US EditionA Machine Learning Approach to Identify Predictive Molecular Markers for Cisplatin Chemosensitivity Following Surgical Resection in Ovarian Cancer
6 Articles
6 Articles
A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer
Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplatin sensitivity was generated using the Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas databases. Four potential biomarkers (CYTH3, GALNT3, S100A14, and ERI1) were identified and o…
Researchers from Spain and the United Kingdom develop an analysis that could avoid treatments that will not be effective in patients with ovarian, breast, prostate, and sarcoma tumors.
Researchers at the National Center for Oncological Research (CNIO) have discovered biomarkers that predict which patients will not respond to cancer chemotherapy; their use will prevent side effects and apply more effective treatment.
Researchers at the National Center for Oncological Research (CNIO) have discovered biomarkers that predict which patients will not respond to cancer chemotherapy; their use will prevent side effects and apply more effective treatment.
The use of these biomarkers in clinical practice would allow us to know if there are patients with a negative response and thus avoid the side effects of chemotherapy and a more effective treatment will be applied, the researchers of the CNIO, who today publish the results of their work in the journal Nature Genetics. Chemotherapy seeks to end tumor cells by means of drugs, and it is for decades a regular treatment against cancer, although it do…
Chemotherapy seeks to end tumor cells through drugs, and it has been a regular cancer treatment for decades. However, it does not always work. “Chemotherapy is good for some patients, but it is not effective in all cases. Between 20% and 50% of cancer patients do not respond to these drugs,” explains Geoff Macintyre, head of the Computer Oncology Group at the National Cancer Research Center (CNIO). “These patients will suffer side effects caused…
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