{"title":"c-Jun N-terminal kinase (JNK), p38, and Caspases: Promising Therapeutic Targets for the Regulation of Apoptosis in Cancer Cells by Phytochemicals","authors":"Manish Kumar, S. Kaur, S. Kaur","doi":"10.2174/1573394719666230817094831","DOIUrl":"https://doi.org/10.2174/1573394719666230817094831","url":null,"abstract":"\u0000\u0000Carcinogenesis is a process in which uncontrolled cell proliferation forms preneoplastic nodules which precede the appearance of cancer. In normal cells, growth and proliferation are regulated by certain growth and hormonal stimulation, while mutational alterations in these signals render the cells independent and resistant to these signals. In cancer, the critical homeostatic balance between cell growth and apoptosis is lost and the cells continue to survive beyond their normal life span. The activation of c-Jun N-terminal kinase (JNK), p38 and caspases are involved in potential proapoptotic signaling pathways. JNK, p38 MAPK pathway and caspases play a crucial role in the control of apoptosis in response to stress.\u0000\u0000\u0000\u0000The most recent and up-to-date literature was evaluated in this study, which describes the role of JNK, p38 MAPK pathway and caspases as therapeutic target in cancer. Chemotherapy uses drugs that are cytotoxic to highly proliferating tumor cells but also kills the non-tumor rapidly proliferating cells in the hair, skin and gastrointestinal tract epithelium, thereby accounting the side effects of these types of treatments. Recently, chemopreventive modalities derived from phytoconstituents present in plants provide a broad-spectrum strategy to overcome the incidence of cancer. Non-toxic, safe and affordable bioavailabilities of chemopreventive agents provide credence support in the field of cancer research compared to conventional therapies that cause serious consequences. Chemoprevention envisages the basic mechanisms like modulating the activity of xenobiotic-metabolizing enzymes, induction of apoptosis, immune system activation, suppressing angiogenesis and the formation of metastasis, antioxidant and anti-inflammatory properties.\u0000\u0000\u0000\u0000The present review highlighted the role of phytoconstituents derived from food, vegetables and medicinal plants in the induction of apoptosis in cancer cells, which in turn is mediated by the activation of JNK, p38 MAPK pathways, and caspases.\u0000","PeriodicalId":43754,"journal":{"name":"Current Cancer Therapy Reviews","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44975257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"CAD system design for Two-Class Brain Tumor classification using Transfer Learning","authors":"Shruti Jain, Falguni Bhardwaj","doi":"10.2174/1573394719666230816091316","DOIUrl":"https://doi.org/10.2174/1573394719666230816091316","url":null,"abstract":"\u0000\u0000The occurrence of brain tumors is rapidly increasing, mostly in the younger generation. Tumors can directly destroy all healthy brain cells and spread rapidly to other parts. However, tumor detection and removal still pose a challenge in the field of biomedicine. Early detection and treatment of brain tumors are vital as otherwise can prove to be fatal.\u0000\u0000\u0000\u0000This paper presents the Computer Aided Diagnostic (CAD) system design for two classifications of brain tumors employing the transfer learning technique. The model is validated using machine learning techniques and other datasets.\u0000\u0000\u0000\u0000Different pre-processing and segmentation techniques were applied to the online dataset. A two-class classification CAD system was designed using pre-trained models namely VGG16, VGG19, Resnet 50, and Inception V3. Later GLDS, GLCM, and hybrid features were extracted which were classified using Support Vector Machine (SVM), k-Nearest Neighbor (kNN), and Probabilistic Neural Network (PNN) techniques.\u0000\u0000\u0000\u0000The overall classification accuracy using Inception V3 is observed as 83%. 85% accuracy was obtained using hybrid GLCM and GLDS features using the SVM algorithm. The model has been validated on the BraTs dataset which results in 84.5% and 82% accuracy using GLCM + GLDS + SVM and Inception V3 technique respectively.\u0000\u0000\u0000\u00002.9% accuracy improvement was attained while considering GLCM + GLDS + SVM over kNN and PNN. 0.5% and 1.2% accuracy improvement were attained for CAD system design based on GLCM + GLDS + SVM and Inception v3 model respectively.\u0000","PeriodicalId":43754,"journal":{"name":"Current Cancer Therapy Reviews","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49230661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Atar Singh Kushwah, K. Srivastava, Rajnikant Mishra, M. Banerjee
{"title":"Impact of Human Papillomavirus (HPV) Infection on the Treatment Outcome\u0000of Concomitant Chemoradiotherapy (CRT) in Cervical Cancer","authors":"Atar Singh Kushwah, K. Srivastava, Rajnikant Mishra, M. Banerjee","doi":"10.2174/1573394719666230807161948","DOIUrl":"https://doi.org/10.2174/1573394719666230807161948","url":null,"abstract":"\u0000\u0000Human Papilloma Virus (HPV) infection and its persistence are responsible\u0000for the development of cervical cancer (CaCx). Chemoradiotherapy (CRT) is the only treatment option, especially in advanced stages. However, it is not influenced by the status of HPV infection. CRT\u0000controls cancer growth along with mild to severe adverse effects.\u0000\u0000\u0000\u0000The aim of this study was to assess the HPV-associated risk factors and correlate them\u0000with chemoradiation therapy (CRT) response in cervical cancer.\u0000\u0000\u0000\u0000The study was undertaken in 103 histologically positive CaCx patients. Anthrodemographic and obstetric characterizations were conducted by face-to-face interviews, and HPV\u0000testing was done by conventional PCR. All the patients received a 40-50Gy total effective dose using\u0000tele‑ and brachytherapy. The treatment response, survivorship and statistical analysis were made using GraphPad Prism 9 and SPSS (ver.25.0).\u0000\u0000\u0000\u0000Out of 103 patients, 84% were HPV infected, and 16% CaCx were HPV-negative. Advanced age, lower-middle socioeconomic status (SES), illiteracy, and patients from rural backgrounds\u0000were significantly higher in CaCx patients with HPV infection. Multiparity, irregular menstrual cycle,\u0000poor menstrual hygiene, and use of contraception were significantly associated with HPV positivity.\u0000Patients with HPV infection showed a better clinical response (P =0.031), alive vital status (P\u0000=0.007), and 59 months of median survival (P <0.001) with a poor hazard ratio (HR 0.29 at 95% CI).\u0000\u0000\u0000\u0000HPV-infected CaCx patients showed better response to definitive chemoradiation therapy compared to HPV-negative with a poor hazard ratio. Therefore, HPV testing can potentially stratify CaCx patients for more effective therapeutic regimens, treatment assessments and follow-ups.\u0000","PeriodicalId":43754,"journal":{"name":"Current Cancer Therapy Reviews","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46115477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}