| ORIGINAL ARTICLE |
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| Year : 2011 | Volume
: 3
| Issue : 3 | Page : 119-128 |
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Ki-67 biomarker in breast cancer of Indian women
Amit V Patil1, Rajeev Singhai2, Rahul S Bhamre3, Vinayak W Patil2
1 Department of General Surgery, Government Medical College, Miraj, Maharashtra, India
2 Department of Biochemistry, Grant Medical College and Sir J.J. Group of Hospitals, Mumbai, India
3 Department of General Surgery, D.Y. Patil Hospital and Research Centre, Nerul, Navi Mumbai, India
Correspondence Address:
Rajeev Singhai
C-505, Beach Classic CHS Ltd. near Gorai Pumping Station, Chikoowadi, Borivali (West), Mumbai-400092
India
 Source of Support: None, Conflict of Interest: None  | Check |
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Background: Biological markers that reliably predict clinical or pathological response to primary systemic therapy early during a course of chemotherapy may have considerable clinical potential. Aims: Aims of study to evaluated changes in Ki-67 (MIB-1) labeling index and apoptotic index (AI) before, during, and after neoadjuvant anthracycline chemotherapy in breast cancer in Indian women. Materials and Methods: Breast cancer tissues were collected from Grant Medical College and Sir J.J. Group of Hospitals, Mumbai, India. Twenty-seven patients receiving neoadjuvant FEC (5-fluorouracil, epirubicin, and cyclophosphamide) chemotherapy for operable breast cancer underwent repeat core biopsy after 21 days of treatment. Results: The objective clinical response rate was 56%. Eight patients (31%) achieved a pathological response by histopathological criteria; two patients had a near-complete pathological response. Increased day-21 AI was a statistically significant predictor of pathological response (p = 0.049). A strong trend for predicting pathological response was seen with higher Ki-67 indices at day 21 and AI at surgery (p = 0.06 and 0.06, respectively). Conclusion: The clinical utility of early changes in biological marker expression during chemotherapy remains unclear. Until further prospectively validated evidence confirming the reliability of predictive biomarkers is available, clinical decision-making should not be based upon individual biological tumor biomarker profiles. |
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