[Aging and carcinogenesis].

V N Anisimov

Home/Archive/PubMed

PubMed · 12577699

[Aging and carcinogenesis].

V N Anisimov

View original source ↗Export metadata ↓

Abstract

The incidence of cancer increases with age in humans and in laboratory animals alike. There are different patterns of age-related distribution of tumors in different organs and tissues. Aging may increase of decrease the susceptibility of various tissues to initiation of carcinogenesis and usually facilitates promotion and progression of carcinogenesis. Aging may predispose to cancer by several mechanisms: 1) tissue accumulation of cells in late stages of carcinogenesis; 2) alterations in homeostasis, in particular, alterations in immune and endocrine system and 3) telomere instability linking aging and increased cancer risk. Increased susceptibility to the effects of tumor promoters is found both in aged animals and aged humans, as predicted by the multistage model of carcinogenesis. Available evidence supporting the relevance of replicative senescence of human cells and telomere biology to human cancer seems quite strong, however the evidence linking cellular senescence to human aging is controversial and required additional studies. Some common genetic processes (e.g. telomere dysfunction, changes in p53 and Rb activity and in DNA repair, accumulation of DNA lesions, genomic instability) play a critical role both in carcinogenesis and aging. Data on the acceleration of aging by carcinogenic agents as well as on increased cancer risk in patients with premature aging are critically discussed. In genetically modified mouse models (transgenic, knockout or mutant) characterized by the aging delay the incidence of tumors usually similar to those in controls, whereas the latent period of tumor development is increased. Practically all models of accelerated of aging in genetically modified animals show the increase in the incidence and the decline in the latency of tumors. Strategies for cancer prevention must include not only measures to minimize exposure to exogenous carcinogenic agents, but also measures to normalize the age-related alterations in internal milieu. Life-span prolonging drugs (geroprotectors) and genetic modifications may either postpone population aging and increase of tumor latency or decrease the mortality in long-living individuals in populations and inhibit carcinogenesis. At least some geroprotectors and modifications may increase the survival of a short-living individuals in populations but increase the incidence of malignancy.

Explore related subjects

Aging Animals Cell Transformation, Neoplastic Humans Neoplasms English Abstract Journal Article Review

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

V N Anisimov. 2002. [Aging and carcinogenesis].. https://pubmed.ncbi.nlm.nih.gov/12577699/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

An open benchmark and language models for AI in aging biology.

Over the past two decades, human aging has been characterized across DNA methylation, transcriptomic, proteomic, and clinical modalities, yet no benchmark evaluates whether AI systems can interpret these heterogeneous data types in the context of aging biology. We introduce LongevityBench, an open suite of 17 tasks spanning five biodata domains, and use it to assess 18 frontier AI systems from six developer teams. Despite recent advances in AI, no single model dominates all tasks, with omics-based age prediction being the hardest task regardless of scale. To test whether these gaps can be closed without frontier-scale resources, we fine-tuned a family of five multitask Longevity-LLMs on domain-specific aging data. The compact (0.6B-9B parameters) Longevity-LLMs matched or exceeded far larger frontier systems on LongevityBench, showing that general-purpose language models can be adapted to structured-omics tasks. We publicly release the benchmark, models, and Longevity Claw, an agentic research interface for aging researchers.

Aging↗

PubMed2026

Association between sirtuin 1 and markers of oxidative stress in master athletes.

BACKGROUND: Lifelong training in master athletes confers protective effects, promoting higher sirtuin levels and enhanced antioxidant capacity. Although Sirtuin 1 (SIRT1) is well studied, no previous study has examined the relationship between circulating SIRT1 levels and antioxidant defense variables in master athletes. PURPOSE: To compare and analyze the relationships between circulating levels of SIRT1 and variables related to antioxidant defense in master athletes (MA) and untrained middle-aged individuals (UMA). METHODS: Male MA (n = 42; 51.62 ± 7.33 years; ≥10 years of training and competition in running) and UMA (n = 15; 47.73 ± 8.52 years) were evaluated. Venous blood samples were collected for biochemical analyses of SIRT1, antioxidant enzymes, TBARS and F2-isoprostanes, 8-OHdG, and redox balance indexes. RESULTS: MA showed higher levels of SIRT1 (18.22 ± 4.53 vs. 6.08 ± 2.11 ng/mL; p < 0.0001), as well as of SOD, CAT, and GSH (p < 0.001), indicating a more favorable antioxidant profile. After adjustment for body fat percentage, differences in SOD, CAT, GSH and TBARS, remained significant. SIRT1 was positively correlated with SOD (r = 0.279; p = 0.031), CAT (r = 0.485; p < 0.001), GSH (r = 0.476; p < 0.001) and CAT/8-OHdG (r = 0.430; p = 0.032), and negatively correlated with TBARS (r = - 0.518; p < 0.001). CONCLUSION: Master athletes exhibited higher circulating SIRT1 concentrations and a more favorable systemic redox profile than untrained individuals, with SIRT1 being associated with markers of antioxidant defense, lipid peroxidation, and redox balance.

Aging↗

PubMed2026

Decoding SUMOylation as a metabolic stress sensor in aging and age-related disorders: Mechanisms, tissue specificity and therapeutic potential.

SUMOylation is a reversible post-translational modification increasingly recognized for its role in coordinating cellular responses to metabolic stress during aging. Emerging evidence indicates that it functions beyond a conventional modification, representing an adaptive stress‑responsive regulatory network that integrates metabolic, oxidative, inflammatory, and proteotoxic signals. Rather than acting on isolated pathways, this network finely tunes mitochondrial function, proteostasis, genome maintenance, immune balance, and epigenetic regulation. Accumulating evidence indicates that SUMO-dependent regulation exhibits remarkable tissue specificity, supporting mitochondrial adaptation and contractile integrity in skeletal muscle, shaping lipid and glucose metabolism in the liver, modulating proteotoxic stress and neuronal resilience in the brain, and contributing to immune cell differentiation and chronic low-grade inflammation during aging. In this review, we summarize current mechanistic insights into SUMO signaling across aging-relevant tissues, with particular emphasis on its functional interplay with other post-translational modifications, including ubiquitination and acetylation. We discuss how SUMOylation operates as a shared regulatory layer while enabling context-dependent outcomes that underlie diverse aging phenotypes and age-related disorders. Finally, we evaluate emerging translational approaches-ranging from pharmacological modulation of SUMO enzymes to lifestyle interventions such as caloric restriction and exercise-that highlight both the opportunities and challenges of targeting SUMO-regulated stress responses in aging. Together, this synthesis provides a framework for understanding how SUMOylation links metabolic stress to tissue-specific aging trajectories and therapeutic potential.

Aging↗