Olaparib in germline-mutated metastatic breast cancer: implications of the OlympiAD trial.

Breast cancer remains a leading cause of death worldwide. Our increased understanding of cellular mechanisms inherent to cancer has led to the development of new therapeutic targets. One such therapy is that of poly(ADP-ribose) polymerase (PARP) inhibitors, with PARP playing a key role in the repair of single stranded DNA breaks. The development of drugs able to inhibit PARP led to their investigation in tumors that have defective DNA repair, including that of BRCA1/2-associated cancers. The PARP inhibitor Olaparib, has recently been evaluated in the Phase III OlympiAD trial, and demonstrated a significant progression-free survival advantage in patients with HER2-negative metastatic breast cancer and a germline BRCA-mutation. This article will review the findings and potential implications of the trial.

A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers.

BACKGROUND: Multispectral microscopy and multiple staining can be used to identify cells with distinct immunohistochemical (IHC) characteristics. We present here a method called hypothesized interaction distribution (HID) analysis for characterizing the statistical distribution of pair-wise spatial relationships between cells with particular IHC characteristics and apply it to clinical data. MATERIALS AND METHODS: We retrospectively analyzed data from a study of 26 follicular lymphoma patients in which sections were stained for CD20 and YY1. HID analysis, using leave-one-out validation, was used to assign patients to one of two groups. We tested the null hypothesis of no difference in Kaplan-Meier survival curves between the groups. RESULTS: Shannon entropy of HIDs assigned patients to groups that had significantly different survival curves (median survival was 7.70 versus 110 months, P = 0.00750). Hypothesized interactions between pairs of cells positive for both CD20 and YY1 were associated with poor survival. CONCLUSIONS: HID analysis provides quantitative inferences about possible interactions between spatially proximal cells with particular IHC characteristics. In follicular lymphoma, HID analysis was able to distinguish between patients with poor versus good survival, and it may have diagnostic and prognostic utility in this and other diseases.

YY1 expression predicts favourable outcome in follicular lymphoma.

AIMS: Follicular lymphoma is the second most common type of non-Hodgkin's lymphoma worldwide. The majority of patients diagnosed as having follicular lymphoma have an indolent form of the disease, but a subset of patients have aggressive disease with a shorter survival interval. Optimal treatment stratification requires a distinction between these two groups, though there are presently few prognostic biomarkers available. The transcription factor YY1 has been shown to play an important role in cancer biology. The authors have previously reported a correlation of Yin Yang 1 (YY1) mRNA levels with survival in FL. This study aimed to validate these findings at the protein level. METHODS: Quantification of YY1 protein was carried out on 26 FL biopsy samples using quantum dot labelled immunohistochemistry. Ki-67 percentage, grade, YY1 protein levels and T cell and macrophage markers were used in a multivariable analysis for survival in 26 cases of FL. RESULTS: Expression levels of YY1 protein were significantly increased in patients alive in comparison with those dead after follow-up (p ≤ 0.025). Kaplan-Meier analysis showed association of higher expression levels of YY1 with longer survival (p ≤ 0.01) (hazard ratio 3.33, 95% CI 1.26 to 8.85). The multivariable analysis identified YY1 protein level as the strongest predictor of outcome (p ≤ 0.018), with none of the other markers being significantly associated with outcome. CONCLUSION: These results support the prognostic utility of YY1 in FL, indicating potential as a clinical biomarker.