Risk Of Endometrial Carcinoma Research Articles

Integrated histological parameters define prognostically relevant groups in atypical endometrial hyperplasia/endometrioid intraepithelial neoplasia

ObjectiveTo assess the risk of endometrial carcinoma following a diagnosis of atypical hyperplasia/endometrioid intraepithelial neoplasia by endometrial biopsy, stratified based on integrated histological parameters.MethodsAll women with atypical hyperplasia/endometrioid intraepithelial neoplasia...

A Comprehensive Approach: Correlating Ultrasound Imaging with Endometrial Histopathological Analysis in Perimenopausal Women with Heavy MenstrualBleeding.

Abnormal uterine bleeding (AUB) is a common troublesome symptom in the perimenopausal age group. The most common type of AUB in this age group is heavy menstrual bleeding. There is a risk of endometrial carcinoma and atypical endometrial hyperplasia in women with AUB in the age group of 40-50 years. Hence early evaluation is of paramount importance in managing women with perimenopausal heavy menstrual bleeding. The current study was undertaken to study the correlation between ultrasound findings and various benign and malignant endometrial histologies in perimenopausal women with heavy menstrual bleeding. Women aged 40-55 years presenting with heavy menstrual bleeding at the gynaecology outpatient department at Sree Balaji Medical College and Hospital, Chennai, India, were included in the study. Patients on anti-platelet and anti-coagulation therapy and patients already on hormonal treatment for heavy menstrual bleeding were excluded from the study. The demographic factors, symptom profiles, ultrasound findings, and histopathological reports were tabulated and analysed. Of the 147 women included in the study, 75 (51%) were aged 45-50 years and 107 (73%) had two or more pregnancies. Fibroid was the common non-endometrial cause of heavy menstrual bleeding in 52 (35%) cases. The proliferative pattern was the most common non-pathological histology identified in 46 (31%) cases. Endometrial hyperplasia without atypia was the most common pathological histology observed in the study population. Endometrial thickness of more than 8 mm was strongly associated with premalignant or malignant endometrial lesions. Our study has attempted to identify the correlation between ultrasound evaluation of perimenopausal women with heavy menstrual bleeding and endometrial pathology. Ultrasound, being cost-effective and widely available, is proven to be a tool for first-line investigation of perimenopausal women with heavy menstrual bleeding that guides further evaluation and management.

Analysis of Characteristics of Endometrial Carcinoma in Peri- and Postmenopausal Women with Abnormal Uterine Bleeding.

To analyze the menstrual characteristics of endometrial carcinoma and investigate whether abnormal uterine bleeding in the perimenopausal period differs from postmenopausal bleeding. We conducted a retrospective analysis of 928 cases of endometrial carcinoma in patients admitted from January 2016 to December 2022. We gathered fundamental clinical data and analyzed distinct clinical risk factors between the perimenopausal and postmenopausal groups. Furthermore, we computed the statistical variances in menarche, regular menstrual cycles, and the duration of abnormal uterine bleeding. Perimenopausal patients with endometrial carcinoma exhibit similar factors to postmenopausal patients, especially if they have a history of menstrual cycles lasting more than 30 years, hypertension, abnormal uterine bleeding for over 1 year, and a high risk of endometrial carcinoma. Early intervention for abnormal uterine bleeding during the perimenopausal stage can prevent up to 80% of women from developing endometrial carcinoma. Perimenopause women experiencing abnormal uterine bleeding should be mindful of the risk of endometrial carcinoma, as this awareness can substantially decrease the occurrence of the disease.

Interaction between XRCC2 gene polymorphism and abdominal obesity on risk of endometrial carcinoma

Aims The aim of this study was to investigate the impact of three single nucleotide polymorphisms (SNPs) within X-Ray Repair Cross Complementary Group 2 (XRCC2) gene and additional gene- abdominal obesity (AO) interaction with endometrial carcinoma (EC) risk. Methods Hardy–Weinberg equilibrium was tested for all participants by using SNPstats (online software: http://bioinfo.iconcologia.net/SNPstats). The best SNP–SNP and gene–AO interaction combination among three SNPs within XRCC2 gene and AO was screened using generalized multifactor dimensionality reduction (GMDR). Results We employed the logistic regression analysis showed that rs718282-T allele is associated with increased EC risk, adjusted ORs (95%CI) were 1.67 (1.23–2.04). However, we did not find statistical association between rs3218536, and rs3218384 and EC susceptibility. GMDR analysis was used for SNP-SNP- and gene-abdominal obesity analysis. The cross-validation consistency and the testing accuracy for the interaction were calculated. The two-locus model between rs718282 and AO had a testing accuracy of 60.11%, which was significant at the p < .001 level, and this two- locus model was considered as the best model. It provided statistical evidence for rs718282 gene–AO interaction effects. The results indicated that AO influenced the EC risk depending on the rs718282 genotypes. Compared with non- AO subjects with rs718282–CC genotype, AO subjects with rs718282-CT or TT genotype had the highest EC risk, OR (95%CI) was 2.83 (1.67 − 4.02), after covariates adjustment. Conclusions Both the rs718282- T allele, and its interaction with AO were associated with increased EC risk.

Fabrication of controlled-release polymeric microneedles containing progesterone-loaded self-microemulsions for transdermal delivery

Progesterone (PG) has been approved for hormone replacement therapy to mitigate the risk of endometrial carcinoma. However, there has been a lack of success in oral PG due to its rapid degradation. Transdermal PG has advantages but lacks efficacy due to its poor solubility (Log p = 3.9). Therefore, this study aimed to evaluate how combining self-microemulsifying drug delivery systems (SMEDDS) and polymeric microneedles (MNs) could improve the transdermal delivery of PG in a controlled-release manner. Among PG-SMEDDS, PG–SME5 was selected for its desirable properties and stability. The two-layer polymeric MNs formulation incorporating PG–SME5 (PG-SMEDDS-tMNs) was formulated from aqueous blends of polymers as a first layer and 20% PCL as a second layer. It successfully penetrated neonatal porcine skin with the dissolution of the first layer observed within 15 min after application. In vitro skin permeation revealed that the percentage of PG which permeated the skin over 82 h using PG-SMEDDS-tMNs was higher than a PG-suspension and PG-SMEDDS. The Higuchi kinetic showed controlled release over 15 days of PG from PG-SMEDDS-tMNs. These studies suggested that incorporating PG-SMEDDS into controlled-release two-layer polymeric MNs could be a promising approach for improving the transdermal delivery of PG.

Risk of Endometrial Cancer in Asymptomatic Postmenopausal Women in Relation to Ultrasonographic Endometrial Thickness: Systematic Review and Diagnostic Test Accuracy Meta-analysis

(Abstracted from Am J Obstet Gynecol 2023;228:22–35.e2) Endometrial carcinoma (EC) can be suspected in cases of postmenopausal bleeding (PMB) with a thickened endometrium on transvaginal ultrasonography (TVS) examination. Typical guidelines recommend further investigation of PMB when the endometrial lining is greater than 4–5 mm, indicating an elevated risk of EC.

Time interval from biopsy of endometrial atypical hyperplasia to surgery and risk for concurrent endometrial carcinoma - A retrospective study.

Time interval from biopsy of endometrial atypical hyperplasia to surgery and risk for concurrent endometrial carcinoma - A retrospective study.

Exploring the Molecular Interaction of PCOS and Endometrial Carcinoma through Novel Hyperparameter-Optimized Ensemble Clustering Approaches

Polycystic ovary syndrome (PCOS) and endometrial carcinoma (EC) are gynecological conditions that have attracted significant attention due to the higher prevalence of EC in patients with PCOS. Even with this proven association, little is known about the complex molecular pathways that connect PCOS to an increased risk of EC. In order to address this, our study presents two main innovations. To provide a solid basis for our analysis, we have first created a dataset of genes linked to EC and PCOS. Second, we start by building fixed-size ensembles, and then we refine the configuration of a single clustering algorithm within the ensemble at each step of the hyperparameter optimization process. This optimization evaluates the potential performance of the ensemble as a whole, taking into consideration the interactions between each algorithm. All the models in the ensemble are individually optimized with the suitable hyperparameter optimization method, which allows us to tailor the strategy to the model’s needs. Our approach aims to improve the ensemble’s performance, significantly enhancing the accuracy and robustness of clustering outcomes. Through this approach, we aim to enhance our understanding of PCOS and EC, potentially leading to diagnostic and treatment breakthroughs.

Development and validation of prediction model for early warning of ovarian metastasis risk of endometrial carcinoma.

Ovarian metastasis of endometrial carcinoma (EC) patients not only affects the decision of the surgeon, but also has a fatal impact on the fertility and prognosis of patients. This study aimed build a prediction model of ovarian metastasis of EC based on machine learning algorithm for clinical diagnosis and treatment management guidance. We retrospectively collected 536 EC patients treated in Hubei Cancer Hospital from January 2017 to October 2022 and 487 EC patients from Tongji Hospital (January 2017 to December 2020) as an external validation queue. The random forest model, gradient elevator model, support vector machine model, artificial neural network model (ANNM), and decision tree model were used to build ovarian metastasis prediction model for EC patients. The predictive efficacy of 5 machine learning models was evaluated by receiver operating characteristic curve and decision curve analysis. For screening of candidate predictors of ovarian metastasis of EC, the degree of tumor differentiation, lymph node metastasis, CA125, HE4, Alb, LH can be used as a potential predictor of ovarian metastasis prediction model in EC patients. The effectiveness of the prediction model constructed by the 5 machine learning algorithms was between (area under curve [AUC]: 0.729, 95% confidence interval [CI]: 0.674-0.784) and (AUC: 0.899, 95% CI: 0.844-0.954) in the training set and internal verification set, respectively. Among them, the ANNM was equipped with the best prediction effectiveness (training set: AUC: 0.899, 95% CI: 0.844-0.954) and (internal verification set: AUC: 0.892, 95% CI: 0.837-0.947). The prediction model of ovarian metastasis of EC patients based on machine learning algorithm can achieve satisfactory prediction efficiency, among which ANNM is the best, which can be used to guide clinicians in diagnosis and treatment and improve the prognosis of EC patients.

PErsonalized TReatment for Endometrial Carcinoma (PETREC): study design and methods of a prospective Finnish multicenter trial

BackgroundEndometrial carcinomas can be classified into four molecular subgroups – mismatch repair deficient (MMRd), p53 abnormal (p53abn), polymerase-ϵ (POLE) ultramutated, and ‘no specific molecular profile’ (NSMP). Retrospective data imply that...

Triglyceride-glucose index (TyG index) and endometrial carcinoma risk: A retrospective cohort study.

We analyzed the association between the triglyceride-glucose index (TyG index) and incident endometrial carcinogenesis, aiming to determine whether the TyG index is a promising predictive biomarker for endometrial carcinoma (EC). In this retrospective cohort study, multiple logistic regression analysis was performed to evaluate the relationship between TyG index and EC incidence and progression. The receiver operating characteristic (ROC) curve was used to calculate the area under the curve (AUC), as well as the cut-off value of the TyG index for ECincidence. The TyG index was significantly higher in patients with EC or endometrial atypical hyperplasia (EAH) than in those with normal endometrium (P < 0.001). A continuous rise was observed in the incidence of EC and EAH among the tertiles of the TyG index (P < 0.001). The multiple logistic regression analysis revealed that the TyG index was associated with EC and EAH risk after adjusting for potential confounding factors (EAH: odds ratio [OR] 2.54, 95% confidence interval [CI] 1.33-4.85, P = 0.005; EC: OR 2.65, 95% CI 1.60-4.41, P < 0.001). Moreover, high TyG index was positively associated with advanced pathological stage (OR 2.14, 95% CI 1.32-3.47, P = 0.002) and poorer differentiation (OR 2.53, 95% CI 1.36-4.72, P = 0.004). The TyG index might be a promising biomarker for endometrial carcinogenesis. Subjects with a higher TyG index should be aware of the risk of EC incidence and progression.

Patient-initiated follow-up in women with early-stage endometrial cancer: a long-term follow-up of the OPAL trial.

A long-term follow-up of the OPAL trial to compare the effect of patient-initiated (PIFU) versus hospital-based (HBFU) follow-up on fear of cancer recurrence (FCR), quality of life (QoL) and healthcare use after 34 months of follow-up. Pragmatic, multicentre randomised trial. Four Danish departments of gynaecology between May 2013 and May 2016. 212 women diagnosed with stage I low-intermediate risk endometrial carcinoma. The control group attended HBFU with regular outpatient visits (i.e., 8)for 3 years after primary treatment. The intervention group underwent PIFU with no prescheduled visits but with instructions about alarm symptoms and options of self-referral. The endpoints were FCR as measured by the Fear of Cancer Recurrence Inventory (FCRI) and QoL as measured by the European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire C-30 (EORTC QLQ C-30), and healthcare use as measured by questionnaires and chart reviews after 34 months of follow-up. FCR decreased from baseline to 34 months in both groups and no difference was found between allocations (difference -6.31 [95% confidence interval -14.24 to 1.63]). QoL remained stable with no difference in any domains between the two arms at 34 months using a linear mixed model analysis. The use of healthcare was significantly lower in the PIFU group (P < 0.01). Patient-initiated follow-up is a valid alternative to hospital-based follow-up for people who have been treated for endometrial cancer and have low risk of recurrence.

Does concomitant hysterectomy impact menopausal symptoms in premenopausal BRCA1/2 pathogenic carriers undergoing risk reducing salpingo-oophorectomy?

Prevention of high-grade serous carcinoma in women with a pathogenic variant in the BRCA1/2 genes includes prophylactic bilateral salpingo-oophorectomy (PBSO). There is debate on whether concomitant hysterectomy should be offered, with benefits including decreased risk of endometrial carcinoma and the option to use estrogen-alone menopausal hormone therapy (MHT), which is thought to be associated with better menopause-specific quality of life and lower breast cancer risk. The objective is to determine if BRCA1/2 mutation carriers undergoing premenopausal PBSO with concomitant hysterectomy have improved MENQOL compared with those women with an intact uterus.

Development of a Risk Prediction Model for endometrial carcinoma among postmenopausal women in the Western province of Sri Lanka.

Globally, endometrial carcinoma is the most common reproductive tract cancer among women. Risk prediction model is a simple, low-cost tool to identify women with increased risk of developing endometrial carcinoma. Objectives: The aim of the study was to develop a model to predict the risk of endometrial carcinoma among postmenopausal women in Sri Lanka. A case control study was conducted. The cases and the controls were defined as postmenopausal women who had and had not been diagnosed as endometrial carcinoma based on histological confirmation respectively. Variable selection was done considering the objectivity and feasibility of the measurements in addition to the statistical criteria. A scoring system [0-9] was designed based on weighted score of each risk predictor. Predictive validity of the model was tested by calibration and discrimination. Receiver Operator Characteristic (ROC) curve was used to determine the cut-off value. The developed model consisted of six predictors; Age >55 years, never conceived, age at menarche ≤11 years, ever experienced postmenopausal bleeding, having family history of any type of cancer among first degree relative, generalized obesity. Discrimination of the model was measured by the area under the ROC curve (0.92, 95% Confidence Interval: 0.88-0.95). Calibration with goodness of fit by Hosmer and Lemeshow test (p=0.72) was satisfactory. The tool demonstrated a good predictive ability with sensitivity of 79.5% (CI: 68.9%-87.3%) and specificity of 90.7% (CI: 86.8%-93.5%) at the cut-off point of 4.5. Model demonstrated good discrimination and well calibration. It can be used in screening of high-risk women for developing endometrial carcinoma.

Interpretable prognostic modeling of endometrial cancer

Endometrial carcinoma (EC) is one of the most common gynecological cancers in the world. In this work we apply Cox proportional hazards (CPH) and optimal survival tree (OST) algorithms to the retrospective prognostic modeling of disease-specific survival in 842 EC patients. We demonstrate that linear CPH models are preferred for the EC risk assessment based on clinical features alone, while interpretable, non-linear OST models are favored when patient profiles can be supplemented with additional biomarker data. We show how visually interpretable tree models can help generate and explore novel research hypotheses by studying the OST decision path structure, in which L1 cell adhesion molecule expression and estrogen receptor status are correctly indicated as important risk factors in the p53 abnormal EC subgroup. To aid further clinical adoption of advanced machine learning techniques, we stress the importance of quantifying model discrimination and calibration performance in the development of explainable clinical prediction models.

MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer

High- and low-risk endometrial carcinoma (EC) differ in whether or not a lymphadenectomy is performed. We aimed to develop MRI-based radio-genomic models able to preoperatively assess lymph-vascular space invasion (LVSI) and discriminate between low- and high-risk EC according to the ESMO-ESGO-ESTRO 2020 guidelines, which include molecular risk classification proposed by "ProMisE". This is a retrospective, multicentric study that included 64 women with EC who underwent 3T-MRI before a hysterectomy. Radiomics features were extracted from T2WI images and apparent diffusion coefficient maps (ADC) after manual segmentation of the gross tumor volume. We constructed a multiple logistic regression approach from the most relevant radiomic features to distinguish between low- and high-risk classes under the ESMO-ESGO-ESTRO 2020 guidelines. A similar approach was taken to assess LVSI. Model diagnostic performance was assessed via ROC curves, accuracy, sensitivity and specificity on training and test sets. The LVSI predictive model used a single feature from ADC as a predictor; the risk class model used two features as predictors from both ADC and T2WI. The low-risk predictive model showed an AUC of 0.74 with an accuracy, sensitivity, and specificity of 0.74, 0.76, 0.94; the LVSI model showed an AUC of 0.59 with an accuracy, sensitivity, and specificity of 0.60, 0.50, 0.61. MRI-based radio-genomic models are useful for preoperative EC risk stratification and may facilitate therapeutic management.

Risk of Endometrial Polyps, Hyperplasia, Carcinoma, and Uterine Cancer After Tamoxifen Treatment in Premenopausal Women With Breast Cancer

The association of tamoxifen use with the risk of uterine diseases, such as endometrial cancer, in premenopausal women with breast cancer remains controversial. However, many studies have reported an increased risk of uterine disease among postmenopausal tamoxifen users. To investigate the association of tamoxifen use with the risk of endometrial cancer and other uterine diseases in premenopausal women with breast cancer. A nationwide, population-based, retrospective longitudinal cohort study with an 18-year study period was conducted using data obtained from the Korean National Health Insurance Service. Participants included premenopausal women aged 20 to 50 years with breast cancer diagnoses between January 2003 and December 2018. Data were analyzed from April to December 2021. Tamoxifen treatment. The incidence of uterine diseases, including endometrial cancer, hyperplasia, polyps, and other uterine cancers, was identified in the study cohort using insurance claim codes. The incidence of uterine diseases per 1000 person-years was compared between women receiving tamoxifen and those not treated with adjuvant hormone therapy. Multivariable Cox proportional hazard regression analysis was performed to determine the risk of each uterine disease. Among 78 320 female participants with a mean (SD) age of 42.1 (6.1) years, 34 637 (44.2%) were categorized into the tamoxifen group and 43 683 (55.8%) were categorized into the control group. Among tamoxifen users, during the mean (SD) follow-up duration of 6.13 (4.15) years, the incidence of newly diagnosed endometrial polyps was 20.13 cases per 1000 person-years, that of endometrial hyperplasia was 13.49 cases per 1000 person-years, that of endometrial cancer was 2.01 cases per 1000 person-years, and that of other uterine cancers was 0.45 cases per 1000 person-years. The risk of endometrial cancer was higher in the tamoxifen group than in the control group (hazard ratio, 3.77; 95% CI, 3.04-4.66) after adjusting for age, body mass index, history of diabetes, hypertension, dyslipidemia, polycystic ovary syndrome, gonadotropin-releasing hormone agonist treatment, and trastuzumab treatment. In this longitudinal cohort study, premenopausal Korean women with breast cancer who received tamoxifen as adjuvant hormone therapy had a significantly increased risk of endometrial hyperplasia, polyps, carcinoma, and other uterine cancers compared with those who were not treated with adjuvant hormone therapy. These findings suggest that clinicians should consider the risk of uterine disease among tamoxifen users, including premenopausal women.

Misunderstood “menopausal” hormones: their controversy and complexity

No AccessMisunderstood “menopausal” hormones: their controversy and complexityBringing harmony to a bunch of misinterpreted hormones and to the women that flower our world Paulo de Valdoleiros Paulo de Valdoleiros1 https://orcid.org/0000-0002-7911-1293 Search for more papers by this author Affiliations 1Private practice, Cape Town, South Africa Published Online:1 Nov 2022https://doi.org/10.36303/SAGP.2022.3.5.0142https://hdl.handle.net/10520/ejc-mp_sagp_v3_n5_a5SectionsPDFView Full Text ToolsAdd to favouritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditGMailOutlookYammermore AboutAbstractThis is the fourth article in the menopause series that began three South African GP editions ago. For the sake of continuity, it is recommended that you access the previous episodes if you missed them.1. Smith DCPrentice RThompson DJHerrmann WL "Association of exogenous estrogen and endometrial carcinoma" N Engl J Med1975 2932311647 DOI: https://doi.org/10.1056/NEJM197512042932302 Google Scholar2. Ziel HKFinkle WD "Increased risk of endometrial carcinoma among users of conjugated estrogens" N Engl J Med1975 29323116770 DOI: https://doi.org/10.1056/NEJM197512042932303 Google Scholar3. Kohn GERodriguez KMHotaling JPastuszak AW "The history of estrogen therapy" Sex Med Rev2019 7341621 DOI: https://doi.org/10.1016/j.sxmr.2019.03.006 Google Scholar4. WHOCancer fact sheetAvailable from: https://www.who.int/news-room/fact-sheets/detail/cancer#:~:text=The%20most%20common%20causes%20of,lung%20(1.80%20million%20deaths)%3B Google Scholar5. Stefanick ML "Estrogens and progestins: background and history, trends in use, and guidelines and regimens approved by the US Food and Drug Administration" Am J Med2005 118Suppl 12B6473 DOI: https://doi.org/10.1016/j.amjmed.2005.09.059 Google Scholar6. Horvath SSchreiber CASonalkar S "Contraception" Updated 2018 Jan 17Feingold KRAnawalt BBoyce Aet al.Endotext [Internet]South Dartmouth (MA) MDText.com, Inc.2000Table 2, Contraindications to Progestin-only Hormonal Contraceptives. Available from: https://www.ncbi.nlm.nih.gov/books/NBK279148/table/contraception.progestino/ Google Scholar7. Czyzyk APodfigurna AGenazzani ARMeczekalski B "The role of progesterone therapy in early pregnancy: from physiological role to therapeutic utility" Gynecol Endocrinol2017 3364214 DOI: https://doi.org/10.1080/09513590.2017.1291615 Google Scholar8. Rossouw JEAnderson GLPrentice RLet al. "Writing Group for the Women’s Health Initiative Investigators. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women’s Health Initiative randomized controlled trial" JAMA2002 288332133 DOI: https://doi.org/10.1001/jama.288.3.321 Google Scholar9. Viscoli CMBrass LMKernan WNet al. "A clinical trial of estrogen-replacement therapy after ischemic stroke" N Engl J Med2001 3451712439 DOI: https://doi.org/10.1056/NEJMoa010534 Google Scholar10. Manson JEChlebowski RTStefanick MLet al. "Menopausal hormone therapy and health outcomes during the intervention and extended poststopping phases of the Women’s Health Initiative randomized trials" JAMA2013 31013135368 DOI: https://doi.org/10.1001/jama.2013.278040 Google Scholar Previous article Next article FiguresReferencesRelatedDetails None Volume 3, Issue 5 | Nov 2022 Downloaded 1 times LanguagesEnglish InformationCopyright © 2022, Medpharm Publications:All rights reservedKeywordscardiovascularprogestinMIprogesteronemenopauseosteoporosisHRTestradiolstrokecancerPDF download Disclosure The authors confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. The authors confirm that they have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. Ethical conduct of research The authors state that they have obtained appropriate institutional review board outlined in the Declaration of Helsinki for all human or animal experimental investigations. A signed informed consent document has been obtained from all participants included in the study.

A functional polymorphism in the poly(ADP-ribose) polymerase-1 gene increases the risk of endometrial carcinoma

The aim of this study was to investigate the effects of two functional genetic polymorphisms in the poly(ADP-ribose) polymerase-1 (PARP-1) gene on the risk of endometrial carcinoma (EC). Genotypes of the rs1136410 and rs8679 polymorphisms were determined by polymerase chain reaction and ligase detection reaction in 327 EC patients and 329 controls. The results showed that there were significant differences in the genotype distributions of rs1136410 between cases and controls. Women carrying the rs1136410 CC genotype had a significantly increased risk of EC compared to those with the rs1136410 TT genotype (OR = 1.73, 95% CI = 1.10–2.72, p = .018). After adjustment for clinical characteristics, the rs1136410 CC genotype still significantly increased the risk of EC (adjusted OR = 1.83, 95% CI = 1.09–3.07, p = .021). However, no significant difference was observed in the genotype frequencies of rs8679 between cases and controls. This study indicated that rs1136410 was related to the risk of developing EC, and the CC genotype of rs1136410 may be a risk factor for EC in the northern Chinese population. IMPACT STATEMENT What is already known on this subject? Genetic variations in the PARP-1 gene may affect protein function and hence reduce DNA repair capacity, leading to the accumulation of DNA damage and a subsequent increased probability of tumorigenesis. Previous studies have shown that polymorphisms of the PARP-1 gene are associated with the risk of various carcinomas, including breast cancer, lung cancer, thyroid cancer, colorectal cancer, and oral squamous cell carcinoma. What do the results of this study add? Our results suggest that the rs1136410 polymorphism of PARP-1 was related to the risk of developing endometrial carcinoma, and the CC genotype of rs1136410 may be a risk factor for endometrial carcinoma in the northern Chinese population. What are the implications of these findings for clinical practice and/or further research? The new genetic marker may help to identify genetic basis of endometrial carcinoma, and develop gene-targeted therapies for endometrial carcinoma.

Predicting recurrence and metastasis risk of endometrial carcinoma via prognostic signatures identified from multi-omics data.

ObjectivesEndometrial carcinoma (EC) is one of the three major gynecological malignancies, in which 15% - 20% patients will have recurrence and metastasis. Though there are many studies on the prognosis on this cancer, the performances of existing models evaluating the risk of its recurrence and metastasis are yet to be improved. In addition, a comprehensive multi-omics analyses on the prognostic signatures of EC are on demand. In this study, we aimed to construct a relatively stable and reliable model for predicting recurrence and metastasis of EC. This will help determine the risk level of patients and choose appropriate adjuvant therapy, thereby avoiding improper treatment, and improving the prognosis of patients.MethodsThe mRNA, microRNA (miRNA), long non-coding RNA (lncRNA), copy number variation (CNV) data and clinical information of patients with EC were downloaded from The Cancer Genome Atlas (TCGA). Differential expression analyses were performed between the recurrence or metastasis group and the non-recurrence/metastasis group. Then, we screened potential prognostic markers from the four kinds of omics data respectively and established prediction models using three classifiers.ResultsWe achieved differential expressed mRNAs, lncRNAs, miRNAs and CNVs between the two groups. According to feature selection scores by the random forest algorithm, 275 CNV features, 50 lncRNA features, 150 miRNA features and 150 mRNA features were selected, respectively. And the prediction model constructed by the features of lncRNA data using random forest method showed the best performance, with an area under the curve of 0.763, and an accuracy of 0.819 under 10-fold cross-validation.ConclusionWe developed a computational model using omics information, which is able to predicting recurrence and metastasis risk of EC accurately.