{"id":105391,"date":"2025-07-08T13:12:32","date_gmt":"2025-07-08T11:12:32","guid":{"rendered":"https:\/\/www.pcb.ub.edu\/irb-barcelona-develops-a-method-to-identify-mutational-signatures-that-improves-prognosis-prediction-in-ovarian-cancer\/"},"modified":"2025-07-08T15:45:07","modified_gmt":"2025-07-08T13:45:07","slug":"irb-barcelona-develops-a-method-to-identify-mutational-signatures-that-improves-prognosis-prediction-in-ovarian-cancer","status":"publish","type":"post","link":"https:\/\/www.pcb.ub.edu\/en\/irb-barcelona-develops-a-method-to-identify-mutational-signatures-that-improves-prognosis-prediction-in-ovarian-cancer\/","title":{"rendered":"IRB Barcelona develops a method to identify mutational signatures that improves prognosis prediction in ovarian cancer"},"content":{"rendered":"

Researchers from IRB Barcelona<\/a>, located at the Barcelona Science Park, and the Biotech Research & Innovation Centre (BRIC) at the University of Copenhagen, have presented a new method that combines two types of mutations to more effectively identify DNA repair defects. The study of this new method, published in the journal Genome Medicine<\/em>, has shown improved accuracy in predicting survival in ovarian cancer and could potentially be extended to other types of tumors.<\/strong><\/p>\n

As cancer develops, it leaves behind tell-tale marks on the DNA of tumour cells, revealing how the disease progresses and how it might respond to treatment. However, some of these patterns\u2014known as mutational signatures\u2014are hard to detect, which limits their use for predicting patient outcomes or deciding on the best therapy.<\/p>\n

Researchers from the Genome Data Science group<\/a> at IRB Barcelona, lead by Dr. Fran Supek<\/strong>, Professor at the\u00a0Biotech Research & Innovation Centre (BRIC)<\/strong>, University of Copenhagen, have developed a new approach that combines two kinds of genetic changes to better identify faults in the DNA repair systems of cancer cells.<\/p>\n

\u201cThis work is about reading the history written in the DNA of cancer cells more precisely, so we can understand why some patients respond better to treatment than others, and help doctors make more informed decisions\u201d, says Dr. Fran Supek<\/strong>.<\/p>\n

Looking deeper into cancer\u2019s DNA patterns<\/strong><\/h3>\n

Instead of focusing on just one type of genetic change, as most studies have done until now, researchers Patricia Ferrer\u2011Torres<\/strong>, Dr. Iv\u00e1n Galv\u00e1n\u2011Femen\u00eda<\/strong> and Dr. Fran Supek<\/strong> analysed two kinds simultaneously: tiny DNA letter changes and small insertions or deletions. By integrating this information, they gained a much clearer view of the genetic scars left by faulty DNA repair processes.<\/p>\n

The study looked at data from more than 380 whole-genome sequences of ovarian cancer collected from four international cohorts. Using their new method, the researchers were able to spot distinct DNA patterns linked to how well patients responded to standard treatments like platinum-based chemotherapy.<\/p>\n

Better predictions for patients\u2014and wider potential<\/strong><\/h3>\n

One of the key findings was that these DNA patterns could more accurately predict which ovarian cancer patients were likely to have longer survival, outperforming other commonly used genetic markers.<\/p>\n

Importantly, the same approach also showed promise in other cancers, including pancreatic, breast, and prostate tumours. \u201cWhat makes this method powerful is that it doesn\u2019t rely on any prior knowledge of the tumour\u2019s gene alterations\u2014it learns directly from the data, meaning it could be applied to many different types of cancer,\u201d reflects Patricia Ferrer\u2011Torres<\/strong>, first author of the study and a PhD student at IRB Barcelona.<\/p>\n

This research highlights how looking at the cancer genome in a more integrated way can provide valuable tools for personalised oncology. By better identifying DNA repair problems in tumours, doctors could more precisely tailor treatments and determine who might benefit most from certain therapies.<\/p>\n

\u00bb Article of reference: <\/strong>Joint inference of mutational signatures from indels and single-nucleotide substitutions reveals prognostic impact of DNA repair deficiencies. Patricia Ferrer-Torres, Iv\u00e1n Galv\u00e1n-Femen\u00eda & Fran Supek. Genome Medicine (2025); doi:\u00a010.1186\/s13073-025-01497-7<\/a><\/p>\n

\u00bb Link to the news: <\/strong>IRB website [+]<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers from IRB Barcelona, located at the Barcelona Science Park, and the Biotech Research & Innovation Centre (BRIC) at the University of Copenhagen, have presented a new method that combines…<\/p>\n","protected":false},"author":14,"featured_media":105385,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[36],"tags":[260],"class_list":["post-105391","post","type-post","status-publish","format-standard","has-post-thumbnail","category-science","tag-irb-en"],"acf":[],"yoast_head":"\nIRB Barcelona develops a method to identify mutational signatures that improves prognosis prediction in ovarian cancer - Parc Cient\u00edfic de Barcelona<\/title>\n<meta name=\"description\" content=\"The study of this new method has shown improved accuracy in predicting survival in ovarian cancer.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.pcb.ub.edu\/en\/irb-barcelona-develops-a-method-to-identify-mutational-signatures-that-improves-prognosis-prediction-in-ovarian-cancer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"IRB Barcelona develops a method to identify mutational signatures that improves prognosis prediction in ovarian cancer - 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