HE4 as a serum biomarker for the diagnosis of pelvic masses: a prospective, multicenter study in 965 patients

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.

Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer

BACKGROUND

Both mitophagy and long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). We sought to explore the characteristics of mitophagy-related gene (MRG) and mitophagy-related lncRNAs (MRL) to facilitate treatment and prognosis of OC.

METHODS

The processed data were extracted from public databases (TCGA, GTEx, GEO and GeneCards). The highly synergistic lncRNA modules and MRLs were identified using weighted gene co-expression network analysis. Using LASSO Cox regression analysis, the MRL-model was first established based on TCGA and then validated with four external GEO datasets. The independent prognostic value of the MRL-model was evaluated by Multivariate Cox regression analysis. Characteristics of functional pathways, somatic mutations, immunity features, and anti-tumor therapy related to the MRL-model were evaluated using abundant algorithms, such as GSEA, ssGSEA, GSVA, maftools, CIBERSORT, xCELL, MCPcounter, ESTIMATE, TIDE, pRRophetic and so on.

RESULTS

We found 52 differentially expressed MRGs and 22 prognostic MRGs in OC. Enrichment analysis revealed that MRGs were involved in mitophagy. Nine prognostic MRLs were identified and eight optimal MRLs combinations were screened to establish the MRL-model. The MRL-model stratified patients into high- and low-risk groups and remained a prognostic factor (P < 0.05) with independent value (P < 0.05) in TCGA and GEO. We observed that OC patients in the high-risk group also had the unfavorable survival in consideration of clinicopathological parameters. The Nomogram was plotted to make the prediction results more intuitive and readable. The two risk groups were enriched in discrepant functional pathways (such as Wnt signaling pathway) and immunity features. Besides, patients in the low-risk group may be more sensitive to immunotherapy (P = 0.01). Several chemotherapeutic drugs (Paclitaxel, Veliparib, Rucaparib, Axitinib, Linsitinib, Saracatinib, Motesanib, Ponatinib, Imatinib and so on) were found with variant sensitivity between the two risk groups. The established ceRNA network indicated the underlying mechanisms of MRLs.

CONCLUSIONS

Our study revealed the roles of MRLs and MRL-model in expression, prognosis, chemotherapy, immunotherapy, and molecular mechanism of OC. Our findings were able to stratify OC patients with high risk, unfavorable prognosis and variant treatment sensitivity, thus improving clinical outcomes for OC patients.

Comparison of Human Epididymis Protein 4, Cancer Antigen 125, and Ultrasound Prediction Model in Differentiating Benign from Malignant Adnexal Masses

Background

This study aimed to compare the diagnostic performance of carcinogenic antigen (CA) 125, (HE)-4 (Human epididymis protein 4), and ultrasound (International Ovarian Tumor Analysis [IOTA]) Simple Rules individually and to derive a composite score in the differentiating ovarian cancer from benign ovarian mass.

Subjects and Methods

Consecutive patients (n = 100) with pelvic mass admitted during February 2018-August 2019 were included prospectively. Patients with either known case of epithelial ovarian cancer (EOC) or metastatic EOC were excluded. The primary outcome was to assess the sensitivity and specificity of CA-125, HE-4, and IOTA Simple Rules in predicting benign from malignant mass independently, while secondary outcome was derivation of a new model incorporating these variables using multivariate logistic regression analysis to predict benign from malignant lesions. Receiver operator curve (ROC) was drawn to redefine the best-performing cutoff values and difference between area under the ROC (AUROC) were compared by DeLong's method.

Results

Out of 100 cases of adnexal mass selected, the sensitivity and specificity of CA-125 were 73.8% and 77.6%, HE-4 were 90.5% and 87.9%, and IOTA Simple Rules were 92.9% and 81.0%. CA-125, HE-4, and IOTA Simple Rules were independently associated with the likelihood of malignancy/borderline (P < 0.001). The area under the curve for the "composite score" (AUC = 0.93) was the highest and was significantly better than that of CA-125 (AUC = 0.786) (P = 0.004 using DeLong's test) and comparable with HE-4 (AUROC = 0.90; P = 0.128 using DeLong's Test).

Conclusion

The sensitivity and specificity of HE-4 and IOTA Simple Rules for predicting malignant ovarian tumor was better than those of CA-125. The diagnostic performance of "composite score" was comparable to those of either HE-4 or IOTA Simple Rules and significantly better than CA-125.

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.