Genomic data in prognostic models-what is lost in translation? The case of deletion 17p and mutant TP53 in chronic lymphocytic leukaemia.

Genomic technologies are revolutionizing the practice of haematology-oncology, leading to improved disease detection, more accurate prognostication and targeted treatment decisions. These advances, however, have also introduced new clinical challenges, which include problems of prognostic underdetermination and its attendant risks of over- and undertreatment. Genomic data is generated from different technologies, from cytogenetics to next-generation sequencing, which are often interpreted interchangeably and in a binary fashion-as the presence or absence of a given chromosomal deletion or mutation-an oversimplification which may lead to mistaken prognosis. We discuss the clinical use of one such prognostic marker, represented by sequence and copy number alterations in TP53, located on chromosome 17p. Mutations in TP53 are strongly linked to poor prognosis in a variety of haematological malignancies, including chronic lymphocytic leukaemia (CLL). We review studies in CLL which utilize the 17p deletion or TP53 mutations for prognostic stratification with specific focus on the technologies used for detection, the thresholds established for clinical significance, and the clinical contexts in which these alterations are identified. The case of CLL illustrates issues arising from simplistic, binary interpretation of genetic testing and highlights the need to apply a critical lens when incorporating genomics into prognostic models.