Biomarker For Ovarian Cancer Research Articles

"Silicon-On-Insulator"-Based Biosensor for the Detection of MicroRNA Markers of Ovarian Cancer.

Ovarian cancer is a gynecological cancer characterized by a high mortality rate and tumor heterogeneity. Its early detection and primary prophylaxis are difficult to perform. Detecting biomarkers for ovarian cancer plays a pivotal role in therapy effectiveness and affects patients' survival. This study demonstrates the detection of microRNAs (miRNAs), which were reported to be associated with ovarian cancer tumorigenesis, with a nanowire biosensor based on silicon-on-insulator structures (SOI-NW biosensor). The advantages of the method proposed for miRNA detection using the SOI-NW biosensor are as follows: (1) no need for additional labeling or amplification reaction during sample preparation, and (2) real-time detection of target biomolecules. The detecting component of the biosensor is a chip with an array of 3 µm wide, 10 µm long silicon nanowires on its surface. The SOI-NW chip was fabricated using the "top-down" method, which is compatible with large-scale CMOS technology. Oligonucleotide probes (oDNA probes) carrying sequences complementary to the target miRNAs were covalently immobilized on the nanowire surface to ensure high-sensitivity biospecific sensing of the target biomolecules. The study involved two experimental series. Detection of model DNA oligonucleotides being synthetic analogs of the target miRNAs was carried out to assess the method's sensitivity. The lowest concentration of the target oligonucleotides detectable in buffer solution was 1.1 × 10-16 M. In the second experimental series, detection of miRNAs (miRNA-21, miRNA-141, and miRNA-200a) isolated from blood plasma samples collected from patients having a verified diagnosis of ovarian cancer was performed. The results of our present study represent a step towards the development of novel highly sensitive diagnostic systems for the early revelation of ovarian cancer in women.

Plasma exosomal miR-320d, miR-4479, and miR-6763-5p as diagnostic biomarkers in epithelial ovarian cancer.

Exosomal miRNA had been proved as the promising biomarkers for multiple cancers including epithelial ovarian cancer (EOC). This study aimed to validate the diagnostic accuracy of exosomal miR-320d, miR-4479, and miR-6763-5p for EOC. Exosomes isolated from the plasma by ultracentrifugation were verified using TEM, qNano and western blot. MiRNAs sequencing was used to screen out the differential exosomal miRNAs and miR-320d, miR-4479, and miR-6763-5p were selected as candidates, which were further verified by RT-qPCR in 168 healthy donors and 161 primary EOC patients. Besides, the diagnostic accuracy of these three exosomal miRNAs were evaluated using the receiver operating characteristic curve (ROC). MiRNAs sequencing revealed 95 differential exosomal miRNAs between EOC patients and healthy donors. Subsequently, exosomal miR-320d, miR-4479, and miR-6763-5p were significantly down regulated in EOC patients compared with healthy controls and benign patients. More importantly, these three miRNAs could serve as circulating diagnostics biomarkers for EOC, possessing areas under the curve (AUC) of 0.6549, 0.7781, and 0.6834, respectively. Moreover, these three exosomal miRNAs levels were closely associated with lymph node metastasis, meanwhile exosomal miR-320d and miR-4479 expression was related to tumor stage. Exosomal miR-320d, miR-4479, and miR-6763-5p might serve as potential biomarkers for EOC.

Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model.

Serous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > Eb/Ea ≤ Eb) of gene pairs closely associated with serous ovarian prognosis, we tried constructing a potential individualized qualitative biomarker by the greedy algorithm and evaluated the performance in independent validation datasets. We constructed a prognostic biomarker consisting of 20 gene pairs (SOV-P20). The overall survival between high- and low-risk groups stratified by SOV-P20 was statistically significantly different in the training and independent validation datasets from other platforms (p < 0.05, Wilcoxon test). The average area under the curve (AUC) values of the training and three validation datasets were 0.756, 0.590, 0.630, and 0.680, respectively. The distribution of most immune cells between high- and low-risk groups was quite different (p < 0.001, Wilcoxon test). The low-risk patients tended to show significantly better tumor response to chemotherapy than the high-risk patients (p < 0.05, Fisher's exact test). SOV-P20 achieved the highest mean index of concordance (C-index) (0.624) compared with the other seven existing prognostic signatures (ranging from 0.511 to 0.619). SOV-P20 is a promising prognostic biomarker for serous ovarian cancer, which will be applicable for clinical predictive risk assessment.

Evaluation of the Diagnostic Potential of Circulating MicroRNAs miR-1 and miR-21 in Patients With Ovarian Cancer.

MicroRNA (miR) is implicated in the development of ovarian cancer (OC), the emergence of therapy resistance, and metastatic spread. In the past decade, a variety of relevant miRs have been identified in the context of OC, including miR-1 and miR-21. miR-21 plays a crucial role in OC carcinogenesis via activation of phosphatidylinositol-4,5-bisphosphate 3-kinase signaling and development of platinum resistance, and has prognostic value. miR-1 has been identified as a tumor suppressor across various cancer entities, with reduced expression in malignant tissue compared to benign. This evidence highlights the potential of miR-1 and miR-21 to serve as diagnostic and prognostic biomarkers in OC. We studied the diagnostic potential of serum expression of miR-1 and miR-21 in a cohort comprising patients with malignant and benign ovarian tumors. Furthermore, levels of miR expression were analyzed with regard to clinical outcomes in patients with malignant ovarian tumors to evaluate their prognostic value. We identified significant differential expression of miR-1 (p=0.0397) and miR-21 (p=0.0154) in malignant and benign ovarian tumors: Higher expression of miR-1 was found in patients with benign ovarian tumors, whereas expression of miR-21 was higher in patients with malignant ovarian tumors. In receiver operating characteristic analyses, the diagnostic potential of both miRs was confirmed, however, diagnostic significance was inferior to that of cancer antigen 125. No further value, in particular no prognostic value, was obtained for miR-1 and miR-21 in patients with malignant ovarian tumors. Serum levels of miR-1 and miR-21 might serve as promising biomarkers in the diagnosis of ovarian cancer.

Prognostic biomarker MCP-4 triggers epithelial-mesenchymal transition via the p38 MAPK pathway in ovarian cancer.

Monocyte chemoattractant protein-4 (MCP-4/CCL13) is a proinflammatory factor that is overexpressed in various malignant tumors and may play an important role in tumor progression and metastasis. However, its role and mechanism of action in ovarian cancer remains unknown. Immunohistochemistry (IHC) was performed to detect the expression of MCP-4 in ovarian cancer tissues, and the effect of MCP-4 on patient survival and prognosis was analyzed. Overexpression and suppression of MCP-4 in ovarian cancer cell lines were then established, and their effects on cell invasion, migration, and apoptosis were studied. ES-2 cell lines were employed to establish a peritoneal dissemination model in nude mice. Western blotting was performed to detect the expression of epithelial mesenchymal transition (EMT) markers and the p38 mitogen-activated protein kinase (p38 MAPK) signaling pathway. MCP-4 was highly expressed in ovarian cancer tissues and its expression level was related to the prognosis of patients with ovarian cancer. MCP-4 overexpression promoted the migration and invasion of ovarian cancer cells but inhibited apoptosis. MCP-4 overexpression increased the expression of MMP-2, MMP-9, N-cadherin, vimentin and Bcl2/Bax and decreased the expression of E-cadherin. MCP-4 overexpression increased the phosphorylation of the p38 MAPK pathway. The inhibition of MCP-4 expression indicated an opposite trend. In vivo experiments have also confirmed that MCP-4 overexpression can promote metastasis of ovarian cancer. MCP-4 promotes ovarian cancer progression through the p38 MAPK signaling pathway, and may be a potential biomarker and therapeutic target for ovarian cancer.

Mitochondrial AAA protease gene associated with immune infiltration is a prognostic biomarker in human ovarian cancer.

Early diagnosis and identification of prognostic markers for ovarian cancer can significantly improve survival and reduce mortality. The role of the YME1L1 signaling axis in genetic alterations and immune infiltration of the tumor microenvironment remains unclear. Bioinformatics web resources, including GEPIA2, cBioPortal, Oncomine, Kaplan-Meier Plotter, and TIMER, were used to analyze the expression profile, prognostic value, and immune infiltration of YME1L1. We further performed a tissue microarray analysis of paraffin-embedded tissues from 60 patients with ovarian cancer, recorded at the FIGO/TNM cancer staging. Here, we used multi-omics analysis of multiple histological datasets to map the role of epigenetic and genetic alterations of YME1L1 in tumor immune infiltration and the prognosis of cancer patients. We explored YME1L1 gene expression profiles by systematically analyzing the association between YME1L1 expression and the prognosis of patients with ovarian cancer confirmed in multiple databases. High expression levels of YME1L1 were associated with poor overall and disease-free survival. Together, our studies suggest that YME1L1 may modulate tumor survival and immune features and contribute to tumor immune invasion, poor prognosis, and immunotherapy failure. Our findings may have clinical implications for the design of treatment strategies, prognosis assessment, and follow-up management of patients receiving immunotherapy for various cancers.

Epithelial Membrane Protein 1 is a Potential Prognostic Biomarker for Ovarian Cancer

Background: Epithelial membrane protein 1 (EMP1) is a cell junction protein located in the plasma membrane. The function of EMP1 in cancer cells varies in different tumour types. In the present study we investigated the expression of EMP1 and its clinical significance in ovarian cancer. Methods: Sequencing data from the Cancer Genome Atlas (TCGA) and from several other public databases was used to study the expression of EMP1 and its gene regulation networks in ovarian cancer patients. Oncomine and Gene Expression Profiling Interactive Analysis tools (GEPIA) were used to evaluate EMP1 expression. EMP1 alterations were identified using cBioPortal and the prognostic value of EMP1 was assessed using Kaplan-Meier analysis and OncoLnc online tools. Genes that were co-expressed with EMP1 were identified using LinkedOmics and the Link-Interpreter module was used to analyse pathway enrichment and the possible functions of co-expressed genes. Results: EMP1 was highly expressed in ovarian cancer and was associated with advanced tumour stage and poor overall survival (OS). Amplification of the EMP1 gene was also common in ovarian cancer. EMP1 participates mainly in the biological processes of epidermal development, cell adhesion, peptidyl tyrosine modification and angiogenesis. Functional network analysis suggests that EMP1 regulates tumorigenesis and progression of ovarian cancer through different signalling pathways that include several kinases, microRNAs (miRNAs) and transcription factors related to tumorigenesis. Conclusions: This study confirmed the expression of EMP1 in ovarian cancer and elucidated its regulatory networks, thus providing a theoretical basis for further studies into its functions. EMP1 could potentially serve as a diagnostic and prognostic biomarker in ovarian cancer patients. However, owing to the limited sample size and range of experimental work, further validation studies are needed to confirm the role of EMP1 in ovarian cancer.

Mucin 13 (MUC13) as a candidate biomarker for ovarian cancer detection: potential to complement CA125 in detecting non-serous subtypes.

Ovarian cancer is the most lethal gynecological malignancy in developed countries. One of the key associations with the high mortality rate is diagnosis at late stages. This clinical limitation is primarily due to a lack of distinct symptoms and detection at the early stages. The ovarian cancer biomarker, CA125, is mainly effective for identifying serous ovarian carcinomas, leaving a gap in non-serous ovarian cancer detection. Mucin 13 (MUC13) is atransmembrane, glycosylated protein with aberrant expression in malignancies, including ovarian cancer. We explored the potential of MUC13 to complement CA125 as an ovarian cancer biomarker, by evaluating its ability to discriminate serous and non-serous subtypes of ovarian cancer at FIGO stages I-IV from benign conditions. We used our newly developed, high sensitivity ELISA to measure MUC13 protein in a large, well-defined cohort of 389 serum samples from patients with ovarian cancer and benign conditions. MUC13 and CA125 serum levels were elevated in malignant compared to benign cases (p<0.0001). Receiver-operating characteristic (ROC) curve analysis showed similar area under the curve (AUC) of 0.74 (MUC13) and 0.76 (CA125). MUC13 concentrations were significantly higher in mucinous adenocarcinomas compared to benign controls (p=0.0005), with AUC of 0.80. MUC13 and CA125 showed significant elevation in early-stage cases (stage I-II) in relation to benign controls (p=0.0012 and p=0.014, respectively). We report the novel role of MUC13 as a serum ovarian cancer biomarker, where it could complement CA125 for detecting some subtypes of non-serous ovarian carcinoma and early-stage disease.

Hormone Receptor Expression in Primary and Recurrent High-Grade Serous Ovarian Cancer and Its Implications in Early Maintenance Treatment.

Endocrine therapy is an effective treatment for low-grade serous ovarian cancer. However, the role of estrogen and progesterone receptors as biomarkers for high-grade serous ovarian cancer (HGSOC) is yet to be elucidated because not all estrogen and progesterone receptor-positive tumors benefit from anti-estrogen therapy. The degree of expression is presumed to play a vital role; however, that role is not well-defined in ovarian cancer. We aimed to determine the role of estrogen and progesterone receptor expression in primary and paired relapsed HGSOC. In this study, primary and matched relapsed tumor samples were collected from 80 patients with International Federation of Gynecology and Obstetrics Stage II-IV HGSOC. Tissue microarray was conducted and immunohistochemistry for estrogen and progesterone receptor expression was performed. Two independent pathologists performed the tissue microarray analysis with the Immunoreactive Score and Allred Total score. In the paired analysis, no significant difference in estrogen receptor expression was observed. However, progesterone receptor expression was significantly lower in patients with recurrent platinum-sensitive HGSOC. We conclude that anti-estrogen therapy targeting estrogen receptor positive HGSOC could be administered in primary and relapsed settings. The use of endocrine maintenance with an aromatase inhibitor in patients with estrogen receptor positive HGSOC needs to be further evaluated and validated in a randomized controlled trial.

Nanobodies for the Early Detection of Ovarian Cancer.

Ovarian cancer ranks fifth in cancer-related deaths among women. Since ovarian cancer patients are often asymptomatic, most patients are diagnosed only at an advanced stage of disease. This results in a 5-year survival rate below 50%, which is in strong contrast to a survival rate as high as 94% if detected and treated at an early stage. Monitoring serum biomarkers offers new possibilities to diagnose ovarian cancer at an early stage. In this study, nanobodies targeting the ovarian cancer biomarkers human epididymis protein 4 (HE4), secretory leukocyte protease inhibitor (SLPI), and progranulin (PGRN) were evaluated regarding their expression levels in bacterial systems, epitope binning, and antigen-binding affinity by enzyme-linked immunosorbent assay and surface plasmon resonance. The selected nanobodies possess strong binding affinities for their cognate antigens (KD~0.1-10 nM) and therefore have a pronounced potential to detect ovarian cancer at an early stage. Moreover, it is of utmost importance that the limits of detection (LOD) for these biomarkers are in the pM range, implying high specificity and sensitivity, as demonstrated by values in human serum of 37 pM for HE4, 163 pM for SLPI, and 195 pM for PGRN. These nanobody candidates could thus pave the way towards multiplexed biosensors.

Systematic Pan-Cancer Analysis and Experimental Verification Identify FOXA1 as an Immunological and Prognostic Biomarker in Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) has the lowest survival rate among female reproductive cancers present with symptoms of aggressive malignancies, poor prognosis, drug resistance and postoperative recurrence. The majority of patients with EOC are diagnosed at an advanced stage due to the therapeutic challenges including lack of early diagnosis and effective therapeutic targets for EOC. Pan-cancer analyses were performed to explore the features of forkhead-box (FOX) A1 (FOXA1) using data from TCGA and GTEx databases. R package "clusterprofiler" was used to perform the enrichment analysis of FOXA1 in EOC. Data downloaded from Drug Sensitivity in Cancer (GDSC) database were used to evaluate the association between FOXA1 and antitumor drug sensitivity. In experimental verification, FOXA1 expression was detected using qRT-PCR and western blot assays. Western blot, immunofluorescence staining, and Transwell assays were used to assess the influence of FOXA1 silencing on epithelial-mesenchymal transition (EMT) of EOC cells. We found that FOXA1 was highly expressed in EOC and predicted poorer survival of EOC patients. We observed that FOXA1 expression was positively correlated EMT-related pathways. Through experimental verification, we found the underlying function of FOXA1 to promote EMT in ovarian cancers. The results from western blot, immunofluorescence staining, and Transwell assays showed that FOXA1 silencing impeded the progression of EMT and invasiveness of the cancer cells. Furthermore, CCK-8 and invasion assays suggested that siRNA-FOXA1 attenuated the ability of cancer cells to metastasize and proliferate. Dual-luciferase reporter assays confirmed the binding activity of FOXA1 to the promoter of connective tissue growth factor (CTGF). In addition, we found that FOXA1 was closely correlated immunosuppressive microenvironment of EOC. High FOXA1 expression may contribute to the resistance of many anticancer drugs. Our results predict and validate the function of FOXA1 in promoting EMT and the progression of disease in EOC. Targeting FOXA1 may improve the sensitivity of EOC treatment.

Utility of Matrix Metalloproteinases in the Diagnosis, Monitoring and Prognosis of Ovarian Cancer Patients.

Ovarian cancer is one of the most common gynecologic malignancies. It is characterized by a high mortality rate, which is mainly due to the asymptomatic course of the disease. In light of the high mortality rate and increasing morbidity, new diagnostic methods are being explored to enable earlier detection, better monitoring, and improved prognosis. Such diagnostic methods include the assessment of tumor markers in various biological samples. Among the markers currently being investigated, extracellular matrix metalloproteinases (MMPs) are of particular interest. The objective of this article was to compile the existing knowledge of MMPs in ovarian cancer patients and to describe their potential diagnostic utility. Additionally, this article provides an overview of the symptoms, complications, and risk factors associated with ovarian cancer and the role of MMPs in physiology and pathology. Preliminary results indicate that tissue expression and blood and body fluid levels of MMPs may be different in ovarian cancer patients than in healthy women. The expression and concentration of individual MMPs have been shown to be correlated with cancer stage and disease severity. In addition, the preliminary value of some of these enzymes in predicting prognosis is discussed. However, as the amount of data is limited, more studies are needed to fully evaluate the potential function of individual MMPs in ovarian cancer patients. Based on the knowledge gathered for this article, it seems that MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-13, are tentatively the most useful. A thorough evaluation of their utility as modern biomarkers in ovarian cancer requires further investigation.

BDP1 as a biomarker in serous ovarian cancer.

TFIIIB, an RNA polymerase III specific transcription factor has been found to be deregulated in human cancers with much of the research focused on the TBP, BRF1, and BRF2 subunits. To date, the TFIIIB specific subunit BDP1 has not been investigated in ovarian cancer but has previously been shown to be deregulated in neuroblastoma, breast cancer, and Non-Hodgkins lymphoma. Using in silico analysis of clinically derived platforms, we report a decreased BDP1 expression as a result of deletion in serous ovarian cancer and a correlation with higher and advanced ovarian stages. Further analysis in the context of TP53 mutations, a major contributor to ovarian tumorigenesis, suggests that high BDP1 expression is unfavorable for overall survival and high BDP1 expression occurs in stages 2, 3 and 4 serous ovarian cancer. Additionally, high BDP1 expression is disadvantageous and unfavorable for progression-free survival. Lastly, BDP1 expression significantly decreased in patients treated with first-line chemotherapy, platin and taxane, at twelve-month relapse-free survival. Taken together with a ROC analysis, the data suggest BDP1 could be of clinical relevance as a predictive biomarker in serous ovarian cancer. Lastly, this study further demonstrates that both the over- and under expression of BDP1 warrants further investigation and suggests BDP1 may exhibit dual function in the context of tumorigenesis.

Gene co-expression network analysis revealed novel biomarkers for ovarian cancer.

Ovarian cancer is the second most common gynecologic cancer and remains the leading cause of death of all gynecologic oncologic disease. Therefore, understanding the molecular mechanisms underlying the disease, and the identification of effective and predictive biomarkers are invaluable for the development of diagnostic and treatment strategies. In the present study, a differential co-expression network analysis was performed via meta-analysis of three transcriptome datasets of serous ovarian adenocarcinoma to identify novel candidate biomarker signatures, i.e. genes and miRNAs. We identified 439 common differentially expressed genes (DEGs), and reconstructed differential co-expression networks using common DEGs and considering two conditions, i.e. healthy ovarian surface epithelia samples and serous ovarian adenocarcinoma epithelia samples. The modular analyses of the constructed networks indicated a co-expressed gene module consisting of 17 genes. A total of 11 biomarker candidates were determined through receiver operating characteristic (ROC) curves of gene expression of module genes, and miRNAs targeting these genes were identified. As a result, six genes (CDT1, CNIH4, CRLS1, LIMCH1, POC1A, and SNX13), and two miRNAs (mir-147a, and mir-103a-3p) were suggested as novel candidate prognostic biomarkers for ovarian cancer. Further experimental and clinical validation of the proposed biomarkers could help future development of potential diagnostic and therapeutic innovations in ovarian cancer.

PDP1 Promotes Cell Malignant Behavior and Is Associated with Worse Clinical Features in Ovarian Cancer Patients: Evidence from Bioinformatics and In Vitro Level.

PDP1 has been reported in multiple diseases. However, it has not been fully explored in ovarian cancer (OC). The public data was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed gene analysis was conducted out using the limma package. Prognosis analysis was performed using the survival package. Gene Set Enrichment Analysis (GSEA) was performed using the fgsea package. Immune infiltration analysis was performed based on the CIBERSORT algorithm. CCK8 assay was used to evaluate the cell proliferation ability of cancer cells. Transwell assay was used for the invasion and migration ability. Our result showed that PDP1 was overexpressed in OC tissue in RNA and protein level based on multiple databases (TCGA, GSE18520, GSE27651, and GSE54388). At the same time, we found PDP1 was correlated with poor prognosis and worse clinical parameters. In vitro experiment showed that PDP1 could significantly promote proliferation, invasion, and migration ability of OC cells. GSEA analysis showed that in the OC patients with high PDP1 expression, the pathway of IL6/JAK/STAT3 signaling, interferon-alpha response, apoptosis, adipogenesis, KRAS signaling, and IL2/STAT5 signaling was activated, which might be responsible for its oncogenic effect in OC. Immune infiltration analysis indicated that PDP1 was positively correlated with activated myeloid dendritic cells, resting CD4 memory T cells, neutrophil, and M1 and M2 macrophages, yet negatively correlated with M0 macrophages, plasma B cells, γδT cells, and activated CD4 memory T cells. Drug sensitivity analysis showed a negative correlation between PDP1 expression and the IC50 of bleomycin and gemcitabine, yet a positive correlation of cisplatin, indicating that the OC patients with high PDP1 expression might be more sensitive to bleomycin and gemcitabine and more resistant to cisplatin. PDP1 could facilitate OC progression and is associated with patient prognosis and chemosensitivity, making it an underlying biomarker of OC.

ALG3 Promotes Peritoneal Metastasis of Ovarian Cancer through Increasing Interaction of α1,3-mannosylated uPAR and ADAM8.

Peritoneal metastasis is the main cause of poor prognoses and high mortality in ovarian cancer patients. Abnormal protein glycosylation modification is associated with cancer malignancy. Elevated α1,3-mannosyltransferase 3 (ALG3), which catalyzes the α1,3-mannosylation of glycoproteins, has been found in some malignant tumors. However, the pathological significance of ALG3 and its regulatory mechanism in ovarian cancer metastasis is unclear. The results showed that the level of ALG3/α1,3-mannosylation was higher in human ovarian cancer tissues compared with normal ovarian tissues, as measured by Lectin chip, Western blot and Lectin blot analyses, as well as ovarian tissue microarray analysis. ALG3 was also correlated with the poor prognosis of ovarian cancer patients, according to survival analysis. The downregulation of ALG3 decreased the proliferation, stemness and peritoneal metastasis of ovarian cancer cells. The increase in urokinase plasminogen activator receptor (uPAR) α1,3-mannosylation catalyzed by ALG3 enhanced urokinase plasminogen activator (uPA)/uPAR activation and the interaction of uPAR with a disintegrin and metalloproteinase 8 (ADAM8), which promoted ovarian cancer peritoneal metastasis via the ADAM8/Ras/ERK pathway. Furthermore, decreased ALG3 suppressed ascites formation and the peritoneal metastasis of ovarian cancer cells in mice. This study highlights ALG3 as a potential diagnostic biomarker and prospective therapeutic target for ovarian cancer.

Homologous Recombination Deficiency as an Ovarian Cancer Biomarker in a Real-World Cohort: Validation of Decentralized Genomic Profiling

The diagnostic evaluation of homologous recombination deficiency (HRD) is central to define targeted therapy strategies for patients with ovarian carcinoma. We evaluated HRD in 514 ovarian carcinoma samples by next-generation sequencing of DNA libraries, including BRCA1/BRCA2 and 26,523 single-nucleotide polymorphisms using the standardized Myriad HRD assay, with the predefined cut point of ≥42 for a positive genomic instability score (GIS). All samples were measured in the central Myriad laboratory and in an academic molecular pathology laboratory. A positive GIS was detected in 196 (38.1%) of tumors, whereas 318 (61.9%) were GIS negative. Combining GIS and BRCA mutations, a total of 200 (38.9%) of the 514 tumors were HRD positive. A positive GIS was significantly associated with high-grade serous histology (P<0.000001), grade 3 tumors (P=0.001), and patient age <60 years (P=0.0003). The concordance between both laboratories for the GIS status was 96.9% (P<0.000001), with a sensitivity of 94.6% and a specificity of 98.4%. Concordance for HRD status was 97.1% (499 of 514 tumors). The percentage of HRD-positive tumors in our real-life cohort was similar to the proportion observed in the recently published PAOLA-1 trial, with high concordance between central and local laboratories. Our results support introduction of the standardized HRD assay in academic molecular pathology laboratories, thus broadening access to personalized oncology strategies for patients with ovarian cancer worldwide.

Rational design of near-infrared ratiometric fluorescent probes for real-time tracking of β-galactosidase in vivo

β-Galactosidase (β-gal) is a hydrolytic enzyme in lysosomes and is also an important biomarker of cellular senescence and primary ovarian cancer. Therefore, real-time non-invasive detection of β-gal activity in vivo is of great significance for the prevention of cell senescence and early diagnosis of ovarian cancer. We designed an enzyme-activated proportional near-infrared (NIR) probe (Gal-Br-NO2) for real-time fluorescence quantification and capture of β-gal activity in vivo. The main characteristics of the Gal-Br-NO2 probe include short response time (less than 10 min), large Stokes displacement (155 nm), and near-infrared fluorescence emission (670 nm). The probe has also been successfully used to detect β-gal in ovarian cancer cells and senile cells and can accurately detect endogenous β-gal in zebrafish. Our work provides a potential tool for pre-clinical real-time tracking of β-gal activity in vivo and early diagnosis of disease.

Engineered water-soluble photosensitive fluorescent probes of β-galactosidase with fast response based on triarylboron compound derivatives for ovarian cancer cell imaging

β-Galactosidase is a primary biomarker for ovarian cancer, which poses a serious threat to the health of women. Herein, we report the design and synthesis of three fluorescent probes for β-galactosidase based on triarylboron (TAB): TAB-2-Gal, TAB-4-Gal, and TAB-6-Gal. The performance of these probes was tuned by changing their structure. They demonstrate excellent water solubility and fast responses, superior to most of the previously reported properties of existing β-galactosidase probes. In particular, using TAB-4-Gal the entire recognition process can be completed within 4 min and this probe produces the greatest fluorescence signal. As TAB-4-Gal possesses a piperazine group in its structure, it better able to locate lysosomes and produces a strong fluorescence signal from ovarian cancer cells. Thus, it is an ideal fluorescent probe for distinguishing ovarian cancer cells from other cells. Moreover, the high photosensitivity of TAB-4-Gal means that it can also selectively induce apoptosis of ovarian cancer cells under low-intensity visible light irradiation (1.5 mW/cm2).

Black phosphorus nanosheets/poly(allylamine hydrochloride) based electrochemical immunosensor for the selective detection of human epididymis protein 4

In this work, an electrochemical immunosensor based on black phosphorus nanosheets (BPNS)/poly(allylamine hydrochloride) (PAH) nanocomposite modified glassy carbon electrode was developed for the detection of ovarian cancer biomarker HE4. PAH has been applied to retain BPNS in its original honeycomb structure and to anchor biomolecules electrostatically on the transducer surface. The as synthesized nanocomposite was characterized by zeta potential analysis, scanning electron microscopy, x-ray photoelectron spectroscopy, transmission electron microscopy, high-resolution transmission electron microscopy. Subsequently, the performance of the electrochemical immunosensor was evaluated through cyclic voltammetry, differential pulse voltammetry and electrochemical impedance spectroscopy. Under the optimal condition, the developed electrochemical immunosensor permitted to detect HE4 with a linear range of 0.1–300 ng ml−1 and a detection limit of 0.01 ng ml−1. The developed sensor exhibited good selectivity and specificity to HE4 with negligible interference effect from common biomolecules like bovine serum albumin, lysozyme, protamine, glucose, fructose, hemoglobin and fetal bovine serum. Further, practical application of developed electrochemical immunosensor was demonstrated in spiked human serum which showed satisfactory recovery percentages.