Current status of photodynamic technology for urothelial cancer
-
- Keiji Inoue
- Department of Urology Kochi Medical School Nankoku Japan
-
- Hideo Fukuhara
- Department of Urology Kochi Medical School Nankoku Japan
-
- Shinkuro Yamamoto
- Department of Urology Kochi Medical School Nankoku Japan
-
- Takashi Karashima
- Department of Urology Kochi Medical School Nankoku Japan
-
- Atsushi Kurabayashi
- Department of Pathology Kochi Medical School Nankoku Japan
-
- Mutsuo Furihata
- Department of Pathology Kochi Medical School Nankoku Japan
-
- Kazuhiro Hanazaki
- Center for Photodynamic Medicine Kochi Medical School Nankoku Japan
-
- Hung Wei Lai
- School of Life Science and Technology Tokyo Institute of Technology Yokohama Japan
-
- Shun‐Ichiro Ogura
- Center for Photodynamic Medicine Kochi Medical School Nankoku Japan
説明
<jats:title>Abstract</jats:title><jats:p>5‐Aminolevulinic acid is a new‐generation photosensitizer with high tumor specificity. It has been used successfully in the diagnosis, treatment, and screening of urological cancers including bladder cancer; specifically, it has been used in photodynamic diagnosis to detect tumors by illuminating the lesion with a specific wavelength of light to produce fluorescence in the lesion after administration of 5‐aminolevulinic acid, in photodynamic therapy, which induces tumor cell death via production of cytotoxic reactive oxygen species, and in photodynamic screening, in which porphyrin excretion in the blood and urine is used as a tumor biomarker after administration of 5‐aminolevulinic acid. In addition to these applications in urological cancers, 5‐aminolevulinic acid–based photodynamic technology is expected to be used as a novel strategy for a large number of cancer types because it is based on a property of cancer cells known as the Warburg effect, which is a basic biological property that is common across all cancers.</jats:p>
収録刊行物
-
- Cancer Science
-
Cancer Science 113 (2), 392-398, 2021-12-02
Wiley
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1360857593697817088
-
- ISSN
- 13497006
- 13479032
-
- データソース種別
-
- Crossref
- KAKEN