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The endocrine therapy resistance of breast cancer is the difficulty and challenge to be urgently solved in the current treatment. In this study, we examined the effects of noncoding RNA LINC00094 and miR-19a-3p on breast cancer in vivo and in vitro by RT-QPCR, Western Blot, luciferase assay, immunofluorescence and drug sensitivity tests. The plasma level of CYP19A1 in patients with breast cancer resistance was lower than that in drug sensitive patients. Compared with normal subjects, miR-19a-3p was highly expressed in plasma of patients with breast cancer. miR-19a-3p is highly expressed in estrogen receptor positive breast cancer cells. The expression of miR-19a-3p promoted the migration and EMT of breast cancer cells and reduced the sensitivity of breast cancer to Letrozole. LINC00094 sponge adsorbed miR-19a-3p. LINC00094 promotes the expression of CYP19A1, the target gene of miR-19a-3p, and inhibits the EMT process of breast cancer, ultimately promoting the sensitivity of ER-positive breast cancer cells to Letrozole. This study found a new mechanism of Letrozole sensitivity in ER positive breast cancer.

Lung adenocarcinoma is a malignant and fatal respiratory disease. However, due to its complex pathogenesis and poorly effective therapeutic options, accurate early diagnosis and prognosis remain elusive. Now, there is increasing evidence that tumor stem cells are involved in tumorigenesis, metastasis, relapse, resistance to chemotherapy and radiotherapy and are one of the reasons why tumors cannot be cured. The mRNA expression based-stemness index (mRNAsi) is a parameter obtained by Malta and his colleagues applying innovative one-class logistic regression machine learning algorithm (OCLR) on mRNA expression in normal stem cells and their progeny. It is a valid evaluation parameter and is currently employed to evaluate the degree of differentiation of a certain tumor. In this study, we first used WGCNA and the software Cytoscape to obtain key modules and hub genes. We then applied LASSO regression analysis to calculate the genes in the key module to obtain a six-gene risk model. Moreover, the accuracy of this model was validated. Finally, we took the intersection of hub genes and risk genes and validated CENPA as both a tumor stemness regulator and a tumor prognostic factor in lung cancer.

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Liver cancer is a malignant cancer phenotype for which there currently remains a lack of reliable biomarkers and therapeutic targets for disease management. Tryptophan 2,3-dioxygenase (TDO2), a heme-containing polyoxygenase enzyme, is primarily expressed in cells of the liver and nervous systems. In the present study, through the combination of cancer bioinformatics and analysis of clinical patient samples, it was shown that TDO2 expression in liver cancer tissue samples was significantly higher than that in normal tissues, and liver cancer patients with high TDO2 expression had a poor prognosis. Mechanistic studies on liver cancer cells showed that TDO2 promoted cancer cell migration and invasion via signal transduction through the Wnt5a pathway. Such regulation impacted the expression of cancer-associated biomarkers, such as matrix metalloprotease 7 (MMP7) and the cell adhesion receptor CD44. Treatment with a calcium channel blocker (azelnidipine) reduced TDO2 levels and inhibited liver cancer cell migration and invasion. A mouse xenograft cancer model showed that TDO2 promoted tumorigenesis. Furthermore, azelnidipine treatment to downregulate TDO2 also decreased liver cancer development in this mouse cancer model. TDO2 is thus not only a useful liver cancer biomarker but a potential drug target for management of liver cancer.