Tamoxifen (Tam) has long been a top treatment option for breast cancer patients, but the challenge of eliminating cancer recurrence remains. Here, we identify a signalling pathway involving ELOVL2, ELOVL2-AS1, and miR-1233-3p, which contributes to drug resistance in Tam-resistant (TamR) breast cancer. ELOVL2-AS1, a long noncoding RNA, was significantly upregulated by its antisense gene, ELOVL2, which is known to be downregulated in TamR cells. Additionally, ELOVL2-AS1 underwent the most hypermethylation in MCF-7/TamR cells. Furthermore, patients with breast cancer who developed TamR during chemotherapy had significantly lower expression of ELOVL2-AS1 compared to those who responded to Tam. Ectopic downregulation of ELOVL2-AS1 by siRNA both stimulated cancer cell growth and deteriorated TamR. We also found that ELOVL2-AS1 sponges miR-1233-3p, which has pro-proliferative activity and elevates TamR, leading to the activation of potential target genes, such as MYEF2, NDST1, and PIK3R1. These findings suggest that ELOVL2-AS1, in association with ELOVL2, may contribute to the suppression of drug resistance by sponging miR-1233-3p in breast cancer.
While a number of coding genes have explained the anticancer activity of ginsenoside Rh2, little is known about noncoding RNAs. This study was performed to elucidate the regulatory activity of long noncoding RNA (lncRNA) CFAP20DC-AS1, which is known to be downregulated by Rh2. MiR-3614-3p, which potentially binds CFAP20DC-AS1, was screened using the LncBase Predicted program, and the binding was verified by assaying the luciferase activity of a luciferase/lncRNA recombinant plasmid construct. The competitive endogenous RNA (ceRNA) relationship of the two RNAs was further validated by quantitative PCR after deregulation of each RNA using siRNA. The effect of miRNA and target genes on the MCF-7 cancer cell growth was determined by monitoring proliferation and apoptosis in the presence of Rh2 after deregulating the corresponding gene. The miRNA decreased the luciferase activity of the luciferase/CFAP20DC-AS1 fusion vector, confirming the binding. SiRNA-based deregulation of CFAP20DC-AS1 attenuated the expression of miR-3614-3p and vice versa. In contrast to CFAP20DC-AS1, miR-3614-3p was upregulated by Rh2, inhibiting proliferation but stimulating apoptosis of the MCF-7 cells. Target genes of miR-3614-3p, BBX and TNFAIP3, were downregulated by Rh2 and the miRNA but upregulated by the lncRNA. Rh2 inhibits CFAP20DC-AS1, which obscures the association of the lncRNA with miR-3614-3p, resulting in the suppression of oncogenic BBX and TNFAIP3. Taken together, the Rh2/CFAP20DC-AS1/miR-3614-3p/target gene axis contributes to the antiproliferation activity of Rh2 in cancer cells.
Ginsenosides in ginseng are known for their potential health benefits, including antioxidant properties and their potential to exhibit anticancer effects. Besides a various range of coding genes, ginsenosides impose their efficacy by targeting noncoding RNAs. Long noncoding RNA ( lncRNA) has gained significant attention from both basic and clinical oncology fields due to its involvement in various cancer cell activities such as proliferation, apoptosis, metastasis, and autophagy. These events can be achieved either by lncRNA alone or in association with microRNAs or proteins. This review aims to summarize the diverse activities of lncRNAs that are regulated by ginsenosides, focusing on their role in regulating target genes through signaling pathways in human diseases. We highlight the results of studies on the expression profiles of lncRNAs induced by ginsenosides in efforts to inhibit cancer cell proliferation. Finally, we discuss the potential and challenges of utilizing lncRNAs as diagnostic markers for disease treatment.
This paper proposes new estimators for the panel autoregressive (PAR) model of order 1 with short time dimensions and large cross sections. These estimators are based on the cross-sectional regression model using the rst time series ob- servations as a regressor and the last as a dependent variable. The regressors and errors of this regression model are correlated. The rst estimator is the quasi maximum likelihood estimator (QMLE). The second estimator is the bias- corrected pooled least squares estimator (BCPLSE) that eliminates the asymp- totic bias of the pooled least squares estimator by using the QMLE. The QMLE and BCPLSE are extended to the PAR model with endogenous regressors. The QMLE and BCPLSE provide consistent estimates of the PAR coe¢ cients for stationary, unit root and explosive PAR models and consistently estimate the coe¢ cients of endogenous regressors. Their nite sample properties are com- pared with those of some other estimators for the PAR model of order 1. This papers estimators are shown to perform quite well in nite samples.
'%3e%3cg id='b'%3e%3cpath id='a' stroke='%23000' stroke-width='2' d='M-6-25H6m-12 3H6m-12 3H6'/%3e%3cuse xlink:href='%23a' y='44'/%3e%3c/g%3e%3cpath stroke='%23fff' d='M0 17v10'/%3e%3ccircle r='12' fill='%23cd2e3a'/%3e%3cpath fill='%230047a0' d='M0-12A6 6 0 0 0 0 0a6 6 0 0 1 0 12 12 12 0 0 1 0-24z'/%3e%3c/g%3e%3cg transform='rotate(-123.69)'%3e%3cuse xlink:href='%23b'/%3e%3cpath stroke='%23fff' d='M0-23.5v3M0 17v3.5m0 3v3'/%3e%3c/g%3e%3c/svg%3e)
