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2. DGCL: A Contrastive Learning Method for Predicting Cancer Driver Genes Based on Graph Diffusion

Author

Peng, Wei, Zhou, Zhengnan, Dai, Wei, Xu, Xinping, Fu, Xiaodong, Liu, Li, Liu, Lijun, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Peng, Wei, editor, Cai, Zhipeng, editor, and Skums, Pavel, editor

Published
2024
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3. Combined treatment with cetuximab and STA9090 has synergistic anticancer effects on human non-small cell lung cancer

Author

Lu Wanjun, Liu Lixia, Kang Xiang, Ren Kangkang, Huang Ye, Cheng Minzhang, Li Xiaolei, Xu Fei, and Xu Xinping

Subjects
cetuximab, STA9090, synergistic effect, receptor tyrosine kinase, non-small cell lung cancer, Biochemistry, QD415-436, Genetics, QH426-470
Abstract

Cetuximab (CET), a human murine chimeric IgG monoclonal antibody and an inhibitor of epidermal growth factor receptor (EGFR), has been shown to be effective in treating various types of cancer. However, its use is hindered by limitations such as resistance development, variability in patient response, side effects, and challenges in biomarker identification. Therefore, CET is often combined with other targeted therapies or chemotherapies to enhance its effectiveness. In this study, we investigate the anticancer effects and underlying mechanisms of the combination of CET, an EGFR inhibitor, and STA9090, an inhibitor of heat shock protein 90 (Hsp90), in both in vitro and in vivo models of non-small cell lung cancer (NSCLC). The results demonstrate significantly stronger effects on NSCLC cells in response to combination therapy than to treatment with either agent alone, indicating that the combination of CET and STA9090 has potential synergistic effects. Additionally, the combination therapy inhibits tumor growth in a xenograft nude mouse model more effectively than treatment with either agent alone, suggesting improved efficacy when used together. Furthermore, the synergistic effects of the combination therapy are likely due to inactivation of the receptor tyrosine kinase (RTK) pathway, which is overly activated in cancer and contributes to tumor growth, angiogenesis, and metastasis. Consequently, our findings suggest that STA9090 has potent direct antitumor activity and synergizes with CET against NSCLC tumors. It is highly likely that these synergistic effects are mediated through RTK pathway inactivation caused by the combination. Therefore, our findings strongly and consistently support the potential synergistic effect of STA9090, an RTK inhibitor, in combination with EGFR-targeting agents.

Published
2024
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5. List of contributors

Author

Aizawa, Shin-Ichi, primary, Alberdi, Pilar, additional, Alexander, David C., additional, Alía, Alberto, additional, Allison, D.G., additional, Amyes, Sebastian G.B., additional, An, Haoran, additional, Andrade, María J., additional, Antelmann, Haike, additional, Arias, Cesar A., additional, Asensio, Miguel A., additional, Axell-House, Dierdre B., additional, Bae, Hee-Won, additional, Baena, Laura Muñoz, additional, Baig, Abdul Mannan, additional, Bailey, Spenser O., additional, Baize, Sylvain, additional, Baldi, Pablo C., additional, Barbosa, Angela Silva, additional, Barbuddhe, Sukhadeo B., additional, Bard, Emilie, additional, Barry, Eileen M., additional, Basarab, Gregory S., additional, Beloborodova, N.V, additional, Bermúdez, Elena, additional, Bidmos, Fadil A., additional, Bisgaard, Magne, additional, Blakely, Garry W., additional, Bloch, Evan, additional, Boesen, Thias Oberg, additional, Bose, Dipayan, additional, Botero, Javier Enrique, additional, Bouabe, Hicham, additional, Bouchard, Michael J., additional, Bozue, Joel A., additional, Bradbury, Richard S., additional, Brett Moreau, G., additional, Cabezas-Cruz, Alejandro, additional, Cai, Rong-Jun, additional, Calderón, Enrique J., additional, Cao, Boyang, additional, Carmena, David, additional, Carvalho, Eneas, additional, Caulfield, Amanda D., additional, Cen, Shan, additional, Chai, Jong-Yil, additional, Chamberland, Robin R., additional, Champredon, David, additional, Chan, Edward D., additional, Charbon, Godefroid, additional, Chato, Connor, additional, Chelomina, G.N., additional, Chen, Jingyu, additional, Chen, Min, additional, Chen, Shuyu, additional, Chen, Suilin, additional, Chen, Yanfei, additional, Chen, Zhaoyuan, additional, Cheng, Aimin, additional, Cheng, Keding, additional, Chiu, Charles Y., additional, Cho, You-Hee, additional, Christensen, Henrik, additional, Chrtdernevskaya, E.A., additional, Contreras, Adolfo, additional, Contreras, Marinela, additional, Córdoba, Juan J., additional, Córdoba, María G., additional, Costa, Rita, additional, Cote, Christopher K., additional, Cui, Xiangling, additional, Cui, Yujun, additional, Dacal, Elena, additional, Dammann, Allison N., additional, Das, Shubhagata, additional, Dashti, Alejandro, additional, de la Fuente, José, additional, de la Garza, Mireya, additional, Delgado, Josué, additional, Delgado-Cuesta, Juan, additional, Deng, Haiteng, additional, Deng, Li, additional, Dey, Debajit, additional, Dhama, Kuldeep, additional, Diego, Juan García-Bernalt, additional, Ding, Hao, additional, Doern, Christopher D., additional, Dorman, Charles J., additional, Du, Zongmin, additional, Dunbar, Sherry A., additional, Duthie, Malcolm, additional, Dybvig, Kevin F., additional, Eakin, Ann E., additional, Eallonardo, Samuel J., additional, Eberly, Allison R., additional, Echeverry, Adriana Jaramillo, additional, Egland, Paul G., additional, El Zowalaty, Mohamed E., additional, Endsley, Janice Jones, additional, Eom, Keeseon S., additional, Evans, Benjamin A., additional, Falkinham, Joseph O., additional, Feng, Siwei, additional, Feng, Yaoyu, additional, Feng, Zongdi, additional, Fernández-Soto, Pedro, additional, Ferreira, Roux-Cil, additional, Flores-Huerta, Nadia, additional, Foster, Timothy J., additional, Fox-Moon, Sandra M., additional, Fraga, Tatiana Rodrigues, additional, Fredricks, David N., additional, Freitag, Nancy E., additional, Frimodt-Møller, Jakob, additional, Fuller, Risa, additional, Ganesh, Balasubramanian, additional, Gao, Ning, additional, García-Carnero, Laura C., additional, Garzetti, Debora, additional, Geoghegan, Joan A., additional, Ghenim, Raed, additional, Giambartolomei, Guillermo H., additional, Gilbert, Nicole M., additional, Gillis, Thomas Phillip, additional, Gladstone, Camilla A., additional, Gómez-Gaviria, Manuela, additional, Gómez-Marín, Jorge E., additional, Gong, Tengfang, additional, González, Ramón A., additional, Gray-Owen, Scott D., additional, Gu, Bing, additional, Guzmán-Téllez, Paula, additional, Hajal, Caroline, additional, Han, Yanping, additional, Hao, Yi, additional, Harrington, Amanda T., additional, Harris, Jason B., additional, Harvill, Eric T., additional, Hasan, S. Saif, additional, He, Guang-Jun, additional, He, Yongqun, additional, Heffron, Jared D., additional, Hidalgo, Paloma, additional, Hindiyeh, Musa Y., additional, Hreha, Teri N., additional, Hu, Xiaoyu, additional, Huang, Guanghua, additional, Huang, Jiangqing, additional, Huang, Liang, additional, Huang, Shifeng, additional, Huang, Xingxu, additional, Huang, Xueting, additional, Huang, Yilun, additional, Huffman, Anthony, additional, Humphreys, Tricia L., additional, Hunstad, David A., additional, Inglis, Timothy J.J., additional, Isaac, Lourdes, additional, Jacobs, Samantha E., additional, Janowicz, Diane M., additional, Jeon, Hyeong-Kyu, additional, Ji, Quanjiang, additional, Jia, Qi, additional, Jia, Wei, additional, Jin, Shouguang, additional, Jneidi, Lama, additional, Jose, Shinsmon, additional, Jung, Bong-Kwang, additional, Kattan, Randa, additional, Kaushik, Rahul, additional, Khare, Reeti, additional, Kim, Eun Sook, additional, Kirn, Thomas J., additional, Koo, Hyun, additional, Köster, Pamela C., additional, Krause, Peter J., additional, Kumar, Sanjai, additional, Kupz, Andreas, additional, Lambert, P.A., additional, Lamont, Richard J., additional, Langford, Paul R., additional, Lebeaux, David, additional, Legname, Giuseppe, additional, Li, Bin, additional, Li, Chunhao, additional, Li, Fen, additional, Li, Jun, additional, Li, Lanjuan, additional, Li, Ruofan, additional, Li, Ruoyu, additional, Li, Ting, additional, Li, Yang-Yang, additional, Li, Yanhua, additional, Li, Zhuorong, additional, Liang, Xiaomeng, additional, Liao, Guojian, additional, Lin, Ping, additional, Ling, Yun, additional, Liu, Bo, additional, Liu, Dongyou, additional, Liu, Guohua, additional, Liu, Huidi, additional, Liu, Jiafeng, additional, Liu, Jintao, additional, Liu, Qi, additional, Liu, Shu-Lin, additional, Liu, Taiping, additional, Liu, Tongbao, additional, Liu, Wei, additional, Liu, Yan, additional, Liu, Yanni, additional, Liu, Yisong, additional, Liu, Yuan, additional, Løbner-Olesen, Anders, additional, Loeffelholz, Michael, additional, Lu, Hongzhou, additional, Luna, Brian, additional, Ma, Bingting, additional, Ma, Chengying, additional, Ma, Shuang, additional, Ma, TianLi, additional, Madan, Rajat, additional, Mahle, Rachael E., additional, Mahlen, Steven D., additional, Malik, Satya Veer Singh, additional, Malik, Yashpal Singh, additional, Malvy, Denis, additional, Mann, Barbara J., additional, Marasini, Daya, additional, Maris, Alexander S., additional, Marjomäki, Varpu, additional, Marjuki, Henju, additional, Martín, Alberto, additional, Martín, Irene, additional, Martínez-Castillo, Moisés, additional, Martínez-Pabón, María Cecilia, additional, Mathison, Blaine A., additional, Ma’ayeh, Showgy, additional, McDowell, Andrew, additional, McLaughlin, Stephanie E., additional, McSheffrey, Gordon G., additional, Medrano, Francisco J., additional, Meehan, Conor J., additional, Mehta, Dhwani, additional, Mejía-Oquendo, Manuela, additional, Melo-Cristino, José, additional, Mendoza-Barberá, Elena, additional, Meng, Xinan, additional, Merino, Susana, additional, Merritt, Adam J., additional, Miller, Steve, additional, Miller, William R., additional, Minamino, Tohru, additional, Mirzaei, Mohammadali Khan, additional, Mora-Montes, Héctor M., additional, Mortensen, Joel, additional, Mostafa, Heba H., additional, Muhsen, Khitam, additional, Mujahed, Ahlam, additional, Muro, Antonio, additional, Murphy, Olwen C., additional, Newton, Hayley J., additional, Nguyen, April H., additional, Nichols, Wright W., additional, Niu, Siqiang, additional, Núñez, Félix, additional, Obregon, Dasiel, additional, Okamoto, Akira, additional, Okutani, Akiko, additional, Olabode, Abayomi, additional, Omar, Muna, additional, Ong, Edison, additional, Ouyang, Zhiming, additional, Pacak, Christina A., additional, Pacheco-Yépez, Judith, additional, Palmer, John, additional, Pang, Xiaoli, additional, Paredes-Sabja, Daniel, additional, Peng, Zhong, additional, Peng, Zonggen, additional, Pérez-Nevado, Francisco, additional, Poon, Art, additional, Pospíšilová, Petra, additional, Potts, Caelin C., additional, Pu, Qinqin, additional, Pujic, Petar, additional, Qi, Rui, additional, Qian, Chenyun, additional, Qian, Liu, additional, Qin, Aiping, additional, Qu, Fen, additional, Rakin, Alexander, additional, Ramesh, Ashwin, additional, Ramirez, Mario, additional, Rao, Yu, additional, Ratner, Adam J., additional, Rawool, Deepak B., additional, Rehman, Asma, additional, Ren, Jie, additional, Ren, Ping, additional, Retchless, Adam C., additional, Robertson, Erle S., additional, Rodríguez, Alicia, additional, Rodriguez, Azucena, additional, Rodríguez-Medina, Carolina, additional, Rodriguez-Nava, Veronica, additional, Rohde, Manfred, additional, Romero-Rodríguez, Alba, additional, Rosales-Morgan, Gabriela, additional, Rosenkranz, Andrea L., additional, Ruiz-Moyano, Santiago, additional, Ruokolainen, Visa, additional, Sabateen, Ali, additional, Sahu, Radhakrishna, additional, Sails, Andrew, additional, Sang, Yu, additional, Santana, Clarissa H., additional, Santos, Jesus A., additional, Santos, Renato L., additional, Schmitz, Jonathan E., additional, Serrano-Luna, Jesús, additional, Shen, Jianzhong, additional, Shen, Zhangqi, additional, Shibayama, Mineko, additional, Shirtliff, Mark E., additional, Silva-Costa, Catarina, additional, Silva-Olivares, Angélica, additional, Singh, Niraj Kumar, additional, Šmajs, David, additional, Smith, Robert P., additional, Smith, Sophie, additional, Snyder, Lori A.S., additional, Song, Yinggai, additional, Soro, Aurea Simon, additional, Spearman, Paul, additional, Spellberg, Brad, additional, Sprague, Lisa D., additional, Stratton, Charles W., additional, Strenk, Susan M., additional, Strugnell, Richard A., additional, Sun, Keer, additional, Suo, Xun, additional, Suzuki-Hatano, Silveli, additional, Svärd, Staffan, additional, Talbot, Elizabeth A., additional, Tamez-Castrellón, Alma K., additional, Tan, Nie, additional, Tang, Cynthia Y., additional, Tang, Yi-Wei, additional, Tao, Jia, additional, Tao, Lili, additional, Terrero-Salcedo, David, additional, Tharmalingam, Jayaraman, additional, Thwe, Phyu M., additional, Tiamani, Kawtar, additional, Tomás, Juan M., additional, Topaz, Nadav, additional, Tsai, Ang-Chen, additional, Tsalik, Ephraim L., additional, Tuomanen, Elaine I., additional, Turenne, Christine Y., additional, Tyagi, Anuj, additional, Uprety, Priyanka, additional, Valour, Florent, additional, van Hensbergen, Vincent P., additional, Venkatesan, Arun, additional, Vergis, Jess, additional, Villar, Margarita, additional, Vollmer, Waldemar, additional, Waites, Ken B., additional, Wan, Xiu-Feng, additional, Wang, Guiqing, additional, Wang, Lijun, additional, Wang, Lin, additional, Wang, Linqi, additional, Wang, Xiangru, additional, Wang, Xin, additional, Wang, Xinjie, additional, Wang, Ya-Ting, additional, Wang, Yang, additional, Wang, Yating, additional, Weil, Ana A., additional, Welkos, Susan L., additional, Wengenack, Nancy L., additional, Westblade, Lars F., additional, Whitfield, Chris, additional, Wu, Hui, additional, Wu, Lijuan, additional, Wu, Min, additional, Wu, Yarong, additional, Wu, Zhaowei, additional, Xiang, Ye, additional, Xiao, Di, additional, Xiao, Li, additional, Xiao, Lihua, additional, Xu, Tao, additional, Xu, Wenyue, additional, Xu, Xinping, additional, Xue, Jinling, additional, Yadav, Jay Prakash, additional, Yan, Junxiang, additional, Yan, Yixin, additional, Yang, Changmei, additional, Yang, Ruifu, additional, Yang, Ying, additional, Yao, Kaihu, additional, Yao, Yu-Feng, additional, Yeakle, Kyle C., additional, Yu, Demin, additional, Yu, Hao, additional, Yu, Xue-Jie, additional, Yuan, Zhenghong, additional, Zai, Wenjing, additional, Zhang, Jianzhong, additional, Zhang, Jing-Ren, additional, Zhang, Lanyue, additional, Zhang, Lijie, additional, Zhang, Qiwei, additional, Zhang, Wenbao, additional, Zhang, Wenhong, additional, Zhang, Xinxin, additional, Zhao, Youbao, additional, Zhou, Chuanmin, additional, Zhu, Feng, additional, Zhu, Jingting, additional, and Zhu, Yongqun, additional

Published
2024
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15. Feasibility of the Anchor‐Free Deep Learning Method in Coronary Stenosis Automatic Detection.

Author

Yue, Hanlin, Yu, Wei, Dong, Ji, Lai, Yunfei, Wu, You, Zhao, Haixia, Song, Yiwei, Zhao, Li, Wang, Hui, Zhang, Jing, Xu, Xinping, Yao, Binwei, Zhao, Jianghao, Wang, Kexian, Sun, Yue, Wang, Haoyu, Peng, Ruiyun, and Nguyen, Thach N.

Subjects
CORONARY artery stenosis, OBJECT recognition (Computer vision), DEEP learning, CORONARY angiography, CORONARY artery disease
Abstract

Background. Coronary artery disease (CAD) is a type of cardiovascular disease which is one of the leading causes of death around the world. The presence of coronary stenosis is considered a pivotal indicator in the diagnosis of various CADs. The main purpose of this paper was to investigate the feasibility of an anchor‐free deep learning (DL) method, fully convolutional one‐stage object detection (FCOS), in coronary artery stenosis automatic detection. Methods. First, 2786 invasive coronary angiography (ICA) images from 130 patients were randomly divided into training, validation, and testing datasets using the 10‐fold cross‐validation approach. Then, FCOS was compared with other three widely used anchor‐based DL models: single shot multibox detector (SSD), faster region‐based convolutional network (Faster R‐CNN), and you only look once (YOLOv3), in terms of precision, recall, F1 score, average precision (AP), and average recall (AR). Finally, the performances of different models in the detection of stenosis were compared in either single or multiple lesion scenarios using statistical tests. Results. FCOS achieved significantly superior precision (96.14% ± 0.53%), recall (94.36% ± 0.79%), F1 score (95.22% ± 0.56%), AP0.50 (93.36% ± 0.93%), AR0.50:0.95 (64.73% ± 1.46%), APsmall (55.04 ± 0.96%), APmedium (59.97 ± 1.13%), and APlarge (68.09 ± 5.18%) compared to Faster R‐CNN and YOLOv3. Moreover, FCOS demonstrated significantly higher AR0.50:0.95 and APsmall compared to SSD. Regardless of the presence of single or multiple coronary stenoses in ICA images, FCOS also outperformed Faster R‐CNN and YOLOv3. Furthermore, it showed significantly higher AR0.50:0.95 compared to SSD when in the multiple stenosis scenario. Conclusions. It is feasible to use the anchor‐free DL model FCOS in detecting coronary stenosis based on ICA images. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Fast acquisition method using modified PCA with a sparse factor for burst DS spread-spectrum transmission

Author

Tang, Chengyao, Wen, Tailai, Liang, Zhengyu, Xu, Xinping, and Mou, Weihua

Abstract

To improve the acquisition speed and inbound capacity of the ground station in a burst direct-sequence (DS) spread-spectrum transmission system, an acquisition method based on a modified parallel code-phase acquisition (PCA) scheme is proposed. By taking advantage of the sparsity of the acquisition result with PCA in the time domain, we introduce the sparse factor to handle the signals via sparsification and apply the sparse recovery algorithm to search and estimate the acquisition result. The computational complexity, mean acquisition time, and relationship between the inbound capacity and acquisition performance are provided. We theoretically analyse the effect of the sparse factor on the acquisition performance. The estimation errors verify our analysis, and simulations show that the acquisition time of our proposed method outperforms that of advanced PCA by 1.2–4.0 times; additionally, the inbound capacity increases by 6.2–36.7%.

Published
2024
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20. EGFR mutations and abnormal trafficking in cancers.

Author

Kang X, Li R, Li X, and Xu X

Subjects
Humans, Protein Transport, Endocytosis genetics, Signal Transduction genetics, Animals, ErbB Receptors genetics, ErbB Receptors metabolism, Neoplasms genetics, Mutation genetics
Abstract

Epidermal growth factor receptor (EGFR) is a transmembrane tyrosine kinase receptor and a member of the ErbB receptor family. As a significant cancer driver, EGFR undergoes mutations such as gene amplification or overexpression in a wide range of malignant tumors and is closely associated with tumorigenesis. This review examines the aberrant expression of EGFR in several common cancers and summarizes the current therapeutic strategies developed for this receptor. Additionally, this review compares the differences in EGFR activation, internalization, endocytosis, and sorting in normal and cancer cells, and highlights some regulatory factors that influence its trafficking process.Kindly check and confirm the edit made in the title.Yes, correctAs per journal instructions structured abstract is mandatory kindly provideThe abstract format does not apply to Review articles., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Published
2024
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