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01 januari 2023, Item does not contain fulltext, OBJECTIVE: This study presents the diagnostic performance of four different preoperative imaging workups (IWs) for prediction of lymph node metastases (LNMs) in endometrial cancer (EC): pelvic MRI alone (IW1), MRI and [(18)F]FDG-PET/CT in all patients (IW2), MRI with selective [(18)F]FDG-PET/CT if high-risk preoperative histology (IW3), and MRI with selective [(18)F]FDG-PET/CT if MRI indicates FIGO stage ≥ 1B (IW4). METHODS: In 361 EC patients, preoperative staging parameters from both pelvic MRI and [(18)F]FDG-PET/CT were recorded. Area under receiver operating characteristic curves (ROC AUC) compared the diagnostic performance for the different imaging parameters and workups for predicting surgicopathological FIGO stage. Survival data were assessed using Kaplan-Meier estimator with log-rank test. RESULTS: MRI and [(18)F]FDG-PET/CT staging parameters yielded similar AUCs for predicting corresponding FIGO staging parameters in low-risk versus high-risk histology groups (p ≥ 0.16). The sensitivities, specificities, and AUCs for LNM prediction were as follows: IW1-33% [9/27], 95% [185/193], and 0.64; IW2-56% [15/27], 90% [174/193], and 0.73 (p = 0.04 vs. IW1); IW3-44% [12/27], 94% [181/193], and 0.69 (p = 0.13 vs. IW1); and IW4-52% [14/27], 91% [176/193], and 0.72 (p = 0.06 vs. IW1). IW3 and IW4 selected 34% [121/361] and 54% [194/361] to [(18)F]FDG-PET/CT, respectively. Employing IW4 identified three distinct patient risk groups that exhibited increasing FIGO stage (p < 0.001) and stepwise reductions in survival (p ≤ 0.002). CONCLUSION: Selective [(18)F]FDG-PET/CT in patients with high-risk MRI findings yields better detection of LNM than MRI alone, and similar diagnostic performance to that of MRI and [(18)F]FDG-PET/CT in all. KEY POINTS: • Imaging by MRI and [(18)F]FDG PET/CT yields similar diagnostic performance in low- and high-risk histology groups for predicting central FIGO staging parameters. • Utilizing a stepwise imaging workup with MRI in all patients and

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 x 10-8) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.Copyright © 2020 Union for International Cancer Control

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.

Contains fulltext : 220465.pdf (publisher's version ) (Open Access), BACKGROUND: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. METHODS AND FINDINGS: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte

Objective Design Correct preoperative identification of high-risk patients is important to optimise surgical treatment and improve survival. We wanted to explore if asparaginase-like protein 1 (ASRGL1) expression in curettage could predict lymph node metastases and poor outcome, potentially improving preoperative risk stratification. Multicentre study. Setting Population Ten hospitals in Norway, Sweden and Belgium. Women diagnosed with endometrial carcinoma. Methods Main outcome measures ASRGL1 expression in curettage specimens from 1144 women was determined by immunohistochemistry. ASRGL1 status related to disease-specific survival, lymph node status, preoperative imaging parameters and clinicopathological data. Results Conclusions ASRGL1 expression had independent prognostic value in multivariate survival analyses, both in the whole patient population (hazard ratio (HR) 1.63, 95% CI 1.11-2.37, P = 0.012) and in the low-risk curettage histology subgroup (HR 2.54, 95% CI 1.44-4.47, P = 0.001). Lymph node metastases were more frequent in women with low expression of ASRGL1 compared with women with high ASRGL1 levels (23% versus 10%, P < 0.001), and low ASRGL1 level was found to independently predict lymph node metastases (odds ratio 2.07, 95% CI 1.27-3.38, P = 0.003). Low expression of ASRGL1 in curettage independently predicts lymph node metastases and poor disease-specific survival.

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.Copyright © 2018, The Author(s).

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (rg = 0.23, P = 9.3 × 10-3 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10-3 ) and concordance in effect direction (P = 2.0 × 10-3 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10-5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10-8 , OR = 1.11, 95% CI = 1.07-1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.

Item does not contain fulltext, BACKGROUND: Several studies have identified L1 cell adhesion molecule (L1CAM) as a strong prognostic marker in endometrial cancer. To further underline the clinical usefulness of this biomarker, we investigated L1CAM as a predictive marker for lymph node metastases and its prognostic impact in curettage specimens and preoperative plasma samples. In addition, we aimed to validate the prognostic value of L1CAM in hysterectomy specimen. METHODS: Immunohistochemical staining of L1CAM was performed for 795 hysterectomy and 1134 curettage specimen from endometrial cancer patients. The L1CAM level in preoperative blood samples from 372 patients was determined using ELISA. RESULTS: Expression of L1CAM in curettage specimen was significantly correlated to L1CAM level in corresponding hysterectomy specimen (P<0.001). Both in curettage and preoperative plasma samples L1CAM upregulation was significantly associated with features of aggressive disease and poor outcome (P<0.001). The L1CAM was an independent predictor of lymph node metastases, after correction for curettage histology, both in curettage specimen (P=0.002) and plasma samples (P=0.048). In the hysterectomy samples L1CAM was significantly associated with poor outcome (P<0.001). CONCLUSIONS: We demonstrate that preoperative evaluation of L1CAM levels, both in curettage or plasma samples, predicts lymph node metastases and adds valuable information on patient prognosis.

Contains fulltext : 170511.pdf (publisher's version ) (Closed access), Purpose: Uterine sarcomas are rare and heterogeneous tumors characterized by an aggressive clinical behavior. Their high rates of recurrence and mortality point to the urgent need for novel targeted therapies and alternative treatment strategies. However, no molecular prognostic or predictive biomarkers are available so far to guide choice and modality of treatment.Experimental Design: We investigated the expression of several druggable targets (phospho-S6S240 ribosomal protein, PTEN, PDGFR-alpha, ERBB2, and EGFR) in a large cohort of human uterine sarcoma samples (288), including leiomyosarcomas, low-grade and high-grade endometrial stromal sarcomas, undifferentiated uterine sarcomas, and adenosarcomas, together with 15 smooth muscle tumors of uncertain malignant potential (STUMP), 52 benign uterine stromal tumors, and 41 normal uterine tissues. The potential therapeutic value of the most promising target, p-S6S240, was tested in patient-derived xenograft (PDX) leiomyosarcoma models.Results: In uterine sarcomas and STUMPs, S6S240 phosphorylation (reflecting mTOR pathway activation) was associated with higher grade (P = 0.001) and recurrence (P = 0.019), as shown by logistic regression. In addition, p-S6S240 correlated with shorter progression-free survival (P = 0.034). Treatment with a dual PI3K/mTOR inhibitor significantly reduced tumor growth in 4 of 5 leiomyosarcoma PDX models (with tumor shrinkage in 2 models). Remarkably, the 4 responding models showed basal p-S6S240 expression, whereas the nonresponding model was scored as negative, suggesting a role for p-S6S240 in response prediction to PI3K/mTOR inhibition.Conclusions: Dual PI3K/mTOR inhibition represents an effective therapeutic strategy in uterine leiomyosarcoma, and p-S6S240 expression is a potential predictive biomarker for response to treatment. Clin Cancer Res; 23(5); 1274-85. (c)2017 AACR.

Contains fulltext : 180483.pdf (publisher's version ) (Closed access)

Contains fulltext : 165692.pdf (publisher's version ) (Open Access), BACKGROUND: Identification of aggressive endometrioid endometrial carcinomas (EECs) and non-endometrioid carcinomas (NEECs) is essential to improve outcome. L1 cell adhesion molecule (L1CAM) expression is a strong prognostic marker in stage I EECs, but less is known about L1CAM expression in advanced-stage EECs and NEECs. This study analyses L1CAM expression in a clinically representative cohort of endometrial carcinomas. METHODS: The expression of L1CAM was immunohistochemically determined in 1199 endometrial carcinomas, treated at one of the European Network for Individualized Treatment of Endometrial Cancer (ENITEC) centres. Staining was considered positive when >10% of the tumour cells expressed L1CAM. The association between L1CAM expression and several clincopathological characteristics and disease outcome was calculated. RESULTS: In all, L1CAM was expressed in 10% of the 935 stage I EECs, 18% of the 160 advanced stage EECs, and 75% of the 104 NEECs. The expression of L1CAM was associated with advanced stage, nodal involvement, high tumour grade, non-endometrioid histology, lymphovascular space invasion, and distant recurrences in all cases, and with reduced survival in the EECs, but not in the NEECs. CONCLUSIONS: The expression of L1CAM is a strong predictor of poor outcome in EECs, but not NEECs. It is strongly associated with non-endometrioid histology and distant spread, and could improve the postoperative selection of high-risk endometrial carcinomas. The value of L1CAM expression in the preoperative selection of high-risk endometrial carcinomas should be studied.

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression.

Several studies have reported associations between multiple cancer types and single-nucleotide polymorphisms (SNPs) on chromosome 5p15, which harbours TERT and CLPTM1L, but no such association has been reported with endometrial cancer. To evaluate the role of genetic variants at the TERT-CLPTM1L region in endometrial cancer risk, we carried out comprehensive fine-mapping analyses of genotyped and imputed SNPs using a custom Illumina iSelect array which includes dense SNP coverage of this region. We examined 396 SNPs (113 genotyped, 283 imputed) in 4,401 endometrial cancer cases and 28,758 controls. Single-SNP and forward/backward logistic regression models suggested evidence for three variants independently associated with endometrial cancer risk (P = 4.9 × 10(-6) to P = 7.7 × 10(-5)). Only one falls into a haplotype previously associated with other cancer types (rs7705526, in TERT intron 1), and this SNP has been shown to alter TERT promoter activity. One of the novel associations (rs13174814) maps to a second region in the TERT promoter and the other (rs62329728) is in the promoter region of CLPTM1L; neither are correlated with previously reported cancer-associated SNPs. Using TCGA RNASeq data, we found significantly increased expression of both TERT and CLPTM1L in endometrial cancer tissue compared with normal tissue (TERT P = 1.5 × 10(-18), CLPTM1L P = 1.5 × 10(-19)). Our study thus reports a novel endometrial cancer risk locus and expands the spectrum of cancer types associated with genetic variation at 5p15, further highlighting the importance of this region for cancer susceptibility.

High-risk mutations in several genes predispose to both colorectal cancer (CRC) and endometrial cancer (EC). We therefore hypothesised that some lower-risk genetic variants might also predispose to both CRC and EC. Using CRC and EC genome-wide association series, totalling 13,265 cancer cases and 40,245 controls, we found that the protective allele [G] at one previously-identified CRC polymorphism, rs2736100 near TERT, was associated with EC risk (odds ratio (OR) = 1.08, P = 0.000167); this polymorphism influences the risk of several other cancers. A further CRC polymorphism near TERC also showed evidence of association with EC (OR = 0.92; P = 0.03). Overall, however, there was no good evidence that the set of CRC polymorphisms was associated with EC risk, and neither of two previously-reported EC polymorphisms was associated with CRC risk. A combined analysis revealed one genome-wide significant polymorphism, rs3184504, on chromosome 12q24 (OR = 1.10, P = 7.23 × 10(-9)) with shared effects on CRC and EC risk. This polymorphism, a missense variant in the gene SH2B3, is also associated with haematological and autoimmune disorders, suggesting that it influences cancer risk through the immune response. Another polymorphism, rs12970291 near gene TSHZ1, was associated with both CRC and EC (OR = 1.26, P = 4.82 × 10(-8)), with the alleles showing opposite effects on the risks of the two cancers.

The MDM2 proto-oncogene plays a key role in central cellular processes like growth control and apoptosis, and the gene locus is frequently amplified in sarcomas. Two polymorphisms located in the MDM2 promoter P2 have been shown to affect cancer risk. One of these polymorphisms (SNP309T

The MDM2 proto-oncogene plays a key role in central cellular processes like growth control and apoptosis, and the gene locus is frequently amplified in sarcomas. Two polymorphisms located in the MDM2 promoter P2 have been shown to affect cancer risk. One of these polymorphisms (SNP309T>G; rs2279744) facilitates Sp1 transcription factor binding to the promoter and is associated with increased cancer risk. In contrast, SNP285G>C (rs117039649), located 24 bp upstream of rs2279744, and in complete linkage disequilibrium with the SNP309G allele, reduces Sp1 recruitment and lowers cancer risk. Thus, fine tuning of MDM2 expression has proven to be of significant importance with respect to tumorigenesis. We assessed the potential functional effects of a third MDM2 promoter P2 polymorphism (SNP344T>A; rs1196333) located on the SNP309T allele. While in silico analyses indicated SNP344A to modulate TFAP2A, SPIB and AP1 transcription factor binding, we found no effect of SNP344 status on MDM2 expression levels. Assessing the frequency of SNP344A in healthy Caucasians (n = 2,954) and patients suffering from ovarian (n = 1,927), breast (n = 1,271), endometrial (n = 895) or prostatic cancer (n = 641), we detected no significant difference in the distribution of this polymorphism between any of these cancer forms and healthy controls (6.1% in healthy controls, and 4.9%, 5.0%, 5.4% and 7.2% in the cancer groups, respectively). In conclusion, our findings provide no evidence indicating that SNP344A may affect MDM2 transcription or cancer risk.

Although 75% of endometrial cancers are treated at an early stage, 15% to 20% of these recur. We performed an integrated analysis of genome-wide expression and copy-number data for primary endometrial carcinomas with extensive clinical and histopathological data to detect features predictive of recurrent disease. Unsupervised analysis of the expression data distinguished 2 major clusters with strikingly different phenotypes, including significant differences in disease-free survival. To identify possible mechanisms for these differences, we performed a global genomic survey of amplifications, deletions, and loss of heterozygosity, which identified 11 significantly amplified and 13 significantly deleted regions. Amplifications of 3q26.32 harboring the oncogene PIK3CA were associated with poor prognosis and segregated with the aggressive transcriptional cluster. Moreover, samples with PIK3CA amplification carried signatures associated with in vitro activation of PI3 kinase (PI3K), a signature that was shared by aggressive tumors without PIK3CA amplification. Tumors with loss of PTEN expression or PIK3CA overexpression that did not have PIK3CA amplification also shared the PI3K activation signature, high protein expression of the PI3K pathway member STMN1, and an aggressive phenotype in test and validation datasets. However, mutations of PTEN or PIK3CA were not associated with the same expression profile or aggressive phenotype. STMN1 expression had independent prognostic value. The results affirm the utility of systematic characterization of the cancer genome in clinically annotated specimens and suggest the particular importance of the PI3K pathway in patients who have aggressive endometrial cancer., Dana-Farber Harvard Cancer Center Prostate Specialized Program in Research Excellence, National Institutes of Health, Department of Defense, Research Council of Norway, Norwegian Cancer Society, University of Bergen, Helse Vest