Yong Soon Chun

Ki-67 as a Predictor of Response to Neoadjuvant Chemotherapy in Breast Cancer Patients

Purpose The objectives of this study were to assess the potential value of Ki-67 in predicting response to neoadjuvant chemotherapy in breast cancer patients and to suggest a reasonable cutoff value for classifying Ki-67 expression. Methods This study included 74 breast cancer patients who underwent surgery after anthracycline-based neoadjuvant chemotherapy between 2007 and 2012. We analyzed the clinical and immunohistochemical characteristics using core biopsy specimens obtained before neoadjuvant chemotherapy to determine their correlations with the response to chemotherapy. Results A clinical complete response was observed in 6 patients (8.1%); a clinical partial response, in 44 patients (59.5%); and clinical stable disease, in 24 patients (32.4%). A pathologic complete response (pCR) was observed in 10 patients (13.5%). In univariate analysis, estrogen receptor (ER) negativity (p=0.031), human epidermal growth factor receptor 2 (HER2) positivity (p=0.040), and high Ki-67 expression (p=0.036) were predictive factors for a pCR. In multivariate analysis, Ki-67 was the only independent predictor of a pCR (p=0.049). The analysis of Ki-67 values revealed that 25% was a reasonable cutoff value for predicting the response to chemotherapy. In subgroup analysis, a higher Ki-67 value (≥25%) was a significant predictive factor for the response to neoadjuvant chemotherapy, especially in ER-negative and HER2-positive breast cancer patients. Conclusion Ki-67 expression in breast cancer tissue may be an effective factor for predicting the response to neoadjuvant chemotherapy. We suggest that a 25% level of Ki-67 expression is a reasonable cutoff value for predicting a response to chemotherapy. Moreover, Ki-67 is a useful predictive factor for pCR, especially in patients with ER-negative and HER2-positive breast cancer.

Prognostically Distinctive Subgroup in Pathologic N3 Breast Cancer

Purpose The aim of this retrospective study was to investigate whether there are prognostically different subgroups among patients with pathologic N3 (pN3) breast cancer. Methods The records of 220 patients who underwent surgery for pN3 breast cancer from January 2006 to September 2012 were reviewed. All patients received adjuvant therapy according to standard protocols. The primary outcome was disease-free survival (DFS). Results Patients were followed for a median time of 68.3 months after their primary surgery (range, 10–122 months), during which time 75 patients (34.1%) had developed disease recurrence and 48 patients (21.8%) had died. The DFS and overall survival were 67.8% and 86.1%, respectively, at 5 years. Multiple logistic regression analysis showed that young age (<35 years, p=0.009), high serum neutrophil/lymphocyte ratio (>3.0) (p=0.020), high nodal ratio (number of metastatic lymph nodes divided by number of removed nodes) (>0.65) (p=0.062), and molecular phenotype (p=0.012) were significantly associated with tumor recurrence. Tumor biological subtype was the most significant predictor of recurrence. The 5-year DFS rates in patients with hormone receptor (HR) positive and human epidermal growth factor receptor 2 (HER2) negative, HR+HER2+, HR–HER2+, and triple negative subtypes were 82%, 63%, 58%, and 37%, respectively. Conclusion Clinical outcomes of patients with extensive nodal metastasis were heterogeneous in terms of prognosis. Tumor biological subtype was the most important prognostic factor for pN3 disease. The prognosis of patients with HR+HER2– subtype in pN3 breast cancer was similar to that of patients with stage II breast cancer.

Gene expression assay and Watson for Oncology for optimization of treatment in ER-positive, HER2-negative breast cancer

Background Personalized treatment for cancer patients is a hot topic of debate, particularly the decision to initiate chemotherapy in patients with Estrogen receptor (ER)-positive, HER2-negative tumors in the early stages of breast cancer (BC). Owing to significant advancements in information technology (IT) and genomics, clinicians are increasingly attaining therapeutic goals rapidly and safely by effectively differentiating patient subsets that require chemotherapy. IBM Watson for Oncology (WFO) is a cognitive computing system employed by clinicians to provide evidence-based treatment options for cancer. WFO aids in clinical diagnosis, with claims that it may be superior in performance to human clinicians. The current study was based on the hypothesis that WFO alone cannot effectively determine whether or not chemotherapy is essential for the subset of ER-positive, HER2-negative BC patients. Patients and methods From December 2015 to July 2017, 95 patients with ER-positive, HER2- negative BC subjected to treatment were retrospectively examined using WFO, and outputs compared to real clinical practice. Treatment options were suggested by WFO, and WFO recommendations calculated both with and without data from the gene expression assay (GEA). Results WFO without GEA was unable to determine the groups of patients that did not require chemotherapy. Concordant therapeutic recommendations between real clinical practice and WFO without GEA were obtained for 23.2% of the patient group. On the other hand, the results of WFO with GEA showed good clinical applicability. Sensitivity, specificity, positive predictive and negative predictive values of WFO with GEA were 100%, 80%, 61% and 100%, respectively. Conclusions Our collective findings indicate that WFO without the gene expression assay has limited clinical utility.