{"id":263385,"date":"2025-10-27T12:22:44","date_gmt":"2025-10-27T11:22:44","guid":{"rendered":"https:\/\/www.unipi.it\/news\/tumore-al-seno-her2-positivo-a-pisa-un-algoritmo-predittivo-per-terapie-sempre-piu-personalizzate\/"},"modified":"2025-11-05T15:23:11","modified_gmt":"2025-11-05T14:23:11","slug":"her2-positive-breast-cancer-a-predictive-algorithm-developed-in-pisa-paves-the-way-for-more-personalised-therapies","status":"publish","type":"news","link":"https:\/\/www.unipi.it\/en\/news\/her2-positive-breast-cancer-a-predictive-algorithm-developed-in-pisa-paves-the-way-for-more-personalised-therapies\/","title":{"rendered":"HER2-Positive Breast Cancer: A predictive algorithm developed in Pisa paves the way for more personalised therapies"},"content":{"rendered":"
\"\"
Professor Cristian Scatena<\/figcaption><\/figure>\n

In the very month dedicated to breast cancer awareness, a study conducted by the University Hospital of Pisa and the University of Pisa marks a potential step forward in the fight against one of its most aggressive forms \u2014 HER2-positive breast cancer \u2014 thanks to an innovative model (MTClin) capable of accurately predicting patients\u2019 response to neoadjuvant therapies<\/strong>. Although HER2-positive tumours are among the most responsive to targeted molecular drugs, some patients still fail to achieve a complete response, largely because treatments cannot yet be tailored with absolute precision.<\/p>\n

MTClin \u2014 developed through research published in the \u201cEuropean Journal of Cancer\u201d <\/a>and partly supported by PNRR funding \u2014 has proven to be a highly reliable predictive tool. Applied to a large group of patients treated with anti-HER2 therapy, the algorithm accurately identified which individuals would fully benefit from the treatment and which would have only a partial response<\/strong>. The results showed very high sensitivity and specificity rates, particularly in certain subgroups of early-stage patients, where predictive accuracy was at its highest. Moreover, MTClin also demonstrated the ability to forecast the risk of disease recurrence at three and five years, with accuracy levels approaching 100%. Once externally validated, the tool could become part of standard clinical practice.<\/strong><\/p>\n

The algorithm is the result of research led by Cristian Scatena<\/strong>, from the Pathological Anatomy Unit 1 \u2014 headed by Antonio Giuseppe Naccarato<\/strong>, Full Professor of Pathological Anatomy \u2014 and Associate Professor of Pathological Anatomy at the University of Pisa.<\/p>\n

\u201cClose collaboration played a crucial role in achieving these results,\u201d Scatena emphasised, \u201cparticularly with oncologists from Aoup, including Andrea Fontana<\/strong> from the Medical Oncology Unit 2, directed by Gianluca Masi<\/strong>, Associate Professor of Medical Oncology at the University of Pisa, as well as colleagues from the Humanitas Institute and the University of Catania, whose contributions helped broaden the case study. Special mention also goes to Eugenia Belcastro<\/strong>, researcher in General Pathology at the University of Pisa, who made a key contribution to the development of the study.\u201d<\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

The study has been published in the \u201cEuropean Journal of Cancer\u201d<\/p>\n","protected":false},"featured_media":262514,"menu_order":5,"template":"","format":"standard","meta":[],"tag-notizie-persone":[],"tags_news":[1225,2305],"categorie":[159],"class_list":["post-263385","news","type-news","status-publish","format-standard","has-post-thumbnail","hentry","tags_news-department-of-translational-research-and-of-new-surgical-and-medical-technologies","tags_news-research-en","categorie-unipinews-en"],"yoast_head":"\nHER2-Positive Breast Cancer: A predictive algorithm developed in Pisa paves the way for more personalised therapies ~ UNIPI<\/title>\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.unipi.it\/en\/news\/her2-positive-breast-cancer-a-predictive-algorithm-developed-in-pisa-paves-the-way-for-more-personalised-therapies\/\" \/>\n<meta property=\"og:locale\" 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