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Sauer, M.* ; Lucas, M.C.* ; Prokosch, V.* ; Keßler, T.* ; Risch, T.* ; Laner, A.* ; Henkel, J.* ; Benet-Pages, A. ; Hallermayr, A.* ; Steinke-Lange, V.* ; Holinski-Feder, E.* ; Klink, B.*

Improving genetic diagnosis of hereditary tumor syndromes: From expanded gene panels to functional genomics.

Int. J. Cancer, DOI: 10.1002/ijc.70274 (2025)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
Genetic tumor risk syndromes (genturis) contribute substantially to the overall cancer burden and provide opportunities for early detection, prevention, and individualized treatment. Yet, many affected individuals remain undiagnosed due to restrictive testing criteria and challenges in variant interpretation. This review summarizes recent advances in the diagnostic evaluation of genturis. We trace the evolution from single-gene testing to multigene panel testing, highlighting gains in diagnostic yield alongside the growing prevalence of uncertain and incidental findings. We then describe emerging functional approaches such as RNA sequencing and proteomics that generate molecular evidence to refine variant classification. Next, we outline how long-read sequencing overcomes technical limitations in complex genomic regions. Finally, we discuss practical aspects of clinical implementation, including reporting practices, workflow integration, and professional education, and propose strategies to improve diagnostic accuracy, efficiency, and equitable access to testing.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Functional Genomics ; Hereditary Tumor Syndromes ; Long‐read Sequencing ; Multigene Panel Testing ; Variant Interpretation; Uncertain Significance; Colorectal-cancer; Lynch-syndrome; Pathogenic Variants; Ovarian-cancer; Rna-seq; Breast; Guidelines; Risk; Pms2
ISSN (print) / ISBN 0020-7136
e-ISSN 1097-0215
Zeitschrift International Journal of Cancer
Verlag Wiley
Verlagsort 111 River St, Hoboken 07030-5774, Nj Usa
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Neurogenomics (ING)