{"id":9021,"date":"2026-09-01T08:00:00","date_gmt":"2026-09-01T06:00:00","guid":{"rendered":"https:\/\/www.isrec.ch\/?post_type=recherche&p=9021"},"modified":"2026-09-04T15:54:59","modified_gmt":"2026-09-04T13:54:59","slug":"lymphomas-prof-laurence-de-leval-chuv-and-prof-raphael-gottardo-chuv","status":"publish","type":"recherche","link":"https:\/\/www.isrec.ch\/en\/research\/lymphomas-prof-laurence-de-leval-chuv-and-prof-raphael-gottardo-chuv\/","title":{"rendered":"Lymphomas<\/strong> – Prof. Laurence de Leval (CHUV) and Prof. Raphael Gottardo (CHUV)"},"content":{"rendered":"\n

When Digital Pathology Meets Spatial Proteomics: Toward a Transformed Precision Diagnosis for T Cell Lymphomas<\/strong><\/strong><\/h2>\n\n\n
Prof. Laurence de Leval (CHUV) and Prof. Raphael Gottardo (CHUV) were granted this \u201callocated fund\u201d in September 2026 for 3 years. Supported with a generous contribution of the Loterie Romande.<\/h5>\n\n\n
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T cell lymphomas are aggressive and rare malignant tumors, the treatment of which is considered an unmet clinical need. Their classification is complex due to their diverse histological types, cellular origins and genetics. The aim of our project is to improve diagnoses by focusing on the anaplastic, auxiliary follicular and \u201cnon-specified\u201d entities. Using cyclic immunofluorescence (COMET\u2122 imaging), we will exploit individual diagnostic markers in multiplex panels to map cellular phenotypes and spatial interactions in routinely processed biopsies. This course of action will replace standard immunohistochemistry and will make use of new tumor- and microenvironment-related phenotypic signatures identified using spatially resolved single-cell transcriptomics.<\/p>\n\n\n\n

The aim of the project is to exploit multiplex imaging and spatial biology for more precise diagnoses, thereby paving the way for pertinent and effective clinical applications and improved patient care.<\/p>\n\n\n\n

Approach<\/strong><\/p>\n\n\n\n

The project will integrate digital pathology and deep learning models to identify morphological characteristics in images of H&E-stained tissues by combining molecular and histological information. The aim is to generate a genetically characterized T cell lymphoma atlas validated by diagnostic experts and to analyze control lymphoid tissue samples. This approach will enable us to establish reference thresholds, identify models specific to the different lymphoma subtypes and single out actionable prognostic and therapeutic signatures.<\/p>\n\n\n

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