Estradiol metabolites as biomarkers of endometrial cancer prognosis after surgery

Circulating adrenal 11-oxygenated androgens are associated with clinical outcome in endometrial cancer

Context

Recent evidence support that androgens play an important role in the etiology of endometrial cancer (EC). Adrenal-derived 11-oxygenated androgens are highly potent agonists of the androgen receptor (AR), comparable to testosterone (T) and dihydrotestosterone (DHT) that have not been studied in the context of EC.

Methodology

We studied a cohort of 272 newly diagnosed postmenopausal EC cases undergoing surgical treatment. Circulating concentrations of seven 11-oxygenated androgens including precursors, potent androgens and their metabolites were established in serum samples collected before and 1 month after surgery using a validated liquid chromatography tandem mass spectrometry method (LC-MS/MS). Free (unconjugated) and total (free + sulfate and glucuronide conjugates following enzymatic hydrolysis) were analyzed in relation to clinicopathological features, recurrence and disease-free survival (DFS).

Results

Levels of 11-oxygenated androgens were weakly correlated to those of canonical androgens such as testosterone (T) and dihydrotestosterone (DHT), with no evidence of their association with clinicopathological features. Levels of 11-oxygenated androgens declined after surgery but remained higher in overweight and obese compared to normal weight cases. Higher levels of preoperative free 11-ketoandrosterone (11KAST) were associated with an increased risk of recurrence (Hazard ratio (HR) of 2.99 (95%CI=1.09-8.18); P=0.03). Postoperative free 11β-hydroxyandrosterone (11OHAST) levels were adversely associated with recurrence and DFS (HR = 3.23 (1.11-9.40); P=0.03 and 3.27 (1.34-8.00); P=0.009, respectively).

Conclusion

11-oxygenated androgen metabolites emerge as potential prognostic markers of EC.

Endometrial cancer diagnostic and prognostic algorithms based on proteomics, metabolomics, and clinical data: a systematic review

Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies

Metabolic heterogeneity of cancer contributes significantly to its poor treatment outcomes and prognosis. As a result, studies continue to focus on identifying new biomarkers and metabolic vulnerabilities, both of which depend on the understanding of altered metabolism in cancer. In the recent decades, the rise of mass spectrometry imaging (MSI) enables the in situ detection of large numbers of small molecules in tissues. Therefore, researchers look to using MSI-mediated spatial metabolomics to further study the altered metabolites in cancer patients. In this review, we examined the two most commonly used spatial metabolomics techniques, MALDI-MSI and DESI-MSI, and some recent highlights of their applications in cancer studies. We also described AFADESI-MSI as a recent variation from the DESI-MSI and compare it with the two major techniques. Specifically, we discussed spatial metabolomics results in four types of heterogeneous malignancies, including breast cancer, esophageal cancer, glioblastoma and lung cancer. Multiple studies have effectively classified cancer tissue subtypes using altered metabolites information. In addition, distribution trends of key metabolites such as fatty acids, high-energy phosphate compounds, and antioxidants were identified. Therefore, while the visualization of finer distribution details requires further improvement of MSI techniques, past studies have suggested spatial metabolomics to be a promising direction to study the complexity of cancer pathophysiology.

Multi-Omic Profiling of Multi-Biosamples Reveals the Role of Amino Acid and Nucleotide Metabolism in Endometrial Cancer

Background

Endometrial cancer (EC) is one of the most common gynecological cancers. The traditional diagnosis of EC relies on histopathology, which, however, is invasive and may arouse tumor spread. There have been many studies aiming to find the metabolomic biomarkers of EC to improve the early diagnosis of cancer in a non-invasive or minimally invasive way, which can also provide valuable information for understanding the disease. However, most of these studies only analyze a single type of sample by metabolomics, and cannot provide a comprehensive view of the altered metabolism in EC patients. Our study tries to gain a pathway-based view of multiple types of samples for understanding metabolomic disorders in EC by combining metabolomics and proteomics.

Methods

Forty-four EC patients and forty-three controls were recruited for the research. We collected endometrial tissue, urine, and intrauterine brushing samples. Untargeted metabolomics and untargeted proteomics were both performed on the endometrial tissue samples, while only untargeted metabolomics was performed on the urine and intrauterine brushing samples.

Results

By integrating the differential metabolites and proteins between EC patients and controls detected in the endometrial tissue samples, we identified several EC-related significant pathways, such as amino acid metabolism and nucleotide metabolism. The significance of these pathways and the potential of metabolite biomarker-based diagnosis were then further verified by using urine and intrauterine brushing samples. It was found that the regulation of metabolites involved in the significant pathways showed similar trends in the intrauterine brushings and the endometrial tissue samples, while opposite trends in the urine and the endometrial tissue samples.

Conclusions

With multi-omics characterization of multi-biosamples, the metabolomic changes related to EC are illustrated in a pathway-based way. The network of altered metabolites and related proteins provides a comprehensive view of altered metabolism in the endometrial tissue samples. The verification of these critical pathways by using urine and intrauterine brushing samples provides evidence for the possible non-invasive or minimally invasive biopsy for EC diagnosis in the future.

Current and Emerging Prognostic Biomarkers in Endometrial Cancer

Endometrial cancer is the most common gynaecological malignancy in high income countries and its incidence is rising. Whilst most women with endometrial cancer are diagnosed with highly curable disease and have good outcomes, a significant minority present with adverse clinico-pathological characteristics that herald a poor prognosis. Prognostic biomarkers that reliably select those at greatest risk of disease recurrence and death can guide management strategies to ensure that patients receive appropriate evidence-based and personalised care. The Cancer Genome Atlas substantially advanced our understanding of the molecular diversity of endometrial cancer and informed the development of simplified, pragmatic and cost-effective classifiers with prognostic implications and potential for clinical translation. Several blood-based biomarkers including proteins, metabolites, circulating tumour cells, circulating tumour DNA and inflammatory parameters have also shown promise for endometrial cancer risk assessment. This review provides an update on the established and emerging prognostic biomarkers in endometrial cancer.

CKMT1A is a novel potential prognostic biomarker in patients with endometrial cancer

PURPOSE

The International Federation of Gynecology and Obstetrics (FIGO) stage remains the standard staging system for the assessment of endometrial cancer (EC) prognosis. Thus, we aim to identify the significant genes or biomarkers associated with the stage of endometrial cancer, which may also help reveal the mechanism of EC progression and assess the prognosis of patients with EC.

MATERIALS AND METHODS

We compared the mRNA expression levels of EC patients with stages I and II as well as stages III and IV in the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) of EC patients at different stages were selected by volcano plot and Venn analysis. Gene Ontology (GO) and Pathways were applied to analyze the identified genes. Protein protein interaction (PPI) network was employed to identify the correlation. The survival analyses based on TCGA database were conducted for further screening. The Human Protein Atlas, quantitative PCR and immunohistochemistry were utilized to confirm the differences in expression of DEGs in endometrial cancer samples at different FIGO stages.

RESULTS

CKMT1A was identified as a candidate gene. Through survival analyses, we found that CKMT1A may be a poor prognostic factor in the overall survival of endometrial cancer patients. GO and Pathways revealed that CKMT1A is closely associated with the metabolic process. More importantly, Human Protein Atlas and quantitative PCR confirmed the differences in expression of CKMT1A in endometrial cancer samples at different FIGO stages.

CONCLUSION

In summary, this study shows that CKMT1A is a newly identified essential tumor progression regulator of endometrial cancer, which may give rise to novel therapeutic strategies in the management of endometrial cancer patients to prolong its prognosis and prevent tumor progression.

Circulating estradiol and its biologically active metabolites in endometriosis and in relation to pain symptoms

OBJECTIVES

Endometriosis (EM) is an estrogen-dominant inflammatory disease linked to infertility that affects women of reproductive age. EM lesions respond to hormonal signals that regulate uterine tissue growth and trigger inflammation and pain. The objective of this study was to evaluate whether estradiol (E₂) and its biologically active metabolites are differentially associated with EM given their estrogenic and non-estrogenic actions including proliferative and inflammatory properties.

DESIGN

We performed a retrospective study of 209 EM cases and 115 women without EM.

METHODS

Pain-related outcomes were assessed using surveys with validated scales. Preoperative serum levels of estradiol (E₂) and estrone (E₁), their 2-, 4- and 16- hydroxylated (OH) and methylated (MeO) derivatives (n=16) were measured by mass spectrometry. We evaluated the associations between estrogen levels and EM anatomic sites, surgical stage, risk of EM, and symptoms reported by women. Spearman correlations established the relationships between circulating steroids.

RESULTS

Of the sixteen estrogens profiled, eleven were detected above quantification limits in most individuals. Steroids were positively correlated, except 2-hydroxy 3MeO-E₁ (2OH-3MeO-E₁). Higher 2OH-3MeO-E₁ was linked to an increased risk of EM (Odd ratio (OR)=1.91 (95%CI 1.09-3.34); P=0.025). Ovarian EM cases displayed enhanced 2-hydroxylation with higher 2MeO-E₁ and 2OH-E₁ levels (P< 0.009). Abdominal, pelvic and back pain symptoms were also linked to higher 2OH-3MeO-E₁ levels (OR=1.86; 95%CI 1.06-3.27; P=0.032).

CONCLUSIONS

The 2-hydroxylation pathway emerges as an unfavorable feature of EM, and is associated with ovarian EM and pain related outcomes.

Urinary oestrogen steroidome as an indicator of the risk of localised prostate cancer progression

BACKGROUND

Prostate cancer (PCa) is the most common cancer in North American men. Beyond the established contribution of androgens to disease progression, growing evidence suggest that oestrogen-related pathways might also be of clinical importance. The aim of this study was to explore the association of urinary oestrogen levels with clinical outcomes.

METHODS

Urine samples from the prospective multi-institutional PROCURE cohort were collected before RP for discovery (n = 259) and validation (n = 253). Urinary total oestrogens (unconjugated + conjugated), including oestrone and oestradiol, their bioactive and inactive catechol and methyl derivatives (n = 15), were measured using mass spectrometry (MS).

RESULTS

The median follow-up time for the discovery and replication cohorts was 7.6 and 6.5 years, respectively. Highly significant correlations between urinary oestrogens were observed; however, correlations with circulating oestrogens were modest. Our findings indicate that higher levels of urinary oestriol and 16-ketoestradiol were associated with lower risk of BCR. In contrast, higher levels of 2-methoxyestrone were associated with an increased risk of development of metastasis/deaths.

CONCLUSIONS

Our data suggest that urinary levels of oestriol and 16-ketoestradiol metabolites are associated with a more favourable outcome, whereas those of 2-methoxyestrone are associated with an elevated risk of metastasis after RP. Further studies are required to better understand the impact of oestrogens on disease biology and as easily accessible urine-based risk-stratification markers.

Metabolomics for Diagnosis and Prognosis of Uterine Diseases? A Systematic Review

This systematic review analyses the contribution of metabolomics to the identification of diagnostic and prognostic biomarkers for uterine diseases. These diseases are diagnosed invasively, which entails delayed treatment and a worse clinical outcome. New options for diagnosis and prognosis are needed. PubMed, OVID, and Scopus were searched for research papers on metabolomics in physiological fluids and tissues from patients with uterine diseases. The search identified 484 records. Based on inclusion and exclusion criteria, 44 studies were included into the review. Relevant data were extracted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist and quality was assessed using the QUADOMICS tool. The selected metabolomics studies analysed plasma, serum, urine, peritoneal, endometrial, and cervico-vaginal fluid, ectopic/eutopic endometrium, and cervical tissue. In endometriosis, diagnostic models discriminated patients from healthy and infertile controls. In cervical cancer, diagnostic algorithms discriminated patients from controls, patients with good/bad prognosis, and with/without response to chemotherapy. In endometrial cancer, several models stratified patients from controls and recurrent from non-recurrent patients. Metabolomics is valuable for constructing diagnostic models. However, the majority of studies were in the discovery phase and require additional research to select reliable biomarkers for validation and translation into clinical practice. This review identifies bottlenecks that currently prevent the translation of these findings into clinical practice.

Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer

Endometrial cancer (EC) is the commonest gynaecological malignancy. Current prognostic markers are inadequate to accurately predict patient survival, necessitating novel prognostic markers, to improve treatment strategies. Telomerase has a unique role within the endometrium, whilst aberrant telomerase activity is a hallmark of many cancers. The aim of the current in silico study is to investigate the role of telomere and telomerase associated genes and proteins (TTAGPs) in EC to identify potential prognostic markers and therapeutic targets. Analysis of RNA-seq data from The Cancer Genome Atlas identified differentially expressed genes (DEGs) in EC (568 TTAGPs out of 3467) and ascertained DEGs associated with histological subtypes, higher grade endometrioid tumours and late stage EC. Functional analysis demonstrated that DEGs were predominantly involved in cell cycle regulation, while the survival analysis identified 69 DEGs associated with prognosis. The protein-protein interaction network constructed facilitated the identification of hub genes, enriched transcription factor binding sites and drugs that may target the network. Thus, our in silico methods distinguished many critical genes associated with telomere maintenance that were previously unknown to contribute to EC carcinogenesis and prognosis, including NOP56, WFS1, ANAPC4 and TUBB4A. Probing the prognostic and therapeutic utility of these novel TTAGP markers will form an exciting basis for future research.

Circulating Transcripts and Biomarkers in Uterine Tumors: Is There a Predictive Role?

PURPOSE OF REVIEW

Uterine cancer comprises endometrial carcinoma and the uterine sarcoma. Endometrial carcinomas are the most frequent variant and have early symptoms and a solid diagnostic work up, resulting in a rather fair prognosis. However, in case of advanced stage disease and relapse, treatment options are limited and prognosis is impaired. Uterine sarcomas are rare, often lacking symptoms and no diagnostic tool for correct pre-operative diagnosis are available. Prognosis is poor.

RECENT FINDINGS

Circulating biomarkers as a liquid biopsy could be beneficial as a diagnostic tool in uterine sarcomas. For both carcinomas and sarcomas, circulating biomarkers could be of use in predicting early disease recurrence. This review in endometrial carcinoma and uterine sarcoma focus on circulating biomarkers; such as proteins; circulating tumor cells; circulating tumor DNA; microRNA; and immune cells.

Steroidomics for the Prevention, Assessment, and Management of Cancers: A Systematic Review and Functional Analysis

Steroidomics, an analytical technique for steroid biomarker mining, has received much attention in recent years. This systematic review and functional analysis, following the PRISMA statement, aims to provide a comprehensive review and an appraisal of the developments and fundamental issues in steroid high-throughput analysis, with a focus on cancer research. We also discuss potential pitfalls and proposed recommendations for steroidomics-based clinical research. Forty-five studies met our inclusion criteria, with a focus on 12 types of cancer. Most studies focused on cancer risk prediction, followed by diagnosis, prognosis, and therapy monitoring. Prostate cancer was the most frequently studied cancer. Estradiol, dehydroepiandrosterone, and cortisol were mostly reported and altered in at least four types of cancer. Estrogen and estrogen metabolites were highly reported to associate with women-related cancers. Pathway enrichment analysis revealed that steroidogenesis; androgen and estrogen metabolism; and androstenedione metabolism were significantly altered in cancers. Our findings indicated that estradiol, dehydroepiandrosterone, cortisol, and estrogen metabolites, among others, could be considered oncosteroids. Despite noble achievements, significant shortcomings among the investigated studies were small sample sizes, cross-sectional designs, potential confounding factors, and problematic statistical approaches. More efforts are required to establish standardized procedures regarding study design, analytical procedures, and statistical inference.

Measuring estrogens in women, men, and children: Recent advances 2012-2017

The measurement of estrogens is important for diagnosing and monitoring the health of women, men, and children. For example, for postmenopausal women or women undergoing treatment for breast cancer with aromatase inhibitors, the measurement of extremely low concentrations of estrogens in serum, especially estradiol, is problematic but essential for proper medical care. Achieving superb analytical sensitivity and specificity has been and continues to be a challenge for the clinical laboratory, but is a challenge that is being taken seriously. Focusing on publications from 2012 to 2017, this review will provide an overview of recent research in the development of methods to accurately and precisely measure estrogens, including a variety of estrogen metabolites. Additionally, the latest in clinical research involving estrogen measurement in women, men, and children will be presented to provide an update on the association of estrogens with diseases or conditions such as breast cancer, precocious puberty, infertility, and pregnancy. This research update will provide context as to why estrogen measurement is important and why laboratories are working hard to support the recommendations made by the Endocrine Society regarding estrogen measurement.

Identification of Metabolomic Biomarkers for Endometrial Cancer and Its Recurrence after Surgery in Postmenopausal Women

Endometrial cancer (EC) is the most frequent gynecological cancer in developed countries. Most EC occurs after menopause and is diagnosed as endometrioid (type I) carcinomas, which exhibit a favorable prognosis. In contrast, non-endometrioid (type II) carcinomas such as serous tumors have a poor prognosis. Our goal was to identify novel blood-based markers associated with EC subtypes and recurrence after surgery in postmenopausal women. Using mass spectrometry-based untargeted metabolomics, we examined preoperative serum metabolites among control women (n = 18) and those with non-recurrent (NR) and recurrent (R) cases of type I endometrioid (n = 24) and type II serous (n = 12) carcinomas. R and NR cases were similar with respect to pathological characteristics, body mass index, and age. A total of 1,592 compounds were analyzed including 14 different lipid classes. When we compared EC cases with controls, 137 metabolites were significantly different. A combination of spermine and isovalerate resulted in an age-adjusted area under the receiver-operating characteristic curve (AUC_adj) of 0.914 (P < 0.001) for EC detection. The combination of 2-oleoylglycerol and TAG42:2-FA12:0 allowed the distinction of R cases from NR cases with an AUC_adj of 0.901 (P < 0.001). Type I R cases were also characterized by much lower levels of bile acids and elevated concentrations of phosphorylated fibrinogen cleavage peptide, whereas type II R cases displayed higher levels of ceramides. The findings from our pilot study provide a detailed metabolomics study of EC and identify putative serum biomarkers for defining clinically relevant risk groups.