Aberrant methylation of FAT4 and SOX11 in peripheral blood leukocytes and their association with gastric cancer risk

SOX11 as a potential prognostic biomarker in hepatocellular carcinoma linked to immune infiltration and ferroptosis

Objective

SOX11 is expressed in numerous malignancies, including hepatocellular carcinomas (HCC), but its oncogenic function has not been elucidated. Here, we performed a comprehensive bioinformatics analysis of the Liver Hepatocellular Carcinoma (LIHC) dataset to investigate the function of SOX11 in tumorgenesis.

Methods

SOX11 expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were validated by immunohistochemistry (IHC). Co-expression, differential expression, and functional analyses utilized TCGA-LIHC, Timer 2.0, Metascape, GTEx, and LinkedOmics databases. Associations with immune infiltration, ferroptosis, and immune checkpoint genes were assessed. Genetic changes were explored via CBioPortal. Logistic regression, receiver operating characteristic curve (ROC), Kaplan-Meier analysis, and nomogram modeling evaluated associations with HCC clinicopathological features. SOX11's impact on proliferation and migration was studied in HepG2 and HuH7 cell lines.

Results

SOX11 was significantly elevated in HCC tumors compared to controls. SOX11-associated genes exhibited differential expression in pathways involving extracellular membrane ion channels. Significant associations were found between SOX11 levels, immune infiltration, ferroptosis, and immune checkpoint genes in HCC tissue. SOX11 levels correlated with HCC stage, histologic grade, and tumor status, and independently predicted overall and disease-specific survival. SOX11 expression effectively distinguished between tumor and normal liver tissue. Spearman correlations highlighted a significant relationship between SOX11 and ferroptosis-associated genes. Decreased SOX11 levels in HepG2 and HuH7 cells resulted in reduced proliferation and migration.

Conclusions

SOX11 was found to represent a promising biomarker within HCC diagnosis and prognosis together with being a possible drug-target.

DNA methylation drives a new path in gastric cancer early detection: Current impact and prospects

Gastric cancer (GC) is one of the most common and deadly cancers worldwide. Early detection offers the best chance for curative treatment and reducing its mortality. However, the optimal population-based early screening for GC remains unmet. Aberrant DNA methylation occurs in the early stage of GC, exhibiting cancer-specific genetic and epigenetic changes, and can be detected in the media such as blood, gastric juice, and feces, constituting a valuable biomarker for cancer early detection. Furthermore, DNA methylation is a stable epigenetic alteration, and many innovative methods have been developed to quantify it rapidly and accurately. Nonetheless, large-scale clinical validation of DNA methylation serving as tumor biomarkers is still lacking, precluding their implementation in clinical practice. In conclusion, after a critical analysis of the recent existing literature, we summarized the evolving roles of DNA methylation during GC occurrence, expounded the newly discovered noninvasive DNA methylation biomarkers for early detection of GC, and discussed its challenges and prospects in clinical applications.

Fat and Dachsous cadherins in mammalian development

Cell growth and patterning are critical for tissue development. Here we discuss the evolutionarily conserved cadherins, Fat and Dachsous, and the roles they play during mammalian tissue development and disease. In Drosophila, Fat and Dachsous regulate tissue growth via the Hippo pathway and planar cell polarity (PCP). The Drosophila wing has been an ideal tissue to observe how mutations in these cadherins affect tissue development. In mammals, there are multiple Fat and Dachsous cadherins, which are expressed in many tissues, but mutations in these cadherins that affect growth and tissue organization are context dependent. Here we examine how mutations in the Fat and Dachsous mammalian genes affect development in mammals and contribute to human disease.

Systematic Investigation of the Multifaceted Role of SOX11 in Cancer

SRY-box transcription factor 11 (SOX11), as a member of the SOX family, is a transcription factor involved in the regulation of specific biological processes and has recently been found to be a prognostic marker for certain cancers. However, the roles of SOX11 in cancer remain controversial. Our study aimed to explore the various aspects of SOX11 in pan-cancer. The expression of SOX11 was investigated by the Genotype Tissue-Expression (GTEX) dataset and the Cancer Genome Atlas (TCGA) database. The protein level of SOX11 in tumor tissues and tumor-adjacent tissues was verified by human pan-cancer tissue microarray. Additionally, we used TCGA pan-cancer data to analyze the correlations among SOX11 expression and survival outcomes, clinical features, stemness, microsatellite instability (MSI), tumor mutation burden (TMB), mismatch repair (MMR) related genes and the tumor immune microenvironment. Furthermore, the cBioPortal database was applied to investigate the gene alterations of SOX11. The main biological processes of SOX11 in cancers were analyzed by Gene Set Enrichment Analysis (GSEA). As a result, aberrant expression of SOX11 has been implicated in 27 kinds of cancer types. Aberrant SOX11 expression was closely associated with survival outcomes, stage, tumor recurrence, MSI, TMB and MMR-related genes. In addition, the most frequent alteration of the SOX11 genome was mutation. Our study also showed the correlations of SOX11 with the level of immune infiltration in various cancers. In summary, our findings underline the multifaceted role and prognostic value of SOX11 in pan-cancer.

Risk factors and a nomogram model for postoperative delirium in elderly gastric cancer patients after laparoscopic gastrectomy

Background

To evaluate the risk factors of postoperative delirium (POD) in elderly gastric cancer (GC) patients after laparoscopic gastrectomy and construct a predictive model.

Methods

Elderly GC patients undergoing laparoscopic gastrectomy were enrolled and grouped based on the status of POD development within postoperative 7 days. Independent risk factors were selected out by univariate and multivariate logistic regression analyses and then enrolled in the nomogram prediction model.

Results

A total of 270 elderly GC patients were enrolled, and POD occurred in 74 (27.4%) patients within postoperative 7 days. The results of multivariate regression analysis indicated that age (OR: 3.30, 95% CI: 1.41–6.85, P < 0.001), sleeping pills (OR: 1.87, 95% CI: 1.12–3.09, P = 0.012), duration of ICU stay (OR: 1.55, 95% CI: 1.02–2.37, P = 0.029), albumin/fibrinogen ratio (AFR) (OR: 1.74, 95% CI: 1.03–2.76, P = 0.019), and neutrophils/lymphocytes ratio (NLR) (OR: 2.12, 95% CI: 1.11–4.01, P = 0.016) were five independent risk factors for POD in elderly GC patients. The AUC of the constructed nomogram model based on these five factors was 0.807.

Conclusions

This study highlighted that age, AFR, NLR, sleeping pills taking, and duration of ICU stay were independent risk factors for POD, and the nomogram model based on these factors could effectively predict POD in elderly GC patients.

DNA Methylation: An Important Biomarker and Therapeutic Target for Gastric Cancer

Gastric cancer (GC) is a very common malignancy with a poor prognosis, and its occurrence and development are closely related to epigenetic modifications. Methylation of DNA before or during gastric cancer is an interesting research topic. This article reviews the studies on DNA methylation related to the cause, diagnosis, treatment, and prognosis of gastric cancer and aims to find cancer biomarkers to solve major human health problems.

Epigenome-Wide Association Study of Prostate Cancer in African Americans Identifies DNA Methylation Biomarkers for Aggressive Disease

DNA methylation plays important roles in prostate cancer (PCa) development and progression. African American men have higher incidence and mortality rates of PCa than other racial groups in U.S. The goal of this study was to identify differentially methylated CpG sites and genes between clinically defined aggressive and nonaggressive PCa in African Americans. We performed genome-wide DNA methylation profiling in leukocyte DNA from 280 African American PCa patients using Illumina MethylationEPIC array that contains about 860K CpG sties. There was a slight increase of overall methylation level (mean β value) with the increasing Gleason scores (GS = 6, GS = 7, GS ≥ 8, P for trend = 0.002). There were 78 differentially methylated CpG sites with P < 10-4 and 9 sites with P < 10-5 in the trend test. We also found 77 differentially methylated regions/genes (DMRs), including 10 homeobox genes and six zinc finger protein genes. A gene ontology (GO) molecular pathway enrichment analysis of these 77 DMRs found that the main enriched pathway was DNA-binding transcriptional factor activity. A few representative DMRs include HOXD8, SOX11, ZNF-471, and ZNF-577. Our study suggests that leukocyte DNA methylation may be valuable biomarkers for aggressive PCa and the identified differentially methylated genes provide biological insights into the modulation of immune response by aggressive PCa.

Peripheral Blood-Based DNA Methylation of Long Non-Coding RNA H19 and Metastasis-Associated Lung Adenocarcinoma Transcript 1 Promoters are Potential Non-Invasive Biomarkers for Gastric Cancer Detection

Introduction

The early diagnosis and detection could greatly improve the clinical outcome of gastric cancer (GC) patients. However, the non-invasive biomarkers for GC detection remain to be identified.

Method

We used online databases (GEPIA, UALCAN, Kaplan-Meier plotter, TIMER, and MEXPRESS) to explore the association between H19 or metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) expression in tissues and the occurrence, development, prognosis, the levels of immune cell infiltration, and methylation of GC; the correlation between mRNA expression and DNA methylation levels of genes were also examined. Methylation levels of H19 or MALAT1 in peripheral blood were compared between 150 GC patients and 100 healthy controls (HCs). Predictive nomograms were constructed among female and male groups for GC diagnosis. The calibration curves, Hosmer–Lemeshow test, and decision curve analysis were also used to examine the nomograms’ predictive ability and clinical values.

Results

Using multiple online databases, we found that the mRNA expressions of H19 and MALAT1 in tissues were related to the occurrence of GC, and such expressions were associated with immune cell infiltration of GC and negatively correlated with DNA methylation levels of H19 and MALAT1. H19 gene, H19C island, and MALAT1B island, as well as 20 CpG sites were hypermethylated in peripheral blood of GC patients compared with HCs; similar results were also found in female and male groups (P < .05 for all). The combination of H19c3, H19c4, MALAT1b12, and age, as well as the combination of H19b7, H19c1, H19c5, and age in the nomograms could distinguish GC patients from HCs in the female group and male group, respectively.

Conclusion

We found statistically significant hypermethylation of H19 and MALAT1 promoters in GC patients, and meaningful sensitivity and specificity of MALAT1 and H19 methylation in discriminating GC and HCs were observed in both female and male groups, which indicates that the peripheral blood-based DNA methylation of H19 and MALAT1 could act as potential non-invasive biomarkers for the diagnosis of GC.

Associations of BNIP3 and DAPK1 gene polymorphisms with disease susceptibility, clinicopathologic features, anxiety, and depression in gastric cancer patients

The purpose of this study is to explore the associations of BNIP3 and DAPK1 polymorphisms with disease susceptibility, clinicopathologic characteristics, depression, and anxiety in gastric cancer (GC) patients. In this study, 150 GC patients and 100 healthy controls were recruited. 1000 Genomes database and Haploview 4.0 software were used to select tag SNPs. Improved multiplex ligase detection reaction was used for genotyping. Data were analyzed using Chi-square test (χ² test) and univariate and multivariate logistic regression. The results demonstrated that the rs10781582 of BNIP3 in the dominant model was associated with a reduced risk of GC in the younger group (P _BH = 0.015), and the minor allele G of rs1329600 at DAPK1 was associated with reduced risk of GC (P _BH = 0.018). In the stratified analysis, the rs3793742 and rs10781582 of BNIP3 in the dominant model were associated with gender and age of GC patients, respectively (rs3793742: P _BH = 0.033; rs10781582: P _BH = 0.030). The rs10781582 of BNIP3 in the dominant model was correlated with depression in GC patients (P _BH = 0.003). However, no association was found between BNIP3 and DAPK1 polymorphisms and differentiation degree, TNM stage, lymph node metastases, visceral metastasis, and anxiety. In summary, polymorphisms of BNIP3 and DAPK1 were associated with a protective effect against GC. So far, this is the first study to explore the association between BNIP3 and DAPK1 gene polymorphism and GC risk, which may provide new insight about biologic mechanisms of GC pathogenesis.

Association of ZNF331 and WIF1 methylation in peripheral blood leukocytes with the risk and prognosis of gastric cancer

Background

Peripheral blood leukocyte (PBL) DNA methylation may serve as a surrogate marker to evaluate the susceptibility to and prognosis of gastric cancer (GC). In this study, blood-derived DNA methylation levels of two tumour-related genes, namely, ZNF331 and WIF1, and their impacts on the risk and prognosis of GC were evaluated.

Methods

In total, 398 GC cases and 397 controls were recruited for the study. Then, all cases were followed up for 5 years. ZNF331 and WIF1 promoter methylation status in PBLs was measured using a methylation-sensitive high-resolution melting method. Logistic and Cox regression models were used to analyse the correlation between gene methylation and the risk and prognosis of GC. Confounders were balanced through propensity score (PS) matching.

Results

High ZNF331 methylation significantly decreased GC risk after PS adjustment (OR = 0.580, 95% CI: 0.375–0.898, P = 0.015), which also presented in males (OR = 0.577, 95% CI: 0.343–0.970, P = 0.038). However, WIF1 methylation was not associated with GC risk. Additionally, significant combined effects between ZNF331 methylation and the intake of green vegetables and garlic were observed (OR = 0.073, 95% CI: 0.027–0.196, P < 0.001 and OR = 0.138, 95% CI: 0.080–0.238, P < 0.001, respectively). Furthermore, ZNF331 and WIF1 methylation had no impact on the prognosis of GC.

Conclusion

ZNF331 methylation in PBLs may affect GC risk in combination with the consumption of green vegetables and garlic and may act as a potential biomarker of GC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08199-4.

The role of SOX family transcription factors in gastric cancer

Gastric cancer (GC) is a leading cause of death worldwide. GC is the third-most common cause of cancer-related death after lung and colorectal cancer. It is also the fifth-most commonly diagnosed cancer. Accumulating evidence has revealed the role of signaling networks in GC progression. Identification of these molecular pathways can provide new insight into therapeutic approaches for GC. Several molecular factors involved in GC can play both onco-suppressor and oncogene roles. Sex-determining region Y (Sry)-box-containing (SOX) family members are transcription factors with a well-known role in cancer. SOX proteins can bind to DNA to regulate cellular pathways via a highly conserved domain known as high mobility group (HMG). In the present review, the roles of SOX proteins in the progression and/or inhibition of GC are discussed. The dual role of SOX proteins as tumor-promoting and tumor-suppressing factors is highlighted. SOX members can affect upstream mediators (microRNAs, long non-coding RNAs and NF-κB) and down-stream mediators (FAK, HIF-1α, CDX2 and PTEN) in GC. The possible role of anti-tumor compounds to target SOX pathway members in GC therapy is described. Moreover, SOX proteins may be used as diagnostic or prognostic biomarkers in GC.

Discovery of novel DNA methylation biomarkers for non-invasive sporadic breast cancer detection in the Latino population

Human diversity is one of the main pitfalls in the development of robust worldwide biomarkers in oncology. Epigenetic variability across human populations is associated with different genetic backgrounds, as well as variable lifestyles and environmental exposures, each of which should be investigated. To identify potential non-invasive biomarkers of sporadic breast cancer in the Uruguayan population, we studied genome-wide DNA methylation using Illumina methylation arrays in leukocytes of 22 women with sporadic breast cancer and 10 healthy women in a case-control study. We described a panel of 38 differentially methylated CpG positions that was able to cluster breast cancer patients (BCP) and controls, and that also recapitulated methylation differences in 12 primary breast tumors and their matched normal breast tissue. Moving forward, we simplified the detection method to improve its applicability in a clinical setting and used an independent well-characterized cohort of 80 leukocyte DNA samples from BCP and 80 healthy controls to validate methylation results at specific cancer-related genes. Our investigations identified methylation at CYFIP1 as a novel epigenetic biomarker candidate for sporadic breast cancer in the Uruguayan population. These results provide a proof-of-concept for the design of larger studies aimed at validating biomarker panels for the Latin American population.

A predictive model for assessing prognostic risks in gastric cancer patients using gene expression and methylation data

BACKGROUND

The role(s) of epigenetic reprogramming in gastric cancer (GC) remain obscure. This study was designed to identify methylated gene markers with prognostic potential for GC.

METHODS

Five datasets containing gene expression and methylation profiles from GC samples were collected from the GEO database, and subjected to meta-analysis. All five datasets were subjected to quality control and then differentially expressed genes (DEGs) and differentially expressed methylation genes (DEMGs) were selected using MetaDE. Correlations between gene expression and methylation status were analysed using Pearson coefficient correlation. Then, enrichment analyses were conducted to identify signature genes that were significantly different at both the gene expression and methylation levels. Cox regression analyses were performed to identify clinical factors and these were combined with the signature genes to create a prognosis-related predictive model. This model was then evaluated for predictive accuracy and then validated using a validation dataset.

RESULTS

This study identified 1565 DEGs and 3754 DEMGs in total. Of these, 369 were differentially expressed at both the gene and methylation levels. We identified 12 signature genes including VEGFC, FBP1, NR3C1, NFE2L2, and DFNA5 which were combined with the clinical data to produce a novel prognostic model for GC. This model could effectively split GC patients into two groups, high- and low-risk with these observations being confirmed in the validation dataset.

CONCLUSION

The differential methylation of the 12 signature genes, including VEGFC, FBP1, NR3C1, NFE2L2, and DFNA5, identified in this study may help to produce a functional predictive model for evaluating GC prognosis in clinical samples.

From Anti-EBV Immune Responses to the EBV Diseasome via Cross-reactivity

Sequence analyses highlight a massive peptide sharing between immunoreactive Epstein-Barr virus (EBV) epitopes and human proteins that—when mutated, deficient or improperly functioning—associate with tumorigenesis, diabetes, lupus, multiple sclerosis, rheumatoid arthritis, and immunodeficiencies, among others. Peptide commonality appears to be the molecular platform capable of linking EBV infection to the vast EBV-associated diseasome via cross-reactivity and questions the hypothesis of the “negative selection” of self-reactive lymphocytes. Of utmost importance, this study warns that using entire antigens in anti-EBV immunotherapies can associate with autoimmune manifestations and further supports the concept of peptide uniqueness for designing safe and effective anti-EBV immunotherapies.

A panel of DNA methylation signature from peripheral blood may predict colorectal cancer susceptibility

Background

Differential DNA methylation panel derived from peripheral blood could serve as biomarkers of CRC susceptibility. However, most of the previous studies utilized post-diagnostic blood DNA which may be markers of disease rather than susceptibility. In addition, only a few studies have evaluated the predictive potential of differential DNA methylation in CRC in a prospective cohort and on a genome-wide basis. The aim of this study was to identify a potential panel of DNA methylation biomarkers in peripheral blood that is associated with CRC risk and therefore serve as epigenetic biomarkers of disease susceptibility.

Methods

DNA methylation profile of a nested case-control study with 166 CRC and 424 healthy normal subjects were obtained from the Gene Expression Omnibus (GEO) database. The differentially methylated markers were identified by moderated t-statistics. The DNA methylation panel was constructed by stepwise logistic regression and the least absolute shrinkage and selection operator in the training dataset. A methylation risk score (MRS) model was constructed and the association between MRS and CRC risk assessed.

Results

We identified 48 differentially methylated CpGs sites, of which 33 were hypomethylated. Of these, sixteen-CpG based MRS that was associated with CRC risk (OR = 2.68, 95% CI: 2.13, 3.38, P <  0.0001) was constructed. This association is confirmed in the testing dataset (OR = 2.02, 95% CI: 1.48, 2.74, P <  0.0001) and persisted in both males and females, younger and older subjects, short and long time-to-diagnosis. The MRS also predicted CRC with AUC 0.82 (95% CI: 0.76, 0.88), indicating high accuracy.

Conclusions

Our study has identified a novel DNA methylation panel that is associated with CRC and could, if validated be useful for the prediction of CRC risk in the future.

Rapid screening of MMACHC gene mutations by high-resolution melting curve analysis

Background

Cobalamin (cbl) C is a treatable rare hereditary disorder of cbl metabolism with autosomal recessive inheritance. It is the most common organic acidemia, manifested as methylmalonic academia combined with homocysteinemia. Early screening and diagnosis are important. The mutation spectrum of the MMACHC gene causing cblC varies among populations. The mutation spectrum in Chinese population is notably different from that in other populations.

Methods

A PCR followed by high‐resolution melting curve analysis (PCR‐HRM) method covering all coding exons of MMACHC gene was designed to verify 14 pathogenic MMACHC gene variants found in patients with cblC, including all common mutations in Chinese patients with cblC.

Result

By PCR‐HRM analysis, 14 pathogenic variants of MMACHC showed distinctly different melting curves, which were consistent with Sanger sequencing. The homozygous type of the most common mutation c.609G > A (p.Trp203Ter) can also be analyzed by specially designed PCR‐HRM.

Conclusion

The established PCR‐HRM method for screening common pathogenic MMACHC variants in Chinese patients with cblC has the advantages of high accuracy, high throughput, low cost, and high speed. It is suitable for the large‐sample screening of suspected children with methylmalonic acidemia and carriers in population.

Combined effect between WT1 methylation and Helicobacter pylori infection, smoking, and alcohol consumption on the risk of gastric cancer

BACKGROUND

Peripheral blood leukocyte DNA methylation status has been proposed to be a surrogate marker for evaluating susceptibility to gastric cancer (GC). Helicobacter pylori (H pylori) infection, smoking, and alcohol consumption are known to induce gene methylation. A case-control study was performed to investigate the interactions between the methylation of two candidate genes and H pylori infection, smoking, and alcohol consumption in the risk of GC.

METHODS

A total of 400 GC cases and 402 controls were included in this study. The methylation status of WT1 and IGF2 was semiquantitatively determined by using methylation-sensitive high-resolution melting assays. H pylori IgG antibodies were detected by ELISA method.

RESULTS

Based on the area under the curve (AUC), 0% methylated DNA and 0.5% methylated DNA were used as the cutoff values for WT1 and IGF2, respectively. WT1 methylation was significantly associated with increased GC risk (OR = 1.65, 95% CI = 1.09-2.51, P = .019), especially in males (OR = 1.80, 95% CI: 1.10-2.95, P = .019) and older individuals (≥60 years) (OR = 2.03, 95% CI: 1.15-3.57, P = .014). A significant combination was observed between WT1 methylation and H pylori infection, alcohol consumption, and smoking for the risk of GC (OR_c  = 2.28, 95% CI = 1.47-3.55, P = .003, OR_c  = 2.19, 95% CI = 1.37-3.51, P = .001, OR_c  = 2.21, 95% CI = 1.39-3.51, P = .001, respectively). However, no association between IGF2 methylation and the risk of GC was found in this study.

CONCLUSIONS

WT1 methylation may serve as a new potential biomarker for GC susceptibility and can combine with H pylori infection, smoking, and alcohol consumption to influence GC risk.

Incorporating molecular biomarkers into clinical practice for gastric cancer

Introduction: Gastric cancer is one of the most common causes of cancer-related mortality worldwide. To improve clinical outcomes, it is critical to develop appropriate approaches to diagnosis and treatment. Biomarkers have numerous potential clinical applications, including screening, assessing risk, determining prognosis, monitoring recurrence, and predicting response to treatment. Furthermore, biomarkers may contribute to the development of effective therapies. Areas covered: Here we review recent progress in exploiting GC-specific biomarkers such as protein-coding genes, microRNAs, long noncoding RNAs, and methylated gene promoters. Expert opinion: The development of biomarkers for diagnosing and monitoring gastric cancer and for individualizing therapeutic targets shows great promise for improving gastric cancer management.

SOX11 hypermethylation as a tumor biomarker in endometrial cancer

We previously reported that SOX4 is overexpressed in endometrial cancer and that it partially contributes to hypermethylation of miR-129-2 and miR-203. The current study seeks to identify methylation and expression levels of the SOX gene family in endometrial carcinomas. Methylation levels of the 16 SOX gene family members were measured by combining bisulfite restriction analysis (COBRA), MassARRAY, and pyrosequencing assays of cell lines and endometrial cancer samples. Gene expression was determined by RT-qPCR. The methylation level of the SOX11 locus was correlated with clinicopathologic factors in primary endometrial tumors and in TCGA endometrial cohort. It was also examined in DNA of serum and endometrial specimens from a longitudinal cohort of early stage endometrial cancer patients. COBRA assays indicated that hypermethylation of SOX1, SOX2, SOX11, SOX14, SOX15, SOX17, and SOX18 was present in endometrial cancer cell lines and not in the normal control. SOX11 expression was reactivated only by a DNA methylation inhibitor. Moreover, aberrant DNA methylation of SOX11 was detected in the majority of endometrioid endometrial carcinomas (n=114) and none of the 22 adjacent normal endometrial samples (P<0.0001). The methylation status of SOX11 associated significantly with microsatellite instability and MLH1 methylation in endometrial tumors (P<0.0001), and this finding was validated in TCGA endometrial cohort. Furthermore, SOX11 was not hypermethylated in serum DNA from early stage endometrial cancer patients. This study found that hypermethylation of SOX11 is common in endometrial carcinomas and strongly associates with microsatellite instability and MLH1 methylation.