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

Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response

BACKGROUND

Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes.

METHODS

We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts.

RESULTS

We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment.

CONCLUSIONS

Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

DNA methylation profiling identifies epigenetic signatures of early gastric cancer

Research on the DNA methylation status of gastric cancer (GC) has primarily focused on identifying invasive GC to develop biomarkers for diagnostic. However, DNA methylation in noninvasive GC remains unclear. We conducted a comprehensive DNA methylation profiling study of differentiated-type intramucosal GCs (IMCs). Illumina 850K microarrays were utilized to assess the DNA methylation profiles of formalin-fixed paraffin-embedded tissues from eight patients who were Epstein-Barr virus-negative and DNA mismatch repair proficient, including IMCs and paired adjacent nontumor mucosa. Gene expression profiling microarray data from the GEO database were analyzed via bioinformatics to identify candidate methylation genes. The final validation was conducted using quantitative real-time PCR, the TCGA methylation database, and single-sample gene set enrichment analysis (GSEA). Genome-wide DNA methylation profiling revealed a global decrease in methylation in IMCs compared with nontumor tissues. Differential methylation analysis between IMCs and nontumor tissues identified 449 differentially methylated probes, with a majority of sites showing hypomethylation in IMCs compared with nontumor tissues (66.1% vs 33.9%). Integrating two RNA-seq microarray datasets, we found one hypomethylation-upregulated gene: eEF1A2, overlapped with our DNA methylation data. The mRNA expression of eEF1A2 was higher in twenty-four IMC tissues than in their paired adjacent nontumor tissues. GSEA indicated that the functions of eEF1A2 were associated with the development of IMCs. Furthermore, TCGA data indicated that eEF1A2 is hypomethylated in advanced GC. Our study illustrates the implications of DNA methylation alterations in IMCs and suggests that aberrant hypomethylation and high mRNA expression of eEF1A2 might play a role in IMCs development.

Potential crosstalk between SPP1 + TAMs and CD8 + exhausted T cells promotes an immunosuppressive environment in gastric metastatic cancer

BACKGROUND

Immunotherapy brings new hope to patients with advanced gastric cancer. However, liver metastases can reduce the efficacy of immunotherapy in patients. Tumor-associated macrophages (TAMs) may be the cause of this reduction in efficacy. SPP1 + TAMs are considered to have immunosuppressive properties. We aimed to investigate the involvement of SPP1 + TAMs in the metastasis of gastric cancer.

METHODS

The single-cell transcriptome was combined with batched BULK datasets for analysis. Animal models were used to verify the analysis results.

RESULTS

We reveal the interaction of SPP1 + TAMs with CD8 + exhausted T cells in metastatic cancer. Among these interactions, GDF15-TGFBR2 may play a key immunosuppressive role. We constructed an LR score to quantify interactions based on ligands and receptors. The LR score is highly correlated with various immune features and clinical molecular subtypes. The LR score may also guide the prediction of the efficacy of immunotherapy and prognosis.

CONCLUSIONS

The crosstalk between SPP1 + TAMs and CD8 + exhausted T cells plays a key immunosuppressive role in the gastric metastatic cancer microenvironment.

Comprehensive analysis reveals the prognostic and immunogenic characteristics of DNA methylation regulators in lung adenocarcinoma

DNA methylation regulators (DMRs) play a key role in DNA methylation, thus mediating tumor occurrence, metastasis, and immunomodulation. However, the effects of DMRs on clinical outcomes and immunotherapy response remain unexplored in lung adenocarcinoma (LUAD). In this study, eight LUAD cohorts and one immunotherapeutic cohort of lung cancer were utilized. We constructed a DNA methylation regulators-related signature (DMRRS) using univariate and multivariate COX regression analysis. The DMRRS-defined low-risk group was preferentially associated with favorable prognosis, tumor-inhibiting microenvironment, more sensitivity to several targeted therapy drugs, and better immune response. Afterward, the prognostic value and predictive potential in immunotherapy response were validated. Collectively, our findings uncovered that the DMRRS was closely associated with the tumor immune microenvironment and could effectively predict the clinical outcome and immune response of LUAD patients.

DNA methylation regulator-mediated modification patterns and risk of intracranial aneurysm: a multi-omics and epigenome-wide association study integrating machine learning, Mendelian randomization, eQTL and mQTL data

BACKGROUND

Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions.

METHODS

We employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA.

RESULTS

We identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition.

CONCLUSION

These insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis.

Methylation across the central dogma in health and diseases: new therapeutic strategies

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

High Expression of Ten Eleven Translocation 1 Is Associated with Poor Prognosis in Hepatocellular Carcinoma

Background

DNA methylation patterns have been found to be distinct between tumor and normal patients. However, the effect of DNA demethylation enzymes, ten eleven translocation (TET) proteins, has not been comprehensively characterized in liver cancer. In this research, we sought to unravel the linkage of TET proteins with prognosis, immune characteristics and biological pathways in hepatocellular carcinoma (HCC).

Materials and Methods

Four independent datasets with gene expression data and clinical data of HCC samples were downloaded from public databases. CIBERSORT, single sample Gene Set Enrichment Analysis (ssGSEA), MCP-counter, and TIMER were implemented to evaluate immune cell infiltration. limma was employed to screen differentially expressed genes (DEGs) between two groups. The demethylation-related risk model was established by using univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO), and stepwise Akaike information criterion (stepAIC).

Results

TET1 was significantly higher expressed in tumor samples than that in normal samples. HCC patients with advanced stages (III+IV) and grades (G3+G4) had higher TET1 expression compared to early stages (I+II) and grades (G1+G2). HCC samples with high TET1 expression had worse prognosis than that with low expression. High and low TET1 expression groups had distinct immune cell infiltration and response to immunotherapy and chemotherapy. We identified 90 DEGs related to DNA demethylation in high vs. low TET1 expression groups. Furthermore, we established a risk model based on 90 DEGs containing seven key prognostic genes (SERPINH1, CDC20, HACD2, SPHK1, UGT2B15, SLC1A5, and CYP2C9) with effectiveness and robustness in predicting HCC prognosis.

Conclusions

Our study suggested TET1 as a potential indicator in HCC progression. TET1 was closely involved in immune infiltration and activation of oncogenic pathways. The DNA demethylation-related risk model was potential to be applied for predicting HCC prognosis in clinics.

Reshaping the tumour immune microenvironment in solid tumours via tumour cell and immune cell DNA methylation: from mechanisms to therapeutics

In recent years, the tumour microenvironment (TME) of solid tumours has attracted more and more attention from researchers, especially those non-tumour components such as immune cells. Infiltration of various immune cells causes tumour immune microenvironment (TIME) heterogeneity, and results in different therapeutic effects. Accumulating evidence showed that DNA methylation plays a crucial role in remodelling TIME and is associated with the response towards immune checkpoint inhibitors (ICIs). During carcinogenesis, DNA methylation profoundly changes, specifically, there is a global loss of DNA methylation and increased DNA methylation at the promoters of suppressor genes. Immune cell differentiation is disturbed, and exclusion of immune cells from the TME occurs at least in part due to DNA methylation reprogramming. Therefore, pharmaceutical interventions targeting DNA methylation are promising. DNA methyltransferase inhibitors (DNMTis) enhance antitumor immunity by inducing transcription of transposable elements and consequent viral mimicry. DNMTis upregulate the expression of tumour antigens, mediate immune cells recruitment and reactivate exhausted immune cells. In preclinical studies, DNMTis have shown synergistic effect when combined with immunotherapies, suggesting new strategies to treat refractory solid tumours.

Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer

Background

Currently, a very small number of patients with colorectal cancer (CRC) respond to immune checkpoint inhibitor (ICI) treatment. Therefore, there is an urgent need to investigate effective biomarkers to determine the responsiveness to ICI treatment. Recently, aberrant 5-methylcytosine (m⁵C) RNA modification has emerged as a key player in the pathogenesis of cancer. Thus, we aimed to explore the predictive signature based on m⁵C regulator-related genes for characterizing the immune landscapes and predicting the prognosis and response to therapies.

Methods

The Cancer Genome Atlas (TCGA) cohort was used as the training set, while GEO data sets, real-time quantitative PCR (RT-qPCR) analysis from paired frozen tissues, and immunohistochemistry (IHC) data from tissue microarray (TMA) were used for validation. We constructed a novel signature based on three m⁵C regulator-related genes in patients with rectal adenocarcinoma (READ) using a least absolute shrinkage and selection operator (LASSO)-Cox regression and unsupervised consensus clustering analyses. Additionally, we correlated the three-gene signature risk model with the tumor immune microenvironment, immunotherapy efficiency, and potential applicable drugs.

Results

The m⁵C methylation-based signature was an independent prognostic factor, where low-risk patients showed a stronger immunoreactivity phenotype and a superior response to ICI therapy. Conversely, the high-risk patients had enriched pathways of cancer hallmarks and presented immune-suppressive state, which demonstrated that they are more insensitive to immunotherapy. Additionally, the signature markedly correlated with drug susceptibility.

Conclusions

We developed a reliable m⁵C regulator-based risk model to predict the prognosis, clarify the molecular and tumor microenvironment status, and identify patients who would benefit from immunotherapy or chemotherapy. Our study could provide vital guidance to improve prognostic stratification and optimize personalized therapeutic strategies for patients with rectal cancer.

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.

Expression profiles of m6A RNA methylation regulators, PD-L1 and immune infiltrates in gastric cancer

Gastric cancer is the fourth most frequent cancer and has a high death rate. Immunotherapy represented by PD-1 has brought hope for the treatment of advanced gastric cancer. Methylation of the m6A genes is linked to the onset and progression of numerous cancers, but there are few studies on gastric cancer. The main purpose of this study aims to analyze the relationship between m6A RNA methylation regulators, PD-L1, prognosis and tumor immune microenvironment (TIME) in gastric cancer. The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases were used to acquire transcriptomic data and clinical information from gastric cancer patients. The changes in m6A regulator expression levels in gastric cancer tissues and normal tissues were studied. Consensus clustering analysis was used to separate gastric cancer samples into two categories. We employed Least Absolute Shrinkage, Selection Operator (LASSO) Cox regression analysis, Gene Set Enrichment Analysis (GSEA), and cBioPortal to analyze the m6A regulators, PD-L1 and TIME in gastric cancer. In gastric cancer tissues, the majority of m6A regulatory factors are considerably overexpressed. Two gastric cancer subgroups (Cluster1/2) based on consensus clustering of 21 m6A regulators. PD-L1 and PD-1 expression levels were significantly higher in gastric cancer tissues, and they were significantly linked with METTL3, WTAP, HNRNPD, ZC3H7B, METTL14, FTO, PCIF1, HNRNPC, YTHDF1 and YTDHF2. Cluster1 showed a large increase in resting memory CD4⁺ T cells, regulatory T cells, naïve B cells, active NK cells, and resting Mast cells. Cluster1 and Cluster2 were shown to be involved in numerous critical signaling pathways, including base excision repair, cell cycle, nucleotide excision repair, RNA degradation, and spliceosome pathways. Gastric cancer RiskScores based on prognostic factors have been found as independent prognostic indicators. The amount of tumor-infiltrating immune cells is dynamically affected by changes in the copy number of m6A methylation regulators associated with TIME.

Construction and Validation of an Epigenetic Regulator Signature as A Novel Biomarker For Prognosis, Immunotherapy, And Chemotherapy In Hepatocellular Carcinoma

Background

Epigenetic modification regulates various aspects of cancer biology, from tumor growth and invasion to immune microenvironment modulation. Whether epigenetic regulators (EGRs) can decide tumor malignant degree and risk of immune evasion in liver hepatocellular carcinoma (LIHC) remains unclear.

Method

An EGR signature called “EGRscore” was constructed based on bulk RNA-seq data of EGR in hepatocellular carcinoma (HCC). The correlation between EGRscore and overall survival (OS) was validated in HCC cohorts and other tumor cohorts. Mutation profiles, copy number alterations (CNAs), enriched pathways, and response to immunotherapy and chemotherapy were compared between EGRscore-high and EGRscore-low patients.

Results

We found that EGRscore was associated with OS in HCC as well as several tumors including glioma, uveal melanoma (UVM), and kidney tumors. A mechanism study demonstrated that the distinct mutation profile of TP53 was present in EGRscore-high and EGRscore-low patients. Meanwhile, EGRscore-low patients were characterized with immune cells that promote killing tumors. Furthermore, EGRscore was associated with genes regulating drug resistance in HCC. Finally, we indicated that EGRscore-low patients had higher response rates to immunotherapy and targeted therapy.

Conclusions

EGRscore could be used to distinguish OS, tumor progression, mutation pattern, and immune microenvironment. The present study contributes to improving hepatocellular carcinoma patient prognosis and predicting response to immunotherapy.

Transcriptome Profiling of N7-Methylguanosine Modification of Messenger RNA in Drug-Resistant Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive hematological tumor caused by the malignant transformation of myeloid progenitor cells. Although intensive chemotherapy leads to an initial therapeutic response, relapse due to drug resistance remains a significant challenge. In recent years, accumulating evidence has suggested that post-transcriptional methylation modifications are strongly associated with tumorigenesis. However, the mRNA profile of m7G modification in AML and its role in drug-resistant AML are unknown. In this study, we used MeRIP-seq technology to establish the first transcriptome-wide m7G methylome profile for AML and drug-resistant AML cells, and differences in m7G between the two groups were analyzed. In addition, bioinformatics analysis was conducted to explore the function of m7G-specific methylated transcripts. We found significant differences in m7G mRNA modification between AML and drug-resistant AML cells. Furthermore, bioinformatics analysis revealed that differential m7G-modified mRNAs were associated with a wide range of cellular functions. Importantly, down-methylated m7G modification was significantly enriched in ABC transporter-related mRNAs, which are widely recognized to play a key role in multidrug resistance. Our results provide new insights into a novel function of m7G methylation in drug resistance progression of AML.

TFPI inhibits breast cancer progression by suppressing ERK/p38 MAPK signaling pathway

BACKGROUND

Tissue factor pathway inhibitor-1 (TFPI) is a serine protease inhibitor, which is responsible for inactivating TF-induced coagulation. Recently, increasing studies revealed that TFPI was lowly expressed in tumor cells and exhibited the antitumor activity.

OBJECTIVE

The aim of this study was to explore the role and underlying molecular mechanisms of TFPI in breast cancer.

METHODS

The expression and prognostic value of TFPI were analyzed using UALCAN and Kaplan-Meier plotter website. The expression level of TFPI in breast cancer tissues and cells was examined by immunohistochemistry (IHC) and western blot analysis, respectively. Cellular proliferation was evaluated by CCK-8 and colony formation assays. Cell migration and invasion were determined by transwell assay. The methylation level of TFPI promoter was determined by methylation-specific PCR.

RESULTS

TFPI expression was significantly lower in breast cancer tissues and cells compared to normal breast tissues and normal breast cells. Patients with low TFPI levels showed worse overall survival (OS). Furthermore, overexpression of TFPI significantly inhibited the proliferation, migration and invasion of breast cancer cells. Conversely, knockdown of TFPI promoted the proliferation, migration and invasion of breast cancer cells. Mechanistically, TFPI inhibited the ERK/p38 MAPK signaling pathway in breast cancer. Moreover, DNA hypermethylation of TFPI promoter was responsible for the downregulation of TFPI in breast cancer cells.

CONCLUSION

TFPI inhibited breast cancer cell proliferation, migration and invasion through inhibition of the ERK/p38 MAPK signaling pathway, suggesting that TFPI may serve as a novel prognostic biomarker and therapeutic target for breast cancer.

Molecular subtypes, prognostic and immunotherapeutic relevant gene signatures mediated by DNA methylation regulators in hepatocellular carcinoma

Growing evidence has revealed the crucial role of epigenetics in tumor progression and immune response. However, the molecular subtypes and their microenvironment characterization mediated by DNA methylation regulators in hepatocellular carcinoma remain little known. In this study, we comprehensively integrated the transcriptome profiling of twenty DNA methylation regulators in hepatocellular carcinoma. Consensus clustering was used to identify distinct methylation regulator-related molecular subtypes. The prognostic DMS signature was constructed using principal components analysis. Most regulators experienced a low genomic variation, but we found a remarkably difference in mRNA expression of these regulators between normal and tumor tissues. Three distinct methylation regulator-related molecular subtypes were successfully identified according to the expression of 20 regulators, which had substantially different biological characteristics and prognosis. The classic carcinogenic pathways and stromal activity including TGF-beta, p53 and WNT signaling pathway were significantly activated in subtype B, leading to a survival inferiority in subtype B compared to other two subtypes. Further analysis demonstrated the constructed DMS signature was an independent predictive biomarker in patient prognosis. Two anti-checkpoint immunotherapy cohorts demonstrated patients with high DMS presented significantly improved treatment advantages and enhanced responses especially the survival prolonged. Generally, the high DMS groups improved more than 15% clinical response to immunotherapy than low DMS groups. In conclusion, this study identified three DNA methylation regulator-related subtypes with distinct clinical, molecular and biological characteristics, and constructed a prognostic and immunotherapeutic relevant gene signature. It might help to promote individualized immunotherapy for hepatocellular carcinoma from the perspective DNA methylation regulators.

Crosstalk of Histone and RNA Modifications Identified a Stromal-Activated Subtype with Poor Survival and Resistance to Immunotherapy in Gastric Cancer

Emerging evidence has revealed the pivotal role of epigenetic modifications in shaping the tumor microenvironment (TME). However, crosstalk between different modification types and their clinical relevance in cancers remain largely unexplored. In this study, using ChIP/MeRIP-seq data of seven human gastric cell lines, we systematically characterized the crosstalk of four epigenetic modification types including H3K4me1, H3K4me3, H3K27ac, and N6-methyladenosine (m6A) and identified a recurrent subtype with high FTO expression and low HDAC1 expression across three independent gastric cancer (GC) cohorts, which we named the epigenetic-modification-dysregulated (EMD) subtype. Patients of the EMD subtype were featured with poor survival, stromal activation, and immune suppression. Extensive relevance to clinical characteristics was observed in the EMD subtype, including the Lauren classification, MSI status, histological grade, TNM stage, the Asian Cancer Research Group classification, and the immune/fibrotic classification. An EMD score was then constructed using WGCNA and ssGSEA algorithms, to precisely recognize the EMD subtype and indicate prognosis and response to immunotherapy in multiple independent GC cohorts. Correlations of the EMD score with tumor mutation burden, tumor purity, aneuploidy score, tumorigenic pathways, TME characteristics, and FTO/HDAC1 ratio were measured. In vitro experiments were performed to demonstrate the correlation between FTO and the epithelial–mesenchymal transition pathway, which suggested FTO as a targetable vulnerability for GC patients with a high EMD score. Altogether, by comprehensively analyzing the epigenetic modification patterns of 1518 GC patients, we identified a novel stromal-activated subtype with poor survival and resistance to immunotherapy, which might benefit from the combined immune checkpoint inhibition therapy with FTO inhibition.

Cross talk between RNA modification writers and tumor development as a basis for guiding personalized therapy of gastric cancer

Background

Gastric cancer (GC) shows high metastasis and low survival. RNA modification writers play critical roles in tumor development. This study examined the clinical significance of RNA modification writers in GC prognosis based on four types of adenosine modifications (m¹A, m⁶A, APA and A-to-I).

Results

Writers demonstrated high mutation and expression in GC patients. Different expressions of 26 RNA modification writers were differentially associated with GC prognosis. High-WM score group appeared worse overall survival, higher immune infiltration and activation of EMT pathways than low-WM score group. WM score was correlated with both miRNAs-targeted signaling pathways and patients’ sensitivity to chemotherapeutic drugs and efficacy of immunotherapy.

Conclusions

This study further revealed the close association between adenosine-related RNA modifications and progression of GC. A cross talk between EMT and RNA modification was identified to be one of the mechanisms underlying GC development. Our WM scoring system could serve as a clinical indicator for predicting GC prognosis. Importantly, the WM score could guide personalized treatments such as chemotherapy and immunotherapy for GC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-022-00386-z.

Modification Patterns of DNA Methylation-Related lncRNAs Regulating Genomic Instability for Improving the Clinical Outcomes and Tumour Microenvironment Characterisation of Lower-Grade Gliomas

Background: DNA methylation is an important epigenetic modification that affects genomic instability and regulates gene expression. Long non-coding RNAs (lncRNAs) modulate gene expression by interacting with chromosomal modifications or remodelling factors. It is urgently needed to evaluate the effects of DNA methylation-related lncRNAs (DMlncRNAs) on genome instability and further investigate the mechanism of action of DMlncRNAs in mediating the progression of lower-grade gliomas (LGGs) and their impact on the immune microenvironment.

Methods: LGG transcriptome data, somatic mutation profiles and clinical features analysed in the present study were obtained from the CGGA, GEO and TCGA databases. Univariate, multivariate Cox and Lasso regression analyses were performed to establish a DMlncRNA signature. The KEGG and GO analyses were performed to screen for pathways and biological functions associated with key genes. The ESTIMATE and CIBERSORT algorithms were used to determine the level of immune cells in LGGs and the immune microenvironment fraction. In addition, DMlncRNAs were assessed using survival analysis, ROC curves, correlation analysis, external validation, independent prognostic analysis, clinical stratification analysis and qRT-PCR.

Results: We identified five DMlncRNAs with prognostic value for LGGs and established a prognostic signature using them. The Kaplan–Meier analysis revealed 10-years survival rate of 10.10% [95% confidence interval (CI): 3.27–31.40%] in high-risk patients and 57.28% (95% CI: 43.17–76.00%) in low-risk patients. The hazard ratio (HR) and 95% CI of risk scores were 1.013 and 1.009–1.017 (p < 0.001), respectively, based on the univariate Cox regression analysis and 1.009 and 1.004–1.013 (p < 0.001), respectively, based on the multivariate Cox regression analysis. Therefore, the five-lncRNAs were identified as independent prognostic markers for patients with LGGs. Furthermore, GO and KEGG analyses revealed that these lncRNAs are involved in the prognosis and tumorigenesis of LGGs by regulating cancer pathways and DNA methylation.

Conclusion: The findings of the study provide key information regarding the functions of lncRNAs in DNA methylation and reveal that DNA methylation can regulate tumour progression through modulation of the immune microenvironment and genomic instability. The identified prognostic lncRNAs have high potential for clinical grouping of patients with LGGs to ensure effective treatment and management.

Molecular classification reveals the diverse genetic and prognostic features of gastric cancer: A multi-omics consensus ensemble clustering

BACKGROUND

Globally, gastric cancer (GC) is the fifth most common tumor. It is necessary to identify novel molecular subtypes to guide patient selection for specific target therapeutic benefits.

METHODS

Multi-omics data, including transcriptomics RNA-sequencing (mRNA, LncRNA, miRNA), DNA methylation, and gene mutations in the TCGA-STAD cohort were used for the clustering. Ten classical clustering algorithms were executed to recognize patients with different molecular features using the "MOVICS" package in R. The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The differential distribution of gene mutations, copy number alterations, and tumor mutation burden was compared, and potential responses to immunotherapy and chemotherapy were also assessed.

RESULTS

Two molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with consensus ensembles. Patients in the CS1 group had a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) as compared to those in the CS2 group. Extracellular associated biological process activation was higher in the CS1 group, while the CS2 group displayed the enhanced activation of cell cycle-associated pathways. Significantly higher total mutation numbers and neoantigens were observed in the CS2 group, along with specific mutations in TTN, MUC16, and ARID1A. Higher infiltration of immunocytes was also observed in the CS2 group, reflective of the potential immunotherapeutic benefits. Moreover, the CS2 group could also respond to 5-fluorouracil, cisplatin, and paclitaxel. The similar diversity in clinical outcomes between CS1 and CS2 groups was successfully validated in the external cohorts, GSE62254, GSE26253, GSE15459, and GSE84437.

CONCLUSION

The findings provided novel insights into the GC subtypes through integrative analysis of five -omics data by ten clustering algorithms. These could provide potential clinical therapeutic targets based on the specific molecular features.

DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer

Background

An increasing number of studies have indicated a close link between DNA methylation and tumor metabolism. However, the overall influence of DNA methylation on tumor metabolic characteristics in prostate cancer (PCa) remains unclear.

Methods

We first explored the subtypes of DNA methylation modification regulators and tumor metabolic features of 1,205 PCa samples using clustering analysis and gene set variation analysis based on the mRNA levels of DNA methylation modification regulators. A DNA methylation-related score (DMS) was calculated using principal component analysis and the DNA methylation modification-related gene signatures to quantify DNA methylation characteristics. We then performed a meta-analysis to identify the hazard ratio of DMS in the six cohorts. In addition, a nomogram was drawn using univariate and multivariate Cox analyses based on the DMS and clinical variables. Finally, a drug sensitivity analysis of the DMS was performed based on the genomics of drug sensitivity in cancer datasets.

Results

Three PCa clusters showing different DNA methylation modification patterns and tumor metabolic features were identified. A DMS system was established to quantify the characteristics of DNA methylation modification. PCa samples showed a differential metabolic landscape between the high and low DMS groups. The prognostic value of the DMS and nomogram was independently validated in multiple cohorts. A high DMS was associated with increases in the tumor mutation burden, copy number variation, and microsatellite instability; high tumor heterogeneity; and poor prognosis. Finally, DMS was closely related to different types of antitumor treatment.

Conclusion

Improving the understanding of tumor metabolism by characterizing DNA methylation modification patterns and using the DMS may help clinicians predict prognosis and aid in more personalized antitumor therapy strategies for PCa.

TNF Patterns and Tumor Microenvironment Characterization in Head and Neck Squamous Cell Carcinoma

Background

HNSCC is a heterogeneous disease, which arises from distinct anatomic subsites, associates with various risk factors and possesses diverse molecular pathological features. Generally, HNSCC is considered as an immunosuppressive disease, characterized by abnormal tumor immune microenvironment. The TNF family plays a crucial role in the survival, proliferation, differentiation, and effector functions in both immune and non-immune cells. However, the expression patterns of TNF in HNSCC remains to be systematically analyzed.

Methods

We downloaded transcriptional profile data of HNSCC from TCGA and GEO datasets. Unsupervised clustering methods were used to identify different TNF patterns and classify patients for further analysis. PCA was conducted to construct a TNF relevant score, which we called risk score.

Results

In this study, we systematically evaluated the patterns of TNF family and tumor immune microenvironment characteristics of HNSCC patients by clustering the expression of 46 members of TNF family. We identified two subtypes with distinct clinical and immune characteristics in HNSCC and constructed a risk scoring system based on the expression profile of TNF family genes.

Conclusion

Risk score serves as a reliable predictor of overall survival, clinical characteristics, and immune cell infiltration, which has the potential to be applied as a valuable biomarker for HNSCC immunotherapy.

A Signature-Based Classification of Gastric Cancer That Stratifies Tumor Immunity and Predicts Responses to PD-1 Inhibitors

Gastric cancer is a leading cause of cancer-related deaths with considerable heterogeneity among patients. Appropriate classifications are essential for prognosis prediction and individualized treatment. Although immunotherapy showed potential efficacy in a portion of patients with gastric cancer, few studies have tried to classify gastric cancer specifically based on immune signatures. In this study, we established a 3-subtype cluster with low (C_LIM), medium (C_MIM), and high (C_HIM) enrichment of immune signatures based on immunogenomic profiling. We validated the classification in multiple independent datasets. The C_HIM subtype exhibited a relatively better prognosis and showed features of “hot tumors”, including low tumor purity, high stromal components, overexpression of immune checkpoint molecules, and enriched tumor-infiltrated immune cells (activated T cells and macrophages). In addition, C_HIM tumors were also characterized by frequent ARID1A mutation, rare TP53 mutation, hypermethylation status, and altered protein expression (HER2, β-catenin, Cyclin E1, PREX1, LCK, PD-L1, Transglutaminase, and cleaved Caspase 7). By Gene Set Variation Analysis, “TGFβ signaling pathway” and “GAP junction” were enriched in C_LIM tumors and inversely correlated with CD8⁺ and CD4⁺ T cell infiltration. Of note, the C_HIM patients showed a higher response rate to immunotherapy (44.4% vs. 11.1% and 16.7%) and a more prolonged progression-free survival (4.83 vs. 1.86 and 2.75 months) than C_MIM and C_LIM patients in a microsatellite-independent manner. In conclusion, the new immune signature-based subtypes have potential therapeutic and prognostic implications for gastric cancer management, especially immunotherapy.