Citations

Purpose To identify approaches to operationalizing the development of competence in Accreditation Council for Graduate Medical Education (ACGME) milestones. Method The authors reviewed all 25 “Milestone Project” documents available on the ACGME Web site on September 11, 2013, using an iterative process to identify approaches to operationalizing the development of competence in the milestones associated with each of 601 subcompetencies. Results Fifteen approaches were identified. Ten focused on attributes and activities of the learner, such as their ability to perform different, increasingly difficult tasks (304/601; 51%), perform a task better and faster (171/601; 45%), or perform a task more consistently (123/601; 20%). Two approaches focused on context, inferring competence from performing a task in increasingly difficult situations (236/601; 29%) or an expanding scope of engagement (169/601; 28%). Two used socially defined indicators of competence such as progression from “learning” to “teaching,” “leading,” or “role modeling” (271/601; 45%). One approach focused on the supervisor’s role, inferring competence from a decreasing need for supervision or assistance (151/601; 25%). Multiple approaches were often combined within a single set of milestones (mean 3.9, SD 1.6). Conclusions Initial ACGME milestones operationalize the development of competence in many ways. These findings offer insights into how physicians understand and assess the developmental progression of competence and an opportunity to consider how different approaches may affect the validity of milestone-based assessments. The results of this analysis can inform the work of educators developing or revising milestones, interpreting milestone data, or creating assessment tools to inform milestone-based performance measures.

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low‐density lipoprotein (LDL), and high‐density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP‐CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20–1.79, p = 1.68 × 10−4). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92–1.18, p = 0.49), 0.94 (95% CI: 0.84–1.05, p = 0.27), and 0.98 (95% CI: 0.85–1.12, p = 0.75) respectively. A genetic risk score for 3‐hydoxy‐3‐methylglutaryl‐coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR = 0.69, 95% CI: 0.49–0.99, p = 0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia.

Abstract Clinical genetic testing panels are broadly used to gather information about cancer predisposition in individuals with personal and/or family history of breast cancer. However, the involvement of several of the genes on clinical testing panels in predisposition to breast cancer, such as MRE11A and RAD50, has recently come into question. In addition, accurate risk estimates for breast and other cancer are not well defined for the majority of genes on testing panels. We studied 60,000 women diagnosed with breast cancer who were tested for germline cancer predisposing mutations using hereditary cancer gene panels. Information on personal and family cancer history, age of diagnosis, and ethnicity of patients was obtained from test requisition forms. Greater than 90% met National Comprehensive Cancer Network HBOC testing criteria. To estimate gene-specific risks for breast cancer, case-control analyses were performed comparing the frequencies of pathogenic mutations from Caucasian cancer cases with frequencies from Caucasian, non-Finnish, non-TCGA controls from the Exome Aggregation Consortium (ExAC) database. Mutations were detected in 9% of breast cancer patients. Twelve genes displayed a significant association (p<0.05) with breast cancer. Nine of these genes, including ATM, RAD51D, NF1, and MSH6, were associated with moderate risk (RR>2.0) of breast cancer and three genes (BRCA1, BRCA2, PALB2) were associated with high risk (RR>5.0) of breast cancer. Cumulative age-dependent risk models were developed for each gene. This large clinical testing dataset of 60,000 women with breast cancer provides useful data for many predisposition genes previously lacking risk estimates, and should prove useful for clinical risk management of patients with inherited mutations in these genes. Citation Format: Couch FJ, Hu C, Lilyquist J, Shimelis H, Akinhanmi M, Na J, Polley EC, Hart SN, McFarland R, LaDuca H, Huether R, Goldgar DE, Dolinsky JS. Breast cancer risks associated with mutations in cancer predisposition genes identified by clinical genetic testing of 60,000 breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr S2-01.

Abstract Clinical genetic testing of individuals with a personal or family history of breast and ovarian cancer using panels for BRCA1/2 and other candidate cancer predisposition genes has become routine clinical practice. Several of the genes on hereditary cancer testing panels have been strongly associated with specific subtypes of breast cancer. In particular, individuals with germline mutations in BRCA1 predominantly develop estrogen receptor (ER)-negative and triple negative (TN) (estrogen receptor negative, progesterone receptor negative, HER2 negative) breast tumors. In contrast, CHEK2 and ATM mutations have been associated with ER-positive breast cancer. In this study, associations between mutations in panel genes and breast cancer subtypes were evaluated. A cohort of 60,000 breast cancer patients tested for germline cancer predisposing mutations using hereditary cancer gene panels was utilized. Information on personal and family cancer history, age of diagnosis, tumor pathology, and ethnicity of patients was obtained from test requisition forms or by follow up with ordering health care providers. Mutations in each gene were combined into four histological subtypes (triple negative; HER2 positive; ER-positive,HER2-positive; and ER-positive,HER2 negative). Associations for each subtype were estimated by case-control analyses comparing the frequencies of pathogenic mutations in each subtype with frequencies from non-TCGA controls from the Exome Aggregation Consortium (ExAC) database. In addition, case-case analyses were conducted to assess enrichment of gene mutations in specific breast cancer subtypes. Among the observed associations between genes and breast cancer subtypes, mutations in CHEK2 and ATM were highly enriched in luminal breast cancers and BARD1 was specifically associated with TN breast cancer. Refining the spectrum of pathological correlates with mutations in hereditary breast cancer genes will aid gene specific cancer risk management, and may accelerate the development of novel gene-specific therapeutic interventions. Citation Format: Couch FJ, Lilyquist J, Na J, Hu C, Polley EC, Shimelis H, Akinhanmi M, McFarland R, LaDuca H, Goldgar DE, Dolinsky JS. Associations between breast cancer subtypes and mutations in cancer predisposition genes identified by clinical genetic testing of breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-09-03.

Abstract Background: The primary mechanism by which tamoxifen (Tam) and its metabolites exert their biologic effects is through estrogen receptor (ER) binding and inhibition of ER signaling. We and others demonstrated that endoxifen (Endx) has greater antitumor activity in vitro and in vivo compared to Tam and the first-in-human Endx phase I study demonstrated its antitumor activity in patients with prior progression on Tam (Goetz SABC 2015). PKCs are a family of serine/threonine-specific protein kinases that regulate signaling pathways involved in cell proliferation and tumorigenic transformation. Our prior protein docking studies suggested endoxifen may be a substrate for PKCs. Here we report the effects of Tam and Endx on PKCβ1 binding, kinase activity, as well as interactions between PKCβ1 and ERα. Methods: Surface Plasmon Resonance (SPR, Biacore T200, GE Healthcare) was used to evaluate binding of Tam, N-desmethyl Tam (NDMT), 4-HT, and Endx to PKCβ1 and PKCβ2. The effects of Tam and Endx on PKCβ1 kinase activity were determined. Proliferation and colony formation in MCF7 parental and PKCβ1 overexpressing cells were evaluated. siRNA silencing was used to knockdown PKCβ1 expression in the following cells: MCF7 aromatase expressing cells that were either sensitive (MCF7/AC1) or resistant to letrozole (MCF7/AC1 L-resistant); T47D; and MDA-MB-361. Coimmunoprecipitation assay and DUOlink in situ proximity ligation were used to investigate the interaction between PKCβ1 and ERα. Results: Endx more potently inhibited PKCβ1 kinase activity compared to Tam ( IC50 350 nM vs 47.8 μM ) with KDs for PKCβ1 binding as follows: Endx (100 nM ), Tam ( 2 μM ), 4-HT ( 2 μM ) and NDMT (> 7 μM ). None of the SERMs exhibited PKCβ2 binding. In the MCF7/AC1 and MCF7/AC1 L-resistant cells, PKCβ1 knockdown resulted in ERα degradation and potently inhibited cell proliferation. These results were confirmed in T47D and MDA-MB-361 cells. Notably, PKCβ1 knockdown in MCF7/AC1 cells resulted in significantly greater E2 induced proliferation comparing siRNA knockdown vs. control. To further explore these effects, we evaluated the effects of PKCβ1 overexpression in MCF7 cells and demonstrated that PKCβ1 overexpression reduced cell proliferation and colony formation compared to parental MCF-7 cells without affecting ERα protein stability. Coimmunoprecipitation assays in transient transfected MCF-7 cells with exogenous PKCβ1 as well as PKCβ1 expressing MDA-MB-231 cells transiently or stably transfected with ERα demonstrated PKCβ1 and ERα interaction, with confirmation by Duolink assay that this interaction occurs in the cytoplasm. Conclusions: Our findings demonstrated that endoxifen binds and inhibits PKCβ1 at relevant concentrations achieved in the endoxifen clinical trial studies. PKCβ1 interacts with cytoplasmic ERα and PKCβ1 knockdown inhibits cell proliferation and enhances ERα turnover. However, in PKCβ1 overexpressing cells, PKCβ1 may exhibit tumor suppressive effects. These data suggest a complex interaction between PKCβ1 and ERα and that endoxifen's effects on PKCβ1 may alter drug response of endocrine therapy. Further studies are ongoing to characterize the role of PKCβ1 and its role in ER biology and response to endoxifen. Citation Format: Guo C, Kuffel MJ, Kudgus RA, Huang Z, Bode AM, Cheng J, Suman VJ, Reid JM, Bruinsma ES, Subramaniam M, Ames MM, Hawse JR, Goetz MP. Identification and characterization of a novel endoxifen substrate, PKCβ1, and its interaction with the estrogen receptor [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-08-03.

463 Background: The genomic assessment of cancer has been revolutionized by next-generation sequencing and is increasingly being applied in the clinic to guide therapeutic decision-making. Time to reporting of results, specimen quantity, and analyte quality have constrained initial clinical applications to gene panels and whole exome based strategies. Methods: Patients underwent surgical resection, excisional or core biopsies, or bone marrow biopsy. Samples were analyzed by whole genome or exome sequencing and RNA sequencing, bioinformatics analysis, and therapeutic target prioritization by a multi-disciplinary Clinical Genomics Board. All prioritized targets were CLIA validated using Sanger sequencing, RT-qPCR, FISH, or IHC as appropriate. Treatment was delivered using off-label FDA approved drugs, clinical trials, or single patient INDs. Results: We have enrolled 40 patients with advanced, treatment-refractory cancers of whom sequencing data is available on 33. The initial 6 patients were evaluated in a non-CLIA pilot phase and 27 in the CLIA enabled phase. Upon availability of the initial report, identified targets of putative therapeutic relevance were then prioritized by the CGB in 22/27 patients (81%) for subsequent CLIA validation. Eleven patients have been treated with genomically selected therapy with partial response in 3/10 assessed patients. A testicular cancer patient had aberrations in two testes specific genes, a copy number gain in TSSK6 and a novel gene fusion between thyroid hormone receptor associated protein 3 (THRAP3) and Tektin 2 (TEKT2). Additionally, a case of papillary renal cell carcinoma had an amplification of YAP1 and a previously unreported P287T mutation in CCND1, suggesting potential benefit with a CDK4/6 inhibitor. Treatment is ongoing and results will be reported. Conclusions: Integrated whole genome analysis in a CLIA setting is feasible. Integration of SNV, copy number and transcriptional data may allow for selection of putative driver genes to enhance targeted therapy decisions. Barriers for future broader implementation include the need for reduced time from biopsy to report and availability of therapies.

CRA1002 Background: Weekly P is superior to q 3 week (wk) dosing, and adding B improves progression free survival (PFS) (E2100). Ix is a potent epothilone that can be effective after microtubule inhibitor resistance. NP is a novel albumin-bound formulation of P with promising activity in the first-line MBC setting. In this phase III trial, the efficacy of weekly Ix or NP is compared to P, in combination with B in patients (pts) with chemotherapy (CTX) naïve MBC. Toxicity including >Grade 2 sensory neuropathy (SN) is compared to P. Methods: Pts were randomized 1:1:1 to receive P (90 mg/m2), Ix (16 mg/m2) or NP (150 mg/m2) on a 3 wk on, 1 wk off schedule, stratified by prior adjuvant taxane use and hormone receptor status. B was initially given to all pts, but became optional in 3/2011 and was added to stratification. The primary end point of PFS is defined as time from randomization to progression or all-cause death. With a target N=900 pts, the study was powered to detect a hazard ratio (HR) of 1.36 (median PFS 10 vs 13.6 mos). Eligibility included no prior CTX for MBC, >12 mos from adjuvant P and measurable disease. Results: 799 pts were enrolled between 11/08-11/11 (283 to P, 271 to NP, 245 to Ix); 98% received B. 72% had ER+ disease, 44% received adjuvant P. At the 1st interim analysis (165 events) the comparison of Ix to P crossed the futility boundary (FB) and accrual to Ix was closed. At the 2nd interim analysis (236 events), NP to P crossed the FB and the study was closed on 11/30/11. Median PFS was 10.4, 9.6 and 7.6 mos for P, NP and Ix, with HRs (95% CIs) of 0.94 (0.73-1.22) and 0.66 (0.51-0.84) for P to NP and Ix respectively. Grade 2+ SN was 48% for NP, 44% for Ix and 37% for P; Grade 3+ hematologic toxicity was 49% for NP, 20% for Ix, and 12% for P. Conclusions: In pts with CTX naive MBC, both NP and Ix are highly unlikely to be superior to P for PFS (when all are combined with B), and in combination with B, weekly P is the better tolerated drug. Toxicity including SN was greater in each experimental arm compared to P. Updated data will be presented, and correlative studies will be reported at a future date.

11 Background: Currently there are no serum markers of response to AA. We performed a proteome based analysis of serum from prostate cancer patients, followed by mapping of candidate markers to networks based on known molecular interactions in Ingenuity Knowledge Base (IKB). Methods: Isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) was performed in serum of 3 non-localized prostate cancer cohorts. The first cohort included 15 paired untreated hormone-sensitive “pre AA” and 3-month “post AA” specimens; the second included 10 “early AA failure” (median failure time: 11 months) and the third included 10 “late AA failure” specimens (median failure time: 95 months). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post AA proteomes and (ii) post AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. To facilitate biological interpretation of multiple candidates identified in the comparisons, IPA was used. Candidate markers implicated in IPA networks with statistical significance were pursued in a second, independent patient cohort for association with time to AA failure using univariate Cox regression analysis. Results: Median PSA for pre/post AA first cohort were 3.15 and 0.29 ng/ml. Median PSA for the second and third cohorts were 27.3 and 4.3 ng/ml. Between post AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. Network enrichment analysis of the 47 proteins by IPA identified four interaction networks (p<0.01), one of which highlighted a role for 17-β-estradiol (E1). Gas chromatography used for measuring 3-month post AA initiation serum E1, estrone (E2) and testosterone levels (N=38) detected high E1, E2 levels associated with longer time to AA failure (P=0.07 for E1; P=0.08 for E2) in the independent cohort. Conclusions: A global proteomic analysis identified post AA initiation serum E1, E2 levels as potential response markers, which needs validation.

36 Background: Following radical prostatectomy (RP), 30-40% of patients have adverse pathology and are deemed at high risk for metastatic progression. The objective of this study was to validate the ability of Decipher, a genomic classifier (GC), to improve prediction of metastatic disease progression compared with clinical variables in order to better identify candidates for therapy intensification. Methods: A previously developed 22-feature GC model was validated in a prospectively designed case-cohort study of a clinically high-risk population (i.e., with one or more adverse pathological features) of 1,010 RP patients treated at Mayo Clinic between 2000-2006. A random sample of 20% of the cohort was subjected to microarray analysis and GC scores were generated for 219 patients. The primary endpoint, the c-index for predicting metastatic disease progression (i.e., positive bone or CT scans) was evaluated in a blinded analysis. Cox modeling and decision curve analyses were used to compare the performance of GC to individual clinical variables and prediction models. Results: GC had a c-index 0.79 (95% CI 0.71-0.86) that was significantly better than any single clinical variable. Cumulative incidence curves in the cohort showed that 72% of patients had low GC scores with only 3% and 6% incidence of metastatic disease at 5 and 10 years post RP. In contrast, for the 28% of patients with high GC scores, the cumulative incidence was 17% and 25% at 5 and 10 years post RP. Decision curve analysis showed that the GC model had higher overall net benefit compared to clinical variables over a wide range of ‘decision-to-treat’ thresholds for risk of metastasis. In multivariable modeling with clinicopathologic variables, GC remained the only significant independent predictor of metastasis (HR=1.51, for each 0.1 unit increment, p<0.001). Conclusions: GC can better predict metastatic disease progression compared with clinical variables and may select among patients with adverse pathology a majority that is in fact at low risk for metastasis.