Title |
Role of CTGF in Sensitivity to Hyperthermia in Ovarian and Uterine Cancers
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Published in |
Cell Reports, November 2016
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DOI | 10.1016/j.celrep.2016.10.020 |
Pubmed ID | |
Authors |
Hiroto Hatakeyama, Sherry Y. Wu, Yasmin A. Lyons, Sunila Pradeep, Wanqin Wang, Qian Huang, Karem A. Court, Tao Liu, Song Nie, Cristian Rodriguez-Aguayo, Fangrong Shen, Yan Huang, Takeshi Hisamatsu, Takashi Mitamura, Nicholas Jennings, Jeajun Shim, Piotr L. Dorniak, Lingegowda S. Mangala, Marco Petrillo, Vladislav A. Petyuk, Athena A. Schepmoes, Anil K. Shukla, Madeline Torres-Lugo, Ju-Seog Lee, Karin D. Rodland, Anna Fagotti, Gabriel Lopez-Berestein, Chun Li, Anil K. Sood |
Abstract |
Even though hyperthermia is a promising treatment for cancer, the relationship between specific temperatures and clinical benefits and predictors of sensitivity of cancer to hyperthermia is poorly understood. Ovarian and uterine tumors have diverse hyperthermia sensitivities. Integrative analyses of the specific gene signatures and the differences in response to hyperthermia between hyperthermia-sensitive and -resistant cancer cells identified CTGF as a key regulator of sensitivity. CTGF silencing sensitized resistant cells to hyperthermia. CTGF small interfering RNA (siRNA) treatment also sensitized resistant cancers to localized hyperthermia induced by copper sulfide nanoparticles and near-infrared laser in orthotopic ovarian cancer models. CTGF silencing aggravated energy stress induced by hyperthermia and enhanced apoptosis of hyperthermia-resistant cancers. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 1 | 20% |
Turkey | 1 | 20% |
United States | 1 | 20% |
Venezuela, Bolivarian Republic of | 1 | 20% |
Puerto Rico | 1 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Science communicators (journalists, bloggers, editors) | 1 | 20% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 50 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 16% |
Student > Doctoral Student | 7 | 14% |
Researcher | 5 | 10% |
Professor | 4 | 8% |
Student > Bachelor | 3 | 6% |
Other | 12 | 24% |
Unknown | 11 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 6 | 12% |
Pharmacology, Toxicology and Pharmaceutical Science | 5 | 10% |
Biochemistry, Genetics and Molecular Biology | 5 | 10% |
Medicine and Dentistry | 5 | 10% |
Nursing and Health Professions | 4 | 8% |
Other | 9 | 18% |
Unknown | 16 | 32% |