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This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compressed image, and Track 2 targets the super-resolution of compressed video. In Track 1, we use the popular dataset DIV2K as the training, validation and test sets. In Track 2, we propose the LDV 3.0 dataset, which contains 365 videos, including the LDV 2.0 dataset (335 videos) and 30 additional videos. In this challenge, there are 12 teams and 2 teams that submitted the final results to Track 1 and Track 2, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution on compressed image and video. The proposed LDV 3.0 dataset is available at https://github.com/RenYang-home/LDV_dataset. The homepage of this challenge is at https://github.com/RenYang-home/AIM22_CompressSR.

With the availability of the location information of drivers and passengers, ride-sourcing platforms can now provide increasingly efficient online matching compared with physical searching and meeting performed in the traditional taxi market. The matching time interval (the time interval over which waiting passengers and idle drivers are accumulated and then subjected to peer-to-peer matching) and matching radius (or maximum allowable pick-up distance, within which waiting passengers and idle drivers can be matched or paired) are two key control variables that a platform can employ to optimize system performance in an online matching system. By appropriately extending the matching time interval, the platform can accumulate large numbers of waiting (or unserved) passengers and idle drivers and thus match the two pools with a reduced expected pick-up distance. However, if the matching time interval is excessively long, certain passengers may become impatient and even abandon their requests. Meanwhile, a short matching radius can reduce the expected pick-up distance but may decrease the matching rate as well. Therefore, the matching time interval and matching radius should be optimized to enhance system efficiency in terms of passenger waiting time, vehicle utilization, and matching rate. This study proposes a model that delineates the online matching process in ride-sourcing markets. The model is then used to examine the impact of the matching time interval and matching radius on system performance and to jointly optimize the two variables under different levels of supply and demand. Numerical experiments are conducted to demonstrate how the proposed modeling and optimization approaches can improve the real-time matching of ride-sourcing platforms.

This paper presents a method to assess the safety of uncontrolled intersections considering two major properties of traffic conflicts-conflict probability and severity. This method assesses both the safety level of the entire intersection in addition to the distribution of safety within it. Intersections are modeled by a two-dimensional Cartesian coordinate system and the internal space of intersections is divided into cells. First, the vehicle movement characteristics of an uncontrolled intersection are modeled. Second, the conflict probability of each cell within the intersection is estimated considering the approaching probability and lateral migration probability of vehicles. The quantification of conflict severity is based on kinetic energy loss of potential crashes. Cluster analysis is used to combine conflict probability and severity to model the safety assessment of each cell. Third, the application of the method is discussed, and an overall safety index of intersections is proposed which considers weighted safety level and relative value of areas of different safety levels. Finally, a case study, which includes three different designs, is presented along with safety heatmaps to demonstrate the results. The results not only demonstrate the validity of the model, but also indicate that the proposed method can be applied to: i) safety evaluation of build-up intersections; ii) dangerous position management within an intersection; iii) safety assessment of designed intersections, and iv) safety level comparison among different intersections or various designs for a single intersection. Using this method, engineers and planners can better evaluate and improve the safety of existing or future uncontrolled intersections.

As demands for convenient and comfortable mobility grow, transportation network companies (TNCs) begin to diversify the ride-hailing services they offer. Modes that are offered now include ride-pooling (RP), non-ride-pooling (NP), and a third “bundled” option, which combines RP and NP. This emerging bundled option allows riders to be served via either RP or NP mode, whichever becomes available first. This paper examines the added complexity that a ride-hailing service platform faces when it introduces a third bundled option. Incorporating the predicted pooling information in the near future, a ride-matching problem is dedicated to matching vehicles with riders under various scenarios over a number of matching iterations. We formulate the multi-period ride-matching problem using an integer linear programming model with multiple objectives and to make dispatching decisions based on certain matching criteria. The complexity of the problem requires resolution via a two-stage Kuhn-Munkres (2-KM) algorithm, whose robustness is verified by computational tests. Some interesting insights are obtained: (1) how the bundled option impacts system performance metrics depends on whether the supply is sufficient or not; (2) there is an optimal value of the criterion of the maximum pickup time that maximizes the ride-pooling time savings.

The recognition of manga (Japanese comics) characters is an essential step in industrial applications, such as manga character retrieval, content analysis and copyright protection. However, conventional methods for manga character recognition are mainly based on handcrafted features which are not robust enough for manga of various style. The emergence of deep learning based methods provides representational features, which has a huge demand for labeled data. In this paper, we propose a framework to exploit unlabeled manga data to facilitate the discriminative capability of deep feature representations for manga character recognition (i.e., unsupervised learning on manga images), which does not rely on any manual annotation. Specifically, we first train an initial feature model using an anime character dataset. Then, we adopt a Progressive Main Characters Mining (PMCM) strategy which iterates between two steps: 1) produce selected data with estimated labels from unlabeled data, 2) update the feature model by the selected data. These two steps are mutually promoted in essence. Experimental results on Manga109 dataset, to which we introduce new head annotations, demonstrate the effectiveness of the proposed framework and the usefulness in manga character verification and retrieval.

With the availability of location information on drivers and passengers, ride-sourcing platforms are now able to provide more efficient online matching than the physical searching and meeting in traditional taxi market. The matching time interval (a time interval over which waiting passengers and idle drivers are accumulated and then peer-to-peer matching is executed) and matching radius (or maximum allowable pickup distance, within which matching or pairing between waiting passengers and idle drivers can be done) are two key control variables that the platform can employ to optimize the system performance in an online matching system. By appropriately extending matching time interval, the platform can accumulate more waiting (or unserved) passengers and idle drivers and thus match the two pools with shorter expected pickup distance. However, if the matching time interval is excessively long, some passengers may become impatient, and may even cancel their requests. Meanwhile, a short matching radius can reduce expected pickup distance but may decrease the matching rate as well. Therefore, it is important to optimize the matching time interval and matching radius to enhance system efficiency in terms of passenger waiting time, vehicle utilization and matching rate. This paper proposes a model to delineate the online matching process in a ride-sourcing market. The model is then used to examine the impact of the matching time interval and matching radius on system performance and to jointly optimize the two variables under different levels of supply and demand. Numerical experiments are conducted to demonstrate how the proposed modelling and optimization approaches can improve real-time matching processes of ride-sourcing platforms.

With the rapid development of mobile-internet technologies, on-demand ride-sourcing services have become increasingly popular and largely reshaped the way people travel. Demand prediction is one of the most fundamental components in supply-demand management systems of ride-sourcing platforms. With an accurate short-term prediction for origin-destination (OD) demand, the platforms make precise and timely decisions on real-time matching, idle vehicle reallocations, and ride-sharing vehicle routing, etc. Compared to the zone-based demand prediction that has been examined in many previous studies, OD-based demand prediction is more challenging. This is mainly due to the complicated spatial and temporal dependencies among the demand of different OD pairs. To overcome this challenge, we propose the Spatio-Temporal Encoder-Decoder Residual Multi-Graph Convolutional network (ST-ED-RMGC), a novel deep learning model for predicting ride-sourcing demand of various OD pairs. Firstly, the model constructs OD graphs, which utilize adjacent matrices to characterize the non-Euclidean pair-wise geographical and semantic correlations among different OD pairs. Secondly, based on the constructed graphs, a residual multi-graph convolutional (RMGC) network is designed to encode the contextual-aware spatial dependencies, and a long-short term memory (LSTM) network is used to encode the temporal dependencies, into a dense vector space. Finally, we reuse the RMGC networks to decode the compressed vector back to OD graphs and predict the future OD demand. Through extensive experiments on the for-hire-vehicles datasets in Manhattan, New York City, we show that our proposed deep learning framework outperforms the state-of-arts by a significant margin.

Developing electric ride-hailing vehicles (ERVs) is an integral part of promoting green transportation. To understand how ERVs operate, and in turn to improve their battery systems, we have developed a comprehensive, methodological framework to construct their utilization patterns and driving cycles. The methodology is based on a multi-state model (MSM). It builds one-day activity patterns of electric vehicles that belong in an ERV fleet. The driving patterns outline when (time of occurrence), for how long (duration), and under what battery conditions (state of charge) a driver typically decides to either operate or charge a vehicle. Two driving patterns, pointing toward two typical types of drivers, have been identified. By utilizing operational data in Xiamen, China, obtained from Didi Chuxing, we propose a novel method to build the first driving cycle series of ERVs, which can delineate how ERV drivers drive under the operating state. The cycle series consists of four driving cycles, synthesized by the micro-trip-based method using operational data from four time slices. Analysis against real data has shown that our method significantly outperforms existing methods, demonstrating the representativeness of the cycles.

Face detection of comic characters is a necessary step in most applications, such as comic character retrieval, automatic character classification and comic analysis. However, the existing methods were developed for simple cartoon images or small size comic datasets, and detection performance remains to be improved. In this paper, we propose a Faster R-CNN based method for face detection of comic characters. Our contribution is twofold. First, for the binary classification task of face detection, we empirically find that the sigmoid classifier shows a slightly better performance than the softmax classifier. Second, we build two comic datasets, JC2463 and AEC912, consisting of 3375 comic pages in total for characters face detection evaluation. Experimental results have demonstrated that the proposed method not only performs better than existing methods, but also works for comic images with different drawing styles.

Tyrosine Kinase Inhibitor (TKI) of Epidermal Growth Factor Receptor (EGFR) is a first-line therapy for non-small cell carcinoma lung cancer patients with EGFR mutations, but patients often develop resistance to such a target therapy. Recently several PD-1 and PD-L1 inhibitors were approved for treating NSCLC, however, it remains unclear whether EGFR mutant NSCLC would benefit from PD-1/PD-L1 treatment. PD-1 response in cancer patients is closely associated with oncogenic mutation status, tumor microenvironment, PD-L1 expression and tumor mutation burden (TMB); however, the lack of pre-clinical models limited the investigation of the checkpoint inhibitors in EGFR mutant tumors. Here we use human PBMC reconstitution system for immune-humanization, and established a series of IO-Xenograft models (IO-CDX and IO-PDX) with cancer cell lines (IO-CDX) or patient-derived tissues (IO-PDX) that contain various EGFR mutations, including EGFR 19 del, L858R, T790M, and EGFR over-expression, amplification and fusion. We treated these models with either EGFR TKI (erlotinib, afatinib or osimertinib) or nivolumab, a PD-1 inhibitor. The predictive biomarkers including PD-L1 expression and TMB were analyzed by whole exom sequencing (WES) and FACS for tumor infiltrating lymphocytes (TILs), respectively. We found that 3 TKI-resistant PDX models bearing EGFR T790M mutation exhibited lower TILs than those bearing EGFR wild type or exon 19del mutation. Of the 8 IO-CDX or IO-PDX humanized models we have examined, those exhibiting higher TILs achieved better responses to nivolumab treatment. The 3 most sensitive models are EGFR amplification (wt), EGFR over-expression (wt) and EGFR exon 19del. In contrast, the EGFR T790M model from H1975 cell line was observed with hyper-progressive disease after nivolumab treatment. We will also discuss the contribution of PD-L1 expression and TMB to nivolumab in other models. In summary, these well-established IO-CDX and IO-PDX models can provide a human-resembling immune system for of immune therapeutics and combination with targeted therapies, and help to facilitate the understanding of relationship among tumor microenvironment, driver oncogenic mutations and drug response. Citation Format: Xuzhen Tang, Li Yang, Hui Qi, Xianzhi Zhai, Fuyang Wang, Xiangnan Qiang, Jie Xu, Xiaoran Qin, Qingyang Gu, Shaoyu Yan, Qunsheng Ji. Evaluation of immune checkpoint inhibitor efficacy in EGFR mutant tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1055.

We evaluated the influence of DNA aneuploidy on chemotherapy-resistance in human Gastric cancer cell MKN45; we also evaluated the reversal effects of HZ08 on these cells and then preliminary investigated the possible involved pathway. We made use of a pair of human Gastric cancer cell dip-MKN45 (diploid MKN45) and aneu-MKN45 (aneuploid MKN45). Growth inhibition in response to chemotherapeutic drugs was evaluated by CellTiter-Glo Luminescent Cell Viability assay and clone formation assay. Flow cytometry and immuno-assay were applied to evaluate apoptosis and the expression of relative signaling molecules. MKN45 xenograft was generated to evaluate in vivo action. Aneu-MKN45 developed a resistance to cisplatin which could be reversed by HZ08; Flow cytometry and western-blot indicates that HZ08-combination could induce apoptosis and increase the expression of apoptosis-related biomarkers on aneu-MKN45; in vivo study also reflect the same correlation between aneuploidy and cisplatin-resistance, which could be antagonized by HZ08 combination; When investigating the involved pathway, in anue-MKN45, the expression of molecules in p53 pathway was decreased; HZ08 could increase the expression of p53 down-stream molecules as well as elevate the activity of p53, while inhibiting Mdm2, the major negative regulator of p53; p53 inhibitor Pifithrin-α could completely abrogate HZ08's synergism effects, and mimic cisplatin-resistance on dip-MKN45.Lower p53 pathway expression that attenuates cisplatin-induced apoptosis might be at least partly the reason of cisplatin-resistance occurred in aneuploid MKN45 both in vitro and in vivo; Combination of HZ08 could sensitize cisplatin-induced apoptosis through the activation of the p53 pathway, therefore represented a synergism effect on aneuploid MKN45 cells.

The dispatching policy of public bicycles during peak hours largely determines the sharing rate of bicycles and service level of public bicycle system. Firstly, a dynamic demand prediction model of public bicycle system is proposed considering reservation data and historical data. Secondly, a hierarchical dispatching policy and network partitioning method are discussed. Thirdly, an optimization model with time window to decide the number of bicycles that need to be dispatched is put forward considering the cost of dispatching and waiting time of passengers, and the method to decide the path of dispatching is also discussed. Finally, a case study in Guangzhou shows that the proposed policy could provide lower waiting time for passengers and better bicycle sharing rate of bicycles.

The reasonable rental price is helpful to improve the service level of urban public bicycle system and adjust the number of system users. Firstly, the framework for pricing public bicycle service from perspectives of the users, government and public bicycle company is developed and data collection is discussed. Secondly, three models are established considering benefits of users and public bicycle companies. The objectives of these models are maximizing amount of users, balancing income and expenses of public bicycle system and maximizing the benefit of bicycle companies respectively. Finally, a case study in Guangzhou was analyzed to verify the feasibility and effectiveness of the proposed models.

The limited therapeutic effect of gemcitabine on pancreatic cancer is largely attributed to pre-existing or acquired resistance of the tumor cells. This study was aimed at screening for candidate resistance-related gene(s) and elucidating the underlying mechanisms. NME5 was found to be highly expressed in an innate gemcitabine-resistant human pancreatic cancer sample and the cell line PAXC002 derived from the sample. Downregulation of NME5 significantly reversed gemcitabine resistance in PAXC002 cells, whereas NME5 overexpression induced gemcitabine resistance in the pancreatic cancer cell line BxPC-3. NME5 attenuated the induction of apoptosis and cell cycle arrest induced by gemcitabine, probably accounting for the blunted sensitivity to gemcitabine. Furthermore, NME5 was demonstrated to play its role in a nuclear factor kappaB (NF-κB)-dependent manner. NME5 was capable of directly binding NF-κB, and possibly regulated its expression level in PAXC002 cells. Our results also suggest that NF-κB is a key executor of NME5 in regulating apoptosis and cell cycle. All of these data suggest that NME5 is a promising target for relieving innate gemcitabine resistance in pancreatic cancer cells.

To investigate the role of DKK-1/Wnt/beta-catenin signaling in high proliferation of LM-MCF-7 breast cancer cells, a sub-clone of MCF-7 cell line.Two cell lines (MCF-7 and LM-MCF-7) with different proliferation abilities were used. LM-MCF-7 cells were transiently transfected with the pcDNA3-DKK-1 plasmid encoding the DKK-1 gene (or MCF-7 cells were transfected siRNA targeting DKK-1 mRNA). Flow cytometry analysis and 5-bromo-2'-deoxyuridine (BrdU) incorporation assay were applied to detect the cell proliferation. The expression levels of beta-catenin, phosphorylated beta-catenin, c-Myc, cyclin D1 and Survivin were examined by Western blot analysis. The regulation of Survivin was investigated by Luciferase reporter gene assay.Western blot and RT-PCR analysis showed that the expression level of DKK-1 was downregulated in LM-MCF-7 relative to MCF-7 cells. Flow cytometry and BrdU incorporation assay showed DKK-1 could suppress growth of breast cancer cells. Overexpression of DKK-1 was able to accelerate phosphorylation-dependent degradation of beta-catenin and downregulate the expression of beta-catenin, c-Myc, cyclin D1 and Survivin. Luciferase reporter gene assay demonstrated that Survivin could be regulated by beta-catenin/TCF4 pathway.We conclude that the downregulation of DKK-1 is responsible for the high proliferation ability of LM-MCF-7 breast cancer cells via losing control of Wnt/beta-catenin signaling pathway, in which c-Myc, cyclinD1 and Survivin serve as essential downstream effectors. Our finding provides a new insight into the mechanism of breast cancer cell proliferation.

The actin-myosin interaction of vascular smooth muscle cells (VSMCs) is regulated by myosin light chain kinase (MLCK), which is a fusion protein of the central catalytic domain with the N-terminal actin-binding and C-terminal myosin-binding domains. In addition to the regulatory role of kinase activity mediated by the catalytic domain, nonkinase activity that derives from both terminals is able to exert a regulatory role as reviewed by Nakamura et al. ( 32 ). We previously showed that nonkinase activity mediated the filopodia upon the stimulation by sphingosylphosphorylcholine (SPC) ( 25 ). To explore the regulatory role of nonkinase activity in chemotaxis, we constructed VSMCs where the expression of MLCK was totally abolished by using a lentivirus-mediated RNAi system. We hypothesized that the MLCK-downregulated VSMCs were unable to form filopodia and to migrate upon SPC stimulation and confirmed the hypothesis. We further constructed a kinase-inactive mutant from bovine cDNA coding wild-type (WT) MLCK by mutating the ATP-binding sites located in the catalytic domain, followed by confirming the presence (absence) of the kinase activity of WT (kinase-inactive mutant). We transfected WT and the mutant into MLCK-downregulated VSMCs. We expected that the transfected VSMCs will recover the ability to induce filopodia and chemotaxis toward SPC and found both constructs rescued the ability. Because they share the actin- and myosin-binding domains, we concluded nonkinase activity plays a major role for SPC-induced migration.

Resveratrol has been shown recently to exhibit antimetastatic effect on various human solid tumors. However, the possible molecular mechanism for its antimetastatic action needs to be elucidated. In this study, we investigated the effect of resveratrol on metastasis potential of colon carcinoma cells under normoxia and hypoxia in vitro. These results showed that, resveratrol can restrict the migration, adhesion, invasion and MMP-9 and MMP-2 secretion in Lovo cells cultured under normoxia and hypoxia. Hypoxia and iron chelator 2,2'-dipyridyl treatment can stimulate the invasion and migration enhancement of Lovo cells, while resveratrol exhibited substantial resistance on the metastasis potential stimulation by inhibiting the mRNA expression of VEGF and MMP-9 in colon carcinoma cells under normoxia and hypoxia, reducing HIF-1 alpha protein expression under hypoxia. Also, iron chelator 2,2'-dipyridyl treatment showed approximately the same effect on metastasis potential as Lovo cells cultured under hypoxia. These data demonstrated that, the antimetastatic effect of resveratrol under hypoxia were associated with the restriction of HIF-1 alpha protein expression and stabilization, which could be a promising drug target for resveratrol in the development of an effective chemopreventive and anticancer therapy in human tumors.

Blebbistatin is a myosin II-specific inhibitor. However, the mechanism and tissue specificity of the drug are not well understood. Blebbistatin blocked the chemotaxis of vascular smooth muscle cells (VSMCs) toward sphingosylphosphorylcholine (IC50= 26.1 ± 0.2 and 27.5 ± 0.5 μM for GbaSM-4 and A7r5 cells, respectively) and platelet-derived growth factor BB (IC50= 32.3 ± 0.9 and 31.6 ± 1.3 μM for GbaSM-4 and A7r5 cells, respectively) at similar concentrations. Immunofluorescence and fluorescent resonance energy transfer analysis indicated a blebbistatin-induced disruption of the actin-myosin interaction in VSMCs. Subsequent experiments indicated that blebbistatin inhibited the Mg2+-ATPase activity of the unphosphorylated (IC50= 12.6 ± 1.6 and 4.3 ± 0.5 μM for gizzard and bovine stomach, respectively) and phosphorylated (IC50= 15.0 ± 0.6 μM for gizzard) forms of purified smooth muscle myosin II, suggesting a direct effect on myosin II motor activity. It was further observed that the Mg2+-ATPase activities of gizzard myosin II fragments, heavy meromyosin (IC50= 14.4 ± 1.6 μM) and subfragment 1 (IC50= 5.5 ± 0.4 μM), were also inhibited by blebbistatin. Assay by in vitro motility indicated that the inhibitory effect of blebbistatin was reversible. Electron-microscopic evaluation showed that blebbistatin induced a distinct conformational change (i.e., swelling) of the myosin II head. The results suggest that the site of blebbistatin action is within the S1 portion of smooth muscle myosin II.

This paper implements a visual tool for the quick customization of virtual characters in 3D virtual worlds with a three-layer structure based on the Open Sim and Second Life platforms and "Knowledge" theory. "Knowledge" refers to specific controlling conditions and the corresponding behaviors of virtual characters. The three-layer structure is divided into the data layer, entity layer, and implementation layer. The data layer is used to store the data needed by the virtual characters' login and the behavioral control, the entity layer enables the exchange of data with the data layer and passes parameters to the implementation layer, and the implementation layer allows for realizing the knowledge of virtual characters with the support of the API in the Open Metaverse open source framework. Moreover, visualization of the tool is implemented through the interfaces provided by the entity layer. With this tool, users can generate a group of virtual characters quickly and conveniently at any place in a certain virtual world and select a variety of knowledge for diverse virtual characters.

Bus rapid transit is one of the best ways to improve urban transit. However, how to integrate the traditional bus and BRT is a problem that limits the efficiency of BRT system. Elastic route BRT system is a new BRT mode, which allows the BRT buses turn into or turn out of the bus lane at intersections. This paper puts forward a BRT approach capacity calculation method at intersection in Elastic route BRT system based on the data of Guangzhou BRT. And a case of Guangzhou BRT is studied to verify the validity developed method.

The use of 3D virtual technology in cultural transmission has been more and more innovative and popular in the recent years. Meanwhile, with the high interactivity, experience of virtual technology deeply rooted in the people's hearts, the use of 3D virtual world in cultural transmission shows an evident advantage. Through scene construction and intelligent interaction in a 3D virtual world environment, we developed the project “Confucius' Journey”. And considering the problems in such applications, such as the lack of interaction and reduced effectiveness in representing the application purpose, we explored interactive objects and virtual human technology. In addition, we can verify the advantage of using the 3D platform via the experimental results.

Through scene construction and intelligent interaction in a 3D virtual world environment, we developed the project "Confucius' Journey". Considering the problems in such applications, such as the lack of interaction and reduced effectiveness in representing the application purpose, we explored interactive objects and virtual human technology. In addition, we can verify the advantage of using the 3D platform via the experimental results.

In this paper, influence factors of pedestrian speed and pedestrian crossing velocity distribution are analyzed using the pedestrian speed observation data. More than 9,000 samples are collected from five kinds of land use areas in Guangzhou, including business district, transport hub, neighborhood, university campus, and comprehensive land use. The main influence factors of pedestrian crossing speed are the condition of road infrastructure, pedestrian signals, and pedestrian flow characteristics. Impact of these influence factors on pedestrian crossing speed is studied. This research also provides the reference for design and management of pedestrian crossing facilities.

Multiple drug resistance (MDR) occurring during chemotherapy is a major obstacle for treatment of cancers using chemotherapeutic drugs; thus, the mechanisms underlying MDR have attracted intensive attention. Many studies have shown that tumor-initiating cells exhibit a chemotherapeutic tolerance characteristic. However, whether the MDR cells possess tumor-initiating cells properties and its underlying mechanisms remain to be fully elucidated. In this study, we utilized a well-established MDR cell line K562/A02 enriched by doxorubicin from K562 cells to determine if the K562/A02 cells possess tumor-initiating properties and investigated its potential molecular mechanisms. We observed that the expressions of Oct4, Sox2, and Nanog, all of which are well-characterized stem cell markers, in K562/A02 cells were elevated in comparison to parental K562 cells; in addition, we found that K562/A02 cells exhibited more potent in vitro and in vivo tumor-initiating properties, as revealed by sphere assay, self-renewal assay, soft agar assay, and animal studies. Furthermore, our data suggest that snail and twist1, two well known transcriptional factors for the epithelial-mesenchymal transition (EMT) program, may be potentially involved in the acquisition of tumor-initiating properties of K562/A02 cells. Thus, our study demonstrates that MDR K562/A02 cells possess tumor-initiating properties, most likely due to the elevated expressions of snail and twist1. Keywords:: multi-drug resistance, K562/A02, tumor-initiating cell, snail, twist1

The limited therapeutic effect of gemcitabine on pancreatic cancer is largely attributed to pre-existing or acquired resistance of the tumor cells. This study was aimed at screening for candidate resistance-related gene(s) and elucidating the underlying mechanisms. NME5 was found to be highly expressed in an innate gemcitabine-resistant human pancreatic cancer sample and the cell line PAXC002 derived from the sample. Downregulation of NME5 significantly reversed gemcitabine resistance in PAXC002 cells, whereas NME5 overexpression induced gemcitabine resistance in the pancreatic cancer cell line BxPC-3. NME5 attenuated the induction of apoptosis and cell cycle arrest induced by gemcitabine, probably accounting for the blunted sensitivity to gemcitabine. Furthermore, NME5 was demonstrated to play its role in a nuclear factor kappaB (NF-κB)-dependent manner. NME5 was capable of directly binding NF-κB, and possibly regulated its expression level in PAXC002 cells. Our results also suggest that NF-κB is a key executor of NME5 in regulating apoptosis and cell cycle. All of these data suggest that NME5 is a promising target for relieving innate gemcitabine resistance in pancreatic cancer cells.

Non-metastatic cells 5 (NME5), a recently found gene belonging to the NDPK-like molecules gene family, is highly expressed in testis and some types of human cancer. Current studies have revealed diverse potential functions of NME5 and we have reported that NME5 is associated with innate resistance to gemcitabine in human pancreatic cancer cells in previous study. However, the mechanism underlying the transcriptional regulation of NME5 has not been elucidated yet. In this study, we analyzed the 5′-flanking region of the human NME5 gene and revealed its transcription start site (TSS) at − 35 bp relative to its translation start codon ATG. Using 5′ unidirectional deletion analysis, we demonstrated that the proximal promoter of NME5 is located within − 1051 bp to + 35 bp. Two functional GC-boxes (− 300 bp and − 323 bp) were identified within the promoter region. Mutation of either GC-box led to significant reduction in NME5 promoter activity, whereas overexpression of Sp1 activated NME5 promoter activity in MIA PaCa-2 and 293T cells. In silico analysis predicted that transcription factor Sp1 binds to both GC-boxes, which were confirmed by EMSA and ChIP. In addition, we found that compared with MIA PaCa-2, Sp1 was highly expressed in PAXC002, a well characterized human pancreatic cancer cell line with innate gemcitabine resistance where NME5 was reported to be highly expressed, indicating that Sp1 induces NEM5 expression in PAXC002 cells. In conclusion, our study characterized for the first time the human NME5 promoter which is controlled by Sp1 transcription factor in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDA) remains one of the most lethal malignancies in the world, often diagnosed at an advanced stage, resistant to conventional chemotherapy and having high invasive and metastatic potential. The mechanism of drug resistance of PDA is still not clear. In the present study, we established two novel pancreatic cancer cell lines PAXC-002 and PAXC-003 from human primary xenograft models. The cell lines were characterized by morphology, karyotype, pancreatic cancer marker and short tandem repeat (STR) analysis, and growth kinetics and tumorigenicity. The in vitro anti-proliferation test revealed that PAXC-002 cell was intrinsically resistant to the standard of care chemotherapy-gemcitabine, compared with that of PAXC-003 and other widely used pancreatic cancer cell lines. Interestingly, the gemcitabine resistant PAXC-002 cell line was more potent in forming colonies in 3-Dimensional matrigel culture conditions and had a higher percentage of CD133 positive cells, which is recognized as a cancer stem cell marker, compared to the gemcitabine-sensitive PAXC-003 cell line. In this study, we present two novel pancreatic cancer cell lines which could be used for gemcitabine resistance investigation, mechanism identification of pancreatic cancer and anticancer drug screening. The preliminary data indicate that the drug resistance of pancreatic carcinoma cells is associated with a cancer stem cell-like phenotype.

Beta-catenin is a multifunctional protein acting as a key factor in the cadherin-mediated cell-cell adhesion system and in the Wnt signaling pathway. To demonstrate the molecular mechanisms of metastasis of hepatocellular carcinoma (HCC) cells, we established a metastatic subclone of human HCC H7402 cells, termed M-H7402, by isolating from transplantation of H7402 cells into severe combined immunodeficient (SCID) mice. Based on the 2 parallel cell lines, we investigated the roles of dickkopf-1 (Dkk-1) and Wnt/beta-catenin pathway in proliferation and migration of HCC cells. cDNA microarray showed that 24 genes were related to tumor metastasis differentially expressed between H7402 and M-H7402 cells. Western blot analysis revealed that the expression levels of beta-catenin, c-Myc, and cyclin D1 were upregulated, but Dkk-1 and nm23 were dramatically downregulated in M-H7402 cells, which suggests that the 2 cell lines were remarkably different in molecular events associated with metastasis. Furthermore, we found that overexpression of Dkk-1 by transfection was able to downregulate the expression of c-Myc and cyclin D1, and it also inhibited the growth and migration in M-H7402 cells. Although reduction of Dkk-1 expression by RNA interference was able to upregulate the expression of beta-catenin, c-Myc, and cyclin D1 in H7402 cells, it also promoted beta-catenin translocation from cytoplasm into nuclei and increased the migration of the cells. Therefore, we conclude that Dkk-1/Wnt/beta-catenin cascade may mediate the proliferation and migration of HCC cells during the metastasis process.