How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Prolonged fasting times reap greater geroprotective effects when combined with caloric restriction in adult female mice.

Emerging new evidence highlights the importance of prolonged daily fasting periods for the health and survival benefits of calorie restriction (CR) and time-restricted feeding (TRF) in male mice; however, little is known about the impact of these feeding regimens in females. We placed 14-month-old female mice on five different dietary regimens, either CR or TRF with different feeding windows, and determined the effects of these regimens on physiological responses, progression of neoplasms and inflammatory diseases, serum metabolite levels, and lifespan. Compared with TRF feeding, CR elicited a robust systemic response, as it relates to energetics and healthspan metrics, a unique serum metabolomics signature in overnight fasted animals, and was associated with an increase in lifespan. These results indicate that daytime (rest-phase) feeding with prolonged fasting periods initiated late in life confer greater benefits when combined with imposed lower energy intake.

The road ahead for health and lifespan interventions.

Aging is a modifiable risk factor for most chronic diseases and an inevitable process in humans. The development of pharmacological interventions aimed at delaying or preventing the onset of chronic conditions and other age-related diseases has been at the forefront of the aging field. Preclinical findings have demonstrated that species, sex and strain confer significant heterogeneity on reaching the desired health- and lifespan-promoting pharmacological responses in model organisms. Translating the safety and efficacy of these interventions to humans and the lack of reliable biomarkers that serve as predictors of health outcomes remain a challenge. Here, we will survey current pharmacological interventions that promote lifespan extension and/or increased healthspan in animals and humans, and review the various anti-aging interventions selected for inclusion in the NIA's Interventions Testing Program as well as the ClinicalTrials.gov database that target aging or age-related diseases in humans.

Energy Restriction and Colorectal Cancer: A Call for Additional Research.

: Colorectal cancer has the second highest cancer-related mortality rate, with an estimated 881,000 deaths worldwide in 2018. The urgent need to reduce the incidence and mortality rate requires innovative strategies to improve prevention, early diagnosis, prognostic biomarkers, and treatment effectiveness. Caloric restriction (CR) is known as the most robust nutritional intervention that extends lifespan and delays the progression of age-related diseases, with remarkable results for cancer protection. Other forms of energy restriction, such as periodic fasting, intermittent fasting, or fasting-mimicking diets, with or without reduction of total calorie intake, recapitulate the effects of chronic CR and confer a wide range of beneficial effects towards health and survival, including anti-cancer properties. In this review, the known molecular, cellular, and organismal effects of energy restriction in oncology will be discussed. Energy-restriction-based strategies implemented in colorectal models and clinical trials will be also revised. While energy restriction constitutes a promising intervention for the prevention and treatment of several malignant neoplasms, further investigations are essential to dissect the interplay between fundamental aspects of energy intake, such as feeding patterns, fasting length, or diet composition, with all of them influencing health and disease or cancer effects. Currently, effectiveness, safety, and practicability of different forms of fasting to fight cancer, particularly colorectal cancer, should still be contemplated with caution.

Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling.

BACKGROUND: Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumors. In this work, we identified a new set of gene markers for CRC associated to prognosis and risk using a large unified cohort of patients with transcriptomic profiles and survival information. RESULTS: We built an integrated dataset with 1273 human colorectal samples, which provides a homogeneous robust framework to analyse genome-wide expression and survival data. Using this dataset we identified two sets of genes that are candidate prognostic markers for CRC in stages III and IV, showing either up-regulation correlated with poor prognosis or up-regulation correlated with good prognosis. The top 10 up-regulated genes found as survival markers of poor prognosis (i.e. low survival) were: DCBLD2, PTPN14, LAMP5, TM4SF1, NPR3, LEMD1, LCA5, CSGALNACT2, SLC2A3 and GADD45B. The stability and robustness of the gene survival markers was assessed by cross-validation, and the best-ranked genes were also validated with two external independent cohorts: one of microarrays with 482 samples; another of RNA-seq with 269 samples. Up-regulation of the top genes was also proved in a comparison with normal colorectal tissue samples. Finally, the set of top 100 genes that showed overexpression correlated with low survival was used to build a CRC risk predictor applying a multivariate Cox proportional hazards regression analysis. This risk predictor yielded an optimal separation of the individual patients of the cohort according to their survival, with a p-value of 8.25e-14 and Hazard Ratio 2.14 (95% CI: 1.75-2.61). CONCLUSIONS: The results presented in this work provide a solid rationale for the prognostic utility of a new set of genes in CRC, demonstrating their potential to predict colorectal tumor progression and evolution towards poor survival stages. Our study does not provide a fixed gene signature for prognosis and risk prediction, but instead proposes a robust set of genes ranked according to their predictive power that can be selected for additional tests with other CRC clinical cohorts.

The ellagic acid derivative 4,4'-di-O-methylellagic acid efficiently inhibits colon cancer cell growth through a mechanism involving WNT16.

Ellagic acid (EA) and some derivatives have been reported to inhibit cancer cell proliferation, induce cell cycle arrest, and modulate some important cellular processes related to cancer. This study aimed to identify possible structure-activity relationships of EA and some in vivo derivatives in their antiproliferative effect on both human colon cancer and normal cells, and to compare this activity with that of other polyphenols. Our results showed that 4,4'-di-O-methylellagic acid (4,4'-DiOMEA) was the most effective compound in the inhibition of colon cancer cell proliferation. 4,4'-DiOMEA was 13-fold more effective than other compounds of the same family. In addition, 4,4'-DiOMEA was very active against colon cancer cells resistant to the chemotherapeutic agent 5-fluoracil, whereas no effect was observed in nonmalignant colon cells. Moreover, no correlation between antiproliferative and antioxidant activities was found, further supporting that structure differences might result in dissimilar molecular targets involved in their differential effects. Finally, microarray analysis revealed that 4,4'-DiOMEA modulated Wnt signaling, which might be involved in the potential antitumor action of this compound. Our results suggest that structural-activity differences between EA and 4,4'-DiOMEA might constitute the basis for a new strategy in anticancer drug discovery based on these chemical modifications.