An analysis of drug resistance among people living with HIV/AIDS in Shanghai, China

<div><p>Background</p><p>Understanding the mechanisms of drug resistance can facilitate better management of antiretroviral therapy, helping to prevent transmission and decrease the morbidity and mortality of people living with HIV/AIDS. However, there is little data about transmitted drug resistance and acquired drug resistance for HIV/AIDS patients in Shanghai.</p><p>Methods</p><p>A retrospective cohort study of HIV-infected patients who visited the Department of Infectious Disease from June 2008 to June 2015 was conducted in Shanghai, China. Logistic regression analysis was performed to analyze risk factors for drug resistance among HIV-infected people with virological failure. The related collected factors included patient age, gender, marital status, infection route, baseline CD4 count, antiretroviral therapy regimens, time between HIV diagnosis and initiating antiretroviral therapy. Factors with p<0.1 in the univariate logistic regression test were analyzed by multivariate logistic regression test.</p><p>Results</p><p>There were 575 subjects selected for this study and 369 participated in this research. For the antiretroviral therapy drugs, the rates of transmitted drug resistance and acquired drug resistance were significantly different. The non-nucleoside reverse transcriptase inhibitor (NNRTI) had the highest drug resistance rate (transmitted drug resistance, 10.9%; acquired drug resistance, 53.3%) and protease inhibitors (PIs) had the lowest drug resistance rate (transmitted drug resistance, 1.7%; acquired drug resistance, 2.7%). Logistic regression analysis found no factors that were related to drug resistance except marital status (married status for tenofovir: odds ratio = 6.345, 95% confidence interval = 1.553–25.921, P = 0.010) and the time span between HIV diagnosis and initiating antiretroviral therapy (≤6M for stavudine: odds ratio = 0.271, 95% confidence interval = 0.086–0.850, P = 0.025; ≤6M for didanosine: odds ratio = 0.284, 95% confidence interval = 0.096–0.842, P = 0.023; ≤6M for tenofovir: odds ratio = 0.079, 95% confidence interval = 0.018–0.350,P<0.001).</p><p>Conclusion</p><p>NNRTI had a higher DR rate compared with nucleoside reverse transcriptase inhibitor (NRTI) and PIs, consequently, LPV/r was a reasonable choice for patients with NNRTI drugs resistance in China. Only married status and a time span≤6 month between the HIV confirmed date and the time initiating antiretroviral therapy were risk factors for TDF drug resistance. Both baseline HIV-RNA load and resistance test is crucial for TDR diagnosis, and frequent monitoring of HIV-RNA load is crucial for ADR identification and intervention. Treatment adherence still plays a positive role on the outcome of ART.</p></div

Logistic Regression Analysis for All Drug Resistance Factors in the ART-experienced Group.

<p>Few participants used TDF and few participants had ≤12M between ART to DR testing, so these were not included in the logistic regression analysis for AZT drug resistance. Significant results are shown in bold.</p

TDR and ADR of ART drugs most frequently used in China.

<p>TDR and ADR of ART drugs most frequently used in China.</p

Flow Chart of the Study.

<p>Flow Chart of the Study.</p

Inhibition of TMEM16A Expression Suppresses Growth and Invasion in Human Colorectal Cancer Cells

<div><p>Metastasis leads to poor prognosis in colorectal cancer patients, and there is a growing need for new therapeutic targets. TMEM16A (ANO1, DOG1 or TAOS2) has recently been identified as a calcium-activated chloride channel (CaCC) and is reported to be overexpressed in several malignancies; however, its expression and function in colorectal cancer (CRC) remains unclear. In this study, we found expression of TMEM16A mRNA and protein in high-metastatic-potential SW620, HCT116 and LS174T cells, but not in primary HCT8 and SW480 cells, using RT-PCR, western blotting and immunofluorescence labeling. Patch-clamp recordings detected CaCC currents regulated by intracellular Ca²⁺ and voltage in SW620 cells. Knockdown of TMEM16A by short hairpin RNAs (shRNA) resulted in the suppression of growth, migration and invasion of SW620 cells as detected by MTT, wound-healing and transwell assays. Mechanistically, TMEM16A depletion was accompanied by the dysregulation of phospho-MEK, phospho-ERK1/2 and cyclin D1 expression. Flow cytometry analysis showed that SW620 cells were inhibited from the G1 to S phase of the cell cycle in the TMEM16A shRNA group compared with the control group. In conclusion, our results indicate that TMEM16A CaCC is involved in growth, migration and invasion of metastatic CRC cells and provide evidence for TMEM16A as a potential drug target for treating metastatic colorectal carcinoma.</p></div

Effect of T16Ainh-A01 on growth of SW480 and SW620 cells.

<p>Cells were treated with different concentrations of T16Ainh-A01 for 24 h and cell viability was measured by MTT assay. Data are expressed as Mean ± SD (n = 3).</p

TMEM16A knockdown induced a decrease in proliferation of SW620 cells.

<p>A, The growth of SW620 cells was inhibited by TMEM16A shRNA #1 and #2 compared to the control group (Mean ± SD; n = 3; * P<0.05). B, Representative immunoblots confirming knockdown of TMEM16A. Ctrl, control.</p

Scratch wound assay of TMEM16A shRNA on SW620 cells.

<p>A, Migration of SW620 cells was assessed by a wound-healing assay in the presence of TMEM16A shRNA #1 and shRNA #2, compared with control shRNA. Representative images of wound closure were taken at 0 h, 24 h, 48 h and 72 h after wounding under 100× magnification. B, Bar graphs of panel A are shown. Values are the means ± SD; n = 3; ** P<0.01. Ctrl, control.</p

TMEM16A knockdown decreased activation of the MEK-ERK1/2 pathway and expression of cyclin D1.

<p>Western blot results show inhibition of TMEM16A led to a decrease in phospho-MEK, phospho-ERK1/2 and cyclin D1. Ctrl, control.</p

Knockdown of TMEM16A in SW620 cells.

<p>A, Western blot analysis of TMEM16A protein expression in SW620 cells that were transfected with shRNA #1 and #2. B, The bar graph summarizes the relative expression level of TMEM16A protein from panel A. Expression of TEMEM16A protein was normalized with the expression level of β-actin (n = 3). C, Representative immunofluence images of SW620 cells are shown after TMEM16A is knockdown by shRNA #1 and shRNA #2, compared with control shRNA (200×). D, The bar graph summarizes the peak currents recorded at 100 mV voltage in SW620 cells after TMEM16A was knocked down, compared with control shRNA. **p<0.01. All data are shown as mean ± SD. E, Whole-cell currents were recorded from SW620 cells transfected with control shRNA, shRNA #1 and #2 at a holding potential of 0 mV followed by pulsing voltages between ±100 mV in steps of 20 mV.</p