Pub Date : 2024-01-09DOI: 10.2174/0115733947271076231204181500
Jia Zeng, Huiqun Tian, Le Kang, Qian Wu, Shiwen Liu, Yugang Xiao, Hongwei Shao, Guangrui Huang, Song Liu
Chemotherapy resistance often occurs in the conventional treatment with AML and results in poor cure rates. CKI was found to have a good therapeutic effect when it was combined with other chemotherapy drugs in the clinical treatment of AML. However, the underlying mechanism is unclear. Therefore, this study aims to preliminarily describe the pharmacological activity and mechanism of CKI through comprehensive network pharmacology methods. This study aimed to explore the possible mechanism of Compound Kushen Injection (CKI) in the treatment of acute myeloid leukemia (AML) by using network pharmacology, molecular docking, and molecular dynamics techniques. Active compounds of CKI were identified based on the Traditional Chinese Medicine Systems Pharmacy (TCMSP) database, and the related targets of the active compounds were predicted using Swiss Target Prediction; AML-related targets from Gene Cards and Online Mendelian Inheritance in Man (OMIM) were collected. Protein-protein interaction (PPI) network was constructed, and its mechanism was predicted through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. The protein-protein interaction (PPI) network construction, module partitioning, and hub node screening were visualized by using the Cytoscape software and its plugins. These module partitionings were also verified by using molecular docking and molecular dynamics. Fifty-six active ingredients corresponding to 223 potential targets were identified. Biological function analysis showed that 731, 70, and 137 GO entries were associated with biological processes, cellular components, and molecular functions, respectively. A total of 163 KEGG pathways were identified. Network analysis showed that the key anti-AML targets of CKI are MAPK3, EGFR, SRC, PIK3CA, and PIK3R1 targets, which are involved in the PI3K/Akt and Ras/MAPK signaling pathways or related crosstalk pathways. Our results suggested that the key anti-AML targets of CKI, such as MAPK3, EGFR, SRC, PIK3CA and PIK3R1, are involved in the PI3K/Akt and Ras/MAPK signaling pathways or related crosstalk pathways. Concentrating on the dynamic and complex crosstalk regulation between PI3K/Akt and Ras/MAPK signal pathways and related signal pathways may be a new direction in anti-AML therapy in the future.
{"title":"Mechanism of Compound Kushen Injection in the Treatment of Acute Myeloid Leukemia from the Analysis Perspectives","authors":"Jia Zeng, Huiqun Tian, Le Kang, Qian Wu, Shiwen Liu, Yugang Xiao, Hongwei Shao, Guangrui Huang, Song Liu","doi":"10.2174/0115733947271076231204181500","DOIUrl":"https://doi.org/10.2174/0115733947271076231204181500","url":null,"abstract":"\u0000\u0000Chemotherapy resistance often occurs in the conventional treatment with\u0000AML and results in poor cure rates. CKI was found to have a good therapeutic effect when it was\u0000combined with other chemotherapy drugs in the clinical treatment of AML. However, the underlying\u0000mechanism is unclear. Therefore, this study aims to preliminarily describe the pharmacological activity\u0000and mechanism of CKI through comprehensive network pharmacology methods.\u0000\u0000\u0000\u0000This study aimed to explore the possible mechanism of Compound Kushen Injection\u0000(CKI) in the treatment of acute myeloid leukemia (AML) by using network pharmacology, molecular\u0000docking, and molecular dynamics techniques.\u0000\u0000\u0000\u0000Active compounds of CKI were identified based on the Traditional Chinese Medicine Systems\u0000Pharmacy (TCMSP) database, and the related targets of the active compounds were predicted using\u0000Swiss Target Prediction; AML-related targets from Gene Cards and Online Mendelian Inheritance in\u0000Man (OMIM) were collected. Protein-protein interaction (PPI) network was constructed, and its mechanism\u0000was predicted through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes\u0000(KEGG) enrichment. The protein-protein interaction (PPI) network construction, module partitioning,\u0000and hub node screening were visualized by using the Cytoscape software and its plugins. These\u0000module partitionings were also verified by using molecular docking and molecular dynamics.\u0000\u0000\u0000\u0000Fifty-six active ingredients corresponding to 223 potential targets were identified. Biological\u0000function analysis showed that 731, 70, and 137 GO entries were associated with biological processes,\u0000cellular components, and molecular functions, respectively. A total of 163 KEGG pathways were\u0000identified. Network analysis showed that the key anti-AML targets of CKI are MAPK3, EGFR, SRC,\u0000PIK3CA, and PIK3R1 targets, which are involved in the PI3K/Akt and Ras/MAPK signaling pathways\u0000or related crosstalk pathways.\u0000\u0000\u0000\u0000Our results suggested that the key anti-AML targets of CKI, such as MAPK3, EGFR,\u0000SRC, PIK3CA and PIK3R1, are involved in the PI3K/Akt and Ras/MAPK signaling pathways or related\u0000crosstalk pathways. Concentrating on the dynamic and complex crosstalk regulation between\u0000PI3K/Akt and Ras/MAPK signal pathways and related signal pathways may be a new direction in\u0000anti-AML therapy in the future.\u0000","PeriodicalId":503819,"journal":{"name":"Current Cancer Therapy Reviews","volume":"62 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139535288","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}
Pub Date : 2024-01-03DOI: 10.2174/0115733947268695231116100736
Pinky Sharma, V. Jhawat, Jatinder Singh, Rohit Dutt
Academic clinical research is considered the most important for cancer research because it frequently tests novel drug combinations, investigates rarer diseases, and lowers the risk for future commercial investments. However, due to the potential risks to the cancer patient, clinical research is governed by strict regulations. In high-income countries, comprehensive cancer centers (CCCs) have been established to align academic clinical cancer research with the regulatory framework. In comparison, academic clinical cancer research is considered ineffective in low-income countries. A cross-sectional, online survey was conducted to evaluate the knowledge of Indian health science students regarding cutting-edge cancer therapeutics and their underlying regulatory requirements. The survey found that 163 out of the 265 respondents were aware of the challenges of developing safe and effective anticancer therapeutics. 43 respondents found no challenges, while 59 respondents were unaware of any. Out of 163, 44 respondents identified technical challenges, 31 identified regulatory issues, and 88 identified both challenges in developing novel anticancer therapeutics. Interestingly, only 83 students out of 265, study cancer therapy regulations in their curriculum. This clearly indicates that most of India's health science students have a significant lack of understanding about the regulations for new cancer treatments. Academic clinical cancer research in India is just recognized as a prerequisite for degree completion due to a lack of regulatory foundation. An emphasis should be placed on restructuring the coursework offered to health science students to improve their ability to translate theoretical cancer research to real-world clinical care.
{"title":"Knowledge and Awareness of Emerging Cancer Therapies and their Regulations among Budding Scientists in India: A Survey","authors":"Pinky Sharma, V. Jhawat, Jatinder Singh, Rohit Dutt","doi":"10.2174/0115733947268695231116100736","DOIUrl":"https://doi.org/10.2174/0115733947268695231116100736","url":null,"abstract":"\u0000\u0000Academic clinical research is considered the most important for cancer research\u0000because it frequently tests novel drug combinations, investigates rarer diseases, and lowers the\u0000risk for future commercial investments. However, due to the potential risks to the cancer patient, clinical\u0000research is governed by strict regulations. In high-income countries, comprehensive cancer centers\u0000(CCCs) have been established to align academic clinical cancer research with the regulatory\u0000framework. In comparison, academic clinical cancer research is considered ineffective in low-income\u0000countries.\u0000\u0000\u0000\u0000A cross-sectional, online survey was conducted to evaluate the knowledge of Indian health\u0000science students regarding cutting-edge cancer therapeutics and their underlying regulatory requirements.\u0000\u0000\u0000\u0000The survey found that 163 out of the 265 respondents were aware of the challenges of developing\u0000safe and effective anticancer therapeutics. 43 respondents found no challenges, while 59\u0000respondents were unaware of any. Out of 163, 44 respondents identified technical challenges, 31\u0000identified regulatory issues, and 88 identified both challenges in developing novel anticancer therapeutics.\u0000Interestingly, only 83 students out of 265, study cancer therapy regulations in their curriculum.\u0000This clearly indicates that most of India's health science students have a significant lack of understanding\u0000about the regulations for new cancer treatments.\u0000\u0000\u0000\u0000Academic clinical cancer research in India is just recognized as a prerequisite for degree\u0000completion due to a lack of regulatory foundation. An emphasis should be placed on restructuring the\u0000coursework offered to health science students to improve their ability to translate theoretical cancer\u0000research to real-world clinical care.\u0000","PeriodicalId":503819,"journal":{"name":"Current Cancer Therapy Reviews","volume":"31 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139389340","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}
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