title: Flow cytometric DNA analysis of cirrhotic liver cells in patients with hepatocellular carcinoma can provide a new prognostic factor.
abstract: BACKGROUND
  DNA flow cytometry of hepatocellular carcinoma (HCC) cells has been investigated in many studies, but, to the best of our knowledge, there are no data on DNA analysis of cirrhotic parenchyma around the HCC. In this study, cell kinetics and ploidy of parenchymal cells around HCC were performed to ascertain if this would predict the possibility of recurrence in the cirrhotic areas.
  
  
  METHODS
  The DNA content of 93 cases of HCC and of cirrhotic liver around the tumor nodules was analyzed by flow cytometry. Ploidy and proliferative index of HCC and cirrhotic liver were compared with macroscopic, histologic, and clinical features of each case and linked with the behavior of these tumors. Survival curves were assessed according to the Kaplan-Meier method. A multivariate analysis based on Cox proportional hazards regression model was performed on cases of diploid cirrhosis cells in which the S-phase fraction was evaluable.
  
  
  RESULTS
  The univariate analysis of survival suggested significant roles for age, number of intrahepatic nodules, Edmondson-Steiner's classification, portal invasion, vascular invasion, presence of necrosis, hepatitis B surface antigen, alpha-feto-protein, Child's score, ploidy, and S-phase fraction of HCC cells. The DNA analysis of the cirrhotic cells showed that polyploidy was dramatically reduced in patients with HCC, compared with normal hepatocytes, and aneuploid clones were present among diploid cells. High S-phase fraction of cirrhotic cells and Child-Pugh classification were the strongest independent parameters affecting the tumor behavior in this study.
  
  
  CONCLUSIONS
  The results of this study suggest that S-phase fraction of cirrhotic liver parenchyma may be employed as a new parameter in the prognostic evaluation of HCC patients.
authors.affiliation: Department of Pathological Anatomy and Histology, City Hospital, Cuneo, Italy.
authors.forename: S
authors.initials: S
authors.lastname: Ruà
authors.forename: A
authors.initials: A
authors.lastname: Comino
authors.forename: A
authors.initials: A
authors.lastname: Fruttero
authors.forename: P
authors.initials: P
authors.lastname: Torchio
authors.forename: H
authors.initials: H
authors.lastname: Bouzari
authors.forename: S
authors.initials: S
authors.lastname: Taraglio
authors.forename: B
authors.initials: B
authors.lastname: Torchio
authors.forename: L
authors.initials: L
authors.lastname: Capussotti
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D006528:Carcinoma, Hepatocellular / Q000235:genetics / Q000473:pathology*; D002453:Cell Cycle; D002455:Cell Division; D004273:DNA, Neoplasm / Q000032:analysis*; D004171:Diploidy; D005260:Female; D005434:Flow Cytometry; D005544:Forecasting; D006514:Hepatitis B Surface Antigens / Q000032:analysis; D006801:Humans; D008103:Liver Cirrhosis / Q000235:genetics / Q000473:pathology*; D008113:Liver Neoplasms / Q000235:genetics / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness; D009364:Neoplasm Recurrence, Local / Q000235:genetics / Q000473:pathology; D011003:Ploidies; D011379:Prognosis; D016016:Proportional Hazards Models; D012044:Regression Analysis; D016196:S Phase; D015996:Survival Rate; D000509:alpha-Fetoproteins / Q000032:analysis
chemical_list: D004273:DNA, Neoplasm; D006514:Hepatitis B Surface Antigens; D000509:alpha-Fetoproteins