{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T07:56:38Z","timestamp":1781078198437,"version":"3.54.1"},"reference-count":30,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Adlai Nortye"},{"name":"CRCHUM researcher internal research funds"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background: Buparlisib, combined with paclitaxel, improved survival in BERIL-1 trial patients with recurrent\/metastatic head and neck squamous cell carcinoma (R\/M HNSCC). However, predictive biomarkers of benefit remain undefined. Objective: To evaluate whether spatial biomarkers extracted from hematoxylin and eosin (H&amp;E) slides using artificial intelligence (AI) can predict overall survival benefit from buparlisib. Methods: Whole-slide H&amp;E images from BERIL-1 trial patients were analyzed using a deep learning model trained to segment tissue compartments and classify cell phenotypes. Three predefined spatial features were evaluated: tumor-infiltrating lymphocyte density, tumor microenvironment heterogeneity, and granulocyte fraction in the tumor invasive margin. Cox proportional hazards model assessed biomarker-treatment interactions. Results: Of 158 trial participants, 144 had available slides. High tumor-infiltrating lymphocyte density (&gt;10%) was associated with significantly improved overall survival with buparlisib versus placebo (HR, 0.25 (95% CI, 0.01\u20130.64; p = 0.002)), as were high tumor microenvironment heterogeneity (HR, 0.47 (95% CI, 0.27\u20130.80; p = 0.005)) and granulocyte enrichment in the tumor invasive margin (HR, 0.51 (95% CI, 0.30\u20130.88; p = 0.01)); within-arm proximity analysis showed higher granulocyte\u2013tumor-cell proximity correlated with improved overall survival on buparlisib (HR, 0.32 (95% CI, 0.18\u20130.58; p &lt; 0.001)). AI-derived spatial metrics outperformed CD3 immunohistochemistry. Among oropharyngeal tumors, HPV-positive cases were more frequent in patients with high tumor-infiltrating lymphocytes. Conclusions: AI-extracted spatial features from H&amp;E slides were associated with overall survival benefit from buparlisib in R\/M HNSCC. These scalable biomarkers support image-based patient selection strategies and are being prospectively evaluated in the BURAN phase 3 trial.<\/jats:p>","DOI":"10.3390\/cancers18121887","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T06:33:44Z","timestamp":1781073224000},"page":"1887","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial Biomarker Deep Learning Model Predicts Response to PI3K Inhibition in Head and Neck Cancer"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9382-7597","authenticated-orcid":false,"given":"Antoine","family":"Desilets","sequence":"first","affiliation":[{"name":"Hematology-Oncology Service, Department of Medicine, Centre Hospitalier de l\u2019Universit\u00e9 de Montr\u00e9al (CHUM), Montreal, QC H2X 0A9, Canada"},{"name":"Cancer Axis, Centre de Recherche du CHUM (CRCHUM), Montreal, QC H2X 0A9, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minh Tri","family":"Le","sequence":"additional","affiliation":[{"name":"Cancer Axis, Centre de Recherche du CHUM (CRCHUM), Montreal, QC H2X 0A9, Canada"},{"name":"Department of Pathology, Centre Hospitalier de l\u2019Universit\u00e9 de Montr\u00e9al (CHUM), Montreal, QC H2X 0A9, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catalina","family":"Moreno","sequence":"additional","affiliation":[{"name":"Cancer Axis, Centre de Recherche du CHUM (CRCHUM), Montreal, QC H2X 0A9, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justin","family":"Lucas","sequence":"additional","affiliation":[{"name":"Adlai Nortye, North Brunswick, NJ 08902, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandre","family":"Pellan Cheng","sequence":"additional","affiliation":[{"name":"Cancer Axis, Centre de Recherche du CHUM (CRCHUM), Montreal, QC H2X 0A9, 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Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ettai","family":"Markovits","sequence":"additional","affiliation":[{"name":"Nucleai, Tel Aviv 6744840, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Kaplan Kerner","sequence":"additional","affiliation":[{"name":"Nucleai, Tel Aviv 6744840, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5288-4109","authenticated-orcid":false,"given":"Amit","family":"Gutwillig","sequence":"additional","affiliation":[{"name":"Nucleai, Tel Aviv 6744840, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hadar","family":"Yehezkeli","sequence":"additional","affiliation":[{"name":"Nucleai, Tel Aviv 6744840, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisa F.","family":"Licitra","sequence":"additional","affiliation":[{"name":"Head and Neck Cancer Medical Oncology 3 Unit, Fondazione IRCCS 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