RESUMO
OBJECTIVE: To propose a new decision algorithm combining biomarkers measured in a tumor biopsy with clinical variables, to predict recurrence after liver transplantation (LT). BACKGROUND: Liver cancer is one of the most frequent causes of cancer-related mortality. LT is the best treatment for hepatocellular carcinoma (HCC) patients but the scarcity of organs makes patient selection a critical step. In addition, clinical criteria widely applied in patient eligibility decisions miss potentially curable patients while selecting patients that relapse after transplantation. METHODS: A literature systematic review singled out candidate biomarkers whose RNA levels were assessed by quantitative PCR in tumor tissue from 138 HCC patients submitted to LT (>5 years follow up, 32% beyond Milan criteria). The resulting 4 gene signature was combined with clinical variables to develop a decision algorithm using machine learning approaches. The method was named HepatoPredict. RESULTS: HepatoPredict identifies 99% disease-free patients (>5 year) from a retrospective cohort, including many outside clinical criteria (16%-24%), thus reducing the false negative rate. This increased sensitivity is accompanied by an increased positive predictive value (88.5%-94.4%) without any loss of long-term overall survival or recurrence rates for patients deemed eligible by HepatoPredict; those deemed ineligible display marked reduction of survival and increased recurrence in the short and long term. CONCLUSIONS: HepatoPredict outperforms conventional clinical-pathologic selection criteria (Milan, UCSF), providing superior prognostic information. Accurately identifying which patients most likely benefit from LT enables an objective stratification of waiting lists and information-based allocation of optimal versus suboptimal organs.
Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Transplante de Fígado , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/cirurgia , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/cirurgia , Recidiva Local de Neoplasia/genética , Recidiva Local de Neoplasia/patologia , Seleção de Pacientes , RNA , Estudos Retrospectivos , Fatores de Risco , TranscriptomaRESUMO
Cutaneous metastases of internal malignancies occur infrequently and the zosteriform spread of the skin lesions represents a rare entity. We report here a case of cutaneous metastases from a colon carcinoma clinically mimicked Herpes varicella-zoster. The literature is also reviewed.