independent risk factor affecting the prognosis of EOC and SOC. Furthermore, UBE2T was associated with specific immune cells and was mainly involved in cell cycle-related events. Genomic analysis showed that TP53 and TTN mutations were associated with UBE2T expression. Gene copy number amplification and hypomethylation may be responsible for UBE2T upregulation in OC. In conclusion, UBE2 family members may play a role in the development of OC. Specifically, UBE2T could serve as a new prognostic marker and therapeutic target for this disease. (IRB Approval No. 2020PS533K).

Noncoding RNA (ncRNA) Profile Association with Patient Outcome in Epithelial Ovarian Cancer Cases

Ovarian cancer (OC) is the second most frequent type of gynecological cancers worldwide. In the past decades, the development of novel diagnostic and prognostic biomarkers available for OC has been limited, reflecting by the lack of specificity of such markers or very costly management. Microarray expression profiling has shown very effective results in exploring new molecular markers for patients with OC. Nonetheless, most screenings are focused on mutations or expression of molecules that are translated into proteins, corresponding to only 2% of the total human genome. In order to account for the vast majority of transcripts, in the present exploratory study, we assessed the expression levels of a comprehensive panel of noncoding RNA in different subtypes of OC. We further evaluated their association with patient overall survival (OS) and aggressive forms of the disease, such as tumor type, stage, and chemotherapy resistance. By microarray profiling in a total of 197 epithelial OC patients (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas), we found two candidates, SNORA68 and SNORD74, which associated with OS and poor clinicopathological features. The overexpression of those two targets combined was correlated with shorter OS and progression-free survival. That association was further observed to correlate with a more aggressive form of the disease. Overall, the results indicate that a panel comprised of SNORA68 and SNORD74 may be clinically relevant, where patients could be offered a more individualized, targeted follow-up, given its further validation on future prospective clinical studies.

A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer

Ovarian cancer (OC) is the most malignant tumor in the female reproductive tract. Although abundant molecular biomarkers have been identified, a robust and accurate gene expression signature is still essential to assist oncologists in evaluating the prognosis of OC patients. In this study, samples from 367 patients in The Cancer Genome Atlas (TCGA) database were subjected to mRNA expression profiling. Then, we used a gene set enrichment analysis (GSEA) to screen genes correlated with epithelial–mesenchymal transition (EMT) and assess their prognostic power with a Cox proportional regression model. Six genes (TGFBI, SFRP1, COL16A1, THY1, PPIB, BGN) associated with overall survival (OS) were used to construct a risk assessment model, after which the patients were divided into high-risk and low-risk groups. The six-gene signature was an independent prognostic biomarker of OS for OC patients based on the multivariate Cox regression analysis. In addition, the six-gene model was validated with samples from the Gene Expression Omnibus (GEO) database. In summary, we established a six-gene signature relevant to the prognosis of OC, which might become a therapeutic tool with clinical applications in the future.

Collagen-rich omentum is a premetastatic niche for integrin α2-mediated peritoneal metastasis

The extracellular matrix (ECM) plays critical roles in tumor progression and metastasis. However, the contribution of ECM proteins to early metastatic onset in the peritoneal cavity remains unexplored. Here, we suggest a new route of metastasis through the interaction of integrin alpha 2 (ITGA2) with collagens enriched in the tumor coinciding with poor outcome in patients with ovarian cancer. Using multiple gene-edited cell lines and patient-derived samples, we demonstrate that ITGA2 triggers cancer cell adhesion to collagen, promotes cell migration, anoikis resistance, mesothelial clearance, and peritoneal metastasis in vitro and in vivo. Mechanistically, phosphoproteomics identify an ITGA2-dependent phosphorylation of focal adhesion kinase and mitogen-activated protein kinase pathway leading to enhanced oncogenic properties. Consequently, specific inhibition of ITGA2-mediated cancer cell-collagen interaction or targeting focal adhesion signaling may present an opportunity for therapeutic intervention of metastatic spread in ovarian cancer.

Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome

Endometrioid ovarian carcinoma (EnOC) demonstrates substantial clinical and molecular heterogeneity. Here, we report whole exome sequencing of 112 EnOC cases following rigorous pathological assessment. We detect a high frequency of mutation in CTNNB1 (43%), PIK3CA (43%), ARID1A (36%), PTEN (29%), KRAS (26%), TP53 (26%) and SOX8 (19%), a recurrently-mutated gene previously unreported in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy is constructed, identifying clinically distinct EnOC subtypes: cases with TP53 mutation demonstrate greater genomic complexity, are commonly FIGO stage III/IV at diagnosis (48%), are frequently incompletely debulked (44%) and demonstrate inferior survival; conversely, cases with CTNNB1 mutation, which is mutually exclusive with TP53 mutation, demonstrate low genomic complexity and excellent clinical outcome, and are predominantly stage I/II at diagnosis (89%) and completely resected (87%). Moreover, we identify the WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC.

Analysis of gene expression signatures identifies prognostic and functionally distinct ovarian clear cell carcinoma subtypes

Background

Ovarian clear cell carcinoma (OCCC) is a histological subtype of epithelial ovarian cancer (EOC) with distinct pathological, biological, and molecular features. OCCCs are more resistant to conventional treatment regimen of EOC and have the worst stage-adjusted prognosis amongst EOC subtypes. As the OCCC incidence rate in Asian populations has significantly increased in recent decades, it is critical to elucidate its molecular features that could lead to OCCC-tailored therapeutic strategies.

Methods

Gene expression profiles of 222 OCCC were analyzed by hierarchical clustering and statistical analyses.

Findings

We identified two OCCC gene expression subtypes: EpiCC—epithelial-like, which is associated with early-stage disease, with a relatively higher rate of gene mutations in the SWI/SNF complex; and MesCC—mesenchymal-like, associated with late-stage and higher enrichment of immune-related pathway activity. Genetic, copy number and transcriptomic analyses showed that both EpiCC and MesCC carried OCCC-associated aberrations. The EpiCC/MesCC classification was reproducible in validation cohorts and OCCC cell lines. MesCC tumors had a poorer progression-free survival (PFS) than EpiCC tumors (HR: 3·0, p = 0·0006). Functional assays in cell lines showed that the MesCC subtype was more proliferative and more anoikis-resistant than the EpiCC. By applying the EpiCC/MesCC classification to the TCGA renal clear cell carcinoma cohort, our results indicated interoperability of the subtyping scheme, and revealed preferential drug response of MesCC to bevacizumab.

Interpretation

The EpiCC/MesCC classification shows promise for prognostic and therapeutic stratification in OCCC patients and warrants further investigation in the context of OCCC gene expression subtype-tailored treatment strategies.

Safety, clinical activity and biomarker assessments of atezolizumab from a Phase I study in advanced/recurrent ovarian and uterine cancers

OBJECTIVE

Patients with advanced/recurrent epithelial ovarian and uterine cancers have limited treatment options beyond platinum chemotherapy. Both tumor types can express programmed death-ligand 1 (PD-L1), providing a potential therapeutic target for these patients. Here we present data from the ovarian and uterine cancer cohorts of the Phase I atezolizumab monotherapy study (PCD4989g).

METHODS

This Phase I, multi-center, first-in-human, open-label, dose-escalation/expansion clinical trial investigated single-agent atezolizumab in cohorts of patients with recurrent epithelial ovarian or uterine cancer. The primary objective was to evaluate the safety and tolerability of single-agent atezolizumab. Anti-tumor activity and preliminary assessment of potential biomarkers were evaluated as secondary and exploratory objectives, respectively.

RESULTS

The ovarian and uterine cancer cohorts enrolled 12 and 15 patients, respectively (10 [83%] and 5 [33%], respectively, had PD-L1 ≥ 5% on tumor-infiltrating immune cells). Atezolizumab was generally well tolerated with no new safety signals identified. The safety profiles in both cohorts were consistent with the known profile of atezolizumab monotherapy. Treatment-related adverse events (AEs) were mostly Grade ≤ 2, with no treatment-related Grade ≥ 4 AEs reported. Preliminary anti-tumor activity, with long durations of response, was observed in 2 patients from each cohort (ovarian cancer, 8.1 and 30.6+ months; uterine cancer, 7.3 and 16.6+ months). High microsatellite instability and tumor mutational burden were noted in the responders from the uterine cancer cohort.

CONCLUSIONS

Atezolizumab monotherapy was well tolerated in patients with epithelial ovarian or uterine cancer and may have clinical activity warranting further investigation.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01375842.

Radiogenomics: bridging imaging and genomics

From diagnostics to prognosis to response prediction, new applications for radiomics are rapidly being developed. One of the fastest evolving branches involves linking imaging phenotypes to the tumor genetic profile, a field commonly referred to as "radiogenomics." In this review, a general outline of radiogenomic literature concerning prominent mutations across different tumor sites will be provided. The field of radiogenomics originates from image processing techniques developed decades ago; however, many technical and clinical challenges still need to be addressed. Nevertheless, increasingly accurate and robust radiogenomic models are being presented and the future appears to be bright.

Developing a Clinico-Molecular Test for Individualized Treatment of Ovarian Cancer: The interplay of Precision Medicine Informatics with Clinical and Health Economics Dimensions

We report recent progress in the development of a precision test for individualized use of the VEGF-A targeting drug bevacizumab for treating ovarian cancer. We discuss the discovery model stage (i.e., past feasibility modeling and before conversion to the production test). Main results: (a) Informatics modeling plays a critical role in supporting driving clinical and health economic requirements. (b) The novel computational models support the creation of a precision test with sufficient predictivity to reduce healthcare system costs up to $30 billion over 10 years, and make the use of bevacizumab affordable without loss of length or quality of life.

An integrative systems biology approach for precision medicine in diabetic kidney disease

Current therapeutic approaches are ineffective in many patients with established diabetic kidney disease (DKD), an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large-scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed show that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to first identify patients at high risk of progression, and second to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.

Inter-pathologist and pathology report agreement for ovarian tumor characteristics in the Nurses' Health Studies

BACKGROUND

Grade and histotype of ovarian carcinomas are often used as surrogates of molecular subtypes. We examined factors affecting pathologists' reproducibility in two prospective studies.

METHODS

Two pathologists independently reviewed slides from 459 incident ovarian cancers in the Nurses' Health Study (NHS) and NHSII. We described agreement on tumor characteristics using percent agreement and Cohen's standard kappa (κ) coefficients. We used logistic regression, with disagreement as the outcome, to evaluate the contribution of case and tumor characteristics to agreement.

RESULTS

Inter-rater agreement was 95% (κ = 0.81) for carcinoma versus borderline, 89% (κ = 0.58) for grade and 85% (κ = 0.71) for histotype. Inter-rater grading disagreement was higher for non-serous histotypes (OR = 4.66, 95% CI 2.09-10.36) and lower for cancers with bizarre atypia (OR = 0.13, 95% CI 0.04-0.38). Agreement with original pathology reports was 94% (κ = 0.73) for carcinoma versus borderline, 78% (κ = 0.60) for histotype, and 79% (κ = 0.24) for grade. Grading disagreement was significantly lower for tumors with 'solid, pseudoendometrioid or transitional' (SET) architecture (OR = 0.08, 95%CI 0.01-0.84). Date of original diagnosis, hospital type, number of slides available for review, tumor stage, and slide quality were not related to agreement.

CONCLUSION

Overall, inter-rater agreement for tumor type and grade for archival tissue specimens was good. Agreement between the consensus review and original pathology reports was lower. Factors contributing to grading disagreement included non-serous histotype, absence of bizarre atypia, and absence of SET architecture.

Endometriosis-associated Ovarian Cancers

Endometriosis-associated cancers include clear cell and endometrioid ovarian carcinoma. A history of endometriosis has long been considered to be a risk factor for later development of these malignancies; however, recent molecular genetic evidence has provided unequivocal evidence that these lesions are in fact the precursors for endometriosis-associated cancers. Herein, we will explore the relationship between endometriosis and ovarian carcinomas, similarities between the premalignant lesions and their cancerous counterparts, and the potential role of mutations and the ovarian microenvironment that may contribute to malignant transformation.

Recurrent ubiquitin B silencing in gynecological cancers establishes dependence on ubiquitin C

Transcriptional repression of ubiquitin B (UBB) is a cancer-subtype-specific alteration that occurs in a substantial population of patients with cancers of the female reproductive tract. UBB is 1 of 2 genes encoding for ubiquitin as a polyprotein consisting of multiple copies of ubiquitin monomers. Silencing of UBB reduces cellular UBB levels and results in an exquisite dependence on ubiquitin C (UBC), the second polyubiquitin gene. UBB is repressed in approximately 30% of high-grade serous ovarian cancer (HGSOC) patients and is a recurrent lesion in uterine carcinosarcoma and endometrial carcinoma. We identified ovarian tumor cell lines that retain UBB in a repressed state, used these cell lines to establish orthotopic ovarian tumors, and found that inducible expression of a UBC-targeting shRNA led to tumor regression, and substantial long-term survival benefit. Thus, we describe a recurrent cancer-specific lesion at the level of ubiquitin production. Moreover, these observations reveal the prognostic value of UBB repression and establish UBC as a promising therapeutic target for ovarian cancer patients with recurrent UBB silencing.

The Diagnostic and Prognostic Potential of microRNAs in Epithelial Ovarian Carcinoma

Ovarian cancer causes more than 100,000 deaths globally per year. Despite intensive research efforts, there has been little improvement in the overall survival of patients over the past three decades. Most patients are not diagnosed until the cancer is at an advanced stage, by which time their chances of still being alive after 5 years are appallingly low. Attempts to extend life in these patients have been, for the most part, unsuccessful. This owes partly to the lack of suitable biomarkers for stratifying patients at the molecular level, into responders and non-responders. This would lead to more drugs being shown to have a clinical benefit and being approved for use in subgroups of patients. There is also a desperate need for improved biomarkers for earlier detection of ovarian cancer; if the disease is detected sooner there is a significantly improved outlook. In this review, we outline the evidence that microRNAs are deregulated in ovarian cancer, what this can tell us about tumour progression and how it could be used to improve patient stratification in clinical trials. We also describe the potential for circulating microRNAs, both associated with proteins or carried in vesicles, to be used as diagnostics for earlier detection or as biomarkers for informing clinicians on the prognosis and best treatment of ovarian cancer.

The role of MicroRNA molecules and MicroRNA-regulating machinery in the pathogenesis and progression of epithelial ovarian cancer

MicroRNA molecules are small, single-stranded RNA molecules that function to regulate networks of genes. They play important roles in normal female reproductive tract biology, as well as in the pathogenesis and progression of epithelial ovarian cancer. DROSHA, DICER, and Argonaute proteins are components of the microRNA-regulatory machinery and mediate microRNA production and function. This review discusses aberrant expression of microRNA molecules and microRNA-regulating machinery associated with clinical features of epithelial ovarian cancer. Understanding the regulation of microRNA molecule production and function may facilitate the development of novel diagnostic and therapeutic strategies to improve the prognosis of women with epithelial ovarian cancer. Additionally, understanding microRNA molecules and microRNA-regulatory machinery associations with clinical features may influence prevention and early detection efforts.

Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes

Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer.Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed.Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34-0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44-1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27-0.74), P = 0.0015].Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794-801. ©2017 AACR.

Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes

Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer.Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed.Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34-0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44-1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27-0.74), P = 0.0015].Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794-801. ©2017 AACR.

Loss of TAB3 expression by shRNA exhibits suppressive bioactivity and increased chemical sensitivity of ovarian cancer cell lines via the NF-κB pathway

Ovarian cancer is a leading cause of death among gynaecologic malignancies. Despite many years of research, it still remains sparing in reliable diagnostic markers and methods for early detection and screening. Transforming growth factor β-activated protein kinase 1 (TAK1)-binding protein 3 (TAB3) was initially characterized as an adapter protein essential for TAK1 activation in response to IL-1β or TNFα, however, the physiological role of TAB3 in ovarian cancer tumorigenesis is still not fully understood. In this study, we evaluated the effects of TAB3 on ovarian cancer cell lines. Expressions of TAB3 and PCNA (proliferating cell nuclear antigen) were found to be gradually increased in EOC tissues and cell lines, by western blot analysis and qRT-PCR. Distribution of TAB3 was further analysed by immunohistochemistry. In vitro, knockdown of TAB3 expression in HO8910 or SKOV3 ovarian cancer cells significantly inhibited bioactivity of ovarian cancer cells, including proliferation and cell-cycle distribution, and promoted chemical sensitivity to cisplatin and paclitaxel treatment via inhibiting NF-κB pathways. In conclusion, our study strongly suggests a novel function of TAB3 as an oncogene that could be used as a biomarker for ovarian cancer. It provides a new insight into the potential mechanism for therapeutic targeting, in chemotherapy resistance, common in ovarian cancer.