Ovarian cancer (OC) is the single most deadly form of women's cancer, typically presenting as an advanced disease at diagnosis in part due to a lack of known risk factors or genetic markers of risk. The KRAS oncogene and altered levels of the microRNA (miRNA) let-7 are associated with an increased risk of developing solid tumors. In this study, we investigated a hypothesized association between an increased risk of OC and a variant allele of KRAS at rs61764370, referred to as the KRAS-variant, which disrupts a let-7 miRNA binding site in this oncogene. Specimens obtained were tested for the presence of the KRAS-variant from nonselected OC patients in three independent cohorts, two independent ovarian case-control studies, and OC patients with hereditary breast and ovarian cancer syndrome (HBOC) as well as their family members. Our results indicate that the KRAS-variant is associated with more than 25% of nonselected OC cases. Further, we found that it is a marker for a significant increased risk of developing OC, as confirmed by two independent case-control analyses. Lastly, we determined that the KRAS-variant was present in 61% of HBOC patients without BRCA1 or BRCA2 mutations, previously considered uninformative, as well as in their family members with cancer. Our findings strongly support the hypothesis that the KRAS-variant is a genetic marker for increased risk of developing OC, and they suggest that the KRAS-variant may be a new genetic marker of cancer risk for HBOC families without other known genetic abnormalities. Cancer Res; 70(16); 6509-15. ©2010 AACR.

he prospect of improved clinical outcomes and more efficient health systems has fueled a rapid rise in the development and evaluation of AI systems over the last decade. Because most AI systems within healthcare are complex interventions designed as clinical decision support systems, rather than autonomous agents, the interactions among the AI systems, their users and the implementation environments are defining components of the AI interventions' overall potential effectiveness. Therefore, bringing AI systems from mathematical performance to clinical utility needs an adapted, stepwise implementation and evaluation pathway, addressing the complexity of this collaboration between two independent forms of intelligence, beyond measures of effectiveness alone 1 . Despite indications that some AI-based algorithms now match the accuracy of human experts within preclinical in silico studies 2 , there

After repeated media attention in 2013 due to the Angelina Jolie disclosure and the Supreme Court decision to ban gene patents, the demand for cancer genetic counseling and testing services has never been greater. Debate has arisen regarding who should provide such services and the quality of genetics services being offered. In this ongoing case series, we document 35 new cases from 7 states (California, Connecticut, Florida, Georgia, Missouri, Pennsylvania, and Utah) and the District of Columbia of adverse outcomes in cancer genetic testing when performed without the involvement of a certified genetic counselor. We identified 3 major themes of errors: wrong genetic tests ordered, genetic test results misinterpreted, and inadequate genetic counseling. Patient morbidity and mortality were an issue in several of these cases. The complexity of cancer genetic testing and counseling has grown exponentially with the advent of multigene panels that include rare genes and the potential for more variants of uncertain significance. We conclude that genetic counseling and testing should be offered by certified genetics providers to minimize the risks, maximize the benefits, and utilize health care dollars most efficiently.