Network-based assessment of HDAC6 activity predicts preclinical and clinical responses to the HDAC6 inhibitor ricolinostat in breast cancer.

Inhibiting individual histone deacetylase (HDAC) is emerging as well-tolerated anticancer strategy compared with pan-HDAC inhibitors. Through preclinical studies, we demonstrated that the sensitivity to the leading HDAC6 inhibitor (HDAC6i) ricolinstat can be predicted by a computational network-based algorithm (HDAC6 score). Analysis of ~3,000 human breast cancers (BCs) showed that ~30% of them could benefice from HDAC6i therapy. Thus, we designed a phase 1b dose-escalation clinical trial to evaluate the activity of ricolinostat plus nab-paclitaxel in patients with metastatic BC (MBC) (NCT02632071). Study results showed that the two agents can be safely combined, that clinical activity is identified in patients with HR+/HER2- disease and that the HDAC6 score has potential as predictive biomarker. Analysis of other tumor types also identified multiple cohorts with predicted sensitivity to HDAC6i's. Mechanistically, we have linked the anticancer activity of HDAC6i's to their ability to induce c-Myc hyperacetylation (ac-K148) promoting its proteasome-mediated degradation in sensitive cancer cells.

Factors Associated with False Positive Results on Screening Mammography in a Population of Predominantly Hispanic Women.

Background: Potential harms of screening mammography include false positive results, such as recall breast imaging or biopsies.Methods: We recruited women undergoing screening mammography at Columbia University Medical Center in New York, New York. They completed a questionnaire on breast cancer risk factors and permitted access to their medical records. Breast cancer risk status was determined using the Gail model and a family history screener. High risk was defined as a 5-year invasive breast cancer risk of ≥1.67% or eligible for BRCA genetic testing. False positive results were defined as recall breast imaging (BIRADS score of 0, 3, 4, or 5) and/or biopsies that did not yield breast cancer.Results: From November 2014 to October 2015, 2,361 women were enrolled and 2,019 were evaluable, of whom 76% were Hispanic and 10% non-Hispanic white. Fewer Hispanic women met high-risk criteria for breast cancer than non-Hispanic whites (18.0% vs. 68.1%), but Hispanics more frequently engaged in annual screening (71.9% vs. 60.8%). Higher breast density (heterogeneously/extremely dense vs. mostly fat/scattered fibroglandular densities) and more frequent screening (annual vs. biennial) were significantly associated with false positive results [odds ratio (OR), 1.64; 95% confidence interval (CI), 1.32-2.04 and OR, 2.18; 95% CI, 1.70-2.80, respectively].Conclusions: We observed that women who screened more frequently or had higher breast density were at greater risk for false positive results. In addition, Hispanic women were screening more frequently despite having a lower risk of breast cancer compared with whites.Impact: Our results highlight the need for risk-stratified screening to potentially minimize the harms of screening mammography. Cancer Epidemiol Biomarkers Prev; 27(4); 446-53. ©2018 AACR.

Automatic Genetic Risk Assessment Calculation Using Breast Cancer Family History Data from the EHR compared to Self-Report.

Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis.