Metformin, as the preferred antihyperglycemic drug for type 2 diabetes, has been found to have a significant effect in inhibiting tumor growth in recent years. However, metformin alone in cancer treatment has the disadvantages of high dose concentrations and few targeted cancer types. Increasing studies have confirmed that metformin can be used in combination with conventional anticancer therapy to obtain more promising clinical benefits, which is expected to be rapidly transformed and applied in clinic. Some combination therapy strategies including metformin combined with chemotherapy, radiotherapy, targeted therapy and immunotherapy have been proven to have more significant antitumor effects and longer survival time than monotherapy. In this review, we summarize the synergistic antitumor effects and mechanisms of metformin in combination with other current conventional anticancer therapies. In addition, we update the research progress and the latest prospect of the metformin-combined application in the cancer treatment. This work could provide more evidence and future direction for the clinical application of metformin in antitumor.

Isocitrate dehydrogenase (IDH) is a key metabolic enzyme catalyzing the interconversion of isocitrate to α-ketoglutarate (α-KG). Mutations in IDH lead to loss of normal enzymatic activity and gain of neomorphic activity that irreversibly converts α-KG to 2-hydroxyglutarate (2-HG), which can competitively inhibit a-KG-dependent enzymes, subsequently induces cell metabolic reprograming, inhibits cell differentiation, and initiates cell tumorigenesis. Encouragingly, this phenomenon can be reversed by specific small molecule inhibitors of IDH mutation. At present, small molecular inhibitors of IDH1 and IDH2 mutant have been developed, and promising progress has been made in preclinical and clinical development, showing encouraging results in patients with IDH2 mutant cancers. This review will focus on the biological roles of IDH2 mutation in tumorigenesis, and provide a proof-of-principle for the development and application of IDH2 mutant inhibitors for human cancer treatment.

Background: The well-known traditional Chinese herbal formula Guizhi Fuling Wan (GFW) was recently reported to improve the curative effects of chemotherapy for ovarian cancer with few clinical side effects. The present study aimed to investigate the reversal mechanism of sera derived from rats exposed to Guizhi Fuling Wan extract (GFWE) in cisplatin-resistant human ovarian cancer SKOV3/DDP cells; the proteins examined included phosphatase and tensin homolog (PTEN) and metadherin (MTDH), and the possible protein interaction between PTEN and MTDH was explored. Methods: GFWE was administered to healthy Wistar rats, and the sera were collected after five days. The PubMed and CNKI databases were searched for literature on the bioactive blood components in the sera. The systemsDock website was used to predict potential PTEN/MTDH interactions with the compounds. RT-qPCR, western blotting, and immunofluorescence analyses were used to analyze the mRNA and protein levels of MTDH and PTEN. Laser confocal microscopy and coimmunoprecipitation (co-IP) were used to analyze the colocalization and interaction between MTDH and PTEN. Results: Sixteen bioactive compounds were identified in GFWE sera after searching the PubMed and CNKI databases. The systemsDock website predicted the potential PTEN/MTDH interactions with the compounds. RT-qPCR, western blotting, and immunofluorescence analyses showed decreased MTDH expression and increased PTEN expression in the sera. Laser confocal microscopy images and coimmunoprecipitation (co-IP) analyses demonstrated that a colocalization and interaction occurred between MTDH and PTEN, and the addition of the sera changed the interaction status. Conclusions: GFWE restored sensitivity to cisplatin by inhibiting MTDH expression, inducing PTEN expression, and improving the interaction between MTDH and PTEN in SKOV3/DDP cells, and these proteins and their interaction may serve as potential targets for cancer treatment. The sera may represent a new source of anticancer compounds that could help to manage chemoresistance more efficiently and safely.

Background: Autophagy is a “self-feeding” phenomenon of cells, which is crucial in mammalian development. Long non-coding RNA (lncRNA) is a new regulatory factor for cell autophagy, which can regulate the process of autophagy to affect tumor progression. However, poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer.Objective: This study aimed to construct an autophagy-related lncRNA signature that can effectively predict the prognosis of breast cancer patients and explore the potential functions of these lncRNAs.Methods: The RNA sequencing (RNA-Seq) data of breast cancer patients was collected from The Cancer Genome Atlas (TCGA) database and the GSE20685 database. Multivariate Cox analysis was implemented to produce an autophagy-related lncRNA signature in the TCGA cohort. The signature was then validated in the GSE20685 cohort. The receiver operator characteristic (ROC) curve was performed to evaluate the predictive ability of the signature. Gene set enrichment analysis (GSEA) was used to explore the potential functions based on the signature. Finally, the study developed a nomogram and internal verification based on the autophagy-related lncRNAs.Results: A signature composed of 9 autophagy-related lncRNAs was determined as a prognostic model, and 1,109 breast cancer patients were divided into high-risk group and low-risk group based on median risk score of the signature. Further analysis demonstrated that the over survival (OS) of breast cancer patients in the high-risk group was poorer than that in the low-risk group based on the prognostic signature. The area under the curve (AUC) of ROC curve verified the sensitivity and specificity of this signature. Additionally, we confirmed the signature is an independent factor and found it may be correlated to the progression of breast cancer. GSEA showed gene sets were notably enriched in carcinogenic activation pathways and autophagy-related pathways. The qRT-PCR identified 5 lncRNAs with significantly differential expression in breast cancer cells based on the 9 lncRNAs of the prognostic model, and the results were consistent with the tissues.Conclusion: In summary, our signature has potential predictive value in the prognosis of breast cancer and these autophagy-related lncRNAs may play significant roles in the diagnosis and treatment of breast cancer.