Targeting AraC-Resistant Acute Myeloid Leukemia by Dual Inhibition of CDK9 and Bcl-2: A Systematic Review and Meta-Analysis

As a catalytic subunit of the positive transcription elongation factor b (P-TEFb), cyclin-dependent kinase 9 (CDK9) has been demonstrated to contribute to carcinogenesis. This review focuses on the development of selective CDK9 inhibitors and proteolysis-targeting chimera (PROTAC) degraders. Twenty selective CDK9 inhibitors and degraders are introduced along with their structures, IC50 values, in vitro and in vivo experiments, mechanisms underlying their inhibitory effects, and combination regimens. NVP-2, MC180295, fadraciclib, KB-0742, LZT-106, and 21e have been developed mainly for treating solid tumors, and most of them work only on certain genotypes of solid tumors. Only VIP152 has been proven to benefit the patients with advanced high-grade lymphoma (HGL) and solid tumors in clinical trials. Continued efforts to explore the molecular mechanisms underlying the inhibitory effects, and to identify suitable tumor genotypes and combination treatment strategies, are crucial to demonstrate the efficacy of selective CDK9 inhibitors and degraders in tumor therapy.

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“… 103 A combination of AZD4573 and c-MYC inhibitor 10,058-F4 can effectively suppress araC-resistant AML. 119 …”

Section: Cdk9 Selective Inhibitors and Degraders And Combination Regimenmentioning

confidence: 99%

Targeting CDK9 with selective inhibitors or degraders in tumor therapy: an overview of recent developments

Xiao

Liu

Chen

et al. 2023

Cancer Biology & Therapy

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“…2 CDK9 forms the catalytic subunit of the positive transcription elongation factor b (P-TEFb), which is required for the phosphorylation of RNA polymerase II (RNA Pol II) C-terminal domain (CTD) and transcription elongation. [3][4][5] Dysregulation of the CDK9 pathway has been demonstrated in a range of cancers including acute myeloid leukemia, [6][7][8] prostate cancer, [9][10][11] and colorectal cancer. [12][13][14] It has been shown that CDK9 promotes the expression and activation of oncogenes, such as MYC and Mcl-1.…”

Section: Introductionmentioning

confidence: 99%

Biomimetic black phosphorus nanosheets codeliver CDK9 and BRD4 inhibitors for gastric cancer targeted therapy

Zhang

Zhao

et al. 2023

J. Mater. Chem. B

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“…This algorithm can assist clinicians and medical personnel to a great extent. Acute lymphoblastic leukemia is a type of malignant blood cell cancer that affects mostly children and adults above age 65 [ 12 ]. Leukocytes, or white blood cells as they are commonly known, make up around one percent of all blood cells.…”

Section: Introductionmentioning

confidence: 99%

Customized Deep Learning Classifier for Detection of Acute Lymphoblastic Leukemia Using Blood Smear Images

et al. 2022

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Acute lymphoblastic leukemia (ALL) is a rare type of blood cancer caused due to the overproduction of lymphocytes by the bone marrow in the human body. It is one of the common types of cancer in children, which has a fair chance of being cured. However, this may even occur in adults, and the chances of a cure are slim if diagnosed at a later stage. To aid in the early detection of this deadly disease, an intelligent method to screen the white blood cells is proposed in this study. The proposed intelligent deep learning algorithm uses the microscopic images of blood smears as the input data. This algorithm is implemented with a convolutional neural network (CNN) to predict the leukemic cells from the healthy blood cells. The custom ALLNET model was trained and tested using the microscopic images available as open-source data. The model training was carried out on Google Collaboratory using the Nvidia Tesla P-100 GPU method. Maximum accuracy of 95.54%, specificity of 95.81%, sensitivity of 95.91%, F1-score of 95.43%, and precision of 96% were obtained by this accurate classifier. The proposed technique may be used during the pre-screening to detect the leukemia cells during complete blood count (CBC) and peripheral blood tests.

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Targeting AraC-Resistant Acute Myeloid Leukemia by Dual Inhibition of CDK9 and Bcl-2: A Systematic Review and Meta-Analysis

Cited by 5 publications

References 53 publications

Targeting CDK9 with selective inhibitors or degraders in tumor therapy: an overview of recent developments

Targeting CDK9 with selective inhibitors or degraders in tumor therapy: an overview of recent developments

Biomimetic black phosphorus nanosheets codeliver CDK9 and BRD4 inhibitors for gastric cancer targeted therapy

Customized Deep Learning Classifier for Detection of Acute Lymphoblastic Leukemia Using Blood Smear Images

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