Executive Summary PURPOSE With prospective clinical sequencing of tumors emerging as a mainstay in cancer care, there is an urgent need for a clinical support tool that distills the clinical implications associated with specific mutation events into a standardized and easily interpretable format. To this end, we developed OncoKB, an expert-guided precision oncology knowledge base. METHODS OncoKB annotates the biological and oncogenic effect and the prognostic and predictive significance of somatic molecular alterations. Potential treatment implications are stratified by the level of evidence that a specific molecular alteration is predictive of drug response based on US Food and Drug Administration (FDA) labeling, National Comprehensive Cancer Network (NCCN) guidelines, disease-focused expert group recommendations and the scientific literature. RESULTS To date, over 3000 unique mutations, fusions, and copy number alterations in 418 cancer-associated genes have been annotated. To test the utility of OncoKB, we annotated all genomic events in 5983 primary tumor samples in 19 cancer types. Forty-one percent of samples harbored at least one potentially actionable alteration, of which 7.5% were predictive of clinical benefit from a standard treatment. OncoKB annotations are available through a public web resource (http://oncokb.org/) and are also incorporated into the cBioPortal for Cancer Genomics to facilitate the interpretation of genomic alterations by physicians and researchers. CONCLUSION OncoKB, a comprehensive and curated precision oncology knowledge base, offers oncologists detailed, evidence-based information about individual somatic mutations and structural alterations present in patient tumors with the goal of supporting optimal treatment decisions.

We thank Dr Giral and colleagues for their comments on our recent study of lipoprotein(a) [Lp(a)].1 The quantitative assessment of Lp(a) has historically proven challenging in part because of the (1) highly heterogeneous number of Kringle-IV type-2 repeats (and thus molecular weight), and (2) lack of standardized methodology and calibration across published studies. A 2002 National Heart, Lung, and Blood Institute consensus workshop that recommended use of isoform size-independent assays that express Lp(a) concentrations in terms of particle number (nmol/L) rather than total mass (mg/dL) and provided control samples for calibration served as a major advance in the field.2 In accordance with these standards, our study reported Lp(a) concentrations in nmol/L, and did not formally assess cholesterol mass associated with Lp(a) particles.The Friedewald formula for calculating LDL cholesterol, which was used in the JUPITER study when triglycerides were <400 mg/ dL, remains the current standard for clinical use but has clear limitations as discussed by Dr Giral and colleagues. Calculated LDL cholesterol reflects variable contributions from intermediate-density lipoproteins, low-density lipoproteins, and Lp(a) particles.3 In part to address this, we performed statistical models that either did or did not include calculated LDL cholesterol as a covariable, and Lp(a) was a significant determinant of residual risk in JUPITER regardless of LDL cholesterol inclusion in the models.

Background Lipoprotein(a) [Lp(a)] is an LDL-like particle largely independent of known risk factors and predictive of cardiovascular disease (CVD). Statins may offset the risk associated with elevated Lp(a), but it is unknown if Lp(a) is a determinant of residual risk in the setting of low LDL-cholesterol after potent statin therapy. Methods and Results Baseline and on-treatment Lp(a) concentrations were assessed in 9,612 multiethnic JUPITER trial participants before and after random allocation to rosuvastatin 20 mg/day or placebo, with outcomes reported for whites (N=7,746). Lp(a) concentrations (nmol/L) were highest in blacks (median [25th–75th percentile] 60 [34–100]), then Asians (38 [18–60]), hispanics (24 [11–46]), and whites (23 [10–50]); p<0.001. While the median change in Lp(a) with rosuvastatin and placebo was zero, rosuvastatin nonetheless resulted in a small but statistically significant positive shift in the overall Lp(a) distribution (p<0.0001). Baseline Lp(a) concentrations were associated with incident CVD: adjusted hazard ratio (HR) per 1-SD increment in Ln[Lp(a)] 1.18 (95%CI 1.03 – 1.34; p=0.02). Similarly, on-statin Lp(a) concentrations were associated with residual risk of CVD: adjusted HR 1.27 (95%CI 1.01 – 1.59; p=0.04), which was independent of LDL-cholesterol and other factors. Rosuvastatin significantly reduced incident CVD among participants with baseline Lp(a)≥median (HR 0.62, 0.43–0.90) and Lp(a)

Purpose: Fragile X syndrome is caused by expansion and methylation of a CGG tract in the 5Ј untranslated region of the FMR1 gene. The estimated frequency of expanded alleles (Ն55 repeats) in the United States is 1:257-1:382, but these estimates were not calculated from unbiased populations. We sought to determine the frequency of fragile X syndrome premutation (55-200 repeats) and full mutation (Ͼ200 repeats) alleles in nonselected, unbiased populations undergoing routine carrier screening for other diseases. Methods: A previously validated laboratory-developed test using triplet-primed polymerase chain reaction was used to detect premutation and full mutation alleles in an unselected series of 11,759 consecutive cystic fibrosis carrier screening samples and 2011 samples submitted for screening for genetic diseases prevalent among the Ashkenazi Jewish population. Results: Premutations were identified in 48 cystic fibrosis screening samples (1:245) and 15 samples (1:134) from the Ashkenazi Jewish population. Adjusted for the ethnic mix of the US population and self-reported ethnicity in our screening population, the estimated female premutation carrier frequency in the United States was 1:178. The calculated frequency of full mutation alleles was 1:3335 overall, and the calculated premutation frequency in males was 1:400. Based on frequency of larger, Ն70 repeat alleles, and reported penetrance, the calculated fragile X-associated tremor and ataxia syndrome, and fragile X-associated primary ovarian insufficiency frequencies is 1:4848 and 1:3560, respectively. Conclusion: Our calculated fragile X syndrome carrier rate is higher than previous estimates for the US population and warrants further consideration of population-based carrier screening. Genet Med 2011:13(1): 39 -45.