IDO1 Modulates the Sensitivity of Epithelial Ovarian Cancer Cells to Cisplatin through ROS/p53-Dependent Apoptosis.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a heme-containing dioxygenase that may play a part in chemoresistance in ovarian cancer. However, its role in cisplatin (DDP) resistance is unclear. Here, the expression level of IDO1 in tumors in platinum-resistant (n = 22) and -sensitive (n = 46) ovarian cancer patients was determined, and then how IDO1 modulated DDP resistance was explored in vitro and in vivo. The IDO1 expression level in platinum-resistant patients was higher than that in -sensitive patients, and a higher IDO1 level was correlated with poor prognosis in type II cancer patients. Up-regulating IDO1 decreased DDP-induced apoptosis in SKOV3 cells via inhibiting the ROS/p53 cell-death pathway, thereby attenuating cytotoxicity of DDP. Silencing IDO1 enhanced p53-dependent apoptosis by increasing ROS accumulation, thereby enhancing DDP against SKOV3 cells. Down-knocking IDO1 augmented the action of DDP in vivo. These data demonstrated that silencing IDO1 enhanced the efficacy of DDP by intensifying p53-dependent apoptosis, and that targeting IDO1 can be a strategy to modulate DDP-based chemotherapy for epithelial ovarian cancer.

Microwave catalytic co-pyrolysis of chlorella vulgaris and oily sludge: Characteristics and bio-oil analysis.

Co-pyrolysis of Chlorella vulgaris (CV) and Oily sludge (OS) under different mixing ratios were investigated by microwave furnace. NiO, activated carbon (AC) and their 1:1 compound (N1A1) with different additions (5%, 10%, 15% and 20%) were selected as microwave additives to study the effects on optimum mixing ratio of co-pyrolysis. The results indicated that mixing ratio of CV/OS = 1:1 (C1O1) was optimum for co-pyrolysis. Besides, 10% AC was optimal on improving pyrolysis characteristics of the C1O1 group. The most significant synergistic interaction of NiO and AC occurred in the 10% N1A1 group. Moreover, hydrocarbons in bio-oil of the C1O1 group increased by 31.84% compared with theoretical values, while nitrogenous, oxygenated compounds decreased by 74.18% and 19.01%. Addition of 10% N1A1 in the C1O1 group increased aliphatic hydrocarbons by 22.44%, and decreased nitrogenous, oxygenated compounds by 41.79% and 36.58%. Overall, 10% N1A1 was conducive for the C1O1 group to obtain high-quality bio-oil.

Microwave catalytic co-pyrolysis of Chlorella vulgaris and high density polyethylene over activated carbon supported monometallic: Characteristics and bio-oil analysis.

Activated carbon (AC) has attracted much attention owing to its low cost and abundant sources. In this paper, three monometallic supported catalysts were prepared using AC as support (Ce/AC, Fe/AC, Ni/AC), and the effects of three catalysts on the microwave co-pyrolysis of Chlorella vulgaris (C. vulgaris) with high density polyethylene (HDPE) were studied. The results showed that the co-pyrolysis characteristics of C. vulgaris/HDPE = 1:1 (C1HP1) were significantly improved by three catalysts at high additions (>20 %). Among them, the C1HP1 group with 50 % Fe/AC addition had the shortest co-pyrolysis reaction time (2901 s). Besides, Ce/AC and Fe/AC have a promoting effect on bio-oil yields, while Ni/AC has an inhibiting effect. The maximum bio-oil yield (25.6 %) was obtained under 40 % addition of Fe/AC. Moreover, Ce/AC obtained the highest hydrocarbons content (66.68 %), while Fe/AC obtained the highest aromatic hydrocarbons content (36.64 %). Additionally, Ce/AC had the highest deoxygenation efficiency (47.33 %) and denitrification efficiency (42.28 %).

Construction and Validation of an Immune-Based Prognostic Model for Pancreatic Adenocarcinoma Based on Public Databases.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) is a highly lethal and aggressive tumor with poor prognoses. The predictive capability of immune-related genes (IRGs) in PAAD has yet to be explored. We aimed to explore prognostic-related immune genes and develop a prediction model for indicating prognosis in PAAD. METHODS: The messenger (m)RNA expression profiles acquired from public databases were comprehensively integrated and differentially expressed genes were identified. Univariate analysis was utilized to identify IRGs that related to overall survival. Whereafter, a multigene signature in the Cancer Genome Atlas cohort was established based on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Moreover, a transcription factors regulatory network was constructed to reveal potential molecular processes in PAAD. PAAD datasets downloaded from the Gene Expression Omnibus database were applied for the validations. Finally, correlation analysis between the prognostic model and immunocyte infiltration was investigated. RESULTS: Totally, 446 differentially expressed immune-related genes were screened in PAAD tissues and normal tissues, of which 43 IRGs were significantly related to the overall survival of PAAD patients. An immune-based prognostic model was developed, which contained eight IRGs. Univariate and multivariate Cox regression revealed that the risk score model was an independent prognostic indicator in PAAD (HR > 1, P < 0.001). Besides, the sensitivity of the model was evaluated by the receiver operating characteristic curve analysis. Finally, immunocyte infiltration analysis revealed that the eight-gene signature possibly played a pivotal role in the status of the PAAD immune microenvironment. CONCLUSION: A novel prognostic model based on immune genes may serve to characterize the immune microenvironment and provide a basis for PAAD immunotherapy.

Nomogram to Predict Preoperative Occult Peritoneal Metastasis of Gastrointestinal Stromal Tumors (GIST) Based on Imaging and Inflammatory Indexes.

BACKGROUND: Preoperative imaging examination is the primary method for diagnosing metastatic gastrointestinal stromal tumor (GIST), but it is associated with a high rate of missed diagnosis. Therefore, it is important to establish an accurate model for predicting occult peritoneal metastasis (PM) of GIST. PATIENTS AND METHODS: GIST patients seen between April 2002 and December 2018 were selected from an institutional database. Using multivariate logistic regression analyses, we created a nomogram to predict occult PM of GIST and validated it with an independent cohort from the same center. The concordance index (C-index), decision curve analysis (DCA) and a clinical impact curve (CIC) were used to evaluate its predictive ability. RESULTS: A total of 522 eligible GIST patients were enrolled in this study and divided into training (n=350) and validation cohorts (n=172). Factors associated with occult PM were included in the model: tumor size (odds ratio [OR] 1.194 95% confidence interval [CI], 1.034-1.378; p=0.016), primary location (OR 7.365 95% CI, 2.192-24.746; p=0.001), tumor capsule (OR 4.282 95% CI, 1.209-15.166; p=0.024), Alb (OR 0.813 95% CI, 0.693-0.954; p=0.011) and FIB (OR 2.322 95% CI, 1.410-3.823; p=0.001). The C-index was 0.951 (95% CI, 0.917-0.985) in the training cohort and 0.946 (95% CI, 0.900-0.992) in the validation cohort. In the training cohort, the prediction model had a sensitivity of 82.8%, a specificity of 93.8%, a positive predictive value of 54.7%, and a negative predictive value of 98.4%; the validation cohort values were 94.7%, 85.0%, 43.9% and 99.2%, respectively. DCA and CIC results showed that the nomogram had clinical value in predicting occult PM in GIST patients. CONCLUSION: Imaging and inflammatory indexes are significantly associated with microscopic metastases of GIST. A nomogram including these factors would have an excellent ability to predict occult PM.