Faculty Bibliography

Melanoma brain metastasis is the largest cause of melanoma morbidity and mortality, and melanoma has the highest rate of brain metastasis of any cancer. The mechanisms that mediate melanoma brain metastasis remain poorly understood. We characterized patient-derived Short-Term Cultures (STCs) as a novel model system for the study of melanoma brain metastasis. Unbiased proteomics analysis of STCs revealed striking alterations in brain metastasis vs non-brain metastasis derived STCs in proteins related to neurodegeneration. Through in-vivo assays, we show that loss of Amyloid Precursor Protein (APP) in melanoma cells dramatically inhibits melanoma brain metastasis formation without affecting metastasis to other organs and that amyloid beta is the form of APP critically required for melanoma brain metastasis. Additionally, we demonstrate that APP is required for late growth and survival of melanoma cells in the brain parenchyma. Furthermore, we demonstrate that melanoma-derived amyloid beta polarizes astrocytes to an anti-inflammatory secretory phenotype that inhibits microglial phagocytosis of melanoma cells. Finally, we show that treatment of mice with a beta secretase inhibitor (LY2886721), which prevents amyloid beta production, decreases brain metastatic burden. Our results demonstrate a critical role for amyloid beta in melanoma brain metastasis, establish a novel connection between brain metastasis and neurodegenerative pathologies, and show that amyloid beta is a promising therapeutic target for brain metastasis treatment. Studies to further characterize how amyloid beta acts in the melanoma brain metastasis microenvironment are currently underway

Advances in mass spectrometry-based methods have enabled deeper biological insights using proteomics and metabolomics approaches. This has also resulted in improvements in our ability to compare and correlate these data with other 'omics methods such as genomics and transcriptomics-thus creating the new field of multi-omics. In this session, experts will present their work in the area of multi-omics research. Robert Hettich (Oak Ridge National Laboratory) will present his experiences with integrating advanced mass spectrometry technology and meta-omics analysis for characterizing complex microbiomes. Kelly Ruggles (NYU Langone Health) will discuss ways to integrate the results from diverse experiments and develop complementary statistical analysis methods for large comprehensive proteogenomics datasets. Ewy Mathe (Ohio State University) will cover analytical methods in genomics, epigenomics, and metabolomics to characterize disease biomarkers and therapeutic targets. Lastly, Tejaswini Mis-hra (Stanford University) will tell of her work in multi-omics profiling. The presentations will be followed by a panel discussion that will address challenges and solutions for adopting multi-omics methods in core facility settings

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Aberrant phospho-signaling is a hallmark of cancer. We investigated kinase-substrate regulation of 33,239 phosphorylation sites (phosphosites) in 77 breast tumors and 24 breast cancer xenografts. Our search discovered 2,134 quantitatively-correlated kinase-phosphosite pairs, enriching for and extending experimental or binding-motif predictions. Among the 91 kinases with auto-phosphorylation, elevated EGFR, ERBB2, PRKG1, and WNK1 phosphosignaling were enriched in basal, HER2-E, Luminal A, and Luminal B breast cancers, respectively, revealing subtype-specific regulation. CDKs, MAPKs, and ataxia-telangiectasia proteins were dominant, master regulators of substrate-phosphorylation, whose activities are not captured by genomic evidence. We unveiled phospho-signaling and druggable targets from 113 kinase-substrate pairs and cascades downstream of kinases, including AKT1, BRAF and EGFR. We further identified kinase-substrate-pairs associated with clinical or immune signatures and experimentally validated activated phosphosites of ERBB2, EIF4EBP1, and EGFR. Overall, kinase-substrate regulation revealed by the largest unbiased global phosphorylation data to date connects driver events to their signaling effects.

Objective: To better understand uterine cancer using an integrated, high-throughput strategy that evaluates patterns of protein expression, post-translational modification (PTM), somatic mutations, copy number variation (CNV), and patterns of protein-coding and noncoding RNA expression in parallel.
Method(s): State-of-the-art platforms for mass spectrometry, next-generation sequencing, and bioinformatics were used to comprehensively profile carefully annotated specimens of endometrial cancer and matched adjacent and nonmatched normal tissue. Normals were histologically assessed for their relative composition of endometrium and myometrium. Microsatellite instability (MSI) was categorized as high or low based on whole exome sequencing and patterns of genomic methylation. Clinical demographics, including tumor histology and patient comorbid conditions, were verified across multiple source sites.
Result(s): Use of mass spectrometry consistently identified ~11,000 distinct proteins for each cancer (n = 101) and normal specimen (n = 40) in the discovery dataset (matched endometrium low, n = 25; nonmatched endometrium high normal cores, n = 9; and matched pure myometrium, n = 6). These data reveal unique patterns of proteomic biomarkers and neoantigen expression that differ significantly between cancer histotypes and normals. Cancer-associated protein expression is driven, at least partly, by distinct patterns of mutations and genomic CNV. Our data also reveal novel patterns of circular RNA associated with disruptions in protein expression that vary by uterine cancer histotype. Last, proteogenomic integration reveals previously unrecognized mechanisms potentially responsible for modulating immune responses in MSI-H uterine cancers. Ongoing work includes integrating patterns of microRNA expression, protein phosphorylation, and acetylation into our analyses.
Conclusion(s): Comprehensive proteogenomic analyses have revealed novel patterns of protein, PTM, and circular RNA expression associated with uterine cancer. These observations will be discussed, emphasizing the novel metabolic and immunologic susceptibilities we have identified.
Copyright

Alterations in gut microbiota are known to affect intestinal inflammation and obesity. Antibiotic treatment can affect weight gain by elimination of histone deacetylase (HDAC) inhibitor-producing microbes, which are anti-inflammatory by augmenting regulatory T (T_reg) cells. We asked whether mice that lack HDAC6 and have potent suppressive T_reg cells are protected from microbiota-induced accelerated weight gain. We crossed wild-type and HDAC6-deficient mice and subjected the offspring to perinatal penicillin, inducing weight gain via microbiota disturbance. We observed that male HDAC6-deficient mice were not protected and developed profoundly accelerated weight gain. The antibiotic-exposed HDAC6-deficient mice showed a mixed immune phenotype with increased CD4⁺ and CD8⁺ T-cell activation yet maintained the enhanced T_reg cell-suppressive function phenotype characteristic of HDAC6-deficient mice. 16S rRNA sequencing of mouse fecal samples reveals that their microbiota diverged with time, with HDAC6 deletion altering microbiome composition. On a high-fat diet, HDAC6-deficient mice were depleted in representatives of the S24-7 family and Lactobacillus but enriched with Bacteroides and Parabacteroides; these changes are associated with obesity. Our findings further our understanding of the influence of HDACs on microbiome composition and are important for the development of HDAC6 inhibitors in the treatment of human diseases.-Lieber, A. D., Beier, U. H., Xiao, H., Wilkins, B. J., Jiao, J., Li, X. S., Schugar, R. C., Strauch, C. M., Wang, Z., Brown, J. M., Hazen, S. L., Bokulich, N. A., Ruggles, K. V., Akimova, T., Hancock, W. W., Blaser, M. J. Loss of HDAC6 alters gut microbiota and worsens obesity.

BACKGROUND:Translatomics data, particularly genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency. The increasing popularity of these techniques has resulted in multiple algorithms to detect translational regulation, typically distributed in the form of command line tools that require a basic level of programming ability. Additionally, due to the static nature of current software, dynamic transcriptional and translational comparative analysis cannot be adequately achieved. In order to streamline hypothesis generation, investigators must have the ability to manipulate and interact with their data in real-time. RESULTS:To address the lack of integration in current software, we introduce RIVET, Ribosomal Investigation and Visualization to Evaluate Translation, an R shiny based graphical user interface for translatomics data exploration and differential analysis. RIVET can analyze either microarray or RNA sequencing data from polysome profiling and ribosome profiling experiments. RIVET provides multiple choices for statistical analysis as well as integration of transcription, translation, and translational efficiency data analytics and the ability to visualize all results dynamically. CONCLUSIONS:RIVET is a user-friendly tool designed for bench scientists with little to no programming background. RIVET facilitates the data analysis of translatomics data allowing for dynamic generation of results based on user-defined inputs and publication ready visualization. We expect RIVET will allow for scientists to efficiently make more comprehensive data observations that will lead to more robust hypothesis regarding translational regulation.

People living traditional lifestyles have higher gut microbiota diversity than urban subjects. We hypothesized that shifting lifestyles from an urban environment to a traditional rainforest village would lead to changes in the microbiota of visitors, which would become more similar to the microbiota of villagers. Here, we characterized at different time points the microbiota of 7 urban visitors (5 adults and 2 children) staying in a rainforest Amerindian village for 16 days and compared them with a reference collection of samples from age-matched local villagers. We performed a 16S rRNA gene survey of samples from multiple body sites (including fecal, oral, nasal, and skin samples) using Illumina MiSeq sequencing. The main factor segregating the microbiotas of each body site was the human group (i.e., visitors versus villagers), with the visitor microbiota tending to have lower alpha diversity; the lowered alpha diversity was statistically significant in the microbiota of skin and in the children's fecal and oral microbiota. During the rainforest period, all visitors experienced microbiota changes within their personal cloud of variation. For all body sites, the microbiota conformations in the visitor children better matched the microbiota conformations in villagers of the same age than did those of the visitor adults, which showed a lower "microbiota age" than the microbiota of the villagers. The results suggest higher stability in the adult microbiota, with the less resilient children's microbiota responding more to dietary changes.IMPORTANCE Despite the limitations of a small study, our results evidence higher resilience of the gut microbiota with respect to dietary manipulation in adults than in children and urge further studies to understand the extent of microbiota plasticity in response to dietary changes and the mechanisms underlying microbiota resilience. These studies are relevant to the potential of future human pre- and probiotics in preventing or curing microbiota-associated diseases.