Sunitinib is a first-line targeted therapy for patients with renal cell carcinoma (RCC), but resistance represents a significant obstacle to the treatment of advanced and metastatic RCC. Metabolic reprogramming is a characteristic of RCC, and changes in metabolic processes might contribute to resistance to sunitinib. In this study, we identified methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), a mitochondrial enzyme involved in one-carbon metabolism, as a critical mediator of sunitinib resistance in RCC. MTHFD2 was elevated in sunitinib-resistant RCC cells, and loss of MTHDF2 conferred sensitivity to sunitinib. In patients, MTHFD2 was highly expressed in RCC and was associated with poor outcomes. Mechanistically, MTHFD2 stimulated UDP-N-acetylglucosamine (UDP-GlcNAc) biosynthesis and promoted cMYC O-GlcNAcylation by driving the folate cycle. O-GlcNAcylation enhanced cMYC stability and promoted MTHFD2 and cyclin D1 transcription. Targeting MTHFD2 or cyclin D1 sensitized tumor cells to sunitinib in vitro and in vivo. Consistently, development of a peptide drug capable of efficiently degrading MTHFD2 enabled reversal of sunitinib resistance in RCC. These findings identify a noncanonical metabolic function of MTHFD2 in cell signaling and response to therapy and reveal the interplay between one-carbon metabolism and sunitinib resistance in RCC. Targeting MTHFD2 could be an effective approach to overcome sunitinib resistance. Significance: MTHFD2 regulates cMYC O-GlcNAcylation to promote sunitinib resistance in renal cell carcinoma, highlighting the important role of one-carbon metabolism in sunitinib resistance and proposing therapeutic strategies to improve patient outcomes.

Background: Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC. Methods: The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort. Results: We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort. Conclusion: The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.

Background: Our study aims to investigate the mechanisms through which Fc receptor‐like A (FCRLA) promotes renal cell carcinoma (RCC) and to examine its significance in relation to tumor immune infiltration.Materials and Methods: The correlation between FCRLA and data clinically related to RCC was explored using The Cancer Genome Atlas (TCGA), then validated using Gene Expression Omnibus (GEO) gene chip data. Enrichment and protein–protein interaction (PPI) network analyses were performed for FCRLA and its co‐expressed genes. FCRLA was knocked down in RCC cell lines to evaluate its impact on biological behavior. Then the potential downstream regulators of FCRLA were determined by western blotting, and rescue experiments were performed for verification. The relevance between FCRLA and various immune cells was analyzed through GSEA, TIMER, and GEPIA tools. TIDE and ESTIMATE algorithms were used to predict the effect of FCRLA in immunotherapy.Results: Fc receptor‐like A was associated with clinical and T stages and could predict the M stage (AUC = 0.692) and 1–3‐ and 5‐year survival rates (AUC = 0.823, 0.834, and 0.862) of RCC patients. Higher expression of FCLRA predicted an unfavorable overall survival (OS) in TCGA‐RCC and GSE167573 datasets (p = 0.03, p = 0.04). FCRLA promoted the malignant biological behavior of RCC cells through the pERK1/2/‐MMP2 pathway and was associated with tumor immune microenvironment in RCC.Conclusion: Fc receptor‐like A is positively correlated with poor outcomes in RCC patients and plays an oncogenic role in RCC through the pERK1/2‐MMP2 pathway. Patients with RCC might benefit from immunotherapy targeting FCRLA.

Background: As a novel type of the prevalent post-transcriptional modifications, N7-methylguanosine (m7G) modification is essential in the tumorigenesis, progression, and invasion of many cancers, including bladder cancer (BCa). However, the integrated roles of m7G-related lncRNAs in BCa remain undiscovered. This study aims to develop a prognostic model based on the m7G-related lncRNAs and explore its predictive value of the prognosis and anti-cancer treatment sensitivity. Methods: We obtained RNA-seq data and corresponding clinicopathological information from the TCGA database and collected m7G-related genes from previous studies and GSEA. Based on LASSO and Cox regression analysis, we developed a m7G prognostic model. The Kaplan–Meier (K-M) survival analysis and ROC curves were performed to evaluate the predictive power of the model. Gene set enrichment analysis (GSEA) was conducted to explore the molecular mechanisms behind apparent discrepancies between the low- and high-risk groups. We also investigated immune cell infiltration, TIDE score, TMB, the sensitivity of common chemotherapy drugs, and the response to immunotherapy between the two risk groups. Finally, we validated the expression levels of these ten m7G-related lncRNAs in BCa cell lines by qRT-PCR. Results: We developed a m7G prognostic model (risk score) composed of 10 m7G-related lncRNAs that are significantly associated with the OS of BCa patients. The K-M survival curves revealed that the high-risk group patients had significantly worse OS than those in the low-risk group. The Cox regression analysis confirmed that the risk score was a significant independent prognostic factor for BCa patients. We found that the high-risk group had higher the immune scores and immune cell infiltration. Furthermore, the results of the sensitivity of common anti-BCa drugs showed that the high-risk group was more sensitive to neoadjuvant cisplatin-based chemotherapy and anti-PD1 immunotherapy. Finally, qRT-PCR revealed that AC006058.1, AC073133.2, LINC00677, and LINC01338 were significantly downregulated in BCa cell lines, while the expression levels of AC124312.2 and AL158209.1 were significantly upregulated in BCa cell lines compared with normal cell lines. Conclusion: The m7G prognostic model can be applied to accurately predict the prognosis and provide robust directions for clinicians to develop better individual-based and precise treatment strategies for BCa patients.

Background: During the COVID-19 pandemic, elective surgery has to undergo longer wait times, including nephrectomy for T1 renal cell carcinoma (RCC). This study aimed to investigate the time-to-surgery (TTS) of Chinese T1 RCC patients and its influencing factors, and to illustrate the impact of TTS on the prognosis of T1 RCC. Methods: We retrospectively enrolled 762 Chinese patients with pathological T1 RCC that underwent nephrectomy. To discover the impact of TTS on survival outcomes, we explored the possible delay intervals by week using the Kaplan-Meier method and Log-rank test. Cox proportional hazard models with inverse probability-treatment weighting (IPTW) were used to assess the association between TTS and disease-free survival (DFS) and overall survival (OS). Results: The median TTS of T1 RCC patients was 15 days. The Charlson comorbidity index, the Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score, and the maximal tumor diameter on presentation were independent influencing factors for TTS. The cut-off point of TTS was selected as 5 weeks according to the Log-rank analysis. For T1a RCC, patients with TTS > 5 weeks had similar DFS (HR = 2.39; 95% CI, 0.82–6.94; p = 0.109) and OS (HR = 1.28; 95% CI, 0.23–7.16; p = 0.779) compared to patients with TTS ≤ 5 weeks. For T1b RCC, patients with TTS > 5 weeks had shorter DFS (HR = 2.90; 95% CI = 1.46–5.75; p = 0.002) and OS (HR = 2.49, 95% CI = 1.09–5.70; p = 0.030) than patients with TTS ≤ 5 weeks. Conclusions: Prolonged TTS had no impact on the prognosis of T1a RCC while surgery delayed for over 5 weeks may lead to worse survival in T1b RCC.