Background: N⁶-methyladenosine (m⁶A), is the most common modification found in mRNA and lncRNA in higher organisms and plays an important role in physiology and pathology. However, its role in pan-cancer has not been explored. Results: A total of 31 m⁶A modification regulators, including 12 writers, 2 erasers, and 17 readers are identified in the current study. The functional analysis of the regulators results in the enrichment of processes, primarily related to RNA modification and metabolism, and the PPI network reveals multiple interactions among the regulators. The mRNA expression analysis reveals a high expression for most of the regulators in pan-cancer. Most of the m⁶A regulators are found to be mutated across the cancers, with ZC3H13, VIRMA, and PRRC2A having a higher frequency rate. Significant correlations of the regulators with clinicopathological parameters, such as age, gender, tumor stage, and grade are identified in pan-cancer. The m⁶A regulators’ expression is found to have significant positive correlations with the miRNAs in pan-cancer. The expression pattern of the m⁶A regulators is able to classify the tumors into different subclusters as well as into high- and low-risk groups. These tumor groups show differential patterns in terms of their immune cell infiltration, tumor stemness score, genomic heterogeneity score, expression of immune regulatory/checkpoint genes, and correlations between the regulators and the drugs. Conclusions: Our study provide a comprehensive overview of the functional roles, genetic and epigenetic alterations, and prognostic value of the RNA m⁶A regulators in pan-cancer.

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor.Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs.Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML.Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

Introduction: Primary testicular diffuse large B-cell lymphoma (PT-DLBCL) is a rare and aggressive form of mature B-cell lymphoma commonly found in elder males, but its genetic features are poorly understood. In this study, we had performed target-sequencing of 360 lymphoma-related genes on 76 PT-DLBCL patients with a median age of 65 (33– 89). Our data provide a comprehensive understanding of the landscape of mutations in a small subset of PT-DLBCL. Methods: A total of 76 PT-DLBCL patients were sequenced, and their clinical data and follow-up data were collected. The relationship between mutated genes, clinical data and prognosis and survival of PT-DLBCL patients was retrospectively analyzed by statistical software. Results: We observed a median of 15 protein-altering variants per patient in our data and was identified recurrent oncogenic mutations of 360 lymphoma-related genes involved in PT-DLBCL, including PIM1 (74%), MYD88 (50%), KMT2D (38%), KMT2C (34%), BTG2 (34%), TBL1XR1 (34%) and ETV6 (24%). Compared with classic DLBCL, PT-DLBCL showed an increased mutation frequency of PIM1, MYD88, BTG2, while NOTCH1 appeared exclusive mutated with PIM1, MSH3 and ETV6. Cox risk model regression analysis showed that age ≥ 60 years, IPI 3– 5 points, BTG2 gene mutation and extranodal organ invasion suggested poor prognosis. Finally, we constructed an OS predict model of PT-DLBCL patients using above factors with a high accuracy. Conclusion: In conclusion, our results revealed genomic characterization of PT-DLBCL, and the mutation of BTG2 was an independent factor predicting a poor prognosis.

Acute myeloid leukemia (AML) is a highly heterogeneous malignant disease of the blood cell. The current therapies for AML are unsatisfactory and the molecular mechanisms underlying AML are unclear. 5-methylcytosine (m5C) is an important posttranscriptional modification of mRNA, and is involved in the regulation of mRNA stability, translation, and other aspects of RNA metabolism. However, based on our knowledge of published literature, the role of the m5C regulators has not been explored in AML till date. In this study, we clarified the expression and gene variants of m5C regulators in AML and found that most m5C regulators were differentially expressed and correlated with disease prognosis. We also found that the methylation status of certain m5C regulators (e.g., DNMT3A, DNMT3B) affects the survival of AML patients. Two m5C modification subtypes, and high- and low-risk subgroups identified based on the expression of m5C regulators showed significant differences in the prognosis as well as immune cell infiltration. In addition, most of the m5C regulators were found to be correlated with miRNA expression in AML, as well as IC50 values of many drugs. The miRNA and GSVA analysis were used to identify the different miRNAs and KEGG or hallmark pathways between high- and low-risk subgroups. We also built a prognostic model based on m5C regulators, which was validated by two GSE databases. To verify the reliability of our analysis and conclusions, qPCR was used to identify the expressions of m5C regulators between normal and AML. In summary, we comprehensively explored the molecular characteristics of m5C regulators and built a prognostic model in AML. We proposed new mechanistic insights into the role of m5C in multiple databases and clinical data, which may pave novel ways for the development of therapeutic strategies.

Background: Ankylosing Spondylitis (AS) and inflammatory bowel disease (IBD) exhibit substantial pathophysiological overlap, including dysregulated innate immunity, barrier dysfunction, and Th17-mediated inflammation. However, whether Na⁺ overload-related genes (NRGs) exhibit shared transcriptional alterations in IBD and AS remains unclear. This study aimed to characterize the expression patterns of NRGs across IBD and AS and to identify candidate genes associated with both diseases. Methods: Differential expression analysis was performed to identify differentially expressed NRGs (DE-NRGs) in diseased tissues relative to normal tissues. Shared DE-NRGs between IBD and AS were screened and defined as common differentially expressed NRGs (Co-DE-NRGs). We then analyzed the correlations of these Co-DE-NRGs and explored their relationships with immune cell infiltration in target tissues. Four machine learning algorithms were applied to screen key NRGs associated with both IBD and AS. Potential therapeutic agents targeting these core biomarkers were predicted using drug–gene interaction databases, and molecular docking was conducted for further validation. Results: A total of 32 shared Co-DE-NRGs were identified for IBD and AS, with nine key regulatory NRGs recognized: CALR, CD63, CYBA, DYSF, HYOU1, IL1B, JAK1, MMP9, and STAT3. Exploratory MR analysis identified disease-specific associations between genetically predicted expression of NRGs and CD, UC, and AS. Genetically predicted STAT3 expression showed positive associations with CD and UC but an inverse association with AS and therefore did not represent a consistent risk factor across the three diseases. Furthermore, transcriptome-based drug-response analysis identified four candidate agents shared between AS and at least one IBD dataset: ciclosporin, BCL-LZH-4, BRD-K79669418, and CID-5951923. Exploratory molecular docking generated STAT3 binding poses for BCL-LZH-4 and CID-5951923, with DOCK Grid Scores of −35.321896 and −28.361128, respectively. CID-5951923 was selected for representative visualization of its predicted interaction with STAT3. Single-cell RNA-sequencing analysis identified tissue- and cell-type-specific STAT3 mRNA expression patterns in the analyzed IBD colonic and AS peripheral-blood datasets, with monocytes representing a major cell population exhibiting detected STAT3 expression in the AS dataset. Conclusions: These findings identify shared NRG-related transcriptional alterations in IBD and AS, with STAT3 emerging as a candidate gene associated with both diseases. Further experimental studies are required to determine whether these alterations reflect the involvement of NECSO and to evaluate their potential diagnostic or therapeutic relevance.

Background: Plasticizers, including phthalate esters and phthalate-free alternatives, are widely detected environmental chemicals. Although increasing evidence suggests that plasticizers may disrupt gastrointestinal homeostasis, their potential molecular links with inflammatory gastrointestinal disorders (IGDs) remain unclear. Methods: This study aimed to systematically identify potential molecular targets and pathways linking representative plasticizers with IGDs. An integrative network toxicology framework was applied to investigate four plasticizers, including dimethyl phthalate (DMP), diethyl phthalate (DEP), dioctyl phthalate/di(2-ethylhexyl) phthalate (DOP/DEHP), and acetyl tributyl citrate (ATBC), in relation to Crohn’s disease (CD), ulcerative colitis (UC), esophagitis, and gastritis. Plasticizer- and disease-related targets were collected from public databases, followed by overlapping target screening, protein–protein interaction network analysis, functional enrichment analysis, GEO-based transcriptomic validation, molecular docking, molecular dynamics simulation, and single-cell RNA-seq analysis. Results: Disease-specific candidate targets were identified, including CXCL8 and FN1 for CD, IL1B for UC, MAPK3, FASN, FN1, PPARG, CXCL8, FOS, and HIF1A for esophagitis, and MMP9, TNF, TLR4, IL6, CCR2, IFNG, and PTGS2 for gastritis. Cross-disease analysis further identified plasticizer-associated signature targets, including MMP7 for DMP, HMOX1 and NOS2 for DEP, and LTF and CCL11 for ATBC. Enrichment analysis indicated that these targets were mainly involved in inflammatory, chemokine, MAPK-related, and xenobiotic response pathways. Molecular docking and dynamics simulations suggested stable interactions between selected plasticizers and candidate targets, while single-cell analysis revealed their cell-type-specific expression patterns in epithelial, immune, and stromal compartments. Conclusions: This study provides an exploratory network toxicology framework for identifying potential molecular associations between plasticizer exposure and IGDs. The findings highlight disease-specific and plasticizer-associated candidate targets that may guide future experimental validation and environmental risk assessment.