Characterization and function of biomarkers in sunitinib-resistant renal carcinoma cells

Identification of molecular characteristics of FUT8 and alteration of core fucosylation in kidney renal clear cell cancer

BACKGROUND

Kidney renal clear cell cancer (KIRC) is a type of urological cancer that occurs worldwide. Core fucosylation (CF), as the most common post-translational modification, is involved in the tumorigenesis.

METHODS

The alterations of CF-related genes were summarized in pan-cancer. The "ConsensusClusterPlus" package was utilized to identify two CF-related KIRC subtypes. The "ssgsea" function was chosen to estimate the CF score, signaling pathways and cell deaths. Multiple algorithms were applied to assess immune responses. The "oncoPredict" was utilized to estimate the drug sensitivity. The IHC and subgroup analysis was performed to reveal the molecular features of FUT8. Single-cell RNA sequencing (scRNA-seq) data were scrutinized to evaluate the CF state.

RESULTS

In pan-cancer, there was a noticeable alteration in the expression of CF-related genes. In KIRC, two CF-related subtypes (i.e., C1, C2) were obtained. In comparison to C2, C1 exhibited a higher CF score and correlated with poorer overall survival. Additionally, the TME of C2 demonstrated increased activity in neutrophils, macrophages, myeloid dendritic cells, and B cells, alongside a higher presence of silent mast cells, NK cells, and endothelial cells. Compared to normal samples, higher expression of FUT8 is observed in KIRC. The mutation of SETD2 was more frequent in low-FUT8 samples while the mutation of DNAH9 was more frequent in high-FUT8 samples. scRNA-seq analyses revealed that the CF score was predominantly higher in endothelial cells and fibroblast cells.

CONCLUSIONS

Two CF-related subtypes with distinct prognosis and TME were identified in KIRC. FUT8 exhibited elevated expression in KIRC samples.

Mechanisms of sunitinib resistance in renal cell carcinoma and associated opportunities for therapeutics

Sunitinib is the first-line drug for renal cell carcinoma (RCC) treatment. However, patients who received sunitinib treatment will ultimately develop drug resistance after 6-15 months, creating a huge obstacle to the current treatment of renal cell carcinoma. Therefore, it is urgent to clarify the mechanisms of sunitinib resistance and develop new strategies to overcome it. In this review, the mechanisms of sunitinib resistance in renal cell carcinoma have been summarized based on five topics: activation of bypass or alternative pathway, inadequate drug accumulation, tumour microenvironment, metabolic reprogramming and epigenetic regulation. Furthermore, present and potential biomarkers, as well as potential treatment strategies for overcoming sunitinib resistance in renal cell carcinoma, are also covered.

FMR1 is identified as an immune-related novel prognostic biomarker for renal clear cell carcinoma: A bioinformatics analysis of TAZ/YAP

WW domain-containing transcription regulator 1 (TAZ, or WWTR1) and Yes-associated protein 1 (YAP) are both important effectors of the Hippo pathway and exhibit different functions. However, few studies have explored their co-regulatory mechanisms in kidney renal clear cell carcinoma (KIRC). Here, we used bioinformatics approaches to evaluate the co-regulatory roles of TAZ/YAP and screen novel biomarkers in KIRC. GSE121689 and GSE146354 were downloaded from the GEO. The limma was applied to identify the differential expression genes (DEGs) and the Venn diagram was utilized to screen co-expressed DEGs. Co-expressed DEGs obtained the corresponding pathways through GO and KEGG analysis. The protein-protein interaction (PPI) network was constructed using STRING. The hub genes were selected applying MCODE and CytoHubba. GSEA was further applied to identify the hub gene-related signaling pathways. The expression, survival, receiver operating character (ROC), and immune infiltration of the hub genes were analyzed by HPA, UALCAN, GEPIA, pROC, and TIMER. A total of 51 DEGs were co-expressed in the two datasets. The KEGG results showed that the enriched pathways were concentrated in the TGF-β signaling pathway and endocytosis. In the PPI network, the hub genes (STAU2, AGO2, FMR1) were identified by the MCODE and CytoHubba. The GSEA results revealed that the hub genes were correlated with the signaling pathways of metabolism and immunomodulation. We found that STAU2 and FMR1 were weakly expressed in tumors and were negatively associated with the tumor stages. The overall survival (OS) and disease-free survival (DFS) rate of the high-expressed group of FMR1 was greater than that of the low-expressed group. The ROC result exhibited that FMR1 had certainly a predictive ability. The TIMER results indicated that FMR1 was positively correlated to immune cell infiltration. The abovementioned results indicated that TAZ/YAP was involved in the TGF-β signaling pathway and endocytosis. FMR1 possibly served as an immune-related novel prognostic gene in KIRC.