Analysis of DNA methylation in cancer: location revisited

DNA methylation regulator-mediated modification patterns and tumor microenvironment characterization in glioma

Growing evidences indicate DNA methylation plays a crucial regulatory role in inflammation, innate immunity, and immunotherapy. However, the overall landscape of various DNA methylation regulatory genes and their relationship with the infiltration of immune cells into the tumor microenvironment (TME) as well as the response to immunotherapy in gliomas is still not clear. Therefore, we comprehensively analyzed the correlation between DNA methylation regulator patterns, infiltration of immune cell-types, and tumor immune response status in gather glioma cohorts. Furthermore, we calculated the DNA methylation score (DMS) for individual glioma samples, then evaluated the relationship between DMS, clinicopathological characteristics, and overall survival (OS) in patients with gliomas. Our results showed three distinct DNA methylation regulator patterns among the glioma patients which correlated with three distinct tumor immune response phenotypes, namely, immune-inflamed, immune-excluded, and immune desert. We then calculated DMS for individual glioma samples based on the expression of DNA methylation-related gene clusters. Furthermore, DMS, tumor mutation burden (TMB), programmed death 1 (PD-1) expression, immune cell infiltration status in the TME, and Tumor Immune Dysfunction and Exclusion (TIDE) scores were associated with survival outcomes and clinical responses to immune checkpoint blockade therapy. We also validated the predictive value of DMS in two independent immunotherapy cohorts. In conclusion, our results demonstrated that three DNA methylation regulator patterns that correlated with three tumor immune response phenotypes. Moreover, we demonstrated that DMS was an independent predictive biomarker that correlated with survival outcomes of glioma patients and their responses to immunotherapy therapeutic regimens.

A pan-cancer analysis of the oncogenic role of dual-specificity tyrosine (Y)-phosphorylation- regulated kinase 2 (DYRK2) in human tumors

Although there have been studies correlating DYRK2 with a number of human cancers, there has been no pan-cancer analysis. Therefore, through the TCGA database, we conducted a related study on the expression of DYRK2 in cancers.The expression of DYRK2 is obviously increased in some cancers, while the opposite is true in others, and there is a clear association between its expression and the prognosis of cancer patients.The mutation of DYRK2 is also significantly correlated with patients’ prognosis in certain human tumors. In addition, phosphorylation and methylation levels of DYRK2 are different between tumor tissues and adjacent normal tissues in various tumors. In the tumour microenvironment, the expression of DYRK2 correlates with cancer-associated fibroblast infiltration, such as BLCA or HNSC. In order to fully understand the role of DYRK2 in different tumors, we conducted a pan-cancer analysis.

The DPY30-H3K4me3 Axis-Mediated PD-L1 Expression in Melanoma

Background

DPY30 is a common subunit of the human SET1/MLL complex and is an essential protein required for the activity of SET1/MLL methyltransferase. DPY30 regulates the histone H3K4 modification, and dysfunction of DPY30 might contribute to the regulation of cancer immune evasion. However, the functions and regulation of DPY30 in the expression of programmed cell death ligand 1 (PD-L1) is still not completely explored.

Methods

Various online databases were used for data processing and visualization, including UALCAN, Oncomine, cBioPortal, SangerBox, TISIDB, TIMER, and GEPIA databases. The expression of DPY30 and PD-L1 in melanoma tissues were evaluated by IHC. Chromatin Immunoprecipitation (ChIP), RT-PCR and flow cytometry were used to elucidate the underlying molecular mechanism of PD-L1 expression regulation and its function.

Results

The mRNA level of DPY30 in melanoma was higher than in normal tissues. The expression of DPY30 was positively associated with TMB, neoantigens and PD-L1 expression. Furthermore, DPY30 expression showed significant positive correlations with immune suppressor cells and ICP genes involved in T-cell exhaustion. IHC showed that the positive rates of DPY30 and PD-L1 in melanoma tissues were 62% and 58%, respectively. Correlation analysis revealed that DPY30 over-expression was positively associated with PD-L1 expression. Silencing of DPY30 by specific siRNA significantly inhibited PD-L1 expression. ChIP analysis revealed that H3K4me3 levels were enriched in the proximal PD-L1 promoter region in tumor cells. Inhibition of DPY30 still suppressed the PD-L1 level in IFN-γ treated MMAC-SF cells. Furthermore, the apoptosis of PD1⁺ T-cells in co-culture with MMAC-SF cells by knockdown of DPY30 were markedly reduced.

Conclusion

This study shows the roles of DPY30 in regulating the cancer immune evasion in melanoma. Targeting the DPY30-H3K4me3 axis might be an alternative approach to enhance the efficacy of checkpoint immunotherapy.

Integration of Transcriptome and Epigenome to Identify and Develop Prognostic Markers for Ovarian Cancer

DNA methylation is a widely researched epigenetic modification. It is associated with the occurrence and development of cancer and has helped evaluate patients' prognoses. However, most existing DNA methylation prognosis models have not simultaneously considered the changes of the downstream transcriptome. Methods. The RNA-Sequencing data and DNA methylation omics data of ovarian cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Consensus Cluster Plus algorithm was used to construct the methylated molecular subtypes of the ovary. Lasso regression was employed to build a multi-gene signature. An independent data set was applied to verify the prognostic value of the signature. The Gene Set Variation Analysis (GSVA) was used to carry out the enrichment analysis of the pathways linked to the gene signature. The IMvigor 210 cohort was used to explore the predictive efficacy of the gene signature for immunotherapy response. Results. We distinguished ovarian cancer samples into two subtypes with different prognosis, based on the omics data of DNA methylation. Differentially expressed genes and enrichment analysis among subtypes indicated that DNA methylation was related to fatty acid metabolism and the extracellular matrix (ECM)-receptor. Furthermore, we constructed an 8-gene signature, which proved to be efficient and stable in predicting prognostics in ovarian cancer patients with different data sets and distinctive pathological characteristics. Finally, the 8-gene signature could predict patients' responses to immunotherapy. The polymerase chain reaction experiment was further used to verify the expression of 8 genes. Conclusion. We analyzed the prognostic value of the related genes of methylation in ovarian cancer. The 8-gene signature predicted the prognosis and immunotherapy response of ovarian cancer patients well and is expected to be valuable in clinical application.

DNA methylation regulators-related molecular patterns and tumor immune landscape in hepatocellular carcinoma

Increasing evidence showed that the dysregulation of DNA methylation regulators is a decisive feature of almost all cancer types and affects tumor progressions. However, few studies focused on the underlying influences of DNA methylation regulators-related genes (DMRegs) in immune cell-infiltration characteristics, tumor microenvironment (TME) and immunotherapy in HCC patients. In our study, the alterations of DNA methylation regulators modification patterns (DMRPs) were clustered from hepatocellular carcinoma (HCC) samples based on the expression of DNA methylation regulators as well as genetic and transcriptional features. In addition, based on molecular identification of three distinct molecular subtypes, we found that different DMRPs alterations were related to different clinicopathological characteristics, prognosis, and immune cells infiltration features. Moreover, we constructed and validated a DNA methylation regulators-related genes score (DMRegs_score) to predict the survival of HCC patients. A high DMRegs _score, which was characterized by more TP53 wild mutation, high expression of PD-1, CTLA-4, and remarkable immunity activation, was indicative of poor prognosis. Furthermore, we validated the expression of eight genes which were used for the prognostic signature in this risk score by RT-qPCR using tissues from our center. More importantly, DMRegs_score was highly correlated with targeted drug sensitivity. Additionally, we developed a highly accurate scoring system that could be used to improve the clinical applicability of DMRegs _score. In conclusion, these findings may contribute to a better understanding of DNA methylation regulators and provide new strategies for evaluating prognosis and developing more effective combination therapy for HCC patients.

miR-22 Suppresses EMT by Mediating Metabolic Reprogramming in Colorectal Cancer through Targeting MYC-Associated Factor X

Colorectal cancer (CRC) is one of the most frequent gastrointestinal cancers. MicroRNAs (miRNAs) have been proved to be unusually expressed in CRC progression and thus alter multiple pathological processes in CRC cells. However, the specific roles and mechanisms of miR-22 in CRC have not been clearly reported. MicroRNA-22 (miR-22) and MYC-associated factor X (MAX) expressions were determined by RT-qPCR in CRC tissues and cells. The targeted regulatory effects of miR-22 and MAX were confirmed by luciferase reporter and coimmunoprecipitation assays. Also, gain- and loss-of-function and rescue experiments were used to elucidate the function and mechanism of miR-22 and MAX in CRC cells and the mouse xenograft model. We discovered that miR-22 was hypermethylated and downregulated, while MAX was upregulated in CRC. miR-22 markedly inhibited migration, invasion, glycolysis, and cancer stem cell transcription factors in CRC cells. In addition, it was found that miR-22 can directly target MAX. Additional functional experiments confirmed that MAX overexpression can rescue the effects of miR-22 on the behavior of CRC cells. This study suggested that miR-22, as a cancer suppressor, participates in CRC progression by targeting MAX, which might provide basic information for therapeutic targets for CRC.

The Landscape of Early Growth Response Family Members 1-4 in Hepatocellular Carcinoma: Their Biological Roles and Diagnostic Utility

The incidence of hepatocellular carcinoma (HCC), which is one of the most frequent types of cancer seen all over the world, is steadily growing from year to year. EGR genes are members of the early growth response (EGR) gene family. It has been shown that EGR genes play an increasingly essential role in the development of tumors and the progression of numerous malignancies. However, the possible diagnostic and prognostic roles of EGR genes in HCC have only been examined in a limited number of studies. Expression and methylation data on EGR family members were obtained from TCGA datasets. The prognostic values of EGR members were studied. Additionally, the correlations of EGR members with immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA). In this study, we found that the expression of EGR1, EGR2, EGR3, and EGR4 was distinctly decreased in HCC specimens compared with nontumor specimens. ROC assays confirmed that they have a strong ability in screening HCC specimens from nontumor specimens. According to the findings of Pearson's correlation, EGR1, EGR2, EGR3, and EGR4 were found to have a negative association with the methylation level. Survival study revealed that EGR1, EGR2, and EGR3 were associated with the clinical outcome of HCC patients. Immune cell enrichment analysis demonstrated that the expressions of all EGR members were positively related to the levels of most types of immune cells, such as macrophages, NK cells, B cells, T cells, eosinophils, and CD8 T cells. Overall, the current work demonstrated the expression mode and prognostic value of EGR members in HCC in a comprehensive manner, offering insights for further research of the EGR family as possible clinical biomarkers in HCC.

Discovery and validation of tissue-specific DNA methylation as noninvasive diagnostic markers for colorectal cancer

Background

Noninvasive diagnostic markers that are capable of distinguishing patients with colorectal cancer (CRC) from healthy individuals or patients with other cancer types are lacking. We report the discovery and validation of a panel of methylation-based markers that specifically detect CRC.

Methods

This was a large-scale discovery study based on publicly available datasets coupled with a validation study where multiple types of specimens from six cohorts with CRC, other cancer types, and healthy individuals were used to identify and validate the tissue-specific methylation patterns of CRC and assess their diagnostic performance.

Results

In the discovery and validation cohort (N = 9307), ten hypermethylated CpG sites located in three genes, C20orf194, LIFR, and ZNF304, were identified as CRC-specific markers. Different analyses have suggested that these CpG sites are CRC-specific hypermethylated and play a role in transcriptional silencing of corresponding genes. A random forest model based on ten markers achieved high accuracy rates between 85.7 and 94.3% and AUCs between 0.941 and 0.970 in predicting CRC in three independent datasets and a low misclassification rate in ten other cancer types. In the in-house validation cohort (N = 354), these markers achieved consistent discriminative capabilities. In the cfDNA pilot cohort (N = 14), hypermethylation of these markers was observed in cfDNA samples from CRC patients. In the cfDNA validation cohort (N = 155), the two-gene panel yielded a sensitivity of 69.5%, specificity of 91.7%, and AUC of 0.806.

Conclusions

Hypermethylation of the ten CpG sites is a CRC-specific alteration in tissue and has the potential use as a noninvasive cfDNA marker to diagnose CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01312-9.

IGFBP5 is Upregulated and Associated with Poor Prognosis in Colorectal Cancer

Purpose

This study aimed to investigate the role of IGFBP5 in colorectal cancer (CRC) and the relationship between the expression of IGFBP5 and clinicopathological parameters in CRC patients.

Patients and Methods

Immunohistochemical analysis was used to detect the expression of IGFBP5 and its correlation with clinicopathological parameters of CRC patients. Prognosis analysis, gene set enrichment analysis, and protein interaction network analysis were performed using bioinformatics analysis. The Genomics of Drug Sensitivity in Cancer (GDSC) dataset was used to analyze the correlation between the expression of IGFBP5 and drug resistance.

Results

Immunohistochemical analysis revealed that the expression of IGFBP5 was significantly higher in CRC tissues than in para-cancerous tissues (P < 0.05). High expression of IGFBP5 was associated with tumor differentiation and the N stage of CRC (P < 0.05). Moreover, high expression of IGFBP5 predicted worse overall survival and disease-free survival in CRC patients (P < 0.05). The expression of IGFBP5 was associated with cell–matrix adhesion, extracellular matrix binding, and collagen binding (P < 0.05). Furthermore, IGFBP5 was involved in the Hedgehog signaling pathway and PI3K-Akt signaling pathway (P < 0.05). IGF1, IGF2, SPP1, LTBP1, and FAM20C were most closely related to IGFBP5.

Conclusion

The expression of IGFBP5 is upregulated and associated with tumor differentiation, lymph node metastasis, drug resistance, and prognosis in CRC patients.

Investigating and modeling the differential DNA methylation for early lung adenocarcinoma diagnosis

Background: Aberrant DNA methylations serve as rich sources of diagnostic biomarkers, but a further improvement in their accuracy and clinical utility is warranted. Methods: Large panel bisulfite sequencing were performed on paired normal and stage I/IV tumors from 226 lung adenocarcinoma cancer patients to characterize the differentially methylated regions (DMRs). Results: Random forest model achieved high prediction accuracy (sensitivity 96% and specificity 97.56%) to separate normal controls from both early and advanced cancer samples, which is superior to most previous prediction models tested in lung adenocarcinoma. Conclusion: Our results suggest that combining the random forest model with targeted bisulfite sequencing have great clinical potentials to accurately predict and early diagnose lung adenocarcinoma during cancer screening.

High-throughput DNA methylation analysis in ITP confirms NOTCH1 hypermethylation through the Th1 and Th2 cell differentiation pathways

BACKGROUND

Immune thrombocytopenia (ITP) is a prevalent autoimmune disease with a complex aetiology where DNA methylation changes are becoming triggers.

METHOD

To investigate novel abnormally methylated genes in the pathogenesis of ITP, we performed a high-throughput methylation analysis on 21 ITP patients and 9 normal control samples. We analysed the extent of key methylated genes and their downstream cytokines through Luminex assay or qRT-PCR. Then, bone marrow mononuclear cells were extracted from ITP patients, and decitabine (demethylation drug) was added to the culture medium of cultured cells. qRT-PCR and ELISA were used to detect whether decitabine could effectively affect target genes and related cytokines.

RESULTS

Through the STRING and Metascape databases, hypermethylated NOTCH1 can be identified and can influence ITP by regulating many downstream cytokines through Th1 and Th2 cell differentiation pathways. Compared with those in the normal control group, the expression levels of NOTCH1 and its downstream Th2 cytokines (IL-4, IL-10, and GATA3) were significantly decreased and those of Th1 cytokines (IFN-γ, IL-12, and TNF-α) were significantly increased in the ITP group. Decitabine exerts its demethylation effect, so the expression of NOTCH1 and its related cytokines in the ITP group treated with 100 nM decitabine were significantly reversed.

CONCLUSIONS

Our results suggest that the pathogenesis of ITP may exert its influence on epigenetics through alteration of DNA methylation at regulatory regions of the target NOTCH1 gene in the Th1 and Th2 cell differentiation pathways. At the same time, decitabine may achieve a therapeutic effect on ITP by demethylation.

Benchmarking DNA Methylation Analysis of 14 Alignment Algorithms for Whole Genome Bisulfite Sequencing in Mammals

Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on biological insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algorithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methylation detection accuracy in mammals.

The prediction of tumor and normal tissues based on the DNA methylation values of ten key sites

Abnormal DNA methylation can alter the gene expression to promote or inhibit tumorigenesis in colon adenocarcinoma (COAD). However, the finding important genes and key sites of abnormal DNA methylation which result in the occurrence of COAD is still an eventful task. Here, we studied the effects of DNA methylation in the 12 types of genomic features on the changes of gene expression in COAD, the 10 important COAD-related genes and the key abnormal DNA methylation sites were identified. The effects of important genes on the prognosis were verified by survival analysis. Moreover, it was shown that the important genes were participated in cancer pathways and were hub genes in a co-expression network. Based on the DNA methylation levels in the ten sites, the least diversity increment algorithm for predicting tumor tissues and normal tissues in seventeen cancer types are proposed. The better results are obtained in jackknife test. For example, the predictive accuracies are 94.17 %, 91.28 %, 89.04 % and 88.89 %, respectively, for COAD, rectum adenocarcinoma, pancreatic adenocarcinoma and cholangiocarcinoma. Finally, by computing enrichment score of infiltrating immunocytes and the activity of immune pathways, we found that the genes are highly correlated with immune microenvironment.

DNA methylation fingerprint of hepatocellular carcinoma from tissue and liquid biopsies

Hepatocellular carcinoma (HCC) is amongst the cancers with highest mortality rates and is the most common malignancy of the liver. Early detection is vital to provide the best treatment possible and liquid biopsies combined with analysis of circulating tumour DNA methylation show great promise as a non-invasive approach for early cancer diagnosis and monitoring with low false negative rates. To identify reliable diagnostic biomarkers of early HCC, we performed a systematic analysis of multiple hepatocellular studies and datasets comprising > 1500 genome-wide DNA methylation arrays, to define a methylation signature predictive of HCC in both tissue and cell-free DNA liquid biopsy samples. Our machine learning pipeline identified differentially methylated regions in HCC, some associated with transcriptional repression of genes related with cancer progression, that benchmarked positively against independent methylation signatures. Combining our signature of 38 DNA methylation regions, we derived a HCC detection score which confirmed the utility of our approach by identifying in an independent dataset 96% of HCC tissue samples with a precision of 98%, and most importantly successfully separated cfDNA of tumour samples from healthy controls. Notably, our risk score could identify cell-free DNA samples from patients with other tumours, including colorectal cancer. Taken together, we propose a comprehensive HCC DNA methylation fingerprint and an associated risk score for detection of HCC from tissue and liquid biopsies.

The hnRNPK/A1/R/U Complex Regulates Gene Transcription and Translation and is a Favorable Prognostic Biomarker for Human Colorectal Adenocarcinoma

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are emerging as a crucially important protein family in tumors. However, it is unclear which family members are essential for cancer progression, and their diverse expression patterns and prognostic values are rarely reported. In this work, we found that the expression levels of hnRNPs were all upregulated in colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) tissues. Immunohistochemical staining revealed that hnRNPA1, hnRNPA2B1, hnRNPC, hnRNPK, hnRNPR, and hnRNPU are overexpressed in colorectal adenocarcinoma. Additionally, the promoter methylation levels of hnRNPs were significantly elevated or decreased, and multiple genetic alterations of hnRNPs were found in colorectal adenocarcinoma patients. Correlation analysis showed that the expression levels of hnRNPs were positively correlated with each other. Furthermore, we demonstrated that high expressions of hnRNPA1, hnRNPK, hnRNPR, and hnRNPU were associated with better overall survival rates for colorectal adenocarcinoma patients. The co-expression network and functional prediction analysis indicated that hnRNPK/A1/R/U was involved in cellular gene transcription and translation. Moreover, hnRNPK/A1/R/U complex was identified and confirmed by mass spectrometry and co-immunoprecipitation. RNA sequencing analysis revealed that the transcription factor hnRNPK regulated transcription and translation of related genes. Finally, through establishment of stable cell lines in vitro, we verified that hnRNPK was a favorable factor in human colorectal adenocarcinoma which promoted immune cell infiltration and inhibited tumor growth. Our findings illustrate that the hnRNPK/A1/R/U complex is a favorable prognostic biomarker for human colorectal adenocarcinoma. Targeting hnRNPK during transcription and translation could be a promising therapeutic strategy for colorectal adenocarcinoma treatment.

Associations of DNA methylation algorithms of aging and cancer risk: Results from a prospective cohort study

Background

Previous studies have shown that three DNA methylation (DNAm) based algorithms of aging, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), to be strong predictors of mortality and aging related outcomes. We aimed to investigate if and to what extent these algorithms predict cancer.

Methods

In four subsets (n = 727, 1003, 910, and 412) of a population-based cohort from Germany, DNA methylation in whole blood was measured using the Infinium Methylation EPIC BeadChip kit or the Infinium HumanMethylation450K BeadChip Assay (Illumina.Inc, San Diego, CA, USA). AgeAccelPheno, AgeAccelGrim, and a revised MRscore based on 8 CpGs only (MRscore-8CpGs), were calculated. Hazard ratios (HRs) were calculated to assess associations of the three DNAm algorithms with total cancer risk and risk of invasive breast, lung, prostate, and colorectal cancer incidence.

Findings

During 17 years of follow-up, a total of 697 malignant tumors (thereof breast cancer = 75, lung cancer = 146, prostate cancer = 114, colorectal cancer = 155) were observed. All three algorithms showed strong positive associations with lung cancer risk in a dose response manner, with adjusted HRs per SD increase in AgeAccelPheno, AgeAccelGrim, and MRscore-8CpGs, of 1·37 (1·03-1·82), 1·74 (1·11-2·73), and 2·06 (1·39-3·06), respectively. By contrast, strong inverse associations were seen with breast cancer risk [adjusted HRs 0·65 (0·49-0·86), 0·45 (0·25-0·80), and 0·42 (0·25-0·70), respectively]. Weak positive associations of MRscore-8CpGs were seen with total cancer risk.

Interpretation

The DNAm algorithms, particularly the MRscore-8CpGs, have potential to contribute to site-specific cancer risk prediction.

Funding

The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).

mRNA expression and epigenetic-based role of chromodomain helicase DNA-binding 5 in hepatocellular carcinoma

Objective

Chromodomain helicase DNA-binding 5 (CHD5) acts as a tumor suppressor gene in some cancers. CHD5 expression levels may affect an individual’s susceptibility to hepatocellular carcinoma (HCC). This study aimed to evaluate the methylation pattern of the CHD5 promoter region and the gene’s corresponding mRNA expression in HCC patients compared with healthy individuals.

Methods

In this case–control study, CHD5 mRNA gene expression levels and DNA methylation patterns were analyzed in 81 HCC patients and 90 healthy individuals by quantitative reverse transcription polymerase chain reaction and methylation-specific polymerase chain reaction, respectively.

Results

The CHD5 gene was hypermethylated in 61.8% of the HCC patients and 54.4% of the controls, and this difference was statistically significant. The CHD5 mRNA expression levels were significantly lower in the HCC patient group.

Conclusions

Hypermethylation of the CHD5 promoter region may significantly lower the expression of this gene, affecting the incidence and severity of HCC. The methylation status of CHD5 can also be further studied as a prognostic factor in HCC.

Identification of Prognostic DNA Methylation Signatures in Lung Adenocarcinoma

BACKGROUND

Increasing evidence exists of a link between DNA methylation and tumor immunotherapy. However, the impact of DNA methylation on the characteristics of the lung adenocarcinoma microenvironment and its effect on immunotherapy remain unclear.

METHOD

This study collected TCGA-LUAD related data sets (LUAD) to explore the characteristics and regulation of 20 DNA methylation-related genes. We further identified two DNA methylation subtypes by analysing the expression profiles of these 20 DNA methylation-related genes. Subsequently, the differences in immune cell infiltration (ICI) and the expression of immune-related signaling factors among different DNA methylation subtypes were explored, and the differentially expressed genes (DEGs) among different LUAD DNA methylation subtypes were identified. Using univariate Cox to screen differentially expressed genes meaningful for survival, a DNA methylation score (DMS) was constructed based on the weight of the first and second dimensions after dimensionality reduction by principal component analysis (PCA). Our study found that DMS can better evaluate the prognosis of lung adenocarcinoma.

RESULTS

Based on DMS, LUAD samples were divided into two groups with high and low scores. The differences in clinical characteristics, tumor mutation load, and tumor immune cell infiltration between different DMS groups of LUAD were deeply explored, and the prediction ability of DMS for the benefit of immunotherapy was evaluated.

CONCLUSIONS

DMS is a valuable tool for predicting survival, clinicopathological features, and immunotherapeutic efficacy, which may help to promote personalized LUAD immunotherapy in the future.

DNA Methylation Biomarkers in Colorectal Cancer: Clinical Applications for Precision Medicine

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide that is attributed to gradual long-term accumulation of both genetic and epigenetic changes. To reduce the mortality rate of CRC and to improve treatment efficacy, it will be important to develop accurate noninvasive diagnostic tests for screening, acute, and personalized diagnosis. Epigenetic changes such as DNA methylation play an important role in the development and progression of CRC. Over the last decade, a panel of DNA methylation markers has been reported showing a high accuracy and reproducibility in various semi-invasive or noninvasive biosamples. Research to obtain comprehensive panels of markers allowing a highly sensitive and differentiating diagnosis of CRC is ongoing. Moreover, the epigenetic alterations for cancer therapy, as a precision medicine strategy will increase their therapeutic potential over time. Here, we discuss the current state of DNA methylation-based biomarkers and their impact on CRC diagnosis. We emphasize the need to further identify and stratify methylation-biomarkers and to develop robust and effective detection methods that are applicable for a routine clinical setting of CRC diagnostics particularly at the early stage of the disease.

Association between germline variants and somatic mutations in colorectal cancer

Colorectal cancer (CRC) is a heterogeneous disease with evidence of distinct tumor types that develop through different somatically altered pathways. To better understand the impact of the host genome on somatically mutated genes and pathways, we assessed associations of germline variations with somatic events via two complementary approaches. We first analyzed the association between individual germline genetic variants and the presence of non-silent somatic mutations in genes in 1375 CRC cases with genome-wide SNPs data and a tumor sequencing panel targeting 205 genes. In the second analysis, we tested if germline variants located within previously identified regions of somatic allelic imbalance were associated with overall CRC risk using summary statistics from a recent large scale GWAS (n≃125 k CRC cases and controls). The first analysis revealed that a variant (rs78963230) located within a CNA region associated with TLR3 was also associated with a non-silent mutation within gene FBXW7. In the secondary analysis, the variant rs2302274 located in CDX1/PDGFRB frequently gained/lost in colorectal tumors was associated with overall CRC risk (OR = 0.96, p = 7.50e-7). In summary, we demonstrate that an integrative analysis of somatic and germline variation can lead to new insights about CRC.

Increased ATP2A1 Predicts Poor Prognosis in Patients With Colorectal Carcinoma

Colorectal cancer is one of the most common malignant tumors in the digestive system. Traditional diagnosis and treatment methods have not significantly improved the overall survival of patients. In this study, we explored the value of ATP2A1 as a biomarker in predicting the prognosis of colorectal cancer patients. We used the TCGA database to reveal the relationship between ATP2A1 mRNA level and prognosis, methylation, and immune invasion in colorectal cancer. The results showed that the expression of ATP2A1 was increased in colorectal cancer. The overall survival of patients with high expression of ATP2A1 was significantly lower than patients with low expression of ATP2A1. Cox regression analysis showed that high expression of ATP2A1 was an independent risk factor for poor prognosis in colorectal cancer patients. In addition, we used three datasets to perform a meta-analysis, which further confirmed the reliability of the results. Furthermore, we revealed that ATP2A1 could significantly inhibit the proliferation of colorectal cancer cells by inhibiting the autophagy process and was associated with several immune cells, especially CD8 + T cells. Finally, four small molecule drugs with potential inhibition of ATP2A1 expression were found by CMap analysis. This study demonstrates for the first time that ATP2A1 is a potential pathogenic factor, which may play a significant role in colorectal cancer.

Lessons From a Systematic Literature Search on Diagnostic DNA Methylation Biomarkers for Colorectal Cancer: How to Increase Research Value and Decrease Research Waste?

OBJECTIVES

To improve colorectal cancer (CRC) survival and lower incidence rates, colonoscopy and/or fecal immunochemical test screening are widely implemented. Although candidate DNA methylation biomarkers have been published to improve or complement the fecal immunochemical test, clinical translation is limited. We describe technical and methodological problems encountered after a systematic literature search and provide recommendations to increase (clinical) value and decrease research waste in biomarker research. In addition, we present current evidence for diagnostic CRC DNA methylation biomarkers.

METHODS

A systematic literature search identified 331 diagnostic DNA methylation marker studies published before November 2020 in PubMed, EMBASE, Cochrane Library, and Google Scholar. For 136 bodily fluid studies, extended data extraction was performed. STARD criteria and level of evidence were registered to assess reporting quality and strength for clinical translation.

RESULTS

Our systematic literature search revealed multiple issues that hamper the development of DNA methylation biomarkers for CRC diagnosis, including methodological and technical heterogeneity and lack of validation or clinical translation. For example, clinical translation and independent validation were limited, with 100 of 434 markers (23%) studied in bodily fluids, 3 of 434 markers (0.7%) translated into clinical tests, and independent validation for 92 of 411 tissue markers (22%) and 59 of 100 bodily fluids markers (59%).

DISCUSSION

This systematic literature search revealed that major requirements to develop clinically relevant diagnostic CRC DNA methylation markers are often lacking. To avoid the resulting research waste, clinical needs, intended biomarker use, and independent validation should be better considered before study design. In addition, improved reporting quality would facilitate meta-analysis, thereby increasing the level of evidence and enabling clinical translation.

Chromobox 4 (CBX4) promotes tumor progression and stemness via activating CDC20 in gastric cancer

BACKGROUND

The Chromobox homolog 4 (CBX4) has been found to be overexpressed in multiple malignancies. However, the associations between CBX4 and gastric cancer (GC) have remained unclear. This study aimed to determine the biological roles of CBX4 in GC and identify effective therapeutic targets.

METHODS

The 3-(4,5-dimethylthiazol-2-yl) (MTT) assays were used to screen CBX family members. Differential analysis was utilized to evaluate the CBX4 levels. Kaplan-Meier analysis was used to perform prognostic analysis. Western blotting assay, quantitative polymerase chain reaction (qPCR) assay and immunohistochemistry (IHC) were used to assess CBX4 expressions. Colony formation assay, Cell Counting Kit-8 (CCK-8) assay, and Transwell assay were used to assess progression features of cells. The tail vein injection model was utilized to determine the metastatic efficacy of GC cells. Tumor sphere formation assay was used to assess tumor stemness maintenance ability. Chromatin immunoprecipitation (ChIP)-qPCR assay was used to evaluate the associations between CBX4 and CDC20. A subcutaneous tumor model was used to assess the in vivo growth ability of GC.

RESULTS

The MTT assay revealed that only CBX4 inhibition could lead to notable restriction of GC growth, as compared to others. Differential analysis suggested that CBX4 was upregulated in tumor samples relative to normal tissues. Less favorable overall survival (OS) outcomes were noticed in GC patients with high CBX4 in comparison to those with low CBX4. High CBX4 could notably enhance cell proliferation capacity, migration ability, and in vivo metastatic efficacy. Gene set enrichment analysis (GSEA) indicated the relationships between CBX4 and GC stemness, and CBX4 overexpression could remarkably elevate self-renewal ability of GC cells. In addition, CBX4 could mainly promote CDC20 messenger RNA (mRNA) levels, and targeting CBX4 suppressed the relative CDC20 levels. The ChIP-qPCR assay further demonstrated that CBX4 coordinated with H3K4me3 to bind at the CDC20 promoter region. Additionally, CBX4 depended on CDC20 to drive GC growth. Lastly, downregulated CBX4 could notably inhibit the growth of GC in vivo.

CONCLUSIONS

This study highlights the oncogenic roles of CBX4 in GC. CBX4 activates CDC20 to maintain stemness features of GC, thereby creating therapeutic vulnerabilities in the treatment of GC.

Tumor DNA Methylation Profiles Enable Diagnosis, Prognosis Prediction, and Screening for Cervical Cancer

Background

DNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.

Methods

The methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program. We first screened out the differential methylation sites in CC and normal tissues and performed multiple statistical analyses to discover DNA methylation diagnostic markers that are used to distinguish CC and normal control. Then, we developed a methylation-based survival model to improve risk stratification.

Results

A diagnostic prediction panel consists of five CpG markers that could predict cervical cancer versus normal tissue with highly correct rate of 100%, and cg16428251, cg22341310, and cg23316360 which in diagnostic prediction panel all could yield high sensitivity and specificity for detection of CC and normal in six cohorts (area under curve [AUC] > 0.8), in addition to excellent performance in discriminating between CC and normal sample. The diagnostic marker panel also effectively predicted the CIN3 versus normal tissue with high accuracy in two datasets (AUC = 0.80, 0.789, respectively). Furthermore, a prognostic prediction model aggregated two CpG markers that effectively stratified the prognosis of high-risk and low-risk groups (training cohort: hazard ratio [HR] 4, 95% CI: 1.7–9.6, P = 0.0021; testing cohort: hazard ratio [HR] 1.9, 95% CI: 1.2–3.1, P = 0.0072).

Conclusion

The findings of our study showed that DNA methylation markers are of great value in the diagnosis and prognosis of CC.

Global DNA Methylation Profiling Reveals Differentially Methylated CpGs between Salivary Gland Pleomorphic Adenomas with Distinct Clinical Course

Pleomorphic adenomas (PAs) are the most frequently diagnosed benign salivary gland tumors. Although the majority of PAs are characterized by slow growth, some develop very fast and are more prone to recur. The reason for such differences remains unidentified. In this study, we performed global DNA methylation profiling using the Infinium Human Methylation EPIC 850k BeadChip Array (Illumina) to search for epigenetic biomarkers that could distinguish both groups of tumors. The analysis was performed in four fast-growing tumors (FGTs) and four slow-growing tumors (SGTs). In all, 85 CpG dinucleotides differentiating both groups were identified. Six CpG tags (cg06748470, cg18413218, cg10121788, cg08249296, cg18455472, and cg19930657) were selected for bisulfite pyrosequencing in the extended group of samples. We confirmed differences in DNA methylation between both groups of samples. To evaluate the potential diagnostic accuracy of the selected markers, ROC curves were constructed. We indicated that CpGs included in two assays showed an area under the curve with an acceptable prognostic value (AUC > 0.7). However, logistic regression analysis allowed us to indicate a more optimal model consisting of five CpGs ((1) cg06748470, (2) cg00600454, (3) CpG located in chr14: 77,371,501−77,371,502 (not annotated in GRCh37/hg19), (4) CpG2 located in chr16: 77,469,589−77,469,590 (not annotated GRCh37/hg19), and (5) cg19930657) with AUC > 0.8. This set of epigenetic biomarkers may be considered as differentiating factors between FGT and SGT during salivary gland tumor diagnosis. However, this data should be confirmed in a larger cohort of samples.

Comprehensive Pan-Cancer Analysis Reveals the Role of UHRF1-Mediated DNA Methylation and Immune Infiltration in Renal Cell Carcinoma

Ubiquitin-like PHD and ring finger domain protein 1 (UHRF1) are members of the multifunctional UHRF family, which can participate in DNA methylation change and histone posttranslational change through particular domains and participate in the event and development of tumors. The purpose of this study was to decide the molecular traits and potential medicine-based importance of UHRF1 that helped settle methylated immune infiltration in generalized cancer by carefully studying the relationship between UHRF1 expression and a variety of tumors and to further check for truth the functional role of UHRF1 in kidney-related cancer. A comprehensive analysis of UHRF1 in 33 cancers was performed based on TCGA database. This research involves analysis of mRNA expression profiles, prognostic value, immune infiltration, immune neoantigens, TMB, microsatellite instability, DNA methylation, and gene set enrichment analysis (GSEA). Both immune infiltration and DNA methylation were used to evaluate the importance and method of UHRF1 in renal cancer. The results showed that tumor tissue had higher expression level of UHRF1 than usual tissue. The high expression level of UHRF1 is related to the survival rate of renal cancer. UHRF1 expression was associated with tumor mutation load and microsatellite instability in different cancer types, and enrichment analysis identified terminology and pathways associated with UHRF1. This study showed that UHRF1 plays an important role in the group of objects and development of 33 tumors. UHRF1 may serve as a biomarker of immune infiltration and poor outlook of cancer.

PTBP1 as a Promising Predictor of Poor Prognosis by Regulating Cell Proliferation, Immunosuppression, and Drug Sensitivity in SARC

Background. Sarcomas (SARC) have been found as rare and heterogeneous malignancies with poor prognosis. PTBP1, belonging to the hnRNPs family, plays an essential role in some biological functions (e.g., pre-mRNA splicing, cell growth, and nervous system development). However, the role of PTBP1 in SARC remains unclear. In this study, the aim was to investigate the potential role of PTBP1 with a focus on SARC. Methods. The expression, prognostic value, possible biological pathways of PTBP1, and its relationship with immune infiltration and drug sensitivity were comprehensively analyzed based on multiple databases. PTBP1 was further validated in osteosarcoma as the most prominent bone SARC. The expression of PTBP1 was investigated through IHC. The prognostic value of PTBP1 was verified in TARGET-OS databases. CRISPR/Cas9-mediated PTBP1 knockout HOS human osteosarcoma cell lines were used to assess the effect of PTBP1 on cell proliferation, migration, metastasis and cell cycle by CCK-8, Transwell migration, invasion, and FACS experiment. Result. PTBP1 was highly expressed and significantly correlated with poor prognosis in several cancers, especially in SARC, which was validated in the clinical cohort and osteosarcoma cell lines. The genetic alteration of PTBP1 was found most frequently in SARC. Besides, PTBP1 played a role in oncogenesis and immunity through cell cycle, TGFB, autophagy, and WNT pathways at a pan-cancer level. Knockout of PTBP1 was observed to negatively affect proliferation, migration, metastasis, and cell cycle of osteosarcoma in vitro. Furthermore, PTBP1 was significantly correlated with tumor immune infiltration, DNA methylation, TMB, and MSI in a wide variety of cancers. Moreover, the potential of the expression level of PTBP1 in predicting drug sensitivity was assessed. Conclusions. PTBP1 is highly expressed and correlated with prognosis and plays a vital pathogenic role in oncogenesis and immune infiltration of various cancers, especially for SARC, which suggests that it may be a promising prognostic marker and therapeutic target in the future.

Multi-Omics Analysis of the Prognosis and Biological Function for TRPV Channel Family in Clear Cell Renal Cell Carcinoma

Background

The transient receptor potential vanilloid (TRPV) channels family, TRPV1-6, has been identified to profoundly affect a wide spectrum of pathological processes in various cancers. However, the biological function and prognostic value of TRPVs in clear cell renal cell carcinoma (ccRCC) are still largely unknown.

Methods

We obtained the gene expression data and clinical information of 539 ccRCC patients from The Cancer Genome Atlas (TCGA) database. A series of databases were used for data processing and visualization, including GEPIA, GeneMANIA, MethSurv, GSCA, TIMER, and starBase databases.

Results

The mRNA expression of TRPV2/3 was upregulated while the expression of TRPV5/6 was downregulated in ccRCC tumor tissues. TRPV family members in ccRCC were rarely mutated (nearly 7 frequencies). The ROC curve showed that TRPV2/5/6 had a high diagnostic ability in discriminating ccRCC from the control samples (AUC>0.9). Higher levels of TRPV3 expression were associated with poor prognosis of ccRCC patients, while higher expression of TRPV4 was associated with favorable prognosis. The expression of TRPV3 in normal and ccRCC tissues was validated by Immunohistochemistry, and its expression was remarkably related to high histologic grade and advanced stage. Besides, TRPV3 exhibit a reduction of DNA methylation level with tumor progression, and 12 CpGs of TRPV3 were associated with a significant prognosis. In addition, TRPV3 expression was significantly associated with the accumulation of several tumor-infiltrating immune cells, especially regulatory T cells. Furthermore, high levels of TRPV3 induced the expression of immune checkpoints such as LAG3, CTLA4, PDCD1, and TIGIT. Finally, we predicted a key SNHG3/AL513497.1-miR-10b-5p-TRPV3 axis linking to carcinogenesis and progression of ccRCC.

Conclusion

Our study may uncover TRPV channels–associated molecular mechanisms involved in the tumorigenesis and progression of ccRCC. TRPV family members might be diagnosed and prognostic markers and potential therapeutic targets for ccRCC patients.

Multiomics Data Analysis and Identification of Immune-Related Prognostic Signatures With Potential Implications in Prognosis and Immune Checkpoint Blockade Therapy of Glioblastoma

Background

In recent years, glioblastoma multiforme (GBM) has been a concern of many researchers, as it is one of the main drivers of cancer-related deaths worldwide. GBM in general usually does not responding well to immunotherapy due to its unique microenvironment.

Methods

To uncover any further informative immune-related prognostic signatures, we explored the immune-related distinction in the genetic or epigenetic features of the three types (expression profile, somatic mutation, and DNA methylation). Twenty eight immune-related hub genes were identified by Weighted Gene Co-Expression Network Analysis (WGCNA). The findings showed that three genes (IL1R1, TNFSF12, and VDR) were identified to construct an immune-related prognostic model (IRPM) by lasso regression. Then, we used three hub genes to construct an IRPM for GBM and clarify the immunity, mutation, and methylation characteristics.

Results

Survival analysis of patients undergoing anti-program cell death protein 1 (anti-PD-1) therapy showed that overall survival was superior in the low-risk group than in the high-risk group. The high-risk group had an association with epithelial-mesenchymal transition (EMT), high immune cell infiltration, immune activation, a low mutation number, and high methylation, while the low-risk group was adverse status.

Conclusions

In conclusion, IRPM is a promising tool to distinguish the prognosis of patients and molecular and immune characteristics in GBM, and the IRPM risk score can be used to predict patient sensitivity to checkpoint inhibitor blockade therapy. Thus, three immune-related signatures will guide us in improving treatment strategies and developing objective diagnostic tools.

Comprehensive Analysis of DNA Methylation and Transcriptome to Identify PD-1-Negative Prognostic Methylated Signature in Endometrial Carcinoma

Background

Epigenetic mechanism plays an important role in endometrial carcinoma (EC). This study was designed to analyze the epigenetic mechanism between DNA methylation-driven genes (DEDGs) and drugs targeting DEDGs and to develop a DEDG score model for predicting the prognosis of EC.

Methods

Expression profile and methylation profile data of PD-1-negative EC samples were obtained from TCGA. To obtain intersected DEDGs, differentially expressed genes (DEGs) and differentially methylated genes from tumor tissues and normal tissues were analyzed by limma. A linear discriminant classification model was constructed using the gene expression profile of DMDGs, methylation profile of TSS1500, TSS200, and gene body regions. Principal component analysis (PCA) and ROC analysis were conducted. The protein-drug interactions analysis of DMDGs was performed using Network Analyst 3.0 tool. Lasso Cox regression analysis was used to screen prognostic DNA methylation driving gene and to build a risk score model. The ROC curve and Kaplan-Meier survival curve were plotted to evaluate the model prediction capability.

Results

A total of 96 DMDGs were screened from the three regions, distributed on 22 chromosomes, with consistent methylation patterns in different gene regions. Both the expression profile and methylation profile of the three regions can neatly distinguish tumor samples from normal ones, with a high classifying performance. A gene signature, which consisted of ELFN1-AS1 and ZNF132, could classify EC patients into a high-risk group and low-risk group. Prognosis of the high-risk group was significantly worse than that of the low-risk group. The risk model showed a high performance in predicting the prognosis of EC.

Conclusion

We successfully established a risk score system with two DMDGs, which showed a high prediction accuracy of EC prognosis.

RecQ mediated genome instability 2 (RMI2): a potential prognostic and immunological biomarker for pan-cancers

Background: RecQ mediated genome instability 2 (RMI2) is an essential component of the BLM-TopoIIIa-RMI1-RMI2 (BTR) complex. However, the mysterious veil of the potential immunological relationship of RMI2 in tumorigenesis and development has not been revealed.

Methods: We conducted the differential expression (DE) analysis of the RMI2 in pan-cancer using data onto Oncomine, TIMER, and GEPIA databases. Afterward, survival analysis and clinical-stage correlation analysis were performed via the TCGA database. Subsequently, we used R software to further explore the relationship between the expression level of RMI2 and tumor mutation burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), tumor immune-infiltrated cells (TILs), immune checkpoints (ICP), mismatch repairs (MMRs) -related genes, m6A-related genes, DNA methylation-related genes. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional networks were also performed for annotation via gene set enrichment analysis (GSEA).

Results: The RMI2 expressed remarkably high in most cancer types compared to cancer adjacent normal tissues (P < 0.05). High expression of RMI2 was linked to unfavorable prognosis and advanced stage of disease, especially in LIHC and PAAD. RMI2 expression was related to TMB in 16 cancer types and MSI in 8 cancer types. Furthermore, it is significant positive correlations between RMI2 and stromal and immune cells, ICP-related genes, MMRs-related genes, m6A-related genes, and DNA methylation-related genes. Finally, GSEA analysis revealed that RMI2 was engaged in a variety of signaling pathways in pan-cancers.

Conclusions: RMI2 may serve as a potential biological target and probably assume a crucial part in tumorigenesis and progression.

A Pan-Cancer Analysis of UBE2S in Tumorigenesis, Prognosis, Pathway, Immune Infiltration and Evasion, and Therapy Response from an Immune-Oncology Perspective

Background

Ubiquitin conjugating enzyme E2S (UBE2S), a member of the ubiquitin-conjugating enzyme family, is known to play a pivotal role in tumorigenesis and progression in some tumor types. However, whether UBE2S plays an irreplaceable role in the immune-oncology context of tumorigenesis, prognosis, pathogenesis, immune regulation, and therapeutic response through certain common molecular mechanisms remains to be defined. The present pan-cancer study was intended to decipher the landscape of UBE2S in pathologic, immunological, and therapeutic aspects across various cancers.

Methods

Data used for UBE2S analysis were obtained from TCGA database. The pan-cancer analysis was mainly focused on the expression patterns, prognostic values, mutation landscapes, biological pathways, tumor microenvironment remodeling, and therapeutic resistance of UBE2S using multiple databases including cBioPortal, Cancer Cell Line Encyclopedia (CCLE) database, Tumor Immune Estimation Resource (TIMER), and Gene Expression Profiling Interactive Analysis (GEPIA). External experimental validation was conducted to delineate the association of UBE2S with tumor phenotypes through assays of proliferation, colony formation, and migration. Data processing, statistical analysis, and plotting were performed using R software and GraphPad Prism software.

Results

UBE2S was aberrantly expressed in almost all human cancers, and elevated UBE2S expression was unfavorably associated with the clinical pathological stage and prognosis. DNA methylation and RNA modification were significantly correlated with the UBE2S expression level. The results of enrichment analysis revealed that UBE2S positively regulated MYC, G2M cell cycle, and DNA repair pathways and negatively regulated adipogenesis, fatty acid metabolism, and heme metabolism. In addition, UBE2S exhibited a significantly positive correlation with myeloid-derived suppressor cell MDSC and Th2 subsets in almost all tumors analyzed. UBE2S could confer immune evasion via coexpressed immunoinhibitors and T cell exhaustion. Notably, a higher UBE2S expression indicated a higher level of stemness, TMB, MSI, and MMR deficiency and DNA methyltransferases, as well as chemotherapeutic resistance in various cancers. Notably, in vitro functional validation showed that UBE2S knockdown attenuated the phenotypes of proliferation, clonogenicity, and migration in hepatocellular carcinoma cells.

Conclusions

Our study provided meaningful clues to support UBE2S as an immune-oncogenic molecule and shed light on potential applications of UBE2S in cancer detection, prognostic prediction, and therapeutic response assessment.

Genetic Regulation of DNA Methylation Yields Novel Discoveries in GWAS of Colorectal Cancer

BACKGROUND

Colorectal cancer has a strong epigenetic component that is accompanied by frequent DNA methylation (DNAm) alterations in addition to heritable genetic risk. It is of interest to understand the interrelationship of germline genetics, DNAm, and colorectal cancer risk.

METHODS

We performed a genome-wide methylation quantitative trait locus (meQTL) analysis in 1,355 people, assessing the pairwise associations between genetic variants and lymphocytes methylation data. In addition, we used penalized regression with cis-genetic variants ± 1 Mb of methylation to identify genome-wide heritable DNAm. We evaluated the association of genetically predicted methylation with colorectal cancer risk based on genome-wide association studies (GWAS) of over 125,000 cases and controls using the multivariate sMiST as well as univariately via examination of marginal association with colorectal cancer risk.

RESULTS

Of the 142 known colorectal cancer GWAS loci, 47 were identified as meQTLs. We identified four novel colorectal cancer-associated loci (NID2, ATXN10, KLHDC10, and CEP41) that reside over 1 Mb outside of known colorectal cancer loci and 10 secondary signals within 1 Mb of known loci.

CONCLUSIONS

Leveraging information of DNAm regulation into genetic association of colorectal cancer risk reveals novel pathways in colorectal cancer tumorigenesis. Our summary statistics-based framework sMiST provides a powerful approach by combining information from the effect through methylation and residual direct effects of the meQTLs on disease risk. Further validation and functional follow-up of these novel pathways are needed.

IMPACT

Using genotype, DNAm, and GWAS, we identified four new colorectal cancer risk loci. We studied the landscape of genetic regulation of DNAm via single-SNP and multi-SNP meQTL analyses.

SNHG3 Affects Gastric Cancer Development by Regulating SEPT9 Methylation

Background

Gastric cancer (GC) is a common malignancy that can be formed by methylation-induced deactivation of tumor silencer genes, which is one of the key mechanisms of tumorigenesis. SEPT9 methylation, a symptomatic marker for tumors, can downregulate gene expression. Long noncoding RNA small nucleolar host gene 3 (lncRNA SNHG3) is a new type of lncRNA related to cancer. Our study investigated the mechanism of SNHG3 regulation of SEPT9 methylation and its effects on the growth, metastasis, and spread of gastric cancer cells.

Methods

Quantitative real-time PCR (qRT–PCR) was used to detect SNHG3 and miR-448 in gastric cancer, and a dual-luciferase experiment verified the effects of SNHG3, miR-448, and DNMT1. After abnormally expressing SNHG3, miR-448, and DNMT1 alone or together, methylation-specific PCR was performed to determine the methylation of SEPT9, Western blotting was performed to detect the expression of DNA methyltransferase 1 (DNMT1) and SEPT9, and Transwell, scratch, and CCK-8 assays were performed to reveal the invasion, migration, and cell growth of gastric cancer cells.

Results

We found that SNHG3 was upregulated in gastric cancer and that SNHG3 knockdown or miR-448 overexpression inhibited SEP9 methylation and therefore increased its expression, thereby inhibiting the growth, metastasis, and spread of gastric cancer cells.

Conclusion

Our study indicates that SNHG3 regulates SEPT9 methylation by targeting miR-448/DNMT1 and subsequently affecting the occurrence and development of gastric cancer.

Technical considerations in PCR-based assay design for diagnostic DNA methylation cancer biomarkers

Background

DNA methylation biomarkers for early detection, risk stratification and treatment response in cancer have been of great interest over the past decades. Nevertheless, clinical implementation of these biomarkers is limited, as only < 1% of the identified biomarkers is translated into a clinical or commercial setting. Technical factors such as a suboptimal genomic location of the assay and inefficient primer or probe design have been emphasized as important pitfalls in biomarker research. Here, we use eleven diagnostic DNA methylation biomarkers for colorectal cancer (ALX4, APC, CDKN2A, MGMT, MLH1, NDRG4, SDC2, SFRP1, SFRP2, TFPI1 and VIM), previously described in a systematic literature search, to evaluate these pitfalls.

Results

To assess the genomic assay location, the optimal genomic locations according to TCGA data were extracted and compared to the genomic locations used in the published assays for all eleven biomarkers. In addition, all primers and probes were technically evaluated according to several criteria, based on literature and expert opinion. Both assay location and assay design quality varied widely among studies.

Conclusions

Large variation in both assay location and design hinders the development of future DNA methylation biomarkers as well as inter-study comparability.

Application of amino acid ionic liquids for increasing the stability of DNA in long term storage

The structural stability of DNA is important because of its biological activity. DNAs due to their inherent chemical properties are not stable in an aqueous solution, therefore, a long period of storage of DNA at the ambient condition in bioscience is of importance. Ionic liquids (ILs) as interesting alternatives compared to organic solvents and water due to their considerable properties can be used as new agents to increase the stability of DNA for a long period of storage. In this article, molecular dynamics (MD) simulations and quantum chemistry calculations were applied to investigate the effects of amino acid ionic liquids ([BMIM][Ala], [BMIM][Gly], [BMIM][Val], [BMIM][Pro] and [BMIM][Leu]) on the dynamical behavior and the structural stability of calf thymus DNA. Based on the obtained MD results ILs enter into the solvation shell of the DNA and push away the water molecules from the DNA surface. Structural analysis shows that [BMIM]⁺ cations can occupy the DNA minor groove without disturbing the double-helical structure of DNA. ILs due to strong electrostatic and van der Waals (vdW) interactions with the DNA structure contribute to the stability of the double-helical structure. Quantum chemistry calculations indicate that the interactions between the [BMIM]⁺ cation and DNA structure has an electrostatic character. Moreover, this cation forms a more stable complex with the CGCG region of the DNA in comparison with AATT base pairs. Overall, the results of this study can provide new insight into the application of ILs for maintaining DNA stability during long-term storage.Communicated by Ramaswamy H. Sarma.

A High Methylation Level of a Novel −284 bp CpG Island in the RAMP1 Gene Promoter Is Potentially Associated with Migraine in Women

Migraine is a complex neurovascular disorder affecting one billion people worldwide, mainly females. It is characterized by attacks of moderate to severe headache pain, with associated symptoms. Receptor activity modifying protein (RAMP1) is part of the Calcitonin Gene-Related Peptide (CGRP) receptor, a pharmacological target for migraine. Epigenetic processes, such as DNA methylation, play a role in clinical presentation of various diseases. DNA methylation occurs mostly in the gene promoter and can control gene expression. We investigated the methylation state of the RAMP1 promoter in 104 female blood DNA samples: 54 migraineurs and 50 controls. We treated DNA with sodium bisulfite and performed PCR, Sanger Sequencing, and Epigenetic Sequencing Methylation (ESME) software analysis. We identified 51 CpG dinucleotides, and 5 showed methylation variability. Migraineurs had a higher number of individuals with all five CpG methylated when compared to controls (26% vs. 16%), although non-significant (p = 0.216). We also found that CpG −284 bp, related to the transcription start site (TSS), showed higher methylation levels in cases (p = 0.011). This CpG may potentially play a role in migraine, affecting RAMP1 transcription or receptor malfunctioning and/or altered CGRP binding. We hope to confirm this finding in a larger cohort and establish an epigenetic biomarker to predict female migraine risk.

PMEPA1 Serves as a Prognostic Biomarker and Correlates with Immune Infiltrates in Cervical Cancer

Emerging studies have demonstrated that Prostate transmembrane protein androgen induced 1 (PMEPA1) plays crucial roles in the carcinogenesis of many developing human tumors. However, the clinical significance of PMEPA1 expression in cervical cancer (CC) and its contribution to cancer immunity have not been investigated. In this study, we identified PMEPA1 as a survival-related gene in CC based on TCGA datasets. Univariate and multivariate analysis showed that PMEPA1 expression was an independent predictor for overall survival in CC patients. We could observe a strong negative correlation between PMEPA1 expression and PMEPA1 methylation. Two CpG sites of PMEPA1 were associated with overall survival, and one CpG site of PMEPA1 was associated with progression-free survival. The low level of PMEPA1 methylation was associated with advanced clinical stage of CC patients. KEGG assays revealed the genes associated with PMEPA1 expression were mainly enriched in several tumor-related pathways. Increased PMEPA1 expressions were observed to be positively related to high immune infiltration levels in several immune cells. Finally, the pan-cancer assays revealed that PMEPA1 expression was associated with the overall survival of UVM, PAAD, LUSC, BLCA, CESC, and LUAD. Taken together, PMEPA1 is a prognosis-related biomarker for multiple cancer types, especially CC. PMEPA1 is involved in tumor immunity, suggesting PMEPA1 may be a potential immunotherapeutic target in CC.

Ultrasensitive DNA Methylation Ratio Detection Based on the Target-Induced Nanoparticle-Coupling and Site-Specific Base Oxidation Damage for Colorectal Cancer

DNA methylation analysis holds great promise in the whole process management of cancer early screening, diagnosis, and prognosis monitoring. Nevertheless, accurate detection of target methylated DNA, especially its methylation ratio in the genome, remains challenging. Herein, we report for the first time an integrated strategy of target-induced nanoparticle-coupling and site-specific base oxidation damage for DNA methylation analysis with the assistance of well-designed nanosensors. The ultrahigh sensitivity for detecting target methylated DNA as low as 32 × 10^-17 M and high specificity for distinguishing 0.001% methylation ratio are achieved by this proposed strategy without amplification operations. Notably, the precise quantification of target DNA methylation ratio has been achieved for the first time. Through quantitative detection of target methylated DNA and methylation ratio, this proposed strategy could reliably diagnose and monitor cancer progression and treatment responses for colorectal cancer, which is superior to the clinical Septin 9 kit. It is anticipated that the proposed strategy has attractive application prospects in early diagnosis and monitoring for colorectal cancer and other various diseases.

A molecular approach integrating genomic and DNA methylation profiling for tissue of origin identification in lung-specific cancer of unknown primary

BACKGROUND

Determining the tissue of origin (TOO) is essential for managing cancer of unknown primary (CUP). In this study, we evaluated the concordance between genome profiling and DNA methylation analysis in determining TOO for lung-specific CUP and assessed their performance by comparing the clinical responses and survival outcomes of patients predicted with multiple primary or with metastatic cancer.

METHODS

We started by retrospectively screening for CUP patients who presented with both intra- and extrathoracic tumors. Tumor samples from included patients were analyzed with targeted sequencing with a 520-gene panel and targeted bisulfite sequencing. TOO inferences were made in parallel via an algorithm using genome profiles and time interval between tumors and via machine learning-based classification of DNA methylation profiles.

RESULTS

Four hundred patients were screened retrospectively. Excluding patients definitively diagnosed with conventional diagnostic work-up or without available samples, 16 CUP patients were included. Both molecular approaches alone enabled inference of clonality for all analyzed patients. Genome profile enabled TOO inference for 43.8% (7/16) patients, and the percentage rose to 68.8% (11/16) after considering inter-tumor time lag. On the other hand, DNA methylation analysis was conclusive for TOO prediction for 100% (14/14) patients with available samples. The two approaches gave 100% (9/9) concordant inferences regarding clonality and TOO identity. Moreover, patients predicted with metastatic disease showed significantly shorter overall survival than those with multiple primary tumors.

CONCLUSIONS

Genome and DNA methylation profiling have shown promise as individual analysis for TOO identification. This study demonstrated the feasibility of incorporating the two methods and proposes an integrative scheme to facilitate diagnosing and treating lung-specific CUPs.

CCNA2 as an Immunological Biomarker Encompassing Tumor Microenvironment and Therapeutic Response in Multiple Cancer Types

Background

Cancer is a major threat to human health worldwide. Although recent innovations and advances in early detection and effective therapies such as targeted drugs and immune checkpoint inhibitors have saved more lives of cancer patients and improved their quality of life, our knowledge about cancer remains largely unknown. CCNA2 belongs to the cell cyclin family and has been demonstrated to be a tumorigenic gene in multiple solid tumor types. The aim of the present study was to make a comprehensive analysis on the role of CCNA2 at a pancancer level.

Methods

Multidatabases were collected to evaluate the different expression, prognostic value, DNA methylation, tumor mutation burden, microsatellite instability, mismatch repair, tumor immune microenvironment, and drug sensitivity of CCNA2 across pancancer. IHC was utilized to validate the expression and prognostic value of CCNA2 in ccRCC patients from SMMU cohort.

Results

CCNA2 was differentially expressed in most cancer types vs. normal tissues. CCNA2 may significantly influence the prognosis of multiple cancer types, especially clear cell renal cell carcinoma (ccRCC). CCNA2 was also frequently mutated in most cancer types. Notably, CCNA2 was significantly correlated with immune cell infiltration and immune checkpoint inhibitory genes. In addition, CCNA2 was also strongly related to drug resistance.

Conclusion

CCNA2 may prove to be a new biomarker for prognostic prediction, tumor immunity assessment, and drug susceptibility evaluation in pancancer level, especially in ccRCC.

The Expression Pattern of Ferroptosis-Related Genes in Colon Adenocarcinoma: Highly Correlated to Tumor Microenvironment Characteristics

In the latest literatures, ferroptosis caused by T cells in cancerous cells provided new insights of improving curative effect of the PD-1/PD-L1 antibody. The microenvironment on which tumor cells develop and survive was also emphasized as its crucial role in tumor occurrence, development, metastasis and immune escape. Thus, the interaction of ferroptosis related genes and tumor microenvironment (TME) was urgently be detected in a comprehensive perspective. We comprehensively evaluated the transcriptional feature of ferroptosis related genes in colon adenocarcinoma (COAD), and systematically associated these ferroptosis subtypes with DNA damage repair (DDR) and TME characteristics. We found two unique patterns of ferroptosis characterized by distinct biological pathways activation. We also demonstrated that FRG score constructed based on ferroptosis subtypes has a significant correlation with prognosis of colon cancer and could act as an independent prognostic biomarker for predicting patients’ survival. The higher immune infiltrating level, immune functional pathways activation was observed in the high FRG score group. Furthermore, these results were verified by an independent external GEO cohort. This work revealed ferroptosis was highly associated with TME complexity and diversity. A novel ferroptosis subtypes related gene scoring system can be used for prognostic prediction in COAD. Targeting ferroptosis may be a therapeutic alternative for COAD.

The World of Oral Cancer and Its Risk Factors Viewed from the Aspect of MicroRNA Expression Patterns

Oral cancer is one of the leading causes of death worldwide, with a reported 5-year survival rate of around 50% after treatment. Epigenetic modifications are considered to have a key role in oral carcinogenesis due to histone modifications, aberrant DNA methylation, and altered expression of miRNAs. MicroRNAs (miRNAs) are small non-coding RNAs that have a key role in cancer development by regulating signaling pathways involved in carcinogenesis. MiRNA deregulation identified in oral cancer has led to the idea of using them as potential biomarkers for early diagnosis, prognosis, and the development of novel therapeutic strategies. In recent years, a key role has been observed for risk factors in preventing and treating this malignancy. The purpose of this review is to summarize the recent knowledge about the altered mechanisms of oral cancer due to risk factors and the role of miRNAs in these mechanisms.

Update of gene expression/methylation and MiRNA profiling in colorectal cancer; application in diagnosis, prognosis, and targeted therapy

Background

Colorectal cancer is one of the most deadliest malignancies worldwide. Due to the dearth of appropriate biomarkers, the diagnosis of this mortal disease is usually deferred, in its turn, culminating in the failure of prevention. By the same token, proper biomarkers are at play in determining the quality of prognosis. In other words, the survival rate is contingent upon the regulation of such biomarkers.

Materials and methods

The information regarding expression (GSE41258, and GSE31905), methylation (GSE101764), and miRNA (dbDEMC) were downloaded. MEXPRESS and GEPIA confirmed the validated differentially expressed/methylated genes using TCGA data. Taking advantage of the correlation plots and receiver-operating-characteristic (ROC) curves, expression and methylation profiles were compared. The interactions between validated differentially expressed genes and differentially expressed miRNA were recognized and visualized by miRTarBase and Cytoscape, respectively. Then, the protein-protein interaction (PPI) network and hub genes were established via STRING and Cytohubba plugin. Utilizing R packages (DOSE, Enrichplot, and clusterProfiler) and DAVID database, the Functional Enrichment analysis and the detection of KEGG pathways were performed. Ultimately, in order to recognize the prognostic value of found biomarkers, they were evaluated through drawing survival plots for CRC patients.

Results

In this research, we found an expression profile (with 13 novel genes), a methylation profile (with two novel genes), and a miRNA profile with diagnostic value. Concerning diagnosis, the expression profile was evaluated more powerful in comparison with the methylation profile. Furthermore, a prognosis-related expression profile was detected.

Conclusion

In addition to diagnostic- and prognostic-applicability, the discerned profiles can assist in targeted therapy and current therapeutic strategies.

The prognostic effect of PNN in digestive tract cancers and its correlation with the tumor immune landscape in colon adenocarcinoma

Background

The present study investigated the expression, mutation, and methylation profile of PNN and its prognostic value in digestive tract cancers. The disparities in signaling pathways and the immune landscape in colon adenocarcinoma (COAD) based on PNN expression were specifically explored.

Methods

The expression, mutation, methylation levels of PNN, and survival data in esophageal cancer, gastric adenocarcinoma, COAD, and rectal adenocarcinoma were evaluated using several bioinformatic databases. Gene Ontology (GO) enrichment analysis and gene set enrichment analysis (GSEA) were performed to investigate the enriched biological functions and pathways in COAD. Several acknowledged bioinformatic algorithms were employed to assess the correlation between PNN expression and the tumor immune landscape in COAD.

Results

PNN was upregulated and remarkably related to tumor stage in digestive tract cancers. High expression of PNN was positively associated with poor progression‐free survival and overall survival time, specifically in COAD. PNN expression was identified as an independent prognostic factor in COAD. GO and GSEA analyses revealed that PNN participates in multiple biological processes underlying carcinogenicity in COAD. Further investigation showed that PNN expression was significantly associated with tumor‐infiltrating immune cells, immune cell functions, and several immune checkpoints in COAD. The PNN low expression group had a lower tumor immune dysfunction and exclusion (TIDE) score and a higher immunophenoscore (IPS), indicating a better response to immunotherapy.

Conclusion

PNN was highly expressed in digestive tract cancers and could act as an independent prognostic factor and a response predictor for immunotherapy in COAD.