Immunohistochemical Algorithm for the Diagnosis and Classification of Hepatocellular Carcinomas With TERT, TP53 and CTNNB1 Mutation
Immunohistochemical Algorithm for the Diagnosis and Classification of Hepatocellular Carcinomas With TERT, TP53 and CTNNB1 Mutation
The presence of certain mutations in HCC, such as TERT and TP53, have a suspected or proven prognostic role in resected patients, but lack a morphological or immunophenotypic counterpart, which would allow us to define which tumours are rationally candidate for molecular biology analysis. The identification of a histological and immunohistochemical algorithm to determine which HCCs to take to NGS for prognostic purposes will save time and economic costs in the laboratory by rationalising available resources. In the future, the application of the immunohistochemical and molecular algorithm on biopsy could allow better prognosis and predictivity even before surgery/therapy.
The primary aim is the identification of possible associations between the biomarkers p53 and beta-Catenin and the presence of the genetic mutations TERT, TP53 and CTNNB1 identified by clinical practice, in patients undergoing hepatic resection of HCC.
The secondary objective is the identification of possible associations between the presence of biomarkers Glutamin Synthetase, Glypican-3 and HSP70 and genetic mutations identified by clinical practice, in patients undergoing hepatic resection of HCC.
STUDY DESIGN: exploratory study. It is planned to recruit approximately 100 patients, who underwent liver resection for HCC and already underwent NGS analysis (for which the mutational profile is already known). All clinical and histological data will be collected, immunohistochemistry investigations will be performed on formalin-fixed and paraffin-embedded material corresponding to that used for molecular analysis.
STUDY POPULATION: The study envisages the enrolment of 100 patients, already undergoing liver resection for HCC at the IRCCS AOU of Bologna, in the period 2020-2022, who will be retrospectively re-evaluated.
Inclusion Criteria:
Exclusion Criteria:
francesco.vasuri2@unibo.it0512143761
deborah.malvi@aosp.bo.it0512143761