The m6A-Related mRNA Signature Predicts the Prognosis of Pancreatic Cancer Patients

Identification of key differentially methylated genes regulating muscle development in chickens: insights from Jingyuan breed

Skeletal muscle development is a complex, regulated physiological process that involves myoblast proliferation and differentiation and the fusion of myotubes. In this study, phenotypic differences in the breast and leg muscles of 180-day-old Jingyuan chickens were investigated. Differentially methylated genes (DMG) that regulate muscle development were identified through differential expression analysis and weighted gene co-expression network analysis. Moreover, myoblasts were used as test material and treated with cycloleucine to investigate the effect of N6-methyladenosine (m6A) modification on their proliferation and differentiation. The results revealed that the myofiber diameter and cross-sectional area in the breast muscle of Jingyuan chickens were significantly smaller than those in the leg muscle, while myofiber density in the breast muscle was significantly higher. A total of 484 DMG were identified in both muscle types. Module gene association analysis with DMGs revealed multiple DMG associated with muscle development. In vitro cell model analysis revealed that cycloleucine treatment significantly downregulated the m6A modification level of myoblasts and inhibited their proliferation and differentiation. Additionally, stage-specific differences in LDHA, LDHB, and GAPDH expressions were observed during myoblast differentiation. Cycloleucine treatment significantly inhibited LDHA, LDHB, and GAPDH expression. These findings indicate that m6A methylation modifications play significant regulatory roles in muscle development, with LDHA, LDHB, and GAPDH being potential candidate genes for regulating muscle development. This study provides an essential theoretical basis for further study on the functional mechanisms of m6A modifications involved in muscle development.

YTHDC1 m6A-dependent and m6A-independent functions converge to preserve the DNA damage response

Cells have evolved a robust and highly regulated DNA damage response to preserve their genomic integrity. Although increasing evidence highlights the relevance of RNA regulation, our understanding of its impact on a fully efficient DNA damage response remains limited. Here, through a targeted CRISPR-knockout screen, we identify RNA-binding proteins and modifiers that participate in the p53 response. Among the top hits, we find the m6A reader YTHDC1 as a master regulator of p53 expression. YTHDC1 binds to the transcription start sites of TP53 and other genes involved in the DNA damage response, promoting their transcriptional elongation. YTHDC1 deficiency also causes the retention of introns and therefore aberrant protein production of key DNA damage factors. While YTHDC1-mediated intron retention requires m6A, TP53 transcriptional pause-release is promoted by YTHDC1 independently of m6A. Depletion of YTHDC1 causes genomic instability and aberrant cancer cell proliferation mediated by genes regulated by YTHDC1. Our results uncover YTHDC1 as an orchestrator of the DNA damage response through distinct mechanisms of co-transcriptional mRNA regulation.

Clinicopathological Significances and Prognostic Value of PPFIA4 in Colorectal Cancer

Purpose: The PPFIA gene family (PPFIA1, PPFIA2, PPFIA3, and PPFIA4) is associated with multiple human diseases, particularly malignant tumors. However, the expression and prognostic value of the PPFIA family in human colorectal cancers (CRCs) have not been reported. Materials and methods: In this study, several databases, including Oncomine, UALCAN, and the cancer cell line encyclopedia, were used to compare differences in PPFIA1, PPFIA2, PPFIA3, and PPFIA4 expression between normal colon samples and CRCs. The expression levels of these four proteins were used to evaluate the survival of patients with CRC, as determined by the Cancer Genome Atlas Program (TCGA) portal and gene expression profiling interactive analysis (GEPIA) databases. Western blotting and reverse transcription-polymerase chain reaction were performed to detect protein and mRNA levels of PPFIA1, PPFIA3, and PPFIA4, respectively. Immunohistochemical (IHC) staining was used to detect the correlation between PPFIA4 expression and the degree of CRC malignancy. Furthermore, potential miRNAs targeting PPFIA4 in CRCs were studied and confirmed. Results: Bioinformatic analysis showed that the mRNA levels of PPFIA1, PPFIA3, and PPFIA4 were higher in CRC tissue samples than in normal colon tissue. Both mRNA and protein expression of PPFIA1, PPFIA3, and PPFIA4 were increased in the CRC cell lines LoVo and Hct116 compared with the normal colon epithelial cell line. Only PPFIA4 was associated with the prognosis of patients with CRC, which was confirmed by TCGA portal and GEPIA. IHC staining confirmed that the expression of PPFIA4 was higher in CRC tissues than in normal colon tissues and also increased in poorly differentiated CRC tissues and lymph node metastatic foci in comparison with well-differentiated CRC tissues and moderately differentiated CRC tissues. Functional annotation enrichment analysis indicated that the top 100 genes co-expressed with PPFIA4 were enriched in the G-protein coupled peptide receptor activity, leukotrience B4 receptor activity, and peroxisome proliferator-activated receptors and hypoxia-inducible factor-1 signaling pathways. In addition, miR-485-5p negatively regulates the expression of PPFIA4. Conclusion: PPFIA4 expression is associated with the development of CRCs and may be a novel potential prognostic marker for human CRCs.

Targeting FTO Suppresses Pancreatic Carcinogenesis via Regulating Stem Cell Maintenance and EMT Pathway

N⁶-methyladenosine (m⁶A) is the most prevalent post-transcriptional RNA modification regulating cancer self-renewal. However, despite its functional importance and prognostic implication in tumorigenesis, the relevance of FTO, an m⁶A eraser, in pancreatic cancer (PC) remains elusive. Here, we establish the oncogenic role played by FTO overexpression in PC. FTO is upregulated in PC cells compared to normal human pancreatic ductal epithelial (HPDE) cells. Both RNAi depletion and CS1-mediated pharmacological inhibition of FTO caused a diminution of PC cell proliferation via cell cycle arrest in the G1 phase and p21cip1 and p27kip1 induction. While HPDE cells remain insensitive to CS1 treatment, FTO overexpression confers enhancements in growth, motility, and EMT transition, thereby inculcating tumorigenic properties in HPDE cells. Notably, shRNA-mediated FTO depletion in PC cells impairs their mobility and invasiveness, leading to EMT reversal. Mechanistically, this was associated with impaired tumorsphere formation and reduced expression of CSCs markers. Furthermore, FTO depletion in PC cells weakened their tumor-forming capabilities in nude mice; those tumors had increased apoptosis, decreased proliferation markers, and MET conversion. Collectively, our study demonstrates the functional importance of FTO in PC and the maintenance of CSCs via EMT regulation. Thus, FTO may represent an attractive therapeutic target for PC.

Molecular subtypes identified by pyroptosis-related genes are associated with tumor microenvironment cell infiltration in colon cancer

The important role of pyroptosis in tumor progression has been well characterized in recent years. However, little is known about the impact of tumor pyroptosis characteristics on patient prognosis and tumor microenvironment (TME) as well as efficacy of immunotherapy. In this study, we successfully classified colon cancer samples into three pyroptosis characterizations with different prognosis and TME cell infiltration patterns based on the expression of pyroptosis-related genes. Cluster 2, with the characterizations of immunosuppression, was classified as immune-desert cell infiltration patterns. Cluster 3, with the patterns of immune-inflamed cell infiltration, had the feature of an activated innate and adaptive immunity and significant prolonged survival. The activation of stromal pathways including EMT, angiogenesis and TGF-β in cluster 1 may mediate the impaired immune penetration of this cluster, which was classified as immune-excluded cell infiltration patterns. Our results demonstrated the PyroSig signature was a robust and independent biomarker for predicting patient prognosis. Patients with low PyroSig signature was confirmed to be correlated with treatment advantages and significant prolonged survival in two anti-checkpoint immunotherapy cohorts. This study identified three pyroptosis-related subtypes with distinct molecular features, clinical and microenvironment cell infiltration patterns in colon cancer, which could promote individualized immunotherapy for colon cancer.

Zona Pellucida like Domain Protein 1 (ZPLD1) Polymerization Is Regulated by Two Distinguished Hydrophobic Motifs

Zona Pellucida Like Domain 1 Protein (ZPLD1) is a main component of the cupula, a gelatinous structure located in the labyrinth organ of the inner ear and involved in vestibular function. The N-glycosylated protein is likely able to organize high-molecular-weight polymers via its zona pellucida (ZP) module, which is common for many extracellular proteins that self-assemble into matrices. In this work, we confirmed that ZPLD1 can form multimers while setting up a cellular model leveraging Madin-Darby canine kidney (MDCK) cells to study protein polymerization. We identified two motifs within ZPLD1 which regulate its polymerization and follow previously published conserved regions, identified across ZP proteins. Mutational depletion of either one of these modules led to diminished or abnormal polymer formation outside of the cells, likely due to altered processing at the plasma membrane. Further, intracellular polymer formation was observed. Proteolytic cleavage during secretion, separating the regulatory motif located distinct of the ZP module from the mature monomer, seems to be necessary to enable polymerization. While the molecular interactions of the identified motifs remain to be proven, our findings suggest that ZPLD1 is a polymer forming ZP protein following an orchestrated mechanism of protein polymerization to finally build up a gelatinous hydrogel.

The development and validation of a m6A-lncRNAs based prognostic model for overall survival in lung squamous cell carcinoma

BACKGROUND

No biomarkers have been identified for the prognosis of lung squamous cell carcinoma (LUSC). Risk models based on m6A-lncRNAs help to predict survival in some cancers. However, very few studies have reported m6A-lncRNA risk models in LUSC. We aimed to construct a prognostic model based on m6A-lncRNAs in LUSC.

METHODS

The clinical and RNA-sequencing information of 504 LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Prognostic m6A-lncRNAs were identified by a Pearson correlation analysis and univariate Cox regression analysis. The ConsensusClusterPlus algorithm was used to cluster the prognostic m6A-lncRNAs. The overall survival (OS) and clinicopathological characteristics of the 2 clusters were compared. A gene set enrichment analysis (GSEA) analysis was performed to analyze the genes enriched in the 2 clusters. A least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to construct the risk-score model. Two hundred and forty eight patients were randomly chosen from TCGA-LUSC cohort for the training set. The receiver operating characteristic (ROC) curve analysis was used to assess the predictive ability of the model. The clinical characteristics and OS in the high- and low-risk groups were compared. The independent prognostic value of the model was tested by Cox regression analyses.

RESULTS

Thirteen m6A-lncRNAs were identified as prognostic lncRNAs and classified into cluster A and cluster B. The OS of patients in cluster A was better than that of patients in cluster B (P<0.001). Patients in cluster B had higher expressions of immune checkpoints. Immune score, stromal score, and ESTIMATE score were higher in cluster B (P<0.001). Seven of the 13 lncRNAs were used to construct the risk-score model. Patients in the high-risk group had a worse OS. ROC curves showed a under the curve (AUC) of 0.639 in the training set and 0.624 in the validation set. A high risk was associated with cluster B, a high immune score, and stage III-IV disease. Patients in the high-risk group had increased expressions of immune checkpoints. The Cox regression analyses showed that the risk-score model had independent prognostic value for OS. The risk-score model retained its prognostic value in different subgroups.

CONCLUSIONS

The m6A-lncRNA risk-score model is an independent prognostic factor for OS in LUSC patients. However, the risk-score model need to be further tested clinically.

Comprehensive analysis of the prognosis and immune infiltration landscape of RNA methylation-related subtypes in pancreatic cancer

Background

RNA methylation refers to a form of methyl modification in RNA that modulates various epigenetic alterations. Mounting studies have focused on its potential mechanisms in cancer initiation and progression. However, the prognostic value and potential role of RNA methylation in the immune microenvironment of pancreatic cancer remain unclear.

Methods

Comprehensive bioinformatics analysis was performed to illuminate the expression profiles of RNA methylation modulators. In addition, the ConsensusClusterPlus algorithm was utilized to identify two remarkably different subtypes, and a feasible risk stratification method was established to accurately estimate prognosis. In addition, we validated our signature at the cytology and histology levels and conducted functional experiments to explore the biological functions of our key genes.

Results

Two subtypes with remarkable survival differences were identified by the consensus clustering algorithm. Cluster 2 tended to have higher expression levels of RNA methylation regulators and to be the high RNA methylation group. In addition, cluster 1 exhibited a significantly higher abundance of almost all immune cells and increased immune checkpoint expression compared to cluster 2. Chemotherapeutic sensitivity analysis indicated that there were significant differences in the sensitivity of four of the six drugs between different subgroups. Mutation investigation revealed a higher mutation burden and a higher number of mutations in cluster 2. An accurate and feasible risk stratification method was established based on the expression of key genes of each subtype. Patients with low risk scores exhibited longer survival times in one training (TCGA) and two validation cohorts (ICGC, GSE57495), with p values of 0.001, 0.0081, and 0.0042, respectively. In addition, our signature was further validated in a cohort from Fudan University Shanghai Cancer Center. The low-risk group exhibited higher immune cell abundance and immune checkpoint levels than the high-risk group. The characteristics of the low-risk group were consistent with those of cluster 1: higher stromal score, estimate score, and immune score and lower tumor purity. Additionally, cell function investigations suggested that knockdown of CDKN3 remarkably inhibited the proliferation and migration of pancreatic cancer cells.

Conclusions

RNA methylation has a close correlation with prognosis, immune infiltration and therapy in pancreatic cancer. Our subtypes and risk stratification method can accurately predict prognosis and the efficacy of immune therapy and chemotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09863-z.

N6-Methyladenosine RNA-Binding Protein YTHDF1 in Gastrointestinal Cancers: Function, Molecular Mechanism and Clinical Implication

Simple Summary

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in eukaryotic mRNA and plays a crucial role in the occurrence and development of diseases. YTHDF1 is the most powerful and abundant m⁶A-encoded RNA reader. In this review, we summarize the evidence of the involvement of YTHDF1 in gastrointestinal cancers, its molecular mechanisms of action, and therapeutic implications.

Abstract

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in eukaryotic cell mRNA, and this modification plays a key role in regulating mRNA translation, splicing, and stability. Emerging evidence implicates aberrant m⁶A as a crucial player in the occurrence and development of diseases, especially GI cancers. Among m⁶A regulators, YTHDF1 is the most abundant m⁶A reader that functionally connects m⁶A-modified mRNA to its eventual fate, mostly notably protein translation. Here, we summarized the function, molecular mechanisms, and clinical implications of YTHDF1 in GI cancers. YTHDF1 is largely upregulated in multiple GI cancer and its high expression predicts poor patient survival. In vitro and in vivo experimental evidence largely supports the role of YTDHF1 in promoting cancer initiation, progression, and metastasis, which suggests the oncogenic function of YTHDF1 in GI cancers. Besides, YTHDF1 overexpression is associated with changes in the tumor microenvironment that are favorable to tumorigenesis. Mechanistically, YTHDF1 regulates the expression of target genes by promoting translation, thereby participating in cancer-related signaling pathways. Targeting YTHDF1 holds therapeutic potential, as the overexpression of YTHDF1 is associated with tumor resistance to chemotherapy and immunotherapy. In summary, YTHDF1-mediated regulation of m⁶A modified mRNA is an actionable target and a prognostic factor for GI cancers.

Pancreatic adenocarcinoma associated immune-gene signature as a novo risk factor for clinical prognosis prediction in hepatocellular carcinoma

Pancreatic adenocarcinoma (PAAD) has high mortality and a very poor prognosis. Both surgery and chemotherapy have a suboptimal therapeutic effect, and this caused a need to find new approaches such as immunotherapy. Therefore, it is essential to develop a new model to predict patient prognosis and facilitate early intervention. Our study screened out and validated the target molecules based on the TCGA-PAAD dataset. We established the risk signature using univariate and multivariate Cox regression analysis and used GSE62452 and GSE28735 to verify the accuracy and reliability of the model. Expanded application of PAAD-immune-related genes signature (-IRGS) on other datasets was conducted, and the corresponding nomograms were constructed. We also analyzed the correlation between immune-related cells/genes and potential treatments. Our research demonstrated that a high riskscore of PAAD-IRGS in patients with PAAD was correlated with poor overall survival, disease-specific survival and progression free interval. The same results were observed in patients with LIHC. The models constructed were confirmed to be accurate and reliable. We found various correlations between PAAD-IRGS and immune-related cells/genes, and the potential therapeutic agents. These findings indicate that PAAD-IRGS may be a promising indicator for prognosis and of the tumor-immune microenvironment status in PAAD.

Comprehensive analysis of the PD-L1 and immune infiltrates of N6-methyladenosine related long non-coding RNAs in bladder cancer

Bladder cancer (BLCA) is one of the most frequent genitourinary cancers, with a high rate of morbidity and mortality. The connection of m6A-related lncRNAs with PD-L1 and tumor immune microenvironment (TIME) in BLCA prognosis was extensively investigated in this study, which could suggest novel therapeutic targets for further investigation. 30 m6A-associated lncRNAs with predictive values from the TCGA data set were identified with co-expression analysis. Cluster2 was correlated with a poor prognosis, upregulated PD-L1 expression, and higher immune ratings. Cluster2 had larger amounts of resting CD4 memory-activated T cells, M2 macrophages, neutrophils, and NK cells infiltration. "CHEMOKINE SIGNALING PATHWAY" was the most significantly enriched signaling pathway according to GSEA, which may play an important role in the different immune cell infiltrates between cluster1/2. The risk model for m6A-related lncRNAs could be employed in a prognostic model to predict BLCA prognosis, regardless of other clinical features. Collectively, m6A-related lncRNAs were linked to PD-L1 and TIME, which would dynamically affect the number of tumor-infiltrating immune cells. m6A-related lncRNAs may be key mediators of PD-L1 expression and immune cells infiltration and may strongly affect the TIME of BLCA.

Potential prognosis index for m6A-related mRNA in cholangiocarcinoma

Background

Cholangiocarcinoma (CHOL) is a malignant tumor that originates in the extrahepatic bile duct and can extend from the hilar region to the lower end of the common bile duct. The prognosis of CHOL patients is particularly poor; therefore, in this study, we screened mRNAs correlated with N6-methyladenosine (m⁶A) to construct a risk model for prognosis in CHOL.

Methods

The TCGA-CHOL dataset was applied to obtain and analyze the coexpression of 1281 m⁶A-related mRNAs, from which 14 were selected for further analysis through univariate proportional hazards (cox) regression analysis. Aryl hydrocarbon receptor interacting protein (AIP), CCAAT/enhancer binding protein beta (CEBPB), syndecan1 (SDC1), vacuolar protein sorting 25 homolog (VPS25) and syntaxin binding protein 2 (STXBP2) were then screened out through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to develop a precise m⁶A-related mRNA prognosis risk model (MRMRPM) with an area under curve (AUC) of 0.908 and 0.923 after 1 and 2 years, respectively. We divided the samples into high-risk and low-risk groups using the m⁶A-related mRNA prognosis risk model.

Results

Kaplan–Meier analysis indicated poor overall survival (OS) for the high-risk group. Two Gene Expression Omnibus (GEO) datasets (GSE89748 and GSE107943) were used to validate the risk model. The results of drug sensitivity and immune cell infiltration analysis showed that the risk model could serve as a prognosis index of potential immunotherapeutic characteristics and drug sensitivity. Furthermore, the proportion of resting dendritic cells and regulatory T cells was positively associated with an increased expression of four m⁶A-related mRNAs — AIP, CEBPB, SDC1, and VPS25 — in the high-risk CHOL group.

Conclusions

Our findings suggest that this model can be a prognostic indicator for CHOL patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09665-3.

The "m6A writer" METTL3 and the "m6A reader" IGF2BP2 regulate cutaneous T-cell lymphomas (CTCL) progression via CDKN2A

It has been established that Cutaneous T-Cell lymphomas (CTCL) are caused by the monoclonal proliferation of T lymphocytes in the skin. This heterogeneous group of diseases represents a significant source of distress to patients since the diagnosis and treatment are often challenging. As one of the most abundant internal modifications in mRNA in higher eukaryotes, N6-methyladenosine (m6A) is widely recognized to affect the development and progression of cancers. However, knowledge on the involvement of m6A in CTCL is still limited. In this work, we revealed the role of METTL3-mediated m6A modification in CTCL progression. ELISA, western blot, and qRT-PCR assays demonstrated that METTL3 was significantly downregulated in CTCL cells both in vivo and in vitro. CCK-8, EdU, flow cytometry, and transwell assays showed that the decline in METTL3 levels was responsible for CTCL cell proliferation and migration. Furthermore, using small interfering RNAs (siRNAs) against METTL3 and the RIP assay, we showed that CDKN2A was a key regulator during this process in vitro and in vivo, and insufficient methylation modification blocked the interaction between CDKN2A and m6A reader IGF2BP2, resulting in mRNA degradation. To the best of our knowledge, this is the first study to depict the role of m6A in CTCL development and provide potential bio-targets for therapy. This article is protected by copyright. All rights reserved.

A Signature of N6-methyladenosine Regulator-Related Genes Predicts Prognoses and Immune Responses for Head and Neck Squamous Cell Carcinoma

This study aimed to construct a signature of N⁶-methyladenosine (m6A) regulator-related genes that could be used for the prognosis of head and neck squamous cell carcinoma (HNSCC) and to clarify the molecular and immune characteristics and benefits of immune checkpoint inhibitor (ICI) therapy using the prognostic signature to define the subgroups of HNSCC. This study showed that eighteen m6A regulators were abnormally expressed in the Cancer Genome Atlas (TCGA) HNSCC tissues compared with those in normal tissues. We constructed a signature of 12 m6A regulator-related genes using the Cox risk model, combined with the least absolute shrinkage and selection operator (Lasso) variable screening algorithm. Based on the median of the signature risk score, the patients were divided into high- and low-risk groups. The Kaplan-Meier survival analyses showed that patients with high-risk scores demonstrated poorer overall survival (OS) than those with low-risk scores based on TCGA-HNSCC data (p <0.001). The OS of high-risk patients was significantly worse than that of low-risk patients in the GSE65858 (p <0.001) and International Cancer Genome Consortium (ICGC) oral cancer cohorts (p = 0.0089). Furthermore, immune infiltration analyses showed that 8 types of immune cell infiltration showed highly significant differences between the two risk groups (p <0.001). In the Imvigor210CoreBiologies dataset of patients who received ICIs, the objective response rate (ORR) of the low-risk group (32%) was significantly higher than that of the high-risk group (13%). Additionally, patients in the high-risk group presented with a more significant adverse OS than that of the low-risk group (p = 0.00032). GSE78220 also showed that the ORR of the low-risk group (64%) was higher than that of the high-risk group (43%) and the OS of low-risk patients was better than that of high-risk patients (p = 0.0064). The constructed prognostic signature, based on m6A regulator-related genes, could be used to effectively distinguish between prognoses for HNSCC patients. The prognostic signature was found to be related to the immune cell infiltration of HNSCC; it might help predict the responses and prognoses of ICIs during treatment.

Sensory Ion Channel Candidates Inform on the Clinical Course of Pancreatic Cancer and Present Potential Targets for Repurposing of FDA-Approved Agents

Background: Transient receptor potential channels (TRPs) have been demonstrated to take on functions in pancreatic adenocarcinoma (PAAD) biology. However, little data are available that validate the potential of TRP in a clinical translational setting. Methods: A TRPs-related gene signature was constructed based on the Cox regression using a TCGA-PAAD cohort and receiver operating characteristic (ROC) was used to evaluate the predictive ability of this model. Core genes of the signature were screened by a protein-to-protein interaction (PPI) network, and expression validated by two independent datasets. The mutation analysis and gene set enrichment analysis (GSEA) were conducted. Virtual interventions screening was performed to discover substance candidates for the identified target genes. Results: A four TRPs-related gene signature, which contained MCOLN1, PKD1, TRPC3, and TRPC7, was developed and the area under the curve (AUC) was 0.758. Kaplan−Meier analysis revealed that patients with elevated signature score classify as a high-risk group featuring significantly shorter recurrence free survival (RFS) time, compared to the low-risk patients (p < 0.001). The gene prediction model also had a good predictive capability for predicting shortened overall survival (OS) and disease-specific survival (DSS) (AUC = 0.680 and AUC = 0.739, respectively). GSEA enrichment revealed the core genes of the signature, TRPC3 and TRPC7, were involved in several cancer-related pathways. TRPC3 mRNA is elevated in cancer tissue compared to control tissue and augmented in tumors with lymph node invasion compared to tumors without signs of lymph node invasion. Virtual substance screening of FDA approved compounds indicates that four small molecular compounds might be potentially selective not only for TRPC3 protein but also as a potential binding partner to TRPC7 protein. Conclusions: Our computational pipeline constructed a four TRP-related gene signature that enables us to predict clinical prognostic value of hitherto unrecognized biomarkers for PAAD. Sensory ion channels TRPC3 and TRPC7 could be the potential therapeutic targets in pancreatic cancer and TRPC3 might be involved in dysregulating mitochondrial functions during PAAD genesis.

Analysis and identification of m6A RNA methylation regulators in metastatic osteosarcoma

Osteosarcoma (OS) is characterized by rapid growth and early metastasis. However, its mechanism remains unclear. N6-methyladenosine (m6A) modification and its regulatory factors play essential roles in most cancers, including OS. In this study, we screened out 21 m6A modifiers using the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, followed by the identification of the critical m6A methylation modifiers. The results revealed that the expression levels of three m6A methylation regulators, namely RBM15, METTL3, and LRPPRC, were associated with the low survival rate of patients with OS. We further studied the independent prognostic factors by performing univariate and multivariate Cox analyses and found that metastasis was an independent prognostic factor for patients with OS. Furthermore, we found for the first time that RBM15 was specific for metastatic OS rather than non-metastatic OS. Moreover, the significant overexpression of RBM15 was validated in metastatic OS cell lines and in actual human clinical specimens. We also revealed that RBM15 promoted the invasion, migration, and metastasis of OS cells through loss-functional and gain-functional experiments and an animal metastatic model. In conclusion, RBM15 has a high correlation with OS metastasis formation and the decreased survival rate of patients with OS, and this may serve as a useful biomarker for predicting metastasis and prognosis of patients with OS.

Construction and validation of a novel prognostic model for lung squamous cell cancer based on N6-methyladenosine-related genes

Background

N6-methyladenosine (m6A) is the most prevalent modification in mRNA in biological processes and associated with various malignant tumor initiation and progression. The present study aimed to construct a prognostic risk model based on m6A-related genes (the downstream genes influenced by m6A modulators) for LUSC.

Methods

Based on TCGA, we stratified LUSC patients with and without genetic alteration of m6A modulators into altered and unaltered groups. Using univariate Cox and Lasso regression analyses, we identified prognostic m6A-related genes to construct a prognostic risk model. We then applied a multivariate Cox proportional regression model and the survival analysis to evaluate the risk model. Moreover, we performed the Receiver operating characteristic curve to assess the efficiency of the prognostic model based on TCGA and GSE43131. We analyzed the characteristics of tumor-associated immune cell infiltration in LUSC through the CIBERSORT method.

Results

Three m6A-related genes (FAM71F1, MT1E, and MYEOV) were identified as prognostic genes for LUSC. A novel prognostic risk model based on the three m6A-related genes was constructed. The multivariate Cox analysis showed that the prognostic risk model was an independent risk factor (HR = 2.44, 95% CI = 1.21~3.56, p = 0.029). Patients with a high-risk group had worse overall survival both in TCGA (p = 0.018) and GSE43131 (p = 0.00017). The 1, 2, and 3-year AUC value in TCGA was 0.662, 0.662, and 0.655, respectively; The 1, 2, and 3-year AUC value in GSE43131 was 0.724, 0.724, and 0.722, respectively. The proportion of infiltrated neutrophils in the high-risk group was higher than that in the low-risk group (p = 0.028), whereas that of resting NK cells (p = 0.002) was lower.

Conclusion

A novel prognostic risk model based on three m6A-related genes for LUSC was generated in this study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02509-1.

An Inflammatory Response Related Gene Signature Associated with Survival Outcome and Gemcitabine Response in Patients with Pancreatic Ductal Adenocarcinoma

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors with an extremely low 5-year survival rate. Accumulating evidence has unveiled that inflammatory response promotes tumor progression, enhances angiogenesis, and causes local immunosuppression. Herein, we aim to develop an inflammatory related prognostic signature, and found it could be used to predict gemcitabine response in PDAC.

Methods: PDAC cohorts with mRNA expression profiles and clinical information were systematically collected from the four public databases. An inflammatory response related genes (IRRGs) prognostic signature was constructed by LASSO regression analysis. Kaplan–Meier survival analysis, receiver operating characteristic analysis, principal component analysis, and univariate and multivariate Cox analyses were carried out to evaluate effectiveness, and reliability of the signature. The correlation between gemcitabine response and risk score was evaluated in the TCGA-PAAD cohort. The GDSC database, pRRophetic algorithm, and connectivity map analysis were used to predict gemcitabine sensitivity and identify potential drugs for the treatment of PDAC. Finally, we analyzed differences in frequencies of gene mutations, infiltration of immune cells, as well as biological functions between different subgroups divided by the prognostic signature.

Results: We established a seven IRRGs (ADM, DCBLD2, EREG, ITGA5, MIF, TREM1, and BTG2) signature which divided the PDAC patients into low- and high-risk groups. Prognostic value of the signature was validated in 11 PDAC cohorts consisting of 1337 PDAC patients from 6 countries. A nomogram that integrated the IRRGs signature and clinicopathologic factors of PDAC patients was constructed. The risk score showed positive correlation with gemcitabine resistance. Two drugs (BMS-536924 and dasatinib) might have potential therapeutic implications in high-risk PDAC patients. We found that the high-risk group had higher frequencies of KRAS, TP53, and CDKN2A mutations, increased infiltration of macrophages M0, neutrophils, and macrophages M2 cells, as well as upregulated hypoxia and glycolysis pathways, while the low-risk group had increased infiltration of CD8⁺ T, naïve B, and plasma and macrophages M1 cells.

Conclusion: We constructed and validated an IRRGs signature that could be used to predict the prognosis and gemcitabine response of patients with PDAC, as well as two drugs (BMS-536924 and dasatinib) may contribute to PDAC treatment.

Identification and Validation of a Prognostic Prediction Model of m6A Regulator-Related LncRNAs in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly invasive malignancy prone to recurrence, and patients with HCC have a low 5-year survival rate. Long non-coding RNAs (lncRNAs) play a vital role in the occurrence and development of HCC. N6-methyladenosine methylation (m6A) is the most common modification influencing cancer development. Here, we used the transcriptome of m6A regulators and lncRNAs, along with the complete corresponding clinical HCC patient information obtained from The Cancer Genome Atlas (TCGA), to explore the role of m6A regulator-related lncRNA (m6ARlnc) as a prognostic biomarker in patients with HCC. The prognostic m6ARlnc was selected using Pearson correlation and univariate Cox regression analyses. Moreover, three clusters were obtained via consensus clustering analysis and further investigated for differences in immune infiltration, immune microenvironment, and prognosis. Subsequently, nine m6ARlncs were identified with Lasso-Cox regression analysis to construct the prognostic signature m6A-9LPS for patients with HCC in the training cohort (n = 226). Based on m6A-9LPS, the risk score for each case was calculated. Patients were then divided into high- and low-risk subgroups based on the cutoff value set by the X-tile software. m6A-9LPS showed a strong prognosis prediction ability in the validation cohort (n = 116), the whole cohort (n = 342), and even clinicopathological stratified survival analysis. Combining the risk score and clinical characteristics, we established a nomogram for predicting the overall survival (OS) of patients. To further understand the mechanism underlying the m6A-9LPS-based classification of prognosis differences, KEGG and GO enrichment analyses, competitive endogenous RNA (ceRNA) network, chemotherapeutic agent sensibility, and immune checkpoint expression level were assessed. Taken together, m6A-9LPS could be used as a precise prediction model for the prognosis of patients with HCC, which will help in individualized treatment of HCC.

Development of a Gene Risk Signature for Patients of Pancreatic Cancer

BACKGROUND

Pancreatic cancer is a highly malignant solid tumor with a high lethality rate, but there is a lack of clinical biomarkers that can assess patient prognosis to optimize treatment.

METHODS

Gene-expression datasets of pancreatic cancer tissues and normal pancreatic tissues were obtained from the GEO database, and differentially expressed genes analysis and WGCNA analysis were performed after merging and normalizing the datasets. Univariate Cox regression analysis and Lasso Cox regression analysis were used to screen the prognosis-related genes in the modules with the strongest association with pancreatic cancer and construct risk signatures. The performance of the risk signature was subsequently validated by Kaplan-Meier curves, receiver operating characteristic (ROC), and univariate and multivariate Cox analyses.

RESULT

A three-gene risk signature containing CDKN2A, BRCA1, and UBL3 was established. Based on KM curves, ROC curves, and univariate and multivariate Cox regression analyses in the TRAIN cohort and TEST cohort, it was suggested that the three-gene risk signature had better performance in predicting overall survival.

CONCLUSION

This study identifies a three-gene risk signature, constructs a nomogram that can be used to predict pancreatic cancer prognosis, and identifies pathways that may be associated with pancreatic cancer prognosis.

Phospholipid Phosphatase 4 as a Driver of Malignant Glioma and Pancreatic Adenocarcinoma

Glioma and pancreatic cancer are tumors with a high degree of malignancy, morbidity, and mortality. The present study explored possible molecular mechanisms and potential diagnostic and prognostic biomarker-PLPP4 of glioma and PAAD. PLPP4 is differentially elevated in glioma and PAAD tissues. Statistical analysis from TCGA demonstrated that high expression of PLPP4 significantly and positively correlated with clinicopathological features, including pathological grade and poor overall survival in glioma and PAAD patients. Following this, the methylation levels of PLPP4 also affected overall survival in clinical tissue samples. Silencing PLPP4 inhibited proliferation, invasion, and migration in LN229 cells and PANC-1 cells. Moreover, the combination of multiple proteins for the prognosis prediction of glioma and PAAD was evaluated. These results were conducted to elaborate on the potential roles of the biomarker-PLPP4 in clonability and invasion of glioma and PAAD cells.

Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer

Pancreatic cancer (PAAD) is one of the most malignant cancers and immune microenvironment has been proved to be involved in pathogenesis of PAAD. m6A modification, related to the expression of m6A regulators, participates in the development of multiple cancers. However, the correlation between m6A regulators and immune microenvironment was largely unknown in PAAD. And because of the small sample size of pancreatic cancer in the TCGA database, it is not enough to draw a convincing conclusion. In the present study, we downloaded seven pancreatic cancer datasets with survival data and removed batch effects among these datasets to be used as the PAAD cohort to analyze the immune landscape of PAAD and the expression pattern of m6A regulators and divided the integrated dataset into cluster 1 and cluster 2 by consensus clustering for m6A regulators. Lower m6A regulators were found to be related to higher immune cell infiltration and a better survival. Moreover, we identified six m6A regulators and constructed the prognostic signature of m6A regulators. Patients with low-risk score had a higher response to immune checkpoint inhibitor and a longer overall survival. To figure out the underlying mechanism, we analyzed the cancer immunity cycle, most altered genes, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) in risk subtypes. In summary, the present study proved m6A regulators modulated the PAAD immune microenvironment. And risk scores served as predictive indicator for immunotherapy and played a prognostic role for PAAD patients. Our study provided novel therapeutic targets to improve immunotherapy efficacy.

m6A Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Pancreatic Cancer

Recent studies have shown that RNA N⁶-methyladenosine (m⁶A) modification plays an important part in tumorigenesis and immune-related biological processes. However, the comprehensive landscape of immune cell infiltration characteristics in the tumor microenvironment (TME) mediated by m⁶A methylation modification in pancreatic cancer has not yet been elucidated. Based on consensus clustering algorithm, we identified two m⁶A modification subtypes and then determined two m⁶A-related gene subtypes among 434 pancreatic cancer samples. The TME characteristics of the identified gene subtypes were highly consistent with the immune-hot phenotype and the immune-cold phenotype respectively. According to the m⁶A score extracted from the m⁶A-related signature genes, patients can be divided into high and low m⁶A score groups. The low score group displayed a better prognosis and relatively strong immune infiltration. Further analysis showed that low m⁶A score correlated with lower tumor mutation burden and PD-L1 expression, and indicated a better response to immunotherapy. In general, m⁶A methylation modification is closely related to the diversity and complexity of immune infiltration in TME. Evaluating the m⁶A modification pattern and immune infiltration characteristics of individual tumors can help deepen our understanding of the tumor microenvironment landscape and promote a more effective clinical practice of immunotherapy.

Characterization of Modification Patterns, Biological Function, Clinical Implication, and Immune Microenvironment Association of m6A Regulators in Pancreatic Cancer

Objective: N⁶-methyladenosine (m⁶A) modification may modulate various biological processes. Nonetheless, clinical implications of m⁶A modification in pancreatic cancer are undefined. Herein, this study comprehensively characterized the m⁶A modification patterns in pancreatic cancer based on m⁶A regulators. Methods: Genetic mutation and expression pattern of 21 m⁶A regulators and their correlations were assessed in pancreatic cancer from TCGA dataset. m⁶A modification patterns were clustered using unsupervised clustering analysis in TCGA and ICGC datasets. Differences in survival, biological functions and immune cell infiltrations were assessed between modification patterns. A m⁶A scoring system was developed by principal component analysis. Genetic mutations and TIDE scores were compared between high and low m⁶A score groups. Results: ZC3H13 (11%), RBM15B (9%), YTHDF1 (8%), and YTHDC1 (6%) frequently occurred mutations among m⁶A regulators. Also, most of regulators were distinctly dysregulated in pancreatic cancer. There were tight crosslinks between regulators. Two m⁶A modification patterns were constructed, with distinct prognoses, immune cell infiltration and biological functions. Furthermore, we quantified m⁶A score in each sample. High m⁶A scores indicated undesirable clinical outcomes. There were more frequent mutations in high m⁶A score samples. Lower TIDE score was found in high m⁶A score group, with AUC = 0.61, indicating that m⁶A scores might be used for predicting the response to immunotherapy. Conclusion: Collectively, these data demonstrated that m⁶A modification participates pancreatic cancer progress and ornaments immune microenvironment, providing an insight into pancreatic cancer pathogenesis and facilitating precision medicine development.

Effects of RNA methylation N6-methyladenosine regulators on malignant progression and prognosis of melanoma

Background

Melanoma is an extremely aggressive type of skin cancer and experiencing a expeditiously rising mortality in a current year. Exploring new potential prognostic biomarkers and therapeutic targets of melanoma are urgently needed. The ambition of this research was to identify genetic markers and assess prognostic performance of N6-methyladenosine (m6A) regulators in melanoma.

Methods

Gene expression data and corresponding clinical informations of melanoma patients as well as sequence data of normal controls are collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Quantitative real-time PCR (qRT-PCR) analysis was carried out to detect the RNA expression of IGF2BP3 in A375 cell line, melanoma tissues, and normal tissues. Western blot, cell proliferation, and migration assays were performed to assess the ability of IGF2BP3 in A375 cell line.

Results

Differently expressed m6A regulators between tumor samples and normal samples were analyzed. A three-gene prognostic signature including IGF2BP3, RBM15B, and METTL16 was constructed, and the risk score of this signature was identified to be an independent prognostic indicator for melanoma. In addition, IGF2BP3 was verified to promote melanoma cell proliferation and migration in vitro and associate with lymph node metastasis in clinical samples. Moreover, risk score and the expression of IGF2BP3 were positively associated with the infiltrating immune cells and these hub genes made excellent potential drug targets in melanoma.

Conclusion

We identified the genetic changes in m6A regulatory genes and constructed a three-gene risk signature with distinct prognostic value in melanoma. This research provided new insights into the epigenetic understanding of m6A regulators and novel therapeutic strategies in melanoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02163-9.

N6-Methylandenosine-Related lncRNA Signature Is a Novel Biomarkers of Prognosis and Immune Response in Colon Adenocarcinoma Patients

Background

Colon adenocarcinoma (COAD) is the most common type of colon cancer. To date, however, the prognostic values of m6A RNA methylation-related long non-coding RNAs (lncRNAs) in COAD are largely unknown.

Materials and Methods

The m6A-related lncRNAs were identified from The Cancer Genome Atlas (TCGA) data set. Univariate and multivariate Cox regression analyses were performed to explore the prognostic m6A-related lncRNAs. Consistent clustering analysis was performed to classify the COAD patients into different subgroups based on the expression of m6A-related lncRNAs. The potential biological functions as well as differences in the stemness index and tumor immune microenvironment between different subgroups were analyzed. The prognostic m6A-related lncRNAs were used to establish an m6A-related lncRNA risk model to predict prognosis and survival status.

Results

We identified 31 m6A-associated lncRNAs with prognostic values from the TCGA data set. Based on the expression of prognostic m6A-associated lncRNAs, TCGA-COAD patients were classified into three clusters using consistent clustering analysis. There was a low correlation of tumor stemness between the three clusters but a significant correlation with the tumor immune microenvironment as well as the tumor mutational load. Thirty-one prognostic-related m6A-associated lncRNAs were used to construct a risk model, which was further determined by survival analysis, receiver operating characteristic (ROC) curve, and univariate and multifactor Cox analysis. The m6A-related risk model demonstrates good performance in predicting prognosis and survival status. The model-based high-risk group exhibited poorer overall survival (OS) compared with the low-risk group.

Conclusion

In this study, we construct a risk model that consists of 31 m6A-related lncRNAs with independent prognostic values in COAD. Our study shows the critical roles of these 31 m6A-related lncRNAs in the tumor immune microenvironment, indicating the prospect of informing prognostic stratification and the development of immunotherapeutic strategies for COAD patients.

Function and clinical significance of N6-methyladenosine in digestive system tumours

RNA modification, like DNA methylation, histone modification, non-coding RNA modification and chromatin rearrangement, plays an important role in tumours. N6-methyladenosine (m6A) is the most abundant RNA modification in cells, and it regulates RNA transcription, processing, splicing, degradation, and translation. m6A-associated proteins have been used as new biomarkers and therapeutic targets for tumour prediction and monitoring. There are three main types of proteins involved in m6A methylation: methyltransferases (METTL3, METTL14, WTAP, RBM15, ZC3H13 and KIAA1429), demethylases (FTO, ALKBH5 and ALKBH3) and RNA-binding proteins (YTHDF1-3, YTHDC1-2, IGF2BPs and HNRNPs). This article reviews the origins, characteristics and functions of m6A and its relationship with digestive system tumours based on recent research. The expression of m6A regulators can be used as an evaluation indicator of tumour growth and progression and as a prognostic indicator. In-depth research on m6A methylation in digestive system tumours may provide new directions for clinical prediction and further treatment.

Impact of YTHDF1 gene polymorphisms on Wilms tumor susceptibility: A five-center case-control study

Background

Wilms tumor is the most frequent renal malignancy in children. YTHDF1 is associated with the development of several kinds of cancers, yet whether common variants of the YTHDF1 gene influence Wilms tumor risk is unknown. We present, here, a hospital‐based case‐control study specifically designed to investigate the role of YTHDF1 genetic variants on Wilms tumor.

Methods

We successfully genotyped samples of 408 Wilms tumor cases and 1198 controls which were collected from five hospitals across China. The unconditional logistic regression was adopted to analyze the contributions of YTHDF1 gene single nucleotide polymorphisms (SNPs) to the risk of Wilms tumor. The odds ratio (OR) and 95% confidence interval (CI) were generated to evaluate the conferring risk of YTHDF1 gene SNPs (rs6011668 C>T, rs6090311 A>G).

Results

Neither of the two SNPs could contribute to the risk of Wilms tumor. A negative association was also detected in the combined effects of protective genotypes on Wilms tumor risk. The stratification analysis revealed that compared with those with CC genotype, rs6011668 CT/TT genotype was associated with increased Wilms tumor risk in those ≤18 months (OR = 1.54, 95% CI = 1.02–2.30, p = 0.038), and with decreased Wilms tumor risk in those >18 months (OR = 0.70, 95% CI = 0.50–0.97, p = 0.034).

Conclusion

Our present work sheds some light on the potential role of YTHDF1 gene polymorphisms on Wilms tumor risk.

N6-methyladenosine (m6A) in pancreatic cancer: Regulatory mechanisms and future direction

N6-methyladenosine (m6A), the most abundant RNA modification in eukaryotes, plays a pivotal role in regulating many cellular and biological processes. Aberrant m6A modification has recently been involved in carcinogenesis in various cancers, including pancreatic cancer. Pancreatic cancer is one of the deadliest cancers. It is a heterogeneous malignant disease characterized by a plethora of diverse genetic and epigenetic events. Increasing evidence suggests that dysregulation of m6A regulatory factors, such as methyltransferases, demethylases, and m6A-binding proteins, profoundly affects the development and progression of pancreatic cancer. In addition, m6A regulators and m6A target transcripts may be promising early diagnostic and prognostic cancer biomarkers, as well as therapeutic targets. In this review, we highlight the biological functions and mechanisms of m6A in pancreatic cancer and discuss the potential of m6A modification in clinical applications.

Recent advances in functional annotation and prediction of the epitranscriptome

RNA modifications, in particular N⁶-methyladenosine (m⁶A), participate in every stages of RNA metabolism and play diverse roles in essential biological processes and disease pathogenesis. Thanks to the advances in sequencing technology, tens of thousands of RNA modification sites can be identified in a typical high-throughput experiment; however, it remains a major challenge to decipher the functional relevance of these sites, such as, affecting alternative splicing, regulation circuit in essential biological processes or association to diseases. As the focus of RNA epigenetics gradually shifts from site discovery to functional studies, we review here recent progress in functional annotation and prediction of RNA modification sites from a bioinformatics perspective. The review covers naïve annotation with associated biological events, e.g., single nucleotide polymorphism (SNP), RNA binding protein (RBP) and alternative splicing, prediction of key sites and their regulatory functions, inference of disease association, and mining the diagnosis and prognosis value of RNA modification regulators. We further discussed the limitations of existing approaches and some future perspectives.

N6 -methyladenosine Steers RNA Metabolism and Regulation in Cancer

As one of the most studied ribonucleic acid (RNA) modifications in eukaryotes, N⁶ -methyladenosine (m⁶ A) has been shown to play a predominant role in controlling gene expression and influence physiological and pathological processes such as oncogenesis and tumor progression. Writer and eraser proteins, acting opposite to deposit and remove m⁶ A epigenetic marks, respectively, shape the cellular m⁶ A landscape, while reader proteins preferentially recognize m⁶ A modifications and mediate fate decision of the methylated RNAs, including RNA synthesis, splicing, exportation, translation, and stability. Therefore, RNA metabolism in cells is greatly influenced by these three classes of m⁶ A regulators. Aberrant expression of m⁶ A regulators has been widely reported in various types of cancer, leading to cancer initiation, progression, and drug resistance. The close links between m⁶ A and cancer shed light on the potential use of m⁶ A methylation and its regulators as prognostic biomarkers and drug targets for cancer therapy. Given the notable effects of m⁶ A in reversing chemoresistance and enhancing immune therapy, it is a promising target for combined therapy. Herein, we summarize the recent discoveries on m⁶ A and its regulators, emphasizing their influences on RNA metabolism, their dysregulation and impacts in diverse malignancies, and discuss the clinical implications of m⁶ A modification in cancer.

A novel tp53-associated nomogram to predict the overall survival in patients with pancreatic cancer

BACKGROUND

Gene mutations play critical roles in tumorigenesis and cancer development. Our study aimed to screen survival-related mutations and explore a novel gene signature to predict the overall survival in pancreatic cancer.

METHODS

Somatic mutation data from three cohorts were used to identify the common survival-related gene mutation with Kaplan-Meier curves. RNA-sequencing data were used to explore the signature for survival prediction. First, Weighted Gene Co-expression Network Analysis was conducted to identify candidate genes. Then, the ICGC-PACA-CA cohort was applied as the training set and the TCGA-PAAD cohort was used as the external validation set. A TP53-associated signature calculating the risk score of every patient was developed with univariate Cox, least absolute shrinkage and selection operator, and stepwise regression analysis. Kaplan-Meier and receiver operating characteristic curves were plotted to verify the accuracy. The independence of the signature was confirmed by the multivariate Cox regression analysis. Finally, a prognostic nomogram including 359 patients was constructed based on the combined expression data and the risk scores.

RESULTS

TP53 mutation was screened to be the robust and survival-related mutation type, and was associated with immune cell infiltration. Two thousand, four hundred fifty-five genes included in the six modules generated in the WGCNA were screened as candidate survival related TP53-associated genes. A seven-gene signature was constructed: Risk score = (0.1254 × ERRFI1) - (0.1365 × IL6R) - (0.4400 × PPP1R10) - (0.3397 × PTOV1-AS2) + (0.1544 × SCEL) - (0.4412 × SSX2IP) - (0.2231 × TXNL4A). Area Under Curves of 1-, 3-, and 5-year ROC curves were 0.731, 0.808, and 0.873 in the training set and 0.703, 0.677, and 0.737 in the validation set. A prognostic nomogram including 359 patients was constructed and well-calibrated, with the Area Under Curves of 1-, 3-, and 5-year ROC curves as 0.713, 0.753, and 0.823.

CONCLUSIONS

The TP53-associated signature exhibited good prognostic efficacy in predicting the overall survival of PC patients.

Trials and tribulations of pancreatic cancer immunotherapy

Immunotherapy has revolutionized cancer treatment in the last decade, and strategies to re-activate cytotoxic immunity are now standard of care in several malignancies. Despite rapid advances in immunotherapy for most solid cancers, progress in immunotherapy against pancreatic ductal adenocarcinoma (PDAC) has been exceptionally difficult. This is true for several approaches, most notably immune checkpoint inhibitors (ICIs) and GM-CSF cell-based vaccines (GVAX). Though many immunotherapies have been explored in clinical trials, few have shown significant therapeutic efficacy. Further, many have shown high rates of serious adverse effects and dose-limiting toxicities, and to date, immunotherapy regimens have not been successfully implemented in PDAC. Here, we provide a comprehensive summary of the key clinical trials exploring immunotherapy in PDAC, followed by a brief discussion of emerging molecular mechanisms that may explain the relative failure of immunotherapy in pancreas cancer thus far.

HNRNPA2B1 Affects the Prognosis of Esophageal Cancer by Regulating the miR-17-92 Cluster

N6-methyladenosine (m6A) is the most abundant RNA modification in eukaryotes. Accumulating evidence suggests that dysregulation of m6A modification significantly correlates with tumorigenesis and progression. In this study, we observed an increased expression and positive correlations of all 25 m6A regulators in esophageal cancer (ESCA) data obtained from the TCGA database. Through expression profiling of these regulators, a prognostic score model containing HNRNPA2B1, ALKBH5, and HNRNPG was established, and the high-risk subgroup exhibited strong positive correlations with ESCA progression and outcome. The risk score obtained from this model may represent an independent predictor of ESCA prognosis. Notably, the gene most frequently associated with increased risk was HNRNPA2B1; in ESCA, the increased expression of this gene alone predicted poor prognosis by affecting tumor-promoting signaling pathways through miR-17-92 cluster. An experimental study demonstrated that elevated HNRNPA2B1 expression was positively associated with distant metastasis and lymph node stage, and predicted the poor outcomes of ESCA patients. Knockdown of HNRNPA2B1 significantly decreased the expression of miR-17, miR-18a, miR-20a, miR-93, and miR-106b and inhibited the proliferation of ESCA cells. Therefore, our study indicated that the dynamic changes in 25 m6A regulators were associated with the clinical features and prognosis of patients with ESCA. Importantly, HNRNPA2B1 alone may affect the prognosis of patients with ESCA by regulating the miR-17-92 cluster.

Clinical and prognostic pan-cancer analysis of m6A RNA methylation regulators in four types of endocrine system tumors

N6-methyladenosine (m6A), internal modification of mRNA, has recently been reported to be an important regulatory mechanism affecting tumor proliferation. However, its role in endocrine system tumors is poorly understood. We obtained datasets for four types tumors from the TCGA database, analyzed the GTEx database as a supplement to the control group, and used “Perl” and “R” software to analyze the datasets. Then we differentiated the expression level, used it to cluster consensus. Besides, we established lasso regression model to screen variables, used univariate and multivariate cox analyses to explore the independent risk factors associated with cancer prognosis. The results indicated that except for WTAP, the expression level of METTL3 was negatively correlated with other genes. The expression level of WTAP and METTL16 was positively correlated with overall survival (OS). Moreover, we found that different clinical subtypes of adrenal cortical carcinoma had significant differences in survival status, histologic grading, pathological T grade, and OS. Furthermore, different clinical subtypes of thyroid carcinoma had significant differences in histologic grading and pathological T grade. The differential expression of m6A regulatory genes is closely associated with the presence of endocrine-system-related tumors, and risk scores can be used to assess prognosis.

M6A Regulatory Genes Play an Important Role in the Prognosis, Progression and Immune Microenvironment of Pancreatic Adenocarcinoma

The specific roles of N6-methyladenosine (m6A) regulatory genes in pancreatic adenocarcinoma (PAAD) have not been fully elucidated. In present study, a novel risk signature was constructed by five m6A-related genes (including METTL3, METTL14, KIAA1429, ALKBH5 and YTHDF1) and was identified as an independent prognostic factor (HR = 13.192) via TCGA (185 samples) databases. The immune abundances of 22 leukocyte subtypes in each PAAD sample were exhibited via the CIBERSORT algorithm. High risk group promoted infiltration levels of Macrophages M0 and M2 cells and decreased that of B cells naive, T cells CD8 and T regulatory cells.