Data-driven design of targeted gene panels for estimating immunotherapy biomarkers

We introduce a novel data-driven framework for the design of targeted gene panels for estimating exome-wide biomarkers in cancer immunotherapy. Our first goal is to develop a generative model for the profile of mutation across the exome, which allows for gene- and variant type-dependent mutation rates. Based on this model, we then propose a new procedure for estimating biomarkers such as Tumour Mutation Burden and Tumour Indel Burden. Our approach allows the practitioner to select a targeted gene panel of a prespecified size, and then construct an estimator that only depends on the selected genes. Alternatively, the practitioner may apply our method to make predictions based on an existing gene panel, or to augment a gene panel to a given size. We demonstrate the excellent performance of our proposal using an annotated mutation dataset from 1144 Non-Small Cell Lung Cancer patients.Comment: 21 pages, 10 figure

Statistical and machine learning approaches to genomic medicine

In this thesis, we develop new statistical and machine learning methods for genomic medicine, and apply them to problems in diagnostics and precision oncology. Our overall aim is to introduce techniques that inform practical decision making in the design and use of clinical tests. The work combines domain-specific context with modern advances in Bayesian hierarchical modelling, high-dimensional statistics, and causal inference. We begin in Chapter 1 with an introduction to the concepts and methodologies that are common throughout the thesis. This includes the necessary context from molecular biology, an overview of genomics in medicine with a particular focus on cancer (the subject of Chapters 3 and 4), and a description of data-generating technologies such as DNA sequencing and gene expression profiling. We also provide an in-depth introduction to the relevant statistical learning methods and techniques. This sets the scene for the three projects presented in subsequent chapters. In Chapter 2 we analyse the resolution of the loop-mediated isothermal amplification (LAMP) assay. LAMP is a technology that can be used in medical tests that require quantifying the presence of RNA for each of a set of gene targets. Motivated by the unmet need for statistically principled methods for guided LAMP optimisation, we show how to use data from clinical and synthetic samples to improve the resolution of a LAMP-based diagnostic test for sepsis patients. In this context, by optimisation of the assay we refer both to the selection of gene targets, and to the tuning of reactions conditions and selection of optimal primers to produce robust, high-resolution measurements of gene expression. Our analysis identifies novel quantities associated with primer design that may drive assay performance. Chapter 3 focuses on designing gene panels to estimate tumour mutation burden (TMB) and other exome-wide biomarkers, which are used to determine which cancer patients will benefit from immunotherapy. The cost of whole-exome sequencing presently limits the widespread use of such biomarkers. In this chapter, we introduce a data-driven framework for the design of targeted gene panels for estimating a broad class of biomarkers including tumour mutation burden and tumour indel burden. The first goal is to develop a generative model for the profile of mutation across the exome, which allows for gene- and variant typedependent mutation rates. Based on this model, we then propose a procedure for constructing biomarker estimators. Our approach allows the practitioner to select a targeted gene panel of prespecified size and construct an estimator that only depends on the selected genes. Alternatively, our method may be applied to make predictions based on an existing gene panel, or to augment a gene panel to a given size. We demonstrate the excellent performance of our proposal using data from three non-small cell lung cancer studies, as well as data from six other cancer types. In Chapter 4, we consider causal questions in survival analysis, and investigate the extent to which the heterogeneous treatment effects of immunotherapy vary according to patients’ clinical and genomic features. Methods for identifying heterogeneous treatment effects from survival data are still in their infancy, and so in this chapter we benchmark some recently proposed strategies. In particular, we show that high-throughput targeted sequencing data may offer better understanding into which patients are likely to benefit from immunotherapy, using state-of-the art statistical learning methods based on causal survival forests and regularisation

Characterization of the interaction of Aha1 with components of the Hsp90 chaperone machine and client proteins

AbstractThe activator of Hsp90 ATPase, Aha1, is an Hsp90 co-chaperone that has been suggested to act as a general stimulator of Hsp90 function. In this report, we have characterized the interaction of Aha1 with Hsp90 and its co-chaperones in rabbit reticulocyte lysate (RRL) and in HeLa cell extracts. Complexes formed by Aha1 with Hsp90 in RRL were stabilized by molybdate and contained the co-chaperones FKBP52 and p23/Sba1, but lacked HOP/Sti1 and Cdc37. Aha1 complexes isolated from HeLa cell extracts also contained Hsp70 and DNAJA1. Over-expression of Aha1 has been reported to stimulate the activity of v-Src and steroid hormone receptors ectopically expressed in yeast, however, no interaction between Aha1 and nascent v-Src or the progesterone receptor could be detected in RRL. Contrary to expectations, over-expression of Aha1 also inhibited the rate of Hsp90-dependent refolding of denatured luciferase. A number of potential client proteins that specifically associated with Aha1 were identified by liquid chromatography/ tandem mass spectrometry (LC–MS/MS) and verified by Western blotting. The proteins identified suggest that Aha1 may play roles in modulating RNA splicing and DNA repair, in addition to other cellular processes

Measured Thoracic Gas Volume Versus Two Predictions

Body composition, or one’s fat mass relative to total mass, is important to a person’s health and physical performance. One method to measure body composition is the Bod Pod air displacement plethysmograph. To determine body volume from the Bod Pod, thoracic gas volume (TGV), or the volume of air in the lungs during a normal breath, must be measured or predicted. PURPOSE: The intent of this study was to compare measured TGV to two predictions: one from the Bod Pod (TGVBP) that makes assumptions about functional residual capacity and tidal volume, and one from a recent publication (TGVDucharme) that relies on measures of height and body mass rather than lung volumes. METHODS: Bod Pod data from university club sport athletes participating in a larger study were used. TGV was measured following the Bod Pod manufacturer’s instructions. Comparisons of mean data were made between the measured test and the two predictions with a one-way repeated-measures ANOVA. Individual error scores were evaluated with Bland-Altman plots. RESULTS: Data from 26 club sport athletes (18 male, 8 female) revealed a statistically significant difference (p = .001) between the three TGV measures. The measured TGV (4.108 ± 0.850 L) and TGVDucharme (4.092 ± 0.655 L) were not significantly different from one another (p = .851), but TGVBP (3.724 ± 0.409 L) significantly underestimated the measured TGV (p = .002) and Ducharme’s prediction (p \u3c .001). A clear bias exists for TGVBP (r = -0.799, p \u3c .001), such that the Bod Pod prediction overestimates athletes with a small TGV (\u3c 3.3 L) and underestimates athletes with a large TGV (\u3e 3.3 L). The bias for TGVDucharme is statistically significant (r = -0.460, p = .018), but much smaller than the bias from the Bod Pod prediction. CONCLUSION: When possible, measure TGV. If TGV must be predicted, use the Ducharme prediction rather than the TGV prediction from the Bod Pod

Arterial properties as determinants of left ventricular mass and fibrosis in severe aortic Stenosis : findings from ACRIN PA 4008

Background-The role of arterial load in severe aortic stenosis is increasingly recognized. However, patterns of pulsatile load and their implications in this population are unknown. We aimed to assess the relationship between the arterial properties and both (1) left ventricular remodeling and fibrosis and (2) the clinical course of patients with severe aortic stenosis undergoing aortic valve replacement (AVR). Methods and Results-We enrolled 38 participants with symptomatic severe aortic stenosis scheduled to undergo surgical AVR. Aortic root characteristic impedance, wave reflections parameters (reflection magnitude, reflected wave transit time), and myocardial extracellular mass were measured with cardiac magnetic resonance imaging and arterial tonometry Cardiac magnetic resonance imaging was repeated at 6 months in 30 participants. A reduction in cellular mass (133.6 versus 113.9 g; P=0.002) but not extracellular mass (42.3 versus 40.6 g; P=0.67) was seen after AVR. Participants with higher extracellular mass exhibited greater reflection magnitude (0.68 versus 0.54; P=0.006) and lower aortic root characteristic impedance (56.3 versus 96.9 dynes/s per cm(5); P=0.006). Reflection magnitude was a significant predictor of smaller improvement in the quality of life (Kansas City Cardiomyopathy Questionnaire score) after AVR (R=-0.51; P=0.0026). The 6-minute walk distance at 6 months after AVR was positively correlated with the reflected wave transit time (R=0.52; P=0.01). Conclusions-Consistent with animal studies, arterial wave reflections are associated with interstitial volume expansion in severe aortic stenosis and predict a smaller improvement in quality of life following AVR. Future trials should assess whether wave reflections represent a potential therapeutic target to mitigate myocardial interstitial remodeling and to improve the clinical status of this patient population

Reaction of O2 with a di-iron protein generates a mixed valent Fe2+/Fe3+ center and peroxide

The gene encoding the cyanobacterial ferritin SynFtn is up-regulated in response to copper stress. Here, we show that, while SynFtn does not interact directly with copper, it is highly unusual in several ways. First, its catalytic diiron ferroxidase center is unlike those of all other characterized prokaryotic ferritins and instead resembles an animal H-chain ferritin center. Second, as demonstrated by kinetic, spectroscopic, and high-resolution X-ray crystallographic data, reaction of O2 with the di-Fe2+ center results in a direct, one-electron oxidation to a mixed-valent Fe2+/Fe3+ form. Iron–O2 chemistry of this type is currently unknown among the growing family of proteins that bind a diiron site within a four α-helical bundle in general and ferritins in particular. The mixed-valent form, which slowly oxidized to the more usual di-Fe3+ form, is an intermediate that is continually generated during mineralization. Peroxide, rather than superoxide, is shown to be the product of O2 reduction, implying that ferroxidase centers function in pairs via long-range electron transfer through the protein resulting in reduction of O2 bound at only one of the centers. We show that electron transfer is mediated by the transient formation of a radical on Tyr40, which lies ∼4 Å from the diiron center. As well as demonstrating an expansion of the iron–O2 chemistry known to occur in nature, these data are also highly relevant to the question of whether all ferritins mineralize iron via a common mechanism, providing unequivocal proof that they do not

A new interpretation of total column BrO during Arctic spring

Emission of bromine from sea-salt aerosol, frost flowers, ice leads, and snow results in the nearly complete removal of surface ozone during Arctic spring. Regions of enhanced total column BrO observed by satellites have traditionally been associated with these emissions. However, airborne measurements of BrO and O3 within the convective boundary layer (CBL) during the ARCTAS and ARCPAC field campaigns at times bear little relation to enhanced column BrO. We show that the locations of numerous satellite BrO “hotspots” during Arctic spring are consistent with observations of total column ozone and tropopause height, suggesting a stratospheric origin to these regions of elevated BrO. Tropospheric enhancements of BrO large enough to affect the column abundance are also observed, with important contributions originating from above the CBL. Closure of the budget for total column BrO, albeit with significant uncertainty, is achieved by summing observed tropospheric partial columns with calculated stratospheric partial columns provided that natural, short-lived biogenic bromocarbons supply between 5 and 10 ppt of bromine to the Arctic lowermost stratosphere. Proper understanding of bromine and its effects on atmospheric composition requires accurate treatment of geographic variations in column BrO originating from both the stratosphere and troposphere

The Lick AGN Monitoring Project 2011: Dynamical Modeling of the Broad-Line Region

We present models of the H$\beta$-emitting broad-line region (BLR) in seven Seyfert 1 galaxies from the Lick AGN (Active Galactic Nucleus) Monitoring Project 2011 sample, drawing inferences on the BLR structure and dynamics as well as the mass of the central supermassive black hole. We find that the BLR is generally a thick disk, viewed close to face-on, with preferential emission back toward the ionizing source. The dynamics in our sample range from near-circular elliptical orbits to inflowing or outflowing trajectories. We measure black hole masses of $\log_{10}(M_{\rm BH}/M_\odot) = 6.48^{+0.21}_{-0.18}$ for PG 1310$-$108, $7.50^{+0.25}_{-0.18}$ for Mrk 50, $7.46^{+0.15}_{-0.21}$ for Mrk 141, $7.58^{+0.08}_{-0.08}$ for Mrk 279, $7.11^{+0.20}_{-0.17}$ for Mrk 1511, $6.65^{+0.27}_{-0.15}$ for NGC 4593, and $6.94^{+0.14}_{-0.14}$ for Zw 229$-$015. We use these black hole mass measurements along with cross-correlation time lags and line widths to recover the scale factor $f$ used in traditional reverberation mapping measurements. Combining our results with other studies that use this modeling technique, bringing our sample size to 16, we calculate a scale factor that can be used for measuring black hole masses in other reverberation mapping campaigns. When using the root-mean-square (rms) spectrum and using the line dispersion to measure the line width, we find $\log_{10}(f_{{\rm rms},\sigma})_{\rm pred} = 0.57 \pm 0.19$. Finally, we search for correlations between $f$ and other AGN and BLR parameters and find marginal evidence that $f$ is correlated with $M_{\rm BH}$ and the BLR inclination angle, but no significant evidence of a correlation with the AGN luminosity or Eddington ratio.Comment: 26 pages, 14 figures. Accepted for publication in Ap

Relationship Between Muscular Performance Changes and Increases in Body Mass During Overfeeding Plus Resistance Training

Two critical components of muscular performance are muscular strength (e.g., the maximal load that can be lifted for a given exercise) and muscular endurance (e.g., the maximal number of repetitions that can be performed at a given load). When seeking improvements in muscular performance, it is common to employ nutritional strategies that create an energy surplus and a resultant gain in body mass. Varying rates of body mass gain are often prescribed to optimize training adaptations, including improvements in muscular performance; however, the relationship between rate of body mass gain and muscular performance improvements, if any, is not entirely clear. PURPOSE: The purpose of this analysis was to elucidate if there is a relationship between the rate of body mass gain and changes in muscular performance resulting from a resistance training program. METHODS: Nineteen resistance-trained males (age: 21.7 ± 2.6; body mass [BM]: 74.1 ± 11.5 kg; body fat percentage: 13.7 ± 5.2%; bench press maximal strength: 1.3 ± 0.2 x BM; leg press maximal strength: 3.4 ± 0.9 x BM) completed a supervised resistance training program plus overfeeding. Muscular performance testing took place at baseline and after the 6-week intervention. For the bench press and leg press exercises, strength was assessed via 1-repetition maximum (1RM), and endurance was assessed via repetitions to failure using 70% of the baseline 1RM. Simple linear regression analysis was used to determine if the relative rate of BM gain was related to relative improvements in maximal muscular strength and endurance. Standardized regression coefficients (β) and associated 95% confidence intervals (CI) were generated. RESULTS: The rate of BM gain was related to improvements in bench press 1RM (p=0.05; β=0.46 [0.02, 0.89], mean [95% CI]) and endurance (p=0.007, β =0.61 [0.23, 1.00]), but not leg press 1RM (p=0.16, β =0.33 [-0.11, 0.78]) or endurance (p=0.76, β = 0.08 [-0.42, 0.58]). A 1.0% increase in the relative rate of BM gain corresponded to relative increases of 1.2% (CI of 0.1 to 2.4%) in bench press 1RM and 6.7% (CI of 2.5 to 10.9%) in bench press repetitions to failure. CONCLUSION: The relative rate of body mass gain was positively related to performance improvements in the bench press exercise, but not the leg press exercise. One speculative explanation for this relationship is that the increase in upper body muscularity that results from body mass gain during resistance training could have decreased the range of motion on the bench press exercise, thereby facilitating easier execution of the movement for both strength and endurance tests