Identification of N6-Methyladenosine-Related lncRNAs as a Prognostic Signature in Glioma

Overview of the interplay between m6A methylation modification and non-coding RNA and their impact on tumor cells

N6-methyladenosine (m6A) is one of the most common internal modifications in eukaryotic RNA. The presence of m6A on transcripts can affect a series of fundamental cellular processes, including mRNA splicing, nuclear transportation, stability, and translation. The m6A modification is introduced by m6A methyltransferases (writers), removed by demethylases (erasers), and recognized by m6A-binding proteins (readers). Current research has demonstrated that m6A methylation is involved in the regulation of malignant phenotypes in tumors by controlling the expression of cancer-related genes. Non-coding RNAs (ncRNAs) are a diverse group of RNA molecules that do not encode proteins and are widely present in the human genome. This group includes microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and PIWI interaction RNAs (piRNAs). They function as oncogenes or tumor suppressors through various mechanisms, regulating the initiation and progression of cancer. Previous studies on m6A primarily focused on coding RNAs, but recent discoveries have revealed the significant regulatory role of m6A in ncRNAs. Simultaneously, ncRNAs also exert their influence by modulating the stability, splicing, translation, and other biological processes of m6A-related enzymes. The interplay between m6A and ncRNAs collectively contributes to the occurrence and progression of malignant tumors in humans. This review provides an overview of the interactions between m6A regulatory factors and ncRNAs and their impact on tumors.

Zinc finger Protein207 orchestrates glioma migration through regulation of epithelial-mesenchymal transition

BACKGROUND

Glioma represents the predominant primary malignant brain tumor. For several years, molecular profiling has been instrumental in the management and therapeutic stratification of glioma, providing a deeper understanding of its biological complexity. Accumulating evidence unveils the putative involvement of zinc finger proteins (ZNFs) in cancer. This study aimed to elucidate the role and significance of ZNF207 in glioma.

METHODS

Utilizing online data such as The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), the Genotype-Tissue Expression (GTEx) project, the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA) databases, in conjunction with bioinformatics methodologies including GO, KEGG, GSEA, CIBERSORT immune cell infiltration estimation, and protein-protein interaction (PPI) analysis, enabled a comprehensive exploration of ZNF207's involvement in gliomagenesis. Immunohistochemistry and RT-PCR techniques were employed to validate the expression level of ZNF207 in glioma samples. Subsequently, the biological effects of ZNF207 on glioma cells were explored through in vitro assays.

RESULTS

Our results demonstrate elevated expression of ZNF207 in gliomas, correlating with unfavorable patient outcomes. Stratification analyses were used to delineate the prognostic efficacy of ZNF207 in glioma with different clinicopathological characteristics. Immunocorrelation analysis revealed a significant association between ZNF207 expression and the infiltration levels of T helper cells, macrophages, and natural killer (NK) cells. Utilizing ZNF207 expression and clinical features, we constructed an OS prediction model and displayed well discrimination with a C-index of 0.861. Moreover, the strategic silencing of ZNF207 attenuated glioma cell advancement, evidenced by diminished cellular proliferation, weakened cell tumorigenesis, augmented apoptotic activity, and curtailed migratory capacity alongside the inhibition of the epithelial-mesenchymal transition (EMT) pathway.

CONCLUSIONS

ZNF207 may identify as a prospective biomarker and therapeutic candidate for glioma prevention, providing valuable insights into understanding glioma pathogenesis and treatment strategies.

Genes associated with N6-methyladenosine regulators provide insight into the prognosis and immune response to renal clear cell carcinoma

As one of the most common messenger ribonucleic acid modifications in eukaryotic organisms, N6-methyladenosine (m6A) is involved in a wide variety of biological functions. The imbalance of m6A RNA modification may be linked to cancer and other disorders, according to a growing body of studies. Its effects on clear cell renal cell carcinoma (KIRC) have not been well discussed, though. Here, we acquired the expression patterns of 23 important regulators of m6A RNA modification and assess how they might fare in KIRC. We observed that 17 major m6A RNA modification regulatory factors had a substantial predictive influence on KIRC. Using the "ConsensusCluster" program, we defined two groupings (Cluster 1 and Cluster 2) depending on the expression of the aforementioned 17 key m6A RNA methylation regulators. The Cluster 2 has a less favorable outcome and is strongly related with a lesser immune microenvironment, according to the findings. We also developed a strong risk profile for three m6A RNA modifiers (METTL14, YTHDF1, and LRPPRC) using multivariate Cox regression analysis. According to further research, the aforementioned risk profile could serve as an independent predicting factor for KIRC, and the chemotherapy response sensitivity was analyzed between two risk groups. Moreover, to effectively forecast the future outlook of KIRC clients, we established a novel prognostic approach according to gender, age, histopathological level, clinical stage, and risk score. Finally, the function of hub gene METTL14 was validated by cell proliferation and subcutaneous graft tumor in mice. In conclusion, we discovered that m6A RNA modifiers play an important role in controlling KIRC and created a viable risk profile as a marker of prediction for KIRC clients.

EPYC functions as a novel prognostic biomarker for pancreatic cancer

Pancreatic cancer (PC) has become a worldwide challenge attributed to its difficult early diagnosis and rapid progression. Treatments continue to be limited besides surgical resection. Hence, we aimed to discover novel biological signatures as clinically effective therapeutic targets for PC via the mining of public tumor databases. We found that epiphycan (EPYC) could function as an independent risk factor to predict the poor prognosis in PC based on integrated bioinformatics analysis. We downloaded associated PC data profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) online websites, then applied the software Rstudio to filter out genes under the strict criteria. After the batch survival analysis using Log-rank test and univariate cox regression, we obtained 39 candidate genes. Subsequently, we narrowed the scope to 8 genes by establishing a Lasso regression model. Eventually, we focused on 2 genes (EPYC and MET) by further building a multivariate cox regression model. Given that the role of EPYC in PC remains obscure, we then performed a series of molecular functional experiments, including RT-qPCR, CCK8, EdU, colony formation, Transwell, western blot, cell live-dead staining, subcutaneous tumor formation, to enhance our insight into its underlying molecular mechanisms. The above results demonstrated that EPYC was highly expressed in PC cell lines and could promote the proliferation of PCs via PI3K-AKT signaling pathway in vivo and in vitro. We arrived at a conclusion that EPYC was expected to be a biological neo-biomarker for PC followed by being a potential therapeutic target.

MBNL1‑AS1 attenuates tumor cell proliferation by regulating the miR‑29c‑3p/BVES signal in colorectal cancer

Dysregulation of long non‑coding RNAs (lncRNAs) is involved in the development of colorectal cancer (CRC). In the present study, the identification of muscle blind like splicing regulator 1 antisense RNA 1 (MBNL1‑AS1) lncRNA was reported. Firstly, Cell Counting Kit‑8, EdU and colony formation assays were uesed to explore the role of MBNL1‑AS1 in regulating the proliferation of CRC cells. According to TCGA database, it was found that MBNL1‑AS1 was correlated with microRNA (miR)‑29c‑3p and blood vessel epicardial substance (BVES) expression in CRC cells. Then, the regulation among MBNL1‑AS1, miR‑29C‑3P and BVES was detected by dual luciferase reporter assay and the function of MBNL1‑AS1/miR‑29C‑3P/BVES axis was explored by rescue assay. The results demonstrated that MBNL1‑AS1 expression was decreased in CRC and was associated with the size of tumors derived from patients with CRC. Functionally, the upregulation of MBNL1‑AS1 suppressed CRC cell proliferation in vitro and inhibited tumor growth in vivo, while knockdown of MBNL1‑AS1 expression caused the opposite effects. MBNL1‑AS1 expression correlated with BVES expression in CRC tissues and MBNL1‑AS1 enhanced the stability of BVES mRNA by functioning as a competing endogenous RNA to sponge miR‑29c‑3p; the latter directly targeted MBNL1‑AS1 and BVES mRNA 3'UTR. Collectively, the results indicated that MBNL1‑AS1 suppressed CRC cell proliferation by regulating miR‑29c‑3p/BVES signaling, suggesting that the MBNL1‑AS1/miR‑29c‑3p/BVES axis may be a potential therapeutic target for CRC.

The lncRNA epigenetics: The significance of m6A and m5C lncRNA modifications in cancer

Most of our transcribed RNAs are represented by non-coding sequences. Long non-coding RNAs (lncRNAs) are transcripts with no or very limited protein coding ability and a length >200nt. They can be epigenetically modified. N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), 7-methylguanosine (m7G) and 2’-O-methylation (Nm) are some of the lncRNAs epigenetic modifications. The epigenetic modifications of RNA are controlled by three classes of enzymes, each playing a role in a specific phase of the modification. These enzymes are defined as “writers”, “readers” and “erasers”. m6A and m5C are the most studied epigenetic modifications in RNA. These modifications alter the structure and properties, thus modulating the functions and interactions of lncRNAs. The aberrant expression of several lncRNAs is linked to the development of a variety of cancers and the epigenetic signatures of m6A- or m5C-related lncRNAs are increasingly recognized as potential biomarkers of prognosis, predictors of disease stage and overall survival. In the present manuscript, the most up to date literature is reviewed with the focus on m6A and m5C modifications of lncRNAs and their significance in cancer.

Gene signature of m6A RNA regulators in diagnosis, prognosis, treatment, and immune microenvironment for cervical cancer

Continuing studies imply that m⁶A RNA modification is involved in the development of cervical cancer (CC), but lack strong support on recurrence and diagnosis prediction. In this research, a comprehensive analysis of 33 m⁶A regulators was performed to fulfill them. Here, we performed diagnostic and prognosis models and identified key regulators, respectively. Then the CC patients were separated into two clusters in accordance with 33 regulators, and participants in the cluster 1 had a worse prognosis. Subsequently, the m⁶AScore was calculated to quantify the m⁶A modification pattern based on regulators and we found that patients in cluster 1 had higher m⁶AScore. Afterwards, immune microenvironment, cell infiltration, escape analyses and tumor burden mutation analyses were executed, and results showed that m⁶AScore was correlated with them, but to a limited extent. Interestingly, HLAs and immune checkpoint expression, and immunophenoscore in patients with high-m⁶AScores were significantly lower than those in the low-m⁶AScore group. These suggested the m⁶AScores might be used to predict the feasibility of immunotherapy in patients. Results provided a distinctive perspective on m⁶A modification and theoretical basis for CC diagnosis, prognosis, clinical treatment strategies, and potential mechanism exploration.

Pan-Cancer Gene Analysis of m6A Modification and Immune Infiltration in Uterine Corpus Endometrial Carcinoma

Objective

This investigation was to test the potential role of m6A-related long non-coding RNAs (lncRNAs) and immune infiltration as crucial factors in the diagnosis and treatment of uterine corpus endometrial cancer (UCEC).

Method

The UCEC RNA-seq data were downloaded in the Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/). There were 587 samples totally, containing 543 UCEC cases and 35 healthy cases. The clinical information of UCEC cases included survival time, survival status, gender, age, stage, and TMN stage. Twenty-three m6A-related genes were found in published journals. The RNA-seq documents of UCEC were downloaded in the Cancer Genome Atlas (TCGA). The hub gene data of UCEC were downloaded from GEPIA2 database. The different packages of R language were applied to calculate and analyze in this research.

Results

Among 587 cases in our study, we discovered 3039 lncRNAs in the TCGA-UCEC database. After the differential analysis, 23 m6A-associated genetics were screened and twenty-one m6A-associated differential genetics were found. In the end, we obtained 20 m6A-related lncRNAs. LNCTAM34A was considered as a predictive gene through univariate and multivariate Cox regression analysis. In addition to the above, patients with high LNCTAM34A expression had better outcomes than those with low LNCTAM34A expression. The high-risk cohort had greater scores of activated dendritic cells (aDCs), B cells, and T cell regulatory (Tregs) than low-risk cohort; in the meanwhile, high-risk cohort had lower scores of DCs and iDCs. Then, the high-risk cohort displayed greater scores in the immune functions of MHC class I, para-inflammation, and type I IFN response than those of low-risk cohort. Among 27 immune-inducible genes, the level of CD244, KIR3DLI, NRP1, PDCD1LG2, and TNFRSF8 was reduced in UCEC samples and the level of CD27, CD28, CD70, CD80, CD86, HAVCR2, ICOS, IDO1, LAIR1, PDCD1, TIGIT, TNFRSF18, -25, -9, -14, and VTCN1 was increased in UCEC samples.

Conclusion

The key role of M6A-related lncRNAs in immune microenvironment in high-risk patients of UCEC. The patients with strong expression of LNCTAM34A have a good prognosis, and LNCTAM34A can be used as a prognostic gene for UCEC. m6A-related lncRNAs can be used as a potential treatment for UCEC. Our observations can be used as a hypothetical basis for future in vitro and animal experiments.

Potential biomarkers for predicting the overall survival outcome of kidney renal papillary cell carcinoma: an analysis of ferroptosis-related LNCRNAs

Background

Kidney renal papillary cell carcinoma (KIRP) is a dangerous cancer, which accounts for 15–20% of all kidney malignancies. Ferroptosis is a rare kind of cell death that overcomes medication resistance. Ferroptosis-related long non-coding RNAs (LNCRNAs) in KIRP, remain unknown.

Method

We wanted to express how ferroptosis-related LNCRNAs interact with immune cell infiltration in KIRP. Gene set enrichment analysis in the GO and KEGG databases were used to explore gene expression enrichment. The prognostic model was constructed using Lasso regression. In addition, we also analyzed the modifications in the tumor microenvironment (TME) and immunological association.

Result

The expression of LNCRNA was closely connected to the ferroptosis, according to co-expression analyses. CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were found to be significantly increased in the high-risk group, indicating that all of these markers implicates the malignancy processes for KIRP patients and may be cancer-promoting variables. LNCTAM34A and AC024022.1 were shown to be significantly elevated in the low-risk group; these might represent as the KIRP tumor suppressor genes. According to the TCGA, CCR, and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of CD160, TNFSF4, CD80, BTLA, and TNFRSF9 was different in the two risk groups.

Conclusion

LNCRNAs associated with ferroptosis were linked to the occurrence and progression of KIRP. Ferroptosis-related LNCRNAs and immune cell infiltration in the TME may be potential biomarkers in KIRP that should be further investigated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01037-0.

An m6A/m5C/m1A/m7G-Related Long Non-coding RNA Signature to Predict Prognosis and Immune Features of Glioma

Background: Gliomas are the most common and fatal malignant type of tumor of the central nervous system. RNA post-transcriptional modifications, as a frontier and hotspot in the field of epigenetics, have attracted increased attention in recent years. Among such modifications, methylation is most abundant, and encompasses N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1 methyladenosine (m1A), and 7-methylguanosine (m7G) methylation.

Methods: RNA-sequencing data from healthy tissue and low-grade glioma samples were downloaded from of The Cancer Genome Atlas database along with clinical information and mutation data from glioblastoma tumor samples. Forty-nine m6A/m5C/m1A/m7G-related genes were identified and an m6A/m5C/m1A/m7G-lncRNA signature of co-expressed long non-coding RNAs selected. Least absolute shrinkage and selection operator Cox regression analysis was used to identify 12 m6A/m5C/m1A/m7G-related lncRNAs associated with the prognostic characteristics of glioma and their correlation with immune function and drug sensitivity analyzed. Furthermore, the Chinese Glioma Genome Atlas dataset was used for model validation.

Results: A total of 12 m6A/m5C/m1A/m7G-related genes (AL080276.2, AC092111.1, SOX21-AS1, DNAJC9-AS1, AC025171.1, AL356019.2, AC017104.1, AC099850.3, UNC5B-AS1, AC006064.2, AC010319.4, and AC016822.1) were used to construct a survival and prognosis model, which had good independent prediction ability for patients with glioma. Patients were divided into low and high m6A/m5C/m1A/m7G-LS groups, the latter of which had poor prognosis. In addition, the m6A/m5C/m1A/m7G-LS enabled improved interpretation of the results of enrichment analysis, as well as informing immunotherapy response and drug sensitivity of patients with glioma in different subgroups.

Conclusion: In this study we constructed an m6A/m5C/m1A/m7G-LS and established a nomogram model, which can accurately predict the prognosis of patients with glioma and provides direction toward promising immunotherapy strategies for the future.