A ride through the epigenetic landscape: aging reversal by reprogramming

Camillo, Lucas Paulo de Lima; Quinlan, Robert B. A.

doi:10.1007/s11357-021-00358-6

Cited by 23 publications

(20 citation statements)

References 220 publications

(228 reference statements)

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“…Expressing so called Yamanaka factors, OCT4, SOX2, KLF4 and c-MYC (OSKM) converts somatic cells into induced pluripotent stem cells (iPSCs). Ocampo et al have shown the potential of partial reprogramming in tackling aging [97][98][99]. Unlike previous studies that used Yamanaka factors in vivo which could initiate cancer development or teratoma formation, Ocampo and his co-workers have successfully demonstrated that tumor formation can be avoided by shortterm induction of OSKM.…”

Section: Cellular Reprogrammingmentioning

confidence: 99%

Radiation-induced senescence: therapeutic opportunities

Kim¹,

Brown²,

Gordon

2023

Radiat Oncol

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The limitation of cancer radiotherapy does not derive from an inability to ablate tumor, but rather to do so without excessively damaging critical tissues and organs and adversely affecting patient’s quality of life. Although cellular senescence is a normal consequence of aging, there is increasing evidence showing that the radiation-induced senescence in both tumor and adjacent normal tissues contributes to tumor recurrence, metastasis, and resistance to therapy, while chronic senescent cells in the normal tissue and organ are a source of many late damaging effects. In this review, we discuss how to identify cellular senescence using various bio-markers and the role of the so-called senescence-associated secretory phenotype characteristics on the pathogenesis of the radiation-induced late effects. We also discuss therapeutic options to eliminate cellular senescence using either senolytics and/or senostatics. Finally, a discussion of cellular reprogramming is presented, another promising avenue to improve the therapeutic gain of radiotherapy.

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Section: Cellular Reprogrammingmentioning

confidence: 99%

Radiation-induced senescence: therapeutic opportunities

Kim¹,

Brown²,

Gordon

2023

Radiat Oncol

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“…Furthermore, Ocampo et al demonstrated that partial reprogramming, achieved by transient, periodic induction of OSKM (2 days on, then 5 days off, repeated several times), ameliorates signs of ageing without loss of cellular identity [ 74 ]. They conducted partial reprogramming first on progeroid (model for HGPS) mouse fibroblasts and alleviated age-associated hallmarks, such as DNA damage, nuclear envelope damage, dysregulation of histone modifications, stress and senescence associated factors, and mitochondrial-associated reactive oxygen species (ROS) production (cellular and epigenetic differences between aged and young cells and tissues are reviewed in detail in [ 121 , 122 ]). Similar rejuvenation of dysregulated histone modifications was also observed when transient reprogramming was conducted on high-passage human fibroblasts (derived from iPSCs).…”

Section: Reprogramming-induced Epigenetic Rejuvenationmentioning

confidence: 99%

Cellular reprogramming and epigenetic rejuvenation

2021

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Ageing is an inevitable condition that afflicts all humans. Recent achievements, such as the generation of induced pluripotent stem cells, have delivered preliminary evidence that slowing down and reversing the ageing process might be possible. However, these techniques usually involve complete dedifferentiation, i.e. somatic cell identity is lost as cells are converted to a pluripotent state. Separating the rejuvenative properties of reprogramming from dedifferentiation is a promising prospect, termed epigenetic rejuvenation. Reprogramming-induced rejuvenation strategies currently involve using Yamanaka factors (typically transiently expressed to prevent full dedifferentiation) and are promising candidates to safely reduce biological age. Here, we review the development and potential of reprogramming-induced rejuvenation as an anti-ageing strategy.

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“…Important CpG sites are overwhelmingly closer to CTCF binding sites (Supplementary Figure S4). This suggests that epigenetic alterations proximal to such loci may alter chromatin packing by affecting CTCF binding, as chromatin structure modifications have been associated with aging [26].…”

Section: Resultsmentioning

confidence: 99%

“…This observation suggests that epigenetic alterations proximal to such loci that are involved in chromatin packing by affecting CTCF binding may be captured by AltumAge. This result is relevant because chromatin structure modifications have been associated with aging (see review [31]).…”

Section: Altumage Captures Relevant Age-related Cpg-cpg Interactionsmentioning

confidence: 99%

AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning

Camillo

Lapierre

Singh

2021

Preprint

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Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years. Their accuracy and potential for generalization vary widely based on the training data. Here, we gathered 143 publicly available data sets from several human tissues to develop AltumAge, a highly accurate and precise age predictor based on deep learning. Compared to Horvath's 2013 model, AltumAge performs better across both normal and malignant tissues and is more generalizable to new data sets. Interestingly, it can predict gestational week from placental tissue with low error. Lastly, we used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observed that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. We studied the associated genes of these CpG sites and found literary evidence of their involvement in age-related gene regulation. Using chromatin annotations, we observed that the CpG sites with the highest contribution to the model predictions were related to heterochromatin and gene regulatory regions in the genome. We also found age-related KEGG pathways for genes containing these CpG sites. In general, neural networks are better predictors due to their ability to capture complex feature interactions compared to the typically used regularized linear regression. Altogether, our neural network approach provides significant improvement and flexibility to current epigenetic clocks without sacrificing model interpretability.

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A ride through the epigenetic landscape: aging reversal by reprogramming

Cited by 23 publications

References 220 publications

Radiation-induced senescence: therapeutic opportunities

Radiation-induced senescence: therapeutic opportunities

Cellular reprogramming and epigenetic rejuvenation

AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning

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