Acyl-CoA Binding Domain Containing 4 Polymorphism rs4986172 and Expression Can Serve as Overall Survival Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients After Hepatectomy

A Novel Peroxisome-Related Gene Signature Predicts Breast Cancer Prognosis and Correlates with T Cell Suppression

Background

Peroxisomes are increasingly linked to cancer development, yet the prognostic role of peroxisome-related genes (PRGs) in breast cancer remains unclear.

Objective

This study aimed to construct a prognostic model based on PRG expression in breast cancer to clarify their prognostic value and clinical implications.

Methods

Transcriptomic data from TCGA and GEO were used for training and validation cohorts. TME characteristics were analyzed with ESTIMATE, MCP-counter, and CIBERSORT algorithms. qPCR validated mRNA expression levels of risk genes, and data analysis was conducted in R.

Results

Univariate and multivariate Cox regression identified a 7-gene PRG risk signature (ACBD5, ACSL5, DAO, NOS2, PEX3, PEX10, and SLC27A2) predicting breast cancer prognosis in training (n=1069), internal validation (n=327), and external validation (merged from four GEO datasets, n=640) datasets. While basal and Her2 subtypes had higher risk scores than luminal subtypes, a significant prognostic impact of the PRG risk signature was seen only in luminal subtypes. The high-risk subgroup exhibited a higher frequency of focal synonymous copy number alterations (SCNAs), arm-level amplifications and deletions, and single nucleotide variations. These increased genomic aberrations were associated with greater immune suppression and reduced CD8+ T cell infiltration. Bulk RNA sequencing and single-cell analyses revealed distinct expression patterns of peroxisome-related genes (PRGs) in the breast cancer TME: PEX3 was primarily expressed in malignant and stromal cells, while ACSL5 showed high expression in T cells. Additionally, the PRG risk signature demonstrated efficacy comparable to that of well-known biomarkers for predicting immunotherapy responses. Drug sensitivity analysis revealed that the PRG high-risk subgroup was sensitive to inhibitors of BCL-2 family proteins (BCL-2, BCL-XL, and MCL1) and other kinases (PLK1, PLK1, BTK, CHDK1, and EGFR).

Conclusion

The PRG risk signature serves as a promising biomarker for evaluating peroxisomal activity, prognosis, and responsiveness to immunotherapy in breast cancer.

Predict lncRNA-drug associations based on graph neural network

LncRNAs are an essential type of non-coding RNAs, which have been reported to be involved in various human pathological conditions. Increasing evidence suggests that drugs can regulate lncRNAs expression, which makes it possible to develop lncRNAs as therapeutic targets. Thus, developing in-silico methods to predict lncRNA-drug associations (LDAs) is a critical step for developing lncRNA-based therapies. In this study, we predict LDAs by using graph convolutional networks (GCN) and graph attention networks (GAT) based on lncRNA and drug similarity networks. Results show that our proposed method achieves good performance (average AUCs > 0.92) on five datasets. In addition, case studies and KEGG functional enrichment analysis further prove that the model can effectively identify novel LDAs. On the whole, this study provides a deep learning-based framework for predicting novel LDAs, which will accelerate the lncRNA-targeted drug development process.

Identification of ACBD3 as a new molecular biomarker in pan-cancers through bioinformatic analysis: a preclinical study

BACKGROUND

Acyl-CoA-binding domain-containing 3 (ACBD3) is a multifunctional protein, that plays essential roles in cellular signaling and membrane domain organization. Although the precise roles of ACBD3 in various cancers remain unclear. Thus, we aimed to determine the diverse roles of ACBD3 in pan-cancers.

METHODS

Relevant clinical and RNA-sequencing data for normal tissues and 33 tumors from The Cancer Genome Atlas (TCGA) database, the Human Protein Atlas, and other databases were applied to investigate ACBD3 expression in various cancers. ACBD3-binding and ACBD3-related target genes were obtained from the STRING and GEPIA2 databases. The possible functions of ACBD3-binding genes were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also applied the diagnostic value and survival prognosis analysis of ACBD3 in pan-cancers using R language. The mutational features of ACBD3 in various TCGA cancers were obtained from the cBioPortal database.

RESULTS

When compared with normal tissues, ACBD3 expression was statistically upregulated in eleven cancers and downregulated in three cancers. ACBD3 expression was remarkably different among various pathological stages of tumors, immune and molecular subtypes of cancers, cancer phosphorylation levels, and immune cell infiltration. The survival of four tumors was correlated with the expression level of ACBD3, including pancreatic adenocarcinoma, adrenocortical carcinoma, sarcoma, and glioma. The high accuracy in diagnosing multiple tumors and its correlation with prognosis indicated that ACBD3 may be a potential biomarker of pan-cancers.

CONCLUSION

According to our pan-cancer analysis, ACBD3 may serve as a remarkable prognostic and diagnostic biomarker of pan-cancers as well as contribute to tumor development. ACBD3 may also provide new directions for cancer treatment targets in the future.

Outer dynein arm docking complex subunit 2 polymorphism rs7893462 modulates hepatocellular carcinoma susceptibility and can serve as an overall survival biomarker for hepatitis B virus-related hepatocellular carcinoma after hepatectomy: a cohort study with a long-term follow-up

BACKGROUND

Genetic variants of outer dynein arm docking complex subunit 2 (ODAD2) have been reported to be closely associated with primary ciliary dyskinesia and colorectal cancer in previous studies, but the association of genetic variants of ODAD2 with hepatocellular carcinoma (HCC) has not been reported.

METHODS

We enrolled 80 healthy subjects and 468 Guangxi hepatitis B virus (HBV)-related HCC patients in this study. A case-control study method was used to explore the association of different ODAD2-rs7893462 genotypes with hepatocarcinogenesis. A comprehensive survival analysis was used to explore the association of rs7893462 with the prognosis of HBV-related HCC in Guangxi.

RESULTS

Through a case-control study, we observed that patients carrying the G allele of rs7893462 had a markedly increased susceptibility to hepatocarcinogenesis (odds ratio = 1.712, 95% confidence interval = 1.032-2.839, P = 0.037). We found that there were significant prognosis differences among three different genotypes of rs7893462. Nomogram analysis suggested that the contribution of rs7893462 polymorphisms to the prognosis of HBV-related HCC was second only to the BCLC stage. Stratified survival analysis suggested that the AG genotype of rs7893462 was an independent prognostic risk factor for HBV-related HCC. Joint effect survival analysis also observed that the AG genotype of rs7893462 combined with clinical parameters could significantly identify HBV-related HCC patients with different prognostic outcomes more accurately, and the AG genotype was also observed to be independent of clinical factors in HBV-related HCC survival.

CONCLUSION

The ODAD2-rs7893462 polymorphisms can be used as an independent prognostic indicator of HBV-related HCC overall survival and are significantly associated with susceptibility to hepatocarcinogenesis.

Differential roles for ACBD4 and ACBD5 in peroxisome-ER interactions and lipid metabolism

Peroxisomes and the endoplasmic reticulum (ER) are intimately linked subcellular organelles, physically connected at membrane contact sites. While collaborating in lipid metabolism, for example, of very long-chain fatty acids (VLCFAs) and plasmalogens, the ER also plays a role in peroxisome biogenesis. Recent work identified tethering complexes on the ER and peroxisome membranes that connect the organelles. These include membrane contacts formed via interactions between the ER protein VAPB (vesicle-associated membrane protein-associated protein B) and the peroxisomal proteins ACBD4 and ACBD5 (acyl-coenzyme A-binding domain protein). Loss of ACBD5 has been shown to cause a significant reduction in peroxisome-ER contacts and accumulation of VLCFAs. However, the role of ACBD4 and the relative contribution these two proteins make to contact site formation and recruitment of VLCFAs to peroxisomes remain unclear. Here, we address these questions using a combination of molecular cell biology, biochemical, and lipidomics analyses following loss of ACBD4 or ACBD5 in HEK293 cells. We show that the tethering function of ACBD5 is not absolutely required for efficient peroxisomal β-oxidation of VLCFAs. We demonstrate that loss of ACBD4 does not reduce peroxisome-ER connections or result in the accumulation of VLCFAs. Instead, the loss of ACBD4 resulted in an increase in the rate of β-oxidation of VLCFAs. Finally, we observe an interaction between ACBD5 and ACBD4, independent of VAPB binding. Overall, our findings suggest that ACBD5 may act as a primary tether and VLCFA recruitment factor, whereas ACBD4 may have regulatory functions in peroxisomal lipid metabolism at the peroxisome-ER interface.