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ABSTRACT: This study try to subclassify breast cancer into different prognostic subgroups according to immunohistochemical algorithm and discuss the relationship between subtypes and biological and clinical behavior and prognosis.
One hundred and twenty-eight cases of infiltrative ductal carcinoma were studied using immunohistochemical staining with an antibody panel of ER, PR, HER2 and CK5/6 and subclassified referring to previous reports, and the 9 cases of HER2 positive subtype were tested using FISH.
The expression of ER, PR, HER2, and CK5/6 was detected in 67%, 45%, 27% and 27% cases, respectively. All cases were subclassified into five subgroups, with luminal A (55%), luminal B (20%), HER2 positive (7%), basal-like (10%) and unclassified cases (8%). Nine HER2 positive cases all showed amplification of HER2 gene. It was demonstrated that the luminal A group was associated with the best prognosis but the basal-like group worst by univariate analysis. Multivariate analysis demonstrated that both the clinical stage and immunohistochemical subtypes of tumor were related to overall survival. Menses status were different among these subtypes.
According to the expression of ER, PR, HER2 and CK5/6, infiltrative ductal carcinoma could be subclassified into five subgroups with different biological features and outcome, having a role in evaluating the prognosis and guiding the clinical treatment.
Zhonghua bing li xue za zhi Chinese journal of pathology 06/2010; 39(6):372-6.
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ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) has been classified into different prognostic subgroups using immunohistochemistry in Western populations. However, the applicability in Chinese patients of these subgroups was unclear. We collected 116 specimens and performed immunohistochemical staining for CD10, BCL-6, MUM1, CD138, and CD5, and the results were classified into subgroups according to 3 different algorithms. We then analyzed the subgroups' correlation to patient survival. Expression of CD10 and BCL-6 predicted favorable 5-year OS (70 and 62.5%, respectively) and PFS (64.3 and 61.5%, respectively) rates. In contrast, the expression of MUM1 predicted unfavorable 5-year OS (23.1%) and PFS (17.9%) rates and was also independent of other markers. All algorithms led to useful subclassifications. Using Hans' algorithm based on CD10, BCL-6, and MUM1, the non-germinal center (GC) subgroup (66.4%) had worse 5-year OS (29.8%) and PFS (26.7%) rates than did the GC subgroup. Likewise, using Muris' algorithm based on CD10 and MUM1, fewer non-GC cases (27%) showed poorer OS (20.3%) and PFS (16.2%) rates than did GC cases, an effect that was independent of both the International Prognostic Index, a clinical indicator, and treatment. It identified a subgroup with a high-risk of death and seemed to be applicable in our series. In conclusion, these algorithms can be used effectively in Chinese patients with DLBCL.
Medical Oncology 02/2010; 28(1):241-8. · 2.14 Impact Factor
Zhonghua bing li xue za zhi Chinese journal of pathology 06/2009; 38(6):423-4.
Zhonghua bing li xue za zhi Chinese journal of pathology 08/2005; 34(7):444-5.