Yudie Yang^*1, Xia Zhang^†1, Yajie Gao^*, Yan Dong^*, Di Wang^*, Yanping Huang^*, Tianhao Qu^*, Buqun Fan^*, Qizheng Li^*, Chunxia Zhang^*, Xiaonan Cui^*, Bin Zhang^*

Oncology Research, Vol.29, No.1, pp. 63-74, 2021, DOI:10.3727/096504022X16462176651719

Abstract Lung cancer is a malignant tumor with high incidence and mortality across the world. The use of immune checkpoint inhibitors for lung cancer has improved the prognosis of some lung cancer patients to a greater extent and provided a new direction for the clinical treatment of lung cancer. Immunotherapy still has limitations in terms of its appropriate population and adverse reactions. Particularly for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutation, there has been no major breakthrough in current immunotherapy. Whether immunotherapy can bring new benefits after drug resistance is More >

Hsiang-Lin Tsai^*†, Yen-Cheng Chen^*‡, Tzu-Chieh Yin^*§¶, Wei-Chih Su^*‡, Po-Jung Chen^*,Tsung-Kun Chang^*†, Ching-Chun Li^*, Ching-Wen Huang^*†, Jaw-Yuan Wang^{*†‡#**††‡‡}

Oncology Research, Vol.29, No.1, pp. 47-61, 2021, DOI:10.3727/096504022X16451187313084

Abstract Uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) polymorphism plays a crucial role in the increased susceptibility and toxicity of patients to irinotecan. This retrospective, observational study compared the clinical outcomes and adverse events (AEs) in RAS wild-type metastatic colorectal cancer (mCRC) patients treated with cetuximab or bevacizumab plus FOLFIRI with UGT1A1 genotyping and irinotecan dose escalation as the first-line therapy. In total, 173 patients with mCRC with RAS wild-type were enrolled. Among them, 98 patients were treated with cetuximab, whereas 75 patients were treated with bevacizumab. All patients received irinotecan dose escalation based on UGT1A1 genotyping. We compared the progression-free… More >

Angela Silvano^*†1, Giulio Menegazzi^*1, Silvia Peppicelli^*1, Caterina Mancini^*, Alessio Biagioni^*, Alessandro Tubita^*, Ignazia Tusa^*, Jessica Ruzzolini^*, Matteo Lulli^*, Elisabetta Rovida^*, Persio Dello Sbarba^*

Oncology Research, Vol.29, No.1, pp. 33-46, 2021, DOI:10.3727/096504022X16442289212164

Abstract This study was directed to deepen the effects of nutrient shortage on BCR/Ablprotein expression and signaling in chronic myeloid leukemia (CML) cells. The backbone of the study was cell culture in medium lacking glucose, the consumption of which we had previously shown to drive BCR/Ablprotein suppression, and glutamine, the other main nutrient besides glucose. In this context, we focused on the role of lactate, the main by-product of glucose metabolism under conditions of rapid cell growth, in particular as a modulator of the maintenance of CML stem/progenitor cell potential, a crucial determinant of disease course More >

Shuai Liu^*†1, Lu Lu^*†1, Feng Pan^‡, Chunsheng Yang^*†, Jing Liang^§, Jinfeng Liu^¶, Jian Wang^#, Rong Shen^**, Fu-Ze Xin^††, Nan Zhang^*†

Oncology Research, Vol.29, No.1, pp. 25-31, 2021, DOI:10.3727/096504022X16427607626672

Abstract Fruquintinib, also called HMPL-013, was first discovered by Hutchison Whampoa Pharmaceuticals Co. Ltd., Shanghai, China, and it is an oral vascular endothelial growth factor receptor (VEGFR) inhibitor. In clinical trials, fruquintinib has demonstrated a survival benefit in metastatic colorectal cancer (mCRC) patients. The purpose of this study was to retrospectively evaluate the efficacy and toxicity of fruquintinib in real-world patients. We collected data from patients with mCRC treated with oral fruquintinib from 2018 to 2020 in six different institutions. Patients with mCRC initially received 5 mg of oral fruquintinib daily for 3 weeks. Progression-free survival… More >

Kazuhiro Yamamoto^*, Takeshi Ioroi^*, Kazuaki Shinomiya^†, Ayaka Yoshida^*, Kenichi Harada^‡, Masato Fujisawa^‡, Tomohiro Omura^*, Yasuaki Ikemi^§, Shunsaku Nakagawa^§, Atsushi Yonezawa^§, Osamu Ogawa^¶, Kazuo Matsubara^§, Takuya Iwamoto^#, Kohei Nishikawa^**, Sayaka Hayashi^††, Daichi Tohara^††, Yoji Murakami^‡‡, Takanobu Motoshima^‡‡, Hirofumi Jono^††, Ikuko Yano^*§

Oncology Research, Vol.29, No.1, pp. 11-23, 2021, DOI:10.3727/096504022X16418911579334

Abstract We evaluated the association of signal transducer and activator of transcription 3 (STAT3) polymorphisms with the incidence of mammalian target of rapamycin (mTOR) inhibitor-induced interstitial lung disease (ILD) in patients with renal cell carcinoma (RCC). We also used lung-derived cell lines to investigate the mechanisms of this association. Japanese patients with metastatic RCC who were treated with mTOR inhibitors were genotyped for the STAT3 polymorphism, rs4796793 (−1697C/G). We evaluated the association of the STAT3 genotype with the incidence of ILD and therapeutic outcome. In the 57 patients included in the primary analysis, the ILD rate… More >

Fangjin Lu^*, Bin Mu^†, Ge Jin^*, Lin Zhu^‡, Ping Mu^§

Oncology Research, Vol.29, No.1, pp. 1-10, 2021, DOI:10.3727/096504021X16401852341873

Abstract NeuroD1 is a neuronal differentiation factor that contains a basic helix–loop–helix (bHLH) motif. Recently, NeuroD1 was found to be associated with tumorigenesis in neuroblastoma (NB) and is known to promote cell proliferation and migration in these cells. Here we found that MYCN regulates the expression of NeuroD1 in NB cells and that the downregulation of MYCN using short hairpin RNAs (shRNA) results in the inhibition of cellular proliferation in NB cells. Moreover, the phenotype induced by MYCN shRNA was rescued by the exogenous expression of NeuroD1. Chromatin immunoprecipitation (ChIP) assay showed that MYCN directly binds More >

Jumana Alsubhi¹, Abdulrahman Gharawi¹, Mohammad Alahmadi^2,*

Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 193-200, 2021, DOI:10.32604/jihpp.2021.027871 - 22 March 2022

Abstract Nowadays, machine learning (ML) algorithms cannot succeed without the availability of an enormous amount of training data. The data could contain sensitive information, which needs to be protected. Membership inference attacks attempt to find out whether a target data point is used to train a certain ML model, which results in security and privacy implications. The leakage of membership information can vary from one machine-learning algorithm to another. In this paper, we conduct an empirical study to explore the performance of membership inference attacks against three different machine learning algorithms, namely, K-nearest neighbors, random forest, More >

Mingting Liu¹, Xiaozhang Liu^1,*, Anli Yan¹, Xiulai Li^1,2, Gengquan Xie¹, Xin Tang³

Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 181-192, 2021, DOI:10.32604/jihpp.2021.027385 - 22 March 2022

Abstract As machine learning moves into high-risk and sensitive applications such as medical care, autonomous driving, and financial planning, how to interpret the predictions of the black-box model becomes the key to whether people can trust machine learning decisions. Interpretability relies on providing users with additional information or explanations to improve model transparency and help users understand model decisions. However, these information inevitably leads to the dataset or model into the risk of privacy leaks. We propose a strategy to reduce model privacy leakage for instance interpretability techniques. The following is the specific operation process. Firstly,… More >

Pengzhi Xu^1,2, Zetian Mai^1,2, Yuhao Lin¹, Zhen Guo^1,2,*, Victor S. Sheng³

Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 165-179, 2021, DOI:10.32604/jihpp.2021.027280 - 22 March 2022

Abstract With the increase of software complexity, the security threats faced by the software are also increasing day by day. So people pay more and more attention to the mining of software vulnerabilities. Although source code has rich semantics and strong comprehensibility, source code vulnerability mining has been widely used and has achieved significant development. However, due to the protection of commercial interests and intellectual property rights, it is difficult to obtain source code. Therefore, the research on the vulnerability mining technology of binary code has strong practical value. Based on the investigation of related technologies,… More >

Yichuan Liu¹, Chungen Xu^1,*, Lei Xu¹, Lin Mei¹, Xing Zhang², Cong Zuo³

Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 151-164, 2021, DOI:10.32604/jihpp.2021.026944 - 22 March 2022

Abstract The widespread acceptance of machine learning, particularly of neural networks leads to great success in many areas, such as recommender systems, medical predictions, and recognition. It is becoming possible for any individual with a personal electronic device and Internet access to complete complex machine learning tasks using cloud servers. However, it must be taken into consideration that the data from clients may be exposed to cloud servers. Recent work to preserve data confidentiality has allowed for the outsourcing of services using homomorphic encryption schemes. But these architectures are based on honest but curious cloud servers,… More >