Summary
Nearly 250,000 women are diagnosed each year with ovarian cancer around the world, resulting in 140,000 deaths. High-grade epithelial ovarian cancer (EOC) is the deadliest gynecologic cancer, ranking fifth overall in cancer deaths. The majority of women have widespread intra-abdominal disease at the time of diagnosis, and the 5-year survival rate for these women is only about 40% after receiving standard therapy. Currently, the standard first-line treatment for ovarian cancer consists of surgical cytoreduction and platinum-based chemotherapy. Although this approach has proven to be the most effective treatment to date, many ovarian cancers exhibit primary platinum resistance, and most patients develop secondary platinum resistance during the course of their disease. There is therefore a paucity of approved targeted therapies. Accordingly, effective novel therapies are needed to improve survival rates for patients diagnosed with ovarian cancer, especially in its advanced stages and in the setting of platinum resistance. The phenomenal success of cisplatin, oxaliplatin and carboplatin has boosted the research directed at novel metal-based anticancer drugs. My group has embarked a few years ago into a program to thoroughly investigate Ru compounds as anticancer drug candidates. However, one serious problem of metal-based drugs is often their intrinsic toxicity. To tackle this issue and circumvent these limitations, macromolecular delivery systems can be used to improve the potential of the respective anticancer ruthenium complexes. During the frame of the ERC consolidator grant PhotoMetMed, my group could demonstrate that an innovative drug-initiated polymerization methodology could be used to tackle this problem. In this proposal, to further demonstrate that this technology could be used on human, the in vivo efficacy of this system will be validated in several in ovarian cancer Patient-Derived Xenografts (PDXs) models.
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| Web resources: | https://cordis.europa.eu/project/id/101113026 |
| Start date: | 01-09-2023 |
| End date: | 28-02-2025 |
| Total budget - Public funding: | - 150 000,00 Euro |
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Original description
Nearly 250,000 women are diagnosed each year with ovarian cancer around the world, resulting in 140,000 deaths. High-grade epithelial ovarian cancer (EOC) is the deadliest gynecologic cancer, ranking fifth overall in cancer deaths. The majority of women have widespread intra-abdominal disease at the time of diagnosis, and the 5-year survival rate for these women is only about 40% after receiving standard therapy. Currently, the standard first-line treatment for ovarian cancer consists of surgical cytoreduction and platinum-based chemotherapy. Although this approach has proven to be the most effective treatment to date, many ovarian cancers exhibit primary platinum resistance, and most patients develop secondary platinum resistance during the course of their disease. There is therefore a paucity of approved targeted therapies. Accordingly, effective novel therapies are needed to improve survival rates for patients diagnosed with ovarian cancer, especially in its advanced stages and in the setting of platinum resistance. The phenomenal success of cisplatin, oxaliplatin and carboplatin has boosted the research directed at novel metal-based anticancer drugs. My group has embarked a few years ago into a program to thoroughly investigate Ru compounds as anticancer drug candidates. However, one serious problem of metal-based drugs is often their intrinsic toxicity. To tackle this issue and circumvent these limitations, macromolecular delivery systems can be used to improve the potential of the respective anticancer ruthenium complexes. During the frame of the ERC consolidator grant PhotoMetMed, my group could demonstrate that an innovative drug-initiated polymerization methodology could be used to tackle this problem. In this proposal, to further demonstrate that this technology could be used on human, the in vivo efficacy of this system will be validated in several in ovarian cancer Patient-Derived Xenografts (PDXs) models.Status
SIGNEDCall topic
ERC-2022-POC2Update Date
31-07-2023
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