Diagnostic Biomarker For Ovarian Cancer Research Articles

TMEM158, as plasma cfRNA marker, promotes proliferation and doxorubicin resistance in ovarian cancer.

The current study aimed to identify the potential biomarker for the diagnosis of ovarian cancer within plasma cell-free RNA (cfRNA) species and to characterize their oncogenic properties. cfRNAs were isolated from the peripheral blood of ovarian cancer patients and sequenced using an NGS platform. Principal component analysis (PCA) was performed using Salmon software. Gene ontology (GO) analysis was conducted with clusterProfiler. The relative abundance of TMEM158 transcripts was determined by real-time PCR. Cell viability and proliferation was monitored using the MTT and cell counting assays, respectively. The protein levels of TMEM158 and ABCG2 were quantified by immunoblotting. We observed a clear separation of cfRNAs between ovarian cancer patients and healthy individuals. Additionally, we identified TMEM158 as the most significantly differential gene in both peripheral blood and tumor tissues. Overexpression of TMEM158 stimulated cell viability and promoted cell proliferation in ovarian cancer cells. Notably, the aberrant upregulation of TMEM158 was closely associated with doxorubicin resistance in ovarian cancer. Mechanistically, we demonstrated that TMEM158 positively regulates ABCG2 expression, which consequently contributes to drug resistance. In summary, we identified cfRNA TMEM158 as a potential diagnostic biomarker for ovarian cancer and elucidated the critical involvement of TMEM158-ABCG2 signaling axis in the development of doxorubicin resistance.

SLC7A5 regulates tryptophan uptake and PD‑L1 expression levels via the kynurenine pathway in ovarian cancer.

Ovarian cancer is the third most common gynecological malignancy worldwide and the fifth leading cause of cancer-related death among women. This may be attributed to difficulties in diagnosing early-stage ovarian cancer, as it is typically asymptomatic until metastases, and due to the ineffective management of patients with late-stage ovarian cancer. The aim of the present study was to investigate potential therapeutic targets for the treatment of ovarian cancer. Bioinformatics techniques were used to analyze the expression levels of tryptophan (Trp) metabolism-related genes in tissue samples from patients with ovarian cancer. Additionally, western blots, clonogenic assays, immunohistochemical staining, chromatin immunoprecipitation-quantitative PCR, cell co-culture assays, a xenograft model and high-performance liquid chromatography-tandem mass spectrometry were performed to evaluate the antitumor effects of genes identified from the bioinformatics analysis. Increased expression levels of the amino acid transporter, solute carrier family 7 member 5 (SLC7A5), in tissue samples from patients with ovarian cancer was demonstrated. Inhibition of SLC7A5 reduced ovarian cancer cell proliferation through G2/M cell cycle arrest and blocked intracellular aryl hydrocarbon receptor nucleus entry, which downregulated PD-L1 expression levels. Dysregulation of Trp metabolism in ovarian cancer tissue samples, as well as the upregulation of kynurenine expression levels in the plasma of patients with ovarian cancer, were demonstrated to be unfavorable prognostic factors for the progression-free survival of patients with ovarian cancer. The present study demonstrated that the dysregulation of Trp metabolism could potentially be used as a diagnostic biomarker for ovarian cancer, as well as the potential of targeting SLC7A5 for immunotherapeutic management of patients with ovarian cancer in the future.

Abstract B048: Evaluating the impact of pulmonary diseases on the use of microRNAs as biomarkers for early detection of ovarian cancer

Abstract B048: Evaluating the impact of pulmonary diseases on the use of microRNAs as biomarkers for early detection of ovarian cancer

Serum hsa_circ_0007534 as a diagnostic biomarker for ovarian cancer.

To investigate the implications of serum hsa_circ_0007534 levels in ovarian cancer (OC) patients. A retrospective analysis was conducted on the clinical data of 102 OC patients, and 102 healthy controls (HCs) were included in this study. Serum levels of hsa_circ_0007534 were measured using qPCR. The relationship between circRNA levels and clinicopathologic characteristics was analyzed. Additionally, the diagnostic performances of serum hsa_circ_0007534 and CA-125 levels in OC patients were evaluated using Receiver Operating Characteristic (ROC) curve analyses. OC patients had significantly elevated serum hsa_circ_0007534 levels compared to HCs, allowing a differentiation between OC patients and HCs. Higher serum hsa_circ_0007534 levels were associated with more aggressive disease features and poorer overall survival. Patients with elevated hsa_circ_0007534 levels tended to have worse clinical outcome compared to those with lower levels. Multivariate analyses indicated that high hsa_circ_0007534 levels were independently associated with poorer outcome. Furthermore, serum hsa_circ_0007534 levels effectively distinguished between chemoresistant and chemosensitive patient groups. Serum hsa_circ_0007534 levels may serve as valuable predictors of prognosis in OC patients.

MiR‑146a‑5p and miR‑191‑5p as novel diagnostic marker candidates for ovarian clear cell carcinoma.

Ovarian cancer is a malignant gynecologic disease rarely diagnosed in the early stages. Among the various types of ovarian cancer, clear cell carcinoma has a poor prognosis due to its malignant potential. MicroRNAs (miRNAs/miRs) regulate gene expression in cells by suppressing the translation of target genes or by degrading the target mRNA. miRNAs are also secreted from the cells in the blood, binding to proteins or lipids and assisting in cell-cell communication. Therefore, serum miRNAs may be considered potential diagnostic biomarkers for ovarian cancer. The present study investigated and identified specific miRNAs associated with ovarian clear cell carcinoma and compared them to those in ovarian endometrioma samples and healthy controls. CA125, an ovarian tumor marker, did not differ between patients with ovarian clear cell carcinoma, endometriosis or healthy controls. Subsequently, four miRNAs (miR-146a-5p, miR-191-5p, miR-484 and miR-574-3p) were analyzed. The expression levels of miR-146a-5p and miR-191-5p were significantly increased in the serum samples from patients with ovarian clear cell carcinoma compared with those in the healthy controls, but there was no significant difference compared with in patients with endometriosis. Furthermore, the bioinformatics analysis showed that CCND2 and NOTCH2 were the candidate target genes of miR-146a-5p and miR-191-5p. In conclusion, the results of the present study demonstrated that miR-146a-5p and miR-191-5p may be useful as early and non-invasive diagnostic tools in ovarian clear cell carcinoma. These miRNAs can help in distinguishing between ovarian clear cell carcinoma and ovarian endometrioma. To the best of our knowledge, no previous studies have screened any candidates specifically for ovarian clear cell carcinoma.

Insulin-like growth factor 2 mRNA-binding protein 2 is a therapeutic target in ovarian cancer.

Ovarian cancer (OC) is a fatal gynecologic disease. The most common treatment for OC patients is surgery combined with chemotherapy but most patients at advanced stages eventually develop relapse due to chemoresistance. This study examined the role and function of insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) in OC. We observed that the expression of IGF2BP2 mRNA and protein was up-regulated in OC cells and tissues using quantitative real-time polymerase chain reaction (qRT-PCR) and western blot, respectively. An increase in IGF2BP2 expression at mRNA and protein levels was verified by the analyses of The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), respectively. Gene Expression Omnibus (GEO) and Cancer Cell Line Encyclopedia (CCLE) databases were applied to analyze the expression and clinical value of IGF2BP2. Gene set enrichment analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) analyses explored biological functions and the involvement of IGF2BP2 in cell growth. Indeed, the knockdown of IGF2BP2 resulted in the inhibition of OC cell proliferation evaluated by the Cell Counting Kit-8 assay. Genomic amplification of IGF2BP2 partly accounted for its overexpression. High expression of IGF2BP2 was associated with signal transducer and activator of transcription 1 (STAT1) and drug sensitivity and was correlated with an unfavorable survival outcome in OC patients. Furthermore, the responsiveness of chemotherapy and immunotherapy were analyzed using the "pRRophetic" R package and The Cancer Immune Atlas (TCIA) database, respectively. The low expression of IGF2BP2 was associated with chemoresistance but with high tumor microenvironment scores and tumor-infiltrating immune cells, suggesting that immunotherapy may apply in chemoresistant patients. The alteration of IGF2BP2 expression may respond to chemotherapy and immunotherapy. Thus, IGF2BP2 shows potential as a therapeutic target and diagnostic biomarker for OC.

A Dual Biomarker TK1 Protein and CA125 or HE4-Based Algorithm as a Better Diagnostic Tool than ROMA Index in Early Detection of Ovarian Cancer

The early detection of ovarian cancer is presently not effective, and it is crucial to establish biomarkers for the early diagnosis of ovarian cancer to improve the survival of patients. The aim of this study was to investigate the role of thymidine kinase 1 (TK1) in combination with CA 125 or HE4 to serve as a potential diagnostic biomarkers for ovarian cancer. In this study, a set of 198 serum samples consisting of 134 ovarian tumor patients and 64 healthy age-matched controls were analyzed. The TK1 protein levels in serum samples were determined using the AroCell TK 210 ELISA. A combination of TK1 protein with CA 125 or HE4 showed better performance than either of them alone in the differentiation of early stage ovarian cancer from the healthy control group, but also a significantly better performance than the ROMA index. However, this was not observed using a TK1 activity test in combination with the other markers. Furthermore, the combination of TK1 protein and CA 125 or HE4 could differentiate early stage disease (stage I, II) more efficiently from advanced-stage (stage III, IV) disease (p < 0.0001). The combination of TK1 protein with CA 125 or HE4 increased the potential of detecting ovarian cancer at early stages.

Urine CA125 and HE4 for the Detection of Ovarian Cancer in Symptomatic Women.

The symptoms of ovarian cancer are vague, and current risk assessment tools such as serum CA125 and transvaginal ultrasound scan fail to reliably detect the disease early. This study aimed to evaluate urine CA125 and HE4 as diagnostic biomarkers for ovarian cancer in symptomatic women. Paired urine and serum samples were collected from women undergoing treatment for ovarian cancer (cases) or investigations for gynaecological symptoms (controls). Biomarkers were measured using an automated chemiluminescent enzyme immunoassay analyser. Standard diagnostic accuracy metrics were calculated. In total, 114 women were included, of whom 17 (15%) were diagnosed with an epithelial ovarian malignancy. Levels of urine CA125 and HE4 were significantly elevated in women with ovarian cancer compared to controls [CA125: 8.5 U/mL (IQR: 2.4-19.5) vs. 2.3 U/mL (IQR: 1.0-6.4), p = 0.01. HE4: 12.0 nmol/L (IQR: 10.3-23.1) vs. 6.7 nmol/L (IQR: 3.4-13.6), p = 0.006]. Urine CA125 and HE4 detected ovarian cancer with an AUC of 0.69 (95% CI: 0.55-0.82) and 0.71 (95% CI: 0.69-0.82), respectively (p = 0.73). A combination of urine CA125 and HE4 at optimal thresholds had a sensitivity of 82.4% (95% CI: 56.6-96.2) and was comparable to the sensitivity of serum CA125 [88.2% (95% CI: 63.6-98.5)]. Larger studies are required to confirm our findings, standardise urine collection, and evaluate optimal biomarker thresholds. Urine CA125 and HE4 may be useful non-invasive diagnostic tools to triage women for formal ovarian cancer investigations.

Multivariate logistic regression analysis of the correlation between five biomarkers and ovarian cancer in patients with intermediate-risk: A prospective cross-sectional study.

Objective: To find potential diagnostic biomarkers for ovarian cancer (OC), a prospective analysis of the expression of five biomarkers in patients with intermediate-risk and their correlation with the occurrence of OC was conducted. Method: A prospective observational study was carried out, patients who underwent surgical treatment with benign or malignant ovarian tumors in our hospital from January 2020 to February 2021 were included in this study, and a total of 263 patients were enrolled. Based on the postoperative pathological results, enrolled patients were divided into ovarian cancer group and benign tumor group (n = 135). The ovarian cancer group was further divided into a mid-stage group (n = 46) and an advanced-stage group (n = 82). The basic information of the three groups of patients was collected, the preoperative imaging data of the patients were collected to assess the lymph node metastasis, the preoperative blood samples were collected to examine cancer antigen 125 (CA125), carbohydrate antigen 19–9 (CA19–9), Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and the postoperative pathological data were sorted and summarized. Result: The average during of disease in the advanced ovarian cancer group was 0.55 ± 0.18 years higher than the benign tumor group (0.43 ± 0.14 years), p < 0.001. In the advanced ovarian cancer group, the ratio of patients with the tumor, node, metastasis (TNM) stage IV (64.63%), with tumor Grade stage II and III (93.90%), and without lymph node metastasis (64.63%) was respectively more than that in the mid-stage group (accordingly 0.00, 36.96, 23.91%) (p < 0.001); The ratio of patients with TNM grade III in the mid-stage group (73.91%) was more than that in the advanced group (35.37%) (p < 0.001). The levels of the five biomarkers: CA19-9, CA125, NLR, PLR, and BDNF were different among the three groups (p < 0.001). Conclusion: CA19-9, CA125, NLR, PLR, BDNF are five biomarkers related to the occurrence of ovarian cancer and are risk factors for it. These five biomarkers and their Combined-Value may be suitable to apply in the diagnosis and the identification of ovarian cancer in patients with intermediate-risk.

The diagnostic value of serum miR-21 in patients with ovarian cancer: a systematic review and meta-analysis

ObjectiveThere have been a variety of published studies on the expression of serum miR-21 in patients with ovarian cancer associated with the diagnostic value of ovarian cancer, but the conclusions are not clearly elucidated. This study aims to evaluate the value of serum miR-21 expression in the diagnosis of patients with ovarian cancer by meta-analysis.MethodsDatabases, such as PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), and China WanFang, were searched for relevant studies upon the correlation between the expression of serum miR-21 and the diagnostic value of ovarian cancer from inception to March 7, 2022. Statistical analysis was performed using Stata 15.0 software. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated. The meta-regression analysis and subgroup analysis were used to explore the sources of heterogeneity. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) system was used to evaluate the quality of the included literature.ResultsA total of 6 articles were included in the meta-analysis. The results showed that the pooled sensitivity, specificity, PLR, NLR, and DOR were 0.81 (95%CI: 0.73–0.88), 0.82 (95%CI: 0.75–0.87), 4.51 (95%CI: 3.22–6.31), 0.23 (95%CI: 0.16–0.33), and 19.87 (95% CI: 11.27–35.03), respectively. The area under the summary receiver operating characteristic curve was 0.89 (95%CI: 0.85–0.91). No significant publication bias was found (P > 0.05).ConclusionSerum miR-21 has a good diagnostic value for ovarian cancer, which can be an ideal diagnostic biomarker for ovarian cancer. However, we should gingerly use miR-21 as a diagnostic reference standard, due to the limited number of included studies and heterogeneity.

Exploration of Potential miRNA Biomarkers and Prediction for Ovarian Cancer Using Artificial Intelligence.

Ovarian cancer is the second most dangerous gynecologic cancer with a high mortality rate. The classification of gene expression data from high-dimensional and small-sample gene expression data is a challenging task. The discovery of miRNAs, a small non-coding RNA with 18–25 nucleotides in length that regulates gene expression, has revealed the existence of a new array for regulation of genes and has been reported as playing a serious role in cancer. By using LASSO and Elastic Net as embedded algorithms of feature selection techniques, the present study identified 10 miRNAs that were regulated in ovarian serum cancer samples compared to non-cancer samples in public available dataset GSE106817: hsa-miR-5100, hsa-miR-6800-5p, hsa-miR-1233-5p, hsa-miR-4532, hsa-miR-4783-3p, hsa-miR-4787-3p, hsa-miR-1228-5p, hsa-miR-1290, hsa-miR-3184-5p, and hsa-miR-320b. Further, we implemented state-of-the-art machine learning classifiers, such as logistic regression, random forest, artificial neural network, XGBoost, and decision trees to build clinical prediction models. Next, the diagnostic performance of these models with identified miRNAs was evaluated in the internal (GSE106817) and external validation dataset (GSE113486) by ROC analysis. The results showed that first four prediction models consistently yielded an AUC of 100%. Our findings provide significant evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.

LncRNA RP11-499E18.1 Inhibits Proliferation, Migration, and Epithelial-Mesenchymal Transition Process of Ovarian Cancer Cells by Dissociating PAK2-SOX2 Interaction.

Background: Ovarian cancer (OC)is a deadly gynecological malignancy worldwide. It is urgent to identify diagnostic biomarkers of OC to disclose the underlying mechanism.Methods and Materials: Bioinformatics analysis was used to identify target genes. Gene expression was detected and altered by qRT-PCR and cell transfection, respectively. The interaction between RP11-499E18.1 and PAK2, as well as that between PAK2 and SOX2, was determined using RNA pulldown, RNA immunoprecipitation (RIP), and co-immunoprecipitation (co-IP) assay, respectively. Localizations of RP11-499E18.1, PAK2, and SOX2 were respectively determined employing immunohistochemical (IHC), IF, and FISH. The regulatory effects of RP11-499E18.1, PAK2, and SOX2 on OC cell proliferation, migration, colony formation, epithelial–mesenchymal transition (EMT)-related factor expression, and SOX2 nuclear translocation were determined. Finally, the effects of RP11-499E18.1 and PAK2 expression on the tumor growth in nude mice were determined.Results: RP11-499E18.1, PAK2, and SOX2 were selected in our study. RP11-499E18.1 was downregulated, while PAK2 and SOX2 was upregulated in OC tissues and cells. RP11-499E18.1 coexists in the nucleus and cytoplasm of OC cells. There is an interaction between RP11-499E18.1 and PAK2, as well as PAK2 and SOX2 in OC cells. Alteration of RP11-499E18.1 and PAK2 expression both had no influence on PAK2 and SOX2 levels, but PAK2 upregulation notably augmented p-SOX2 level. RP11-499E18.1 overexpression suppressed OC cell proliferation, migration, and colony formation, as well as SOX2 nuclear translocation. Besides, it inhibited tumor growth in nude mice. However, these effects were notably reversed by PAK2 upregulation and eventually offset by SOX2 knockdown. Additionally, RP11-499E18.1 overexpression reduced PAK2–SOX2 interaction and SOX phosphorylation, and increased the binding of RP11-499E18.1 by PAK2.Conclusion: These lines of evidence demonstrated that RP11-499E18.1 might play its tumor suppressor roles in OC via regulation of the RP11-499E18.1–PAK2–SOX2 axis. This research indicated that RP11-499E18.1 might be used as a diagnostic biomarker for OC in the future.

Relaxin as a potential diagnostic biomarker for ovarian cancer- A prospective study

Ovarian cancer is a leading cause of female mortality worldwide. Although novel approaches on this disease have been developed, overall survival rates remain moderate due to the lack of scientific evidence promoting screening at early stages of the disease. A number of biomarkers have been suggested as predictive for this type of cancer. The role of relaxin in endometrial cancer is well documented but the scientific evidence is lacking with regards to ovarian cancer. We studied patients with ovarian cancer, benign ovarian cyst and healthy patients too. The levels of relaxin have been found to be an adequate diagnostic biomarker for ovarian cancer. We also presented the different range of Ca125, HE4 and ROMA in these three groups. Randomised control trials need to be conducted though, in order to elucidate the true role of relaxin in these cases.

Circulating Cell-Free DNA Methylation Profiles in the Early Detection of Ovarian Cancer: A Scoping Review of the Literature.

Simple SummaryThere are limited non-invasive methods for detecting epithelial ovarian cancer despite early detection and treatment dramatically increasing survival. As alterations in serum or plasma cell-free (cf)DNA methylation occur early in cancer development, they are promising biomarkers for ovarian cancer. Our literature review includes 18 studies depicting a wide array of gene targets and techniques. The data suggest a good performance of these cfDNA methylation tests, with accuracies up to 91% in detecting ovarian cancer in serum or plasma.Epithelial ovarian cancer is the most lethal gynecologic malignancy and has few reliable non-invasive tests for early detection or diagnosis. Recent advances in genomic techniques have bolstered the utility of cell-free DNA (cfDNA) evaluation from peripheral blood as a viable cancer biomarker. For multiple reasons, comparing alterations in DNA methylation is particularly advantageous over other molecular assays. We performed a literature review for studies exploring cfDNA methylation in serum and plasma for the early diagnosis of ovarian cancer. The data suggest that serum/plasma cfDNA methylation tests have strong diagnostic accuracies for ovarian cancer (median 85%, range 40–91%). Moreover, there is improved diagnostic performance if multiple genes are used and if the assays are designed to compare detection of ovarian cancer with benign pelvic masses. We further highlight the vast array of possible gene targets and techniques, and a need to include more earlier-stage ovarian cancer samples in test development. Overall, we show the promise of cfDNA methylation analysis in the development of a viable diagnostic biomarker for ovarian cancer.

Evaluation of FGFR1 as a diagnostic biomarker for ovarian cancer using TCGA and GEO datasets.

BackgroundMalignant ovarian cancer is associated with the highest mortality of all gynecological tumors. Designing therapeutic targets that are specific to OC tissue is important for optimizing OC therapies. This study aims to identify different expression patterns of genes related to FGFR1 and the usefulness of FGFR1 as diagnostic biomarker for OC.MethodsWe collected data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. In the TCGA cohort we analyzed clinical information according to patient characteristics, including age, stage, grade, longest dimension of the tumor and the presence of a residual tumor. GEO data served as a validation set. We obtained data on differentially expressed genes (DEGs) from the two microarray datasets. We then used gene set enrichment analysis (GSEA) to analyze the DEG data in order to identify enriched pathways related to FGFR1.ResultsDifferential expression analysis revealed that FGFR1 was significantly downregulated in OC specimens. 303 patients were included in the TCGA cohort. The GEO dataset confirmed these findings using information on 75 Asian patients. The GSE105437 and GSE12470 database highlighted the significant diagnostic value of FGFR1 in identifying OC (AUC = 1, p = 0.0009 and AUC = 0.8256, p = 0.0015 respectively).ConclusionsOur study examined existing TCGA and GEO datasets for novel factors associated with OC and identified FGFR1 as a potential diagnostic factor. Further investigation is warranted to characterize the role played by FGFR1 in OC.

Long non-coding RNA FOXD2-AS1 promotes proliferation, migration and invasion of ovarian cancer cells via regulating the expression of miR-4492.

The aim of the present study was to determine the role of long non-coding RNA (lncRNA) forkhead box D2 antisense 1 (FOXD2-AS1) in the development of ovarian cancer, investigate the underlying mechanisms and provide a potential diagnostic biomarker for ovarian cancer. A total of 39 ovarian cancer patients were included, and the ovarian cancer tissues and paracancer tissues were obtained. The ovarian cancer cell lines SKOV3 and OVCAR3 and the human ovarian normal epithelial cell line IOSE80 were cultured. The expression of lncRNA FOXD2-AS1 and miR-4492 was detected by reverse transcription-quantitative PCR. Small interfering RNA targeting FOXD2-AS1 (si-FOXD2-AS1), microRNA (miR)-4492 mimics, miR-4492 inhibitor and their corresponding controls were transfected into cells. The proliferation was detected with a Cell-Couting-Kit-8 assay, and migration and invasion were determined using Transwell assays. The mutual binding site of lncRNA FOXD2-AS1 and miR-4492 was predicted with the miRDB database and verified by a luciferase reporter assay. Finally, a rescue assay was performed. The results suggested that lncRNA FOXD2-AS1 was upregulated in ovarian cancer tissues and cell lines. si-FOXD2-AS1 was able to inhibit the proliferation, migration and invasion of ovarian cancer cells. lncRNA FOXD2-AS1 was confirmed to directly target miR-4492. The expression of lncRNA FOXD2-AS1 and miR-4492 exhibited a negative correlation. In a rescue experiment, miR-4492 inhibitor abrogated the effect of siFOXD2-AS1 in SKOV3 and OVCAR3 cell lines. In conclusion, lncRNA FOXD2-AS1 promotes the proliferation and invasion of ovarian cancer cells via regulating the expression of miR-4492. It may be a novel potential diagnostic biomarker and therapeutic target for ovarian cancer.

Identifying Potential Markers for Monitoring Progression to Ovarian Cancer Using Plasma Label-free Proteomics.

Background: Cancer antigen 125 (CA125) is considered to have high sensitivity but poor specificity for ovarian cancer. New biomarkers utilized to early detect and monitor the progression of ovarian cancer patients are critically needed.Methods: A total of 80 patients including 16 early stage, and matched with 17 late stage, 23 benign ovarian tumor (BOT) and 24 uterine fibroid (UF) patients were utilized to perform plasma proteomics analysis using isobaric tag for relative and absolute quantitation (iTRAQ) method to identify differential diagnostic proteins of ovarian cancer patients. A validation set of 9 early stage, 11 late stage, 17 BOT and 16 UF collected by an independent cohort of samples with the same matching principles was examined to confirm the expressed levels of differential expression proteins by ELISA analysis.Results: CRP and ARHGEF 11 were identified as potential diagnostic biomarkers of ovarian cancer. Results of area under the curve (AUC) analysis suggested that combination of diagnostic proteins and CA125 achieved a much higher diagnostic accuracy compared with CA125 alone (AUC values: 0.98 versus 0.80), especially improved the specificity (0.97 versus 0.77). In addition, elevated plasma CRP levels were associated with increased risk of ovarian cancer.Conclusions: Current study found that plasma protein CRP was an indicator for monitoring the progression of ovarian cancer. Combination of plasma protein biomarkers with CA125 could be utilized to early diagnose of ovarian cancer patients.

Desmoglein-2 as a prognostic and biomarker in ovarian cancer

ABSTRACT Greater than 80% of all cancer cases are carcinomas, formed by the malignant transformation of epithelial cells. One of the key features of epithelial tumors is the presence of intercellular junctions, which link cells to one another and act as barriers to the penetration of molecules. This study assessed the expression of desmoglein-2, an epithelial junction protein, as a prognostic and diagnostic biomarker for ovarian cancer. Ovarian cancer sections were stained for DSG2 and signal intensity was correlated to cancer type and grade. DSG2 immunohistochemistry signals and mRNA levels were analyzed in chemo-resistant and chemo-sensitive cases. Ovarian cancer patient serum levels of shed DSG2 were correlated to disease-free and overall survival. Primary ovarian cancer cells were used to study DSG2 levels as they changed in response to cisplatin treatment. DSG2 expression was found to be positively correlated with cancer grade. Ovarian cancer patients with high serum levels of shed DSG2 fared significantly worse in both progression-free survival (median survival of 16 months vs. 26 months, p = .0023) and general survival (median survival of 37 months vs. undefined, p < .0001). A subgroup of primary chemotherapy-resistant cases had stronger DSG2 IHC/Western signals and higher DSG2 mRNA levels. Furthermore, our in vitro studies indicate that non-cytotoxic doses of cisplatin can enhance DSG2 expression, which, in turn, can contribute to chemo-resistance. We suggest that DSG2 can be used in stratifying patients, deciding on where to use aggressive treatment strategies, predicting chemoresistance, and as a companion diagnostic for treatments targeting DSG2.

Ovarian Cancer: Tumor-Specific Urinary Micro-Peptides Profiling as Potential Biomarkers for Early Diagnosis.

Ovarian cancer is the second major lethal gynecologic malignancy in developing countries. This study aimed to characterize urinary micro-peptides as potential diagnostic biomarkers for ovarian cancer. In a prospective, longitudinal and case-controlled study and following informed consent, urine and plasma samples were collected from 112 women with histologically-proven ovarian cancer and 200 apparently healthy age-matched volunteers. Urinary micro-peptides were detected and sequenced using SDS-PAGE and Edman degradation technique. Serum CA125 was detected in less than a quarter (23.2%, 26/112) of patients. One or more urinary micro-peptides were detected in about two thirds of the patients (62.5%, 70/112). A total of 40 patients had three bands (57.1%, 40/70), while two bands (15 and 35 kDa) were detected in 28.6% (20/70) of the patients. Isolated 45 kDa band was seen in 14.3% (10/70). No urinary micro-peptide was detected in the volunteers. The 15 and 35 kDa bands disappeared after 6 months of regular chemotherapy, while the 45 kDa band persisted in 2.9% (2/70) of the patients after treatment. The micro-peptides were identified as: Catalase (45 kDa), α-1 Acid Glycoprotein (35 kDa) and Peroxiredoxin-2 (15 kDa). Urinary catalase, α-1 Acid Glycoprotein and Peroxiredoxin-2 can be useful biomarkers for early detection and treatment response of ovarian cancer.

LINC00662 promotes glycolysis and cell survival by regulating miR- 375/HIF-1α axis in ovarian cancer.

Ovarian cancer (OC) is one of the most common gynecological malignancies, with the highest mortality rate in women worldwide. LINC00662, a long non-coding RNA (lncRNA), was shown to play a vital role in many malignancies, while little is known about its role in OC. Firstly, our study determined the expression of LINC00662 in OC tissues and cells. Upregulation or downregulation of LINC00662 were performed in OC cells to explore its effects on cell proliferation and glycolysis of OC. The interaction between LINC00662 and miR-375 was verified using luciferase assays and RNA immunoprecipitation. Results showed that LINC00662 was highly expressed in OC tissues and cells, and patients with increased expression of LINC00662 were associated with shorter overall survival. Furthermore, functional assays proved that LINC00662 was essential for OC cell proliferation and glycolysis. Subsequently, our study further revealed that LINC00662 acted as a competitive RNA and it could modulate the expression of HIF-1α through directly binding with miR- 375. Collectively, upregulation of LINC00662 in ovarian cancer tissues is closely correlated to poor survival. LINC00662 might regulate HIF-1α expression via miR-375. These findings suggested that LINC00662 has the potential to be explored as a diagnostic biomarker for OC.