Transforming growth factor-β (TGF-β) signaling has a paradoxical role in cancer progression, and it acts as a tumor suppressor in the early stages but a tumor promoter in the late stages of cancer. Once cancer cells are generated, TGF-β signaling is responsible for the orchestration of the immunosuppressive tumor microenvironment (TME) and supports cancer growth, invasion, metastasis, recurrence, and therapy resistance. These progressive behaviors are driven by an “engine” of the metabolic reprogramming in cancer. Recent studies have revealed that TGF-β signaling regulates cancer metabolic reprogramming and is a metabolic driver in the tumor metabolic microenvironment (TMME). Intriguingly, TGF-β ligands act as an “endocrine” cytokine and influence host metabolism. Therefore, having insight into the role of TGF-β signaling in the TMME is instrumental for acknowledging its wide range of effects and designing new cancer treatment strategies. Herein, we try to illustrate the concise definition of TMME based on the published literature. Then, we review the metabolic reprogramming in the TMME and elaborate on the contribution of TGF-β to metabolic rewiring at the cellular (intracellular), tissular (intercellular), and organismal (cancer-host) levels. Furthermore, we propose three potential applications of targeting TGF-β-dependent mechanism reprogramming, paving the way for TGF-β-related antitumor therapy from the perspective of metabolism.

To help provide evidence for prognosis prediction and personalized targeted therapy for patients with head and neck squamous cell carcinoma (HNSCC), we investigated prognosis-specific methylation-driven genes in HNSCC. Survival time data, RNA sequencing data, and methylation data for HNSCC patients were downloaded from The Cancer Genome Atlas. The MethylMix R package based on the β mixture model was utilized to screen genes with different methylation statuses in tumor tissues and adjacent normal tissues, and a total of 182 HNSCC-related methylation-driven genes were then identified. A survival prediction scoring model based on multivariate Cox analysis was developed to screen the genes related to the prognosis of HNSCC, and a linear risk model of the methylation status of six genes (INA, LINC01354, TSPYL4, MAGEB2, EPHX3, and ZNF134) was constructed. The prognostic values of the six genes were further independently explored by survival analysis combined with methylation and gene expression analyses. The 5-year survival rate in the highrisk group of patients in the test set was 30.4% (95% CI: 22.7%-40.8%) and that in the low-risk group of patients was 65.5% (95% CI: 56.1%-76.5%). The area under the receiver operating characteristic curve for the model was 0.723, which further verified the specificity and sensitivity of the model. In addition, subsequent combined survival analysis revealed that all six genes could be used as independent prognostic markers and thus might be potential drug targets. The innovative method provides new insight into the molecular mechanism and prognosis of HNSCC. K E Y W O R D SDNA methylation-driven genes, epigenetics, HNSCC, prognostic risk model, survival analysis

Introduction: Progressive accumulation of amyloid-β (Aβ) is a pathological trait of Alzheimer's disease (AD). Amyloid-β increases free radical production in neuronal cells, leading to neuronal cell death. Hormone replacement therapy can reduce the incidence of AD, and oestrogen significantly improves the clinical signs in patients with AD. However, the long-term use of oestrogen causes a variety of diseases. Phytoestrogens have been reported to bind and activate oestrogen receptors in mammals and humans to produce oestrogen-like or anti-oestrogen-like effects. Kaempferol is a flavonoid phytoestrogen that can produce a certain protective effect in neurons. However, the molecular mechanism of kaempferol in AD is unclear. Material and methods: This study used pheochromocytoma (PC-12) cells that were damaged by Aβ 25-35 as an in vitro model of AD, and oestradiol was a positive control. The cells were incubated with kaempferol alone or in combination with fulvestrant (an antagonist of ER) and U0126 (an inhibitor of ERK) in Aβ 25-35 culture. Cell activity was measured by the MTT method. Cell apoptosis was evaluated by flow cytometry. Gene and protein expression levels were tested by qRT-PCR and Western blotting. Results: This study demonstrated that kaempferol protected PC-12 cells from Aβ 25-35-induced cell death and apoptosis in a dose-dependent manner. Treatment with fulvestrant (an antagonist of ER) and U0126 (an inhibitor of ERK) significantly increased the apoptosis of PC-12 cells. Moreover, kaempferol promoted the expression of anti-apoptotic molecules and inhibited the expression of pro-apoptotic molecules, which were blocked by fulvestrant and U0126. Conclusions: Kaempferol protected PC-12 cells against Aβ 25-35-induced cell apoptosis through the ER/ERK/MAPK signalling pathway.

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