BACKGROUND: Prognostic markers for pancreas cancer, such as CEA, CA19-9, ploidy analysis, and S-phase determination using flow cytometry, have not been consistently predictive. We chose to evaluate nuclear proliferation, as measured by the MIB-1 monoclonal antibody and digital image analysis, as a prognostic marker in pancreatic carcinoma, and compare the findings with DNA ploidy and S-phase analysis. MIB-1 identifies the Ki67 antigen present in nuclei of cells in all phases of the cell cycle except G0. METHODS: We retrospectively reviewed 33 patients with pancreatic adenocarcinoma resected for cure between 1989 and 1994 with available fixed tissue. Sectioned tissue was stained with MIB-1, and the number of positively stained nuclei determined and expressed as a MIB-1 labeling index (LI) by quantitative image analysis. Disaggregated nuclei were analyzed by flow cytometry using standard techniques. RESULTS: MIB-1 LI for pancreas cancers was heterogeneous within and between cancers. The MIB-1 LI for the cancers was 28 +/- 15 (median 29). There was no correlation between survival and MIB-1 expression (R(2) = 0.03). Likewise, there was no correlation between MIB-1 LI and percentage of cells in S-phase, G(2)/M, or total proliferating cells (S+G(2)/M; R(2) = 0.01), nor was there a difference between MIB-1 LI and ploidy (P = 0.88). CONCLUSIONS: We conclude that in our patient population, nuclear proliferation in pancreatic cancer, as determined by expression of Ki67 nuclear antigen, does not appear to correlate with survival and is not a useful prognostic marker. Despite intuitive thoughts to the contrary, there is no correlation between cell cycle analysis as determined by flow cytometry and Ki67 expression in pancreas cancer. Current methods of assessing prognosis after curative resection of cancer of the pancreas, including lymph node and margin status, tumor size, and possibly DNA ploidy as determined by flow cytometry, are not augmented by the assessment of nuclear proliferation by image analysis using the MIB-1 monoclonal antibody.
BACKGROUND: Prognostic markers for pancreas cancer, such as CEA, CA19-9, ploidy analysis, and S-phase determination using flow cytometry, have not been consistently predictive. We chose to evaluate nuclear proliferation, as measured by the MIB-1 monoclonal antibody and digital image analysis, as a prognostic marker in pancreatic carcinoma, and compare the findings with DNA ploidy and S-phase analysis. MIB-1 identifies the Ki67 antigen present in nuclei of cells in all phases of the cell cycle except G0. METHODS: We retrospectively reviewed 33 patients with pancreatic adenocarcinoma resected for cure between 1989 and 1994 with available fixed tissue. Sectioned tissue was stained with MIB-1, and the number of positively stained nuclei determined and expressed as a MIB-1 labeling index (LI) by quantitative image analysis. Disaggregated nuclei were analyzed by flow cytometry using standard techniques. RESULTS:MIB-1 LI for pancreas cancers was heterogeneous within and between cancers. The MIB-1 LI for the cancers was 28 +/- 15 (median 29). There was no correlation between survival and MIB-1 expression (R(2) = 0.03). Likewise, there was no correlation between MIB-1 LI and percentage of cells in S-phase, G(2)/M, or total proliferating cells (S+G(2)/M; R(2) = 0.01), nor was there a difference between MIB-1 LI and ploidy (P = 0.88). CONCLUSIONS: We conclude that in our patient population, nuclear proliferation in pancreatic cancer, as determined by expression of Ki67 nuclear antigen, does not appear to correlate with survival and is not a useful prognostic marker. Despite intuitive thoughts to the contrary, there is no correlation between cell cycle analysis as determined by flow cytometry and Ki67 expression in pancreas cancer. Current methods of assessing prognosis after curative resection of cancer of the pancreas, including lymph node and margin status, tumor size, and possibly DNA ploidy as determined by flow cytometry, are not augmented by the assessment of nuclear proliferation by image analysis using the MIB-1 monoclonal antibody.
Authors: ChongLek Lee; Hang He; Yongjian Jiang; Yang Di; Feng Yang; Ji Li; Chen Jin; Deliang Fu Journal: Med Oncol Date: 2013-09-13 Impact factor: 3.064
Authors: Mark M Aloysius; Shivanthi J De Silva Hewavisenthi; Timothy E Bates; Brian J Rowlands; Dileep N Lobo; Abed M Zaitoun Journal: World J Surg Date: 2010-09 Impact factor: 3.352
Authors: Wolfram Klapper; Eva Hoster; Olaf Determann; Ilske Oschlies; Jeroen van der Laak; Françoise Berger; Heinz Wolfram Bernd; José Cabeçadas; Elias Campo; Sergio Cogliatti; Martin Leo Hansmann; Philip M Kluin; Roman Kodet; Yuri A Krivolapov; Christoph Loddenkemper; Harald Stein; Peter Möller; Thomas E F Barth; Konrad Müller-Hermelink; Andreas Rosenwald; German Ott; Stefano Pileri; Elisabeth Ralfkiaer; Grzegorz Rymkiewicz; Johan H van Krieken; Hans Heinrich Wacker; Michael Unterhalt; Wolfgang Hiddemann; Martin Dreyling Journal: J Hematop Date: 2009-06-16 Impact factor: 0.196