Pyropheophorbide‐α methyl ester (MPPa) was a promising photosensitizer with stable chemical structure, strong absorption, higher tissue selectivity and longer activation wavelengths. The present study investigated the effect of MPPa‐mediated photodynamic treatment on lung cancer A549 cells as well as the underlying mechanisms. Cell Counting Kit‐8 was employed for cell viability assessment. Reactive oxygen species levels were determined by fluorescence microscopy and flow cytometry. Cell morphology was evaluated by Hoechst staining and transmission electron microscopy. Mitochondrial membrane potential, cellular apoptosis and cell cycle distribution were evaluated flow‐cytometrically. The protein levels of apoptotic effectors were examined by Western blot. We found that the photocytotoxicity of MPPa showed both drug‐ and light‐ dose dependent characteristics in A549 cells. Additionally, MPPa‐PDT caused cell apoptosis by reducing mitochondrial membrane potential, increasing reactive oxygen species (ROS) production, inducing caspase‐9/caspase‐3 signaling activation as well as cell cycle arrest at G0/G1 phase. These results suggested that MPPa‐PDT mainly kills cells by apoptotic mechanisms, with overt curative effects, indicating that MPPa should be considered a potent photosensitizer for lung carcinoma treatment.
Lung adenocarcinoma (LUAD) remains the most common deadly disease and has a poor prognosis. More and more studies have reported that mitochondrial-related genes (MTRGs) were associated with the clinical outcomes of multiple tumors solely. In this study, we aimed to develop a novel prognostic model based on MTRGs. Differentially expressed MTRGs were identified from TCGA-LUAD and GSE31210 cohorts. Univariate Cox regression analysis was utilized to screen differentially expressed MTRGs that were related to prognosis of LUAD. Then, LASSO Cox regression analysis was used to develop a prognostic signature. ESTIMATE was used for estimating the fractions of immune cell types. In this study, we identified 44 overlapping differentially expressed MTRGs in TCGA-LUAD and GSE31210 cohorts. Among 44 overlapping differentially expressed MTRGs, nine genes were associated with prognosis of LUAD. When the penalty parameter lambda was the minimum, there were six genes meeting the conditions of constructing the signature, including SERPINB5, CCNB1, FGR MAOB, SH3BP5, and CYP24A1. The survival analysis suggested that prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. Cox regression analyses showed that the risk score was an independent predictor of LUAD prognosis. As with the results of ESTIMATE score, the degree of immune cell infiltration in the low-risk group was higher than that in the high-risk group, such as TIL, Treg, and B cells. In addition, TMB and cancer stem cell infiltration were higher in the low-risk group than the high-risk group. In conclusion, we developed a novel MTRG signature acting as a negative independent prognostic factor. In the future, individualized treatments and medical decision-making may benefit from using the predicted model.
The purpose was to develop a nomogram for the prediction of the 1-and 2-year overall survival (OS) rates in patients with brain metastatic non-small cell lung cancer (BMNSCLC).Patients were collected from the Surveillance Epidemiology and End Results program (SEER) and classified into the training and validation groups. Several independent prognostic factors identified by statistical methods were incorporated to establish a predictive nomogram. The concordance index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration curve were applied to estimate predictive ability of the nomogram. To compare the clinical practicability of the nomogram and TNM staging system by decision curve analysis (DCA).A total of 24,164 eligible patients were collected and assigned into the training (n = 16,916) and validation groups (n = 7248). Based on the prognostic factors, we developed a nomogram with good discriminative ability. The C-indices for training and validation group were 0.727 and 0.728. The AUCs of 1-and 2-year OS rates were both 0.8, and the calibration curves also demonstrated good performance of the nomogram. DCA illustrated that the nomogram provided clinical net benefit compared with the TNM staging system.We developed a predictive nomogram for more accurate and comprehensive prediction of OS in BMNSCLC patients, which can be a useful and convenient tool for clinicians to make proper clinical decisions, and adjust follow-up management strategies.Abbreviations: AUC = the area under the receiver operating characteristics curve, BMNSCLC = brain metastatic non-small cell lung cancer, C-index = concordance index, DCA = decision curve analysis, NSCLC = non-small cell lung cancer, OS = overall survival, SEER = Surveillance Epidemiology and End Results program.
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