Tumor development, involving both cell growth (mass accumulation) and cell proliferation, is a complex process governed by the interplay of multiple signaling pathways. TET2 mainly functions as a DNA dioxygenase, which modulates gene expression and biological functions via oxidation of 5mC in DNA, yet whether it plays a role in regulating cell growth remains unknown. Here we show that TET2 suppresses mTORC1 signaling, a major growth controller, to inhibit cell growth and promote autophagy. Mechanistically, TET2 functions as a 5mC “eraser” by mRNA oxidation, abolishes YBX1–HuR binding and promotes decay of urea cycle enzyme mRNAs, thus negatively regulating urea cycle and arginine production, which suppresses mTORC1 signaling. Therefore, TET2-deficient tumor cells are more sensitive to mTORC1 inhibition. Our results uncover a novel function for TET2 in suppressing mTORC1 signaling and inhibiting cell growth, linking TET2-mediated mRNA oxidation to cell metabolism and cell growth control. These findings demonstrate the potential of mTORC1 inhibition as a possible treatment for TET2-deficient tumors.

Tumor development, involving both cell growth (mass accumulation) and cell proliferation, is a complex process governed by the interplay of multiple signaling pathways. TET2 mainly functions as a DNA dioxygenase, which modulates gene expression and biological functions via oxidation of 5mC in DNA, yet whether it plays a role in regulating cell growth remains unknown. Here we show that TET2 suppresses mTORC1 signaling, a major growth controller, to inhibit cell growth and promote autophagy. Mechanistically, TET2 functions as a 5mC “eraser” by mRNA oxidation, abolishes YBX1–HuR binding and promotes decay of urea cycle enzyme mRNAs, thus negatively regulating urea cycle and arginine production, which suppresses mTORC1 signaling. Therefore, TET2-deficient tumor cells are more sensitive to mTORC1 inhibition. Our results uncover a novel function for TET2 in suppressing mTORC1 signaling and inhibiting cell growth, linking TET2-mediated mRNA oxidation to cell metabolism and cell growth control. These findings demonstrate the potential of mTORC1 inhibition as a possible treatment for TET2-deficient tumors.

BackgroundRenal cell carcinoma (RCC) accounts for approximately 2–3% of all adult malignancies. Clear cell renal cell carcinoma (ccRCC), which comprises 70–80% of all RCC cases, is the most common histological subtype.MethodsccRCC transcriptome data and clinical information were downloaded from the TCGA database. We used the TCGA and GEPIA databases to analyze relative expression of BMP1 in various types of human cancer. GEPIA was used to perform survival analysis for BMP1 in various cancer types. Upstream binding miRNAs of BMP1 were obtained through several important target gene prediction tools. StarBase was used to predict candidate miRNAs that may bind to BMP1 and candidate lncRNAs that may bind to hsa-miR-532-3p. We analyzed the association between expression of BMP1 and immune cell infiltration levels in ccRCC using the TIMER website. The relationship between BMP1 expression levels and immune checkpoint expression levels was also investigated.ResultsBMP1 was upregulated in GBM, HNSC, KIRC, KIRP and STAD and downregulated in KICH and PRAD. Combined with OS and DFS, BMP1 can be used as a biomarker for poor prognosis among patients with KIRC. Through expression analysis, survival analysis and correlation analysis, LINC00685, SLC16A1-AS1, PVT1, VPS9D1-AS1, SNHG15 and the CCDC18-AS1/hsa-miR-532-3p/BMP1 axis were established as the most potential upstream ncRNA-related pathways of BMP1 in ccRCC. Furthermore, we found that BMP1 levels correlated significantly positively with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression.ConclusionOur results demonstrate that ncRNA-mediated high expression of BMP1 is associated with poor prognosis and tumor immune infiltration in ccRCC.

BackgroundThe prevalence of diabetes mellitus (DM) is dramatically increasing around the world, and patients are getting younger with changes in living standards and lifestyle. This study summarized and analyzed the clinical characteristics of different types of newly diagnosed diabetes mellitus patients with an onset age between 18 and 40 years to provide clinical evidence for the early diagnosis and treatment of diabetes, reduce short-term and long-term complications and offer scientific and personalized management strategies.MethodsA total of 655 patients newly diagnosed with early-onset diabetes mellitus in the Department of Endocrinology, the First Medical Center of PLA General Hospital from January 2012 to December 2022 were retrospectively enrolled in this study, with an onset age of 18–40 years. Their clinical data were collected and investigated. All patients were divided into two groups according to whether they presented with diabetic microangiopathy. Similarly, patients with early-onset type-2 diabetes were grouped in accordance with whether they had ketosis at the time of diagnosis. Binary logistic regression analysis was performed to analyze risk factors, and receiver-operating characteristic (ROC) analysis was used to explore the predictive value of significant risk factors.ResultsThe findings were as follows: (1) Of 655 enrolled patients, 477 (72.8%) were male and 178 (27.1%) were female, with a mean age of onset of was 29.73 years ± 0.24 SD. (2) The prevalence of early-onset diabetes was gradually increasing. Type-2 diabetes was the most common type of early-onset diabetes (491, 75.0%). The ages of onset of early-onset type-1 diabetes, type-2 diabetes and LADA were mainly 18–24 years, 25–40 years and 33–40 years, respectively. (3) Initial clinical manifestations of early-onset diabetes were classic diabetes symptoms (361, 55.1%), followed by elevated blood glucose detected through medical examination (207, 31.6%). (4) Binary logistic regression analysis suggested that high serum uric acid (UA), a high urinary albumin-to-creatinine ratio (UACR) and diabetic peripheral neuropathy (DPN) were risk factors for microangiopathy in early-onset diabetes patients (P < 0.05). The area under the curve (AUC) on ROC analysis of the combination of UA, UACR and DPN was 0.848, 95% CI was 0.818 ~ 0.875, sensitivity was 73.8% and specificity was 85.9%, which had higher predictive value than those of UA, UACR and DPN separately. (5) Weight loss, high glycosylated hemoglobin (HbA1c) and young onset age were risk factors for ketosis in patients with early-onset type-2 diabetes (P < 0.05).Conclusion(1) Men were more likely to have early-onset diabetes than women. (2) Early-onset diabetes patients with high serum uric acid levels, high UACRs and peripheral neuropathy were prone to microangiopathy. Comprehensive evaluation of these risk factors could have higher predictive value in the prediction, diagnosis and treatment of microvascular lesions. (3) Patients with weight loss at onset, high HbA1c and young onset age were more likely to develop ketosis. Attention should be given to the metabolic disorders of these patients.