Bergers E, Baak J P, van Diest P J, van Gorp L H, Kwee W S, Los J, Peterse H L, Ruitenberg H M, Schapers R F, Somsen J G, van Beek M W, Bellot S M, Fijnheer J
Department of Pathology, Free University Hospital, Amsterdam, The Netherlands.
Int J Cancer. 1997 Jun 20;74(3):260-9. doi: 10.1002/(sici)1097-0215(19970620)74:3<260::aid-ijc5>3.0.co;2-x.
Conflicting prognostic results with regard to DNA flow cytometric cell cycle variables have been reported for breast cancer patients. An important reason for this may be related to differences in the interpretation of DNA histograms. Several computer programs based on different cell cycle fitting models are available resulting in significant variations in percent S-phase and other cell cycle variables. Our present study evaluated the prognostic value of percent S-phase cells obtained using 5 different cell cycle analysis models. Flow cytometric DNA histograms obtained from 1,301 fresh frozen breast cancer samples were interpreted with 5 different cell cycle analysis models using a commercially available computer program. Model 1 used the zero order S-phase calculation and "sliced nuclei" debris correction, model 2 added fixed G2/M- to G0/G1-phase ratio, and model 3 added correction for aggregates. Model 4 applied the first-order S-phase calculation and sliced debris correction. Model 5 fixed the coefficients of variation CVs of the G0/G1- and G2/M-phases in addition to applying the sliced nuclei debris correction and zero order S-phase calculation. The different models yielded clearly different prognostic results. The average percent S-phase cells of the aggregate correction model (model 3) provided the best prognostic value in all cases for overall survival (OS) as well as disease-free survival (DFS) (OS: p < 0.0001; DFS: p < 0.0001), in lymph node-positive cases (OS: p < 0.0001; DFS: p = 0.004) and in DNA-diploid subgroups (OS: p = 0.004; DFS: p = 0.001). For the lymph node negative and DNA-non-diploid subgroups, the percent S-phase of the second cell cycle reached slightly better prognostic significance than the average percent S-phase cells. In multivariate analysis, the average percent S-phase of the aggregate correction model had the best additional prognostic value to tumor size and lymph node status. In conclusion, different cell cycle analysis models yield clearly different prognostic results for invasive breast cancer patients. The most important prognostic percent S-phase variable was the average percent S-phase cells when aggregate correction was included in cell cycle analysis.
关于乳腺癌患者，已有报道称DNA流式细胞术细胞周期变量的预后结果相互矛盾。造成这种情况的一个重要原因可能与DNA直方图的解读差异有关。有几种基于不同细胞周期拟合模型的计算机程序，这导致S期百分比和其他细胞周期变量存在显著差异。我们目前的研究评估了使用5种不同细胞周期分析模型获得的S期细胞百分比的预后价值。使用市售计算机程序，用5种不同的细胞周期分析模型解读从1301份新鲜冷冻乳腺癌样本中获得的流式细胞术DNA直方图。模型1使用零阶S期计算和“切片细胞核”碎片校正，模型2增加了固定的G2/M期与G0/G1期比值，模型3增加了聚集体校正。模型4应用一阶S期计算和切片碎片校正。模型5除了应用切片细胞核碎片校正和零阶S期计算外，还固定了G0/G1期和G2/M期的变异系数（CVs）。不同模型产生了明显不同的预后结果。聚集体校正模型（模型3）的平均S期细胞百分比在所有情况下对总生存期（OS）和无病生存期（DFS）均提供了最佳预后价值（OS：p<0.0001；DFS：p<0.0001），在淋巴结阳性病例中（OS：p<0.0001；DFS：p = 0.004）以及在DNA二倍体亚组中（OS：p = 0.004；DFS：p = 0.001）。对于淋巴结阴性和DNA非二倍体亚组，第二个细胞周期的S期百分比比平均S期细胞百分比具有稍好的预后意义。在多变量分析中，聚集体校正模型的平均S期百分比对肿瘤大小和淋巴结状态具有最佳的额外预后价值。总之，不同的细胞周期分析模型对浸润性乳腺癌患者产生明显不同的预后结果。当细胞周期分析中包含聚集体校正时，最重要的预后S期百分比变量是平均S期细胞百分比。
