AUP1 regulates lipid metabolism and induces lipid accumulation to accelerate the progression of renal clear cell carcinoma

Low expression of fatty acid oxidation related gene ACADM indicates poor prognosis of renal clear cell carcinoma and is related to tumor immune infiltration

This research aims to identify the key fatty acid beta-oxidation (FAO) genes that are altered in kidney renal clear cell carcinoma (KIRC) and to analyze the role of these genes in KIRC. The Gene Expression Omnibus (GEO) and FAO datasets were used to identify these key genes. Wilcoxon rank sum test was used to assess the levels of acyl-CoA dehydrogenase medium chain (ACADM) between KIRC and non-cancer samples. The logistic regression and Wilcoxon rank sum test were used to explore the association between ACADM and clinical features. The diagnostic performance of ACADM for KIRC was assessed using a diagnostic receiver operating characteristic (ROC) curve. The co-expressed genes of ACADM were identified in LinkedOmics database, and their function and pathway enrichment were analyzed. The correlation between ACADM expression level and immune infiltration was analyzed by Gene Set Variation Analysis (GSVA) method. Additionally, the proliferation, migration, and invasion abilities of KIRC cells were assessed after overexpressing ACADM. Following differential analysis and intersection, we identified six hub genes, including ACADM. We found that the expression level of ACADM was decreased in KIRC tissues and had a better diagnostic effect (AUC = 0.916). Survival analysis suggested that patients with decreased ACADM expression had a worse prognosis. According to correlation analysis, a variety of clinical features were associated with the expression level of ACADM. By analyzing the infiltration level of immune cells, we found that ACADM may be related to the enrichment of immune cells. Finally, ACADM overexpression inhibited proliferation, migration, and invasion of KIRC cells. In conclusion, our findings suggest that reduced ACADM expression in KIRC patients is indicative of poor prognosis. These results imply that ACADM may be a diagnostic and prognostic marker for individuals with KIRC, offering a reference for clinicians in diagnosis and treatment.

The m6A demethylase FTO targets POLQ to promote ccRCC cell proliferation and genome stability maintenance

BACKGROUND AND AIM

As the first identified m6A demethylase, FTO has been implicated in the progression of various cancers. However, the specific mechanism of FTO in clear cell renal cell carcinoma (ccRCC) remains incompletely understood. In this study, we aimed to explore the potential molecular mechanisms influencing the progression of ccRCC.

METHODS

We initially assessed the expression of FTO in tumor and adjacent tissues using TCGA database, RT-qPCR, and Western blot. We then conducted CCK-8, cell cycle analysis, and colony formation assay to investigate the impact of FTO on ccRCC cell proliferation. MeRIP-seq and RNA-seq were employed to identify potential downstream targets of FTO in ccRCC, and these findings were further validated through dual-luciferase reporter assays and MeRIP-qPCR. Then, DNA damage and cell death were assessed separately through gammaH2AX immunofluorescence detection and the LIVE/DEAD Fixable Dead Cell Stain assay, respectively. Subsequently, we identified downstream pathways influenced by FTO's regulation of POLQ through TCGA database analysis and GSEA enrichment analysis. Validation was carried out through Western blot.

RESULTS

FTO is highly expressed in ccRCC tissues and cell lines. Furthermore, ROC curve demonstrates that FTO contributes to the diagnosis of ccRCC. FTO modulates m6A modification, consequently influencing the expression of POLQ, thus facilitating cell proliferation and maintaining genome stability in ccRCC.

CONCLUSION

FTO could potentially serve as a diagnostic marker for ccRCC. FTO promotes the progression of ccRCC by regulating m6A modification, making the inhibition of FTO a potential novel therapeutic strategy in ccRCC.

Targeting lipid biosynthesis on the basis of conventional treatments for clear cell renal cell carcinoma: A promising therapeutic approach

A variety of cancer cells exhibit dysregulated lipid metabolism, characterized by excessive intracellular lipid accumulation, and clear cell renal cell carcinoma (ccRCC) is the most typical disease with these characteristics. As the most common malignancy of all renal cell carcinomas (RCCs), ccRCC is typically characterized by a large accumulation of lipids and glycogen in the cytoplasm and a nucleus that is squeezed by the accumulated lipid droplets and localized to the marginal areas within the cytoplasm. This lipid accumulation has been found to be critically involved in the maintenance of malignant features observed in various cancers. Firstly, it maintains the persistent proliferative and metastasis properties of cancer cells. Secondly, it acts as a buffer against lipid peroxidation, preventing lipid peroxidation-induced ferroptosis. Moreover, lipids can diminish the sensitivity of cancer cells to radiotherapy. As ccRCC is a type of cancer with high lipid synthesis, targeting lipid synthesis-related genes in cancer cells may be a promising therapeutic modality for single treatment or in combination with radiotherapy, chemotherapy, and immunotherapy. This may revolutionize the choice of treatment modality for ccRCC patients. In this review, we concentrate on the current status and progress of research on lipid biosynthesis in ccRCC and the potential applications of targeting lipid synthesis to treat ccRCC. At last, we propose perspective and future research directions for targeting inhibition of lipid biosynthesis in combination with conventional therapeutic approaches for the treatment of ccRCC, which will help to evolve the therapeutic model.

The Potential of Lipid Droplet-associated Genes as Diagnostic and Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma

OBJECTIVE

The role of lipid droplets (LDs) and lipid droplet-associated genes (LD-AGs) remains unclear in head and neck squamous cell carcinoma (HNSCC). This study aimed to investigate LDs in HNSCC and identify LD-AGs essential for the diagnosis and prognosis of HNSCC patients.

METHODS

The LDs in the HNSCC and normal cell lines were stained with oil red O. Bioinformatic analysis was used to find LD-AGs in HNSCC that had diagnostic and prognostic significance.

RESULTS

LDs accumulation was increased in HNSCC cell lines compared with normal cell lines (P<0.05). Fifty-three differentially expressed genes, including 34 upregulated and 19 downregulated, were found in HNSCC based on the TCGA platform (P<0.05). Then, 53 genes were proved to be functionally enriched in lipid metabolism and LDs. Among them, with an AUC value > 0.7, 34 genes demonstrated a high predictive power. Six genes (AUP1, CAV1, CAV2, CAVIN1, HILPDA, and SQLE) out of 34 diagnostic genes were linked to overall survival in patients with HNSCC (P<0.05). The significant prognostic factors AUP1, CAV1, CAV2, and SQLE were further identified using the univariate and multivariate cox proportional hazard models (P<0.05). The protein expression of CAV2 and SQLE was significantly increased in the HNSCC tissue compared to normal tissues (P<0.05). Finally, the knockdown of the four LD-AGs decreased LDs accumulation, respectively.

CONCLUSIONS

Increased LDs accumulation was a hallmark of HNSCC, and AUP1, CAV1, CAV2, and SQLE were discovered as differentially expressed LD-AGs with diagnostic and prognostic potential in HNSCC.

PBRM1 mutation and WDR72 expression as potential combinatorial biomarker for predicting the response to Nivolumab in patients with ccRCC: a tumor marker prognostic study

PURPOSE

Immune checkpoint therapy (ICT) provides a new idea for the treatment of advanced clear cell renal cell carcinoma (ccRCC), which can bring significant benefits to patients. However, the clinical application of ICT is limited because of the lack of predictive biomarkers to select potential responders. This study aims to propose a new biomarker to predict the response to Nivolumab in patients with ccRCC.

MATERIALS AND METHODS

The genes that significantly improve the prognosis of ccRCC were retrieved from The Cancer Genome Atlas (TCGA) database. The genomic and clinical data were from patients that had been registered in prospective clinical trials (CheckMate 009, CheckMate 010 and CheckMate 025). TCGA, Gene Expression Omnibus (GEO), and The Human Protein Atlas database were used to analyze the gene and protein expression of WD repeat-containing protein 72 (WDR72) in ccRCC. Gene Ontology (GO) & The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were performed to dig relevant mechanisms of WDR72. Single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the role of WDR72 in immune infiltration. Cell proliferation assay, FAO and ATP quantification were used to explore and verify the molecular mechanisms. The expression of WDR72, FOXP3, CD8, and CPT1A was examined by IHC in 20 advanced ccRCC tissue samples at the Urology Department of our hospital. The MethSurv was used to identify PBRM1 and WDR72 gene methylation and its effect on prognosis of ccRCC.

RESULTS

WDR72 is the most significant gene for improving overall survival (OS) in ccRCC. In all three checkmates, OS and progression free survival (PFS) were found to be significantly higher in WDR72 high expression group than that in WDR72 low expression group (P=0.040 and P=0.012, respectively), and similar conclusions could be drawn from the PBRM1-mutation (MUT) compared with the PBRM1-wildtype (WT) (P=0.007 and P=0.006, respectively). What's more, high expression of WDR72 plus PBRM1-MUT as a combinatorial biomarker showed improved OS (HR=0.388, P=0.0026) and PFS (HR=0.39, P=0.0066) compared to low expression of WDR72 plus PBRM1-WT. Functional enrichment analysis showed that WDR72 was closely positively related to fatty acid degradation and fatty acid beta oxidation pathway in ccRCC. In vitro experiments showed that high expression of WDR72 can promote fatty acids oxidation and inhibit the proliferation of ccRCC cells. Immune analysis revealed that WDR72 high expression was associated with decreased infiltration of Treg cells and low ssGSEA score of check-point. IHC results showed that WDR72 was negatively correlated with FOXP3 expression (r=-0.506, P=0.023) and positively correlated with CPT1A expression (r=0.529, P=0.017).

CONCLUSIONS

The present study indicated that high expression of WDR72 may indicate a good prognosis of patients treated with Nivolumab and WDR72 expression combined with PBRM1 mutation could be more persuasive to predict the response for ICT in ccRCC patients.

Ancient ubiquitous protein 1 (AUP1) is a prognostic biomarker connected with TP53 mutation and the inflamed microenvironments in glioma

INTRODUCTION

Glioblastoma (GBM) is the most common and lethal brain tumor. The current treatment is surgical removal combined with radiotherapy and chemotherapy, Temozolomide (TMZ). However, tumors tend to develop TMZ resistance which leads to therapeutic failure. Ancient ubiquitous protein 1 (AUP1) is a protein associated with lipid metabolism, which is widely expressed on the surface of ER and Lipid droplets, involved in the degradation of misfolded proteins through autophagy. It has recently been described as a prognostic marker in renal tumors. Here, we aim to use sophisticated bioinformatics and experimental validation to characterize the AUP1's role in glioma.

MATERIAL AND METHODS

We collected the mRNA, proteomics, and Whole-Exon-Sequencing from The Cancer Genome Atlas (TCGA) for bioinformatics analyses. The analyses included the expression difference, Kaplan-Meier-survival, COX-survival, and correlation to the clinical factors (tumor mutation burden, microsatellite instability, and driven mutant genes). Next, we validated the AUP1 protein expression using immunohistochemical staining on the 78 clinical cases and correlated them with P53 and KI67. Then, we applied GSEA analyses to identify the altered signalings and set functional experiments (including Western Blot, qPCR, BrdU, migration, cell-cycle, and RNAseq) on cell lines when supplemented with small interfering RNA targeting the AUP1 gene (siAUP1) for further validation. We integrated the single-cell sequencing and CIBERSORT analyses at the Chinese Glioma Genome Atlas (CGGA) and Glioma Longitudinal AnalySiS (GLASS) dataset to rationale the role of AUP1 in glioma.

RESULTS

Firstly, the AUP1 is a prognostic marker, increased in the tumor component, and correlated with tumor grade in both transcriptomes and protein levels. Secondly, we found higher AUP1 associated with TP53 status, Tumor mutation burden, and increased proliferation. In the function validation, downregulated AUP1 expression merely impacted the U87MG cells' proliferation instead of altering the lipophagy activity. From the single-cell sequencing and CIBERSORT analyses at CGGA and GLASS data, we understood the AUP1 expression was affected by the tumor proliferation, stromal, and inflammation compositions, particularly the myeloid and T cells. In the longitudinal data, the AUP1 significantly dropped in the recurrent IDH wildtype astrocytoma, which might result from increased AUP1-cold components, including oligodendrocytes, endothelial cells, and pericytes.

CONCLUSION

According to the literature, AUP1 regulates lipophagy by stabilizing the ubiquitination of lipid droplets. However, we found no direct link between AUP1 suppression and altered autophagy activity in the functional validation. Instead, we noticed AUP1 expression associated with tumor proliferation and inflammatory status, contributed by myeloid cells and T cells. In addition, the TP53 mutations seem to play an important role here and initiate inflamed microenvironments. At the same time, EGFR amplification and Chromosome 7 gain combined 10 loss are associated with increased tumor growth related to AUP1 levels. This study taught us that AUP1 is a poorer predictive biomarker associated with tumor proliferation and could report inflamed status, potentially impacting the clinical application.

Metabolic classifications of renal cell carcinoma reveal intrinsic connections with clinical and immune characteristics

BACKGROUND

Kidney cancer undergoes a dramatic metabolic shift and has demonstrated responsiveness to immunotherapeutic intervention. However, metabolic classification and the associations between metabolic alterations and immune infiltration in Renal cell carcinoma still remain elucidative.

METHODS

Unsupervised consensus clustering was conducted on the TCGA cohorts for metabolic classification. GESA, mRNAsi, prognosis, clinical features, mutation load, immune infiltration and differentially expressed gene differences among different clusters were compared. The prognosis model and nomograms were constructed based on metabolic gene signatures and verified using external ICGC datasets. Immunohistochemical results from Human Protein Atlas database and Tongji hospital were used to validate gene expression levels in normal tissues and tumor samples. CCK8, apoptosis analysis, qPCR, subcutaneously implanted murine models and flowcytometry analysis were applied to investigate the roles of ACAA2 in tumor progression and anti-tumor immunity.

RESULTS

Renal cell carcinoma was classified into 3 metabolic subclusters and the subcluster with low metabolic profiles displayed the poorest prognosis, highest invasiveness and AJCC grade, enhanced immune infiltration but suppressive immunophenotypes. ACAA2, ACAT1, ASRGL1, AKR1B10, ABCC2, ANGPTL4 were identified to construct the 6 gene-signature prognosis model and verified both internally and externally with ICGC cohorts. ACAA2 was demonstrated as a tumor suppressor and was associated with higher immune infiltration and elevated PD-1 expression of CD8⁺ T cells.

CONCLUSIONS

Our research proposed a new metabolic classification method for RCC and revealed intrinsic associations between metabolic phenotypes and immune profiles. The identified gene signatures might serve as key factors bridging tumor metabolism and tumor immunity and warrant further in-depth investigations.

Integrating single-cell analysis and machine learning to create glycosylation-based gene signature for prognostic prediction of uveal melanoma

BACKGROUND

Increasing evidence suggests a correlation between glycosylation and the onset of cancer. However, the clinical relevance of glycosylation-related genes (GRGs) in uveal melanoma (UM) is yet to be fully understood. This study aimed to shed light on the impact of GRGs on UM prognosis.

METHODS

To identify the most influential genes in UM, we employed the AUCell and WGCNA algorithms. The GRGs signature was established by integrating bulk RNA-seq and scRNA-seq data. UM patients were separated into two groups based on their risk scores, the GCNS_low and GCNS_high groups, and the differences in clinicopathological correlation, functional enrichment, immune response, mutational burden, and immunotherapy between the two groups were examined. The role of the critical gene AUP1 in UM was validated through in vitro and in vivo experiments.

RESULTS

The GRGs signature was comprised of AUP1, HNMT, PARP8, ARC, ALG5, AKAP13, and ISG20. The GCNS was a significant prognostic factor for UM, and high GCNS correlated with poorer outcomes. Patients with high GCNS displayed heightened immune-related characteristics, such as immune cell infiltration and immune scores. In vitro experiments showed that the knockdown of AUP1 led to a drastic reduction in the viability, proliferation, and invasion capability of UM cells.

CONCLUSION

Our gene signature provides an independent predictor of UM patient survival and represents a starting point for further investigation of GRGs in UM. It offers a novel perspective on the clinical diagnosis and treatment of UM.