Identification of metabolism-associated molecular subtype in ovarian cancer

Ovarian cancer (OC) is the most lethal gynaecological cancer with genomic complexity and extensive heterogeneity. This study aimed to characterize the molecular features of OC based on the gene expression profile of 2752 previously characterized metabolism-relevant genes and provide new strategies to improve the clinical status of patients with OC. Finally, three molecular subtypes (C1, C2 and C3) were identified. The C2 subtype displayed the worst prognosis, upregulated immune-cell infiltration status and expression level of immune checkpoint genes, lower burden of copy number gains and losses and suboptimal response to targeted drug bevacizumab. The C1 subtype showed downregulated immune-cell infiltration status and expression level of immune checkpoint genes, the lowest incidence of BRCA mutation and optimal response to targeted drug bevacizumab. The C3 subtype had an intermediate immune status, the highest incidence of BRCA mutation and a secondary optimal response to bevacizumab. Gene signatures of C1 and C2 subtypes with an opposite expression level were mainly enriched in proteolysis and immune-related biological process. The C3 subtype was mainly enriched in the T cell-related biological process. The prognostic and immune status of subtypes were validated in the Gene Expression Omnibus (GEO) dataset, which was predicted with a 45-gene classifier. These findings might improve the understanding of the diversity and therapeutic strategies for OC.     

Identification of two molecular subtypes of dysregulated immune lncRNAs in ovarian cancer

Long non-coding RNA (lncRNA) has increasingly been identified as a key regulator in pathologies such as cancer. Multiple platforms were used for comprehensive analysis of ovarian cancer to identify molecular subgroups. However, lncRNA and its role in mapping the ovarian cancer subpopulation are still largely unknown. RNA-sequencing and clinical characteristics of ovarian cancer were acquired from The Cancer Genome Atlas database (TCGA). A total of 52 lncRNAs were identified as aberrant immune lncRNAs specific to ovarian cancer. We redefined two different molecular subtypes, C1(188) and C2(184 samples), in “iClusterPlus” R package, among which C2 grouped ovarian cancer samples have higher survival probability and longer median survival time (P <0.05) with activated IFN-gamma response, Wound Healing and Cytotoxic lymphocytes signal; 456 differentially expressed genes were acquired in C1 and C2 subtypes using limma (3.40.6) package, among which 419 were up-regulated and 37 were down-regulated, in TCGA dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis revealed that these genes were actively involved in ECM-receptor interaction, PI3K-Akt signaling pathway interaction KEGG pathway. Compared with the existing immune subtype, the Cluster2 sample showed a substantial increase in the proportion of the existing C2 immune subtype, accounting for 81.37%, which was associated with good prognosis. Our C1 subtype contains only 56.49% of the existing immune C1 and C4, which also explains the poor prognosis of C1. Furthermore, 52 immune-related lncRNAs were used to divide the TCGA-endometrial cancer and cervical cancer samples into two categories, and C2 had a good prognosis. The differentially expressed genes were highly correlated with immune-cell-related pathways. Based on lncRNA, two molecular subtypes of ovarian cancer were identified and had significant prognostic differences and immunological characteristics.     

Multi-Omics Analysis Elucidates The Immune And Intratumor Microbes Characteristics Of Ubiquitination Subtypes In Lung Adenocarcinoma

Ubiquitination modification is closely related to cancer and participates in the regulation of tumor microenvironment. However, the role of ubiquitination modification in the immune response and prognosis of lung adenocarcinoma has not been elucidated. This study aims to establish a disease classification associated with ubiquitination and reveal the landscape of intratumor microbes in patients with lung adenocarcinoma for the first time. A total of 1314 patients with lung adenocarcinoma in the GEO and TCGA databases were included in our study. We constructed a ubiquitination scoring model using WGCNA and constructed ubiquitination subtypes using unsupervised clustering, analyzed the clinical characteristics, immune characteristics, and intratumor microbes characteristics, and screened out the relevant gene signatures, which were verified by RT-qPCR in human cancer cells. The results showed that the high ubiquitination subtype had poor prognosis, low degree of immune infiltration, high index of tumor stemness, and poor effect of immunotherapy. The subtypes with lower ubiquitination scores have better prognosis, higher tumor microenvironment score and better immunotherapy effect. The C2 subtype has high level of immune infiltration, lower intratumor microbes diversity and abundance, and good prognosis. The C3 subtype has low level of immune infiltration, higher intratumor microbes diversity and abundance, and poor prognosis. The C1 subtype has characteristics between C2 and C3. In summary, this paper constructs a scoring system and several subtypes based on ubiquitination genes, and analyzed the characteristics, which can help provide new methods for clinical treatment.     

Clinical and molecular characteristics of bladder urothelial carcinoma subtypes

Bladder urothelial carcinoma (BLCA) is a common malignancy with high heterogeneity. A reasonable molecular subtyping can facilitate biological study and personalized therapy of BLCA. In this study, unsupervised consensus clustering was used to acquire the molecular subtypes of BLCA based on messenger RNA (mRNA) and microRNA (miRNA) data. Gene signature markers and canonical signaling pathways were compared between different subtypes. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for the functional annotation of overexpressed genes in different subtypes for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Three molecular subtypes were identified including C1 (luminal-P53 like), C2 (luminal-other), and C3 (basal-immune-squamous). C2 was different from C1 and C3 in clinical characteristics, including younger, better prognosis, and a higher proportion of papillary, Asian, low-grade, early-stage, lymph node negative, and complete remission patients (P < 0.05). Three molecular subtypes also showed distinct mRNA and miRNA expression patterns. luminal and P53-like markers were highly expressed in subtype C1, luminal markers were highly expressed in subtype C2, and basal, EMT/claudin-low, immune and squamous-differentiation markers were highly expressed in subtype C3. In addition, highly expressed genes in C1 were involved in extracellular signal transduction and cell-cell interaction, highly expressed genes in C2 were associated with oxygen transport, energy and steroid metabolism, and highly expressed genes in C3 were related with inflammatory, immune, cytokine, and signal transduction. BLCA in different molecular subtypes showed different clinical and molecular characteristics and personalized therapy needed to be adopted according to the molecular subtypes.     

Localisation and expression of aquaporin subtypes in epithelial ovarian tumours

To characterise AQP subtype localisation and expression in epithelial ovarian tumours, immunohistochemistry was used to assess the localisation and expression of AQP1-9 in 30 benign tumour cases, 30 borderline tumour cases, 50 malignant tumour cases and 20 normal ovarian tissue cases. Multiple AQP subtypes were expressed in epithelial ovarian tumours, with each AQP subtype displaying a different pattern of localisation and expression. AQP1 was mainly expressed in the microvascular endothelium, and AQP 2-9 were mainly expressed in tumour cells. Most AQP subtypes co-localised in the basolateral membranes of the epithelia of benign tumours and plasma membranes of malignant tumour cells. The positive rates for AQP1, 5, 6, 7, 8, and 9 were over 50%, but those for AQP2, 3 and 4 were only 10-40%. The expression of AQP1, 5 and 9 in malignant and borderline tumours was significantly higher than that in benign tumours (P<0.05) and normal ovarian tissue (P<0.05). However, AQP6 expression in ovarian malignant and borderline tumours was significantly lower than that in benign tumours (P<0.01) or normal ovarian tissue (P<0.01). AQP1 expression was increased in cases with ascites volumes greater than 1000 mL (P<0.05), AQP5 expression was greater in cases with lymph node metastasis (P<0.05), and more AQP9 expression was observed in G3 cases versus G1 and G2 cases (P<0.01). These results suggest that changes in the distribution and expression of AQP subtypes may be involved in ovarian carcinogenesis. This study presents a novel avenue of research that could illuminate the mechanism of ovarian carcinogenesis and treatment.     

Identification of immune microenvironment subtypes that predicted the prognosis of patients with ovarian cancer

Ovarian cancer (OC) is associated with high mortality rate. However, the correlation between immune microenvironment and prognosis of OC remains unclear. This study aimed to explore prognostic significance of OC tumour microenvironment. The OC data set was selected from the cancer genome atlas (TCGA), and 307 samples were collected. Hierarchical clustering was performed according to the expression of 756 genes. The immune and matrix scores of all immune subtypes were determined, and Kruskal-Wallis test was used to analyse the differences in the immune and matrix scores between OC samples with different immune subtypes. The model for predicting prognosis was constructed based on the expression of immune-related genes. TIDE platform was applied to predict the effect of immunotherapy on patients with OC of different immune subtypes. The 307 OC samples were classified into three immune subtypes A-C. Patients in subtype B had poorer prognosis and lower survival rate. The infiltration of helper T cells and macrophages in microenvironment indicated significant differences between immune subtypes. Enrichment analyses of immune cell molecular pathways showed that JAK–STAT3 pathway changed significantly in subtype B. Furthermore, predictive response to immunotherapy in subtype B was significantly higher than that in subtype A and C. Immune subtyping can be used as an independent predictor of the prognosis of OC patients, which may be related to the infiltration patterns of immune cells in tumour microenvironment. In addition, patients in immune subtype B have superior response to immunotherapy, suggesting that patients in subtype B are suitable for immunotherapy.     

Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies

Background

Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous) are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype specific. With the emergence of high-throughput molecular techniques, distinct pathogenetic pathways have been identified in these subtypes. We examined variation in biomarker expression rates between subtypes, and how this influences correlations between biomarker expression and stage at diagnosis or prognosis.

Methods and Findings

In this retrospective study we assessed the protein expression of 21 candidate tissue-based biomarkers (CA125, CRABP-II, EpCam, ER, F-Spondin, HE4, IGF2, K-Cadherin, Ki-67, KISS1, Matriptase, Mesothelin, MIF, MMP7, p21, p53, PAX8, PR, SLPI, TROP2, WT1) in a population-based cohort of 500 ovarian carcinomas that was collected over the period from 1984 to 2000. The expression of 20 of the 21 biomarkers differs significantly between subtypes, but does not vary across stage within each subtype. Survival analyses show that nine of the 21 biomarkers are prognostic indicators in the entire cohort but when analyzed by subtype only three remain prognostic indicators in the high-grade serous and none in the clear cell subtype. For example, tumor proliferation, as assessed by Ki-67 staining, varies markedly between different subtypes and is an unfavourable prognostic marker in the entire cohort (risk ratio [RR] 1.7, 95% confidence interval [CI] 1.2%–2.4%) but is not of prognostic significance within any subtype. Prognostic associations can even show an inverse correlation within the entire cohort, when compared to a specific subtype. For example, WT1 is more frequently expressed in high-grade serous carcinomas, an aggressive subtype, and is an unfavourable prognostic marker within the entire cohort of ovarian carcinomas (RR 1.7, 95% CI 1.2%–2.3%), but is a favourable prognostic marker within the high-grade serous subtype (RR 0.5, 95% CI 0.3%–0.8%).

Conclusions

The association of biomarker expression with survival varies substantially between subtypes, and can easily be overlooked in whole cohort analyses. To avoid this effect, each subtype within a cohort should be analyzed discretely. Ovarian carcinoma subtypes are different diseases, and these differences should be reflected in clinical research study design and ultimately in the management of ovarian carcinoma.     

A comprehensive analysis of IDO1 expression with tumour‐infiltrating immune cells and mutation burden in gynaecologic and breast cancers

Gynaecologic and breast cancers share some similarities at the molecular level. The aims of our study are to highlight the similarities and differences about IDO1, an important immune‐related gene in female cancers. The NGS data from TCGA of cervical squamous cell carcinoma (CESC), ovarian serous cystadenocarcinoma (OV), uterine corpus endometrial carcinoma (UCEC), uterine carcinosarcoma (UCS) and breast invasive carcinoma (BRCA) were analysed to identify molecular features, and clinically significant and potential therapeutic targets of IDO1. We found IDO1 was significantly up‐regulated in four gynaecologic cancers and breast cancer. According to breast cancer PAM50 classification scheme, IDO1 expression was higher in tumours of basal than other subtypes and showed better survival prognosis in BRCA and OV. Through immune infiltration analysis, we found a strong correlation between IDO1 and immune cell populations especially for dendritic cells and T cells. In addition, we investigated the association between IDO1 and tumour mutation burden (TMB) and found that IDO1 was significantly correlated with TMB in BRCA and CESC. GSVA revealed that hallmarks significantly correlated with IDO1 were involved in interferon gamma response, allograft rejection and inflammatory response. We also found PD‐L1 and LAG3 were highly positive related to IDO1 in gynaecologic cancers when comparing with their corresponding normal tissues. Our results indicated that IDO1 participated in anti‐tumour immune process and is correlated with mutation burden. These findings may expand our outlook of potential anti‐IDO1 treatments.     

Ovarian Cancer Cell Line Panel (OCCP): Clinical Importance of In Vitro Morphological Subtypes

Epithelial ovarian cancer is a highly heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Therapeutic approaches need to account for inter-patient and intra-tumoural heterogeneity and detailed characterization of in vitro models representing the different histological and molecular ovarian cancer subtypes is critical to enable reliable preclinical testing. There are approximately 100 publicly available ovarian cancer cell lines but their cellular and molecular characteristics are largely undescribed. We have characterized 39 ovarian cancer cell lines under uniform conditions for growth characteristics, mRNA/microRNA expression, exon sequencing, drug response for clinically-relevant therapeutics and collated all available information on the original clinical features and site of origin. We tested for statistical associations between the cellular and molecular features of the lines and clinical features. Of the 39 ovarian cancer cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes: Epithelial (n = 21), Round (n = 7) and Spindle (n = 12) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes in the Spindle subtype. Comparison with the original clinical data showed association of the spindle-like tumours with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the expression profiles of Spindle, Round and Epithelial morphologies clustered with the previously described C1-stromal, C5-mesenchymal and C4 ovarian subtype expression profiles respectively. Comprehensive profiling of 39 ovarian cancer cell lines under controlled, uniform conditions demonstrates clinically relevant cellular and genomic characteristics. This data provides a rational basis for selecting models to develop specific treatment approaches for histological and molecular subtypes of ovarian cancer.     

Prognostic significance of immune landscape in tumour microenvironment of endometrial cancer

Tumour microenvironment (TME) is crucial to tumorigenesis. This study aimed to uncover the differences in immune phenotypes of TME in endometrial cancer (EC) using Uterine Corpus Endometrial Carcinoma (UCEC) cohort and explore the prognostic significance. We employed GVSA enrichment analysis to cluster The Cancer Genome Atlas (TCGA) EC samples into immune signature cluster modelling, evaluated immune cell profiling in UCEC cohort (n = 538) and defined four immune subtypes of EC. Next, we analysed the correlation between immune subtypes and clinical data including patient prognosis. Furthermore, we analysed the expression of immunomodulators and DNA methylation modification. The profiles of immune infiltration in TCGA UCEC cohort showed significant difference among four immune subtypes of EC. Among each immune subtype, natural killer T cells (NKT), dendritic cells (DCs) and CD8⁺T cells were significantly associated with EC patients survival. Each immune subtype exhibited specific molecular classification, immune cell characterization and immunomodulators expression. Moreover, the expression immunomodulators were significantly related to DNA methylation level. In conclusion, the identification of immune subtypes in EC tissues could reveal unique immune microenvironments in EC and predict the prognosis of EC patients.     

Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer.     

PD-L1 expression with QR1 and E1L3N antibodies according to histological ovarian cancer subtype: A series of 232 cases

Therapeutic strategies for epithelial ovarian cancers are evolving with the advent of immunotherapy, such as PD-L1 inhibitors, with encouraging results. However, little data are available on PDL-1 expression in ovarian cancers. Thus, we set out to determine the PD-L1 expression according to histological subtype. We evaluated the expression of two PD-L1 clones – QR1 and E1L3N – with two scores, one based on the percentage of labeled tumor cells (tumor proportion score, TPS) and the other on labeled immune cells (combined proportion score, CPS) in a consecutive retrospective series of 232 ovarian cancers. PD-L1 expression was more frequent in high grade serous carcinoma (27.5% with E1L3N clone and 41.5% with QR1 clone), grade 3 endometrioid carcinoma (25% with E1L3N clone and 50% with QR1 clone), and clear-cell carcinomas (27.3% with E1L3N clone and 29.6% with QR1 clone) than other histological subtypes with CPS score. Using the CPS score, 17% of cases were labeled with E1L3N vs 28% with QR1. Using the TPS score, 14% of cases were positive to E1L3N vs 17% for QR1. For TPS and CPS, respectively, 77% and 78% of the QR1 cases were concordant with E1L3N for the thresholds of 1%. Overall and progression-free survival between PD-L1 positive and PD-L1 negative patients were not different across all histological types, and each subtype in particular for serous carcinomas expressing PD-L1. Expression of PD-L1 is relatively uncommon in epithelium ovarian tumors. When positive, usually <10% of tumor cells are labeled. QR1 clone and CPS appear the best tools to evaluate PD-L1 expression.Key words: Ovarian cancer, PD-L1 antibody, immunochemistry, histological subtype     

Expression of Mitochondrial Regulators PGC1α and TFAM as Putative Markers of Subtype and Chemoresistance in Epithelial Ovarian Carcinoma

Epithelial ovarian carcinoma (EOC), the major cause of gynaecological cancer death, is a heterogeneous disease classified into five subtypes. Each subtype has distinct clinical characteristics and is associated with different genetic risk factors and molecular events, but all are treated with surgery and platinum/taxane regimes. Tumour progression and chemoresistance is generally associated with major metabolic alterations, notably altered mitochondrial function(s). Here, we report for the first time that the expression of the mitochondrial regulators PGC1α and TFAM varies between EOC subtypes; furthermore, we have identified a profile in clear-cell carcinoma consisting of undetectability of PGC1α/TFAM, and low ERα/Ki-67. By contrast, high-grade serous carcinomas were characterised by a converse state of PGC1α/TFAM, ERα positivity and a high Ki-67 index. Interestingly, loss of PGC1α/TFAM and ERα was found also in a non-clear cell EOC cell line made highly resistant to platinum in vitro. Similar to clear-cell carcinomas, these resistant cells also showed accumulation of glycogen. Altogether, our data provide mechanistic insights into the chemoresistant nature of ovarian clear-cell carcinomas. Furthermore, these findings corroborate the need to take into account the diversity of EOC and to develop subtype specific treatment strategies.     

NuMA overexpression in epithelial ovarian cancer

Highly aneuploid tumours are common in epithelial ovarian cancers (EOC). We investigated whether NuMA expression was associated with this phenomenon.NuMA protein levels in normal and tumour tissues, ovarian cell lines and primary cultures of malignant cells derived from ovarian ascitic fluids were analysed by Affymetrix microarray analysis, immunoblotting, immunohistochemistry (IHC) and immunofluorescence (IF), with results correlated to associated clinical data. Aneuploidy status in primary cultures was determined by FACS analysis.Affymetrix microarray data indicated that NuMA was overexpressed in tumour tissue, primary cultures and cell lines compared to normal ovarian tissue. IHC revealed low to weak NuMA expression in normal tissues. Expression was upregulated in tumours, with a significant association with disease stage in mucinous EOC subtypes (p = 0.009), lymph node involvement (p = 0.03) and patient age (p = 0.04). Additional discontinuous data analysis revealed that high NuMA levels in tumours decreased with grade (p = 0.02) but increased with disease stage (p = 0.04) in serous EOC. NuMA expression decreased in late disease stage 4 endometrioid EOCs. High NuMA levels decreased with increased tumour invasion in all subtypes (p = 0.03). IF of primary cultures revealed that high NuMA levels at mitotic spindle poles were significantly associated with a decreased proportion of cells in cytokinesis (p = 0.05), increased binucleation (p = 0.021) and multinucleation (p = 0.007), and aneuploidy (p = 0.008).NuMA is highly expressed in EOC tumours and high NuMA levels correlate with increases in mitotic defects and aneuploidy in primary cultures.     

Annexin A4 Is Involved in Proliferation,Chemo-Resistance and Migration and Invasion in Ovarian Clear Cell Adenocarcinoma Cells

Ovarian clear cell adenocarcinoma (CCC) is the second most common subtype of ovarian cancer after high-grade serous adenocarcinomas. CCC tends to develop resistance to the standard platinum-based chemotherapy, and has a poor prognosis when diagnosed in advanced stages. The ANXA4 gene, along with its product, a Ca⁺⁺-binding annexin A4 (ANXA4) protein, has been identified as the CCC signature gene. We reported two subtypes of ANXA4 with different isoelectric points (IEPs) that are upregulated in CCC cell lines. Although several in vitro investigations have shown ANXA4 to be involved in cancer cell proliferation, chemoresistance, and migration, these studies were generally based on its overexpression in cells other than CCC. To elucidate the function of the ANXA4 in CCC cells, we established CCC cell lines whose ANXA4 expressions are stably knocked down. Two parental cells were used: OVTOKO contains almost exclusively an acidic subtype of ANXA4, and OVISE contains predominantly a basic subtype but also a detectable acidic subtype. ANXA4 knockdown (KO) resulted in significant growth retardation and greater sensitivity to carboplatin in OVTOKO cells. ANXA4-KO caused significant loss of migration and invasion capability in OVISE cells, but this effect was not seen in OVTOKO cells. We failed to find the cause of the different IEPs of ANXA4, but confirmed that the two subtypes are found in clinical CCC samples in ratios that vary by patient. Further investigation to clarify the mechanism that produces the subtypes is needed to clarify the function of ANXA4 in CCC, and might allow stratification and improved treatment strategies for patients with CCC.     

Common miRNAs,candidate genes and their interaction network across four subtypes of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is categorized into four major histological subtypes such as clear cell carcinoma (CCC), endometrioid carcinoma (EC), mucinous carcinoma (MC), and serous carcinoma (SC). Heterogeneity of the EOC leads to different clinical outcomes of the disease, although all the subtypes are originated from the same layer of tissue. Therefore, it is of interest to identify the common candidate genes, miRNA and their interaction network in four the subtypes of EOC. A comparative gene expression analysis identified 248 common differentially expressed genes (DEGs) in the four subtypes of EOC. Identified common DEGs were found to be enriched in cancer specific pathways. A protein-protein interaction (PPI) network of the common DEGs were constructed, and subsequent module and survival analyses identified seven key candidate genes (CCNB1, CENPM, CEP55, RACGAP1, TPX2, UBE2C, and ZWINT). We also documented 10 key candidate miRNAs (hsa-mir-16-5p, hsa-mir-23b-3p, hsa-mir-34a-5p, hsa-mir-103a-3p, hsa-mir-107, hsa-mir-124-3p, hsa-mir-129-2-3p, hsa-mir-147a, hsa-mir-205-5p, and hsa-mir-195-5p) linked to the candidate genes. These derived data find application in the understanding of EOC.