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Doses and LD50 values determinations for SAHA and Cisplatin in U2OS reporter cells

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Conventional chemotherapy plays a key role in hepatocellular carcinoma (HCC) treatment, however, with intrinsic or acquired chemoresistance being a major constraint. Here, we aimed to identify potential target to reverse such chemoresistance. In the present study, we found significant difference in uridine monophosphate synthetase (UMPS) expression between 5-FU resistant and sensitive HCC cell lines and the overexpression or downregulation of UMPS impacted 5-FU response in HCC cells. We further found that inhibition of UMPS activity with uric acid at concentration present in human plasma decreased the 5-FU sensitivity of HCC cells, while reduction of uric acid levels with uricase improved the 5-FU sensitivity of HCC cells as well as colorectal cancer cells. In vivo studies also suggested that modulation of uric acid levels did affect 5-FU sensitivity of tumors. These data indicated that UMPS was correlated with the 5-FU resistance in HCC cells and uricase sensitized cancer cells to 5-FU through uricase-uric acid-UMP synthase axis, which provided a potential strategy to improve the efficacy of 5-FU-based chemotherapy for human cancers.

Background. 5-Fluorouracil (5-FU) has been widely applied in treating cancers. However, its usage is largely limited in hepatocellular carcinoma (HCC), due to acquired resistance. Here, we aim to identify target proteins and investigate their roles in 5-FU sensitivity of HCC cells. Methods. Mass spectrometry (MS) proteomics was performed on 5-FU-resistant cell line (BEL7402/5-FU) and its parental cell line (BEL7402) with 5-FU treatment. In order to identify potential targets, we compared the proteomics between two cell line groups and used bioinformatics tools to select hub proteins from all differentially expressed proteins. Results. We finally focused on a group of cell cycle-related kinases (CDKs). By CCK8 assay, we confirmed that the CDK inhibitor significantly decreased the IC50 of 5-FU-resistant cells. Conclusions. Our study verified that CDK inhibition can reverse 5-FU resistance of HCC cells.

Inducing protein degradation by proteolysis-targeting chimeras (PROTACs) has gained tremendous momentum in the field for its promise in the discovery and development of new therapies. Based on our previously reported PROTAC BCR-ABL degraders, we designed and synthesized additional 4 PROTAC compounds with a novel linker that contains pyrimidine rings. Molecular and cellular studies have shown that different linkers affect the degradation activity of small-molecule degraders on the target protein of BCR-ABL. We screened out a lead compound, DMP11, with stable physicochemical properties and high activity. Preliminary evaluation of its pharmacodynamics in vitro model showed that it has a good inhibitory effect on imatinib-resistant chronic myeloid leukemia cell lines, as has been shown in animal models. Our preliminary research into the mechanism of DMP11 found that DMP11 can overcome drug resistance by simultaneously inhibiting the targets of BCR-ABL and SRC-family kinase (SFK).

Background: The bromodomain and extra-terminal proteins (BET), in particular BRD4, has recently emerged as a potential therapeutic target for the treatment of many human disorders such as cancer, inflammation, obesity and cardiovascular disease, which draw more and more attention to discover potent BRD4 inhibitors in the past years. In this article, we described the discovery process of an entirely new chemotype of BRD4 inhibitors. Methods: A fragment-based drug discovery strategy was employed in attempting to find a novel chemotype of BRD4 inhibitors. Thus, the potential hits were firstly identified by docking study with KAc binding pocket and AlphaScreen assay. Then the elected hit was further structurally optimized based on the interaction revealed by the docking study and the Structure-Activity Relationship (SAR). Results: A 1-(2-hydroxyphenyl)ethan-1-one fragment was first identified as an efficient hit to BRD4 with a weak inhibition activity and high ligand efficiency (IC50 = 8.9 μM, LE > 0.5) based on virtual screening and biochemical assay. Then, two-rounds optimization of the hit by a fragmentbased drug discovery approach enabled the discovery of a potent BRD4 inhibitor 9, which exhibit nanomolar potency in biochemical assays (IC50 = 0.18 μM). Conclusion: The title compounds displayed potent inhibitory activity to BRD4, implying acetophenone core is an effective KAc residue mimic, suggesting acetophenone derivatives as a new chemotype may be promising for developing novel BRD4 inhibitors.

Robot intelligence includes motion intelligence and cognitive intelligence. Aiming at the motion intelligence, a hierarchical reinforcement learning architecture considering stochastic wind disturbance is proposed for the decision-making of the power line maintenance robot with autonomous operation. This architecture uses the prior information of the mechanism knowledge and empirical data to improve the safety and efficiency of the robot operation. In this architecture, the high-level policy selection and the low-level motion control at global and local levels are considered comprehensively under the condition of stochastic wind disturbance. Firstly, the operation task is decomposed into three sub-policies: global obstacle avoidance, local approach and local tightening, and each sub-policy is learned. Then, a master policy is learned to select the operation sub-policy in the current state. The dual deep Q network algorithm is used for the master policy, while the deep deterministic policy gradient algorithm is used for the operation policy. In order to improve the training efficiency, the global obstacle avoidance sub-policy takes the random forest composed of dynamic environmental decision tree as the expert algorithm for imitation learning. The architecture is applied to a power line maintenance scenario, the state function and reward function of each policy are designed, and all policies are trained in an asynchronous and parallel computing environment. It is proved that this architecture can realize stable and safe autonomous operating decision for the power line maintenance robot subjected to stochastic wind disturbance.

The anomaly detection for communication networks is significant for improve the quality of communication services and network reliability. However, traditional communication monitoring methods lack proactive monitoring and real-time alerts and the prediction effect of a single machine learning model on communication data containing multiple features is not ideal. To solve the problem, A prediction-then-detection anomaly detection method was proposed, and quantitative assessment of network anomalies was developed. Specifically, anomaly-free data was obtained by eliminating outliers, and the long short-term memory (LSTM) and autoregressive integral moving average (ARIMA) were combined via residual weighting to predict the future state of the key performance indicators (KPI) without outliers. Anomalies were identified using the error comparison between the prediction and actual values, and the network condition was quantified using the scoring method. It is observed that the proposed LSTM-ARIMA hybrid model has better prediction effect, which can well represent the performance of KPIs of the future state, and the prediction-then-detection anomaly detection method has excellent performance on both precision and recall.

To characterize the structure of purified raspberry pectin and discuss the impact of different extraction methods on the pectin structure, raspberry pectin was extracted by hot-acid and enzyme method and purified by stepwise ethanol precipitation and ion-exchange chromatography isolation. Enzyme-extracted raspberry pectin (RPE50%-3) presented relatively intact structure with molecular weight of 5 × 10

Accurate and efficient prediction of mobile network traffic in a public setting with changing flow of people can not only ensure a stable network but also help operators make resource scheduling decisions before reasonably allocating resources. Therefore, this paper proposes a method based on kernel extreme learning machine (kELM) for traffic data prediction. Particle swarm optimization (PSO), multiverse optimizer (MVO), and moth&ndash, flame optimization (MFO) were adopted to optimize kELM parameters for finding the best solution. To verify the predictive performance of the kernel ELM model, backpropagation (BP) neural network, v-support vector regression (vSVR), and ELM were also applied to traffic prediction, and the results were compared with kELM. Experimental results showed that the smallest mean absolute percentage error in the test (11.150%) was achieved when kELM was optimized by MFO with Gaussian as the kernel function, that is, the prediction result of MFO-kELM was the best. This study can provide significant guidance for network stability and resource conservation.

Proteolysis targeting chimera (PROTAC), hijacking protein of interest (POI) and recruiting E3 ligase for target degradation via the ubiquitin-proteasome pathway, is a novel drug discovery paradigm which has been widely used as biological tools and medicinal molecules with the potential of clinical application value. Currently, ARV-110, an orally small molecule PROTAC was designed to specifically target Androgen receptor (AR), firstly enters clinical phase I trials for the treatment of metastatic castration-resistant prostate cancer, which turns a new avenue for the development of PROTAC. We herein provide a detail summary on the latest one year progress of PROTAC target various proteins and elucidate the advantages of PROTAC technology. Finally, the potential challenges of this vibrant field are also discussed.

Epidermal growth factor receptor (EGFR) is one of the important and valuable drug targets. Overexpression of EGFR is associated with the development of many types of cancer. In this study, three PROTACs small molecules (16a–16c) were designed, synthesized and evaluated for their cytotoxicity against the growth in different NSCLC cell line and the degradation effect. The bioassay results indicated that 16c has a good inhibition in PC9 cells and H1975 cells, and the corresponding IC50 value was 0.413 μM and 0.657 μM, respectively. Western blotting results demonstrated that compound 16c could serve as an effective EGFRdel19-targeting degrader in PC9 cells.

Accurate base station traffic data in a public place with large changes in the amount of people could help predict the occurrence of network congestion, which would allow us to effectively allocate network resources. This is of great significance for festival network support, routine maintenance, and resource scheduling. However, there are a few related reports on base station traffic prediction, especially base station traffic prediction in public scenes with fluctuations in people flow. This study proposes a public scene traffic data prediction method, which is based on a v Support Vector Regression (vSVR) algorithm. To achieve optimal prediction of traffic, a symbiotic organisms search (SOS) was adopted to optimize the vSVR parameters. Meanwhile, the optimal input time step was determined through a large number of experiments. Experimental data was obtained at the base station of Huainan Wanda Plaza, in the Anhui province of China, for three months, with the granularity being one hour. To verify the predictive performance of vSVR, the classic regression algorithm extreme learning machine (ELM) and variational Bayesian Linear Regression (vBLR) were used. Their optimal prediction results were compared with vSVR predictions. Experimental results show that the prediction results from SOS-vSVR were the best. Outcomes of this study could provide guidance for preventing network congestion and improving the user experience.

Purpose: To investigate the role of miRNAs in regulating oxidative damage during cataract formation.Methods: Microarray analysis and gene expression profiling assay were used to separately evaluate the miRNAs and mRNAs profiles in normal human lens epithelium cell line HLE-B3 treated by H2O2. The expression level of miR-630 was detected by RT-qPCR and the gene expression profiles were performed with gene ontology analysis using Bio Informatical database. The targets of miR-630 were predicted using miRecords and the results were used for screening targets of miR-630 combined with the GO analysis above. The mRNA levels of ALCAM, PCDH7, COL12A2, and EDIL3 in HLE-B3 cells after oxidative stimulation or miR-630 mimics transfection were measured by RT-qPCR, and the expression of ALCAM regulated by miR-630 was confirmed by Western blot and dual-luciferase reporter gene assay. The level of cell migration was measured by transwell assay and scratching test after transfection of miR-630 mimics and ALCAM siRNAs.Results: The microarray analysis demonstrated that miR-630 was significantly increased in HLE-B3 cells after oxidative stimulation. ALCAM, PCDH7, COL12A2, and EDIL3 were screened to be the possible targets of miR-630 by miRecords combined with GO analysis, but the results of RT-qPCR, Western blot and dual-luciferase reporter gene assay showed that only the expression of ALCAM was repressed by miR-630 transfection. Cell migration was inhibited through transfection of miR-630 mimics or ALCAM siRNAs and the upregulation of miR-630 partly reduced the cell migration increased by oxidative stimulation.Conclusion: miR-630 is one of the miRNAs increased by oxidative stimulation in human lens epithelium cells. Its upregulation may inhibit cell migration by targeting on ALCAM, which is important for HLECs to resist behavioral changes induced by oxidative damage and may delay the progression of cataract.

Accurate base station traffic data in a public place with large changes in the amount of people could help predict the occurrence of network congestion, which would allow us to effectively allocate network resources. This is of great significance for festival network support, routine maintenance, and resource scheduling. However, there are a few related reports on base station traffic prediction, especially base station traffic prediction in public scenes with fluctuations in people flow. This study proposes a public scene traffic data prediction method, which is based on a v Support Vector Regression (vSVR) algorithm. To achieve optimal prediction of traffic, a symbiotic organisms search (SOS) was adopted to optimize the vSVR parameters. Meanwhile, the optimal input time step was determined through a large number of experiments. Experimental data was obtained at the base station of Huainan Wanda Plaza, in the Anhui province of China, for three months, with the granularity being one hour. To verify the predictive performance of vSVR, the classic regression algorithm extreme learning machine (ELM) and variational Bayesian Linear Regression (vBLR) were used. Their optimal prediction results were compared with vSVR predictions. Experimental results show that the prediction results from SOS-vSVR were the best. Outcomes of this study could provide guidance for preventing network congestion and improving the user experience.

Rhamnogalacturonan I (RG-I) pectin are regarded as strong galectin-3 (Gal-3) antagonist because of galactan sidechains. The present study focused on discussing the effects of more structural regions in pectin on the anti-Gal-3 activity. The water-soluble pectin (WSP) recovered from citrus canning processing water was categorized as RG-I pectin. The controlled enzymatic hydrolysis was employed to sequentially remove the α-1,5-arabinan, homogalaturonan and β-1,4-galactan in WSP. The Gal-3-binding affinity KD (kd/ka) of WSP and debranched pectins were calculated to be 0.32 μM, 0.48 μM, 0.56 μM and 1.93 μM. Moreover, based on the more sensitive cell line (MCF-7) model, the IC30 value of WSP was lower than these of modified pectins, indicating decreased anti-Gal-3 activity. Our results suggested that the total amount of neutral sugar sidechains, the length of arabinan and cooperation between HG and RG-I played important roles in the anti-Gal-3 activity of WSP, not the Gal/Ara ratio or RG-I/HG ratio. These results provided a new insight into structure-activity relationship of citrus segment membrane RG-I as a galectin-3 antagonist and a new functional food.

Pectic oligosaccharides are viewed as excellent immunomodulator, but the specific molecular weight (Mw) range required for anti-inflammatory effects remains unclear. In this study, citrus pectins was depolymerized by the ultrasound/H2O2/Vc system and the pectic mixtures was separated through the superdex 30 chromatography column. Three highly purified pectin fractions (USP1, USP2, USP3) were obtained, with the Mw of 2713 g/mol, 3683 g/mol, and 7469 g/mol. All of them were RG-I pectins and USP3 contained more arabinan sidechains than USP1 and USP2. In vitro anti-inflammation assays based on LPS-induced RAW264.7 macrophages indicated that these pectins could suppress the NO release, ROS production and down-regulated the level of pro-inflammatory cytokines IL-1β, IL-6 and TNF-α in a Mw-dependent manner. The inhibitory effects increased in the order of USP1 3KD should be effective as a prophylactic agent against inflammatory diseases in functional food.

The E26 transformation sequence-related gene ERG encodes a transcription factor involved in normal hematopoiesis, and its expression is abnormal in leukemia. Especially in a type of acute lymphoblastic leukemia (ALL) that is refractory and easy to relapse, the expression of ERG protein is abnormally increased. Chemotherapy can alleviate the condition of ALL, but the location and survival mechanism of the remaining ALL cells after chemotherapy are still not fully understood. It is becoming increasingly clear that the interaction between leukemia cells and their microenvironment plays an important role in the acquisition of drug resistance mutations and disease recurrence. We selected an acute lymphocytic leukemia cell line with high ERG expression, and studied the synergistic effect of chemotherapeutics and small molecule peptides through cell proliferation, apoptosis, and cell cycle experiments; At the same time, we inoculated acute lymphocytic leukemia cells with high ERG expression into mice with severe immunodeficiency to simulate human ALL and investigated (i) the effects of co-administration on the nesting and invasion of leukemia cells and (ii) the effects of the small molecule peptide drug EIP, which targets ERG, on the sensitivity of ALL chemotherapy and the underlying mechanisms.Ara-c and EIP synergistically reduces viability of ALL cells with high ERG expression may be achieved by promoting their apoptosis and inhibiting their nesting.

Human WBSCR22 gene is involved in tumor metastasis, cell growth and invasion, however, its role in chemosensitivity to antitumor agents remains unknown. In this study, we analyzed the TCGA cohort and found the expression of WBSCR22 was significantly elevated in human colorectal cancer (CRC) tissue. WBSCR22 could be served as an independent risk predictor for overall survival (OS), and up-regulated WBSCR22 could predict unfavorable OS for CRC patients. Knockdown of WBSCR22 significantly sensitized CRC cells to oxaliplatin in vitro and in vivo, while overexpression of WBSCR22 led to cellular resistance to oxaliplatin treatment. Although WBSCR22 knockdown did not change cell cycle, it increased the oxaliplatin-induced cellular apoptosis. WBSCR22 knockdown augmented the oxaliplatin-induced intracellular reactive oxygen species (ROS) production and ROS-induced 8-oxoguanine (8-oxoG) oxidative lesion accumulation, likely sensitizing oxaliplatin treatment. These results demonstrate that WBSCR22 is involved in CRC resistance to oxaliplatin, suggesting WBSCR22 may represent a novel oxaliplatin resistance biomarker as well as a potentail target for CRC therapeutics.

Notch1 is a type-1 transmembrane receptor which has been demonstrated to be involved in proliferation in various organisms. A number of studies have proposed that Notch signaling may be aberrantly activated, thus contributing to development, invasion and metastasis in a variety of human cancers. In the present study, the function and mechanism of Notch1 in human prostate cancer (PCa) LNCaP cells in vitro was investigated. Notch1 and cleaved-Notch1 expression were evaluated in human PCa cell lines, including LNCaP, PC-3 and DU 145, and the human prostate epithelial RWPE-1 cell line. LNCaP cells were transfected with Notch1-targeting short hairpin RNAs (shRNAs) and the level of proliferation, the ability to invade and the expression of genes associated with cancer cell invasion were subsequently investigated. Notch1 was highly expressed in LNCaP, PC-3 and DU 145 cells compared with RWPE-1 cells, while cleaved-Notch1 was expressed in LNCaP, PC-3 and DU 145 cells, and only to a minimal extent in RWPE-1 cells. Knockdown of Notch1 by shRNA in LNCaP cells markedly decreased cell invasion through Matrigel and inhibited cell proliferation 48 h following transfection. Reverse transcription-quantitative polymerase chain reaction analysis indicated that Notch1-knockdown resulted in a significant reduction of metastasis-associated 1 (MTA1) and increase of KiSS-1 metastasis-suppressor (KISS-1), mitogen-activated protein kinase 4 (MKK4) and cluster of differentiation 82 (KAI1). The present data demonstrated that expression of Notch1 was significantly associated with the invasion of prostate cancer. Knockdown of Notch1 decreased the invasive ability of LNCaP cells, which may be caused by downregulating MTA1 and upregulating KISS-1, MKK4 and KAI1. These findings indicated that targeting Notch1 may provide a novel method of suppressing or treating metastasis in prostate cancer.

Background: The E-26 transformation-specific related gene (ERG) is frequently expressed in cytogenetically normal acute myeloid leukemia (CN-AML). Herein, we performed a meta-analysis to investigate the relationship between the prognostic significance of ERG expression and CN-AML. Methods: A systematic review of PubMed database and other search engines were used to identify the studies between January 2005 and November 2016. A total of 667 CN-AML patients were collected from seven published studies. Of the 667 patients underwent intensive chemotherapy, 429 had low expression of ERG and 238 had high expression of ERG. Summary odds ratio (OR) and the 95% confidence interval (CI) for the ERG expression and CN-AML were calculated using fixed- or random-effects models. Heterogeneity was assessed using Chi-squared-based Q-statistic test and I2 statistics. All statistical analyses were performed using R.3.3.1 software packages (R Foundation for Statistical Computing, Vienna, Austria) and RevMan5.3 (Cochrane Collaboration, Copenhagen, Denmark). Results: Overall, patients with high ERG expression had a worse relapse (OR = 2.5127, 95% CI: 1.5177–4.1601, P = 0.0003) and lower complete remission (OR = 0.3495, 95% CI: 0.2418–0.5051, P < 0.0001). With regard to the known molecular markers, both internal tandem duplications of the fms-related tyrosine kinase 3 gene (OR = 3.8634, 95% CI: 1.8285–8.1626, P = 0.004) and brain and acute leukemia, cytoplasmic (OR = 3.1538, 95% CI: 2.0537–4.8432, P < 0.0001) were associated with the ERG expression. In addition, the results showed a statistical significance between French-American-British (FAB) classification subtype (minimally differentiated AML and AML without maturation, OR = 4.7902, 95% CI: 2.7772–8.2624, P < 0.0001; acute monocytic leukemia, OR = 0.2324, 95% CI: 0.0899–0.6006, P = 0.0026) and ERG expression. Conclusion: High ERG expression might be used as a strong adverse prognostic factor in CN-AML. Key words: Leukemia, Myeloid, Acute; Meta-analysis; Prognosis; Recurrence

Alzheimer's disease (AD) is a chronic, fatal and complex neurodegenerative disorder, which is characterized by cholinergic system dysregulation, metal dyshomeostasis, amyloid-β (Aβ) aggregation, etc. Therefore in most cases, single-target or single-functional agents are insufficient to achieve the desirable effect against AD. Multi-Target-Directed Ligand (MTDL), which is rationally designed to simultaneously hit multiple targets to improve the pharmacological profiles, has been developed as a promising approach for drug discovery against AD. To identify the multifunctional agents for AD, we developed an innovative method to successfully conceal the metal chelator into acetylcholinesterase (AChE) inhibitor. Briefly, the “hidden” agents first cross the Blood Brain Barrier (BBB) to inhibit the function of AChE, and the metal chelator will then be released via the enzymatic hydrolysis by AChE. Therefore, the AChE inhibitor, in this case, is not only a single-target agent against AD, but also a carrier of the metal chelator. In this study a total of 14 quinoline derivatives were synthesized and biologically evaluated. Both in vitro and in vivo results demonstrated that compound 9b could cross the BBB efficiently, then release 8a, the metabolite of 9b, into brain. In vitro, 9b had a potent AChE inhibitory activity, while 8a displayed a significant metal ion chelating function, therefore in combination, both 9b and 8a exhibited a considerable inhibition of Aβ aggregation, one of the observations that plays important roles in the pathogenesis of AD. The efficacy of 9b against AD was further investigated in both a zebrafish model and two different mice models.

Currently, there is no available biomarker for lung cancer diagnosis. Here we recruited 844 lung cancer patients and 620 healthy participants from six hospitals. A total of four serum proteins was identified and subsequently assessed in the training and validation cohorts. The concentrations of four serum proteins were found to be significantly higher in lung cancer patients compared with healthy participants. The area under the curve (AUC) for the 4-biomarker were 0.86 in the training cohort, and 0.87 in the validation cohort. The classification improved to a corrected AUC of 0.90 and 0.89 respectively following addition of sex, age and smoking status. Similar results were observed for early-stage lung cancer. Remarkably, in a blinded test with a suspicious pulmonary nodule, the adjusted prediction model correctly discriminated the patients with 86.96% sensitivity and 98.25% specificity. These results demonstrated the 4-biomarker panel improved lung cancer prediction beyond that of known risk factors. Moreover, the biomarkers were valuable in differentiating benign nodules which will remain indolent from those that are likely to progress and therefore might serve as an adjuvant diagnosis tool for LDCT scanning., Highlights • A multicentric, case–control study was conducted to identify serum proteins for diagnosing lung cancer. • A 4-marker panel improved lung cancer prediction beyond that of known risk factors. • The biomarkers can detect lung cancer especially stage I–II from healthy controls or benign nodule patients. Currently, low dose chest computed tomography (LDCT) leads to a high false-positive result. Here we identified a panel of four serum proteins, which provides the potential for accurate diagnosis of lung cancer in a multicentric study. More importantly, the biomarkers allowed accurate detection of lung cancer cases especially stage I-II cases from normal and benign nodule subjects. These results suggest that the 4-protein panel might be a useful biomarker for diagnosing lung cancer patients and help discriminate early stage patients, which may serve as an adjuvant diagnosis tool for LDCT scanning in the future.

Lung cancer is a leading cause of cancer-related mortality worldwide, and concurrent chemoradiotherapy has been explored as a therapeutic option. However, the chemotherapeutic agents cannot be administered for most patients at full doses safely with radical doses of thoracic radiation, and further optimizations of the chemotherapy regimen to be given with radiation are needed. In this study, we examined the effects of suberoylanilide hydroxamic acid (SAHA) and cisplatin on DNA damage repairs, and determined the combination effects of SAHA and cisplatin on human non–small cell lung cancer (NSCLC) cells in response to treatment of ionizing radiation (IR), and on tumor growth of lung cancer H460 xenografts receiving radiotherapy. We also investigated the potential differentiation effect of SAHA and its consequences on cancer cell invasion. Our results showed that SAHA and cisplatin compromise distinct DNA damage repair pathways, and treatment with SAHA enhanced synergistic radiosensitization effects of cisplatin in established NSCLC cell lines in a p53-independent manner, and decreased the DNA damage repair capability in cisplatin-treated primary NSCLC tumor tissues in response to IR. SAHA combined with cisplatin also significantly increased inhibitory effect of radiotherapy on tumor growth in the mouse xenograft model. In addition, SAHA can induce differentiation in stem cell–like cancer cell population, reduce tumorigenicity, and decrease invasiveness of human lung cancer cells. In conclusion, our data suggest a potential clinical impact for SAHA as a radiosensitizer and as a part of a chemoradiotherapy regimen for NSCLC. Mol Cancer Ther; 15(5); 842–53. ©2016 AACR.