RELATIONSHIP BETWEEN THE SOCIO-DEMOGRAPHIC FACTORS AND THE CLINICOPATHOLOGICAL CHARACTERISTICS WITH THE INTRINSIC BIOMARKERS OF BREAST CARCINOMA OF WOMEN IN PAHANG, MALAYSIA Page No: 637-647

Khurshid Anwar and Tanveer Ahmad Khan

Keywords: Demographic, breast cancer, biomarkers, ER, cyclin E, p27, nm23, immunohistochemistry.

Abstract: Globally Breast cancer is the most common malignancy in women. The aim of this retrospective study was to determine the relationship between the socio-demographic factors and clinicopathological characteristics, with the known predictors of aggressive biological behaviour of breast cancer women in Pahang, Malaysia.The biomarkers included in this study were estrogen receptor (ER), cyclin E, p27 and nm23. Routine formalin-fixed, paraffin sections of tumor samples were used and immunohistochemically stained with antibodies against ER, cyclin E, p27 and nm23 in 93 cases of breast carcinoma in women attending at Breast clinic in Hospital Tengku Ampuan Afzan, Pahang, Malaysia during January, 1996-December, 2000. All markers studied were more common in the older age group >45 years and were roughly equally distributed among the Malays and Chinese with the exception of cyclin E which is more commonly expressed among the Malays (54.5% versus 43.9%). Breast carcinoma was found to be more common in patients over age 45 years. Most patients were diagnosed at a relatively early stage and were ER positive. ER positivity was more common in the older age, in tumors < 2cm in diameter, in early stages and in tumors with low histological grade. ER positivity was found more in patients who were alive for more than 25 months after their initial diagnosis. The cancer patients survival was significantly associated with ER (p=0.034) and nm23 (p=0.011), ER and tumor stage (p=0.031). Cyclin E expression appeared to influence the recurrence rate of primary tumor which may be a reflection of the secondary effect of treatment modality. Both markers p27 and nm23 were significantly associated with ER (p<0.001). The prognostic value of individual biological factors could be more effective in combination as opposed to single factors.



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