Sensitivity and specificity of microRNA-204, CA125, and CA19.9 as biomarkers for diagnosis of ovarian cancer

The Role of microRNA in the Prognosis and Diagnosis of Ovarian Cancer

Ovarian cancer (OC) is one of the most common cancers in women. Biomarkers for OC are still being sought. The aim of this review was to evaluate microRNAs in the prognosis and diagnosis of OC. We conducted a literature review searching for articles published from January 2014 to September 2024. We included articles presenting the association of microRNAs with ovarian cancer prognosis, where patient survival was shown by the Kaplan-Meier curve, and articles presenting the association of microRNAs with ovarian cancer diagnosis, where the results were presented as an ROC curve. MicroRNAs are promising clinical markers in ovarian cancer patients. As is shown here, expression (high or low) of various miRNAs was differentially associated with survival in OC patients, with some miRNAs being associated with a longer survival and some with a shorter survival. In the absence of diagnostic markers for OC, the raised role of miRNAs in diagnosis seems all the more important. The diagnostic value of miRNAs has been shown, mostly as blood biomarkers, although they have also been evaluated as tissue or urine markers. MiRNAs have an important role as clinical biomarkers for ovarian cancer, not only as single molecules, but also as biomarker pairs or panels of miRNAs. It should be noted that most of the miRNAs reviewed here have been studied once, so despite the promising results, it seems necessary to conduct studies to confirm or negate the results obtained.

An Analysis of Delta Apparent Diffusion Coefficient Values for Epithelial Ovarian Cancer Classification and Ki-67 Expression

BACKGROUND

Ovarian cancer is one of the most common malignant tumors of the female reproductive system, characterized by high malignancy and poor prognosis. Epithelial ovarian cancer (EOC) accounts for 90% to 95% of all cases. This study aims to investigate the diagnostic value of delta apparent diffusion coefficient (dADC) values in distinguishing between type I and type II EOC and to explore its correlation with Ki-67 expression.

METHODS

A retrospective analysis included 95 patients (mean age: 51.6 ± 12.5 y; range: 17 to 73 y) diagnosed with EOC at our hospital from September 2021 to August 2023. Of these, 51 patients had type I EOC (low-grade serous carcinoma, clear cell carcinoma, endometrioid carcinoma, mucinous carcinoma, or borderline tumors), and 44 had type II EOC (high-grade serous carcinoma or high-grade endometrioid carcinoma). Bilateral lesions were observed in 16.8% of patients. Preoperative MRI, including diffusion-weighted imaging (DWI), serum CA125 levels, and postoperative immunohistochemical Ki-67 expression, were analyzed. Tumor staging was based on the 2021 FIGO criteria. Minimum ADC (minADC), maximum ADC (maxADC), and dADC values were calculated from the solid tumor components. Receiver operating characteristic (ROC) curves assessed diagnostic performance, and the correlation between dADC and Ki-67 expression was examined.

RESULTS

The maxADC and minADC of type II EOC were lower than those of type I, while dADC was higher than type I (P<0.05). ROC curve analysis showed that the efficacy of dADC in distinguishing between type I and type II EOC was higher than that of minADC and maxADC (P<0.05). When the dADC threshold was 0.31×10-3 mm2/s, the area under the curve (AUC) was 0.982, with a sensitivity of 95.3% and specificity of 97.3%. Pearson correlation analysis showed a positive correlation between dADC and Ki-67 expression.

CONCLUSION

dADC has a certain value in accurately distinguishing between type I and type II EOC preoperatively, and it can reflect the proliferative activity of tumor cells.

Circulating microRNAs as Diagnostic Biomarkers to Detect Specific Stages of Ovarian Cancer: A Comprehensive Meta-Analysis

Ovarian cancer (OC) is one of the most common gynecological cancers [...].

The glycogene alterations and potential effects in esophageal squamous cell carcinoma

BACKGROUND

Aberrant glycosylation is one of the hallmarks of cancer. The profile of glycoprotein expression caused by abnormal glycosylation has been revealed, while abnormal glycogenes that may disturb the structure of glycans have not yet been identified in esophageal squamous cell carcinoma (ESCC).

METHODS

Genomic alterations driven by differentially expressed glycogenes in ESCC were compared with matched normal tissues by multi-omics analysis. Immunohistochemistry, MTT, colony formation, transwell assays, subcutaneous tumor formation experiments and tail vein injection were used to study the expression and the effect on the proliferation and metastasis of the differentially expressed glycogenes POFUT1 and RPN1 in ESCC. In the alkyne fucose labeling experiment, AAL lectin affinity chromatography and immunoprecipitation were used to explore the mechanism of POFUT1 in ESCC.

RESULTS

The expression of the POFUT1 and RPN1 glycogenes were upregulated, as determined by genomic copy number gain and proteomics analysis. The overexpression of POFUT1 or RPN1 was associated with poor prognosis in ESCC patients and affected the proliferation and metastasis of ESCC in vivo and in vitro. The overexpression of POFUT1 increased the overall fucosylation level and activated the Notch signaling pathway, which partially mediated POFUT1 induced pro-migration in ESCC. The regulation of malignant progression of ESCC by RPN1 may be related to the TNF signaling pathway, p53 signaling pathway, etc. CONCLUSIONS: Our study fills a gap in the study of abnormal glycogenes and highlights the potential role of the POFUT1/Notch axis in ESCC. Moreover, our study identifies POFUT1 and RPN1 as promising anticancer targets in ESCC.

Ovarian cancer: Diagnosis and treatment strategies (Review)

Ovarian cancer is a malignant tumor that seriously endangers health. Early ovarian cancer symptoms are frequently challenging to detect, resulting in a large proportion of patients reaching an advanced stage when diagnosed. Conventional diagnosis relies heavily on serum biomarkers and pathological examination, but their sensitivity and specificity require improvement. Targeted therapy inhibits tumor growth by targeting certain characteristics of tumor cells, such as signaling pathways and gene mutations. However, the effectiveness of targeted therapy varies among individuals due to differences in their unique biological characteristics and requires individualized strategies. Immunotherapy is a promising treatment for ovarian cancer due to its long-lasting antitumor effect. Nevertheless, issues such as variable efficacy, immune-associated adverse effects and drug resistance remain to be resolved. The present review discusses the diagnostic strategies, rationale, treatment strategies and prospects of targeted therapy and immunotherapy for ovarian cancer.

A signature of circulating miRNAs predicts the prognosis and therapeutic outcome of taxane/platinum regimen in advanced ovarian carcinoma patients

PURPOSE

Ovarian carcinoma (OC) is ranked as the eighth most lethal gynecological cancer due to late diagnosis and high recurrence. Existing biomarkers are lacking to predict the recurrence and stratify patients who are likely to benefit from chemotherapy. MicroRNAs (miRNAs/miRs) are persistently present in humans and are capable of predicting treatment outcomes. Thus, the purpose of the study was to assess the potential of circulatory miRNAs to predict the efficacy of OC.

METHODS

Newly diagnosed n = 208 OC patients were administrated neoadjuvant/adjuvant chemotherapy (taxane + platinum) after surgery. Their demographic, gynecologic, clinical parameters, response, and survival were recorded. MiR-27a, miR-182, miR-199a, miR-214, and miR-591 were taken and the expression were analyzed using real-time PCR at different treatment intervals. Further, its prognostic value (Kaplan-Meier, and Cox regression analysis) and diagnostic importance (receiver operating characteristic curve) were validated.

RESULT

The mean age of patients with poorly differentiated (45.2%) serous OC was 48.69 ± 10.38. The majority experienced menarche at ≥ 12 (62.2%) with poor menstrual hygiene (81.8%) and were post-menopausal (69.4%), some were associated with high risk of survival (HR =  > 1). MiRNA signature showed three over-expression and two under-expression (miR-27a, miR-182, and miR-214; miR-199a and miR-591) in advanced OC compared to the control (P=  < 0.05). Also, a significant difference was detected at each time interval of treatment with the response (P =  ≤ 0.001) associated with resistance and overall survival (P =  ≤ 0.001) with risk (HR =  > 1). ROC analysis showed enhanced the diagnostics accuracy (< 0.001).

CONCLUSION

Our findings indicate that circulating miRNAs might be a potential minimally invasive diagnostic marker for treatment outcome and recurrence in ovarian carcinoma.

Sensitivity and Specificity of Selected Biomarkers and Their Combinations in the Diagnosis of Ovarian Cancer

One of the greatest challenges in modern gynecological oncology is ovarian cancer. Despite the numerous studies currently being conducted, it is still sometimes detected at late clinical stages, where the prognosis is unfavorable. One significant contributing factor is the absence of sensitive and specific parameters that could aid in early diagnosis. An ideal screening test, in view of the low incidence of ovarian cancer, should have a sensitivity of greater than 75% and a specificity of at least 99.6%. To enhance sensitivity and specificity, diagnostic panels are being created by combining individual markers. The drive to develop better screening tests for ovarian cancer focuses on modern diagnostic methods based on molecular testing, which in turn aims to find increasingly effective biomarkers. Currently, researchers' efforts are focused on the search for a complementary parameter to those most commonly used that would satisfactorily enhance the sensitivity and specificity of assays. Several biomarkers, including microRNA molecules, autoantibodies, cDNA, adipocytokines, and galectins, are currently being investigated by researchers. This article reviews recent studies comparing the sensitivity and specificity of selected parameters used alone and in combination to increase detection of ovarian cancer at an early stage.

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Assessing the clinical utility of multi-omics data for predicting serous ovarian cancer prognosis

Ovarian cancer (OC) is characterised by heterogeneity that complicates the prediction of patient survival and treatment outcomes. Here, we conducted analyses to predict the prognosis of patients from the Genomic Data Commons database and validated the predictions by fivefold cross-validation and by using an independent dataset in the International Cancer Genome Consortium database. We analysed the somatic DNA mutation, mRNA expression, DNA methylation, and microRNA expression data of 1203 samples from 599 serous ovarian cancer (SOC) patients. We found that principal component transformation (PCT) improved the predictive performance of the survival and therapeutic models. Deep learning algorithms also showed better predictive power than the decision tree (DT) and random forest (RF). Furthermore, we identified a series of molecular features and pathways that are associated with patient survival and treatment outcomes. Our study provides perspective on building reliable prognostic and therapeutic strategies and further illuminates the molecular mechanisms of SOC.Impact statementWhat is already known on this subject? Recent studies have focussed on predicting cancer outcomes based on omics data. But the limitation is the performance of single-platform genomic analyses or the small numbers of genomic analyses.What do the results of this study add? We analysed multi-omics data, found that principal component transformation (PCT) significantly improved the predictive performance of the survival and therapeutic models. Deep learning algorithms also showed better predictive power than did decision tree (DT) and random forest (RF). Furthermore, we identified a series of molecular features and pathways that are associated with patient survival and treatment outcomes.What are the implications of these findings for clinical practice and/or further research? Our study provides perspective on how to build reliable prognostic and therapeutic strategies and further illuminates the molecular mechanisms of SOC for future studies.

Tumor Markers and Their Diagnostic Significance in Ovarian Cancer

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

PURPOSE

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

METHODS

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

RESULTS

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Serum levels of tumor markers and their clinical significance in epithelial ovarian cancer

OBJECTIVES

Tumor markers have been widely used clinically. Detection of serum CA125 is one of the commonly used clinical methods for early screening and early diagnosis of epithelial ovarian cancer, but it is difficult to diagnose epithelial ovarian cancer with a single specific tumor marker. In this study, the combinatorial tumor marker detection method was used to compare the value of each tumor marker alone and different combinations in the diagnosis of epithelial ovarian cancer.

METHODS

The clinical data of patients with epithelial ovarian cancer (n=65) and ovarian benign disease (n=29) were collected. Multiple tumor marker protein chip was used to detect cancer antigen 125 (CA125), carbohydrate antigen 242 (CA242), alpha-fetoprotein (AFP), beta-human chorionic gonadotropin (β-HCG), carcinoembryonic antigen (CEA), cancer antigen 199 (CA199), neuron-specific enolase (NSE), Ferritin, cancer antigen 153 (CA153), and human growth hormone (HGH) serum levels, and to compare the differences between the benign and malignant ovarian tumors. The correlation between tumor markers and clinicopathologic features for ovarian epithelial carcinoma was analyzed by χ2 test. Spearman rank analysis showed the correlation between CA125 expression level and other tumor markers in epithelial ovarian cancer and the correlation between age and the above 10 tumor markers. Sensitivity, specificity, positive predictive value, negative predictive value, Youden index, and diagnostic efficiency were used to evaluate the diagnostic value of single tumor marker and the combination of tumor markers.

RESULTS

The levels of β-HCG, NSE, CA153, and CA125 in the epithelial ovarian cancer group were higher than those in the ovarian benign disease group. The level of NSE in the serum of patients with epithelial ovarian cancer was related to the clinical stage of patients. In addition, the levels of CA242, β-HCG, CEA, NSE, Ferritin, CA153 in the serum of patients with epithelial ovarian cancer were positively correlated with CA125 (rs=0.497, P<0.001; rs=0.612, P<0.001; rs=0.358, P=0.003; rs=0.680, P<0.001; rs=0.322, P=0.009; rs=0.609, P<0.001, respectively), and the levels of β-HCG, Ferritin, CA153 were positively correlated with the patient's age (rs=0.256, P=0.040; rs=0.325, P=0.008; rs=0.249, P=0.046, respectively). In the diagnosis of epithelial ovarian cancer, the sensitivity, Youden index, and diagnostic efficiency of CA125 detection alone were higher than the results of the other 9 separate detections. When CA153, CA199, CA242, Ferritin, and CEA were combined with CA125, the sensitivity of the combined detection of different combinations was higher than that of CA125 alone. The combined detection sensitivities of CA125+CEA and CA125+Ferritin+CEA were 89.2% and 90.8%, respectively, and the diagnostic efficiencies were both 84.1%, which were higher than those of other combinations. The Youden index of CA125+CEA joint detection was 0.616, which was higher than those of other combinations.

CONCLUSIONS

CA125 has a high diagnostic value in the diagnosis of epithelial ovarian cancer. The detection of combined tumor markers in serum has higher sensitivity and specificity in epithelial ovarian cancer.

Evaluation of the Potential Diagnostic Utility of the Determination of Selected Immunological and Molecular Parameters in Patients with Ovarian Cancer

Ovarian cancer is one of the most serious challenges in modern gynaecological oncology. Due to its non-specific symptoms and the lack of an effective screening procedure to detect the disease at an early stage, ovarian cancer is still marked by a high mortality rate among women. For this reason, a great deal of research is being carried out to find new markers that can be used in the detection of ovarian cancer to improve early diagnosis and survival rates of women with ovarian cancer. Our study focuses on presenting the currently used diagnostic markers and the latest selected immunological and molecular parameters being currently investigated for their potential use in the development of new diagnostic and therapeutic strategies.