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DNA methylation age studies. Results for metEPICVal samples according to: Chronological age versus DNAmAge by age groups (A); Age-acceleration differences versus chronological age (B); Boxplot for age-acceleration differences between BCO and BCVY (C). Analogous results for TCGA samples according to: Chronological age versus DNAmAge by age groups (D); Age-acceleration differences versus chronological age (E); Boxplot for age-acceleration difference values between BCO and BCVY (F). Normal breast tissue results: Chronological age versus DNAmAge by age groups (G); Age-acceleration differences versus chronological age (H); Comparison of age-acceleration difference values between cancer and normal tissues (I). Representation of chronological age versus DNAmAge by oestrogen receptor positive and negative for metEPICVal (J) and TCGA samples (K); Age-acceleration differences by oestrogen receptor status for metEPICVal and TCGA data sets (L). Correlation values (r) for chronological age and DNAmAge by age group are included in plot representation.
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Breast cancer in very young women (≤35 years; BCVY) presents more aggressive and complex biological features than their older counterparts (BCO). Our aim was to evaluate methylation differences between BCVY and BCO and their DNA epigenetic age. EPIC and 450k Illumina methylation arrays were used in 67 breast cancer tumours, including 32 from BCVY,...
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... was 64.98 years. We observed in metEPICVal sample set a significant correlation between chronological age and DNAmAge for BCO tumours (r = 0.52, p-value = 0.039). Although, no significant age correlation was found for BCVY (r = 0.14, p-value = 0.52), results shown higher age-acceleration significantly different to BCO (p-value = 5.5 × 10 −4 ) ( Fig. 3A-C). We have reproduced the same analyses to TCGA methylation data detecting also a significant age-acceleration for BCVY (p-value = 6.5 × 10 −3 ) (Fig. 3D-F). We also examined DNAmAge vs. chronological age in normal samples from TCGA data, identifying an extremely good correlation decreasing in women with advanced age (r = 0.88, p-value = ...
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... = 0.039). Although, no significant age correlation was found for BCVY (r = 0.14, p-value = 0.52), results shown higher age-acceleration significantly different to BCO (p-value = 5.5 × 10 −4 ) ( Fig. 3A-C). We have reproduced the same analyses to TCGA methylation data detecting also a significant age-acceleration for BCVY (p-value = 6.5 × 10 −3 ) (Fig. 3D-F). We also examined DNAmAge vs. chronological age in normal samples from TCGA data, identifying an extremely good correlation decreasing in women with advanced age (r = 0.88, p-value = 8.4 × 10 −33 ) (Fig. 3G,H). Despite homogeneously low age-accelerated values for healthy tissues compared with a more dispersed data in cancer samples, ...
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... have reproduced the same analyses to TCGA methylation data detecting also a significant age-acceleration for BCVY (p-value = 6.5 × 10 −3 ) (Fig. 3D-F). We also examined DNAmAge vs. chronological age in normal samples from TCGA data, identifying an extremely good correlation decreasing in women with advanced age (r = 0.88, p-value = 8.4 × 10 −33 ) (Fig. 3G,H). Despite homogeneously low age-accelerated values for healthy tissues compared with a more dispersed data in cancer samples, non-significance was reached (Fig. ...
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... DNAmAge vs. chronological age in normal samples from TCGA data, identifying an extremely good correlation decreasing in women with advanced age (r = 0.88, p-value = 8.4 × 10 −33 ) (Fig. 3G,H). Despite homogeneously low age-accelerated values for healthy tissues compared with a more dispersed data in cancer samples, non-significance was reached (Fig. ...
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... we observed an increased age-acceleration in BCVY-ER+ samples for metEPICVal set (p-value = 0.001), with a similar trend in the BCVY-TCGA cohort (p-value = 0.08). Nevertheless, we found an enrichment of ER+ tumours for BC samples with increased DNAmAge acceleration and we corroborated this association with TCGA (p-value < 2.2 × 10 −16 ) (Fig. 3J-L). Age-acceleration was not associated with relapse or clinical subtypes. Nonetheless, there was an enrichment of luminal/her2 subtype in BCVY samples with increased age-acceleration values for metEPICVal samples that could not be reproduced in TCGA data. Similarly, all BCVY samples with relapse presented increased age-acceleration ...
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Citations
... Few genetic events are significantly linked to those tumors diagnosed at a young age [21,22], with the exceptions of mutations in BRCA1/2 [23], p53 [24], GATA3 [25], and ARID1A [26]. Preliminary reports suggest that circulating tumor cells [27], gene and miRNA expression profiles [28,29], epigenetic alterations [30], and immune modulation [31] may contribute to disease aggressiveness in young patients. Socioeconomic status, adherence to initial and follow-up care [32,33], post-therapy weight gain [34], and complexity in decision making postneoadjuvant therapy [35] have been linked to a young age at diagnosis but, where studied, response to specific molecular therapies was age-independent [36]. ...
Breast cancer in young patients is known to exhibit more aggressive biological behavior and is associated with a less favorable prognosis than the same disease in older patients, owing in part to an increased incidence of brain metastases. The mechanistic explanations behind these findings remain poorly understood. We recently reported that young mice, in comparison to older mice, developed significantly greater brain metastases in four mouse models of triple-negative and luminal B breast cancer. Here we have performed a quantitative mass spectrometry-based proteomic analysis to identify proteins potentially contributing to age-related disparities in the development of breast cancer brain metastases. Using a mouse hematogenous model of brain-tropic triple-negative breast cancer (MDA-MB-231BR), we harvested subpopulations of tumor metastases, the tumor-adjacent metastatic microenvironment, and uninvolved brain tissues via laser microdissection followed by quantitative proteomic analysis using high resolution mass spectrometry to characterize differentially abundant proteins potentially contributing to age-dependent rates of brain metastasis. Pathway analysis revealed significant alterations in signaling pathways, particularly in the metastatic microenvironment, modulating tumorigenesis, metabolic processes, inflammation, and neuronal signaling. Tenascin C (TNC) was significantly elevated in all laser microdissection (LMD) enriched compartments harvested from young mice relative to older hosts, which was validated and confirmed by immunoblot analysis of whole brain lysates. Additional in vitro studies including migration and wound-healing assays demonstrated TNC as a positive regulator of tumor cell migration. These results provide important new insights regarding microenvironmental factors, including TNC, as mechanisms contributing to the increased brain cancer metastatic phenotype observed in young breast cancer patients.
... 39 Accelerated epigenetic age is associated with cancer development 29,40 and cancer also impacts epigenetic age depending on the cancer types. 16,41,42 Since we had access to a long-term cohort, we were able to assess the link between cancer, age, and HIV infection to assess whether there was evidence that cancer further accelerated the epigenetic aging in PLWH. Our results showed that cancers did not further increase age delta in PLWH (Figure 3). ...
Background:
Premature aging has been identified as a global risk factor for cancer. Causes of premature aging are multifactorial, including inflammation, infection, chronic stress, and lifestyle factors.
Method:
We evaluated whether premature aging in people living with HIV (PLWH) was associated with antiretroviral therapy (ART) or the diagnosis of cancer. We used well-established DNA methylation patterns to assess premature aging, using Horvath et al., in individuals with HIV located in Cleveland, Ohio and compared these to standardized datasets of US historical blood samples. Some of the PLWH developed cancer over time.
Results:
We found that DNA methylation analysis identified accelerated aging in PLWH whereas ART therapy mitigated the advancement of DNA methylation age. A variety of cancers were observed in this population, but a cancer diagnosis was not significantly associated with more advanced DNA methylation age.
Conclusion:
We find that the age acceleration detected in PLWH is mitigated by ART therapy and is not further accelerated by a diagnosis of cancer.
... Classic senescence biomarkers include enhanced senescence-associated β-galactosidase activity (SA-β-Gal), accumulation of lipofuscin, loss of lamin B1, upregulation of cell cyclerelated regulators like p16 INK4A and p21 CIP1 , formation of senescence-associated heterochromatin foci (SAHF) and senescence-associated secretory phenotype (SASP) (Kuilman et al., 2010). As they age, cells also lose the Review https://doi.org/10.1631/jzus.B2200178 ability to control DNA methylation and show a DNA methylation landscape like that of cancer cells, providing another prognostic marker for senescence identification (Cruickshanks et al., 2013;Oltra et al., 2019;Shah et al., 2021). There are already successful examples of the use of epigenetic clocks, especially "metaclocks," to precisely predict chronological age (Liu et al., 2020;Sugrue et al., 2021). ...
... Besides, since functionally active T cells are necessary in adoptive cellular immunotherapy (ACT), involving chimeric antigen receptor (CAR)-T cell therapy (CAR-T) and T cell receptor (TCR)-engineered T cell therapy, immunosenescence leads to many more failures in ACT. Thus, undoubtedly, immunosenescence is the most life-threatening among the various types of senescence, and these senescence-associated immune function changes highlight the significance of personalized therapy (Oltra et al., 2019;Liu et al., 2020;Shah et al., 2021). ...
Given its state of stable proliferative inhibition, cellular senescence is primarily depicted as a critical mechanism by which organisms delay the progression of carcinogenesis. Cells undergoing senescence are often associated with the alteration of a series of specific features and functions, such as metabolic shifts, stemness induction, and microenvironment remodeling. However, recent research has revealed more complexity associated with senescence, including adverse effects on both physiological and pathological processes. How organisms evade these harmful consequences and survive has become an urgent research issue. Several therapeutic strategies targeting senescence, including senolytics, senomorphics, immunotherapy, and function restoration, have achieved initial success in certain scenarios. In this review, we describe in detail the characteristic changes associated with cellular senescence and summarize currently available countermeasures.
... For example, Pantissue age acceleration in colon cancer samples has been linked with colon cancer molecular subtypes and improved prognosis prediction because it is linked with overall survival (Zheng et al., 2019). In breast tumor samples, methylation studies within the breast of very young women with more aggressive breast cancer exhibit accelerated DNA methylation age compared with breast cancer in older counterparts, suggesting a role of accelerated epigenetic aging in breast cancer risk (Oltra et al., 2019). In addition, methylation-based markers of cell replication have been associated with cancer risk, including the epigenetic mitotic clock (EpiTOC) which approximates the rate of stem cell division in normal tissues by focusing on promoter CpG sites that localize to PCGT genes, and has been shown to be accelerated in precancerous lesions and cancer (Yang et al., 2016). ...
Accumulation of somatic mutations and genomic instability are hallmarks of both aging and cancer. Epigenetic alterations occur across cell types and tissues with advancing age. DNA methylation-based estimates of biologic age can predict important age-related outcomes, including risk of frailty and mortality, and most recently have been shown to be associated with risk of developing cancer. In this mini-review, we examine pathways known to exhibit altered methylation in aging tissues, pre-malignant lesions, and tumors and review methodologies of epigenetic clocks that reliably predict cancer risk, including those derived from methylation studies of peripheral blood, as well as those methylation levels from within the tissues at high risk of cancer.
... In our analysis, we find that age acceleration is limited to younger patients in the AA group. Such age-accelerated tumors are linked to increased oncogenic signaling and cellular stress (Oltra et al., 2019;Liu et al., 2020). Indeed, we find that younger patients in three of these tumor types are also associated with hallmarks of senescence. ...
Older age is a strong risk factor for several diseases, including cancer. The etiology and biology of age-associated differences among cancers are poorly understood. To address this knowledge gap, we aim to delineate differences in tumor molecular characteristics between younger and older patients across a variety of tumor types from The Cancer Genome Atlas. We show that these groups exhibit widespread molecular differences in select tumor types. Our work shows that tumors in younger individuals exhibit a dysregulated molecular aging phenotype and are associated with hallmarks of premature senescence. Additionally, we find that these tumors are enriched for driver gene mutations, resulting in homologous recombination defects. Lastly, we observe a trend toward decreased immune infiltration and function in older patients and find that, immunologically, young tumor tissue resembles aged healthy tissue. Taken together, we find that tumors from young individuals possess unique characteristics that may be leveraged for therapy.
... BC is the most frequent type of cancer (14%), after lung cancer (14.6%) (1), and has been reported to be the leading cause of cancer-associated death among females worldwide (2). BC accounts for ~40% of all types of cancer that develop after the age of 40 years, while 6.6% of cases arise prior to the age of 40 years (3). The prognosis of BC is associated with early diagnosis, which is detected using mammography (4), while the CA15-3 and CA27-29 markers are used for monitoring the recovery of the disease and the effectiveness of treatment (5,6). ...
... Devall et al. observed that higher DNAm age rates contributed to young age onset of colon cancer in African Americans [10]. Moreover, in patients with breast and colorectal cancer, their matched normal tissues frequently display significantly accelerated DNAm age [32][33][34][35]. However, our present results revealed that most of 54 NT samples (37/54) from TC patients displayed much younger DNAm age than their chronological age, which was contrary to the findings in other tissues above. ...
Alterations in global DNA methylation play a critical role in both aging and cancer, and DNA methylation (DNAm) age drift has been implicated in cancer risk and pathogenesis. In the present study, we analyzed the TCGA cohort of papillary and follicular thyroid carcinoma (PTC and FTC) for their DNAm age and association with clinic-pathological features. In 54 noncancerous thyroid (NT) samples, DNAm age was highly correlated with patient chronological age (R2 = 0.928, p = 2.6 × 10−31), but drifted to younger than chronological age in most specimens, especially those from patients >50 years old. DNAm age in 502 tumors was also correlated with patient chronological age, but to a much lesser extent (R2 = 0.403). Highly drifted DNAm age (HDDA) was identified in 161 tumors, among which were 101 with DNAm age acceleration while 60 with DNAm age deceleration. Tumors with HDDA were characterized by the robust aberrations in metabolic activities, extracellular microenvironment components and inflammation/immunology responses, and dedifferentiation. Importantly, HDDA in tumors independently predicted shorter disease-free survival of patients. Collectively, NT thyroids from TC patients have younger DNAm age, while HDDA frequently occurs in TCs, and contributes to the TC progression and poor patient outcomes. HDDA may serve as a new prognostic factor for TCs.
... Our finding that earlier age at menarche is associated with accelerated aging in breast is consistent with a recent study demonstrating that Pan-tissue age acceleration in peripheral blood was associated with faster pubertal development in girls (24). Recent studies have shown that comparing breast tumor tissues of very young women (age ≤ 35 years) with those of older women, the age difference (pan-tissue age -chronologic age) is higher in breast tumor tissue from younger women with breast cancer (25). These findings, taken together with our finding that the difference (pan-tissue age -chronologic age) is higher at younger ages, suggest that accelerated epigenetic aging may drive breast carcinogenesis in young women. ...
Background:
Estrogens are thought to contribute to breast cancer risk through cell cycling and accelerated breast aging. We hypothesize that lifetime estrogen exposure drives early epigenetic breast aging observed in healthy women. In this study, we examined associations between hormonal factors and epigenetic aging measures in healthy breast tissues.
Methods:
We extracted DNA from breast tissue specimens from 192 healthy female donors to the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center. Methylation experiments were performed using the Illumina EPIC 850K array platform. Age-adjusted regression models were used to examine for associations between factors related to estrogen exposure and five DNA methylation-based estimates: Grim age, Pan-tissue age, Hannum age, Phenotypic age, and Skin and Blood Clock age.
Results:
Women were aged 19-90 years, with 95 pre-menopausal, and 97 nulliparous women. The age difference (Grim age - chronologic age) was higher at earlier ages close to menarche. We found significant associations between earlier age at menarche and age-adjusted accelerations according to the Grim clock, the Skin and Blood clock, and between higher body mass index (BMI) and age-adjusted accelerations in the Grim clock, Hannum clock, Phenotypic clock, and Skin and Blood clock.
Conclusions:
Earlier age at menarche and higher BMI are associated with elevations in DNA methylation-based age estimates in healthy breast tissues, suggesting that cumulative estrogen exposure drives breast epigenetic aging.
Impact:
Epigenetic clock measures may help advance inquiry into the relationship between accelerated breast tissue aging and an elevated incidence of breast cancer in younger women.
... Pathways affected by methylation in EOBC include those related to the neuronal system, extracellular matrix modulation, immune system, DNA repair, Notch/Notch1 signaling, and vesicular trafficking. DNA methylation in EOBC resulted in significant upregulation of HDAC5 which proved to promote tamoxifen resistance through cancer stem cell-related transcription factor SOX9 deacetylation, as well as significant downregulation of EHF that involves in epithelial mesenchymal transition inducing metastasis [116]. ...
Breast cancer commonly affects women of older age; however, in developing countries, up to 20% of breast cancer cases present in young women (younger than 40 years as defined by oncology literature). Breast cancer in young women is often defined to be aggressive in nature, usually of high histological grade at the time of diagnosis and negative for endocrine receptors with poor overall survival rate. Several researchers have attributed this aggressive nature to a hidden unique biology. However, findings in this aspect remain controversial. Thus, in this article, we aimed to review published work addressing somatic mutations, chromosome copy number variants, single nucleotide polymorphisms, differential gene expression, microRNAs and gene methylation profile of early-onset breast cancer, as well as its altered pathways resulting from those aberrations. Distinct biology behind early-onset of breast cancer was clear among estrogen receptor-positive and sporadic cases. However, further research is needed to determine and validate specific novel markers, which may help in customizing therapy for this group of patients.
... For example, breast CSCs possess elevated levels of DNMT1, which is critical for their self-renewal (Fig. 2c) [136]. Moreover, differentially expressed methylation patterns observed in young BC patients (< 35 years) versus old patients are associated with the aggressiveness of the disease [137]. In addition, specific DNA methylation patterns confer breast CSCs resistance to treatment by modulating their TGF-β signaling pathway, which is involved in cellular growth [138]. ...
Cancer remains one of the most challenging diseases despite significant advances of early diagnosis and therapeutic treatments. Cancerous tumors are composed of various cell types including cancer stem cells capable of self-renewal, proliferation, differentiation, and invasion of distal tumor sites. Most notably, these cells can enter a dormant cellular state that is resistant to conventional therapies. Thereby, cancer stem cells have the intrinsic potential for tumor initiation, tumor growth, metastasis, and tumor relapse after therapy. Both genetic and epigenetic alterations are attributed to the formation of multiple tumor types. This review is focused on how epigenetic dynamics involving DNA methylation and DNA oxidations are implicated in breast cancer and glioblastoma multiforme. The emergence and progression of these cancer types rely on cancer stem cells with the capacity to enter quiescence also known as a dormant cellular state, which dictates the distinct tumorigenic aggressiveness between breast cancer and glioblastomas.
