Usefulness of preclinical models for assessing the efficacy of late-life interventions for sarcopenia

Caloric restriction and physical exercise have proven beneficial against age-associated changes in body composition and declining physical performance; however, little is known regarding what benefit these interventions might have when initiated late in life. The study of mimetics of diet and exercise and the combination thereof may provide additional treatments for a vulnerable elderly population; however, how and when to initiate such interventions requires consideration in developing the most safe and efficacious treatment strategies. In this review, we focus on preclinical late-life intervention studies, which assess the relationship between physical function, sarcopenia, and body composition. We provide a conceptual framework for the ever-changing definition of sarcopenia and a rationale for the use of an appropriate rodent model of this condition. We finish by providing our perspective regarding the implications of this body of work and future areas of research that may also contribute to the ultimate goal of extending healthspan. © 2011 The Author

Model selection for DCE‐T1 studies in glioblastoma

Dynamic contrast enhanced T 1 ‐weighted MRI using the contrast agent gadopentetate dimeglumine (Gd‐DTPA) was performed on 10 patients with glioblastoma. Nested models with as many as three parameters were used to estimate plasma volume or plasma volume and forward vascular transfer constant ( K trans ) and the reverse vascular transfer constant ( k ep ). These constituted models 1, 2, and 3, respectively. Model 1 predominated in normal nonleaky brain tissue, showing little or no leakage of contrast agent. Model 3 predominated in regions associated with aggressive portions of the tumor, and model 2 bordered model 3 regions, showing leakage at reduced rates. In the patient sample, v p was about four times that of white matter in the enhancing part of the tumor. K trans varied by a factor of 10 between the model 2 (1.9 ↔ 10 −3 min −1 ) and model 3 regions (1.9 ↔ 10 −2 min −1 ). The mean calculated interstitial space (model 3) was 5.5%. In model 3 regions, excellent curve fits were obtained to summarize concentration‐time data (mean R 2 = 0.99). We conclude that the three parameters of the standard model are sufficient to fit dynamic contrast enhanced T 1 data in glioblastoma under the conditions of the experiment. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91323/1/23211_ftp.pd

Adult Type 3 Adenylyl Cyclase–Deficient Mice Are Obese

Background: A recent study of obesity in Swedish men found that polymorphisms in the type 3 adenylyl cyclase (AC3) are associated with obesity, suggesting the interesting possibility that AC3 may play a role in weight control. Therefore, we examined the weight of AC3 mice over an extended period of time. Methodology/Principal Findings: We discovered that AC3 2/2 mice become obese as they age. Adult male AC3 2/2 mice are about 40 % heavier than wild type male mice while female AC3 2/2 are 70 % heavier. The additional weight of AC3 2/2 mice is due to increased fat mass and larger adipocytes. Before the onset of obesity, young AC3 2/2 mice exhibit reduced physical activity, increased food consumption, and leptin insensitivity. Surprisingly, the obesity of AC3 2/2 mice is not due to a loss of AC3 from white adipose and a decrease in lipolysis. Conclusions/Significance: We conclude that mice lacking AC3 exhibit obesity that is apparently caused by low locomotor activity, hyperphagia, and leptin insensitivity. The presence of AC3 in primary cilia of neurons of the hypothalamus suggests that cAMP signals generated by AC3 in the hypothalamus may play a critical role in regulation of body weight

Natural Selection and Adaptive Evolution of Leptin in the Ochotona Family Driven by the Cold Environmental Stress

BACKGROUND: Environmental stress can accelerate the evolutionary rate of specific stress-response proteins and create new functions specialized for different environments, enhancing an organism's fitness to stressful environments. Pikas (order Lagomorpha), endemic, non-hibernating mammals in the modern Holarctic Region, live in cold regions at either high altitudes or high latitudes and have a maximum distribution of species diversification confined to the Qinghai-Tibet Plateau. Variations in energy metabolism are remarkable for them living in cold environments. Leptin, an adipocyte-derived hormone, plays important roles in energy homeostasis. METHODOLOGY/PRINCIPAL FINDINGS: To examine the extent of leptin variations within the Ochotona family, we cloned the entire coding sequence of pika leptin from 6 species in two regions (Qinghai-Tibet Plateau and Inner Mongolia steppe in China) and the leptin sequences of plateau pikas (O. curzonia) from different altitudes on Qinghai-Tibet Plateau. We carried out both DNA and amino acid sequence analyses in molecular evolution and compared modeled spatial structures. Our results show that positive selection (PS) acts on pika leptin, while nine PS sites located within the functionally significant segment 85-119 of leptin and one unique motif appeared only in pika lineages-the ATP synthase alpha and beta subunit signature site. To reveal the environmental factors affecting sequence evolution of pika leptin, relative rate test was performed in pikas from different altitudes. Stepwise multiple regression shows that temperature is significantly and negatively correlated with the rates of non-synonymous substitution (Ka) and amino acid substitution (Aa), whereas altitude does not significantly affect synonymous substitution (Ks), Ka and Aa. CONCLUSIONS/SIGNIFICANCE: Our findings support the viewpoint that adaptive evolution may occur in pika leptin, which may play important roles in pikas' ecological adaptation to extreme environmental stress. We speculate that cold, and probably not hypoxia, may be the primary environmental factor for driving adaptive evolution of pika leptin

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment