Dietary macronutrient composition impacts gene regulation in adipose tissue.

Diet is a key lifestyle component that influences metabolic health through several factors, including total energy intake and macronutrient composition. While the impact of caloric intake on gene expression and physiological phenomena in various tissues is well described, the influence of dietary macronutrient composition on these parameters is less well studied. Here, we use the Nutritional Geometry framework to investigate the role of macronutrient composition on metabolic function and gene regulation in adipose tissue. Using ten isocaloric diets that vary systematically in their proportion of energy from fat, protein, and carbohydrates, we find that gene expression and splicing are highly responsive to macronutrient composition, with distinct sets of genes regulated by different macronutrient interactions. Specifically, the expression of many genes associated with Bardet-Biedl syndrome is responsive to dietary fat content. Splicing and expression changes occur in largely separate gene sets, highlighting distinct mechanisms by which dietary composition influences the transcriptome and emphasizing the importance of considering splicing changes to more fully capture the gene regulation response to environmental changes such as diet. Our study provides insight into the gene regulation plasticity of adipose tissue in response to macronutrient composition, beyond the already well-characterized response to caloric intake.

Genetics of sexually dimorphic adipose distribution in humans.

Obesity-associated morbidity is exacerbated by abdominal obesity, which can be measured as the waist-to-hip ratio adjusted for the body mass index (WHRadjBMI). Here we identify genes associated with obesity and WHRadjBMI and characterize allele-sensitive enhancers that are predicted to regulate WHRadjBMI genes in women. We found that several waist-to-hip ratio-associated variants map within primate-specific Alu retrotransposons harboring a DNA motif associated with adipocyte differentiation. This suggests that a genetic component of adipose distribution in humans may involve co-option of retrotransposons as adipose enhancers. We evaluated the role of the strongest female WHRadjBMI-associated gene, SNX10, in adipose biology. We determined that it is required for human adipocyte differentiation and function and participates in diet-induced adipose expansion in female mice, but not males. Our data identify genes and regulatory mechanisms that underlie female-specific adipose distribution and mediate metabolic dysfunction in women.

A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA.

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

Multidimensional Molecular Profiling of Metastatic Triple-Negative Breast Cancer and Immune Checkpoint Inhibitor Benefit.

PURPOSE: In metastatic triple-negative breast cancer (mTNBC), consistent biomarkers of immune checkpoint inhibitor (ICI) therapy benefit remain elusive. We evaluated the immune, genomic, and transcriptomic landscape of mTNBC in patients treated with ICIs. METHODS: We identified 29 patients with mTNBC treated with pembrolizumab or atezolizumab, either alone (n = 9) or in combination with chemotherapy (n = 14) or targeted therapy (n = 6), who had tumor tissue and/or blood available before ICI therapy for whole-exome sequencing. RNA sequencing and CIBERSORTx-inferred immune population analyses were performed (n = 20). Immune cell populations and programmed death-ligand 1 expression were assessed using multiplexed immunofluorescence (n = 18). Clonal trajectories were evaluated via serial tumor/circulating tumor DNA whole-exome sequencing (n = 4). Association of biomarkers with progression-free survival and overall survival (OS) was assessed. RESULTS: Progression-free survival and OS were longer in patients with high programmed death-ligand 1 expression and tumor mutational burden. Patients with longer survival also had a higher relative inferred fraction of CD8+ T cells, activated CD4+ memory T cells, M1 macrophages, and follicular helper T cells and enrichment of inflammatory gene expression pathways. A mutational signature of defective repair of DNA damage by homologous recombination was enriched in patients with both shorter OS and primary resistance. Exploratory analysis of clonal evolution among four patients treated with programmed cell death protein 1 blockade and a tyrosine kinase inhibitor suggested that clonal stability post-treatment was associated with short time to progression. CONCLUSION: This study identified potential biomarkers of response to ICIs among patients with mTNBC: high tumor mutational burden; presence of CD8+, CD4 memory T cells, follicular helper T cells, and M1 macrophages; and inflammatory gene expression pathways. Pretreatment deficiencies in the homologous recombination DNA damage repair pathway and the absence of or minimal clonal evolution post-treatment may be associated with worse outcomes.

A pilot study using geospatial analysis to identify hot-spot of populations utilizing services at university based counseling centers.

Objective: Our pilot study tests whether university counseling centers (UCC) can apply the concept of cluster analysis, and geospatial analysis to identify clusters of "hot spots". Participants: Study participants were university students who received services from a large mid-western UCC between August 2015 and July 2016. The study was approved by the University's Institutional Review Board (IRB). Data collected include demographics, address, educational level and declared major. Methods: Data analysis, conducted using SYSTAT 13.1, IBM SPSS Statistics, ArcGIS Desktop and 10.2, ArcOnline, Microsoft excel to clean and analyze demographic data. Analysis included optimized cluster analysis with a p-value < 0.05 as statistically significant. Results: 927 participants, average age was 21.6. We identified "hotspots" using cluster analysis based on age, address, and country of origin. Conclusions: Our study shows that UCCs can apply cluster analysis, and geospatial analysis to identify clusters of "hot spots" to target risk populations.

Modeling clonal structure over narrow time frames via circulating tumor DNA in metastatic breast cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) offers minimally invasive means to repeatedly interrogate tumor genomes, providing opportunities to monitor clonal dynamics induced by metastasis and therapeutic selective pressures. In metastatic cancers, ctDNA profiling allows for simultaneous analysis of both local and distant sites of recurrence. Despite the promise of ctDNA sampling, its utility in real-time genetic monitoring remains largely unexplored. METHODS: In this exploratory analysis, we characterize high-frequency ctDNA sample series collected over narrow time frames from seven patients with metastatic triple-negative breast cancer, each undergoing treatment with Cabozantinib, a multi-tyrosine kinase inhibitor (NCT01738438, https://clinicaltrials.gov/ct2/show/NCT01738438 ). Applying orthogonal whole exome sequencing, ultra-low pass whole genome sequencing, and 396-gene targeted panel sequencing, we analyzed 42 plasma-derived ctDNA libraries, representing 4-8 samples per patient with 6-42 days between samples. Integrating tumor fraction, copy number, and somatic variant information, we model tumor clonal dynamics, predict neoantigens, and evaluate consistency of genomic information from orthogonal assays. RESULTS: We measured considerable variation in ctDNA tumor faction in each patient, often conflicting with RECIST imaging response metrics. In orthogonal sequencing, we found high concordance between targeted panel and whole exome sequencing in both variant detection and variant allele frequency estimation (specificity = 95.5%, VAF correlation, r = 0.949), Copy number remained generally stable, despite resolution limitations posed by low tumor fraction. Through modeling, we inferred and tracked distinct clonal populations specific to each patient and built phylogenetic trees revealing alterations in hallmark breast cancer drivers, including TP53, PIK3CA, CDK4, and PTEN. Our modeling revealed varied responses to therapy, with some individuals displaying stable clonal profiles, while others showed signs of substantial expansion or reduction in prevalence, with characteristic alterations of varied literature annotation in relation to the study drug. Finally, we predicted and tracked neoantigen-producing alterations across time, exposing translationally relevant detection patterns. CONCLUSIONS: Despite technical challenges arising from low tumor content, metastatic ctDNA monitoring can aid our understanding of response and progression, while minimizing patient risk and discomfort. In this study, we demonstrate the potential for high-frequency monitoring of evolving genomic features, providing an important step toward scalable, translational genomics for clinical decision making.

Arabidopsis Protein Kinase D6PKL3 Is Involved in the Formation of Distinct Plasma Membrane Aperture Domains on the Pollen Surface.

Certain regions on the surfaces of developing pollen grains exhibit very limited deposition of pollen wall exine. These regions give rise to pollen apertures, which are highly diverse in their patterns and specific for individual species. Arabidopsis thaliana pollen develops three equidistant longitudinal apertures. The precision of aperture formation suggests that, to create them, pollen employs robust mechanisms that generate distinct cellular domains. To identify players involved in this mechanism, we screened natural Arabidopsis accessions and discovered one accession, Martuba, whose apertures form abnormally due to the disruption of the protein kinase D6PKL3. During pollen development, D6PKL3 accumulates at the three plasma membrane domains underlying future aperture sites. Both D6PKL3 localization and aperture formation require kinase activity. Proper D6PKL3 localization is also dependent on a polybasic motif for phosphoinositide interactions, and we identified two phosphoinositides that are specifically enriched at the future aperture sites. The other known aperture factor, INAPERTURATE POLLEN1, fails to aggregate at the aperture sites in d6pkl3 mutants, changes its localization when D6PKL3 is mislocalized, and, in turn, affects D6PKL3 localization. The discovery of aperture factors provides important insights into the mechanisms cells utilize to generate distinct membrane domains, develop cell polarity, and pattern their surfaces.