Comprehensive Analysis of N6-Methyladenosine-Related lncRNA Signature for Predicting Prognosis and Immune Cell Infiltration in Patients with Colorectal Cancer

N6-methyladenosine modification and post-translational modification of epithelial-mesenchymal transition in colorectal cancer

Colorectal cancer is a leading cause of cancer-related mortality worldwide. Traditionally, colorectal cancer has been recognized as a disease caused by genetic mutations. However, recent studies have revealed the significant role of epigenetic alterations in the progression of colorectal cancer. Epithelial-mesenchymal transition, a critical step in cancer cell metastasis, has been found to be closely associated with the tumor microenvironment and immune factors, thereby playing a crucial role in many kinds of biological behaviors of cancers. In this review, we explored the impact of N6-methyladenosine and post-translational modifications (like methylation, acetylation, ubiquitination, SUMOylation, glycosylation, etc.) on the process of epithelial-mesenchymal transition in colorectal cancer and the epigenetic regulation for the transcription factors and pathways correlated to epithelial-mesenchymal transition. Furthermore, we emphasized that the complex regulation of epithelial-mesenchymal transition by epigenetics can provide new strategies for overcoming drug resistance and improving treatment outcomes. This review aims to provide important scientific evidence for the prevention and treatment of colorectal cancer based on epigenetic modifications.

Non-coding RNA-Mediated N6-Methyladenosine (m6A) deposition: A pivotal regulator of cancer, impacting key signaling pathways in carcinogenesis and therapy response

The emergence of RNA modifications has recently been considered as critical post-transcriptional regulations which governed gene expression. N6-methyladenosine (m6A) modification is the most abundant type of RNA modification which is mediated by three distinct classes of proteins called m6A writers, readers, and erasers. Accumulating evidence has been made in understanding the role of m6A modification of non-coding RNAs (ncRNAs) in cancer. Importantly, aberrant expression of ncRNAs and m6A regulators has been elucidated in various cancers. As the key role of ncRNAs in regulation of cancer hallmarks is well accepted now, it could be accepted that m6A modification of ncRNAs could affect cancer progression. The present review intended to discuss the latest knowledge and importance of m6A epigenetic regulation of ncRNAs including mircoRNAs, long non-coding RNAs, and circular RNAs, and their interaction in the context of cancer. Moreover, the current insight into the underlying mechanisms of therapy resistance and also immune response and escape mediated by m6A regulators and ncRNAs are discussed.

Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer

BACKGROUND

Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

AIM

To stratify CRC patients according to necroptosis-related lncRNAs (NRLs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

METHODS

LncRNA expression profiles were collected from The Cancer Genome Atlas. NRLs were identified by coexpression analysis. Cox regression analysis identified a NRL signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its reliability for CRC prognosis prediction was assessed with clinical CRC data and compared with that of six other lncRNA signatures. Gene set enrichment analysis, TME analysis and half-maximal inhibitory concentration (IC₅₀) prediction were also performed according to the risk score (RS) of the signature.

RESULTS

An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its reliability was validated with clinical CRC data. Most of the areas under the receiver operating characteristic curves (AUCs) values for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival and the progression-free interval were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors showed that this combination could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes and Gene Ontology terms were tumor metastasis-related pathways in the high-risk group; these patients showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts, hematopoietic stem cells and M2 macrophages, but less infiltration of infiltrating antitumor effector immune cells, such as cluster of differentiation 8⁺ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and potential immunotherapeutic and chemotherapeutic drugs with relatively low IC₅₀ values.

CONCLUSION

We identified an NRL signature with strong fidelity that could stably predict prognosis and might be an indicator of the TME of CRC. Furthermore, additional potential immunotherapeutic and chemotherapeutic drugs were explored.

Identification of a novel prognostic signature correlated with epithelial-mesenchymal transition, N6-methyladenosine modification, and immune infiltration in colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) is a commonly diagnosed human malignancy worldwide. Both epithelial-mesenchymal transition (EMT) and N6-methyladenosine (m6A) modification play a crucial role in CRC development. This study aimed to construct a prognostic signature based on the genes related to EMT and m6A modification.

METHOD

Firstly, the mRNA expression profiling of CRC tissues was analyzed using TCGA and GEO databases. The prognostic hub genes related to EMT and m6A modification were selected using weighted correlation network and cox regression analysis. The prognostic signature was constructed based on hub genes, followed by validation in three external cohorts. Finally, the expression of the representative hub gene was detected in clinical samples, and its biological role was investigated using assays in vivo and in vitro.

RESULTS

A prognostic signature was constructed using the following genes: YAP1, FAM3C, NUBPL, GLO1, JARID2, NFKB1, CDKN1B, HOOK1, and GIPC2. The signature effectively stratified the clinical outcome of CRC patients in the training cohort and two validation cohorts. The subgroup analysis demonstrated the signature could identify high-risk population from CRC patients within stage I-II or III-IV, female, male and elder patients. The signature was correlated with the infiltration of some immune cells (such as macrophage and regulatory T cells) and gene mutation counts. Finally, the hub gene GIPC2 was found to be downregulated in CRC tissues and most CRC cells lines. GIPC2 overexpression inhibited the malignant characteristics of CRC cells in vitro and in vivo through upregulating E-cadherin and downregulating N-cadherin, Vimentin, and Snail, while the opposite results were observed for GIPC2 knockdown in CRC cells.

CONCLUSION

Our present study for the first time constructed a novel prognostic signature related to EMT, m6A modification, and immune infiltration for CRC risk stratification. In addition, GIPC2 is identified as a promising clinical biomarker or therapeutical target for CRC.

Identification and validation of a novel signature based on cell-cell communication in head and neck squamous cell carcinoma by integrated analysis of single-cell transcriptome and bulk RNA-sequencing

Background

The heterogeneous crosstalk between tumor cells and other cells in their microenvironment means a notable difference in clinical outcomes of head and neck squamous cell carcinoma (HNSCC). CD8+ T cells and macrophages are effector factors of the immune system, which have direct killing and phagocytosis effects on tumor cells. How the evolution of their role in the tumor microenvironment influences patients clinically remains a mystery. This study aims to investigate the complex communication networks in the HNSCC tumor immune microenvironment, elucidate the interactions between immune cells and tumors, and establish prognostic risk model.

Methods

20 HNSCC samples single-cell rna sequencing (scRNA-seq) data and bulk rna-seq data were derived from public databases. The "cellchat" R package was used to identify cell-to-cell communication networks and prognostic related genes, and then cell-cell communication (ccc) molecular subtypes were constructed by unsupervised clustering. Kaplan-Meier(K-M) survival analysis, clinical characteristics analysis, immune microenvironment analysis, immune cell infiltration analysis and CD8+T cell differentiation correlation analysis were performed. Finally, the ccc gene signature including APP, ALCAM, IL6, IL10 and CD6 was constructed based on univariate Cox analysis and multivariate Cox regression. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the model in the train group and the validation group, respectively.

Results

With CD8+T cells from naive to exhaustion state, significantly decreased expression of protective factor (CD6 gene) is associated with poorer prognosis in patients with HNSCC. The role of macrophages in the tumor microenvironment has been identified as tumor-associated macrophage (TAM), which can promote tumor proliferation and help tumor cells provide more nutrients and channels to facilitate tumor cell invasion and metastasis. In addition, based on the strength of all ccc in the tumor microenvironment, we identified five prognostic ccc gene signatures (cccgs), which were identified as independent prognostic factors by univariate and multivariate analysis. The predictive power of cccgs was well demonstrated in different clinical groups in train and test cohorts.

Conclusion

Our study highlights the propensity for crosstalk between tumors and other cells and developed a novel signature on the basis of a strong association gene for cell communication that has a powerful ability to predict prognosis and immunotherapy response in patients with HNSCC. This may provide some guidance for developing diagnostic biomarkers for risk stratification and therapeutic targets for new therapeutic strategies.

Long Noncoding RNA and mRNA m6A Modification Analyses of Periodontal Ligament Stem Cells from the Periodontitis Microenvironment Exposed to Static Mechanical Strain

Periodontal ligament stem cells (PDLSCs) play important roles in orthodontic tooth movement (OTM) and can respond to mechanical stress. Our previous study demonstrated that periodontal ligament stem cells derived from periodontitis tissue (pPDLSCs) are more sensitive to static mechanical strain (SMS) than those derived from healthy tissue (hPDLSCs) and reported the long noncoding RNA (lncRNA) expression profiles of pPDLSCs exposed to SMS. An increasing number of lncRNAs have been reported by various studies to be associated with the osteogenic differentiation of mesenchymal stem cells. Many studies have demonstrated that the n6-methyladenosine (m6A) modification exerts important effects on lncRNA and mRNA regulation of cell behaviors. However, the regulatory effects of lncRNA and mRNA m6A modification on PDLSCs have not been studied. Therefore, we performed an m6A microarray assay with pPLDSCs and hPDLSCs exposed to 12% SMS and found that 143 lncRNAs and 739 mRNAs were differentially methylated. These RNAs were thought to be involved in multiple differentiation and inflammatory responses. Moreover, we found that METTL3, an essential protein in the m6A system, was expressed at lower levels in the strain-exposed pPDLSCs than in strain-exposed hPLDSCs, and METTL3 promoted the osteogenic differentiation of pPDLSCs.

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks

An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.

Identification of a Novel Ferroptosis-Related Gene Prediction Model for Clinical Prognosis and Immunotherapy of Colorectal Cancer

Background

Colorectal cancer (CRC) is the third most common malignancies worldwide. Ferroptosis is a programmed, iron-dependent cell death observed in cancer cells. However, the prognostic potential and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in CRC patients remains to be clarified.

Methods

At first, we comprehensively analysed the different expression and prognosis of related FRGs in CRC patients based on TCGA cohort. The relationship between functional enrichment of these genes and immune microenvironment in CRC was investigated using the TCGA database. Prognostic model was constructed to determine the association between FRGs and the prognosis of CRC. Relative verification was done based on the GEO database. Meanwhile, the ceRNA network of FRGs in the model was also performed to explore the regulatory mechanisms.

Results

Eight differentially expressed FRGs were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the A, B, and C FRG clusters with different features. And FRG scores were constructed to quantify the FRG pattern of individual patients with colorectal cancer. The CRC patients with higher FRG score showed worse survival outcomes, higher immune dysfunction, and lower response to immunotherapy. The prognostic model showed a high accuracy for predicting the OS of CRC. Finally, a ceRNA network was analysed to show the concrete regulation mechanisms of critical FRGs in CRC.

Conclusions

The FRG risk score prognostic model based on 8 FRGs exhibit superior predictive performance, providing a novel prognostic model with a high accuracy for CRC patients. Moreover, FRG score can be the potential biomarker of the response of immunotherapy for CRC.