Nonadiabatic Field with Triangle Window Functions on Quantum Phase Space.

Recent progress on the constraint coordinate-momentum phase space (CPS) formulation of finite-state quantum systems has revealed that the triangle window function approach is an isomorphic representation of the exact population-population correlation function of the two-state system. We use the triangle window (TW) function and the CPS mapping kernel element to formulate a novel useful representation of discrete electronic degrees of freedom (DOFs). When it is employed with nonadiabatic field (NaF) dynamics, a new variant of the NaF approach (i.e., NaF-TW) is proposed. The NaF-TW expression of the population of any adiabatic state is always positive semidefinite. Extensive benchmark tests of model systems in both the condensed phase and gas phase demonstrate that the NaF-TW approach is able to faithfully capture the dynamical interplay between electronic and nuclear DOFs in a broad region, including where the states remain coupled all the time, as well as where the bifurcation characteristic of nuclear motion is important.

Risk assessment of malignancy in solitary pulmonary nodules in lung computed tomography: a multivariable predictive model study.

BACKGROUND: Computed tomography images are easy to misjudge because of their complexity, especially images of solitary pulmonary nodules, of which diagnosis as benign or malignant is extremely important in lung cancer treatment. Therefore, there is an urgent need for a more effective strategy in lung cancer diagnosis. In our study, we aimed to externally validate and revise the Mayo model, and a new model was established. METHODS: A total of 1450 patients from three centers with solitary pulmonary nodules who underwent surgery were included in the study and were divided into training, internal validation, and external validation sets (n = 849, 365, and 236, respectively). External verification and recalibration of the Mayo model and establishment of new logistic regression model were performed on the training set. Overall performance of each model was evaluated using area under receiver operating characteristic curve (AUC). Finally, the model validation was completed on the validation data set. RESULTS: The AUC of the Mayo model on the training set was 0.653 (95% confidence interval [CI]: 0.613-0.694). After re-estimation of the coefficients of all covariates included in the original Mayo model, the revised Mayo model achieved an AUC of 0.671 (95% CI: 0.635-0.706). We then developed a new model that achieved a higher AUC of 0.891 (95% CI: 0.865-0.917). It had an AUC of 0.888 (95% CI: 0.842-0.934) on the internal validation set, which was significantly higher than that of the revised Mayo model (AUC: 0.577, 95% CI: 0.509-0.646) and the Mayo model (AUC: 0.609, 95% CI, 0.544-0.675) (P < 0.001). The AUC of the new model was 0.876 (95% CI: 0.831-0.920) on the external verification set, which was higher than the corresponding value of the Mayo model (AUC: 0.705, 95% CI: 0.639-0.772) and revised Mayo model (AUC: 0.706, 95% CI: 0.640-0.772) (P < 0.001). Then the prediction model was presented as a nomogram, which is easier to generalize. CONCLUSIONS: After external verification and recalibration of the Mayo model, the results show that they are not suitable for the prediction of malignant pulmonary nodules in the Chinese population. Therefore, a new model was established by a backward stepwise process. The new model was constructed to rapidly discriminate benign from malignant pulmonary nodules, which could achieve accurate diagnosis of potential patients with lung cancer.

MCAM abnormal expression and clinical outcome associations are highly cancer dependent as revealed through pan-cancer analysis.

MCAM (CD146) is a cell surface adhesion molecule that has been reported to promote cancer development, progression and metastasis and is considered as a potential tumor biomarker and therapeutic target. However, inconsistent reports exist, and its clinical value is yet to be confirmed. Here we took advantage of several large genomic data collections (Genotype-Tissue Expression, The Cancer Genome Atlas and Cancer Cell Line Encyclopedia) and comprehensively analyzed MCAM expression in thousands of normal and cancer samples and cell lines along with their clinical phenotypes and drug response information. Our results show that MCAM is very highly expressed in large vessel tissues while majority of tissues have low or minimal expression. Its expression is dramatically increased in a few tumors but significantly decreased in most other tumors relative to their pairing normal tissues. Increased MCAM expression is associated with a higher tumor stage and worse patient survival for some less common tumors but not for major ones. Higher MCAM expression in primary tumors may be complicated by tumor-associated or normal stromal blood vessels yet its significance may differ from the one from cancer cells. MCAM expression is weakly associated with the response to a few small molecular drugs and the association with targeted anti-BRAF agents suggests its involvement in that pathway which warrants further investigation.

Apatinib Reverses Paclitaxel-resistant Lung Cancer Cells (A549) Through Blocking the Function of ABCB1 Transporter.

BACKGROUND/AIM: Multidrug resistance (MDR) is often associated with overexpression of P-glycoprotein (ABCB1) in cancer cells. Apatinib is a novel Vascular endothelial growth factor receptor-TKI (VEGFR-TKI) which inhibits the function of ABCB1 in certain cancers. This study aimed to investigate the effect of apatinib on the reversal of paclitaxel (PTX) resistance in A549 lung cancer cells (A549/PTX) and related mechanisms. MATERIALS AND METHODS: A549/PTX cells were treated with apatinib alone, PTX alone, or PTX and apatinib. Cell viability was measured by the CCK8 assay. Apoptosis rate, cell-cycle arrest, Rhodamine efflux and reactive oxygen species (ROS) generation were determined by flow cytometry. The intracellular paclitaxel concentration was measured by ultra performance liquid chromatography (UPLC). Protein levels were analyzed by western blotting. RESULTS: A549/PTX cells had significant resistance to PTX and higher expression of ABCB1 compared to A549 cells. Apatinib increased the cytotoxicity of PTX, enhanced PTX-induced apoptosis and cycle arrest, and triggered intracellular ROS generation in A549/PTX cells. In addition, apatinib treatment increased the concentration of intracellular PTX in A549/PTX cells. Apatinib-PTX combination inhibited AKT and ERK pathways. CONCLUSION: Apatinib reverses the drug resistance to PTX in A549 PTX-resistant cells through inhibiting the function of ABCB1 and resumes anti-cancer effects.

Apatinib preferentially inhibits PC9 gefitinib-resistant cancer cells by inducing cell cycle arrest and inhibiting VEGFR signaling pathway.

BACKGROUND: Lung cancer is one of the most common and deadly tumors around the world. Targeted therapy for patients with certain mutations, especially by use of tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR), has provided significant benefit to patients. However, gradually developed resistance to the therapy becomes a major challenge in clinical practice and an alternative to treat such patients is needed. Herein, we report that apatinib, a novel anti-angiogenic drug, effectively inhibits obtained gefitinib-resistant cancer cells but has no much effect on their parental sensitive cells. METHODS: Gefitinib-resistant lung cancer cell line (PC9GR) was established from its parental sensitive line (PC9) with a traditional EGFR mutation after long time exposure to gefitinib. Different concentrations of apatinib were used to treat PC9, PC9GR, and other two lung cancer cell lines for its anti-growth effects. RNA sequencing was performed on PC9, PC9GR, and both after apatinib treatment to detect differentially expressed genes and involved pathways. Protein expression of key cycle regulators p57, p27, CDK2, cyclin E2, and pRb was detected using Western blot. Xenograft mouse model was used to assess the anti-tumor activity of apatinib in vivo. RESULTS: The established PC9GR cells had over 250-fold increased resistance to gefitinib than its sensitive parental PC9 cells (IC50 5.311 ± 0.455 µM vs. 0.020 ± 0.003 µM). The PC9GR resistance cells obtained the well-known T790M mutation. Apatinib demonstrated much stronger ( ~ fivefold) growth inhibition on PC9GR cells than on PC9 and other two lung cancer cell lines, A549 and H460. This inhibition was mostly achieved through cell cycle arrest of PC9GR cells in G1 phase. RNA-seq revealed multiple changed pathways in PC9GR cells compared to the PC9 cells and after apatinib treatment the most changed pathways were cell cycle and DNA replication where most of gene activities were repressed. Consistently, protein expression of p57, CDK2, cyclin E2, and pRb was significantly impacted by apatinib in PC9GR cells. Oral intake of apatinib in mouse model significantly inhibited establishment and growth of PC9GR implanted tumors compared to PC9 established tumors. VEGFR2 phosphorylation in PC9GR tumors after apatinib treatment was significantly reduced along with micro-vessel formation. CONCLUSIONS: Apatinib demonstrated strong anti-proliferation and anti-growth effects on gefitinib resistant lung cancer cells but not its parental sensitive cells. The anti-tumor effect was mostly due to apatinib induced cell cycle arrest and VEGFR signaling pathway inhibition. These data suggested that apatinib may provide a benefit to patients with acquired resistance to EGFR-TKI treatment.