Pan-Cancer analysis shows that ACO2 is a potential prognostic and immunotherapeutic biomarker for multiple cancer types including hepatocellular carcinoma

Isoform-level analyses of 6 cancers uncover extensive genetic risk mechanisms undetected at the gene-level

Integrating genome-wide association study (GWAS) and transcriptomic datasets can help identify potential mediators for germline genetic risk of cancer. However, traditional methods have been largely unsuccessful because of an overreliance on total gene expression. These approaches overlook alternative splicing, which can produce multiple isoforms from the same gene, each with potentially different effects on cancer risk. Here, we integrate genetic and multi-tissue isoform-level gene expression data from the Genotype Tissue-Expression Project (GTEx, N = 108-574) with publicly available European-ancestry GWAS summary statistics (all N > 20,000 cases) to identify both isoform- and gene-level risk associations with six cancers (breast, endometrial, colorectal, lung, ovarian, prostate) and six related cancer subtype classifications (N = 12 total). Compared to traditional methods leveraging total gene expression, directly modeling isoform expression through transcriptome-wide association studies (isoTWAS) substantially increases discovery of transcriptomic mechanisms underlying genetic associations. Using the same RNA-seq datasets, isoTWAS identified 164% more significant unique gene associations compared to TWAS (6,163 and 2,336, respectively), with isoTWAS-prioritized genes enriched 4-fold for evolutionarily-constrained genes (P = 6.1 × 10-13). isoTWAS tags transcriptomic associations at 52% more independent GWAS loci compared to TWAS across the six cancers. Additionally, isoform expression mediates an estimated 63% greater proportion of cancer risk SNP heritability compared to gene expression when evaluating cis-genetic influence on isoform expression. We highlight several notable isoTWAS associations that demonstrate GWAS colocalization at the isoform level but not at the gene level, including, CLPTM1L (lung cancer), LAMC1 (colorectal), and BABAM1 (breast). These results underscore the critical importance of modeling isoform-level expression to maximize discovery of genetic risk mechanisms for cancers.

Proteomics Analysis of Interactions between Drug-Resistant and Drug-Sensitive Cancer Cells: Comparative Studies of Monoculture and Coculture Cell Systems

Cell-cell interactions, which allow cells to communicate with each other through molecules in their microenvironment, are critical for the growth, health, and functions of cells. Previous studies show that drug-resistant cells can interact with drug-sensitive cells to elevate their drug resistance level, which is partially responsible for cancer recurrence. Studying protein targets and pathways involved in cell-cell communication provides essential information for fundamental cell biology studies and therapeutics of human diseases. In the current studies, we performed direct coculture and indirect coculture of drug-resistant and drug-sensitive cell lines, aiming to investigate intracellular proteins responsible for cell communication. Comparative studies were carried out using monoculture cells. Shotgun bottom-up proteomics results indicate that the P53 signaling pathway has a strong association with drug resistance mechanisms, and multiple TP53-related proteins were upregulated in both direct and indirect coculture systems. In addition, cell-cell communication pathways, including the phagosome and the HIF-signaling pathway, contribute to both direct and indirect coculture systems. Consequently, AK3 and H3-3A proteins were identified as potential targets for cell-cell interactions that are relevant to drug resistance mechanisms. We propose that the P53 signaling pathway, in which mitochondrial proteins play an important role, is responsible for inducing drug resistance through communication between drug-resistant and drug-sensitive cancer cells.

PRIM2: A Marker of MYC-driven Hyper-proliferation, Disease Progression, Tumor Aggressiveness and Poor Survival in Glioma Patients

BACKGROUND/AIM

Gliomas are the most prevalent brain tumors with metabolic alterations playing a pivotal role in disease progression. However, the precise coordination of metabolic alterations with tumor-promoting cellular mechanisms, leading to tumor initiation, progression, and aggressiveness, resulting in poor outcomes, remains poorly understood in gliomas.

MATERIALS AND METHODS

We conducted a metabolism-targeted differential gene expression analysis using glioma patients' expression profiling data from The Cancer Genome Atlas (TCGA) database. In addition, pathway enrichment analysis, gene set enrichment analysis (GSEA), transcription factor prediction, network construction, and correlation analyses were performed. Survival analyses were performed in R. All results were validated using independent GEO expression datasets.

RESULTS

Metabolism-targeted analysis identified 5 hits involved in diverse metabolic processes linking them to disease aggressiveness in gliomas. Subsequently, we established that cell cycle progression and hyper-proliferation are key drivers of tumor progression and aggressiveness in gliomas. One of the identified metabolic hits, DNA primase 2 (PRIM2), a gene involved in DNA replication was found directly associated with cell cycle progression in gliomas. Furthermore, our analysis indicated that PRIM2, along with other cell cycle-related genes, is under the control of and regulated by the oncogenic MYC transcription factor in gliomas. In addition, PRIM2 expression alone is enough to predict MYC-driven cell cycle progression and is associated with tumor progression, aggressive disease state, and poor survival in glioma patients.

CONCLUSION

Our findings highlight PRIM2 as a marker of MYC-driven cell cycle progression and hyper-proliferation, disease onset and progression, tumor aggressiveness, and poor survival in glioma patients.

ACO2 deficiency increases vulnerability to Parkinson's disease via dysregulating mitochondrial function and histone acetylation-mediated transcription of autophagy genes

Parkinson's disease (PD) is characterized by α-synuclein aggregation in dopaminergic (DA) neurons, which are sensitive to oxidative stress. Mitochondria aconitase 2 (ACO2) is an essential enzyme in the tricarboxylic acid cycle that orchestrates mitochondrial and autophagic functions to energy metabolism. Though widely linked to diseases, its relation to PD has not been fully clarified. Here we revealed that the peripheral ACO2 activity was significantly decreased in PD patients and associated with their onset age and disease durations. The knock-in mouse and Drosophila models with the A252T variant displayed aggravated motor deficits and DA neuron degeneration after 6-OHDA and rotenone-induction, and the ACO2 knockdown or blockade cells showed features of mitochondrial and autophagic dysfunction. Moreover, the transcription of autophagy-related genes LC3 and Atg5 was significantly downregulated via inhibited histone acetylation at the H3K9 and H4K5 sites. These data provided multi-dimensional evidences supporting the essential roles of ACO2, and as a potential early biomarker to be used in clinical trials for assessing the effects of antioxidants in PD. Moreover, ameliorating energy metabolism by targeting ACO2 could be considered as a potential therapeutic strategy for PD and other neurodegenerative disorders.

Genetics of enzymatic dysfunctions in metabolic disorders and cancer

Inherited metabolic disorders arise from mutations in genes involved in the biogenesis, assembly, or activity of metabolic enzymes, leading to enzymatic deficiency and severe metabolic impairments. Metabolic enzymes are essential for the normal functioning of cells and are involved in the production of amino acids, fatty acids and nucleotides, which are essential for cell growth, division and survival. When the activity of metabolic enzymes is disrupted due to mutations or changes in expression levels, it can result in various metabolic disorders that have also been linked to cancer development. However, there remains much to learn regarding the relationship between the dysregulation of metabolic enzymes and metabolic adaptations in cancer cells. In this review, we explore how dysregulated metabolism due to the alteration or change of metabolic enzymes in cancer cells plays a crucial role in tumor development, progression, metastasis and drug resistance. In addition, these changes in metabolism provide cancer cells with a number of advantages, including increased proliferation, resistance to apoptosis and the ability to evade the immune system. The tumor microenvironment, genetic context, and different signaling pathways further influence this interplay between cancer and metabolism. This review aims to explore how the dysregulation of metabolic enzymes in specific pathways, including the urea cycle, glycogen storage, lysosome storage, fatty acid oxidation, and mitochondrial respiration, contributes to the development of metabolic disorders and cancer. Additionally, the review seeks to shed light on why these enzymes represent crucial potential therapeutic targets and biomarkers in various cancer types.

Transcriptome profiling of A549 non-small cell lung cancer cells in response to Trichinella spiralis muscle larvae excretory/secretory products

Trichinella spiralis (T. spiralis) muscle-larva excretory/secretory products (ML-ESPs) is a complex array of proteins with antitumor activity. We previously demonstrated that ML-ESPs inhibit the proliferation of A549 non-small cell lung cancer (NSCLC) cell line. However, the mechanism of ML-ESPs against A549 cells, especially on the transcriptional level, remains unknow. In this study, we systematically investigated a global profile bioinformatics analysis of transcriptional response of A549 cells treated with ML-ESPs. And then, we further explored the transcriptional regulation of genes related to glucose metabolism in A549 cells by ML-ESPs. The results showed that ML-ESPs altered the expression of 2,860 genes (1,634 upregulated and 1,226 downregulated). GO and KEGG analysis demonstrated that differentially expressed genes (DEGs) were mainly associated with pathway in cancer and metabolic process. The downregulated genes interaction network of metabolic process is mainly associated with glucose metabolism. Furthermore, the expression of phosphofructokinase muscle (PFKM), phosphofructokinase liver (PFKL), enolase 2 (ENO2), lactate dehydrogenase B (LDHB), 6-phosphogluconolactonase (6PGL), ribulose-phosphate-3-epimerase (PRE), transketolase (TKT), transaldolase 1 (TALDO1), which genes mainly regulate glycolysis and pentose phosphate pathway (PPP), were suppressed by ML-ESPs. Interestingly, tricarboxylic acid cycle (TCA)-related genes, such as pyruvate dehydrogenase phosphatase 1 (PDP1), PDP2, aconitate hydratase 1 (ACO1) and oxoglutarate dehydrogenase (OGDH) were upregulated by ML-ESPs. In summary, the transcriptome profiling of A549 cells were significantly altered by ML-ESPs. And we also provide new insight into how ML-ESPs induced a transcriptional reprogramming of glucose metabolism-related genes in A549 cells.