| Title |
Autophagy is associated with cucurbitacin D-induced apoptosis in human T cell leukemia cells
|
|---|---|
| Published in |
Medical Oncology, February 2016
|
| DOI | 10.1007/s12032-016-0743-y |
| Pubmed ID | |
| Authors |
Tsukasa Nakanishi, Yuan Song, Cuiying He, Duo Wang, Kentaro Morita, Junichi Tsukada, Tamotsu Kanazawa, Yasuhiro Yoshida |
| Abstract |
We previously reported that the inflammasome inhibitor cucurbitacin D (CuD) induces apoptosis in human leukemia cell lines. In the present study, we investigated the effects of co-treatment with an additional Bcl-xL inhibitor, Z36. Treatment with Z36 induced cell death in leukemia cell lines, with MT-4 cells exhibiting the lowest sensitivity to Z36. Co-treatment of cells with Z36 and CuD resulted in a greater degree of cell death for Hut78 and Jurkat cells than treatment with CuD alone. In contrast, co-treatment of MT-4 cells with Z36 and CuD had a suppressive effect on cell death. The autophagy inhibitor 3-methyladenine (3-MA) suppressed the growth of leukemia cell lines HuT78, Jurkat, MT-1, and MT-4. CuD-induced cell death was enhanced by 3-MA in Jurkat cells, but inhibited in MT-4 cells. Western blotting results revealed cleavage of poly(ADP ribose) polymerase (PARP), supporting CuD-induced cell death; 3-MA enhanced CuD-Z36-induced PARP cleavage. Taken together, our results indicate that autophagy negatively regulates chemical-induced cell death of leukemia cells, and that controlling autophagy could be beneficial in the development of more effective chemotherapies against leukemia. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 3 | 25% |
| Student > Bachelor | 2 | 17% |
| Student > Ph. D. Student | 1 | 8% |
| Professor | 1 | 8% |
| Researcher | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 17% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Psychology | 1 | 8% |
| Immunology and Microbiology | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 4 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2016.
All research outputs
#20,311,744
of 22,852,911 outputs
Outputs from Medical Oncology
#960
of 1,294 outputs
Outputs of similar age
#252,062
of 298,590 outputs
Outputs of similar age from Medical Oncology
#11
of 17 outputs
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