Hypermethylation of PDX1, EN2, and MSX1 predicts the prognosis of colorectal cancer

Understanding the role of DNA methylation in colorectal cancer: Mechanisms, detection, and clinical significance

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.

Identification of potential biomarkers for aging diagnosis of mesenchymal stem cells derived from the aged donors

BACKGROUND

The clinical application of human bone-marrow derived mesenchymal stem cells (MSCs) for the treatment of refractory diseases has achieved remarkable results. However, there is a need for a systematic evaluation of the quality and safety of MSCs sourced from donors. In this study, we sought to assess one potential factor that might impact quality, namely the age of the donor.

METHODS

We downloaded two data sets from each of two Gene Expression Omnibus (GEO), GSE39035 and GSE97311 databases, namely samples form young (< 65 years of age) and old (> 65) donor groups. Through, bioinformatics analysis and experimental validation to these retrieved data, we found that MSCs derived from aged donors can lead to differential expression of gene profiles compared with those from young donors, and potentially affect the function of MSCs, and may even induce malignant tumors.

RESULTS

We identified a total of 337 differentially expressed genes (DEGs), including two upregulated and eight downregulated genes from the databases of both GSE39035 and GSE97311. We further identified 13 hub genes. Six of them, TBX15, IGF1, GATA2, PITX2, SNAI1 and VCAN, were highly expressed in many human malignancies in Human Protein Atlas database. In the MSCs in vitro senescent cell model, qPCR analysis validated that all six hub genes were highly expressed in senescent MSCs. Our findings confirm that aged donors of MSCs have a significant effect on gene expression profiles. The MSCs from old donors have the potential to cause a variety of malignancies. These TBX15, IGF1, GATA2, PITX2, SNAI1, VCAN genes could be used as potential biomarkers to diagnosis aging state of donor MSCs, and evaluate whether MSCs derived from an aged donor could be used for therapy in the clinic. Our findings provide a diagnostic basis for the clinical use of MSCs to treat a variety of diseases.

CONCLUSIONS

Therefore, our findings not only provide guidance for the safe and standardized use of MSCs in the clinic for the treatment of various diseases, but also provide insights into the use of cell regeneration approaches to reverse aging and support rejuvenation.

Single-cell RNA sequencing of anaplastic ependymoma and H3K27M-mutant diffuse midline glioma

BACKGROUND

Anaplastic ependymoma and H3K27M-mutant diffuse midline glioma are two common subtypes of brain tumors with poor long-term prognosis. The present study analyzed and compared the differences in cell types between two tumors by single-cell RNA sequencing (scRNA-seq) technology.

METHODS

ScRNA-seq was performed to profile cells from cancer tissue from anaplastic ependymoma patient and H3K27M-mutant diffuse midline glioma patient. Cell clustering, marker gene identification, cell type annotation, copy number variation analysis and function analysis of differentially expressed genes were then performed.

RESULTS

A total of 11,219 cells were obtained from anaplastic ependymoma and H3K27M mutant diffuse midline glioma, and these cells categorized into 12 distinct clusters. Each cell cluster could be characterized with specific cell markers to indicate cellular heterogeneity. Five cell types were annotated in each sample, including astrocyte, oligodendrocytes, microglial cell, neural progenitor cell and immune cell. The cluster types and proportion of cell types were not consistent between the two brain tumors. Functional analyses suggest that these cell clusters are involved in tumor-associated pathways, with slight differences in the cells of origin between the two tumors. In addition, cell communication analysis showed that the NRG3-ERBB4 pair is a key Ligand-receptor pair for anaplastic ependymoma, while in H3K27M-mutant diffuse midline glioma it is the PTN-PTPRZ1 pair that establishes contact with other cells.

CONCLUSION

There was intratumor heterogeneity in anaplastic ependymoma and H3K27M mutant diffuse midline glioma, and that the subtype differences may be due to differences in the origin of the cells.

Clinical significance and immune landscape of angiogenesis-related genes in bladder cancer

BACKGROUND

Angiogenesis is a major promotor of tumor progression and metastasis. Nevertheless, it is undetermined how angiogenesis-related genes (ARGs) influence bladder cancer.

METHODS

The profiles of bladder cancer gene expression were collected from the TCGA-BLCA cohort. The LASSO regression analysis was used to build an angiogenesis-related signature (ARG_score) with the prognostic ARGs. Verification analyses were conducted across the GSE48075 dataset to demonstrate the robustness of the signature. Differences between the two risk groups based on clinical outcomes, immune landscape, mutation status, chemotherapeutic effectiveness for anticancer drugs, and immunotherapy efficacy were analyzed. A nomogram was developed to improve the clinical efficacy of this predictive tool. The expression levels of model genes in normal bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and 5637) were detected by qRT-PCR assay.

RESULTS

Four angiogenesis-associated gene signature was constructed based on the LASSO regression algorithm. The signature showed independent risk factors of overall survival for bladder cancer, validated using two external survival datasets. Additionally, we built a prognostic nomogram to improve the practicality of the ARG_score. High-risk individuals showed stronger immunocyte infiltration, immune-related functions, elevated expression of immune checkpoints, reduced TIDE score, and higher combined IPS-PD-1 and IPS-CTLA4 scores, suggesting a heightened responsiveness to immune checkpoint inhibitors. Furthermore, patients with low and high risk showed distinct responsiveness to anticancer drugs. The expression levels of 5 model genes (COL5A2, JAG1, MSX1, OLR1, and STC) were significantly increased in bladder cancer cell lines (T24 and 5637) compared with the normal bladder epithelial cell line SV-HUC-1.

CONCLUSIONS

The model constructed based on ARGs may have wide application in predicting outcomes and therapeutic responses.

Methylomics and cancer: the current state of methylation profiling and marker development for clinical care

Epigenetic modifications have long been recognized as an essential level in transcriptional regulation linking behavior and environmental conditions or stimuli with biological processes and disease development. Among them, methylation is the most abundant of these reversible epigenetic marks, predominantly occurring on DNA, RNA, and histones. Methylation modification is intimately involved in regulating gene transcription and cell differentiation, while aberrant methylation status has been linked with cancer development in several malignancies. Early detection and precise restoration of dysregulated methylation form the basis for several epigenetics-based therapeutic strategies. In this review, we summarize the current basic understanding of the regulation and mechanisms responsible for methylation modification and cover several cutting-edge research techniques for detecting methylation across the genome and transcriptome. We then explore recent advances in clinical diagnostic applications of methylation markers of various cancers and address the current state and future prospects of methylation modifications in therapies for different diseases, especially comparing pharmacological methylase/demethylase inhibitors with the CRISPRoff/on methylation editing systems. This review thus provides a resource for understanding the emerging role of epigenetic methylation in cancer, the use of methylation-based biomarkers in cancer detection, and novel methylation-targeted drugs.

Multiomics dynamic learning enables personalized diagnosis and prognosis for pancancer and cancer subtypes

Artificial intelligence (AI) approaches in cancer analysis typically utilize a 'one-size-fits-all' methodology characterizing average patient responses. This manner neglects the diverse conditions in the pancancer and cancer subtypes of individual patients, resulting in suboptimal outcomes in diagnosis and treatment. To overcome this limitation, we shift from a blanket application of statistics to a focus on the explicit recognition of patient-specific abnormalities. Our objective is to use multiomics data to empower clinicians with personalized molecular descriptions that allow for customized diagnosis and interventions. Here, we propose a highly trustworthy multiomics learning (HTML) framework that employs multiomics self-adaptive dynamic learning to process each sample with data-dependent architectures and computational flows, ensuring personalized and trustworthy patient-centering of cancer diagnosis and prognosis. Extensive testing on a 33-type pancancer dataset and 12 cancer subtype datasets underscored the superior performance of HTML compared with static-architecture-based methods. Our findings also highlighting the potential of HTML in elucidating complex biological pathogenesis and paving the way for improved patient-specific care in cancer treatment.

Genome-wide screening for differentially methylated long noncoding RNAs identifies LIFR-AS1 as an epigenetically regulated lncRNA that inhibits the progression of colorectal cancer

Background

Aberrant DNA methylation is an epigenetic marker that has been linked to the pathogenesis of colorectal cancer (CRC). Long noncoding RNAs (lncRNAs) have been increasingly identified to be associated with tumorigenic processes of CRC. Identifying epigenetically dysregulated lncRNAs and characterizing their effects during carcinogenesis are focuses of cancer research.

Methods

Differentially methylated loci and expressed lncRNAs were identified by integrating DNA methylome and transcriptome analyses using The Cancer Genome Atlas database. Bisulfite sequencing PCR (BSP) was performed to analyze LIFR-AS1 promoter methylation status. The functional roles of LIFR-AS1 in CRC were determined by in vitro and in vivo experiments.

Results

We identified a novel hypermethylated lncRNA, LIFR-AS1, that was downregulated and associated with tumorigenesis, metastasis, and poor prognosis in CRC. High methylation burden of LIFR-AS1 indicated a poor survival of CRC patients. Promoter hypermethylation of LIFR-AS1 in tumor tissues was confirmed by BSP. Functional assays revealed that LIFR-AS1 could competitively bind to hsa-miR-29b-3p, and repressed colon cancer cell proliferation, colony formation and invasion. LIFR-AS1 also inhibited tumor growth in a mouse xenograft model of CRC.

Conclusions

Our results showed that the identified DNA methylation-dysregulated lncRNAs may be potential biomarkers and highlighted a role for LIFR-AS1 as a tumor suppressor in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01361-0.

Significance of Hypermethylation of Tumor-Suppressor Genes PTGER4 and ZNF43 at CpG Sites in the Prognosis of Colorectal Cancer

The status of DNA methylation in primary tumor tissue and adjacent tumor-free tissue is associated with the occurrence of aggressive colorectal cancer (CRC) and can aid personalized cancer treatments at early stages. Tumor tissue and matched adjacent nontumorous tissue were extracted from 208 patients with CRC, and the correlation between the methylation levels of PTGER4 and ZNF43 at certain CpG loci and the prognostic factors of CRC was determined using the MassARRAY System testing platform. The Wilcoxon signed-rank test, a Chi-square test, and McNemar’s test were used for group comparisons, and Kaplan–Meier curves and a log-rank test were used for prediction. The hypermethylation of PTGER4 at the CpG_4, CpG_5, CpG_15, and CpG_17 tumor tissue sites was strongly correlated with shorter recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS) [hazard ratio (HR) = 3.26, 95% confidence interval (CI) = 1.38–7.73 for RFS, HR = 2.35 and 95% CI = 1.17–4.71 for PFS, HR = 4.32 and 95% CI = 1.8–10.5 for OS]. By contrast, RFS and PFS were significantly longer in the case of increased methylation of ZNF43 at the CpG_5 site of normal tissue [HR = 2.33, 95% CI = 1.07–5.08 for RFS, HR = 2.42 and 95% CI = 1.19–4.91 for PFS]. Aberrant methylation at specific CpG sites indicates tissue with aggressive behavior. Therefore, the differential methylation of PTGER4 and ZNF43 at specific loci can be employed for the prognosis of patients with CRC.

Comprehensive Network Analysis of Dysregulated Genes Revealed MNX1‐AS1/ hsa‐miR‐4697‐3p/ HOXB13 Axis in OC Chemotherapy Response

Poor chemotherapy response is the main obstacle of ovarian cancer (OC) treatment. Platinum‐refractory and ‐resistant patients are associated with a worse outcome than platinum‐sensitive and partially sensitive patients, but the comprehensive similarities and differences among them are not yet clear. In this study, we analyzed the data of patients with different chemotherapy response in The Cancer Genome Atlas. We found a minority of altered genes were overlapped in refractory and resistant groups, as did the enriched pathways and Gene Ontology terms. We noticed that the neural signaling and drug metabolism enzymes were more significantly enriched and the protein–protein interaction supported these results. The transcription analysis highlighted PDX1 as the common and central transcription factor in both refractory and resistant groups. The competing endogenous RNA (ceRNA) network shared no common ceRNA pairs, indicating a major difference in noncoding RNA post‐transcriptional regulation. In the end, we validated the expression, regulation, binding, and effect on chemotherapy response for selected MNX1‐AS1/hsa‐miR‐4697‐3p/HOXB13 in OC cell lines. Our study offered a novel and comprehensive insight into chemotherapy response, and potential targets for improving chemotherapy response in OC.