Malignant Ovarian Tissues Research Articles

The Role of the Plasminogen Activator Inhibitor 1 (PAI1) in Ovarian Cancer: Mechanisms and Therapeutic Implications

AbstractOvarian cancer (OC) is one among most significantly fatal gynecological cancers, with late-stage detection and an inadequate prognosis. Plasminogen activator inhibitor-1 (PAI1) gene anticipates negative outcomes in many different kinds of malignancies. Several research investigations are currently being done to examine the biological role of PAI1 in OC and the possible benefits of targeted pharmacotherapies. The PAI1 gene has been linked to the emergence and development of cancer in the ovary. PAI1, an inhibitor of serine protease, influences the fibrinolysis and extracellular matrix remodeling, both of which are crucial for tumor expansion and metastatic growth. PAI1 levels have been discovered to be subsequently more elevated in malignant ovarian tissues than in usual ovarian tissue, demonstrating a potential connection among PAI1 overexpression and OC development. PAI1 promotes tumor cell proliferation, movement, and an invasion by influencing the urokinase-plasminogen activators and through interactions with cell surface receptors. In addition, PAI1 gene contributes to angiogenesis and apoptotic cell death, which contribute to the more hostile phenotypes of OC. The prognostic and therapeutic consequences of focusing on PAI1 in OC are explored, demonstrating PAI1's potential to be a biomarker and emphasizing for novel treatment approaches. The PAI1 gene possesses several functions in OC, affecting tumor development, an invasion, and metastatic growth. Comprehending the complicated interactions and mechanisms that regulate PAI1 in OC may lead to more efficient evaluation and treatment strategies and ultimately enhance patient outcomes.

STAT3 mediates ECM stiffness-dependent progression in ovarian cancer.

The treatment of ovarian cancer remains a medical challenge and its malignant progression is connected with obvious changes in both tissue and cell stiffness. However, the accurate mechanical-responsive molecules and mechanism remains unclear in ovarian cancer. Based on our previous results combined with the crucial regulatory role of STAT3 in the malignant progression of various cancer types, we want to investigate the relationship between STAT3 and matrix stiffness in ovarian cancer and further explore the potential mechanisms. Collagen-coated polyacrylamide gels (1, 6, and 60 kPa) were prepared to mimic soft or hard matrix stiffness. Western blotting, qRT-PCR, flow cytometry, IHC, EdU assays, and TEM were used to evaluate the effect of STAT3 in vitro under different matrix stiffnesses. Furthermore, a BALB/c nude mouse model was established to assess the relationship in vivo. Our results confirmed the differential expression of STAT3/p-STAT3 not only in normal and malignant ovarian tissues but also under different matrix stiffnesses. Furthermore, we verified that STAT3 was a mechanically responsive gene both in vitro and in vivo, and the mechanical response was carried out by altering the migration-related molecules (TNFAIP1) and adhesion-related molecules (LPXN, CNN3). The novel findings suggest that STAT3, a potential therapeutic target for clinical diagnosis and treatment, is a mechanically responsive gene that responds to matrix stiffness, particularly regulation in migration and adhesion in the progression of ovarian cancer.

Angio-Long Noncoding RNA MALAT1 (rs3200401) and MIAT (rs1061540) Gene Variants in Ovarian Cancer.

The genotyping of long non-coding RNA (lncRNA)-related single-nucleotide polymorphisms (SNPs) could be associated with cancer risk and/or progression. This study aimed to analyze the angiogenesis-related lncRNAs MALAT1 (rs3200401) and MIAT (rs1061540) variants in patients with ovarian cancer (OC) using "Real-Time allelic discrimination polymerase chain reaction" in 182 formalin-fixed paraffin-embedded (FFPE) samples of benign, borderline, and primary malignant ovarian tissues. Differences in the genotype frequencies between low-grade ovarian epithelial tumors (benign/borderline) and malignant tumors and between high-grade malignant epithelial tumors and malignant epithelial tumors other than high-grade serous carcinomas were compared. Odds ratios (ORs)/95% confidence intervals were calculated as measures of the association strength. Additionally, associations of the genotypes with the available pathological data were analyzed. The heterozygosity of MALAT1 rs3200401 was the most common genotype (47.8%), followed by C/C (36.3%). Comparing the study groups, no significant differences were observed regarding this variant. In contrast, the malignant epithelial tumors had a higher frequency of the MIAT rs1061540 C/C genotype compared to the low-grade epithelial tumor cohorts (56.7% vs. 37.6, p = 0.031). The same genotype was significantly higher in high-grade serous carcinoma than its counterparts (69.4% vs. 43.8%, p = 0.038). Multivariate Cox regression analysis showed that the age at diagnosis was significantly associated with the risk of OC development. In contrast, the MIAT T/T genotype was associated with a low risk of malignant epithelial tumors under the homozygote comparison model (OR = 0.37 (0.16-0.83), p = 0.017). Also, MIAT T allele carriers were less likely to develop high-grade serous carcinoma under heterozygote (CT vs. CC; OR = 0.33 (0.12-0.88), p = 0.027) and homozygote (TT vs. CC; OR = 0.26 (0.07-0.90), p = 0.034) comparison models. In conclusion, our data provide novel evidence for a potential association between the lncRNA MIAT rs1061540 and the malignant condition of ovarian cancer, suggesting the involvement of such lncRNAs in OC development.

Iterative prototyping based on lessons learned from the falloposcope in vivo pilot study experience.

High grade serous ovarian cancer is the most deadly gynecological cancer, and it is now believed that most cases originate in the fallopian tubes (FTs). Early detection of ovarian cancer could double the 5-year survival rate compared with late-stage diagnosis. Autofluorescence imaging can detect serous-origin precancerous and cancerous lesions in ex vivo FT and ovaries with good sensitivity and specificity. Multispectral fluorescence imaging (MFI) can differentiate healthy, benign, and malignant ovarian and FT tissues. Optical coherence tomography (OCT) reveals subsurface microstructural information and can distinguish normal and cancerous structure in ovaries and FTs. We developed an FT endoscope, the falloposcope, as a method for detecting ovarian cancer with MFI and OCT. The falloposcope clinical prototype was tested in a pilot study with 12 volunteers to date to evaluate the safety and feasibility of FT imaging prior to standard of care salpingectomy in normal-risk volunteers. In this manuscript, we describe the multiple modifications made to the falloposcope to enhance robustness, usability, and image quality based on lessons learned in the clinical setting. The diameter falloposcope was introduced via a minimally invasive approach through a commercially available hysteroscope and introducing a catheter. A navigation video, MFI, and OCT of human FTs were obtained. Feedback from stakeholders on image quality and procedural difficulty was obtained. The falloposcope successfully obtained images in vivo. Considerable feedback was obtained, motivating iterative improvements, including accommodating the operating room environment, modifying the hysteroscope accessories, decreasing endoscope fragility and fiber breaks, optimizing software, improving fiber bundle images, decreasing gradient-index lens stray light, optimizing the proximal imaging system, and improving the illumination. The initial clinical prototype falloposcope was able to image the FTs, and iterative prototyping has increased its robustness, functionality, and ease of use for future trials.

Automated Ovarian Cancer Identification Using End-to-End Deep Learning and Second Harmonic Generation Imaging

Surgery is one of the most important methods for the treatment of ovarian cancer. During this procedure, a biopsy is usually required to evaluate the suspicious lesions and provide guidance for the size of the surgical resection. However, the conventional biopsy for intraoperative histopathological diagnosis performed by trained pathologists is labor-intensive, time-consuming, and carries the risk of bias. Therefore, we present a novel optical biopsy method to assist physicians in accurately and rapidly diagnosing ovarian cancer during surgery. We demonstrate that second harmonic generation (SHG) images of unstained, freshly resected ovarian tissues can be accurately characterized by deep learning techniques. Using 13,563 SHG images obtained from freshly resected human ovarian tissues of 74 patients, we fine-trained a convolutional neural network (CNN) based on pretrained ResNet50 framework to distinguish normal, benign, and malignant ovarian tissue with an average accuracy of 99.7%. These results suggest that optical biopsies based on label-free SHG imaging and deep learning technology have great potential for rapid and accurate characterizations of ovarian lesions in surgery.

The Importance of Il8 Gene Expression and Il-8 A251t in Diagnosis and Prognosis of Ovarian Cancer in Iraqi Women

The present study aimed to shed light on the association between the gene expression of IL8 and its genetic polymorphism IL-8 A251T in the incidence and pathogenesis of ovarian cancer. A total of 43 Paraffin-embedded tissue blocks from patients with different stages of newly diagnosed ovarian cancer were provided by certain Iraqi hospitals as well as 14 samples of patients with benign ovarian tumors tissues as a control group were used in this study. In the present study, the level of IL8 gene expression was investigated by comparing it with that of benign tumors, the results detected that IL-8 mRNA was expressed in 47(81.02%) of samples, 36 samples with ovarian cancer and 11 benign ovarian. IL-8 mRNA levels in ovarian cancer tissues were statically significant higher than those in benign ovarian tissue (P=0.0328<0.05). The samples were divided into high and low mRNA-expression depending on the mean value of IL8 gene expression in benign tumors which used as a cutoff, the results showed that samples with high mRNA-expressing 25(69.4%) which showed high significant differences compare with samples that showed low expressing 11(30.55%) (P value=0.0028<0.01). In correlation with histopathological type of ovarian tumors, mucinous tumors showed statistically significant difference in compare with other histopathologic tumor type (P=0.0516,<0.05). According to the tumor stages, statistically significant difference was found between 31(86.11%) of samples with stage I which showed the highest level of expression and 5(13.88%) of samples with stage III (P value=0.0410<0.05). For A251T polymorphism, the result showed that 21(58.33%) patients were heterozygous A/T, 14(38.88%) were homozygous T/T, and 1(2.77%) was homozygous A/A. For patients with benign ovarian tumors 11(91.66%) were heterozygous A/T, 1(8.33%) was homozygous T/T, and no one of the patients were homozygous for the A/A genotype. High significant prevalence of the IL-8 251T allele was detected in both ovarian cancer patients (P value 0.0047 <0.01) and patients with benign ovarian tumors (P value 0.014 <0.02) as compared with IL-8 251A allele. In the present study the association of the A251T polymorphism with ovarian cancer were investigated by attending to levels of IL-8 mRNA in benign and malignant ovarian tissues related with the respective genotypes. In benign ovarian tumors statically analysis showed that there were no significant differences between genotypes, while for cancer samples, the average of IL-8 gene expression in ovarian cancer patients carrying +251TT genotype was highly significant than that in ovarian cancer patients with the +251AT and +251AA genotypes (p value= 0.0037<0.01). In conclusion, the results reflected the possibility of detecting the IL8 gene transcript in benign as well as the malignant ovarian tissues but with wide differences in the sample percentages and level of gene expression which in turn reflect the value of IL8 gene as a useful tool for discriminating malignant breast tumors from non-malignant ones. On the other hand the high level of gene expression associated with stage I of tumor may be reveals the diagnostic value of this gene for early diagnosis of ovarian cancer. The results showed that the genetic variation of IL-8 gene influences susceptibility to ovarian cancer, we also suggested that the TT genotype of IL-8 -251A/T may associate with increase the risk of ovarian cancer in Iraqi women because of altered IL-8 gene expression.

Establishment and Comprehensive Analysis of Underlying microRNA-mRNA Interactive Networks in Ovarian Cancer.

Background The rate of ovarian cancer (OC) is one of the highest in women's reproductive systems. An improperly expressed microRNA (miRNA) has been discovered to have a vital role in the pathophysiology of OC. However, more research into OC's miRNA-message RNA (mRNA) gene interaction network is required. Methods Firstly, the microarray data sets GSE25405 and GSE119055 from the GEO (Gene Expression Omnibus) database were downloaded and then analyzed with the GEO2R tool aiming at identifying DEMs (differential expressed miRNAs) between ovarian malignant tissue and ovarian normal tissue. The whole consistently changed miRNAs were then screened out to be candidate DEMs. For estimating underlying upstream transcription factors, FunRich was employed. miRNet was utilized to determine putative DEMs' downstream target genes. The R program was then used to do the GO annotation as well as the analysis of KEGG pathway enrichment for target genes. The PPI (protein-protein interaction), as well as the DEM-hub gene networks, were created by the Cytoscape software and STRING database. Finally, we chose the GSE74448 dataset to test the precision of hub gene expressions. Results We have screened out six (five upregulated and one downregulated) DEMs. The majority of upregulated and downregulated DEMs are likely regulated by SP1 (specificity protein 1). SP4 (s protein 4), POU2F1 (POU class 2 homeobox 1), MEF2A (myocyte-specific enhancer factor 2A), ARID3A (AT-rich interaction domain 3A), and EGR1 (early growth response 1) can regulate upregulated and downregulated DEMs. We have found 807 target genes (656 upregulated and 151 downregulated DEM), being generally enriched in focal adhesion and proteoglycans in cancer, gastric cancer, hepatocellular carcinoma, as well as breast cancer. The majority of hub genes are projected to be controlled by hsa-miR-429, hsa-miR-140-5p, hsa-miR-199a-5p, and hsa-miR-199a-3p after the DEM-hub gene network was built. VEGFA (vascular endothelial growth factor A), EZH2 (enhancer of zeste 2 polycomb repressive complex 2 subunit), and HIF1A (hypoxia inducible factor 1 subunit alpha) expressions are consistent with the GSE74448 dataset in the first 18 hub genes. Conclusion We have built an underlying miRNA-mRNA interacting network in OC, giving us unparalleled insight into the disease's diagnosis and treatment.

Raman spectroscopic study of benign and malignant ovarian tissues

Ovarian cancer is one of the most common female tumors all over the world, and its mortality rate ranks first among gynecological malignancies. A progressive assessment, diagnosis and remedy are significant for the proper management of the disease process. In this paper, a prompt, non-invasive and highly effective screening test for ovarian cancer was developed based on the Raman spectroscopy (RS) data of fresh ovarian tissues. Raman spectral measurements were performed on fresh ovarian tissue samples from 17 ovarian cancer patients and 14 benign ovarian tumors. We preliminarily identified the Raman peaks in the measured ovarian tissue spectra and summarized their respective characteristic peaks, indicating that specific biomolecules changed among different groups, and their differences were analyzed. The conclusions suggested that the position of the characteristic peaks of Raman spectrum of the ovarian cancer tissues and benign ovarian tissues were different. The relative intensity of ovarian cancer tissue was higher than that of benign ovarian tissue at the 1004, 1155, 1446 cm−1 with phenylalanine, protein and lipids as characteristic peaks, and the difference were significant (P < 0.05). This exploratory work demonstrates that RS may be used as a detection method for screening benign and malignant ovarian tumors.

Proteomic Profile Mapping and Differential Expression of Protein in Ovarian Cancer

This study aimed to characterize differentially expressed proteins in malignant ovarian tissue to find out potential novel biomarkers in ovarian cancer (OC). We enrolled 20 ovarian cancer patients (40-65 years) and an equal number of age-matched healthy women to get malignant and healthy ovarian tissue samples for protein extraction and quantification after tissue lysis. The protein profile was analyzed using two-dimensional gel electrophoresis followed by MALDI-TOF mass spectrometry. Based on the information thus obtained, the proteins were identified using the relevant software and protein databank to analyze the malignant and non-malignant ovarian tissue samples (n = 20/group). In this proteomic analysis of the ovarian tissue, 112 proteins were detected. Based on a minimum of ≥ 1.5-fold expression difference (p-value ≤ 0.05; FDR ≤ 0.05 and PMF ≥ 79), 17 proteins were found to be upregulated while 27 were downregulated in the malignant ovarian tissue. Six of these proteins have not been previously reported in ovarian cancer. Out of these, three are upregulated while the other three are downregulated. The upregulated proteins are centrosomal protein of 290 kDa (Cep290), uncharacterized protein C1orf109 (C1orf109) and GTPase-activating Rap/Ran-GAP domain-like protein 3 (GARNL3), and the three downregulated proteins identified are actin-related protein 3 (ARP3), cytosolic carboxypeptidase 3 (AGBL3) and NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 10 (NDUFA10). This proteomic mapping not only provides data on protein profiling of ovarian cancer in Pakistani population for the first time but also reports six novel differentially expressed proteins, which have not been previously reported in ovarian cancer patients. They may serve as potential novel biomarkers after further validation for early diagnosis and prognosis of ovarian cancer. It also provides additional data to improve existing knowledge of already reported protein ovarian cancer biomarkers.

Long Non-Coding RNA- PVT1 in Ovarian Cancer as Predictors for Platinum Analogues Resistance

Abstract Background Ovarian cancer is the fifth most common type of cancer and the most common cause of death among women with gynecological malignancies. Objectives The aim of this retrospective study was to assess expression of the Lnc_PVT1 in the studied subjects. The expression of Lnc_PVT1 biomarker; was compared in ovarian cancer patients versus the non-cancerous tissue. The data normalization was tested by normality test which shows that the biomarker expression is not normally distributed; thus, a Mann Whitney statistics test for non -parametric values was applied. Our results showed a high significant difference in the expression of Lnc-PVT1 (p &amp;lt; 0.01). Lnc_PVT1 expression is upregulated by 2.4 folds in ovarian cancer patients (median: 32.0; range: 11 – 92) compared to control group (median: 13.0; range: 11 – 16). Methods and Materials This is a retrospective study. Include patients with advanced epithelial ovarian cancer (stage II and IV) who received chemotherapy platinum based and taxines from 2014-2017. Setting: Clinical oncology department Ain Shams University, Egypt, Demerdash hospital. Data collection: The following information will be ANONYMOUSLY extracted from the patient medical files: age at diagnosis, presenting symptoms, laboratory investigations: (Liver function, kidney function, complete blood count &amp;tumor markers), tumor histological type, tumor FIGO stage&amp; degree of differentiation, treatment modalities, type of surgery, chemotherapy regimens (Adjuvant, Neoadjuvant or palliative), chemotherapy responsiveness or resistance, disease recurrence and disease-free period, and patients' survival. Results The current study was enrolled on 55 subjects, they classified into two subgroups. The ovarian cancer cases constitute 45 patients; samples collected from patients after diagnosis has been confirmed by histopathology based on immune-histochemical analysis as well as Computerized axial tomography (CT scan) and Magnetic resonance imaging (MRI). The cancer ovary patients were compared to ten non- malignant ovarian tissues. Table 1 illustrates the demographic and clinical data of the studied subjects. We test the normality for age; the data was normally distributed. For this reason, we represent the data in mean value and standard deviation form. Matched age and gender was observed between ovarian cancer patients and healthy control. The mean age for the studied subjects was 47.7±9.1. In our study; the Cisplatin resistant patients (n = 25) had a mean age of 46±5 compared to Cisplatin sensitive which were older (mean: 50 ±11.5). Regarding the age subgroups; the majority of the studied subjects were younger than 48 years old. The ovarian cancer patients were subcategorized into subgroups (Cisplatin sensitive/resistant). Conclusion Comparative analysis between Cisplatin sensitive and resistant ovarian cancer tissues for the Lnc_PVT1, TGF-b and Caspase-3. A high significant difference was observed by Mann- Whitney test (p = 0.001) between Cisplatin sensitive and resistant ovarian cancer patients; Cisplatin resistant tissues showed higher expression levels of the Lnc_PVT1 expression (median 20.0, range: 10 - 92) in Cisplatin sensitive ovarian tissue compared to Cisplatin resistant tissue (median: 83; range: 46-86).

A pancancer overview of FBN1, asprosin and its cognate receptor OR4M1 with detailed expression profiling in ovarian cancer.

Ovarian cancer affects >295,000 women worldwide and is the most lethal of gynaecological malignancies. Often diagnosed at a late stage, current research efforts seek to further the molecular understanding of its aetiopathogenesis and the development of novel biomarkers. The present study investigated the expression levels of the glucogenic hormone asprosin [encoded by fibrillin-1 (FBN1)], and its cognate receptor, olfactory receptor 4M1 (OR4M1), in ovarian cancer. A blend of in silico open access The Cancer Genome Atlas data, as well as in vitro reverse transcription-quantitative PCR (RT-qPCR), immunohistochemistry and immunofluorescence data were used. RT-qPCR revealed expression levels of OR4M1 and FBN1 in clinical samples and in ovarian cancer cell lines (SKOV-3, PEO1, PEO4 and MDAH-2774), as well as the normal human ovarian surface epithelial cell line (HOSEpiC). Immunohistochemical staining of a tissue microarray was used to identify the expression levels of OR4M1 and asprosin in ovarian cancer samples of varying histological subtype and grade, including clear cell carcinoma, serous ovarian cancer and mucinous adenocarcinoma. Immunofluorescence analysis revealed asprosin expression in SKOV-3 and HOSEpiC cells. These results demonstrated the expression of both asprosin and OR4M1 in normal and malignant human ovarian tissues. This research invokes further investigation to advance the understanding of the role of asprosin and OR4M1 within the ovarian tumour microenvironment.

Differential Expression and Copy Number Variation of Gasdermin (GSDM) Family Members, Pore-Forming Proteins in Pyroptosis, in Normal and Malignant Serous Ovarian Tissue.

Gasdermins (GSDM) are members of a family of pore-forming effector proteins which lead to membrane permeabilization and pyroptosis, a lytic cell death with pro-inflammatory characteristics. Recently, two members of the gasdermin family, gasdermin B (GSDMB) and gasdermin E (GSDME), were shown to suppress tumor growth, through the involvement of cytotoxic lymphocytes. Other studies also reported the important functions of gasdermins in various cancer types including gastric cancer, hepatocarcinoma, and cervix and breast cancer. However, gasdermins have not been previously studied in the context of serous ovarian cancer. Here, we showed that gasdermin D (GSDMD) and gasdermin C (GSDMC) expression increases in serous ovarian cancer; in contrast, the expression of GSDME and PJVK (Pejvakin, DFNB59) is downregulated, compared to healthy ovaries, in multiple independent gene expression datasets. We found that copy number gains are highly frequent (present in approximately 50% of patients) in genes encoding GSDMD and GSDMC in ovarian cancer, in line with their upregulated expression in serous ovarian cancer. Moreover, we observed that the expression of GSDMB and GSDMD, but not of GSDME, is different among several histotypes of epithelial ovarian cancer. Therefore, we propose that differential expression and copy number variations of certain gasdermins might be associated with the development of serous ovarian cancer, in which different members of the family have distinct functions; however, further research is required in in vivo models to understand how changes in gasdermin family members mechanistically contribute to serous ovarian cancer.

Classical HLA class I antigen downregulation and abnormal HLA-G expression in ovarian cancer

Objective: To elucidate the potential role of HLA-G and classical HLA class I molecules in ovarian cancer, we researched their patterns of expression in benign and malignant ovarian tumors. Methods: In 10 benign and 33 malignant ovarian tumor tissues, HLA-G expression was determined both at the mRNA level by reverse transcriptase-polymerase chain reaction and immunohistochemical staining. The expression of classical HLA class I heavy chains were determined immunohistochemically. Results: Immunohistochemical analysis revealed the expression of HLA-G molecules in 27 of the 33 (81.8%) ovarian cancers but in none of the benign ovarian tumors. Classical HLA class I antigen expression was down-regulated in 25 out of the 33 (75.8%) ovarian cancers and in only 1 of the 10 benign ovarian tumors. HLA-G expression and classical HLA class I antigen down-regulation were related to disease stage (Spearman’s rho = 0.468, P = 0.001; Spearman’s rho = -0.392, P = 0.005). Conclusion: Our results reveal that abnormal expression of HLA-G and down-regulation of classical HLA class I antigen in ovarian cancer may be one of the mechanisms by which cancer cells may escape host’s immune system.

Detection and analysis of multiple biomarkers in ovarian cancer: clinical significance in diagnosis, treatment, and prognosis evaluation.

The purpose of this study was to explore the clinical significance of CA125, CK7, CK20, ER, PR, C-erbb2, and P-gp in ovarian cancer. Ovarian cancer patients were recruited from Nantong Cancer Hospital between March 2006 and July 2011. The expressions of CA125, CK7, CK20, ER, PR, C-erbb2, and P-gp were determined by immunohistochemistry (IHC).The chi-square test (χ2) was used to analyze the correlation between each index and the clinical characteristics of the patients. The patients were followed up to record the cancer recurrence time. The Kaplan-Meier method was used to map the cumulative recurrence-free survival (RFS) rate, and COX regression analysis was established for multivariate analysis. The results of IHC showed that the positive expression rates of CA125, CK7, ER, C-erbb2, and P-gp in malignant ovarian cancer tissues were significantly higher than those in benign ovarian cancer tissues. CA125 expression in malignant ovarian cancer was significantly correlated with the age of patients and the Federation of International Gynecology and Obstetrics (FIGO) stage. CK7 expression in malignant ovarian cancer was significantly correlated with the age, tissue differentiation, and number of residual lesions. CK20 expression in malignant ovarian cancer was significantly correlated with the age and tissue differentiation of the patients. ER expression in malignant ovarian cancer was significantly correlated with the age of patients and FIGO stage. PR expression in malignant ovarian cancer was significantly correlated with the age of the patients. C-erbb2 expression in malignant ovarian cancer was significantly correlated with the age of the patients. P-gp expression in malignant ovarian cancer was significantly correlated with the patient age, pathological type, and tissue differentiation. The expression of CA125, CK7, CK20, C-erbb2, and P-gp had significant effects on the prognosis of patients with ovarian cancer. The COX regression analysis showed that P-gp was an independent risk factor for ovarian cancer. In malignant ovarian cancer tissues, CA125, CK7, CK20, ER, PR, C-erbb2, and P-gp are over-expressed. The expression of P-gp is an independent risk factor for ovarian cancer, and it can be an important target for the treatment of malignant ovarian cancer.

Rapid identification of human ovarian cancer in second harmonic generation images using radiomics feature analyses and tree-based pipeline optimization tool.

Ovarian cancer is currently one of the most common cancers of the female reproductive organs, and its mortality rate is the highest among all types of gynecologic cancers. Rapid and accurate classification of ovarian cancer plays an important role in the determination of treatment plans and prognoses. Nevertheless, the most commonly used classification method is based on histopathological specimen examination, which is time-consuming and labor-intensive. Thus, in this study, we utilize radiomics feature extraction methods and the automated machine learning tree-based pipeline optimization tool (TOPT) for analysis of 3D, second harmonic generation images of benign, malignant and normal human ovarian tissues, to develop a high-efficiency computer-aided diagnostic model. Area under the receiver operating characteristic curve values of 0.98, 0.96 and 0.94 were obtained, respectively, for the classification of the three tissue types. Furthermore, this approach can be readily applied to other related tissues and diseases, and has great potential for improving the efficiency of medical diagnostic processes.

Optical Resolution Photoacoustic Microscopy of Ovary and Fallopian Tube

Ovarian cancer is the leading cause of death among gynecological cancers, but is poorly amenable to preoperative diagnosis. In this study, we investigate the feasibility of “optical biopsy,” using high-optical-resolution photoacoustic microscopy (OR-PAM) to quantify the microvasculature of ovarian and fallopian tube tissue. The technique is demonstrated using excised human ovary and fallopian tube specimens imaged immediately after surgery. Quantitative parameters are derived using Amira software. The parameters include three-dimensional vascular segment count, total volume and length, which are associated with tumor angiogenesis. Qualitative results of OR-PAM demonstrate that malignant ovarian tissue has larger and more tortuous blood vessels as well as smaller vessels of different sizes, while benign and normal ovarian tissue has smaller vessels of uniform size. Quantitative analysis shows that malignant ovaries have greater tumor vessel volume, length and number of segments, as compared with benign and normal ovaries. The vascular pattern of benign fallopian tube is different than that of benign ovarian tissue. Our initial results demonstrate the potential of OR-PAM as an imaging tool for fast assessment of ovarian tissue and fallopian tube and could avoid unnecessary surgery if the risk of the examined ovary is extremely low.

Role of a novel circulatory RNA-based biomarker panel expression in ovarian cancer.

Ovarian cancer (OC) is considered the sixth commonest cancer affecting women globally. We choose novel integrated specific ovarian cancer RNA biomarker panel; pellino E3 ubiquitin protein ligase family member 3 (PELI3) gene expressions along with its selected epigenetic regulators (microRNA (miR-361-3p) and long noncoding RNA (lncRNA RP5-837J1.2) by bioinformatic methods. Then, differential expressions of the selected panel in the sera of 50 OC patients, 42 cases with benign ovarian lesions, and among 45 controls were determined using real-time polymerase chain reaction quantitative (qRT-PCR). Furthermore, their expression was measured also in malignant ovarian tissues and adjacent nontumor tissues in 23 of 50 OC patients by quantitative qRT-PCR. The current study reported, for the first time, upregulation of serum lncRNA RP5-837J1.2 with concomitant downregulation of miR-361-3p and PELI3 mRNA in malignant group compared with benign and controls groups. There were associations of serum lncRNA RP5-837J1.2 with the affected ovary and worse International Federation of Gynecology and Obstetrics staging; associations of miR-361-3p with tumor size, grade, stage, and presence of metastasis; as well as associations among PELI3 mRNA expression and tumor size, grade, stage, and presence of metastasis among the OC group. In tumor tissues, miR-361-3p and PELI3 mRNA levels were at a higher level than that of nontumor tissues; however, tumor tissue showed lower level of lncRNA RP5-837J1.2 compared to normal tissue. There were positive correlations between serum and tissue level of RNA RP5-837J1.2, miR-361-3p, and PELI3 mRNA, but they did not reach statistical significance. Receiver operating characteristics curve analyses showed that lncRNA RP5-837J1.2, miR-361-3p, and PELI3 mRNA expression levels can discriminate among OC patient, cases with benign mass, and controls with an accuracy of 96, 76, and 83%, respectively; which increased if they are combined. This novel diagnostic RNA-based panel biomarker could be helpful for OC diagnosis.

Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples.

Ovarian cancer is a highly heterogeneous disease and its formation is affected by many epidemiological factors. It has typical lack of early signs and symptoms, and almost 70% of ovarian cancers are diagnosed in advanced stages. Robust, early and non-invasive ovarian cancer diagnosis will certainly be beneficial. Herein we analysed the regulatory sequence methylation profiles of the RASSF1, PTEN, CDH1 and PAX1 tumour suppressor genes by pyrosequencing in healthy, benign and malignant ovarian tissues, and corresponding plasma samples. We recorded statistically significant higher methylation levels (p < 0.05) in the CDH1 and PAX1 genes in malignant tissues than in controls (39.06 ± 18.78 versus 24.22 ± 6.93; 13.55 ± 10.65 versus 5.73 ± 2.19). Higher values in the CDH1 gene were also found in plasma samples (22.25 ± 14.13 versus 46.42 ± 20.91). A similar methylation pattern with positive correlation between plasma and benign lesions was noted in the CDH1 gene (r = 0.886, p = 0.019) and malignant lesions in the PAX1 gene (r = 0.771, p < 0.001). The random forest algorithm combining methylation indices of all four genes and age determined 0.932 AUC (area under the receiver operating characteristic (ROC) curve) prediction power in the model classifying malignant lesions and controls. Our study results indicate the effects of methylation changes in ovarian cancer development and suggest that the CDH1 gene is a potential candidate for non-invasive diagnosis of ovarian cancer.

HDAC3 positively regulates HE4 expression to promote ovarian carcinoma progression

ObjectiveTo identify the relationship between Histone deacetylase 3 (HDAC3) and Human epididymis protein 4 (HE4) and to explore the mechanisms underlying their effects on the malignant behaviors of ovarian carcinoma cells. MethodsThe expression levels of HDAC3 in ovarian carcinoma tissues were identified by immunohistochemistry, Western blot and real-time PCR. A wound healing assay, a Transwell assay and a CCK8 proliferation assay were used to assess the proliferation, invasion and metastatic capacities of ovarian carcinoma cells before and after transfection and HDAC3 protein treatment. HDAC3 and HE4 protein expression level in epithelial ovarian tissues were detected by immunohistochemistry, and the relationship between them was examined. ResultsHE4 was identified as an HDAC3-interacting protein. HDAC3 promotes ovarian carcinoma cell proliferation, invasion and migration by increasing the expression of HE4. HE4 and HDAC3 expression levels were significantly higher in malignant epithelial ovarian tissues than they were in benign and normal epithelial ovarian tissues. HDAC3 gene interference downregulated the expression of the PI3K/AKT signaling pathway-associated molecules P-PI3K/PI3K and P-AKT/AKT. ConclusionHDAC3 expression is higher in ovarian carcinoma and promotes ovarian carcinoma cell proliferation, invasion and migration. HDAC3 and HE4 binding activates the PI3K/AKT signaling pathway, enhances ovarian carcinoma and promotes ovarian carcinoma cell proliferation, invasion and migration. Therefore, inhibiting the relationship between HDAC3 and HE4 may therefore have potential therapeutic value in patients with ovarian carcinoma.

CD44v6 may influence ovarian cancer cell invasion and migration by regulating the NF-κB pathway.

Ovarian cancer (OC) has the worst prognosis among all malignancy types in females worldwide according to epidemiological studies in 2017. Although radiotherapy, chemotherapy and surgical treatment are the most common treatment methods, their curative effects are not satisfactory. The present study aimed to examine the role of cluster of differentiation 44 variant 6 (CD44v6) in the molecular mechanism of the proliferation and tumorigenicity of OC cells, and provide a novel target for the clinical treatment of OC. A total of 46 clinical samples were collected, including 24 malignant ovarian tumor tissue samples and 22 benign ovarian tissue samples. Expression of CD44v6 and nuclear factor-κB (NF-κB) in these samples was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry. The A2780 OC cell line was used to establish a normal control group, a negative control group and a CD44v6-small interfering (si)RNA transfection group. The expression of CD44v6 and NF-κB mRNA was detected in each group by RT-qPCR. The proliferation, invasion and migration abilities of the cells were then assessed by Transwell and colony formation assays. Additionally, immunofluorescence was used to detect nuclear NF-κB expression. CD44v6 and NF-κB mRNA expression levels were significantly increased in malignant ovarian tumor tissues, compared with normal ovarian tissues (P<0.01), and immunohistochemistry demonstrated similar results. In the CD44v6-siRNA group, NF-κB mRNA expression was significantly reduced, compared with the control and negative control (both P<0.01) groups. Transwell and colony formation assays demonstrated that the migration, invasion and colony formation abilities of OC cells in the CD44v6-siRNA group were significantly reduced, compared with the control and negative control (both P<0.01) groups. Immunofluorescence results demonstrated that the expression of NF-κB in the cytoplasm and nucleus of the CD44v6-siRNA group was also markedly reduced, compared with the other two groups. In conclusion, CD44v6 may participate in the proliferation of OC cells through activation of the NF-κB pathway and these observations may provide a novel therapeutic target for the clinical treatment of OC.