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.

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.

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.

Abstract P3-09-09: Serial circulating tumor DNA from patients with metastatic breast cancer with and without BRCA1/2 mutations

Background: Analysis of circulating tumor DNA (ctDNA) over time allows non-invasive evaluation of tumor genomic evolution. We characterize changes in tumor fraction (TFx), somatic copy number alterations (SCNAs), and somatic mutations over time in patients (pts) with and without BRCA1/2 mutations and metastatic breast cancer (mBC) who received a PARP inhibitor (PARPi) or platinum chemotherapy. Specifically, we seek to identify the frequency of BRCA1/2 reversion mutations. Methods: Pts with mBC and germline or somatic BRCA1/2 mutations were identified on a banking protocol of prospectively-collected serial samples of blood and plasma. Control pts without a BRCA1/2 mutation were matched 2:1 by age and hormone receptor (HR) status. Ultra-low-pass whole genome sequencing (ULPWGS) with 0.1x depth was performed on all plasma samples (n=103) and the ichorCNA algorithm was used to determine TFx and SCNAs. Targeted panel sequencing (TPS) of 402 cancer-related genes was performed at 10,000x depth on plasma samples, and one blood sample per pt. The panel includes BRCA1/2 and 38 other DNA damage repair (DDR) genes. Somatic mutations were identified by joint calling with Mutect2 across plasma timepoints with paired pt normal blood. Germline variant calling from TPS on blood with HaplotypeCaller was used to confirm germline mutations in BRCA1/2. Results: We identified 10 pts with mBC with a germline (n=7) or somatic (n=3) BRCA1 (n=2) or BRCA2 (n=8) mutation and banked blood and plasma samples at 2-9 timepoints at a median of 8 weeks apart (range 1-43). The control cohort of 20 pts with mBC and wildtype BRCA1/2 was well matched by age and HR status. All pts with BRCA1/2 mutations received a PARPi and/or platinum chemotherapy at some point during sample collection. Half of control pts received platinum chemotherapy. Germline BRCA1/2 mutations were confirmed in all 7 pts with known germline mutations. Somatic BRCA2 mutations were confirmed in ctDNA in 2 of 3 patients. Among all samples, median TFx was 0.05 (range 0-0.80) with 35% of samples having TFx &gt;0.10. There was no significant difference in TFx by age, receptor status, or active treatment with a PARPi or platinum. There was no significant change in the percent of genome with a SCNA over time. A reversion mutation of a germline BRCA2 mutation, restoring the open reading frame of BRCA2, was discovered at the last timepoint from 1 pt while receiving carboplatin. She had radiographic progression 4 weeks later. A germline BRCA1/2 reversion mutation in this cohort occurred in 2.3% of samples, 14.3% of pts. The somatic mutation landscape and clonal evolution of TPS using PyClone will be presented. Clonal evolution can show emerging and responding clusters of variants. For pts with available tissue specimens, somatic variants in ctDNA will be compared to somatic mutations detected in tissue with TPS. Conclusions: Evaluation of serial ctDNA samples for TFx, SCNAs, and somatic mutations from banked plasma and blood from pts with mBC is feasible. SCNAs were stable over time. The frequency of reversion mutations in BRCA1/2 was low, suggesting that either their incidence is low or ctDNA TPS is not sensitive enough to detect them.

Citation Format: Katharine A Collier, David Tallman, Zachary T. Weber, Marcy Haynam, Elizabeth J. Adams, Janet Jenison, Sarah Asad, Maryam Lustberg, Mathew Cherian, Bhuvaneswari Ramaswamy, Sagar Sardesai, Nicole Williams, Robert Wesolowski, Jeffrey Vandeusen, Margaret E. Gatti-Mays, Ashley Pariser, Amir Mortazavi, Daniel G. Stover. Serial circulating tumor DNA from patients with metastatic breast cancer with and without BRCA1/2 mutations [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-09-09.

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.

Abstract PS4-25: Comprehensive genomic analysis reveals molecular correlates of response to immune checkpoint inhibitors (ICI) in metastatic triple-negative breast cancer (mTNBC)

Background: Genomic mechanisms associated with response to ICI in mTNBC are largely unknown. The aim of this work is to assess the genomic and immune profiles of mTNBC samples collected from patients (pts) treated with ICI. Methods: We identified 31 women with mTNBC treated with ICI (pembrolizumab, n=6, NCT02447003; atezolizumab, n=4, NCT01375842; nivolumab + cabozantinib, n = 6, NCT03316586; pembrolizumab + eribulin, n=8, NCT02513472; atezolizumab + nab-paclitaxel, n=7, NCT01633970) who had tumor tissue or blood available for sequencing obtained before and after ICI. Clinical benefit (CB), here defined as any objective response or stable disease (SD) for &gt; 24 weeks, was observed in 20 pts (65%). An extraordinary responder was defined as having CB ≥ 2 yrs; 5 pts were considered extraordinary responders (range 26-60months). Whole exome sequencing (WES) was done on each tumor and on germline DNA from blood (23 pts had successful WES performed on samples collected before ICI; 5 of these had WES on samples taken after disease progression). RNA sequencing (RNAseq) was successfully performed in 18 of the tumors with WES performed on samples before ICI; and 3 of these had RNAseq on samples taken after disease progression. 18 pts had tumors assessed by multiplex immunofluorescence (mIF) panels encompassing CD4, CD8, PD-1, PD-L1, and cytokeratin on samples collected before ICI. WES, deep targeted panel and low coverage whole genome sequencing were performed on serially collected plasma samples from 22 pts to evaluate tumor fraction and specific mutations. The association between biomarkers and clinical benefit to ICI was assessed. Results: 21 of 31 pts (67%) had received ≥1 prior lines of systemic therapy in the metastatic setting before starting ICI. Among the most frequently mutated genes at baseline are: TP53 (57%); PIK3CA (18%); DNAH5, MYH8 (both 13%); KMT2C, AKT1, LAMA2 (all 9%). Pts with CB had a higher tumor mutational burden (TMB) than pts with no CB (p=0.018). Differential expression analysis of RNAseq data revealed an upregulation of several immune-related genes in pts with CB, indicating increased immune infiltration in that group. Gene set enrichment analysis of this expression data using hallmark and canonical pathway gene sets from MSigDB (nominal p-val &lt; 0.05) showed that, compared to samples from pts without CB, extraordinary responders had elevated transcriptional signatures of several cancer-related pathways associated with cell survival, proliferation and metabolism, as well as genes associated with increased immune infiltration and upregulation of inflammatory response programs. The mIF showed that the tumor microenvironment (TME) of pts with CB were enriched in Cytokeratin-negative/PD-L1-positive cells compared to those without CB (p=0.014). Expression of CD4, CD8 and PD-1 was not significantly different between pts with and without CB. Genomic analysis of circulating tumor DNA, and tumor evolutionary analysis for pts with both pre- and post-ICI samples (acquired resistance) will be presented. Conclusions: Clinical benefit to ICI in mTNBC was associated with upregulation of immune-related pathways, enrichment of non-tumoral PD-L1-positive cells in TME, and high TMB.

Citation Format: Romualdo Barroso-Sousa, Juliet Forman, Zachary T. Weber, Katherine Collier, Katrina Z. Kao, Edward T. Richardson, III, Tanya Keenan, Ofir Cohen, Michael P. Manos, Ryan C. Brennick, Patrick Ott, F. Steve Hodi, Deborah A. Dillon, Nancy U. Lin, Eliezer E. Van Allen, Scott Rodig, Eric P. Winer, Elizabeth A. Mittendorf, Catherine J. Wu, Daniel Stover, Nikhil Wagle, Sachet Shukla, Sara Tolaney. Comprehensive genomic analysis reveals molecular correlates of response to immune checkpoint inhibitors (ICI) in metastatic triple-negative breast cancer (mTNBC) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS4-25.

Abstract 5471: CNSigs: An R package for the identification of copy number signatures

Copy number aberrations (CNAs) are gains and losses of large genomic segments present across most cancer types and are a hallmark of cancer genomic alterations. However, the processes underlying CNAs and characteristic patterns of CNAs are poorly understood. Using single nucleotide variant (SNV) data, bioinformatic advances have identified underlying mutational signatures resulting from distinct mutational processes. Mutational signatures have led to a variety of discoveries, several of which are being investigated in clinical management of cancer. The development of algorithms able to uncover similar signatures for CNAs, rather than SNVs, is still in its infancy. Here we present an analysis package for the R programming language called CNSigs that allows for the robust and reproducible derivation of copy number signatures. Based on a list of extracted copy number features previously verified in ovarian cancer, we utilize mixed model approaches and non-negative matrix factorization to derive CNA signatures across cancer types. The development of a package to derive signatures from copy number data allows further investigation of underlying processes that may be responsible for these CNA fingerprints. To verify the reproducibility of the signatures, we derived signatures from two independent breast cancer datasets that use distinct copy number segmentation approaches. From these independent datasets we were able to recover the same signatures with high accuracy. We identified five signatures that are distinct from known breast cancer receptor-based or expression-based subtypes, yet reveal unique associations with underlying mutations, mutational processes, and transcriptional programs. To validate robustness, we applied the pipeline to 11 different cancer types from the TCGA dataset and showed that we were able to derive signatures from all of these cancer types of varying sample sizes. We identified certain signatures that cut across tumor types, while others are distinct to individual cancers. This work lays the groundwork for further analysis into the underlying molecular processes leading to these copy number signatures seen across cancer types. The CNSigs package also allows researchers to easily analyze their own samples to look for signatures in their copy number profiles and to compare these to signatures previously derived for their cancer type.

Citation Format: David Tallman, Sinclair Stockard, Zachary T. Weber, Sarah Asad, Katharine Collier, Elizabeth Adams, Jerome Bey, Daniel G. Stover. CNSigs: An R package for the identification of copy number signatures [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5471.

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.