Human epididymis protein 4 (HE4) is a secreted glycoprotein that is overexpressed by serous and endometrioid ovarian carcinomas

Are there relationship otosclerosis with serum HE4 and CA125 level? A pilot study

BACKGROUND

HE4 and CA 125 are identified as a potential biomarker for the detection of some diseases with fibrosis.

OBJECTIVES

The purpose of this pilot study was to evaluate the value of human epididymis protein 4 (HE4) and cancer antigen-125 (CA-125) in otosclerosis patients.

MATERIAL AND METHODS

The study population consisted of 60 people (30 otosclerosis patients, 30 control group). We collected blood samples for HE4 and CA-125 levels. Serum HE4 and CA-125 levels were measured by enzyme-linked immunosorbent assay (ELISA). We compared the results between otosclerosis patients and the normal subject. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic value.

RESULTS

There was no differences in CA-125 level between the otosclerosis (20.3 U/mL [10.4-42.1] and control group (19.3 U/mL [15.3-49.8]) (p > 0.05). HE4 level was significantly higher in the otosclerosis group (60.9 pmol/L [32.1-101.8])] than the control group (25.3 pmol/L [12.4-91.9]) (p < 0.001). The AUC in ROC analysis of HE4 was 0.768 (p < 0.001).

CONCLUSIONS AND SIGNIFICANCE

Serum HE4 level may be a useful biomarker in otosclerosis. Further studies with a larger number of patients are required to confirm our pilot results.

Comparison of the diagnostic efficacy of systemic inflammatory indicators in the early diagnosis of ovarian cancer

Background

This study aimed to determine the diagnostic accuracy of CA125, HE4, systemic immune-inflammation index (SII), prognostic nutritional index (PNI), fibrinogen-to-albumin ratio (FAR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and the combination of the six inflammatory-nutritional markers for ovarian cancer (OC) to identify the best diagnostic indicator for OC early diagnosis. An extensive study was performed to establish the connection between these indicators and the pathological aspects of OC.

Methods

A total of 170 individuals were included in this study, with 87 diagnosed with OC and 83 with benign ovarian tumors (BOTs). The diagnostic abilities of the variables were evaluated by calculating sensitivity, specificity, and area under the ROC curves. Through the use of DCA, we evaluated the variables' clinical value in the discrimination of ovarian masses.

Results

All markers showed significant diagnostic power for OC. CA125, HE4, SII, FAR, and MLR levels significantly increased from the BOTs group to the early-stage OC group. The advanced-stage OC group had significantly lower PNI values compared to the early-stage OC group but significantly higher levels of CA125, HE4, SII, NLR, and FAR. Moreover, the OC group with lymph node metastasis exhibited significantly higher levels of CA125, HE4, SII, NLR, PLR, and FAR, in contrast to the non-metastatic group, while PNI levels were significantly lower. Categorical factors, such as histological grade and pathological classification, showed noticeable discrepancies in CA125 and HE4 levels. NLR was significantly different among the pathological type groups. Among the six inflammatory-nutritional markers, the FAR displayed the greatest diagnostic value. In the analysis of logistic regression, it was observed that a combination marker containing all six inflammatory-nutritional markers exhibited a notably higher AUC value (0.881; 95% CI, 0.823 - 0.926) than any of the individual marker.

Conclusion

PNI, NLR, PLR, MLR, SII, and FAR showed excellent diagnostic performance for OC. The combination of these markers demonstrated a superior diagnostic capability compared to each individual one. The systemic inflammatory indicators may be helpful to diagnose OC.

Human epididymis protein 4: Analysis of national health and nutrition examination survey data

BACKGROUND

Human epididymis protein 4 (HE4) is a tumor marker overexpressed in ovarian cancer and is commonly utilized to aid with diagnosis of an adnexal mass. HE4 levels vary based on pregnancy, age, menopausal status, and tobacco use.

OBJECTIVE(S)

The objective of this study was to evaluate population-based data to examine factors that affect HE4 among adult women in the United States and stratify levels of HE4 by demographic and gynecologic factors.

STUDY DESIGN

A retrospective analysis was conducted using data from 2,480 women aged 20 + who participated in the National Health and Nutrition Examination Survey (2001-2002). From these cross-sectional data, serum HE4 and cotinine, a marker of tobacco exposure, were combined with demographic and interview data. Estimated glomerular filtration rates (eGFR) were based on serum creatinine, age, sex, and race. Other variables of interest included menopausal status, pregnancy, and various gynecologic factors. Summary HE4 data are provided as geometric means with associated 95 % confidence intervals.

RESULTS

HE4 levels were independently associated with age, renal function, and nicotine use, all p < 0.001. Pre-menopausal women with a history of endometriosis were found to have elevated HE4 levels compared to those without, p < 0.01; however, we found no such difference among post-menopausal women. Adjusting for age, no differences in HE4 were found based on race/ethnicity, p = 0.29. HE4 levels showed statistically significant associations with income level; however, these were small and clinically irrelevant.

CONCLUSION

This study provides evaluation of HE4 levels among a data set representative of 98.5 million non-institutionalized women in the United States and gives insight into extraneous factors that may influence these levels.

A predictive and prognostic model for surgical outcome and prognosis in ovarian cancer computed by clinico-pathological and serological parameters (CA125, HE4, mesothelin)

OBJECTIVES

Numerous prognostic models have been proposed for ovarian cancer, extending from single serological factors to complex gene-expression signatures. Nonetheless, these models have not been routinely translated into clinical practice. We constructed a robust and readily calculable model for predicting surgical outcome and prognosis of ovarian cancer patients by exploiting commonly available clinico-pathological factors and three selected serum parameters.

METHODS

Serum CA125, human epididymis protein 4 (HE4) and mesothelin (MSL) were quantified by Lumipulse® G chemiluminescent enzyme immunoassay (Fujirebio) in a total of 342 serum samples from 190 ovarian cancer patients, including 152 paired pre- and post-operative samples.

RESULTS

Detection of pre-operative HE4 and CA125 was the optimal marker combination for blood-based prediction of surgical outcome (AUC=0.86). We constructed a prognostic model, computed by serum levels of pre-operative CA125, post-operative HE4, post-operative MSL and surgical outcome. Prognostic performance of our model was superior to any of these parameters alone and was independent from BRCA1/2 mutational status. We subsequently transformed our model into a prognostic risk index, stratifying patients as "lower risk" or "higher risk". In "higher risk" patients, relapse or death was predicted with an AUC of 0.89 and they had a significantly shorter progression free survival (HR: 9.74; 95 % CI: 5.95-15.93; p<0.0001) and overall survival (HR: 5.62; 95 % CI: 3.16-9.99; p<0.0001) compared to "lower risk" patients.

CONCLUSIONS

We present a robust predictive/prognostic model for ovarian cancer, which could readily be implemented into routine diagnostics in order to identify ovarian cancer patients at high risk of recurrence.

Immunotherapy for Ovarian Cancer: Disappointing or Promising?

Ovarian cancer, one of the deadliest malignancies, lacks effective treatment, despite advancements in surgical techniques and chemotherapy. Thus, new therapeutic approaches are imperative to improving treatment outcomes. Immunotherapy, which has demonstrated considerable success in managing various cancers, has already found its place in clinical practice. This review aims to provide an overview of ovarian tumor immunotherapy, including its basics, key strategies, and clinical research data supporting its potential. In particular, this discussion highlights promising strategies such as checkpoint inhibitors, vaccines, and pericyte transfer, both individually and in combination. However, the advancement of new immunotherapies necessitates large controlled randomized trials, which will undoubtedly shape the future of ovarian cancer treatment.

High WFDC3 gene expression is associated with poor prognosis and reduced immune cells infiltration in pancreatic adenocarcinoma: A study using the TCGA database and bioinformatics analysis

Whey-acidic-protein (WAP) four-disulfide core domain protein 3 (WFDC3) is one of the WAP family proteins. This protein family is associated with the development of solid tumors and affects the tumor immunological microenvironment. However, the prognostic value of WFDC3 in pancreatic adenocarcinoma (PAAD) and its effect on the tumor immune microenvironment is yet to be clarified. The Cancer Genome Atlas database and Genotype-Tissue Expression database were used to analyze the differential expression of WFDC3 between the tumor and adjacent tissues. The clinical significance of WFDC3 was analyzed in The Cancer Genome Atlas and International Cancer Genome Consortium database using WFDC3 transcripts and clinical information. In order to elucidate the underlying mechanisms, gene set enrichment analysis was conducted to determine potential activated pathways. Immune score evaluation and publicly available pharmacogenomics database [the Genomics of Drug Sensitivity in Cancer] were utilized to quantify immune cell infiltration and the effect on chemotherapeutic drug sensitivity. WFDC3 levels were higher in PAAD tissues than in normal pancreatic tissues. High levels of WFDC3 expression progressively increased as PAAD tumor stages progressed. Patients with elevated WFDC3 expression showed a poor prognosis. The gene set enrichment analysis analysis revealed that glutamate, arginine, and proline, and histidine metabolism levels were elevated in patients with a high WFDC3 expression phenotype. B, CD4+ T, and CD8+ T cell infiltration was diminished in PAAD tissues with elevated WFDC3 expression. According to pharmacogenomics, PAAD tissues with high WFDC3 expression are susceptible to gemcitabine. WFDC3 is highly expressed in PAAD, and patients with a high level of WFDC3 expression have a shorter overall survival time, indicating a poorer prognosis. High expression of WFDC3 may lead to the development of PAAD by affecting the amino acid metabolism and the tumor immunological microenvironment. WFDC3 may serve as a potential diagnostic and prognostic biomarker for PAAD patients.

ATNC: Versatile Nanobody Chimeras for Autophagic Degradation of Intracellular Unligandable and Undruggable Proteins

Targeted protein degradation (TPD) through the autophagy pathway displays broad substrate scope and is gaining increasing interest in biology and medicine. However, current approaches using small-molecule degraders have limitations due to the lack of versatility, modularity, and ease of implementation and are restricted to addressing only ligandable proteins. Herein, we report a nonsmall molecule-based autophagy-targeting nanobody chimera (ATNC), or phagobody, for selective degradation of intracellular targets, which overcomes these limitations. The core of an ATNC features a nanobody for recruiting proteins as well as an autophagic pathway-directing module. ATNC turns out to be a general, modular, and versatile degradation platform. We show that ATNC can be versatilely implemented in different ways including expressed ATNC intrabodies for ease of use, chemically induced proximity (CIP)-operated logic-gated conditional and tunable degradation, and cyclic cell-penetrating peptide-tethered cell-permeable phagobodies that selectively degrade the undruggable therapeutically relevant HE4 protein, resulting in effective suppression of ovarian cancer cell proliferation and migration. Overall, ATNC represents a general, modular, and versatile targeted degradation platform that degrades unligandable proteins and offers therapeutic potential.

Revised Cut-Off Value of Human Epididymis Protein 4 Enhances Its Use as an Ovarian Tumor Marker

OBJECTIVES

Human epididymis protein 4 (HE4), a protein secreted by ovarian tumors, has been used as an ovarian tumor marker. This study aimed to improve the usefulness of HE4 to detect malignant ovarian tumors by reviewing the cut-off values.

DESIGN

A retrospective study without intervention was conducted.

PARTICIPANTS

One hundred forty-nine healthy women (premenopausal, 126; postmenopausal, 23) and 24 patients with ovarian tumors (malignant, 12; benign, 12) participated in the study.

SETTING

The study used the Department of Obstetrics and Gynecology of a university hospital in Japan and the university hospital as a workplace from 2016 to 2018.

METHODS

The basic performance of the HE4 assay was evaluated, and the serum HE4 levels of participants were measured. Receiver operating characteristic analysis was performed using the HE4 data of the patients.

RESULTS

There were no significant differences in HE4 levels between the pre- and postmenopausal groups of healthy women. When the global cut-off values (premenopausal, 70 pmol/L; postmenopausal, 140 pmol/L) were adopted, the clinical sensitivity, specificity, positive predictive value, and negative predictive value were 41.7%, 91.7%, 83.3%, and 61.1%, respectively. Based on the results of the receiver operating characteristic analysis, we set the HE4 cut-off level at 60 pmol/L, regardless of the menopausal status. With the newly set cut-off value, the clinical sensitivity, specificity, positive predictive value, and negative predictive value were 66.7%, 91.7%, 88.9%, and 73.3%, respectively. That is, the clinical sensitivity of HE4 was improved without lowering specificity.

LIMITATIONS

The small number of subjects and the fact that the health status of the healthy women was evaluated based on questionnaires were limitations to the study.

CONCLUSION

A clinically useful cut-off value for HE4 as an ovarian tumor marker was established regardless of the menopausal status of the women, with improved clinical sensitivity, positive predictive value, and negative predictive value without lowering specificity. Currently, different cut-off values for HE4 in pre- and postmenopausal women are used globally. The cut-off value for CA125 was the same between pre- and postmenopausal women. Therefore, with the newly established cut-off value, HE4 can be used more conveniently in a non-specialized setting, especially when it is used in combination with CA125.

Utility of human epididymis protein 4 in the differential diagnosis of ascites

BACKGROUND AND AIMS

Human epididymal protein 4 (HE4) may be a useful tool in the differential diagnosis of malignant ascites. The aim of this study was to evaluate the diagnostic utility of HE4 for detecting malignant ascites, taking into account the possible false positives identified with adenosine deaminase (ADA), C-reactive protein (CRP), % polynuclear cells (%PMN) and glomerular filtration rate (eGFR).

METHODS

Concentrations of HE4, ADA, %PMN and CRP were determined in 114 samples of peritoneal fluid and creatinine in serum in order to calculate eGFR.

RESULTS

Concentrations of HE4 presented significant differences (P = 0.028) in benign [median (interquartile range)] [582(372)] pmol/L) and malignant ascites ([8241(367)] pmol/L. Sensitivity was 21.2% and specificity 100%. Significant differences were also observed for HE4 between tumors of gynecological origin ([3165(8769)] pmol/L) and others ([665(663)] pmol/L), with a sensitivity of 67% and a specificity of 100%. Classifying according to possible false positives (ADA > 45U/L, CRP > 50 mg/L, %PMN > 90 and eGFR < 30 mL/min/1.73 m2) at maximum specificity, a sensitivity of 33.3% was obtained for HE4, with a cut-off point of 2660 pmol/L. Without possible false positives (ADA < 45U/L, CRP < 50 mg/L, %PMN < 90 and eGFR ≥ 30 mL/min/1.73 m2), a sensitivity of 37.7% was obtained at 100% specificity for a cut-off point of 1041 pmol/L. Applying these criteria to the entire group, a sensitivity of 36.4% was obtained at maximum specificity.

CONCLUSIONS

HE4 allows the identification of malignant ascites with moderate sensitivity at maximum specificity. HE4 levels can differentiate between tumors of gynecological origin and others. Classification according to possible false positives increases sensitivity without losing specificity.

Diagnostic value of CA125, HE4, and systemic immune-inflammation index in the preoperative investigation of ovarian masses

This study aimed to ascertain the diagnostic accuracy of CA125, HE4, systemic immune-inflammation index (SII), fibrinogen-to-albumin ratio (FAR), prognostic nutritional index (PNI), and their combination for ovarian cancer (OC) to discover an optimal combined diagnostic index for early diagnosis of OC. A thorough investigation was conducted to ascertain the correlation between these markers and the pathological characteristics of OC, thereby providing a foundation for early identification and treatment of this disorder. One hundred seventy patients with documented OC and benign ovarian tumors (BOTs) treated at Hebei General Hospital between January 2019 and December 2022 were included in this retrospective study. Data analysis was conducted using IBM SPSS Statistics version V26.0, MedCalc Statistical Software version 19.4.0, and the R Environment for Statistical Computing software (R Foundation for Statistical Computing). Isolated CA125 showed the best application value for differentiating benign ovarian tumors from OC when the defined variables were compared separately. The combination of CA125, HE4, FAR, SII, and PNI displayed a greater area under the operating characteristic curve curve than any one of them or other combinations of the 5 variables. Compared to CA125 alone, the combination of CA125, HE4, FAR, SII, and PNI showed a slight gain in sensitivity (83.91%), negative predictive value (83.91%), accuracy (85.88%), and a decrease in negative likelihood ratio (0.180%). Higher preoperative CA125, HE4, SII, and FAR levels, and lower PNI levels predicted a higher probability of advanced OC progression and lymph node metastasis. FAR has better application value than other inflammation-related markers (PNI and SII). This study suggests that preoperative serum SII, PNI, and FAR may be clinically valuable markers in patients with OC. FAR has better application value than other inflammation-related markers (PNI and SII). As we delve deeper into the inflammatory mechanisms associated with tumors, we may discover more effective combinations of tumor and inflammatory biomarkers.

Update value and clinical application of MUC16 (cancer antigen 125)

INTRODUCTION

The largest transmembrane mucin, mucin 16 (MUC16), contains abundant glycosylation sites on the molecular surface, allowing it to participate in various molecular pathways. When cells lose polarity and become cancerous, MUC16 is overexpressed, and more of the extracellular region (cancer antigen [CA]125) is released into serum and possibly, promote the development of diseases. Thus, MUC16 plays an indispensable role in clinical research and application.

AREAS COVERED

This review summarizes the update proposed role of MUC16 in carcinogenesis and metastasis. Most importantly, we prospect its potential value in targeted therapy after screening 1226 articles published within the last 10 years from PubMed. Two reviewers screened each record and each report retrieved independently. We have summarized the progress of MUC16/CA125 in basic research and clinical application, and predicted its possible future development directions.

EXPERT OPINION

As an important noninvasive co-factor in the diagnosis of gynecological diseases, MUC16 has been used for a long time, especially in the diagnosis and treatment of ovarian cancer. The overexpression of MUC16 plays a very obvious role in regulating inflammatory response, supporting immune suppression, and promoting the proliferation, division, and metastasis of cancer cells. In the next 20 years, there will be a luxuriant clinical application of MUC16 as a target for immune monitoring and immunotherapy.

Diagnostic performance of IOTA SR and O-RADS combined with CA125, HE4, and risk of malignancy algorithm to distinguish benign and malignant adnexal masses

PURPOSE

To compare the diagnostic performance of International Ovarian Tumour Analysis Simple Rules (IOTA SR) and Ovarian-Adnexal Reporting and Data System (O-RADS), and to analyse whether combining IOTA SR and O-RADS with the biomarkers cancer antigen 125 (CA125), human epididymis protein 4 (HE4), and risk of malignancy algorithm (ROMA) further improves diagnostic performance in women with different menopause status.

METHODS

This study retrospectively included patients with ovarian adnexal masses confirmed by surgical pathology between September 2021 and February 2022. The area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the diagnostic efficacy of IOTA SR, O-RADS, and their combination with CA125, HE4, and ROMA.

RESULTS

This study included 1,179 ovarian adnexal masses. In all women, the AUC of IOTA SR was comparable to O-RADS (0.879 vs. 0.889, P = 0.361), and O-RADS had a significantly higher sensitivity than IOTA SR (95.77 % vs. 87.32 %, P < 0.001). In premenopausal women, O-RADS had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 93.33 %, 84.74 %, and 85.59 %, respectively. In postmenopausal women, IOTA SR + ROMA had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 85.37 %, 93.88 %, and 90.00 %, respectively.

CONCLUSIONS

Our study supports the high diagnostic value of IOTA SR or O-RADS alone in all women, and O-RADS was more sensitive than IOTA SR. In premenopausal women, O-RADS had the highest diagnostic value. In postmenopausal women, IOTA SR outperformed O-RADS, and IOTA SR + ROMA had the highest diagnostic value.

Detection of serum HE4 levels contributes to the diagnosis of lung cancer

Lung cancer (LC) is the most frequently diagnosed cancer and is the leading cause of cancer-associated death. Serum markers that exhibit high sensitivity and specificity for LC may assist in the diagnosis and prognosis of LC. The banked serum samples from 599 individuals, including 201 healthy controls, 124 patients with benign lung diseases, and 274 LC cases, were used. The serum concentrations of biomarkers were determined by electrochemiluminescence immunoassay and chemiluminescence immunoassay. The results showed that the serum human epididymis secretory protein 4 (HE4) levels in the LC group were significantly higher than in the healthy and benign lung disease groups. The serum levels of HE4, NSE, and CYFRA21-1 were significantly higher in patients with LC compared to those in the benign lung disease group. The area under the area under the curve (AUC) of HE4 for discriminating LC from healthy controls was 0.851 (95% CI, 0.818-0.884) and 0.739 (95% CI, 0.695-0.783), 0.747 (95% CI, 0.704-0.790), 0.626 (95% CI, 0.577-0.676), and 0.700 (95% CI, 0.653-0.747) for NSE, CYFRA21-1, SCC, and ProGRP, respectively. The AUC value of the combination of serum HE4 combined with NSE, CYFRA21-1, SCC, and proGRP for cancer diagnosis was 0.896 (95% CI, 0.868-0.923). In early LC, the AUC value of HE4 for discriminating early LC from healthy controls was 0.802 (95% CI, 0.758-0.845), 0.728 (95% CI, 0.679-0.778), 0.699 (95% CI, 0.646-0.752), 0.605 (95% CI, 0.548-0.662), and 0.685 (95% CI, 0.630-0.739) for NSE, CYFRA21-1, SCC, and ProGRP, respectively. The AUC value of the combination of serum HE4 with NSE, CYFRA21-1, SCC, and proGRP for early LC was 0.867 (95% CI, 0.831-0.903). Serum HE4 is a promising LC biomarker, particularly for early-stage LC. Measuring serum HE4 levels may improve the diagnostic efficiency of LC.

Prognostic Role of Human Epididymis Protein4 (HE4) in Endometrial Lesions: Study in a Tertiary Care Centre

Endometrial cancer accounts for 20% of malignant tumours in the female reproductive system. A novel biological marker human epididymis protein4 (HE4) represents an important alternative indicator which may benefit patient mortality. To correlate the immunohistochemical expression of HE4 in different non-neoplastic and neoplastic endometrial lesions and with the WHO grade of the tumours. Our study was a cross-sectional, observational study done in a tertiary care hospital from December 2019 to June 2021 on the hysterectomy sample of 50 patients with a clinical history of abnormal uterine bleeding and pelvic pain. The study showed strong positivity of HE4 in cases of endometrial carcinoma, weak positivity in cases of atypical endometrial hyperplasia, and negativity in cases of endometrial hyperplasia without atypia group. WHO grade 3(50%) and grade 2 (29%) endometrioid adenocarcinoma NOS in our study showed strong positivity for HE4 which was statistically significant (P value = 0.001). In recent studies using overexpression of HE4-related genes, the malignant biological behaviour such as cell adhesion, invasion, and proliferation was enhanced. It was seen in our study that strong positivity of HE4 was seen in all endometrial carcinoma groups and with higher WHO grade. So, HE4 may become a potential therapeutic target for advanced-stage endometrial carcinoma which requires further research. Thus, human epididymis-specific protein 4 (HE4) has been shown to be a promising marker for the detection of endometrial carcinoma patients who could be benefitted from targeted therapy.

Hsp90 is a potential risk factor for ovarian cancer prognosis: an evidence of a Chinese clinical center

BACKGROUND

The potential treatment effects of heat shock protein 90 (Hsp90) inhibitors in ovarian cancer (OC) are controversial. This research aims to investigate the relationship between the level of Hsp90 in peripheral blood and the prognosis of OC patients, as well as the clinicopathological indicators.

MATERIALS AND METHODS

We retrospectively collected the clinicopathological indicators of OC patients who were admitted to the Department of Obstetrics and Gynecology of the First Affiliated Hospital of Anhui Medical University from 2017 to 2022. Hsp90 level in patient blood was detected by enzyme-linked immunosorbent assay, and the correlation between Hsp90 level and OC prognosis was systematically investigated. Kaplan-Meier method was used to draw the survival curve, and the average survival time and survival rate were calculated. The log-rank test and Cox model were used for univariate survival analysis, and the Cox proportional hazards model was applied for multivariate survival analysis. Based on the TCGA dataset of OC obtained by cBioPortal, Pearson's correlation coefficients between Hsp90 level values and other mRNA expression values were calculated to further conduct bioinformatics analysis. GSEA and GSVA analysis were also conducted for gene functional enrichment. The expression of Hsp90 in OC tissues were evaluated and compared by Immunohistochemical staining.

RESULTS

According to the established screening criteria, 106 patients were selected. The enzyme-linked immunosorbent assay results showed that 50.94% OC patients with abnormal Hsp90 level. According to the outcome of Kaplan-Meier curves, the results revealed that the abnormal level of Hsp90 was suggested to poor prognosis (P = 0.001) of OC patients. Furthermore, the result of multivariate Cox proportional hazards regression model analysis also predicted that abnormal Hsp90 level (HR = 2.838, 95%CI = 1.139-7.069, P = 0.025) was linked to poor prognosis, which could be an independent prognostic factor for the prognosis of OC patients. Moreover, top 100 genes screened by Pearson's value associated with Hsp90, indicating that Hsp90 participated in the regulation of ATF5 target genes, PRAGC1A target genes and BANP target genes and also enriched in the metabolic processes of cell response to DNA damage stimulus, response to heat and protein folding.

CONCLUSION

Hsp90 level is positively associated with OC mortality and is a potential prognostic indicator of OC.

A Deep Learning Framework for the Prediction and Diagnosis of Ovarian Cancer in Pre- and Post-Menopausal Women

Ovarian cancer ranks as the fifth leading cause of cancer-related mortality in women. Late-stage diagnosis (stages III and IV) is a major challenge due to the often vague and inconsistent initial symptoms. Current diagnostic methods, such as biomarkers, biopsy, and imaging tests, face limitations, including subjectivity, inter-observer variability, and extended testing times. This study proposes a novel convolutional neural network (CNN) algorithm for predicting and diagnosing ovarian cancer, addressing these limitations. In this paper, CNN was trained on a histopathological image dataset, divided into training and validation subsets and augmented before training. The model achieved a remarkable accuracy of 94%, with 95.12% of cancerous cases correctly identified and 93.02% of healthy cells accurately classified. The significance of this study lies in overcoming the challenges associated with the human expert examination, such as higher misclassification rates, inter-observer variability, and extended analysis times. This study presents a more accurate, efficient, and reliable approach to predicting and diagnosing ovarian cancer. Future research should explore recent advances in this field to enhance the effectiveness of the proposed method further.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker - located on the mucin protein MUC16 - is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies - OC125, M11, "OC125-like," and "M11-like" - to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

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

BACKGROUND

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.

MATERIALS AND METHODS

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.

RESULTS

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).

CONCLUSIONS

The combination of TK1 protein with CA 125 or HE4 increased the potential of detecting ovarian cancer at early stages.

Diagnostic performance of CA125, HE4, ROMA, and CPH-I in identifying primary ovarian cancer

AIMS

To evaluate the ability of carbohydrate antigen 125 (CA125), human epididymis protein 4 (HE4), risk of ovarian malignancy algorithm (ROMA), and Copenhagen Index (CPH-I) to identify primary ovarian cancer (OC) from borderline and benign ovarian tumors (OTs) and explore ideal cutoff points.

METHODS

A total of 684 OTs containing 276 OC patients, 116 ovarian borderline OTs and 292 benign OTs patients who underwent surgery in our hospital were included. We retrospectively searched the results of CA125 and HE4 before patients' surgery from the hospital's electronic medical records system. ROMA and CPH-I were calculated according to their menopausal status and age, respectively. Diagnostic performance of these four were assessed by drawing receiver operating characteristic (ROC) curves.

RESULTS

CA125, HE4, ROMA, and CPH-I were all significantly higher in OC women compared with borderline OTs (p < 0.001), followed by benign OTs (p < 0.001). Area under the curves (AUCs) for distinguishing OC were 0.850 (0.818-0.882), 0.891 (0.865-0.916), 0.910 (0.888-0.933) and 0.906 (0.882-0.930), respectively, and the corresponding ideal cutoff values for CA125, HE4, ROMA, and CPH-I were 132.5, 68.6, 23.8, and 6.4, respectively. The difference between ROMA and CPH-I was not significant (p = 0.97), but both were higher than CA125 and HE4 (p < 0.05). HE4 showed a significantly higher AUC than CA125 (p < 0.05). For postmenopausal women, CA125 performed equivalently to ROMA (p = 0.73) and CPH-I (p = 0.91).

CONCLUSIONS

In identifying patients with OC, ROMA and CPH-I outperformed single tumor marker. The diagnostic performance of HE4 was significantly higher than that of CA125. CA125 was more suitable for postmenopausal women.

The hidden potential of glycomarkers: Glycosylation studies in the service of cancer diagnosis and treatment

Changes in the glycosylation process appear early in carcinogenesis and evolve with the growth and spread of cancer. The correlation of the characteristic glycosylation signature with the tumor stage and the appropriate therapy choice is an important issue in translational medicine. Oncologists also pay attention to extracellular vesicles as reservoirs of new cancer glycomarkers that can be potent for cancer diagnosis/prognosis. In this review, we recall glycomarkers used in oncology and show their new glycoforms of improved clinical relevance. We summarize current knowledge on the biological functions of glycoepitopes in cancer-derived extracellular vesicles and their potential use in clinical practice. Is glycomics a future of cancer diagnosis? It may be, but in combination with other omics analyses than alone.

Through the Looking Glass: Updated Insights on Ovarian Cancer Diagnostics

Epithelial ovarian cancer (EOC) is the deadliest gynaecological malignancy and the eighth most prevalent cancer in women, with an abysmal mortality rate of two million worldwide. The existence of multiple overlapping symptoms with other gastrointestinal, genitourinary, and gynaecological maladies often leads to late-stage diagnosis and extensive extra-ovarian metastasis. Due to the absence of any clear early-stage symptoms, current tools only aid in the diagnosis of advanced-stage patients, wherein the 5-year survival plummets further to less than 30%. Therefore, there is a dire need for the identification of novel approaches that not only allow early diagnosis of the disease but also have a greater prognostic value. Toward this, biomarkers provide a gamut of powerful and dynamic tools to allow the identification of a spectrum of different malignancies. Both serum cancer antigen 125 (CA-125) and human epididymis 4 (HE4) are currently being used in clinics not only for EOC but also peritoneal and GI tract cancers. Screening of multiple biomarkers is gradually emerging as a beneficial strategy for early-stage diagnosis, proving instrumental in administration of first-line chemotherapy. These novel biomarkers seem to exhibit an enhanced potential as a diagnostic tool. This review summarizes existing knowledge of the ever-growing field of biomarker identification along with potential future ones, especially for ovarian cancer.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker-located on the mucin protein MUC16-is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies-OC125, M11, "OC125-like," and "M11-like"-to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Current and emerging biomarkers in ovarian cancer diagnosis; CA125 and beyond

Ovarian cancer (OC) is one of the most common causes of cancer-related death in women worldwide. Its five-year survival rates are worse than the two most common gynecological cancers, cervical and endometrial. This is because it is asymptomatic in the early stages and usually detected in the advanced metastasized stage. Thus, survival is increasingly dependent on timely diagnosis. The delay in detection is contributed partly by the occurrence of non-specific clinical symptoms in the early stages and the lack of effective biomarkers and detection approaches. This underlines the need for biomarker identification and clinical validation, enabling earlier diagnosis, effective prognosis, and response to therapy. Apart from the traditional diagnostic biomarkers for OC, several new biomarkers have been delineated using advanced high-throughput molecular approaches in recent years. They are currently being clinically evaluated for their true diagnostic potential. In this chapter, we document the commonly utilized traditional screening markers and recently identified emerging biomarkers in OC diagnosis, focusing on secretory and protein biomarkers. We also briefly reviewed the recent advances and prospects in OC diagnosis.

LINE-1 ORF1p as a candidate biomarker in high grade serous ovarian carcinoma

Long interspersed element 1 (LINE-1) open reading frame 1 protein (ORF1p) expression is a common feature of many cancer types, including high-grade serous ovarian carcinoma (HGSOC). Here, we report that ORF1p is not only expressed but also released by ovarian cancer and primary tumor cells. Immuno-multiple reaction monitoring-mass spectrometry assays showed that released ORF1p is confidently detectable in conditioned media, ascites, and patients' plasma, implicating ORF1p as a potential biomarker. Interestingly, ORF1p expression is detectable in fallopian tube (FT) epithelial precursors of HGSOC but not in benign FT, suggesting that ORF1p expression in an early event in HGSOC development. Finally, treatment of FT cells with DNA methyltransferase inhibitors led to robust expression and release of ORF1p, validating the regulatory role of DNA methylation in LINE-1 repression in non-tumorigenic tissue.

Identification and Characterization of Aptamers Targeting Ovarian Cancer Biomarker Human Epididymis Protein 4 for the Application in Urine

Ovarian cancer is the deadliest gynecological cancer. With non-specific symptoms of the disease and the lack of effective diagnostic methods, late diagnosis remains the crucial hurdle of the poor prognosis. Therefore, development of novel diagnostic approaches are needed. The purpose of this study is to develop DNA-based aptamers as potential diagnostic probes to detect ovarian cancer biomarker Human epididymis protein 4 (HE4) in urine. HE4 is a protein overexpressed in ovarian cancer, but not in healthy or benign conditions. With high stability and diagnostic value for detection of ovarian cancer, urine HE4 appears as an attractive non-invasive biomarker. The high-affinity anti-HE4 DNA aptamers were selected through 10 cycles of High Fidelity Systematic Evolution of Ligands by EXponential enrichment (Hi-Fi SELEX), a method for aptamer selection based on digital droplet PCR. The anti-HE4 aptamers were identified using DNA sequencing and bioinformatics analysis. The candidate aptamer probes were characterized in urine for binding to HE4 protein using thermofluorimetry. Two anti-HE4 aptamers, AHE1 and AHE3, displayed binding to HE4 protein in urine, with a constant of dissociation in the nanomolar range, with K_d (AHE1) = 87 ± 9 nM and K_d (AHE3) aptamer of 127 ± 28 nM. Therefore, these aptamers could be promising tools for application in diagnostics and future development of urine tests or biosensors for ovarian cancer.

Comparison of ultrasound-based ADNEX model with magnetic resonance imaging for discriminating adnexal masses: a multi-center study

Objectives

The ADNEX model offered a good diagnostic performance for discriminating adnexal tumors, but research comparing the abilities of the ADNEX model and MRI for characterizing adnexal tumors has not been reported to our knowledge. The aim of this study was to evaluate the diagnostic accuracy of the ultrasound-based ADNEX (Assessment of Different NEoplasias in the adneXa) model in comparison with that of magnetic resonance imaging (MRI) for differentiating benign, borderline and malignant adnexal masses.

Methods

This prospective study included 529 women with adnexal masses who underwent assessment via the ADNEX model and subjective MRI analysis before surgical treatment between October 2019 and April 2022 at two hospitals. Postoperative histological diagnosis was considered the gold standard.

Results

Among the 529 women, 92 (17.4%) masses were diagnosed histologically as malignant tumors, 67 (12.7%) as borderline tumors, and 370 (69.9%) as benign tumors. For the diagnosis of malignancy, including borderline tumors, overall agreement between the ADNEX model and MRI pre-operation was 84.9%. The sensitivity of the ADNEX model of 0.91 (95% confidence interval [CI]: 0.85-0.95) was similar to that of MRI (0.89, 95% CI: 0.84-0.94; P=0.717). However, the ADNEX model had a higher specificity (0.90, 95% CI: 0.87-0.93) than MRI (0.81, 95% CI: 0.77-0.85; P=0.001). The greatest sensitivity (0.96, 95% CI: 0.92-0.99) and specificity (0.94, 95% CI: 0.91-0.96) were achieved by combining the ADNEX model and subjective MRI assessment. While the total diagnostic accuracy did not differ significantly between the two methods (P=0.059), the ADNEX model showed greater diagnostic accuracy for borderline tumors (P<0.001).

Conclusion

The ultrasound-based ADNEX model demonstrated excellent diagnostic performance for adnexal tumors, especially borderline tumors, compared with MRI. Accordingly, we recommend that the ADNEX model, alone or with subjective MRI assessment, should be used for pre-operative assessment of adnexal masses.

The Discrepancy between Preoperative Tumor Markers and Imaging Outcomes in Predicting Ovarian Malignancy

Preoperative tumor markers and imaging often differ in predicting whether an ovarian tumor is malignant. Therefore, we evaluated the correlation between the predictive values of imaging and tumor markers for diagnosing ovarian tumors, especially when there were discrepancies between the two. We enrolled 1047 patients with ovarian tumors. The predictive values and concordance rates between the preoperative risk of ovarian malignancy algorithm (ROMA) and imaging, including CT and MRI, were evaluated. Diagnoses of 561 CT (77.9%) and 322 MRI group (69.2%) participants were consistent with the ROMA. Among them, 96.4% of the CT (541/561) and 92.5% of the MRI (298/322) group predicted an accurate diagnosis. In contrast, 67.3% (101/150) of CT and 75.2% (100/133) of MRI cases accurately predicted the diagnosis in cases with discrepancies between ROMA and CT or MRI; a total of 32% (48/150) of the CT and 25.5% (34/133) of the MRI group showed an accurate ROMA diagnosis in cases with discrepancies between ROMA and imaging. In the event of a discrepancy between ROMA and imaging when ovarian tumor malignancy prediction, the question is which method should take precedence. This study demonstrates that MRI has the greatest diagnostic accuracy, followed by CT and ROMA. It is also important to understand underlying diseases and benign conditions and rare histopathologies of malignant tumors.

HE4 Tissue Expression as A Putative Prognostic Marker in Low-Risk/Low-Grade Endometrioid Endometrial Cancer: A Review

Low-grade stage I endometrioid endometrial carcinomas should have an excellent prognosis, but a small subset of these cancers can relapse. The search for putative immunohistochemical prognostic markers for relapse in low-risk/low-grade endometrioid endometrial cancers remains open. Among the candidate molecules that may implicate the roles of immunohistochemical risk markers, we focused our attention on human epididymis protein 4 (HE4) after a review of the literature. Few authors have devoted themselves to this topic, and none have found a correlation between the tissue expression of HE4 and the molecular classification of endometrial cancer. Five different variants of HE4 mRNA and multiple protein isoforms of HE4 were identified many years ago, but current HE4 assays only measure the total HE4 expression and do not distinguish the different proteins encoded by different mRNA variants. It is important to have an approach to distinguish specific variants in the future.

Ovarian cancer stem cells: Critical roles in anti-tumor immunity

Ovarian cancer is a significant cause of cancer-related mortality in women. Over the past 3 decades, there has been a high incidence of recurrent chemoresistant disease, despite the relative effectiveness of current treatment strategies. This is partly attributed to cancer stem cells (CSC), a subpopulation that has acquired stem cell properties that allow these cells to evade standard chemotherapy and cause disease recurrence. Therefore, there is an urgent need for basic knowledge about CSC to develop innovative therapeutic approaches for ovarian cancer. These CSC subpopulations have been identified in ovarian cancer cell lines, tumors or ascites, and findings suggest that ovarian CSCs may be as heterogeneous as the disease itself. CSCs regulate the phenotype and function of immune cells involved in antitumor immunity, so a better understanding of the signaling pathways that interact between CSCs, immune cells and tumor cells will pave the way for the clinical application of CS in cancer immunotherapy. This review will focus on the markers currently used to identify and isolate these cells summarize current knowledge on the molecular and cellular mechanisms responsible for CSC-dependent regulation of antitumor immune responses. We will discuss the signaling pathways involved in CSC survival, replication, and differentiation as well as potential therapeutic targeting strategies.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

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 (K_D~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.

Automated classification of protein expression levels in immunohistochemistry images to improve the detection of cancer biomarkers

Background

The expression changes of some proteins are associated with cancer progression, and can be used as biomarkers in cancer diagnosis. Automated systems have been frequently applied in the large-scale detection of protein biomarkers and have provided a valuable complement for wet-laboratory experiments. For example, our previous work used an immunohistochemical image-based machine learning classifier of protein subcellular locations to screen biomarker proteins that change locations in colon cancer tissues. The tool could recognize the location of biomarkers but did not consider the effect of protein expression level changes on the screening process.

Results

In this study, we built an automated classification model that recognizes protein expression levels in immunohistochemical images, and used the protein expression levels in combination with subcellular locations to screen cancer biomarkers. To minimize the effect of non-informative sections on the immunohistochemical images, we employed the representative image patches as input and applied a Wasserstein distance method to determine the number of patches. For the patches and the whole images, we compared the ability of color features, characteristic curve features, and deep convolutional neural network features to distinguish different levels of protein expression and employed deep learning and conventional classification models. Experimental results showed that the best classifier can achieve an accuracy of 73.72% and an F1-score of 0.6343. In the screening of protein biomarkers, the detection accuracy improved from 63.64 to 95.45% upon the incorporation of the protein expression changes.

Conclusions

Machine learning can distinguish different protein expression levels and speed up their annotation in the future. Combining information on the expression patterns and subcellular locations of protein can improve the accuracy of automatic cancer biomarker screening. This work could be useful in discovering new cancer biomarkers for clinical diagnosis and research.

Diagnostics of Ovarian Tumors in Postmenopausal Patients

Early diagnosis of ovarian cancer remains an urgent issue owing to the continuing trend towards increasing incidence along with only marginal improvements in mortality and 5-year survival rates. Furthermore, there is a lack of a clear formulation of the concept of pathogenesis. The diagnostic values of tumor markers, their potential advantages and disadvantages, and their combination with radiation imaging methods and transvaginal sonography are discussed. More advanced imaging techniques, such as computed tomography and magnetic resonance imaging have proven too expensive for widespread use. According to the World Health Organization, more than half of the world’s population does not have access to diagnostic imaging. Consequently, there is high demand for a low-cost, reliable, and safe imaging system for detecting and monitoring cancer. Currently, there is no clear algorithm available for examining and accurately diagnosing patients with postmenopausal ovarian tumors; moreover, reliable criteria allowing dynamic observation and for determining surgical access and optimal surgical intervention measures in postmenopausal patients are lacking. Medical microwave radiometry shows promising results yielding an accuracy of 90%.

Roles of Antimicrobial Peptides in Gynecological Cancers

Antimicrobial peptides (AMPs) are essential components of the mucosal barrier of the female reproductive tract (FRT) and are involved in many important physiological processes, including shaping the microbiota and maintaining normal reproduction and pregnancy. Gynecological cancers seriously threaten women's health and bring a heavy burden to society so that new strategies are needed to deal with these diseases. Recent studies have suggested that AMPs also have a complex yet intriguing relationship with gynecological cancers. The expression level of AMPs changes during tumor progression and they may act as promising biomarkers in cancer detection and prognosis prediction. Although AMPs have long been considered as host protective, they actually play a "double-edged sword" role in gynecological cancers, either tumorigenic or antitumor, depending on factors such as AMP and cancer types, as well as AMP concentrations. Moreover, AMPs are associated with chemoresistance and regulation of AMPs' expression may alter sensitivity of cancer cells to chemotherapy. However, more work is needed, especially on the identification of molecular mechanisms of AMPs in the FRT, as well as the clinical application of these AMPs in detection, diagnosis and treatment of gynecological malignancies.

Human epididymis protein 4 (HE4) is a novel immunohistochemical marker of neuroendocrine differentiation

Human epididymis protein 4 (HE4) is originally described as an epididymis specific protein and now clinically used as a serum marker for ovarian carcinoma. However, the expression of HE4 in neuroendocrine neoplasms (NENs) has not been studied. By immunohistochemistry, the expressions of HE4 in 94 normal tissues and 484 NENs which included 242 well-differentiated NENs and 242 poorly differentiated NENs were studied. HE4 was positive in 90/94 (95.7%) of the neuroendocrine cells in normal tissues, 228/242 (94.2%) of well-differentiated NENs, and 206/242 (85.1%) of poorly differentiated NENs, and the expression of HE4 decreased progressively with loss of histological differentiation, with the positive rate of 96.2%, 92.7%, 92.3%, 85.4%, and 84.4% in NET-G1/carcinoid, NET-G2/atypical carcinoid, NET-G3, NEC-LC, and NEC-SC respectively. In NET-G1 and NET-G2, HE4 staining showed a peculiar polarized distribution, with an extraordinarily strong granular staining in subnuclear cytoplasm. A diffuse and uniform cytoplastic HE4 staining was observed in NET-G3 and poorly differentiated NENs. The positive rate of HE4 in primary tumors (91.1%, 387/425) was significantly higher than that of metastases (79.7%, 47/59) (p < 0.05). In a series of 70 pure non-NENs poorly differentiated carcinomas, the specificity rate of HE4 was 92.9% (65/70), which was in line with that of Syn. The negative rate of HE4 was 87.0% (40/46) in the non-neuroendocrine components of the MiNEN cases, which was lower than that of the pure non-neuroendocrine carcinomas (92.9%, 65/70) but without statistical significance (p > 0.05). HE4 may prove to be a useful immunohistochemical marker of neuroendocrine differentiation, although comparative studies and a more extensive analysis of other tissue types are necessary.

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

Background

To evaluate the diagnostic value of adding human epididymis protein 4 (HE4), cancer antigen 125 (CA125) and risk of malignancy algorithm (ROMA) to ultrasound for detecting ovarian cancer in patients with a pelvic mass.

Methods

This was a prospective, observational, multicenter study. Patients aged > 18 years who were scheduled to undergo surgery for a suspicious pelvic mass had CA125 and HE4 levels measured prior to surgery, in addition to a routine transvaginal ultrasound scan. The diagnostic performance of CA125, HE4 and ROMA for distinguishing between benign and malignant adnexal masses was assessed using receiver operating characteristic (ROC) analysis and the corresponding area under the curve (AUC).

Results

Of 965 evaluable patients, 804 were diagnosed with benign tumors and 161 were diagnosed with ovarian cancer. In late-stage ovarian cancer, CA125, HE4 and ROMA all had an excellent diagnostic performance (AUC > 0.92), whereas in stage I and II, diagnostic performance of all three biomarkers was less adequate (AUC < 0.77). In the differential diagnosis of ovarian cancer and endometriosis, ROMA and HE4 performed better than CA125 with 99 and 98.1% versus 75.0% sensitivity, respectively, at 75.4% specificity.

Conclusions

ROMA and HE4 could be valuable biomarkers to help with the diagnosis of ovarian cancer in premenopausal patients in order to differentiate from endometriosis, whereas CA125 may be more adequate for postmenopausal patients.

• Serum biomarkers can help to distinguish benign from malignant pelvic masses

• We evaluated the diagnostic value of adding HE4, CA125 and ROMA to ultrasound for detecting ovarian cancer

• In stage III and IV ovarian cancer all three biomarkers showed excellent performance

• ROMA and HE4 performed better than CA125 in the differential diagnosis of ovarian cancer and endometriosis

Menopausal status, ultrasound and biomarker tests in combination for the diagnosis of ovarian cancer in symptomatic women

BACKGROUND

Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Diagnostic delays are caused by non-specific symptoms. Existing systematic reviews have not comprehensively covered tests in current practice, not estimated accuracy separately in pre- and postmenopausal women, or used inappropriate meta-analytic methods.

OBJECTIVES

To establish the accuracy of combinations of menopausal status, ultrasound scan (USS) and biomarkers for the diagnosis of ovarian cancer in pre- and postmenopausal women and compare the accuracy of different test combinations.

SEARCH METHODS

We searched CENTRAL, MEDLINE (Ovid), Embase (Ovid), five other databases and three trial registries from 1991 to 2015 and MEDLINE (Ovid) and Embase (Ovid) form June 2015 to June 2019. We also searched conference proceedings from the European Society of Gynaecological Oncology, International Gynecologic Cancer Society, American Society of Clinical Oncology and Society of Gynecologic Oncology, ZETOC and Conference Proceedings Citation Index (Web of Knowledge). We searched reference lists of included studies and published systematic reviews.

SELECTION CRITERIA

We included cross-sectional diagnostic test accuracy studies evaluating single tests or comparing two or more tests, randomised trials comparing two or more tests, and studies validating multivariable models for the diagnosis of OC investigating test combinations, compared with a reference standard of histological confirmation or clinical follow-up in women with a pelvic mass (detected clinically or through USS) suspicious for OC.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data and assessed quality using QUADAS-2. We used the bivariate hierarchical model to indirectly compare tests at commonly reported thresholds in pre- and postmenopausal women separately. We indirectly compared tests across all thresholds and estimated sensitivity at fixed specificities of 80% and 90% by fitting hierarchical summary receiver operating characteristic (HSROC) models in pre- and postmenopausal women separately.

MAIN RESULTS

We included 59 studies (32,059 women, 9545 cases of OC). Two tests evaluated the accuracy of a combination of menopausal status and USS findings (IOTA Logistic Regression Model 2 (LR2) and the Assessment of Different NEoplasias in the adneXa model (ADNEX)); one test evaluated the accuracy of a combination of menopausal status, USS findings and serum biomarker CA125 (Risk of Malignancy Index (RMI)); and one test evaluated the accuracy of a combination of menopausal status and two serum biomarkers (CA125 and HE4) (Risk of Ovarian Malignancy Algorithm (ROMA)). Most studies were at high or unclear risk of bias in participant, reference standard, and flow and timing domains. All studies were in hospital settings. Prevalence was 16% (RMI, ROMA), 22% (LR2) and 27% (ADNEX) in premenopausal women and 38% (RMI), 45% (ROMA), 52% (LR2) and 55% (ADNEX) in postmenopausal women. The prevalence of OC in the studies was considerably higher than would be expected in symptomatic women presenting in community-based settings, or in women referred from the community to hospital with a suspicion of OC. Studies were at high or unclear applicability because presenting features were not reported, or USS was performed by experienced ultrasonographers for RMI, LR2 and ADNEX. The higher sensitivity and lower specificity observed in postmenopausal compared to premenopausal women across all index tests and at all thresholds may reflect highly selected patient cohorts in the included studies. In premenopausal women, ROMA at a threshold of 13.1 (± 2), LR2 at a threshold to achieve a post-test probability of OC of 10% and ADNEX (post-test probability 10%) demonstrated a higher sensitivity (ROMA: 77.4%, 95% CI 72.7% to 81.5%; LR2: 83.3%, 95% CI 74.7% to 89.5%; ADNEX: 95.5%, 95% CI 91.0% to 97.8%) compared to RMI (57.2%, 95% CI 50.3% to 63.8%). The specificity of ROMA and ADNEX were lower in premenopausal women (ROMA: 84.3%, 95% CI 81.2% to 87.0%; ADNEX: 77.8%, 95% CI 67.4% to 85.5%) compared to RMI 92.5% (95% CI 90.3% to 94.2%). The specificity of LR2 was comparable to RMI (90.4%, 95% CI 84.6% to 94.1%). In postmenopausal women, ROMA at a threshold of 27.7 (± 2), LR2 (post-test probability 10%) and ADNEX (post-test probability 10%) demonstrated a higher sensitivity (ROMA: 90.3%, 95% CI 87.5% to 92.6%; LR2: 94.8%, 95% CI 92.3% to 96.6%; ADNEX: 97.6%, 95% CI 95.6% to 98.7%) compared to RMI (78.4%, 95% CI 74.6% to 81.7%). Specificity of ROMA at a threshold of 27.7 (± 2) (81.5, 95% CI 76.5% to 85.5%) was comparable to RMI (85.4%, 95% CI 82.0% to 88.2%), whereas for LR2 (post-test probability 10%) and ADNEX (post-test probability 10%) specificity was lower (LR2: 60.6%, 95% CI 50.5% to 69.9%; ADNEX: 55.0%, 95% CI 42.8% to 66.6%).

AUTHORS' CONCLUSIONS

In specialist healthcare settings in both premenopausal and postmenopausal women, RMI has poor sensitivity. In premenopausal women, ROMA, LR2 and ADNEX offer better sensitivity (fewer missed cancers), but for ROMA and ADNEX this is off-set by a decrease in specificity and increase in false positives. In postmenopausal women, ROMA demonstrates a higher sensitivity and comparable specificity to RMI. ADNEX has the highest sensitivity in postmenopausal women, but reduced specificity. The prevalence of OC in included studies is representative of a highly selected referred population, rather than a population in whom referral is being considered. The comparative accuracy of tests observed here may not be transferable to non-specialist settings. Ultimately health systems need to balance accuracy and resource implications to identify the most suitable test.

Tissue factor pathway inhibitor 2: A potential diagnostic marker for discriminating benign from malignant ovarian tumors

OBJECTIVES

Carbohydrate antigen 125 (CA125), CA19-9, carcinoembryonic antigen (CEA), human epididymis protein 4 (HE4), and the Risk of Ovarian Malignancy Algorithm (ROMA) are widely used as tumor markers and algorithms for the diagnosis of ovarian cancer (OC). Tissue factor pathway inhibitor 2 (TFPI2) has been developed as a potential serodiagnostic marker for OC in Japan. The aim of this study is to evaluate the diagnostic accuracy of the six markers alone and in combination to find the best marker for discriminating between benign and malignant ovarian tumors.

METHODS

Frozen serum samples collected from 484 patients were divided into three groups based on histopathological results: OC (n = 119), borderline ovarian tumors (BR) (n = 48), and benign ovarian tumors (BN) (n = 317). Diagnostic accuracy was calculated with an area under a receiver operating characteristic (AUC) curve.

RESULTS

TFPI2 achieved the highest discrimination between the OC + BR group versus the BN group (AUC 0.8076). ROMA values best discriminated patients with OC from those with BN (AUC, 0.8966), which was equivalent to TFPI2 (AUC, 0.8937). For discriminating the OC group from the BR + BN group, the highest AUC value was achieved by ROMA values (AUC, 0.8884), and TFPI2 also showed comparable diagnostic accuracy (AUC, 0.8845). Combining TFPI2 with ROMA had the highest AUC (0.8420-0.9357).

CONCLUSION

TFPI2 may be a clinically useful single marker comparable to conventional ROMA values for discriminating between benign and malignant ovarian tumors.

Current Advances in PD-1/PD-L1 Blockade in Recurrent Epithelial Ovarian Cancer

Immunotherapies have revolutionized the treatment of a variety of cancers. Epithelial ovarian cancer is the most lethal gynecologic malignancy, and the rate of advanced tumor progression or recurrence is as high as 80%. Current salvage strategies for patients with recurrent ovarian cancer are rarely curative. Recurrent ovarian cancer is a “cold tumor”, predominantly due to a lack of tumor antigens and an immunosuppressive tumor microenvironment. In trials testing programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) blockade as a monotherapy, the response rate was only 8.0-22.2%. In this review, we illustrate the status of cold tumors in ovarian cancer and summarize the existing clinical trials investigating PD-1/PD-L1 blockade in recurrent ovarian cancer. Increasing numbers of immunotherapy combination trials have been set up to improve the response rate of EOC. The current preclinical and clinical development of immunotherapy combination therapy to convert an immune cold tumor into a hot tumor and their underlying mechanisms are also reviewed. The combination of anti-PD-1/PD-L1 with other immunomodulatory drugs or therapies, such as chemotherapy, antiangiogenic therapies, poly (ADP-ribose) polymerase inhibitors, adoptive cell therapy, and oncolytic therapy, could be beneficial. Further efforts are merited to transfer these results to a broader clinical application.

Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.

Analytical Validation of a Deep Neural Network Algorithm for the Detection of Ovarian Cancer

Early detection of ovarian cancer, the deadliest gynecologic cancer, is crucial for reducing mortality. Current noninvasive risk assessment measures include protein biomarkers in combination with other clinical factors, which vary in their accuracy. Machine learning can be applied to optimizing the combination of these features, leading to more accurate assessment of malignancy. However, the low prevalence of the disease can make rigorous validation of these tests challenging and can result in unbalanced performance.

The Comparison of Three Predictive Indexes to Discriminate Malignant Ovarian Tumors from Benign Ovarian Endometrioma: The Characteristics and Efficacy

This study aimed to evaluate the prediction efficacy of malignant transformation of ovarian endometrioma (OE) using the Copenhagen Index (CPH-I), the risk of ovarian malignancy algorithm (ROMA), and the R2 predictive index. This retrospective study was conducted at the Department of Gynecology, Nara Medical University Hospital, from January 2008 to July 2021. A total of 171 patients were included in the study. In the current study, cases were divided into three cohorts: pre-menopausal, post-menopausal, and a combined cohort. Patients with benign ovarian tumor mainly received laparoscopic surgery, and patients with suspected malignant tumors underwent laparotomy. Information from a review chart of the patients’ medical records was collected. In the combined cohort, a multivariate analysis confirmed that the ROMA index, the R2 predictive index, and tumor laterality were extracted as independent factors for predicting malignant tumors (hazard ratio (HR): 222.14, 95% confidence interval (CI): 22.27−2215.50, p < 0.001; HR: 9.80, 95% CI: 2.90−33.13, p < 0.001; HR: 0.15, 95% CI: 0.03−0.75, p = 0.021, respectively). In the pre-menopausal cohort, a multivariate analysis confirmed that the CPH index and the R2 predictive index were extracted as independent factors for predicting malignant tumors (HR: 6.45, 95% CI: 1.47−28.22, p = 0.013; HR: 31.19, 95% CI: 8.48−114.74, p < 0.001, respectively). Moreover, the R2 predictive index was only extracted as an independent factor for predicting borderline tumors (HR: 45.00, 95% CI: 7.43−272.52, p < 0.001) in the combined cohort. In pre-menopausal cases or borderline cases, the R2 predictive index is useful; while, in post-menopausal cases, the ROMA index is better than the other indexes.

Multiple biomarkers are more accurate than a combination of carbohydrate antigen 125 and human epididymis protein 4 for ovarian cancer screening

Objective

The objective of this study was to compare and evaluate the diagnostic value of serum carbohydrate antigen 125 (CA125) and/or human epididymis protein 4 (HE4) and a panel of novel multiple biomarkers in patients with ovarian tumors to identify more accurate and effective markers for screening ovarian cancer.

Methods

Candidate ovarian cancer biomarkers were selected based on a literature search. Dozens of candidate biomarkers were examined using 143 serum samples from patients with ovarian cancer and 157 healthy serum samples as non-cancer controls. To select the optimal marker panel for an ovarian cancer classification model, a set of biomarker panels was created with the number of possible combinations of 8 biomarkers. Using the set of biomarkers as an input variable, the optimal biomarker panel was selected by examining the performance of the biomarker panel set using the Random Forest algorithm as a non-linear classification method and a 10-fold cross-validation technique.

Results

The final selected optimal combination of five biomarkers (CA125, HE4, CA15.3, ApoA1, and ApoA2) exhibited a sensitivity of 93.71% and specificity of 93.63% for ovarian cancer detection during validation.

Conclusion

Combining multiple biomarkers is a valid strategy for ovarian cancer diagnosis and can be used as a minimally invasive screening method for early ovarian cancer. A panel of five optimal biomarkers, including CA125 and HE4, was verified in this study. These can potentially be used as clinical biomarkers for early detection of ovarian cancer.

The Interplay Between Cervicovaginal Microbial Dysbiosis and Cervicovaginal Immunity

The cervicovaginal microbiota plays a key role in the health and reproductive outcomes of women. In reality epidemiological studies have demonstrated that there is an association between the structure of cervicovaginal microbiota and reproductive health, although key mechanistic questions regarding these effects remain unanswered and understanding the interplay between the immune system and the structure of the cervicovaginal microbiota. Here, we review existing literature relating to the potential mechanisms underlying the interaction between vaginal microbes and the immune system; we also describe the composition and function of the microbiome and explain the mechanisms underlying the interactions between these microbial communities and various aspects of the immune system. Finally, we also discuss the diseases that are caused by disorders of the reproductive tract and how the immune system is involved. Finally, based on the data presented in this review, the future perspectives in research directions and therapeutic opportunities are explored.

Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study

Ovarian cancer (OC) is the most lethal genital malignancy in women. We aimed to develop and validate new proteomic-based models for non-invasive diagnosis of OC. We also compared them to the modified Risk of Ovarian Malignancy Algorithm (ROMA-50), the Copenhagen Index (CPH-I) and our earlier Proteomic Model 2017. Biomarkers were assessed using bead-based multiplex technology (Luminex®) in 356 women (250 with malignant and 106 with benign ovarian tumors) from five European centers. The training cohort included 279 women from three centers, and the validation cohort 77 women from two other centers. Of six previously studied serum proteins (CA125, HE4, osteopontin [OPN], prolactin, leptin, and macrophage migration inhibitory factor [MIF]), four contributed significantly to the Proteomic Model 2021 (CA125, OPN, prolactin, MIF), while leptin and HE4 were omitted by the algorithm. The Proteomic Model 2021 revealed a c-index of 0.98 (95% CI 0.96, 0.99) in the training cohort; however, in the validation cohort it only achieved a c-index of 0.82 (95% CI 0.72, 0.91). Adding patient age to the Proteomic Model 2021 constituted the Combined Model 2021, with a c-index of 0.99 (95% CI 0.97, 1) in the training cohort and a c-index of 0.86 (95% CI 0.78, 0.95) in the validation cohort. The Full Combined Model 2021 (all six proteins with age) yielded a c-index of 0.98 (95% CI 0.97, 0.99) in the training cohort and a c-index of 0.89 (95% CI 0.81, 0.97) in the validation cohort. The validation of our previous Proteomic Model 2017, as well as the ROMA-50 and CPH-I revealed a c-index of 0.9 (95% CI 0.82, 0.97), 0.54 (95% CI 0.38, 0.69) and 0.92 (95% CI 0.85, 0.98), respectively. In postmenopausal women, the three newly developed models all achieved a specificity of 1.00, a positive predictive value (PPV) of 1.00, and a sensitivity of >0.9. Performance in women under 50 years of age (c-index below 0.6) or with normal CA125 (c-index close to 0.5) was poor. CA125 and OPN had the best discriminating power as single markers. In summary, the CPH-I, the two combined 2021 Models, and the Proteomic Model 2017 showed satisfactory diagnostic accuracies, with no clear superiority of either model. Notably, although combining values of only four proteins with age, the Combined Model 2021 performed comparably to the Full Combined Model 2021. The models confirmed their exceptional diagnostic performance in women aged ≥50. All models outperformed the ROMA-50.

Prognostic Significance of HE4 Tissue Expression in Serous Epithelial Ovarian Carcinoma

Background Human Epididymis protein 4 (HE4) is expressed in ovarian cancer. Preoperative serum testing is still not widely available. This pilot study aimed to investigate the magnitude of expression of HE4 in tissue sections of serous epithelial ovarian carcinoma, its correlation with clinical outcome, and the feasibility of HE4 immunohistochemistry as a prognostic marker.

Materials and Method In this ambispective study, immunohistochemistry (IHC) was used to evaluate tissue sections of ovarian serous epithelial carcinoma at primary cytoreductive surgery. On HE4 immunohistochemistry (IHC), the magnitude of HE4 expression was assessed categorically as high or low HE4 expression and semiquantitatively by the H-score, and correlated with clinical outcome in terms of survival status, progression-free survival, and overall survival.

Results Of 32 cases, most (n = 31, 96.8%) were positive for HE4 IHC. The mean age was 49 ± 8.2 years; 29 (90.6%) patients were in FIGO stage IIIC; 25 (78.9%) had ≥1cm residual disease after surgery; 31 (96.8%) received adjuvant chemotherapy, either 3-weekly (n = 25, 81.2%) or dose-dense weekly (n = 6, 18.8%) regimen. The majority (n = 31, 96.8%) had a high-grade tumor, of whom 19 (59.4%) had high HE4 expression and 13(40.6%) patients had H-score in the range of 5 to 8. The mean H-score was 6.97 ± 3.61 (range 0 to 12). The overall survival of the study population at 64 months was 36.65% (95% CI: 8.59–66.34), with median overall survival of 59 months. A new scoring system was developed combining categorical HE4 expression and serum CA-125 levels; the combination of HE4 expression with postoperative CA-125 levels was found to be the best prognostic marker for overall survival (p = 0.05). A composite score of 2 identified patients with poor progression-free survival (HR 4.64, p = 0.039) and overall survival (HR 5.45, p = 0.05).

Conclusion The new composite scoring system using HE4 IHC with postoperative serum CA-125 levels offers an extremely useful option for prognosticating patients with serous epithelial ovarian carcinoma than serum CA-125 alone. This is useful where preoperative records are not available to the treating clinician.