Glycosylation in Renal Cell Carcinoma: Mechanisms and Clinical Implications

High RRM2 Correlates with Mitochondrial and Immune Responses in the Eosinophilic Subtype of Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC), the predominant subtype of RCC, is distinguished by unique biological characteristics and heterogeneity, including eosinophilic and clear subtypes. Notwithstanding progress in therapy, immune checkpoint inhibitors (ICIs), and tyrosine kinase inhibitors (TKIs), the prognosis for individuals with metastatic ccRCC remains poor, presumably owing to metabolic alterations leading to mitochondrial dysfunction, which affects treatment response variability.

Methods

We analyzed histological and immunohistochemical data from a cohort at Dalian Medical University's First Affiliated Hospital alongside RNA-sequencing transcriptome data from the TCGA database. Histologically, eosinophilic and clear ccRCC subtypes were evaluated using Kaplan-Meier and Cox proportional hazards models for survival analysis and prognosis. Differential gene expression (DEG) analysis and Gene Set Enrichment Analysis were performed to explore transcriptomic differences and relevant pathways.

Results

The study discovered substantial histological and molecular differences between the eosinophilic and clear cell subtypes of ccRCC. The eosinophilic subtype linked with frequent high-grade tumors (69.05% eosinophil vs 35.35% clear) and a poorer prognosis (HR=2.659, 95% CI:1.437-4.919, P=0.002). DEG analysis revealed distinct expression patterns among subtypes and identified a risk score signature that remained significant even after adjusting for clinical variables (HR=3.967, 95% CI: 1.665-9.449, P=0.002), showing less favorable survival in the high-risk group (P < 0.0001). RRM2 emerged as the most prognostic gene from this risk score, particularly in the eosinophilic subtype, alongside other clinical variables. By IHC, RRM2 shows high IHC score in eosinophilic compared to clear subtype (P=0.019). In addition, highly expressed RRM2 correlates with poor outcomes and is linked to mitochondrial genes, immunological pathways, and ICIs treatment.

Conclusion

These findings show significant differences in prognosis between subtypes. RRM2 was the most prognostic gene from the discovered novel risk score signature associated with subtypes. Future research is essential to validate these insights and their therapeutic implications for ccRCC management.

N-acetylgalactosaminyltransferase GALNT6 is a potential therapeutic target of clear cell renal cell carcinoma progression

High expression of truncated O-glycans Tn antigen predicts adverse clinical outcome in patients with clear cell renal cell carcinoma (ccRCC). To understand the biosynthetic underpinnings of Tn antigen changes in ccRCC, we focused on N-acetylgalactosaminyltransferases (GALNTs, also known as GalNAcTs) known to be involved in Tn antigen synthesis. Data from GSE15641 profile and local cohort showed that GALNT6 was significantly upregulated in ccRCC tissues. The current study aimed to determine the role of GALNT6 in ccRCC, and whether GALNT6-mediated O-glycosylation aggravates malignant behaviors. Gain- and loss-of-function experiments showed that overexpression of GALNT6 accelerated ccRCC cell proliferation, migration, and invasion, as well as promoted ccRCC-derived xenograft tumor growth and lung metastasis. In line with this, silencing of GALNT6 yielded the opposite results. Mechanically, high expression of GALNT6 led to the accumulation of Tn antigen in ccRCC cells. By undertaking immunoprecipitation coupled with liquid chromatography/mass spectrometry, vicia villosa agglutinin blot, and site-directed mutagenesis assays, we found that O-glycosylation of prohibitin 2 (PHB2) at Ser161 was required for the GALNT6-induced ccRCC cell proliferation, migration, and invasion. Additionally, we identified lens epithelium-derived growth factor (LEDGF) as a key regulator of GALNT6 transcriptional induction in ccRCC growth and an upstream contributor to ccRCC aggressive behavior. Collectively, our findings indicate that GALNT6-mediated abnormal O-glycosylation promotes ccRCC progression, which provides a potential therapeutic target in ccRCC development.

GALNT6 promotes bladder cancer malignancy and immune escape by epithelial-mesenchymal transition and CD8+ T cells

Bladder cancer (BC) ranks as the sixth cancer in males and the ninth most common cancer worldwide. Conventional treatment modalities, including surgery, radiation, chemotherapy, and immunotherapy, have limited efficacy in certain advanced instances. The involvement of GALNT6-mediated aberrant O-glycosylation modification in several malignancies and immune evasion is a subject of speculation. However, its significance in BC has not been investigated. Through the integration of bioinformatics analysis and laboratory experimentation, we have successfully clarified the role of GALNT6 in BC. Our investigation revealed that GALNT6 has significant expression in BC, and its high expression level correlates with advanced stage and high grade, leading to poor overall survival. Moreover, both in vitro and in vivo experiments demonstrate a strong correlation between elevated levels of GALNT6 and tumor growth, migration, and invasion. Furthermore, there is a negative correlation between elevated GALNT6 levels, the extent of CD8+ T cell infiltration in the tumor microenvironment, and the prognosis of patients. Functional experiments have shown that the increased expression of GALNT6 could enhance the malignant characteristics of cancer cells by activating the epithelial-mesenchymal transition (EMT) pathway. In brief, this study examined the impact of GALNT6-mediated abnormal O-glycosylation on the occurrence and progression of bladder cancer and its influence on immune evasion. It also explored the possible molecular mechanism underlying the interaction between tumor cells and immune cells, as well as the bidirectional signaling involved. These findings offer a novel theoretical foundation rooted in glycobiology for the clinical application of immunotherapy in BC.

Insights into the role of glycosyltransferase in the targeted treatment of gastric cancer

Gastric cancer is a remarkably heterogeneous tumor. Despite some advances in the diagnosis and treatment of gastric cancer in recent years, the precise treatment and curative outcomes remain unsatisfactory. Poor prognosis continues to pose a major challenge in gastric cancer. Therefore, it is imperative to identify effective targets to improve the treatment and prognosis of gastric cancer patients. It should be noted that glycosylation, a novel form of posttranslational modification, is a process capable of regulating protein function and influencing cellular activities. Currently, numerous studies have shown that glycosylation plays vital roles in the occurrence and progression of gastric cancer. As crucial enzymes that regulate glycan synthesis in glycosylation processes, glycosyltransferases are potential targets for treating GC. Hence, investigating the regulation of glycosyltransferases and the expression of associated proteins in gastric cancer cells is highly important. In this review, the related glycosyltransferases and their related signaling pathways in gastric cancer, as well as the existing inhibitors of glycosyltransferases, provide more possibilities for targeted therapies for gastric cancer.

Identification of prognostic models for glycosylation-related subtypes and tumor microenvironment infiltration characteristics in clear cell renal cell cancer

Background

One of the most fatal forms of cancer of the urinary system, renal cell carcinoma (RCC), significantly negatively impacts human health. Recent research reveals that abnormal glycosylation contributes to the growth and spread of tumors. However, there is no information on the function of genes related to glycosylation in RCC.

Methods

In this study, we created a technique that can be used to guide the choice of immunotherapy and chemotherapy regimens for RCC patients while predicting their survival prognosis. The Cancer Genome Atlas (TCGA) provided us with patient information, while the GeneCards database allowed us to collect genes involved in glycosylation. GSE29609 was used as external validation to assess the accuracy of prognostic models. The "ConsensusClusterPlus" program created molecular subtypes based on genes relevant to glycosylation discovered using differential expression analysis and univariate Cox analysis. We examined immune cell infiltration as measured by estimate, CIBERSORT, TIMER, and ssGSEA algorithms, Tumor Immune Dysfunction and Exclusion (TIDE) and exclusion of tumour stemness indices (TSIs) based on glycosylation-related molecular subtypes and risk profiles. Stratification, somatic mutation, nomogram creation, and chemotherapy response prediction were carried out based on risk factors.

Results

We built and verified 16 gene signatures associated with the prognosis of ccRCC patients, which are independent prognostic variables, and identified glycosylation-related genes by bioinformatics research. Cluster 2 is associated with lower human leukocyte antigen expression, worse overall survival, higher immunological checkpoints, and higher immune escape scores. In addition, cluster 2 had significantly better angiogenic activity, mesenchymal EMT, and stem ability scores. Higher immune checkpoint genes and human leukocyte antigens are associated with lower overall survival and a higher risk score. Higher estimated and immune scores, lesser tumor purity, lower mesenchymal EMT, and higher stem scores were all characteristics of the high-risk group. High amounts of tumor-infiltrating lymphocytes, a high mutation load, and a high copy number alteration frequency were present in the high-risk group.Discussion.According to our research, the 16-gene prognostic signature may be helpful in predicting prognosis and developing individualized treatments for patients with renal clear cell carcinoma, which may result in new personalized management options for these patients.

Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

BACKGROUND

Ovarian cancer (OC) is one of the most common gynecological tumors with high morbidity and mortality. Altered serum N-glycome has been observed in many diseases, while the association between serum protein N-glycosylation and OC progression remains unclear, particularly for the onset of carcinogenesis from benign neoplasms to cancer.

METHODS

Herein, a mass spectrometry based high-throughput technique was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasms and different stages of OC. To elucidate the alterations of glycan features in OC progression, an orthogonal strategy with lectin-based ELISA was performed.

RESULTS

It was observed that the initiation and development of OC was associated with increased high-mannosylationand agalactosylation, concurrently with decreased total sialylation of serum, each of which gained at least moderately accurate merits. The most important individual N-glycans in each glycan group was H7N2, H3N5 and H5N4S2F1, respectively. Notably, serum N-glycome could be used to accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared to CA125 and HE4. Furthermore, bioinformatics analysis based discriminative model verified the diagnostic performance of serum N-glycome for OC in two independent sets.

CONCLUSIONS

These findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.

Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma

Background

Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them.

Methods

Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC).

Results

We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909).

Conclusions

Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.