Prevalence and Prognostic Significance of PIK3CA Mutation and CNV Status and Phosphorylated AKT Expression in Patients With Cervical Cancer Treated With Primary Surgery.

Currently, there are limited and conflicting reports on the prognostic utility of PIK3CA and associated pathway markers for cervical cancers treated with primary surgical management. Moreover, current studies are lacking complete characterization of adjuvant treatment with RT and/or chemotherapy. We aimed to document the prevalence, clinicopathologic, adjuvant treatment details, and prognostic value of PI3K/AKT pathway mutations and copy number variation and phosphorylated AKT status in patients with cervical cancers treated with primary surgery. A clinicopathologic review was performed on a retrospective cohort of 185 patients with cervical cancer, treated with primary surgery at a single tertiary institution. Next-generation sequencing and digital PCR was used to determine PI3K/AKT pathway mutational status and PIK3CA copy number variation, respectively, and fluorescent immunohistochemistry measured phosphorylated AKT expression. In all, 179 of 185 (96.8%) of tumors were successfully sequenced; 48 (26.8%) were positive for PI3K/AKT pathway mutations-the majority (n=37, 77.1%) PIK3CA mutations. PIK3CA mutation was associated with pathologically positive lymph nodes [12 (32%) vs. 22 (16%); P =0.022] and indication for postoperative chemoradiotherapy [17 (45.9%) vs. 32 (22.5%); P =0.004]. On multivariable analysis, PIK3CA status was not associated with overall survival ( P =0.103) or progression-free survival ( P =0.240) at 5 yrs, nor was PIK3CA copy number variation status. phosphorylated AKT ≤ median significantly predicted for progression-free survival [multivariable hazard ratio 0.39 (0.17-0.89; P =0.025)] but not overall survival ( P =0.087). The correlation of PIK3CA with pathologic positive lymph node status yet lack of association with survival outcomes may be due to the use of adjuvant postoperative therapy. PIK3CA assessment before radical hysterectomy may help identify patients with a higher risk of node-positive disease.

PIK3CA mutation and CNV status and post-chemoradiotherapy survival in patients with cervical cancer.

PURPOSE: This study aimed to describe the prognostic value of PI3K/AKT pathway mutations in a large cohort of patients with cervical cancer. EXPERIMENTAL DESIGN: Patients with pre-treatment archival specimens, diagnosed with FIGO stages IB-IVA cervical cancer between 1998 and 2014 and treated with radical, curative intent chemoradiotherapy (CRT) at a single center were identified. Mutational status was determined by next generation sequencing and PIK3CA copy number (CNV) was assessed by digital PCR. RESULTS: 190 patients with available pre-treatment tumor specimens were identified. Median OS and PFS were 57.4 and 46.0 months, respectively. A total of 161 tumors were successfully sequenced; 60 (37.3%) had PI3K/AKT pathway mutations, with 50 (30.1%) having PIK3CA hotspot mutations. PIK3CA CNV gain was noted in 79 (59.2%) of the 154 successfully analyzed. On univariate analysis, PIK3CA mutation was associated with poor OS (HR 1.73; 95% CI: 1.03-2.92; p = .037) but not PFS (HR 1.38; 0.84-2.28; p = .204). Absence of any PI3K/AKT pathway mutation was associated with improved OS (HR 1.68; 1.01-2.81; p = .046) but not PFS (HR 1.50; 0.93-2.43; p = .202). Associations were not maintained when adjusting for clinical factors. On univariate analysis, PIK3CA mutation positive, CNV normal tumors were associated with poorer OS (HR 2.55; 1.18-5.50; p = .017) and trend to worse PFS (HR 1.87; 0.90-3.83; p = .094) when compared to those with CNV gain and wildtype PIK3CA. CONCLUSIONS: PI3K/AKT pathway mutations are common in cervical cancer. Consideration of PIK3CA mutational status with CNV status may be important in predicting outcome in cervical cancer patients.

MYB-NFIB gene fusions identified in archival adenoid cystic carcinoma tissue employing NanoString analysis: an exploratory study.

BACKGROUND: Adenoid cystic carcinoma (ACC) is a slow growing salivary gland malignancy that is molecularly characterized by t(6:9)(q22-23;p23-24) translocations which predominantly result in MYB-NFIB gene fusions in nearly half of tumours. Detection of MYB-NFIB transcripts is typically performed with fresh ACC tissue using conventional RT-PCR fragment analysis or FISH techniques, which are prone to failure when only archival formalin fixed paraffin embedded (FFPE) tissue is available. The purpose of this pilot study was to evaluate the utility of NanoString probe technology for the detection of MYB-NFIB transcripts in archival ACC tissue. METHODS: A NanoString probeset panel was designed targeting the junctions of three currently annotated MYB-NFIB fusion genes as well as 5'/3' MYB probesets designed to detect MYB gene expression imbalance. RNA isolated from twenty-five archival ACC specimens was profiled and analyzed. RT-qPCR and sequencing were performed to confirm NanoString results. MYB protein expression was analyzed by immunohistochemistry. RESULTS: Of the 25 samples analyzed, 11/25 (44%) expressed a high degree of MYB 5'/3' imbalance and five of these samples were positive for at least one specific MYB-NFIB variant in our panel. MYB-NFIB variant detection on NanoString analysis was confirmed by direct cDNA sequencing. No clinical correlations were found to be associated with MYB fusion status. CONCLUSION: We conclude that the application of NanoString digital probe counting technology is well suited for the detection and quantification of MYB-NFIB fusion transcripts in archival ACC specimens.

The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer.

Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates. The Ki67 indices calculated using this method were highly concordant with manual scoring by a pathologist (Pearson's r = 0.909) and between users (Pearson's r = 0.984). We assessed the clinical validity of this method by scoring Ki67 from 328 whole-slide sections of resected early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. All patients had Oncotype DX testing performed (Genomic Health) and available Recurrence Scores. High Ki67 indices correlated significantly with several clinico-pathological correlates, including higher tumor grade (1 versus 3, P<0.001), higher mitotic score (1 versus 3, P<0.001), and lower Allred scores for estrogen and progesterone receptors (P = 0.002, 0.008). High Ki67 indices were also significantly correlated with higher Oncotype DX risk-of-recurrence group (low versus high, P<0.001). Ki67 index was the major contributor to a machine learning model which, when trained solely on clinico-pathological data and Ki67 scores, identified Oncotype DX high- and low-risk patients with 97% accuracy, 98% sensitivity and 80% specificity. Automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy, in a manner that integrates readily into the workflow of a pathology laboratory. Furthermore, automated Ki67 scores contribute significantly to models that predict risk of recurrence in breast cancer.