Identification of Candidate Biomarker ASXL2 and Its Predictive Value in Pancreatic Carcinoma

Additional Sex Combs-like Family Associated with Epigenetic Regulation

The additional sex combs-like (ASXL) family, a mammalian homolog of the additional sex combs (Asx) of Drosophila, has been implicated in transcriptional regulation via chromatin modifications. Abnormal expression of ASXL family genes leads to myelodysplastic syndromes and various types of leukemia. De novo mutation of these genes also causes developmental disorders. Genes in this family and their neighbor genes are evolutionary conserved in humans and mice. This review provides a comprehensive summary of epigenetic regulations associated with ASXL family genes. Their expression is commonly regulated by DNA methylation at CpG islands preceding transcription starting sites. Their proteins primarily engage in histone tail modifications through interactions with chromatin regulators (PRC2, TrxG, PR-DUB, SRC1, HP1α, and BET proteins) and with transcription factors, including nuclear hormone receptors (RAR, PPAR, ER, and LXR). Histone modifications associated with these factors include histone H3K9 acetylation and methylation, H3K4 methylation, H3K27 methylation, and H2AK119 deubiquitination. Recently, non-coding RNAs have been identified following mutations in the ASXL1 or ASXL3 gene, along with circular ASXLs and microRNAs that regulate ASXL1 expression. The diverse epigenetic regulations linked to ASXL family genes collectively contribute to tumor suppression and developmental processes. Our understanding of ASXL-regulated epigenetics may provide insights into the development of therapeutic epigenetic drugs.

Identification of a de novo variant in the ASXL2 gene related to Shashi-Pena syndrome

BACKGROUND

ASXL2 encodes proteins involved in epigenetic regulation and the assembly of transcription factors at specific genomic loci. Germline de novo truncating variants in ASXL2 have been implicated in Shashi-Pena syndrome, which results in features of developmental delay (DD), glabellar nevus flammeus, hypotonia, and cardiac disorders. However, the variants are rare, and the clinical spectrum may be incomplete.

METHODS

The clinical data such as brain MRI were collect. The whole exome sequencing was performed for genetic etiology analysis.

RESULTS

Here, we report a patient with DD, hypotonia, early atrial septal defect, and abnormal white matter signal. She presented with Shashi-Pena syndrome with a truncated variant in ASXL2 (NM_018263.6, c.2142_2152del, p.Ser714Argfs*5). She died of a digestive tract infection when she was 1 year and 6 months old.

CONCLUSIONS

Our study further expanded the spectrum of phenotypes and genetic variations of the syndrome, and we believe that it is necessary to screen the ASXL2 gene in patients with DD and cardiac and bone disorders.

Glycolysis-Related LINC02432/Hsa-miR-98–5p/HK2 Axis Inhibits Ferroptosis and Predicts Immune Infiltration, Tumor Mutation Burden, and Drug Sensitivity in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a malignant cancer with high incidence and mortality. Glycometabolic rearrangements (aerobic glycolysis) is a hallmark of PAAD and contributes to tumorigenesis and progression through numerous mechanisms. This study aimed to identify a novel glycolysis-related lncRNA-miRNA-mRNA ceRNA signature in PAAD and explore its potential molecular function. We first calculated the glycolysis score for each PAAD patient by the ssGSEA algorithm and found that patients with higher hallmark glycolysis scores had poorer prognosis. Subsequently, we obtained a novel glycolysis-related LINC02432/hsa-miR-98–5p/HK2 axis from the TCGA and GEO databases using comprehensive bioinformatics analysis and developed a nomogram to predict overall survival. Furthermore, functional characterization analysis revealed that LINC02432/hsa-miR-98–5p/HK2 axis risk score was negatively correlated with ferroptosis. The tumor immune infiltration analysis suggested positive correlations between ceRNA risk score and infiltrated M0 macrophage levels in PAAD. Correlation analysis found that ceRNA risk scores were positively correlated with four chemokines (CXCL3, CXCL5, CXCL8 and CCL20) and one immune checkpoint gene (SIGLEC15). Meanwhile, tumor mutation burden (TMB), an indicator for predicting response to immunotherapy, was positively correlated with ceRNA risk score. Finally, the drug sensitivity analysis showed that the high-risk score patients might be more sensitive to EGFR, MEK and ERK inhibitors than low-risk score patients. In conclusion, our study suggested that LINC02432/hsa-miR-98–5p/HK2 axis may serve as a novel diagnostic, prognostic, and therapeutic target in PAAD treatment.

Identification of NAD+ Metabolism-Derived Gene Signatures in Ovarian Cancer Prognosis and Immunotherapy

Background: Nicotinamide adenine dinucleotide (NAD⁺) has emerged as a critical regulator of cell signaling and survival pathways, affecting tumor initiation and progression. In this study it was investigated whether circulating NAD⁺ metabolism-related genes (NMRGs) could be used to predict immunotherapy response in ovarian cancer (OC) patients.

Method: In this study, NMRGs were comprehensively examined in OC patients, three distinct NMRGs subtypes were identified through unsupervised clustering, and an NAD⁺-related prognostic model was generated based on LASSO Cox regression analysis and generated a risk score (RS). ROC curves and an independent validation cohort were used to assess the model’s accuracy. A GSEA enrichment analysis was performed to investigate possible functional pathways. Furthermore, the role of RS in the tumor microenvironment, immunotherapy, and chemotherapy was also investigated.

Result: We found three different subgroups based on NMRGs expression patterns. Twelve genes were selected by LASSO regression to create a prognostic risk signature. High-RS was founded to be linked to a worse prognosis. In Ovarian Cancer Patients, RS is an independent prognostic marker. Immune infiltrating cells were considerably overexpressed in the low-RS group, as immune-related functional pathways were significantly enriched. Furthermore, immunotherapy prediction reveal that patients with low-RS are more sensitive to immunotherapy.

Conclusion: For a patient with OC, NMRGs are promising biomarkers. Our prognostic signature has potential predictive value for OC prognosis and immunotherapy response. The results of this study may help improve our understanding of NMRG in OCs.

Development of a Novel Immune-Related Gene Signature to Predict Prognosis and Immunotherapeutic Efficiency in Gastric Cancer

Background: Gastric cancer (GC) is the fifth most common malignancy and the third leading cause of tumor-related deaths globally. Herein, we attempted to build a novel immune-related gene (IRG) signature that could predict the prognosis and immunotherapeutic efficiency for GC patients.

Methods: The mRNA transcription data and corresponding clinical data of GC were downloaded from The Cancer Genome Atlas (TCGA) database as the training group and the GSE84437 data set as the testing cohort, followed by acquisition of IRGs from the InnateDB resource and ImmPort database. Using the univariate Cox regression analysis, an IRG signature was developed. Several immunogenomic analyses were performed to illustrate the associations between the immune risk score and tumor mutational burden, immune cell infiltrations, function of immune infiltration, clinical characteristics, immune subtype, and immunotherapeutic response.

Results: The analysis of 343 GC samples and 30 normal samples from the TCGA database gave rise to 8,713 differentially expressed genes (DEGs) and 513 differentially expressed immune-related genes (DEIRGs) were extracted. The novel IRG signature contained eight DEIRGs (FABP4, PI15, RNASE2, CGB5, INHBE, RLN2, DUSP1, and CD36) and was found to serve as an independent predictive and prognostic factor for GC. Then, the GC patients were separated into the high- and low-risk groups based on the median risk score, wherein the low-risk group presented a better prognosis and was more sensitive to immunotherapy than did the high-risk group. According to the time-dependent ROC curves and AUCs, the immunotherapeutic value of the signature was better than the Tumor Immune Dysfunction and Exclusion (TIDE) and T-cell inflammatory signature (TIS) scores. In addition, the AUCs of the risk score for predicting 1-, 2-, and 3-year OS were 0.675, 0.682, and 0.710, respectively, which indicated that the signature had great predictive power.

Conclusion: This study presents a novel IRG signature based on the tumor immune microenvironment, which could improve the prediction of the prognosis and immunotherapeutic efficiency for GC patients. The powerful signature may serve as novel biomarkers and provide therapeutic targets for precision oncology in clinical practice.