Diagnostic and Prognostic Values of Serum EpCAM, TGM2, and HE4 Levels in Endometrial Cancer

Novel targets and their functions in the prognosis of uterine corpus endometrial cancer patients

Aberrant mRNA expression is implicated in uterine corpus endometrial carcinoma (UCEC) oncogenesis and progression. However, effective prognostic biomarkers for UCEC remain limited. We aimed to construct a reliable multi-gene risk model using gene expression profiles. Utilizing TCGA data (543 UCEC samples, 35 controls), we identified 1517 differentially acting genes. Weighted gene co-expression complex analysis (WGCCA), hub gene screening, and risk regression analysis (RRA) were employed to determine prognosis-related genes and construct the risk model. Nomograms visualized risk scores and receiver operator characteristic (ROC) curves assessed model performance. Seven novel prognosis-related hub genes (ANGPT1, ASB2, GAL, GDF7, ONECUT2, SV2B, TRPC6) were identified. The model's concordance index (C index) by multivariate Cox regression analysis was 0.79. ROC curves yielded AUCs of 0.811 (3-year) and 0.79 (5-year), demonstrating the model's efficacy in predicting UCEC survival. Our study proposes a promising seven-biomarker risk model for predicting UCEC prognosis, offering potential clinical utility.

An MRI-based radiomics nomogram to predict progression-free survival in patients with endometrial cancer

Aim: This study aimed to explore the importance of an MRI-based radiomics nomogram in predicting the progression-free survival (PFS) of endometrial cancer.Methods: Based on clinicopathological and radiomic characteristics, we established three models (clinical, radiomics and combined model) and developed a nomogram for the combined model. The Kaplan-Meier method was utilized to evaluate the association between nomogram-based risk scores and PFS.Results: The nomogram had a strong predictive ability in calculating PFS with areas under the curve (ROC) of 0.905 and 0.901 at 1 and 3 years, respectively. The high-risk groups identified by the nomogram-based scores had shorter PFS compared with the low-risk groups.Conclusion: The radiomics nomogram has the potential to serve as a noninvasive imaging biomarker for predicting individual PFS of endometrial cancer.

Deciphering the potential of proteomic-based biomarkers in women's reproductive diseases: empowering precision medicine in gynecology

CONTEXT

Gynecological disorders represent a complex set of malignancies that result from a diverse array of molecular changes affecting the lives of over a million women worldwide. Ovarian, Endometrial, and Cervical cancers, Endometriosis, PCOS are the most prevalent ones that pose a grave threat to women's health. Proteomics has emerged as an invaluable tool for developing novel biomarkers, screening methods, and targeted therapeutic agents for gynecological disorders. Some of these biomarkers have been approved by the FDA, but regrettably, they have a constrained diagnostic accuracy in early-stage diagnosis as all of these biomarkers lack sensitivity and specificity. Lately, high-throughput proteomics technologies have made significant strides, allowing for identification of potential biomarkers with improved sensitivity and specificity. However, limited successes have been shown with translation of these discoveries into clinical practice.

OBJECTIVE

This review aims to provide a comprehensive overview of the current and potential protein biomarkers for gynecological cancers, endometriosis and PCOS, discusses recent advances and challenges, and highlights future directions for the field.

CONCLUSION

We propose that proteomics holds great promise as a powerful tool to revolutionize the fight against female reproductive diseases and can ultimately improve personalized patient outcomes in women's biomedicine.

Comprehensive analysis reveals dual biological function roles of EpCAM in kidney renal clear cell carcinoma

Background

Epithelial cell adhesion molecule (EpCAM), a well-established marker for circulating tumor cells, plays a crucial role in the complex process of cancer metastasis. The primary objective of this investigation is to study EpCAM expression in pan-cancer and elucidate its significance in the context of kidney renal clear cell carcinoma (KIRC).

Methods

Data obtained from the public database was harnessed for the comprehensive assessment of the EpCAM expression levels and prognostic and clinicopathological correlations in thirty-three types of cancer. EpCAM was validated in our own KIRC sequencing and immunohistochemical cohorts. Subsequently, an in-depth exploration was conducted to scrutinize the interrelationship between EpCAM and various facets, including immune cells, immune checkpoints, and chemotherapy drugs. We employed Cox regression analysis to identify prognostic immunomodulators associated with EpCAM, which were subsequently utilized in the development of a prognostic model. The model was validated in our own clinical cohort and public datasets, and compared with 137 published models. The role of EpCAM in KIRC was explored by biological function experiments in vitro.

Results

While EpCAM exhibited pronounced overexpression across a wide spectrum of cancer types, a notable reduction was observed in KIRC tissues. As grade increased, EpCAM expression decreased. EpCAM expression decreased in patients without metastasis. EpCAM mRNA and protein levels were used as independent, favorable prognostic factors in patients with KIRC in our own cohort. The expression of EpCAM exhibited strong associations with immune-related pathways, demonstrating an inverse correlation with the majority of immune cell types. Immune checkpoint inhibitors exert better therapeutic effects on patients with low EpCAM expression. In addition, EpCAM can be used as a drug resistance indicator and guide the clinical medication of patients with KIRC. A robust model, which had good predictive accuracy and applicability, showed significant superiority over other models. Importantly, EpCAM played the dual roles of promoting proliferation and resisting metastasis in KIRC.

Conclusion

In the context of KIRC, EpCAM assumes a surprising dual role, where it not only facilitates cell proliferation but also exerts resistance against the metastatic process. EpCAM serves as a standalone prognostic marker for patients with KIRC, and related models can also effectively predict prognosis. These discoveries offer novel perspectives on the functional significance of EpCAM in the context of KIRC.

A new immune checkpoint-associated nine-gene signature for prognostic prediction of glioblastoma

Glioblastoma (GBM) is a highly malignant neurological tumor that has a poor prognosis. While pyroptosis affects cancer cell proliferation, invasion and migration, function of pyroptosis-related genes (PRGs) in GBM as well as the prognostic significance of PRGs remain obscure. By analyzing the mechanisms involved in the association between pyroptosis and GBM, our study hopes to provide new insights into the treatment of GBM. Here, 32 out of 52 PRGs were identified as the differentially expressed genes between GBM tumor versus normal tissues. And all GBM cases were assigned to 2 groups according to the expression of the differentially expressed genes using comprehensive bioinformatics analysis. The least absolute shrinkage and selection operator analysis led to the construction of a 9-gene signature, and the cancer genome atlas cohort of GBM patients were categorized into high risk and low risk subgroups. A significant increase in the survival possibility was found in low risk patients in comparison with the high risk ones. Consistently, low risk patients of a gene expression omnibus cohort displayed a markedly longer overall survival than the high risk counterparts. The risk score calculated using the gene signature was found to be an independent predictor of survival of GBM cases. Besides, we observed significant differences in the expression levels of immune checkpoints between the high risk versus low risk GBM cases, providing instructive suggestions for immunotherapy of GBM. Overall, the present study developed a new multigene signature for prognostic prediction of GBM.

Protein biomarkers in cervicovaginal lavages for detection of endometrial cancer

BACKGROUND

Rates of endometrial cancer (EC) are increasing. For a definitive diagnosis, women undergo various time-consuming and painful medical procedures, such as endometrial biopsy with or without hysteroscopy, and dilation and curettage, which may create a barrier to early detection and treatment, particularly for women with inadequate healthcare access. Thus, there is a need to develop robust EC diagnostics based on non- or minimally-invasive sampling. The objective of this study was to quantify a broad range of immuno-oncology proteins in cervicovaginal lavage (CVL) samples and investigate these proteins as predictive diagnostic biomarkers for EC.

METHODS

One hundred ninety-two women undergoing hysterectomy for benign or malignant indications were enrolled in this cross-sectional study. Classification of women to four disease groups: benign conditions (n = 108), endometrial hyperplasia (n = 18), low-grade endometrioid carcinoma (n = 53) and other EC subtypes (n = 13) was based on histopathology of biopsy samples collected after the surgery. CVL samples were collected in the operating room during the standard-of-care hysterectomy procedure. Concentrations of 72 proteins in CVL samples were evaluated using multiplex immunoassays. Global protein profiles were assessed using principal component and hierarchical clustering analyses. The relationships between protein levels and disease groups and disease severity were determined using Spearman correlation, univariate and multivariate receiver operating characteristics, and logistic regression analyses.

RESULTS

Women with EC and benign conditions exhibited distinctive cervicovaginal protein profiles. Several proteins in CVL samples (e.g., an immune checkpoint protein, TIM-3, growth factors, VEGF, TGF-α, and an anti-inflammatory cytokine, IL-10) discriminated EC from benign conditions, particularly, when tested in combinations with CA19-9, CA125, eotaxin, G-CSF, IL-6, MCP-1, MDC, MCP-3 and TRAIL (sensitivity of 86.1% and specificity of 87.9%). Furthermore, specific biomarkers (e.g., TIM-3, VEGF, TGF-α, TRAIL, MCP-3, IL-15, PD-L2, SCF) associated with histopathological tumor characteristics, including histological type and grade, tumor size, presence and depth of myometrial invasion or mismatch repair protein status, implying their potential utility for disease prognosis or monitoring therapies.

CONCLUSIONS

This proof-of-principle study demonstrated that cervicovaginal sampling coupled with multiplex immunoassay technology can offer a minimally to non-invasive method for EC detection.

The roles and clinical applications of interleukins in endometrial carcinoma

As a common malignant tumor of the female reproductive system, endometrial carcinoma (EC) seriously endangers women's health with an increasing incidence. The oncogenesis and progression of cancer are closely linked with immune microenvironment, of which interleukins are the important components. In order to illustrate the roles and clinical applications of interleukins in EC, literature of interleukins and EC were reviewed. Based on the present studies, interleukins play crucial roles in the oncogenesis and development of EC via regulating the proliferation, migration, invasion, angiogenesis, apoptosis, pyroptosis and autophagy of EC as well as the immune function against EC. And some of the interleukins seems to have prospective clinical applications in EC, such as evaluating the risk of tumorigenesis, discriminating the malignancy from benign disorders or normal condition, indicating cancer aggressiveness, predicting the prognosis of patients and serving as the novel therapy. However, there is still a long way to go before the clinical applications of interleukins in EC come into reality. Nevertheless, it is certain that the exploration of interleukins will definitely be of great benefit to the screening, diagnosis and treatment of EC in the future.

Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers

Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome (peripheral white blood cells) in beef heifers. We used untargeted metabolomics and RNA-Seq paired data from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at artificial insemination (AI). Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. Further, we identified TGM2, TMEM51, TAC3, NDRG4, and PDGFB as more connected in the NP heifers’ network. The NP gene network showed a connectivity gain due to the rewiring of major regulators. The metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan and allantoic acid exhibited a connectivity gain in the NP and AI-P networks, respectively. The gene–metabolite integration identified tocopherol-a as positively correlated with ENSBTAG00000009943 in the AI-P group. Conversely, tocopherol-a was negatively correlated in the NP group with EXOSC2, TRNAUIAP, and SNX12. In the NP group, α-ketoglutarate-SMG8 and putrescine-HSD17B13 were positively correlated, whereas a-ketoglutarate-ALAS2 and tryptophan-MTMR1 were negatively correlated. These multiple interactions identified novel targets and pathways underlying fertility in bovines.

The Role of Human Epididymis Protein 4 in the Diagnosis and Prognosis of Diseases: An Umbrella Review of Systematic Reviews and Meta-Analyses of Observational Studies

Background

The application of human epididymis protein 4 (HE4) in diverse health diseases, especially in cancers, has been extensively studied in recent decades. To summarize the existing evidence of the aforementioned topic, we conducted an umbrella review to systematically evaluate the reliability and strength of evidence regarding the role of HE4 in the diagnostic and prognostic estimate of diverse diseases.

Methods

Electronic searches in PubMed, Web of Science, and Embase databases were conducted from inception to September 16, 2021, for meta-analyses, which focus on the role of HE4 in the diagnosis and prognosis of diseases. This study protocol has been registered at PROSPERO (CRD42021284737). We collected the meta-analysis effect size of sensitivity, specificity, positive predictive value, and negative predictive value from diagnostic studies and gathered the hazard ratio (HR) of disease-free survival, overall survival, and progression-free survival from prognostic studies. For each systematic review and meta-analysis, we used a measurable tool for evaluating systematic reviews and meta-analysis (AMSTAR) to evaluate the methodological quality. Additionally, we assessed the quality of evidence on estimating the ability of HE4 in the diagnosis and prognosis of diverse diseases by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guideline.

Results

Overall, 20 meta-analyses including a total of 331 primary studies of different diseases were examined, mainly including ovarian cancer (OC) (n = 9), endometrial cancer (EC) (n = 6), and lung cancer (LC) (n = 4). The methodological qualities of all studies were rated as moderate (45%) or high (55%) by the AMSTAR. According to the GRADE, the certainties of 18 diagnostic pieces of evidence (9 for sensitivity and 9 for specificity) were rated as moderate (34%), low (33%), and very low (33%). Moreover, outcomes from prognosis studies showed evidence (1 for disease-free survival) with high certainty in regard to cancers (such as EC, OC, and LC) with the remaining three being moderate.

Conclusion

This umbrella review suggested that HE4 was a favored biomarker in the prognosis of cancers, which was supported by high certainty of evidence. Additionally, HE4 could provide a suitable method for the diagnosis of EC, OC, and LC with moderate certainty evidence. Further large prospective cohort studies are needed to better elucidate the diagnostic and prognostic role of HE4 in diseases.

HE4 as a Biomarker for Endometrial Cancer

Simple Summary

There are currently no blood biomarkers approved for routine clinical use in endometrial cancer. Serum human epididymis protein 4 (HE4) is significantly higher in patients with endometrial cancer compared to patients without endometrial cancer and is associated with a poorer prognosis. This makes HE4 an attractive candidate for clinical use in endometrial cancer. The aim of this review is to summarise the evidence for the use of serum HE4 in the detection, prognosis, prediction of therapy response and recurrence monitoring in endometrial cancer. The utility of combining HE4 with other biomarkers or imaging and clinical variables, and its detection in other biofluids is also discussed, as well as potential challenges for clinical use and recommended areas for future research.

Abstract

There are currently no blood biomarkers in routine clinical use in endometrial carcinoma (EC). Human epididymis protein 4 (HE4) is a glycoprotein that is overexpressed in the serum of patients with EC, making it a good candidate for use as a diagnostic and/or prognostic biomarker. HE4 is correlated with poor prognostic factors, including stage, myometrial invasion and lymph node metastases, which means it could be used to guide decisions regarding the extent of surgery and need for adjuvant therapy. Serum HE4 has also shown promise for predicting responses to progestin therapy in early-stage EC. The use of algorithms and indices incorporating serum HE4 and other biomarkers, including clinical and imaging variables, is an area of increasing interest. Serum HE4 levels rise with age and renal dysfunction, which may affect the interpretation of results. This review covers the evidence supporting the use of HE4 as an EC biomarker for diagnosis, prognosis, recurrence monitoring, and prediction of therapy response. The evidence for combining serum HE4 with other biomarkers, including clinical and imaging variables, its value as a biomarker in other biofluids and potential challenges of its clinical use are also discussed.

High-risk endometrial cancer proteomic profiling reveals that FBXW7 mutation alters L1CAM and TGM2 protein levels

BACKGROUND

FBXW7 is frequently somatically mutated in grade 3 endometrioid endometrial cancers (G3EECs) and serous endometrial cancers (SECs), which are high-risk cancers associated with poor outcomes and in need of novel treatment options. The aim of this study was to determine the proteomic effects of 3 FBXW7 mutations in high-risk endometrial cancers (ECs).

METHODS

Clustered regularly interspaced short palindromic repeats (CRISPR) editing was used to generate 3 HEC-50B G3EEC derivative cell lines, each of which harbored 1 FBXW7 mutation, and to revert an endogenous FBXW7 mutation in HEC-1-B grade 2 endometrioid endometrial cancer (G2EEC) cells to the wild-type genotype. Proteomic profiling based on liquid chromatography-tandem mass spectrometry was used to determine protein differences between the HEC-50B derivative lines and parental cells. Western blot analysis was performed to assess differential protein levels of CRISPR-edited derivative lines originating from HEC-50B, ARK1 (SEC), ARK4 (SEC), HEC-1-B, and JHUEM-1 (G2EEC) cell lines in comparison with parental cells.

RESULTS

Results of this study demonstrated the effects of FBXW7 mutations on the proteome and phosphoproteome of HEC-50B G3EEC cells and highlighted proteins that also exhibited altered levels in FBXW7-mutated ARK1 and ARK4 SEC cells, including 2 potentially druggable proteins: L1 cell adhesion molecule (L1CAM) and transglutaminase 2 (TGM2). Furthermore, they demonstrated that reversion of an endogenous FBXW7 mutation to the wild-type genotype in JHUEM-1 and HEC-1-B G2EEC cells resulted in decreased L1CAM and TGM2 protein levels.

CONCLUSIONS

L1CAM and TGM2 protein levels are affected by FBXW7 mutations in ECs.