Construction and Verification of a Radiation Pneumonia Prediction Model Based on Multiple Parameters.

OBJECTIVE: Patients with lung cancer are at risk of radiation pneumonia (RP) after receiving radiotherapy. We established a prediction model according to the critical indicators extracted from radiation pneumonia patients. MATERIALS AND METHODS: 74 radiation pneumonia patients were involved in the training set. Firstly, the clinical data, hematological and radiation dose parameters of the 74 patients were screened by Logistics regression univariate analysis according to the level of radiation pneumonia. Next, Stepwise regression analysis was utilized to construct the regression model. Then, the influence of continuous variables on RP was tested by smoothing function. Finally, the model was externally verified by 30 patients in validation set and visualized by R code. RESULTS: In the training set, there was 40 patients suffered≥ level 2 acute radiation pneumonia. Clinical data (diabetes), blood indexes (lymphocyte percentage, basophil percentage, platelet count) and radiation dose (V15 > 40%, V20 > 30%, V35 >18%, V40 > 15%) were related to radiation pneumonia (P < 0.05). Particularly, stepwise regression analysis indicated that the history of diabetes, the basophils percentage, platelet count and V20 could be the best combination used for predicting radiation pneumonia. The column chart was obtained by fitting the regression model with the combined indicator. The receiver operating characteristic (ROC) curve showed that the AUC in the development term was 0.853, the AUC was 0.656 in the validation term. And calibration curves of both groups showed the high stability in efficiently diagnostic. Furthermore, the DCA curve showed that the model had a satisfactory positive net benefit. CONCLUSION: The combination of the basophils percentage, platelet count and V20 is available to build a predictive model of radiation pneumonia for patients with advanced lung cancer.

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode.

BACKGROUND: The development of human tumors is associated with the abnormal expression of various functional genes, and a massive tumor-based database needs to be deeply mined. Based on a multigene prediction model, access to urgent prognosis of patients has become possible. MATERIALS AND METHODS: We selected three RNA expression profiles (GSE32863, GSE10072, and GSE43458) from the lung adenocarcinoma (LUAD) database of the Gene Expression Omnibus (GEO) and analyzed the differentially expressed genes (DEGs) between tumor and normal tissue using GEO2R program. After that, we analyzed the transcriptome data of 479 LUAD samples (54 normal tissue samples and 425 cancer tissue samples) and their clinical follow-up data from the (TCGA) database. Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) were used to assess the prediction model. Multivariate Cox analysis was used to identify independent predictors. TCGA pancreatic adenocarcinoma datasets were used to establish a nomogram model. RESULTS: We found 98 significantly prognosis-related genes using KM and COX analysis, among which six genes were found to be the DEGs in GEO. Using multivariate analysis, it was found that a single gene could not be used as an independent predictor of prognosis. However, the risk score calculated by weighting these six genes could serve as an independent prognosis predictor. COX analysis performed with multiple covariates such as age, gender, tumor stage, and TNM typing showed that risk score could still be utilized as an independent risk factor for patient survival rate (p = 0.013) and had an applicable reliability (area under the curve, AUC = 0.665). By combining risk score and various clinical features, the nomogram model was constructed, which had been proven to have high consistency for the prediction of 3- and 5-year survival rate (concordance = 0.751) and high accuracy as tested by ROC (AUC = 0.71;AUC = 0.708). CONCLUSION: We proposed a method to predict the prognosis of LUAD by weighting multiple genes and constructed a nomogram model suitable for the prognostic evaluation of LUAD, which could provide a new tool for the identification of therapeutic targets and the efficacy evaluation of LUAD.

Artesunate promotes sensitivity to sorafenib in hepatocellular carcinoma.

Enhancing sensitivity of carcinoma to sorafenib (Sor) is critical to overcome the limits of high frequency resistance and moderate efficiency during chemotherapy for advanced hepatocellular carcinoma (HCC). Here, we promote sensitivity of HCC to Sor by combination with Artesunate (Art), a derivative of artemisinin extracted from Chinese medical herb. The positive synergy of Art on inhibiting HCC growth contributes 48% dosage of Sor to reduce tumor cell viability in vitro and tumor size in vivo. Mechanically, in spite of effective suppression of RAF/MEK/ERK pathway, Sor is not able to eliminate chemoresistance of HCC driven by PI3K/AKT/mTOR pathway, while Art inhibits phosphorylation of AKT and mTOR significantly. Furthermore, combination with Art and Sor further improves apoptosis of HCC by dual inhibition of both pathways. Our study reveals a function of Art that induces HCC apoptosis via PI3K/AKT/mTOR pathway inhibition and suggests a potential therapeutic regimen of combination with Art and SOR against advanced HCC.

Dependence of artesunate on long noncoding RNA-RP11 to inhibit epithelial-mesenchymal transition of hepatocellular carcinoma.

As a first line medicine for malaria treatment, artesunate (ART) also shows antitumor potential. However, little is known about the effect of ART on the cancer cell epithelial-mesenchymal transition (EMT). In this study, we found that ART inhibited cell growth in SK-HEP1 and SM7721 hepatocellular carcinoma cell lines. A microarray was used to identify differentially expressed protein-coding RNAs (pcRNA) and long noncoding RNAs (lncRNA) between SK-HEP1 cells with and without ART treatment. A differentially expressed lncRNA-RP11, the most related to the EMT of liver cancer cells-RP11 was identified by abioinformatics method Overexpressing and silencing assays were used to verify the role of RP11 in cancer cell EMT. The levels of RP11- and EMT-related genes in liver cancer samples from 75 patients were detected by using qualitative polymerase chain reaction or immunohistochemistry. We identified 1334 pcRNAs and 1670 lncRNA with differential expression induced by ART. ART inhibits EMT, proliferation, migration, invasion, and adhesion of liver cancer cells. RP11 depresses the inhibitory effect of ART on cancer cell EMT. The level of RP11 is associated with cancer cell EMT and metastasis and survival rate of the patient. These data suggest that RP11-linking ART and cancer cell EMT are important for ART-inhibited metastasis of liver cancer.

ESAT6 inhibits autophagy flux and promotes BCG proliferation through MTOR.

In recent years, increasing studies have found that pathogenic Mycobacterium tuberculosis (Mtb) inhibits autophagy, which mediates the anti-mycobacterial response, but the mechanism is not clear. We previously reported that secretory acid phosphatase (SapM) of Mtb can negatively regulate autophagy flux. Recently, another virulence factor of Mtb, early secretory antigenic target 6 (ESAT6), has been found to be involved in inhibiting autophagy, but the mechanism remains unclear. In this study, we show that ESAT6 hampers autophagy flux to boost bacillus Calmette-Guerin (BCG) proliferation and reveals a mechanism by which ESAT6 blocks autophagosome-lysosome fusion in a mammalian target of rapamycin (MTOR)-dependent manner. In both Raw264.7 cells and primary macrophages derived from the murine abdominal cavity (ACM), ESAT6 repressed autophagy flux by interfering with the autophagosome-lysosome fusion, which resulted in an increased load of BCG. Impaired degradation of LC3Ⅱ and SQSTM1 by ESAT6 was related to the upregulated activity of MTOR. Contrarily, inhibiting MTOR with Torin1 removed the ESAT6-induced autophagy block and lysosome dysfunction. Furthermore, in both Raw264.7 and ACM cells, MTOR inhibition significantly suppressed the survival of BCG. In conclusion, our study highlights how ESAT6 blocks autophagy and promotes BCG survival in a way that activates MTOR.

Enhanced anti-tuberculosis immunity by a TAT-Ag85B protein vaccine in a murine tuberculosis model.

BACKGROUND: The development of more effective anti-tuberculosis vaccines would contribute to the control of the global problem of infection with Mycobacterium tuberculosis (MTB). Recently, increasing evidences showed that HIV-Tat protein transduction domain is implicated in promotion of vaccines by inducing cellular immuno-response. However, it is rare known about the role of TAT in vaccines against MTB. METHODS: In this study, we expressed recombinant protein-fused Ag85B with TAT (TAT-Ag85B) which was used as a vaccine to inoculate mice infected with MTB. RESULTS: As s result, both IgG2a in serum and IFN-γ or TNFα produced by spleen cells were all increased significantly in the mice inoculated by TAT-Ag85B. Furthermore, consistently, TAT-Ag85B inoculation significantly reduced MTB loads both in lung and spleen. CONCLUSIONS: These findings demonstrate that a novel protein vaccine of TAT-Ag85B enhances immune response both in humoral and cellular immunity, and contributes to protective efficacy against MTB.

Observation of the protective effect of N-NAC on radiation-induced pulmonary injury / 中国基层医药

Objective To observe the protective effect of N-NAC on radiation-induced lung injury. Methods 86 cases of thoracic neoplasm patients were chosen and randomly divided into two groups,group RT +N(n =43)and group RT(n =43).Two groups were observed by CT after radiotherapy.Acute and chronical toxicities were graded by RTOG.TGF-β1,IL-1,IL-4,TNF were observed before and after the radiotherapy.Results After 3 monthsof radiotherapy,RTOG≥2 was 23.4%(RT +N),while RTOG≥2 was 53.1%(RT).there was significant differencebetween the two groups(P <0.01).At 6,9 and 12 months,fibrosis was present in 28.4%,25.4%,22.4% receivingRT vs 58.4%,54.4%,52.4% receiving RT +N,there was significant difference between the two groups(P <0.05).TGF-β1,IL-1,IL-4,TNF were observed which showed that The RT +N were lower than RT.Conclusion N-NAC can reduce incidence rate of lung injury in radiotherapy,and can reduce the content and the release of TGF-β1,IL-1,IL-4,TNF.

Establishment of rat model of silicotuberculosis and its pathological characteristic.

OBJECTIVE: To establish different stages of silicosis rat model complicated with tuberculosis infection, and compare the pathological characteristics and analyze the impact of silicosis on tuberculosis infection. METHODS: SD rats were subjected to intratracheal administration of silica with non-exposure method at the 1st, 30th, or 60th day. At the 50th day, the rats were injected with the suspension of H37Rv (a virulent standard strain of Mycobacterium tuberculosis) via tail-vein. After 40 days post-infection, rats were sacrificed, the lung tissues were isolated, and paraffin was embedded and sectioned. The sections were treated using HE staining for structure observation, acid fast stain of Ziehl-Neelsen for bacterial detection, and Warthin-Starry silver staining for displaying the distribution of dust particles. The bacterial load was quantified by colony counting. RESULTS: Primary to tertiary silicosis could be discovered at the 30th, 60th, and 90th day of post-infection. The rats could be infected by injection of M. tuberculosis via tail vein, with tuberculosis load and the degree of lung tissue lesions positively correlated with silicosis. CONCLUSION: The rat model of silicotuberculosis was established successfully, which facilitated understanding the 'cross-talk' of silicosis and tuberculosis during the process they drive each other.