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Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant
BACKGROUND: One of the most controversial problems for liver transplantation in patients affected by hepatocellular carcinoma (HCC) remains the lack of an oncologic staging system to predict cancer recurrence after liver transplantation (LT). We analyzed allelic imbalance (AI) in 19 microsatellites,...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Scientific Literature, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500106/ https://www.ncbi.nlm.nih.gov/pubmed/31015392 http://dx.doi.org/10.12659/AOT.913692 |
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author | Pagano, Duilio Barbera, Floriana Conaldi, Pier Giulio Seidita, Aurelio Di Francesco, Fabrizio Di Carlo, Daniele Barbàra, Marco Tuzzolino, Fabio Luca, Angelo Gruttadauria, Salvatore |
author_facet | Pagano, Duilio Barbera, Floriana Conaldi, Pier Giulio Seidita, Aurelio Di Francesco, Fabrizio Di Carlo, Daniele Barbàra, Marco Tuzzolino, Fabio Luca, Angelo Gruttadauria, Salvatore |
author_sort | Pagano, Duilio |
collection | PubMed |
description | BACKGROUND: One of the most controversial problems for liver transplantation in patients affected by hepatocellular carcinoma (HCC) remains the lack of an oncologic staging system to predict cancer recurrence after liver transplantation (LT). We analyzed allelic imbalance (AI) in 19 microsatellites, and assessed the post-LT HCC recurrence risk. MATERIAL/METHODS: Seventy-one patients were included; 18 had tumor recurrence within 5 years post-transplant. Molecular analysis was done in the primary HCC and peripheral blood samples: a total of 19 microsatellites was used to assess AI. Specific AI was evaluated when outside of range value between 0.66 and 1.5. Based on data in the literature, we grouped the 19 microsatellites into 4 panels. We calculated the fractional allelic imbalance (FAI) to make comparisons between different panels including different subsets of microsatellites. RESULTS: We report that AI was associated with HCC recurrence in 3 main loci (D3S2303, D9S251, and D9S254). Tumor recurrence was associated only with 2 specific panels with 9 microsatellites previously reported to be associated with high risk for HCC recurrence. Our data show that fractional allelic imbalance (FAI) index has good negative ability to predict HCC recurrence (Panel 2: negative predictive value of 95%). CONCLUSIONS: AI analysis could have prognostic value in risk management of HCC recurrence after LT, especially for early recurrence. |
format | Online Article Text |
id | pubmed-6500106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | International Scientific Literature, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65001062019-05-08 Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant Pagano, Duilio Barbera, Floriana Conaldi, Pier Giulio Seidita, Aurelio Di Francesco, Fabrizio Di Carlo, Daniele Barbàra, Marco Tuzzolino, Fabio Luca, Angelo Gruttadauria, Salvatore Ann Transplant Original Paper BACKGROUND: One of the most controversial problems for liver transplantation in patients affected by hepatocellular carcinoma (HCC) remains the lack of an oncologic staging system to predict cancer recurrence after liver transplantation (LT). We analyzed allelic imbalance (AI) in 19 microsatellites, and assessed the post-LT HCC recurrence risk. MATERIAL/METHODS: Seventy-one patients were included; 18 had tumor recurrence within 5 years post-transplant. Molecular analysis was done in the primary HCC and peripheral blood samples: a total of 19 microsatellites was used to assess AI. Specific AI was evaluated when outside of range value between 0.66 and 1.5. Based on data in the literature, we grouped the 19 microsatellites into 4 panels. We calculated the fractional allelic imbalance (FAI) to make comparisons between different panels including different subsets of microsatellites. RESULTS: We report that AI was associated with HCC recurrence in 3 main loci (D3S2303, D9S251, and D9S254). Tumor recurrence was associated only with 2 specific panels with 9 microsatellites previously reported to be associated with high risk for HCC recurrence. Our data show that fractional allelic imbalance (FAI) index has good negative ability to predict HCC recurrence (Panel 2: negative predictive value of 95%). CONCLUSIONS: AI analysis could have prognostic value in risk management of HCC recurrence after LT, especially for early recurrence. International Scientific Literature, Inc. 2019-04-24 /pmc/articles/PMC6500106/ /pubmed/31015392 http://dx.doi.org/10.12659/AOT.913692 Text en © Ann Transplant, 2019 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) |
spellingShingle | Original Paper Pagano, Duilio Barbera, Floriana Conaldi, Pier Giulio Seidita, Aurelio Di Francesco, Fabrizio Di Carlo, Daniele Barbàra, Marco Tuzzolino, Fabio Luca, Angelo Gruttadauria, Salvatore Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant |
title | Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant |
title_full | Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant |
title_fullStr | Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant |
title_full_unstemmed | Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant |
title_short | Role of Allelic Imbalance in Predicting Hepatocellular Carcinoma (HCC) Recurrence Risk After Liver Transplant |
title_sort | role of allelic imbalance in predicting hepatocellular carcinoma (hcc) recurrence risk after liver transplant |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500106/ https://www.ncbi.nlm.nih.gov/pubmed/31015392 http://dx.doi.org/10.12659/AOT.913692 |
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