Expression level and methylation status of three tumor suppressor genes, DLEC1, ITGA9 and MLH1, in non-small cell lung cancer

Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory

OBJECTIVE

Invasive lung cancer staging poses significant challenges, often requiring painful and costly biopsy procedures. This study aims to identify non-invasive biomarkers for detecting bronchogenic carcinoma and its various stages by analyzing gene expression data using bioinformatics and machine learning techniques. By leveraging these advanced computational methods, we seek to eliminate the need for surgical intervention in the diagnostic process.

METHODS

We utilized the TCGA-LUAD dataset, including gene expression data from healthy and cancerous samples. To identify robust biomarkers, we applied eight metaheuristic algorithms for feature selection, combined with four classification methods and two data fusion techniques to optimize performance.

RESULTS

Our approach achieved 100% accuracy in distinguishing healthy samples from cancerous ones, outperforming existing methods that reported 97% accuracy. Notably, while prior methods have struggled to separate bronchogenic carcinoma stages effectively, our research achieved an approximate accuracy of 77% in stage classification. Furthermore, using gene enrichment methods, we identified 5, 7, and 16 diagnostic biomarker candidates for stages I, II, III, and IV, respectively.

CONCLUSION

This study demonstrates that integrating bioinformatics, gene set enrichment, and biological pathway analysis can enable non-invasive diagnostics for bronchogenic carcinoma stages. These findings hold promise for developing alternatives to traditional, invasive staging systems, potentially improving patient outcomes and reducing healthcare costs.

Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome

Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration. Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA-LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling. Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype. Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC.

Deep-LC: A Novel Deep Learning Method of Identifying Non-Small Cell Lung Cancer-Related Genes

According to statistics, lung cancer kills 1.8 million people each year and is the main cause of cancer mortality worldwide. Non-small cell lung cancer (NSCLC) accounts for over 85% of all lung cancers. Lung cancer has a strong genetic predisposition, demonstrating that the susceptibility and survival of lung cancer are related to specific genes. Genome-wide association studies (GWASs) and next-generation sequencing have been used to discover genes related to NSCLC. However, many studies ignored the intricate interaction information between gene pairs. In the paper, we proposed a novel deep learning method named Deep-LC for predicting NSCLC-related genes. First, we built a gene interaction network and used graph convolutional networks (GCNs) to extract features of genes and interactions between gene pairs. Then a simple convolutional neural network (CNN) module is used as the decoder to decide whether the gene is related to the disease. Deep-LC is an end-to-end method, and from the evaluation results, we can conclude that Deep-LC performs well in mining potential NSCLC-related genes and performs better than existing state-of-the-art methods.

ITGA9: Potential Biomarkers and Therapeutic Targets in Different Tumors

Abstract:

Integrins are a class of a cell surface adhesion molecule which composed of α subunit (ITGA) and β subunit (ITGB). They belong to heterodimer transmembrane glycoproteins. Its main function in organisms is as the receptor of cell adhesion molecules (CAMs) and extracellular matrix (ECM). According to the current research integration analysis, integrin α9 (ITGA9) is one of the integrin subunits, and there are few studies on ITGA9 among integrins. ITGA9 can improve cell migration and regulate various cellular biological functions, such as tumor cell proliferation, adhesion, invasion, and angiogenesis. But its abnormal expression mechanism in cancer and its specific role in tumor growth and metastasis are still unknown to a great extent. This review reveals the role of ITGA9 in the complex pathogenesis of many tumors and cancers, providing a new direction for the treatment of tumors and cancers. Relevant studies were retrieved and collected through the PubMed system. After determining ITGA9 as the research object, we found the close relationship between ITGA9 and tumorigenesis through the analysis of the research articles on ITGA9 in the PubMed system in the last 15 years, and further determined the references mainly based on the influencing factors of the articles. Thus, the role of ITGA9 in tumor and cancer genesis, proliferation, and metastasis was reviewed and analyzed. ITGA9 is an integrin subunit, which has been proved to be abnormally expressed in many tumors. After sorting and analyzing the research data, it was found that the abnormal expression of ITGA9 in a variety of tumors, including glioblastoma, rhabdomyosarcoma, melanoma, hepatocellular carcinoma, nasopharyngeal carcinoma, multiple myeloma, non-small cell lung cancer, and prostate cancer, was closely related to the proliferation, metastasis, adhesion, and angiogenesis of tumor cells. These results suggest that ITGA9 plays an important role in the occurrence and development of tumors. The integrin subunit ITGA9 may serve as a biomarker for the diagnosis of tumors and a potential therapeutic target for anti-tumor therapies.

TMT-based proteomic analysis reveals integrins involved in the synergistic infection of reticuloendotheliosis virus and avian leukosis virus subgroup J

BACKGROUND

Co-infection with the avian leukosis virus subgroup J (ALV-J) and the reticuloendotheliosis virus (REV) increases mutual viral replication, causing a more serious pathogenic effect by accelerating the progression of neoplasia and extending the tumor spectrum. However, the molecular mechanism underlying the synergistic replication of ALV-J and REV remains unclear.

RESULTS

Here, we performed this study to compare the differentially expressed proteins among CEF cells infected with ALV-J, REV or both at the optimal synergistic infection time using TMT-based quantitative proteomics. We identified a total of 719 (292 upregulated and 427 downregulated) and 64 (35 upregulated and 29 downregulated) proteins by comparing co-infecting both viruses with monoinfecting ALV-J and REV, respectively. GO annotation and KEGG pathway analysis showed the differentially expressed proteins participated in virus-vector interaction, biological adhesion and immune response pathways in the synergistic actions of ALV-J and REV at the protein levels. Among the differentially expressed proteins, a large number of integrins were inhibited or increased in the co-infection group. Further, eight integrins, including ITGα1, ITGα3, ITGα5, ITGα6, ITGα8, ITGα9, ITGα11 and ITGβ3, were validated in CEF cells by qRT-PCR or western blot.

CONCLUSIONS

These findings proved that integrins may be key regulators in the mechanism of synergistic infection of REV and ALV-J, which will provide more insight into the pathogenesis of synergism of REV and ALV-J at protein level.

Association study of hypertension susceptibility genes ITGA9, MOV10, and CACNB2 with preeclampsia in Chinese Han population

OBJECTIVE

Preeclampsia (PE) is a disorder that occurs during the pregnancy and could affect the maternal and perinatal mortality as well as morbidity. The aim of our study is to investigate the associations between the hypertension susceptibility genes ITGA9, MOV10 and CACNB2 with PE in Chinese Han population.

METHODS

A case-control study including 178 PE patients and 202 healthy controls was conducted to assess the associations between three loci (ITGA9 rs155524, MOV10 rs2932538 and CACNB2 rs4373814) and PE. The TaqMan probe assay was applied for genotyping in our study. Quantitative real-time PCR was performed to detect the mRNA expression levels of ITGA9, MOV10 and CACNB2. ELISA was carried out to detect the concentration of serum sFlt-1 or PLGF.

RESULTS

Our study detected no significant differences in allelic frequencies of three SNPs between PE patients and healthy controls. In the genetic model, the results showed that the patients with ITGA9 rs155524 GA or AA genotypes had a higher risk of PE development compared to those with GG genotype in codominant model. And PE patients had a higher frequency of GA + AA genotypes based on the dominant model. Subgroup analysis showed ITGA9 rs155524 was associated with early-onset PE but not with late-onset PE. No association was observed between MOV10 and CACNB2 with PE in any genetic model and subgroup analysis. Quantitative real-time PCR results showed that ITGA9 mRNA expression level was apparently increased in the placental tissues of PE patients. In addition, ITGA9 expression levels of GA + AA subjects were apparently higher than that in the genotype GG of placental tissues. sFlt-1/PLGF ratio was higher in GA + AA subjects than that in GG subjects. Regression analysis revealed that ratio of sFlt-1/PLGF was positively correlated with ITGA9 mRNA expression level.

CONCLUSION

This study has identified ITGA9 is a promising candidate susceptibility gene for early-onset PE. Our findings demonstrated that the high expression of ITGA9 might be associated with an increased risk of PE.

PM2.5 exposure and DLEC1 promoter methylation in Taiwan Biobank participants

BACKGROUND

Particulate matter (PM) < 2.5 μm (PM2.5) or fine PM is a serious public health concern. It affects DNA methylation and heightens carcinogenesis. Deleted in lung and esophageal cancer 1 (DLEC1) is a tumor suppressor gene. However, aberrant methylation of the gene is associated with several cancers. We evaluated the association between PM2.5 and DLEC1 promoter methylation in Taiwanese adults based on regular outdoor exercise.

METHODS

We obtained DNA methylation and exercise data of 496 participants (aged between 30 and 70 years) from the Taiwan Biobank (TWB) database. We also extracted PM2.5 data from the Air Quality Monitoring Database (AQMD) and estimated participants' exposure using residential addresses.

RESULTS

DLEC1 methylation and PM2.5 were positively associated: beta coefficient (β) = 0.114 × 10-3; p value = 0.046. The test for interaction between exercise and PM2.5 on DLEC1 methylation was significant (p value = 0.036). After stratification by exercise habits, PM2.5 and DLEC1 methylation remained significantly associated only among those who exercised regularly (β = 0.237 × 10-3; p value = 0.007). PM2.5 quartile-stratified analyses revealed an inverse association between regular exercise and DLEC1 methylation at PM2.5 < 27.37 μg/m3 (β = - 5.280 × 10-3; p value = 0.009). After combining exercise habits and PM2.5 quartiles, one stratum (i.e., regular exercise and PM2.5 < 27.37 μg/m3) was inversely associated with DLEC1 methylation (β = -5.160 × 10-3, p value = 0.007).

CONCLUSIONS

We found significant positive associations between PM2.5 and DLEC1 promoter methylation. Regular exercise at PM2.5 < 27.37 μg/m3 seemingly regulated DLEC1 promoter methylation.

Possible involvement of TGF‑β‑SMAD‑mediated epithelial‑mesenchymal transition in pro‑metastatic property of PAX6

Paired box 6 (PAX6) is a transcription factor that has oncogenic features. In breast cancer, PAX6 facilitates tumor progression; however, the underlying mechanism is largely unknown. The majority of breast cancer-related mortalities are associated with metastasis of cancer cells. Therefore, the present study aimed to investigate the role of PAX6 in breast tumor metastasis. PAX6 was stably overexpressed in breast cancer cells to perform tumor migration and metastasis assays in vitro and in vivo. In addition, the expression of PAX6 and transforming growth factor β (TGF-β)-SMAD signaling associated proteins on human breast cancer tissue array, as well as key factors involved in epithelial-mesenchymal transition (EMT) were assayed to explore the mechanism underlying metastasis of breast cancer cells. The expression levels of PAX6 were demonstrated to be increased in human breast cancer tissues and associated with poor clinical outcomes. Overexpression of PAX6 markedly promoted metastasis. Further investigation revealed that PAX6 overexpression increased TGF-β-SMAD signaling pathway and induced EMT. These results suggested that highly expressed PAX6 led to EMT through TGF-β-SMAD signaling pathway, thereby promoting cell metastasis and ultimately affecting survival in patients with breast cancer. Taken together, findings indicated that PAX6 may serve as a therapeutic target for the clinical treatment of breast cancer and the underlying mechanism could be used to overcome metastasis of cancer cells.

Relationship between DLEC1 and PBX3 promoter methylation and the risk and prognosis of gastric cancer in peripheral blood leukocytes

PURPOSE

Aberrant DNA methylation could regulate the expression of tumor suppressor gene DLEC1 and oncogene PBX3 and was related to the occurrence and prognosis of gastric cancer (GC). In this study, the associations between DLEC1 and PBX3 promoter methylation in peripheral blood leukocytes (PBLs) and the risk and prognosis of GC were investigated.

METHODS

The methylation status of DLEC1 and PBX3 promoter in PBLs of 368 GC cases and 382 controls was detected by the methylation-sensitive high-resolution melting (MS-HRM) method. Logistic and Cox regression were adopted to analyze the associations of DLEC1 and PBX3 methylation with GC risk and prognosis, respectively. Confounding biases were controlled by propensity score (PS).

RESULTS

Compared with negative methylation (Nm), DLEC1-positive methylation (Pm) was associated with increased GC risk in PS (OR 2.083, 95% CI 1.220-3.558, P = 0.007), but PBX3 Pm was not associated with GC risk. In the elderly group (≥ 60 years), DLEC1 Pm was associated with increased GC risk (OR 2.951, 95% CI 1.426-6.104, P = 0.004). The combined effects between DLEC1 methylation and consumption of dairy products, fried food intake and Helicobacter pylori (H. pylori) infection on GC risk were discovered (ORc 3.461, 95% CI 1.847-6.486, P < 0.001, ORc 3.246, 95% CI 1.708-6.170, P < 0.001 and ORc 2.964, 95% CI 1.690-5.197, P < 0.001, respectively). Furthermore, DLEC1 and PBX3 methylation were not associated with GC prognosis.

CONCLUSION

DLEC1 methylation in PBLs and the combined effects of gene-environment can influence GC risk.

Different methylation levels in the KLF4, ATF3 and DLEC1 genes in the myometrium and in corpus uteri mesenchymal tumours as assessed by MS-HRM

Mesenchymal tumours of the corpus uteri comprise common benign lesions - leiomyomas and very rare malignant variants - sarcomas. It can be difficult to distinguish between the particular types of mesenchymal tumours pre-surgically. Primarily, leiomyomas and the very aggressive leiomyosarcomas can be easily misdiagnosed when using only imaging devices. Therefore, a reliable non-invasive marker for these tumour types would provide greater certitude for patients that the lesion remains benign. Our collection comprises 76 native leiomyomas, an equal number of healthy myometrium samples and 49 FFPE samples of various types of sarcomas. The methylation level was assessed by MS-HRM method and we observed differences in the methylation level between healthy, benign and (semi)malignant tissues in the KLF4 and DLEC1 genes. The mean methylation levels of leiomyomas compared to myometrium and leiomyosarcomas were 70.7% vs. 6.5% vs. 39.6 % (KLF4) and 66.1% vs. 14.08% vs. 37.5% (DLEC1). The ATF3 gene was differentially methylated in leiomyomatous and myometrial tissues with 98.1% compared to 76.6%. The AUC values of the predictive logistic regression model for discrimination between leiomyomas and leiomyosarcomas based on methylation levels were 0.7829 (KLF4) and 0.7719 (DLEC1). Finally, our results suggest that there should be distinct models for the methylation events in benign leiomyomas and sarcomas, and that the KLF4 and DLEC1 genes can be considered potential methylation biomarkers for uterine leiomyomas.

DNA repair as an emerging target for COPD-lung cancer overlap

Cigarette smoking is the leading cause of lung cancer and chronic obstructive pulmonary disease (COPD). Many of the detrimental effects of cigarette smoke have been attributed to the development of DNA damage, either directly from chemicals contained in cigarette smoke or as a product of cigarette smoke-induced inflammation and oxidative stress. In this review, we discuss the environmental, epidemiological, and physiological links between COPD and lung cancer and the likely role of DNA damage and repair in COPD and lung cancer development. We explore alterations in DNA damage repair by DNA repair proteins and pathways. We discuss emerging data supporting a key role for the DNA repair protein, xeroderma pigmentosum group C (XPC), in cigarette smoke-induced COPD and early lung cancer development. Understanding the interplay between cigarette smoke, DNA damage repair, COPD, and lung cancer may lead to prognostic tools and new, potentially targetable, pathways for lung cancer prevention and treatment.

CDH1, DLEC1 and SFRP5 methylation panel as a prognostic marker for advanced epithelial ovarian cancer

AIM

To investigate the CDH1, DLEC1 and SFRP5 gene methylation panel for advanced epithelial ovarian carcinoma (EOC).

MATERIALS & METHODS

One hundred and seventy-seven advanced EOC specimens were evaluated by methylation-specific PCR. We also used The Cancer Genome Atlas dataset to evaluate the panel.

RESULTS

The presence of two or more methylated genes was significant in recurrence (hazard ratio [HR]: 1.91 [1.33-2.76]; p = 0.002) and death (HR: 1.96 [1.26-3.06]; p = 0.006) in our cohort. In The Cancer Genome Atlas dataset, the presence of two or three methylated genes was significant in death (HR: 1.59 [1.15-2.18]; p = 0.0047) and close to the significance level in recurrence (HR: 1.37 [0.99-1.88]; p = 0.058).

CONCLUSION

The CDH1, DLEC1 and SFRP5 methylation panel is a potential prognostic biomarker for advanced EOC.

MLH1 Promoter Methylation and Prediction/Prognosis of Gastric Cancer: A Systematic Review and Meta and Bioinformatic Analysis

Background: The promoter methylation of MLH1 gene and gastric cancer (GC)has been investigated previously. To get a more credible conclusion, we performed a systematic review and meta and bioinformatic analysis to clarify the role of MLH1 methylation in the prediction and prognosis of GC.

Methods: Eligible studies were targeted after searching the PubMed, Web of Science, Embase, BIOSIS, CNKI and Wanfang Data to collect the information of MLH1 methylation and GC. The link strength between the two was estimated by odds ratio with its 95% confidence interval. The Newcastle-Ottawa scale was used for quantity assessment. Subgroup and sensitivity analysis were conducted to explore sources of heterogeneity. The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were employed for bioinformatics analysis on the correlation between MLH1 methylation and GC risk, clinicopathological behavior as well as prognosis.

Results: 2365 GC and 1563 controls were included in the meta-analysis. The pooled OR of MLH1 methylation in GC was 4.895 (95% CI: 3.149-7.611, P<0.001), which considerably associated with increased GC risk. No significant difference was found in relation to Lauren classification, tumor invasion, lymph node/distant metastasis and tumor stage in GC. Analysis based on GEO and TCGA showed that high MLH1 methylation enhanced GC risk but might not related with GC clinicopathological features and prognosis.

Conclusion:MLH1 methylation is an alive biomarker for the prediction of GC and it might not affect GC behavior. Further study could be conducted to verify the impact of MLH1 methylation on GC prognosis.

Small suitability of the DLEC1, MLH1 and TUSC4 mRNA expression analysis as potential prognostic or differentiating markers for NSCLC patients in the Polish population

According to the latest data, lung cancer is one of the most common cancer worldwide, men contributing nearly 21.2% and women 8.6% of all diagnosed cancers. Late detection of tumour drastically reduces the chance for a cure. Thus, it is important to search for candidate biomarkers for screening of early stage nonsmall cell lung carcinoma (NSCLC). Tumour suppressor genes, DLEC1, TUSC4 and MLH1, localized on 3p21 are recognized to play a role in NSCLC carcinogenesis. The aim of this study was to assess the relationship between the DLEC1, TUSC4 and MLH1 mRNA expression, and clinical features of NSCLC patients, tobacco addiction, and tumour histopathological characteristics. The DLEC1, TUSC4 and MLH1 expression was analysed in lung tumour tissue samples obtained from 69 patients diagnosed with NSCLC: squamous cell carcinoma (n = 34), adenocarcinoma (n = 24), large cell carcinoma (n = 5), carcinoma adenosquamosum (n = 5). A decreased gene expression (RQ < 0.7) was observed for DLEC1 in 60.9% of tumour samples, for MLH1 in 50.7% and for TUSC4 in 26% of NSCLC samples. DLEC1 was decreased in more aggressive subtypes: large cell carcinoma and adenocarcinoma-squamous cell carcinoma. The simultaneous downregulation of two of the studied genes, DLEC1 andMLH1,was observed in 30.4% of NSCLCsamples, highlighting the importance of these two genes in lung carcinogenesis. We found no correlation between the DLEC1, TUSC4 and MLH1 gene expression and NSCLC patient characteristics (gender, age and smoking) or cancer histopathology. No significant differences in the gene expression among NSCLC subtypes indicate the weakness of DLEC1, TUSC4 and MLH1 expression analysis as potential differentiating markers of NSCLC subtypes in the Polish population.

Integrative analysis of mRNA and lncRNA profiles identified pathogenetic lncRNAs in esophageal squamous cell carcinoma

Systems biology approaches can help understand pathogenesis of complex human diseases like cancers for identification of potential new therapeutic targets. Here in this study, we performed genome-wide screening for mRNA and lncRNA profiles in esophageal cancer to identify the novel cancer-related mRNA and lncRNA in esophageal squamous cell carcinoma (ESCC). We identified 1260 up-regulated/1445 down-regulated mRNAs and 402 up-regulated/741 down-regulated lncRNAs. Further functional analysis revealed differentially expressed genes (DEGs) of mRNA and lncRNA are related to different pathways. mRNA pathways are mainly involved in cell cycles while lncRNA pathways are for regulation and metabolic procession. Differentially expressed mRNAs/lncRNAs were validated with qPCR. At last, mRNA and lncRNA co-expression network were built and highly-connected networks were identified, which may provide a mechanism of mRNA expression regulation by lncRNA. In together, we used next generation sequencing data to explore the co-expression networks of lncRNA and mRNA, which may elucidate the functions and mechanisms of lncRNA in ESCC.

Sulforaphane epigenetically demethylates the CpG sites of the miR-9-3 promoter and reactivates miR-9-3 expression in human lung cancer A549 cells

Increasing evidence suggests that epigenetic aberrations contribute to the development and progression of cancers such as lung cancer. The promoter region of miR-9-3 was recently found to be hypermethylated in lung cancer, resulting in down-regulation of miR-9-3 and poor patient prognosis. Sulforaphane (SFN), a natural compound that is obtained from cruciferous vegetables, has potent anticancer activities. In this study, we aimed to investigate the effect of SFN on restoring the miR-9-3 level in lung cancer A549 cells through epigenetic regulation. DNA methylation of the miR-9-3 promoter was examined using bisulfite genomic sequencing and methylated DNA immunoprecipitation analysis. The expression levels of miR-9-3 and several epigenetic modifying enzymes were measured using quantitative real-time polymerase chain reaction and Western blotting, respectively. The transcriptional activity of the miR-9-3 promoter was evaluated by patch methylation, and histone modifications were analyzed using chromatin immunoprecipitation (ChIP) assays. We found that CpG methylation was reduced in the miR-9-3 promoter and that miR-9-3 expression was increased after 5 days of treatment with SFN. In vitro methylation analysis showed that the methylated recombinant construct exhibited lower luciferase reporter activity than the unmethylated counterpart. ChIP assays revealed that SFN treatment increased H3K4me1 enrichment at the miR-9-3 promoter. Furthermore, SFN treatment attenuated enzymatic DNMT activity and DNMT3a, HDAC1, HDAC3, HDAC6 and CDH1 protein expression. Taken together, these findings indicate that SFN may exert its chemopreventive effects partly through epigenetic demethylation and restoration of miR-9-3.

Role of MLH1 methylation in esophageal cancer carcinogenesis and its clinical significance

The mutL homolog-1 (MLH1) is a DNA mismatch repair gene and has been reported to be frequently methylated in numerous cancers. However, the association between MLH1 methylation and esophageal cancer (EC), as well as its clinical significance, remains unclear. Hence, we conducted a systematic meta-analysis based on 19 articles (including 1384 ECs, 345 premalignant lesions, and 1244 healthy controls). Our analysis revealed that the frequency of MLH1 methylation was significantly elevated during EC carcinogenesis. In addition, we observed that MLH1 promoter methylation was associated with age (odds ratio [OR]=1.79; 95% CI =1.20-2.66), advanced tumor grade (OR=3.7; 95% CI =2.37-5.77), lymph node metastasis (OR=2.65; 95% CI =1.81-3.88), distant metastasis (OR=7.60; 95% CI =1.23-47.19), advanced clinical stage (OR=4.46; 95% CI =2.88-6.91), and poor prognosis in EC patients (hazard ratio =1.64, 95% CI =1.00-2.69). The pooled sensitivity, specificity, and area under the curve of MLH1 methylation in EC patients versus healthy individuals were 0.15, 0.99, and 0.77, respectively. Our findings indicate that MLH1 methylation is involved in the carcinogenesis, progression, and metastasis of EC. Moreover, methylated MLH1 could be a potential diagnostic and prognostic biomarker for EC.

Aberrant methylation of mutL homolog 1 is associated with increased risk of non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) is a common malignant tumor. DNA hypermethylation in the promoter region has been served as a potential molecular marker for several tumors. The goal of the current study was to assess the diagnostic ability of mutL homolog 1 (MLH1) promoter methylation in NSCLC.

METHODS

A total of 111 NSCLC patients' paired tissue samples were obtained to explore the association between MLH1 promoter methylation and NSCLC by methylation-specific polymerase chain reaction (MSP) method. Public databases including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used to verify our findings.

RESULTS

Our results showed a significantly higher MLH1 methylation frequency in tumor tissue samples than their paired adjacent tissues (P = .008). ROC curve indicated that MLH1MSP assay was a sensitive but not a specific method in the diagnosis for NSCLC (sensitivity = 0.964, specificity = 0.135, AUC = 0.550). And the association between the methylation level and clinical characteristics has no statistical significance. TCGA cohort evinced a higher methylation probability in tumor group compared with nontumor group (the mean β value: -0.449 [-0.467, -0.437] vs -0.466 [-0.472, -0.437], P = .011), which was consistent with our results. Meanwhile, an inverse correlation between MLH1 methylation and MLH1 expression was detected in TCGA and GEO databases.

CONCLUSIONS

The MSP method for MLH1 methylation was a sensitive but not a specific diagnostic method for NSCLC.

Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer

The accurate classification of non-small cell lung carcinoma (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is essential for both clinical practice and lung cancer research. Although the standard WHO diagnosis of NSCLC on biopsy material is rapid and economic, more than 13% of NSCLC tumors in the USA are not further classified. The purpose of this study was to analyze the genome-wide pattern differences in copy number variations (CNVs) and to develop a CNV signature as an adjunct test for the routine histopathologic classification of NSCLCs. We investigated the genome-wide CNV differences between these two tumor types using three independent patient datasets. Approximately half of the genes examined exhibited significant differences between LUAD and LUSC tumors and the corresponding non-malignant tissues. A new classifier was developed to identify signature genes out of 20 000 genes. Thirty-three genes were identified as a CNV signature of NSCLC. Using only their CNV values, the classification model separated the LUADs from the LUSCs with an accuracy of 0.88 and 0.84, respectively, in the training and validation datasets. The same signature also classified NSCLC tumors from their corresponding non-malignant samples with an accuracy of 0.96 and 0.98, respectively. We also compared the CNV patterns of NSCLC tumors with those of histologically similar tumors arising at other sites, such as the breast, head, and neck, and four additional tumors. Of greater importance, the significant differences between these tumors may offer the possibility of identifying the origin of tumors whose origin is unknown.