Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Njoku K
PROVIDER: S-EPMC7916512 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Publications
Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer.
Njoku Kelechi K Campbell Amy E AE Geary Bethany B MacKintosh Michelle L ML Derbyshire Abigail E AE Kitson Sarah J SJ Sivalingam Vanitha N VN Pierce Andrew A Whetton Anthony D AD Crosbie Emma J EJ
Cancers 20210210 4
Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analyse ...[more]
Similar Datasets
Project description:BACKGROUND:Obesity and diabetes are associated with increased risk and worse outcomes for endometrial cancer. Metformin is a widely prescribed generic drug for the treatment of type II diabetes and metabolic syndrome and may also have anti-tumorigenic effects. Thus, we assessed the metabolic anti-tumorigenic effects of metformin in (1) human endometrial cancer cell lines under varying glucose concentrations, and (2) a novel genetically engineered mouse model of endometrioid endometrial cancer under obese and lean conditions. METHODS:The effects of metformin on cytotoxicity, apoptosis, cell cycle progression, and the AMPK/mTOR/S6 and MAPK pathways were assessed in ECC-1 and Ishikawa cells under low, normal and high glucose conditions. The impact of metformin treatment on tumor growth under obese and lean conditions was evaluated using a novel LKB1fl/fl p53fl/fl mouse model of endometrial cancer. Global, untargeted metabolomics was used to identify (1) obesity-associated differences between endometrial tumors and (2) the obesity-dependent effects of metformin in the endometrial tumors. RESULTS:Hypoglycemic conditions significantly enhanced the sensitivity of the cells to metformin in regards to its anti-proliferative and apoptotic effects, as compared to hyperglycemic and normal glucose conditions. Metformin inhibited tumor growth in both the obese and lean mice, which metformin-induced inhibition of tumor progression in obese mice was significantly greater than in lean mice. Metabolomic profiling in endometrial cancer tissues revealed significant differences between obese- and lean-mice. Enhanced energy metabolism was seen in obese- versus lean-mice as evidenced by increases in glycolytic and oxidative phosphorylation intermediates. In addition, dramatic increases in lipid biosynthesis and lipid peroxidation were found in the obese- versus lean-mice, whereas metformin obviously reversed the obesity-driven upregulation of lipid and protein biosynthesis in the obese mice. CONCLUSIONS:The obese state promoted tumor aggressiveness in the LKB1fl/fl p53fl/fl mouse model, accompanied by increases in energy metabolism, lipid biosynthesis, and markers of lipid peroxidation. Metformin had increased efficacy against endometrial cancer in obese versus lean mice and reversed the detrimental metabolic effects of obesity in the endometrial tumors. Taken together, it is likely that the unique metabolic milieu underlies metformin's improved efficacy in treating endometrial cancer which develop in an obese host environment.
| S-EPMC6834476 | biostudies-literature
Project description:BackgroundUntargeted metabolomics was used in case-control studies of adenocarcinoma (ADC) lung cancer to develop and test metabolite classifiers in serum and plasma as potential biomarkers for diagnosing lung cancer.MethodsSerum and plasma were collected and used in two independent case-control studies (ADC1 and ADC2). Controls were frequency matched for gender, age, and smoking history. There were 52 adenocarcinoma cases and 31 controls in ADC1 and 43 adenocarcinoma cases and 43 controls in ADC2. Metabolomics was conducted using gas chromatography time-of-flight mass spectrometry. Differential analysis was performed on ADC1 and the top candidates (FDR < 0.05) for serum and plasma used to develop individual and multiplex classifiers that were then tested on an independent set of serum and plasma samples (ADC2).ResultsAspartate provided the best accuracy (81.4%) for an individual metabolite classifier in serum, whereas pyrophosphate had the best accuracy (77.9%) in plasma when independently tested. Multiplex classifiers of either 2 or 4 serum metabolites had an accuracy of 72.7% when independently tested. For plasma, a multimetabolite classifier consisting of 8 metabolites gave an accuracy of 77.3% when independently tested. Comparison of overall diagnostic performance between the two blood matrices yielded similar performances. However, serum is most ideal given higher sensitivity for low-abundant metabolites.ConclusionThis study shows the potential of metabolite-based diagnostic tests for detection of lung adenocarcinoma. Further validation in a larger pool of samples is warranted.ImpactThese biomarkers could improve early detection and diagnosis of lung cancer.
| S-EPMC4633344 | biostudies-literature
Project description: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 (AUCadj) 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 AUCadj 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.
| S-EPMC5857535 | biostudies-literature
Project description:Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a "signature pathway" associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.
| S-EPMC9030452 | biostudies-literature
Project description:Obesity is the strongest risk factor for endometrial cancer (EC). To inform targeted screening and prevention strategies, we assessed the impact of obesity and subsequent bariatric surgery-induced weight loss on endometrial morphology and molecular pathways implicated in endometrial carcinogenesis. Blood and endometrial tissue were obtained from women with class III-IV obesity (body mass index ≥40 and ≥50 kg/m2 , respectively) immediately prior to gastric bypass or sleeve gastrectomy, and at two and 12 months' follow up. The endometrium underwent pathological examination and immunohistochemistry was used to quantify proliferation (Ki-67), oncogenic signaling (PTEN, pAKT, pERK) and hormone receptor (ER, PR) expression status. Circulating biomarkers of insulin resistance, reproductive function and inflammation were also measured at each time point. Seventy-two women underwent bariatric surgery. At 12 months, the mean change in total and excess body weight was -32.7 and -62.8%, respectively. Baseline endometrial biopsies revealed neoplastic change in 10 women (14%): four had EC, six had atypical hyperplasia (AH). After bariatric surgery, most cases of AH resolved (5/6) without intervention (3/6) or with intrauterine progestin (2/6). Biomarkers of endometrial proliferation (Ki-67), oncogenic signaling (pAKT) and hormone receptor status (ER, PR) were significantly reduced, with restoration of glandular PTEN expression, at 2 and 12 months. There were reductions in circulating biomarkers of insulin resistance (HbA1c, HOMA-IR) and inflammation (hsCRP, IL-6), and increases in reproductive biomarkers (LH, FSH, SHBG). We found an unexpectedly high prevalence of occult neoplastic changes in the endometrium of women undergoing bariatric surgery. Their spontaneous reversal and accompanying down-regulation of PI3K-AKT-mTOR signaling with weight loss may have implications for screening, prevention and treatment of this disease.
| S-EPMC6519061 | biostudies-literature
Project description:PurposeWe aimed to study the potential influence of tumour blood flow -obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)- in the metabolomic profiles of endometrial tumours.MethodsLiquid chromatography coupled to mass spectrometry established the metabolomic profile of endometrial cancer lesions exhibiting high (n=12) or low (n=14) tumour blood flow at DCE-MRI. Univariate and multivariate statistics (ortho-PLS-DA, a random forest (RF) classifier and hierarchical clustering) and receiver operating characteristic (ROC) curves were used to establish a panel for potentially discriminating tumours with high versus low blood flow.ResultsTumour blood flow is associated with specific metabolomic signatures. Ortho-PLS-DA and RF classifier resulted in well-defined clusters with an out-of-bag error lower than 8%. We found 28 statistically significant molecules (False Discovery Rate corrected p<0.05). Based on exact mass, retention time and isotopic distribution we identified 9 molecules including resolvin D and specific lysophospholipids associated with blood flow, and hence with a potentially regulatory role relevant in endometrial cancer.ConclusionsTumour flow parameters at DCE-MRI quantifying vascular tumour characteristics are reflected in corresponding metabolomics signatures and highlight disease mechanisms that may be targetable by novel therapies.
| S-EPMC5752500 | biostudies-literature
Project description:BackgroundObesity is a well-known risk factor for endometrial cancer, but the mechanisms of obesity-related carcinogenesis are not well defined, particularly for premenopausal women. With the continuing obesity epidemic, increases in the incidence of endometrial cancer and a younger age of diagnosis are often attributed to a hyperestrogenic state created by hormone production in adipose tissue, but significant knowledge gaps remain. The balance of estrogen-responsive signals has not been defined in the endometrium of premenopausal women with obesity, where obesity may not create hyperestrogenism in the context of ovaries being the primary source of estrogen production. Obesity is associated with a state of low-grade, chronic inflammation that can promote tumorigenesis, and it is also known that hormonal changes alter the immune microenvironment of the endometrium. However, limited research has been conducted on endometrial immune-response changes in women who have an increased risk for cancer due to obesity.ObjectiveEndometrial estrogen-regulated biomarkers, previously shown to be dysregulated in endometrial cancer, were evaluated in a cohort of premenopausal women to determine if obesity is associated with differences in the biomarker expression levels, which might reflect an altered risk of developing cancer. The expression of a multiplexed panel of immune-related genes was also evaluated for expression differences related to obesity.Study designPremenopausal women with a body mass index of ≥30 kg/m2 (n=97) or a body mass index of ≤25 kg/m2 (n=33) were prospectively enrolled in this cross-sectional study, which included the assessment of serum metabolic markers and a timed endometrial biopsy for pathologic evaluation, hormone-regulated biomarker analysis, and immune response gene expression analysis. Medical and gynecologic histories were obtained. Endometrial gene expression markers were also compared across the body mass index groups in a previous cohort of premenopausal women with an inherited cancer risk (Lynch syndrome).ResultsIn addition to known systemic metabolic differences, histologically normal endometria from women with obesity showed a decrease in gene expression of progesterone receptor (P=.0027) and the estrogen-induced genes retinaldehyde dehydrogenase 2 (P=.008), insulin-like growth factor 1 (P=.016), and survivin (P=.042) when compared with women without obesity. The endometrial biomarkers insulin-like growth factor 1, survivin, and progesterone receptor remained statistically significant in multivariate linear regression models. In contrast, women with obesity and Lynch syndrome had an increased expression of insulin-like growth factor 1 (P=.017). There were no differences in endometrial proliferation, and limited endometrial immune differences were observed.ConclusionWhen comparing premenopausal women with and without obesity in the absence of endometrial pathology or an inherited cancer risk, the expression of the endometrial biomarkers does not reflect a local hyperestrogenic environment, but it instead reflects a decreased cancer risk profile that may be indicative of a compensated state. In describing premenopausal endometrial cancer risk, it may be insufficient to attribute a high-risk state to obesity alone; further studies are warranted to evaluate individualized biomarker profiles for differences in the hormone-responsive signals or immune response. In patients with Lynch syndrome, the endometrial biomarker profile suggests that obesity further increases the risk of developing cancer.
| S-EPMC7897335 | biostudies-literature
Project description:This paper describes an ensemble method with supervised module detection and further module prioritization for reliable network-based biomarker discovery. We design a module detection and ranking method called mRank to discover reliable network modules as cancer diagnostic biomarkers, with two procedures: (1) an iterative supervised module detection guided by phenotypic states in a specific network, (2) a block-based module ranking locally and globally via network topological centrality. We validate its effectiveness and efficiency by identifying hepatocellular carcinoma (HCC) network modules on a comprehensive gene regulatory network with specifying gene interactions by HCC RNA-seq data from the Cancer Genome Atlas (TCGA). These top-ranked modules by mRank get a mean AUC of 0.995 on TCGA HCC dataset with 371 tumor samples and 50 controls by cross-validation SVM. Based on the prior knowledge of cancer dysfunctions enriched in top-ranked modules, 69 genes are identified as HCC candidate biomarkers. They are further validated in independent cohorts with a classifier trained on TCGA HCC dataset. A mean AUC of 0.846 is achieved in distinguishing 976 disease samples from 827 controls. Moreover, some known HCC signatures such as AFP and SPP1 are also included in our identified biomarkers. mRank enables us to find more reliable network modules for cancer diagnosis. For a proof-of-concept study, we validate it in identifying HCC network biomarkers and it is generalizable to other cancers or complex disease. The overall results have demonstrated that mRank can find effective network biomarkers for cancer diagnosis which result in less false positives.
| S-EPMC8715301 | biostudies-literature
Project description:Obesity has reached epidemic proportions worldwide. Several animal models of obesity exist, but studies are lacking that compare traditional lard-based high fat diets (HFD) to "Cafeteria diets" (CAF) consisting of nutrient poor human junk food. Our previous work demonstrated the rapid and severe obesogenic and inflammatory consequences of CAF compared to HFD including rapid weight gain, markers of Metabolic Syndrome, multi-tissue lipid accumulation, and dramatic inflammation. To identify potential mediators of CAF-induced obesity and Metabolic Syndrome, we used metabolomic analysis to profile serum, muscle, and white adipose from rats fed CAF, HFD, or standard control diets. Principle component analysis identified elevations in clusters of fatty acids and acylcarnitines. These increases in metabolites were associated with systemic mitochondrial dysfunction that paralleled weight gain, physiologic measures of Metabolic Syndrome, and tissue inflammation in CAF-fed rats. Spearman pairwise correlations between metabolites, physiologic, and histologic findings revealed strong correlations between elevated markers of inflammation in CAF-fed animals, measured as crown like structures in adipose, and specifically the pro-inflammatory saturated fatty acids and oxidation intermediates laurate and lauroyl carnitine. Treatment of bone marrow-derived macrophages with lauroyl carnitine polarized macrophages towards the M1 pro-inflammatory phenotype through downregulation of AMPK and secretion of pro-inflammatory cytokines. Results presented herein demonstrate that compared to a traditional HFD model, the CAF diet provides a robust model for diet-induced human obesity, which models Metabolic Syndrome-related mitochondrial dysfunction in serum, muscle, and adipose, along with pro-inflammatory metabolite alterations. These data also suggest that modifying the availability or metabolism of saturated fatty acids may limit the inflammation associated with obesity leading to Metabolic Syndrome.
| S-EPMC3373493 | biostudies-literature
Project description:BACKGROUND:Endometrial cancer is a common gynecologic cancer. Noninvasive molecular biomarkers for triage of high-risk patients for invasive procedures are needed. Based on the success of cytological Pap smear screening, cervical scrapings are a good source of DNA for molecular testing. In addition to genetic lesions, DNA methylation is a promising biomarker. We assessed the usefulness of combining genetic and epigenetic biomarkers from cervical scrapings to detect endometrial carcinomas. METHODS:We performed a retrospective case-control study of 96 consecutive cervical scrapings from patients with abnormal uterine bleeding who underwent surgery for diagnostic evaluation. Thirty and 16 cases were diagnosed with type I and type II endometrial cancers, respectively. The remaining non-cancer cases included normal endometrium (n = 12), benign uterine lesions (n = 20), and endometrial hyperplasia (n = 18). Quantitative methylation-specific PCR and mass spectrometry were used for DNA methylation and genetic mutation analysis. Logistic regression was used to evaluate the clinical performance of these candidate biomarkers. RESULTS:We tested the effectiveness of the methylation status of four genes (BHLHE22, CDO1, TBX5, and HAND2) in endometrial cancer detection. The area under the receiver operating characteristic curves ranged from 0.703 to 0.878, and panels of hypermethylated BHLHE22/CDO1/HAND2 (87.0% sensitivity and 86.0% specificity) and BHLHE22/CDO1/TBX5 (89.1% sensitivity and 80.0% specificity) showed significant differences and could distinguish benign from malignant endometrial lesions. The sensitivity and specificity in endometrial cancer detection for BHLHE22/CDO1 were 84.8% and 88.0%, respectively. Both type I and II endometrial carcinomas could be detected using a BHLHE22/CDO1-based methylation profile, suggesting that they may have common epigenomes. Moreover, PTEN and TP53 mutations were found in 63.3% of type I and 93.6% of type II endometrial cancers. Unexpectedly, PTEN and TP53 mutations were commonly found in cervical scrapings of the normal endometrium (25% and 33.3%, respectively) and in cases with benign uterine lesions (10% and 50%, respectively). Finally, combinations of any one mutation of PTEN and TP53 mutations had a sensitivity of 91.3%, but a specificity of only 42.0%. CONCLUSIONS:Adding PTEN/TP53 mutation testing to BHLHE22/CDO1-based methylation testing did not improve the detection of endometrial cancer.
| S-EPMC6883641 | biostudies-literature