Summary Tumors are typically sequenced to depths of 75–100× (exome) or 30–50× (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ~312×) whole genome sequencing (WGS) and exome capture (up to ~433×) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ~200,000 putative SNVs by sequencing them to depths of ~1,000×. Additional targeted sequencing provided over 10,000× coverage and ddPCR assays provided up to ~250,000× sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP accession id phs000159).

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co‐segregation, family cancer history profile, co‐occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case‐control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene‐specific calibration of evidence types used for variant classification.

One of the obvious uses which may be made of a tracer in biological studies is the determination of rates. Zilversmitt and associates (1) and more recently London (2) have called attention to this use of a tracer. Only when the isotope can be added without effectively changing the amount or concentration of material in a steady state system can such an application be made. Not until recently has radio iron been available which had sufficiently high specific activity to tag plasma iron without changing its concentration. The amount of iron leaving and entering the plasma would be significant in determining an abnormal turnover rate in some other system of the body containing iron, for example, the red cells. The present theory of iron metabolism conceives of plasma as a pool into which iron is returned before being resynthesized into the complex organic substances, hemoglobin, myoglobin, cytochromes, peroxidases, and ferritin which are so important to body function. Since the approximate normal rate of turnover of red cell iron is known, and since the major portion of this element in the body resides in the red cells, it would be expected that abnormalities in this rate would be directly reflected in plasma iron turnover rates. This paper concerns the plasma iron and red cell iron turnover data on 75 human subjects who were given amounts of iron which did not alter the steady state systems. It is shown that such turnover rates do, indeed, agree with the clinical and laboratory data concerning normal red cell life, abnormal rates of destruction and abnormal rates of formation of red cells. It is believed that the data ascertained from the type of study described here are of value

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Aims We tested the hypothesis that body fat percentage determines cardiac sympathovagal balance in healthy subjects. Main methods Heart rate variability (HRV) measurements were made of the standard deviation of the normal– normal RR intervals (SDNN) and the low frequency/high frequency (LF/HF) ratio, from time domain and fast Fourier transform spectral analysis of electrocardiogram RR intervals during trials of uncontrolled and controlled (paced) breathing at 0.2 Hz. Body fat percentage was measured by dual energy x-ray absorptiometric (DEXA) scanning. Significance of differences between uncontrolled and controlled (paced) breathing was determined by analysis of variance and correlations between body fat percentage and HRV measurements by Pearson's coefficient at P<0.05. Key findings Percent body fat was negatively correlated with LF/HF during the uncontrolled breathing (r= −0.56, two-tailed P<0.05, one-tailed P<0.01) but not during the paced breathing trial (r=−0.34, (P>0.1). Significance We conclude that sympathetic activity produced by paced breathing at 0.2 Hz can obscure the relationship between body fat percentage and sympathovagal balance and that high body fat percentage may be associated with low sympathetic modulation of the heart rate in healthy adolescent/young adult males.