Grading of endometrial cancer using 1H HR-MAS NMR-based metabolomics

The effect of lipidomes on the risk of endometrioid endometrial cancer: a Mendelian randomization study

Objective

This study aimed to explore the potential effects between various human plasma lipidomes and endometrioid endometrial cancer (EEC) by using Mendelian randomization (MR) methods.

Methods

This study designated a total of 179 human plasma lipidomes from the genome-wide association study (GWAS) database as the exposure variable. An EEC-related dataset from the GWAS (GCST006465) served as the outcome variable. MR analyses used the inverse variance-weighted method (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods for regression calculations, accounting for possible biases induced by linkage disequilibrium and weak instrument variables. Any lipidomes failing to pass heterogeneity and horizontal pleiotropy tests were deemed to lack significant causal impact on the outcome.

Results

The results of IVW analysis disclosed that a variety of human plasma lipidomes (n = 15) exhibited a significant causal effect on EEC (p < 0.05). A subset of these lipidomes (n = 13) passed heterogeneity and horizontal pleiotropy tests, which demonstrated consistent and viable causal effects (p < 0.05) including glycerophospholipids, glycerolipids, and sterols. Specifically, phosphatidylcholine (odds ratio [OR]: 1.065-1.129, p < 0.05) exhibited a significant positive causal effect on the occurrence of EEC. Conversely, sterol ester (OR = 0.936, p = 0.007), diacylglycerol (OR = 0.914, p = 0.036), phosphatidylcholine (OR: 0.903-0.927, p < 0.05), phosphatidylethanolamine (OR = 0.907, p = 0.046) and triacylglycerol (OR: 0.880-0.924, p < 0.05) showed a notable negative causal association with EEC, suggesting their inhibitory effects on the EEC occurrence.

Conclusions

The study revealed that human plasma lipidomes have complex impacts on EEC through Mendelian randomization. This indicated that the diversity of structural changes in lipidomes could show different effects on subtypes and then affect EEC occurrence. Although these lipids had the potential to be promising biomarkers, they needed to be further clinically validated nevertheless.

Lipidomics by Nuclear Magnetic Resonance Spectroscopy and Liquid Chromatography-High-Resolution Mass Spectrometry in Osteosarcoma: A Pilot Study

Cancer is a complex disease that can also affect the younger population; however, it is responsible for a relatively high mortality rate of children and youth, especially in low- and middle-income countries (LMICs). Besides that, lipidomic studies in this age range are scarce. Therefore, we analyzed blood serum samples from young patients (12 to 35 years) with bone sarcoma (osteosarcoma) and compared their lipidomics to the ones from the control group of samples, named healthy control (HC group), using NMR and LC-MS techniques. Furthermore, differences in the lipidomic profiles between OS patients with and without metastasis indicate higher glycerophosphocholine (GPC) and glycerophospholipid (GPL) levels in osteosarcoma and increased cholesterol, choline, polyunsaturated fatty acids (PUFAs), and glycerols during the metastasis. These differences, detected in the peripheral blood, could be used as biomarkers for liquid biopsy.

Urine and serum metabolomic analysis of endometrial cancer diagnosis and classification based on ultra-performance liquid chromatography mass spectrometry

OBJECTIVE

This study aimed to reveal the urinary and serum metabolic pattern of endometrial cancer (EC) and establish diagnostic models to identify EC from controls, high-risk from low-risk EC, and type II from type I EC.

METHOD

This study included 146 EC patients (comprising 79 low-risk and 67 high-risk patients, including 124 type I and 22 type II) and 59 controls. The serum and urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry. Analysis was used to elucidate the distinct metabolites and altered metabolic pathways. Receiver operating characteristic (ROC) analyses were employed to discover and validate the potential biomarker models.

RESULTS

Serum and urine metabolomes displayed significant differences between EC and controls, with metabolites related to amino acid and nicotinamide metabolisms. The serum and urine panels distinguished these two groups with Area Under the Curve (AUC) of 0.821 and 0.902, respectively. The panel consisting of serum and urine metabolites demonstrated the best predictive ability (AUC = 0.953 and 0.976 in discovering and validation group). In comparing high-risk and low risk EC, differential metabolites were enriched in purine and glutamine metabolism. The AUC values for serum and urine panels were 0.818, and 0.843, respectively. The combined panel exhibited better predictive accuracy (0.881 in discovering group and 0.936 in external validation). In the comparison between type I and type II group, altered folic acid metabolism was identified. The serum, urine and combined panels discriminated these two groups with the AUC of 0.829, 0.913 and 0.922, respectively.

CONCLUSION

The combined urine and serum metabolome effectively revealed the metabolic patterns in EC patients, offering valuable diagnostic models for EC diagnosis and classification.

Metabolomic-Based Approaches for Endometrial Cancer Diagnosis and Prognosis: A Review

Endometrial cancer, the most prevalent gynecological malignancy in developed countries, is experiencing a sustained rise in both its incidence and mortality rates, primarily attributed to extended life expectancy and lifestyle factors. Currently, the absence of precise diagnostic tools hampers the effective management of the expanding population of women at risk of developing this disease. Furthermore, patients diagnosed with endometrial cancer require precise risk stratification to align with optimal treatment planning. Metabolomics technology offers a unique insight into the molecular landscape of endometrial cancer, providing a promising approach to address these unmet needs. This comprehensive literature review initiates with an overview of metabolomic technologies and their intrinsic workflow components, aiming to establish a fundamental understanding for the readers. Subsequently, a detailed exploration of the existing body of research is undertaken with the objective of identifying metabolite biomarkers capable of enhancing current strategies for endometrial cancer diagnosis, prognosis, and recurrence monitoring. Metabolomics holds vast potential to revolutionize the management of endometrial cancer by providing accuracy and valuable insights into crucial aspects.

Methanethiol: A Scent Mark of Dysregulated Sulfur Metabolism in Cancer

In order to cope with increased demands for energy and metabolites as well as to enhance stress resilience, tumor cells develop various metabolic adaptations, representing a hallmark of cancer. In this regard, the dysregulation of sulfur metabolism that may result in elevated levels of volatile sulfur compounds (VSCs) in body fluids, breath, and/or excretions of cancer patients has recently gained attention. Besides hydrogen sulfide (H2S), methanethiol is the predominant cancer-associated VSC and has been proposed as a promising biomarker for non-invasive cancer diagnosis. Gut bacteria are the major exogenous source of exposure to this foul-smelling toxic gas, with methanethiol-producing strains such as Fusobacterium nucleatum highly abundant in the gut microbiome of colorectal carcinoma (CRC) patients. Physiologically, methanethiol becomes rapidly degraded through the methanethiol oxidase (MTO) activity of selenium-binding protein 1 (SELENBP1). However, SELENBP1, which is considered a tumor suppressor, is often downregulated in tumor tissues, and this has been epidemiologically linked to poor clinical outcomes. In addition to impaired removal, an increase in methanethiol levels may derive from non-enzymatic reactions, such as a Maillard reaction between glucose and methionine, two metabolites enriched in cancer cells. High methionine concentrations in cancer cells may also result in enzymatic methanethiol production in mitochondria. Moreover, enzymatic endogenous methanethiol production may occur through methyltransferase-like protein 7B (METTL7B), which is present at elevated levels in some cancers, including CRC and hepatocellular carcinoma (HCC). In conclusion, methanethiol contributes to the scent of cancer as part of the cancer-associated signature combination of volatile organic compounds (VOCs) that are increasingly being exploited for non-invasive early cancer diagnosis.

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.

Operando NMR metabolomics of a microfluidic cell culture

In this work we demonstrate the use of microfluidic NMR for in situ culture and quantitative analysis of metabolism in hepatocellular carcinoma (HCC) cell lines. A hydrothermal heating system is used to enable continuous in situ NMR observation of HCC cell culture over a 24 h incubation period. This technique is nondestructive, non-invasive and can measure millimolar concentrations at microlitre volumes, within a few minutes and in precisely controlled culture conditions. This is sufficient to observe changes in primary energy metabolism, using around 500-3500 cells per device, and with a time resolution of 17 min. The ability to observe intracellular responses in a time-resolved manner provides a more detailed view of a biological system and how it reacts to stimuli. This capability will allow detailed metabolomic studies of cell-culture based cancer models, enabling quantification of metabolic reporgramming, the metabolic tumor microenvironment, and the metabolic interplay between cancer- and immune cells.

Development of a metabolomics-based data analysis approach for identifying drug metabolites based on high-resolution mass spectrometry

A metabolomics-based approach to data analysis is required for drug metabolites to be identified quickly. This study developed such an approach based on high-resolution mass spectrometry. Our approach is a two-stage one that combines a time-course experiment with stable isotope tracing. Pioglitazone (PIO) was used to improve glycemic management for type 2 diabetes mellitus. Consequently, PIO was taken as a model drug for identifying metabolites. During Stage I of data analysis, 704 out of 26626 ions exhibited a positive relationship between ion abundance ratio and incubation time in a time-course experiment. During Stage II, 25 isotope pairs were identified among the 704 ions. Among these 25 ions, 18 exhibited a dose-response relationship. Finally, 14 of the 18 ions were verified to be PIO structure-related metabolite ions. Otherwise, orthogonal partial least squares-discriminant analysis (OPLS-DA) was adopted to mine PIO metabolite ions, and 10 PIO structure-related metabolite ions were identified. However, only four ions were identified by both our developed approach and OPLS-DA, indicating that differences in the designs of metabolomics-based approaches to data analysis can result in differences in which metabolites are identified. A total of 20 PIO structure-related metabolites were identified by our developed approach and OPLS-DA, and six metabolites were novel. The results demonstrated that our developed two-stage data analysis approach can be used to effectively mine data on PIO metabolite ions from a relatively complex matrix.

The emerging roles of PHOSPHO1 and its regulated phospholipid homeostasis in metabolic disorders

Emerging evidence suggests that phosphoethanolamine/phosphocholine phosphatase 1 (PHOSPHO1), a specific phosphoethanolamine and phosphocholine phosphatase, is involved in energy metabolism. In this review, we describe the structure and regulation of PHOSPHO1, as well as current knowledge about the role of PHOSPHO1 and its related phospholipid metabolites in regulating energy metabolism. We also examine mechanistic evidence of PHOSPHO1- and phospholipid-mediated regulation of mitochondrial and lipid droplets functions in the context of metabolic homeostasis, which could be potentially targeted for treating metabolic disorders.

Quantification of Myoinositol in Serum by Electrochemical Detection with an Unmodified Screen-Printed Carbon Electrode

Simple, rapid, and accurate detection of myoinositol (MI) concentration in blood is crucial in diagnosing polycystic ovary syndrome, neurological disorders, and cancer. A novel electrochemical detection (IED) method was established to quantify MI in human serum using a disposable unmodified screen-printed carbon electrode (SPCE) for the first time. MI was detected indirectly by the reaction product of myoinositol dehydrogenase (IDH) and cofactor β-nicotinamide adenine dinucleotide (NAD⁺). Good linear calibration curves were obtained at the concentration range from 5.0 μM to 500.0 μM (R ² = 0.9981) with the lower limits of detection (LOD) and quantification (LOQ) of 1.0 μM and 2.5 μM, respectively. Recoveries were calculated at three spiked concentrations, and the values were between 90.3 and 106%, with relative standard deviation values of 3.2-6.2% for intraday precision and 7.1-9.0% for interday precision. The SPCE-electrochemical biosensor is simple, accurate, and without modification, showing great potential for point-of-care testing (POCT) of serum MI in clinical samples.

Proof of concept and development of a couple-based machine learning model to stratify infertile patients with idiopathic infertility

We aimed to develop and evaluate a machine learning model that can stratify infertile/fertile couples on the basis of their bioclinical signature helping the management of couples with unexplained infertility. Fertile and infertile couples were recruited in the ALIFERT cross-sectional case-control multicentric study between September 2009 and December 2013 (NCT01093378). The study group consisted of 97 infertile couples presenting a primary idiopathic infertility (> 12 months) from 4 French infertility centers compared with 100 fertile couples (with a spontaneously conceived child (< 2 years of age) and with time to pregnancy < 12 months) recruited from the healthy population of the areas around the infertility centers. The study group is comprised of 2 independent sets: a development set (n = 136 from 3 centers) serving to train the model and a test set (n = 61 from 1 center) used to provide an unbiased validation of the model. Our results have shown that: (i) a couple-modeling approach was more discriminant than models in which men's and women's parameters are considered separately; (ii) the most discriminating variables were anthropometric, or related to the metabolic and oxidative status; (iii) a refined model capable to stratify fertile vs. infertile couples with accuracy 73.8% was proposed after the variables selection (from 80 to 13). These influential factors (anthropometric, antioxidative, and metabolic signatures) are all modifiable by the couple lifestyle. The model proposed takes place in the management of couples with idiopathic infertility, for whom the decision-making tools are scarce. Prospective interventional studies are now needed to validate the model clinical use.Trial registration: NCT01093378 ALIFERT https://clinicaltrials.gov/ct2/show/NCT01093378?term=ALIFERT&rank=1 . Registered: March 25, 2010.

Clinical Efficacy of Treating Endometrial Cancer with Xiaoaiping Tablets under Comprehensive Nursing Intervention and Their Effect on Quality of Life

Objective

To explore the clinical efficacy of treating endometrial cancer with Xiaoaiping tablets under comprehensive nursing intervention and their effect on quality of life.

Methods

The clinical data of 120 endometrial cancer patients treated at the Affiliated Hospital of Southwest Medical University from February 2019 to February 2020 were retrospectively analyzed, and the patients were split into the experimental group and the control group according to their admission order, with 60 cases each. Conventional treatment and Xiaoaiping tablet regimen were received by all patients, those in the control group accepted the general nursing, and those in the experimental group accepted the comprehensive nursing intervention for 12 months, so as to compare their clinical efficacy, quality of life (Functional Assessment of Cancer Therapy, FACT), negative emotion scores (Hospital Anxiety and Depression Scale, HAD), and Medical Coping Modes Questionnaire (MCMQ) scores between the two groups.

Results

No statistical differences in the patients' general information between the two groups were observed (P > 0.05); compared with the control group after nursing, the experimental group obtained a significantly higher objective remission rate (80.0%), significantly higher disease control rate (90.0%) (P < 0.05), significantly better QOL (P < 0.001), significantly lower negative emotion scores (P < 0.001), and significantly better MCMQ scores (P < 0.001).

Conclusion

Adopting Xiaoaiping tablets under comprehensive nursing intervention can improve the negative emotions of patients with endometrial cancer, enhance their confidence in medical treatment, present better efficacy, and obviously promote their QOL. Therefore, comprehensive nursing intervention should be promoted and applied in practice.