Correlation between circulating cell-free PIK3CA tumor DNA levels and treatment response in patients with PIK3CA-mutated metastatic breast cancer.

Liquid biopsies focusing on the analysis of cell-free circulating tumor DNA (ctDNA) may have important clinical implications for personalized medicine, including early detection of cancer, therapeutic guidance, and monitoring of recurrence. Mutations in the oncogene, PIK3CA, are frequently observed in breast cancer and have been suggested as a predictive biomarker for PI3K-selective inhibitor treatment. In this study, we analyzed the presence of PIK3CA mutations in formalin-fixed, paraffin-embedded, metastatic tissue and corresponding ctDNA from serum of patients with advanced breast cancer using a highly sensitive, optimized droplet digital PCR (ddPCR) assay. We found 83% of patients with PIK3CA mutation in the metastatic tumor tissue also had detectable PIK3CA mutations in serum ctDNA. Patients lacking the PIK3CA mutation in corresponding serum ctDNA all had nonvisceral metastatic disease. Four patients with detectable PIK3CA-mutated ctDNA were followed with an additional serum sample during oncological treatment. In all cases, changes in PIK3CA ctDNA level correlated with treatment response. Our results showed high concordance between detection of PIK3CA mutations in tumor tissue and in corresponding serum ctDNA and suggest that serum samples from patients with advanced breast cancer and ddPCR may be used for PIK3CA mutation status assessment to complement imaging techniques as an early marker of treatment response.

Immunohistochemical Ki-67/KL1 double stains increase accuracy of Ki-67 indices in breast cancer and simplify automated image analysis.

BACKGROUND: Ki-67 immunohistochemical expression is a prognostic and predictive marker in many breast cancer studies. Instead of the conventional time-consuming score of Ki-67 single stains associated with low reproducibility, Ki-67/KL1 double stains may facilitate fast, repeatable quantification by digital image analysis. This study aims to detect the difference in accuracy and precision between manual indices of single and double stains, to develop an automated quantification of double stains, and to explore the relation between automated indices and tumor characteristics when quantified in different regions: hot spots, global tumor areas, and invasive fronts. MATERIALS AND METHODS: Paraffin-embedded, formalin-fixed tissue from 100 consecutive patients with invasive breast cancer was immunohistochemically stained for Ki-67 and Ki-67/KL1. Ki-67 was manually scored in different regions by 2 observers and automated image analysis. RESULTS: Indices were predominantly higher for single stains than double stains (P≤0.002), yet the difference between observers was statistically significant (P<0.001) for both stains. The Pearson correlation coefficient for manual and automated indices ranged from 0.69 to 0.85 (P<0.001). Hot spots were slightly superior to other regions when correlating automated indices with tumor characteristics, for example, tumor size (P<0.001), grade (P=0.009), and estrogen receptor status (P=0.04). CONCLUSIONS: Although precision was unsatisfactory for manual indices of both stains, Ki-67 should be quantified on double stains to reach a higher accuracy. Automated indices correlated well with manual estimates and tumor characteristics, and they are thus possibly valuable tools in future exploration of Ki-67 in breast cancer.