Breast cancer has the highest cancer incidence rate in women. Early screening of breast cancer can effectively improve the treatment effect of patients. However, the main diagnostic techniques available for the detection of breast cancer require the corresponding equipment, professional practitioners, and expert analysis, and the detection cost is high. Tumor markers are a kind of active substance that can indicate the existence and growth of the tumor. The detection of tumor markers can effectively assist the diagnosis and treatment of breast cancer. The conventional detection methods of tumor markers have some shortcomings, such as insufficient sensitivity, expensive equipment, and complicated operations. Compared with these methods, biosensors have the advantages of high sensitivity, simple operation, low equipment cost, and can quantitatively detect all kinds of tumor markers. This review summarizes the biosensors (2013–2021) for the detection of breast cancer biomarkers. Firstly, the various reported tumor markers of breast cancer are introduced. Then, the development of biosensors designed for the sensitive, stable, and selective recognition of breast cancer biomarkers was systematically discussed, with special attention to the main clinical biomarkers, such as human epidermal growth factor receptor-2 (HER2) and estrogen receptor (ER). Finally, the opportunities and challenges of developing efficient biosensors in breast cancer diagnosis and treatment are discussed.
Transition metal dichalcogenides (TMDCs) are widely used in biosensing applications due to their excellent physical and chemical properties. Due to the properties of biomaterial targets, the biggest challenge that biosensors face now is how to improve the sensitivity and stability. A lot of materials had been used to enhance the target signal. Among them, TMDCs show excellent performance in enhancing biosensing signals because of their metallic and semi-conducting electrical capabilities, tunable band gap, large specific surface area and so on. Here, we review different functionalization methods and research progress of TMDCs-based biosensors. The modification methods of TMDCs for biosensor fabrication mainly include two strategies: non-covalent and covalent interaction. The article summarizes the advantages and disadvantages of different modification strategies and their effects on biosensing performance. The authors present the challenges and issues that TMDCs need to be addressed in biosensor applications. Finally, the review expresses the positive application prospects of TMDCs-based biosensors in the future.
In conclusion, our study suggests that combined intrapleural cisplatin and OK-432 followed by hyperthermotherapy are more effective in the control of MPE and improve patients' quality of life.
The emergence of resistance to chemotherapy drugs in patients with ovarian cancer is still the main cause of low survival rates. The present study aimed to identify key genes that may provide treatment guidance to reduce the incidence of drug resistance in patients with ovarian cancer. Original data of chemotherapy sensitivity and chemoresistance of ovarian cancer were obtained from the Gene Expression Omnibus dataset GSE73935. Differentially expressed genes (DEGs) between sensitive and resistant ovarian cancer cell lines were screened by Empirical Bayes methods. Overlapping DEGs between four chemoresistant groups were identified by Venn map analysis. Protein-protein interaction networks were also constructed, and hub genes were identified. The hub genes were verified by in vitro experiments as well as The Cancer Genome Atlas data. Results from the present study identified eight important genes that may guide treatment decisions regarding chemotherapy regimens for ovarian cancer, including epidermal growth factor-like repeats and discoidin I-like domains 3, NRAS proto-oncogene, hyaluronan and proteoglycan link protein 1, activated protein C receptor, CD53, cyclin-dependent kinase inhibitor 2A, insulin-like growth factor 1 receptor and roundabout guidance receptor 2 genes. Their expressions were found to have an impact on the prognosis of different treatment groups (cisplatin, paclitaxel, cisplatin + paclitaxel, cisplatin + doxorubicin and cisplatin + topotecan). The results indicated that these genes may minimise the occurrence of ovarian cancer drug resistance and may provide effective treatment options for patients with ovarian cancer.
Background: The systemic immune-inflammation index (SII) has been found to predict outcomes in many tumors. The purpose of this study was to determine the prognostic value of SII in biliary tract cancer.Methods: We searched PubMed, EMBASE, Web of Science, Cochrane Library, CNKI, CBM, Wanfang and VIP databases from its inception until May 18, 2020. Pooled hazard ratio and 95% confidence interval were calculated to assess the prognostic role of SII in patients with BTC. The main outcomes included the overall survival, cancer-specific survival, disease-free survival and recurrence-free survival. Stata 12.0 was used for statistical analysis.Results: A total of 8 studies involving 2249 patients were eventually included. The results showed that elevated SII was significantly associated with poorer OS (HR=1.56, 95% CI: 1.23–1.99, P<0.001, I2 = 68.1%), poorer DFS/RFS (HR=1.42, 95%CI:1.09–1.84, P =0.009) and poorer CSS (HR =1.55, 95% CI: 1.09–2.21, P<0.014). Subgroup analysis further verified the above results. Conclusions: Higher SII is a predictor of poor prognosis in BTC patients. SII can serve as a useful prognostic indicator and help to evaluate the prognosis and formulate treatment strategies.Registered in PROSPERO: CRD42020184556
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