Citations

Abstract Oral cyclophosphamide and prednisone is a convenient regimen in relapsed and refractory multiple myeloma (MM), with a partial response (PR) rate of 40% and median progression-free survival of 19 months in our retrospective analysis of patients in first or second relapse after autologous stem cell transplantation (ASCT) (Trieu Y, et al, Mayo Clin Proc2005; 80: 1582). We sought to enhance the efficacy of this regimen by adding oral lenalidomide (Revlimid®), a potent anti-myeloma agent, in a phase I-II trial. The CPR regimen consisted of cyclophosphamide on days 1, 8 and 15, lenalidomide on days 1–21, and prednisone 100 mg every other day in a 28-day cycle. ASA 81 mg/day was given to all patients (pts) as prophylaxis for DVT. Three dose levels were evaluated using a 3 by 3 dose escalation design. Between 11/2007–07/2008, 15 pts with relapsed/refractory MM were entered onto study. Median age was 60 (45–78) years and 60% were male. Immunoglobulin subtype was IgGκ:λ in 10:1; IgA κ:λ in 2:1 and κ light chain in 1. Median number of prior regimens was 2 (1–3) and 14 had undergone previous ASCT, including double transplants in 2 pts. Prior therapy also included thalidomide in 3 (20%) and bortezomib in 6 (40%). FISH cytogenetics were available in 9, but none had 13q deletion, t(4;14) or p53 deletion. At the time of protocol entry, median β2-microglobulin level was 222 (92–325) nm/L, albumin 38 (35–46) g/L, creatinine 78 (50–100) μmol/L, platelet count 230 (93–318) x 109/L and ANC 2.5 (1.9–9.0) x 109/L. Protocol treatment is summarized in Table 1. Dose level N Cyclophosphamide dose (mg/m2) Lenalidomide dose (mg) Prednisone dose (mg) Median # cycles given 1 3 150 15 100 9 2 3 150 25 100 6 3 6 300 25 100 4 3 (expanded) 3 300 25 100 1 Dose limiting toxicity was not observed during cycle 1 at any of the dose levels and the maximum tolerated dose of this regimen has not yet been reached at the highest dose level planned; all pts remain on active therapy. Grade 3/4 thrombocytopenia was seen in 1 pt (cohort 2) and neutropenia in 4 pts (1 in cohort 1, 1 in cohort 2 and 2 in cohort 3) and were managed with dose reduction and/or growth factor support. No episodes of febrile neutropenia occurred in any pt. Only 1 pt experienced varicella zoster; routine antiviral prophylaxis was not used. Other grade 3/4 non-hematologic toxicities were uncommon and included abdominal pain/bacteremia in 1 pt in cohort 1, hypokalemia in 1 pt in cohort 2, and DVT in 1 pt in cohort 3. Mild grade 1/2 constipation (47%), muscle cramps (33%) and fatigue (33%) were also noted. To date, best response includes the following: dose level 1 (1 near complete remission [nCR], 2 PR); dose level 2 (3 PR); dose level 3 (4 PR, 2 minimal response [MR]); expanded cohort 3 (1 MR, 2 too early). We conclude: 1) the combination of full doses of the agents in CPR can be given in a 28-day cycle with minimal toxicity; 2) the overall response rate (nCR + PR + MR) in 13 evaluable pts to date is 87%; 3) no pts have progressed in this preliminary analysis; 4) longer follow-up is required to assess the long-term efficacy of this regimen.

BackgroundFine needle aspiration (FNA) is commonly used for the preoperative evaluation of salivary gland tumors. Tumor grade is a key factor influencing clinical management of salivary gland carcinomas (SGCs). To assess the ability to grade nonbasaloid SGCs in FNA specimens, an international panel of cytopathologists convened to review and score SGC cases.MethodsThe study cohort included 61 cases of primary SGC from the pathology archives of 3 tertiary medical centers. Cases from 2005 to 2016 were selected, scanned, and digitized. Nineteen cytopathologists blinded to the histologic diagnosis reviewed the digitized cytology slides and graded them as low, high, or indeterminate. The panelists' results were then compared to the tumor grades based on histopathologic examination of the corresponding resection specimens.ResultsAll but 2 of the 19 (89.5%) expert panelists review more than 20 salivary gland FNAs per year; 16 (84.2%) of the panelists work at academic medical centers, and 13 (68.4%) have more than 10 years' experience. Participants had an overall accuracy of 89.4% in the grading of SGC cases, with 90.2% and 88.3% for low‐ and high‐grade SGC, respectively. Acinic cell carcinoma and mucoepidermoid carcinoma had the highest degree of accuracy, while epithelial‐myoepithelial carcinoma and salivary duct carcinoma had the lowest degree of accuracy. As expected, the intermediate‐grade SGC cases showed the greatest variability (high‐grade, 42.1%; low‐grade, 37.5%, indeterminate, 20.4%).ConclusionThis study confirms the high accuracy of cytomorphologic grading of primary SGC by FNA as low‐ or high‐grade. However, caution should be exercised when a grade cannot be confidently assigned.

Abstract Germline mutations in several cancer predisposition genes included in hereditary multigene testing panels have been associated with increased breast cancer risk. However, estimates of breast cancer risks for each gene have in large part been derived from studies of high-risk populations enriched for family history of breast and ovarian cancer, young age of breast cancer diagnosis, or founder mutations. The breast cancer risks associated with mutations in many of these genes in the general population remain to be clearly defined. As clinical hereditary cancer genetic testing is already provided to many women at increased risk and may soon be offered to all breast cancer patients, population-based risk estimates associated with predisposition gene mutations will be needed for appropriate clinical management of mutation carriers. The “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) consortium of 17 cohort-based case-control, population-based case-control, and family studies focused on estimation of population-based breast cancer risks and penetrance analysis for mutations in known and candidate breast cancer predisposition genes. Germline DNA from 39486 breast cancer cases and 35868 matched controls was subjected to dual bar-coded QIAseq multiplex amplification of 1733 target regions in 37 predisposition genes. Products from sets of 768 samples were pooled and sequenced in each lane of a HiSeq 4000 system. Mutations were called by GATK Haplotype Caller and Verdict. High quality sequence data was obtained for 99.3% of target regions. Here we report on results from 34741 population-based breast cancer cases and 32728 matched unaffected controls. The mean age of breast cancer diagnosis for cases was 61.2 years and mean age for controls was 61.1 years. Overall, 20.9% of cases and 14.3% of controls had a family history of breast cancer. Furthermore, 74.3% of cases and 75.8% of controls were non-Hispanic white, whereas 13.3% of cases and 15.3% of controls were African American. Among cases with tumor information available, 81.7% were ER-positive and 7.7% were triple negative breast cancers (TNBC). We assessed mutation frequencies in 24 genes including 12 established breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, RAD51C, RAD51D, andTP53). The overall mutation frequency was 6.2% in cases and 2.7% in controls. Case-control association analysis after adjusting for study, age, family history of breast cancer, and race/ethnicity showed that BRCA1(OR=7.45; 95%CI:5.24-10.95) and BRCA2(OR=5.31; 95%CI:4.15-6.88) were associated with high risks of breast cancer in the general population. However, PALB2mutations were only associated with moderate risks (OR=3.63; 95%CI:2.57-5.26). ATMmutations conferred attenuated risks (OR=1.83; 95%CI:1.47-2.28) relative to studies of high-risk families or young onset breast cancers. NBNmutations were not associated with increased breast cancer risk. Mutations in BARD1, RAD51C, RAD51Dand XRCC2were specifically significantly associated with moderate risks of ER-negative breast cancer and TNBC, whereas mutations in ATM, CDH1and CHEK2were specifically significantly associated with ER-positive disease. On the basis of these findings age-related absolute breast cancer risks for commonly mutated genes were estimated. Overall, results from the CARRIERS study establish that mutations in predisposition genes are associated with lower risks of breast cancer in the general population than in enriched populations including high-risk families and young onset, bilateral, or multiple primary cases. We anticipate that the results from this study will inform cancer screening and other risk management strategies for women in the general population with mutations in predisposition genes. Citation Format: Fergus J Couch, Chunling Hu, Steven N Hart, Rohan Gnanaolivu, Kun Y Lee, Jie Na, Chi Gao, Nicholas J Boddicker, Bruce Eckloff, Raed Samara, Josh Klebba, Christine B Ambrosone, Hoda Anton-Culver, Paul Auer, Leslie Bernstein, Mia M Gaudet, Christopher Haiman, Esther M John, Susan Neuhausen, Janet E Olson, Tuya Pal, Julie R Palmer, Dale P Sandler, Jack A Taylor, Amy Trentham-Dietz, Celine M Vachon, Clarice Weinberg, Song Yao, Jeffrey N Weitzel, David E Goldgar, Susan M Domchek, Katherine L Nathanson, Peter Kraft, Eric C Polley. Population-based breast cancer risk estimates for predisposition gene mutations: Results from the CARRIERS study [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD3-01.

Abstract Background The risks of breast cancer in African American (AA) women associated with inherited mutations in breast cancer predisposition genes are not well defined. Thus, whether multigene germline hereditary cancer testing panels are applicable to this population is unknown. We assessed associations between mutations in panel-based genes and breast cancer risk in 5054 AA women with breast cancer and 4993 unaffected AA women drawn from 10 epidemiologic studies. Methods Germline DNA samples were sequenced for mutations in 23 cancer predisposition genes using a QIAseq multiplex amplicon panel. Prevalence of mutations and odds ratios (ORs) for associations with breast cancer risk were estimated with adjustment for study design, age, and family history of breast cancer. Results Pathogenic mutations were identified in 10.3% of women with estrogen receptor (ER)-negative breast cancer, 5.2% of women with ER-positive breast cancer, and 2.3% of unaffected women. Mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (OR = 47.55, 95% confidence interval [CI] = 10.43 to >100; OR = 7.25, 95% CI = 4.07 to 14.12; OR = 8.54, 95% CI = 3.67 to 24.95, respectively). RAD51D mutations were associated with high risk of ER-negative disease (OR = 7.82, 95% CI = 1.61 to 57.42). Moderate risks were observed for CHEK2, ATM, ERCC3, and FANCC mutations with ER-positive cancer, and RECQL mutations with all breast cancer. Conclusions The study identifies genes that predispose to breast cancer in the AA population, demonstrates the validity of current breast cancer testing panels for use in AA women, and provides a basis for increased referral of AA patients for cancer genetic testing.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.

AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast cancer.

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.