Somatic mutations in human ageing: New insights from DNA sequencing and inherited mutations.

The accumulation of somatic mutations is a driver of cancer and has long been associated with ageing. Due to limitations in quantifying mutation burden with age in non-cancerous tissues, the impact of somatic mutations in other ageing phenotypes is unclear. Recent advances in DNA sequencing technologies have allowed the large-scale quantification of somatic mutations in ageing tissues. These studies have revealed a gradual accumulation of mutations in normal tissues with age as well as a substantial clonal expansion driven mostly by cancer-related mutations. Nevertheless, it is difficult to envision how the burden and stochastic nature of age-related somatic mutations identified so far can explain most ageing phenotypes that develop gradually. Studies across species have also found that longer-lived species have lower somatic mutation rates, though these could be due to selective pressures acting on other phenotypes such as perhaps cancer. Recent studies in patients with higher somatic mutation burden and no signs of accelerated ageing further question the role of somatic mutations in ageing. Overall, with a few exceptions like cancer, recent DNA sequencing studies and inherited mutations do not support the idea that somatic mutations accumulating with age drive ageing phenotypes, and the phenotypic role, if any, of somatic mutations in ageing remains unclear.

Human Ageing Genomic Resources: updates on key databases in ageing research.

Ageing is a complex and multifactorial process. For two decades, the Human Ageing Genomic Resources (HAGR) have aided researchers in the study of various aspects of ageing and its manipulation. Here, we present the key features and recent enhancements of these resources, focusing on its six main databases. One database, GenAge, focuses on genes related to ageing, featuring 307 genes linked to human ageing and 2205 genes associated with longevity and ageing in model organisms. AnAge focuses on ageing, longevity, and life-history across animal species, containing data on 4645 species. DrugAge includes information about 1097 longevity drugs and compounds in model organisms such as mice, rats, flies, worms and yeast. GenDR provides a list of 214 genes associated with the life-extending benefits of dietary restriction in model organisms. CellAge contains a catalogue of 866 genes associated with cellular senescence. The LongevityMap serves as a repository for genetic variants associated with human longevity, encompassing 3144 variants pertaining to 884 genes. Additionally, HAGR provides various tools as well as gene expression signatures of ageing, dietary restriction, and replicative senescence based on meta-analyses. Our databases are integrated, regularly updated, and manually curated by experts. HAGR is freely available online (https://genomics.senescence.info/).

Transcriptomic analysis reveals a tissue-specific loss of identity during ageing and cancer.

INTRODUCTION: Understanding changes in cell identity in cancer and ageing is of great importance. In this work, we analyzed how gene expression changes in human tissues are associated with tissue specificity during cancer and ageing using transcriptome data from TCGA and GTEx. RESULTS: We found significant downregulation of tissue-specific genes during ageing in 40% of the tissues analyzed, which suggests loss of tissue identity with age. For most cancer types, we have noted a consistent pattern of downregulation in genes that are specific to the tissue from which the tumor originated. Moreover, we observed in cancer an activation of genes not usually expressed in the tissue of origin as well as an upregulation of genes specific to other tissues. These patterns in cancer were associated with patient survival. The age of the patient, however, did not influence these patterns. CONCLUSION: We identified loss of cellular identity in 40% of the tissues analysed during human ageing, and a clear pattern in cancer, where during tumorigenesis cells express genes specific to other organs while suppressing the expression of genes from their original tissue. The loss of cellular identity observed in cancer is associated with prognosis and is not influenced by age, suggesting that it is a crucial stage in carcinogenesis.

GeneFriends: gene co-expression databases and tools for humans and model organisms.

Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.

Intercellular communication analysis of the human retinal pigment epithelial and choroidal cells predicts pathways associated with aging, cellular senescence and age-related macular degeneration.

The retinal pigment epithelium (RPE) and the choroid are ocular tissues with fundamental roles in supporting neuroretinal function. The pathogenesis of age-related macular degeneration (AMD), a leading cause of irreversible blindness for which aging is the highest risk factor is closely linked with progressive impairment of various functions of these tissues. Cellular senescence, marked by cell cycle arrest and secretion of proinflammatory factors, is known to be associated with aging and has been proposed as a potential driver of AMD. Here, we investigated the role played by intercellular communication in the RPE/choroid within the context of aging, senescence and AMD. We inferred cell-cell interactions in the RPE/choroid by applying CellChat and scDiffCom on a publicly available scRNA-seq dataset from three human donors with and without AMD. We identified age-regulated ligand and receptor genes by using limma on a separate publicly available bulk microarray dataset providing RPE/choroid samples at multiple time points. Cellular senescence was investigated by assigning a score to each cell and each sample of these scRNA-seq and microarray datasets, respectively, based on the expression of key signature genes determined by a previous senescence meta-analysis. We identified VEGF-, BMP-and tenascin-mediated pathways supporting some of the strongest cell-cell interactions between RPE cells, fibroblasts and choroidal endothelial cells and as strong intercellular communication pathways related to both aging and senescence. Their signaling strength was enhanced between subpopulations of cells having high senescence scores. Predominant ligands of these pathways were upregulated with age whereas predominant receptors were downregulated. Globally, we also observed that cells from AMD samples presented slightly bigger senescence scores than normal cells and that the senescence score positively correlated with age in bulk samples (R = 0.26, value of p < 0.01). Hence, our analysis provides novel information on RPE/choroid intercellular communication that gives insights into the connection between aging, senescence and AMD.

Age-associated differences in the cancer molecular landscape.

Cancer is an age-related disease, as incidence and mortality for most types of cancer increase with age. However, how molecular alterations in tumors differ among patients of different ages remains poorly understood. Recent studies have shed light on the age-associated molecular landscapes in cancer. Here, we summarize the main findings of these current studies, highlighting major differences in the genomic, transcriptomic, epigenetic, and immunological landscapes between cancer in younger and older patients. Importantly, some cancer driver genes are mutated more frequently in younger or older patients. We discuss the potential roles of aging-related processes in shaping these age-related differences in cancer. We further emphasize the remaining unsolved questions that could provide important insights that will have implications in personalized medicine.

An integrative analysis of the age-associated multi-omic landscape across cancers.

Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients' age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

Expression and roles of system L amino acid transporters in human embryonal carcinoma cells.

BACKGROUND: Testicular germ cell tumors (TGCTs) are the most common malignant cancer in young men. Although TGCTs are generally responsive to platinum-based chemotherapy particularly cisplatin, acquired resistance in patients with metastasis still occurs resulting in poor prognosis. Specifically, differentiation of embryonal carcinoma (EC) cells, the stem cells of TGCTs, can lead to the reduction of cisplatin responsiveness. Therefore, novel therapeutic strategies for TGCTs are needed. System L amino acid transporters have been reported to be up-regulated and to play an important role in tumorigenesis. However, expression and role of system L amino acid transporters in TGCTs remain elusive. MATERIALS AND METHODS: Expression of system L amino acid transporters was analyzed in TGCT samples from The Cancer Genome Atlas (TCGA). Expression of LAT1, LAT2, and 4F2hc was examined in human embryonal carcinoma cell line NTERA2. Roles of system L amino acid transporters on NTERA2 cell survival, cell proliferation, pluripotency, and cisplatin sensitivity were evaluated. RESULTS: Based upon TCGA datasets, we found that two isoforms of system L (LAT1 and LAT2) and their chaperone protein 4F2hc are highly expressed in EC samples compared with other groups. Treatment with the system L inhibitor BCH significantly suppressed leucine uptake into the pluripotent EC cell line NTERA2. The malignant phenotypes including cell viability, cell proliferation, and clonal ability were decreased following BCH treatment. Nonetheless, system L inhibition did not alter expression of stemness genes in NTERA2 cells. After NTERA2 differentiation, expressions of LAT1 and LAT2 were decreased. Finally, co-administration of BCH enhanced cisplatin sensitivity in both undifferentiated and differentiated cells. These effects were associated with the reduction in p70S6K phosphorylation. CONCLUSION: Taken together, these results shed light on the roles of system L amino acid transporters in TGCTs. Therefore, system L amino acid transporters could provide novel therapeutic targets for treatment against TGCTs.

A multidimensional systems biology analysis of cellular senescence in aging and disease.

BACKGROUND: Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of aging and has been linked to aging-related diseases. Many genes play a role in cellular senescence, yet a comprehensive understanding of its pathways is still lacking. RESULTS: We develop CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes driving cellular senescence, and perform various integrative analyses. Genes inducing cellular senescence tend to be overexpressed with age in human tissues and are significantly overrepresented in anti-longevity and tumor-suppressor genes, while genes inhibiting cellular senescence overlap with pro-longevity and oncogenes. Furthermore, cellular senescence genes are strongly conserved in mammals but not in invertebrates. We also build cellular senescence protein-protein interaction and co-expression networks. Clusters in the networks are enriched for cell cycle and immunological processes. Network topological parameters also reveal novel potential cellular senescence regulators. Using siRNAs, we observe that all 26 candidates tested induce at least one marker of senescence with 13 genes (C9orf40, CDC25A, CDCA4, CKAP2, GTF3C4, HAUS4, IMMT, MCM7, MTHFD2, MYBL2, NEK2, NIPA2, and TCEB3) decreasing cell number, activating p16/p21, and undergoing morphological changes that resemble cellular senescence. CONCLUSIONS: Overall, our work provides a benchmark resource for researchers to study cellular senescence, and our systems biology analyses reveal new insights and gene regulators of cellular senescence.

Ageing-associated changes in the expression of lncRNAs in human tissues reflect a transcriptional modulation in ageing pathways.

Ageing-associated changes in the protein coding transcriptome have been extensively characterised, but less attention has been paid to the non-coding portion of the human genome, especially to long non-coding RNAs (lncRNAs). Only a minority of known lncRNAs have been functionally characterised; however, a handful of these lncRNAs have already been linked to ageing-associated processes. To gain more information on the effects of ageing on lncRNAs, we identified from GTEx data lncRNAs that show ageing-associated expression patterns (age-lncRNAs) in 29 human tissues in 20-79-year-old individuals. The age-lncRNAs identified were highly tissue-specific, but the protein coding genes co-expressed with the age-lncRNAs and the functional categories associated with the age-lncRNAs showed significant overlap across tissues. Functions associated with the age-lncRNAs, including immune system processes and transcription, were similar to what has previously been reported for protein coding genes with ageing-associated expression pattern. As the tissue-specific age-lncRNAs were associated with shared functions across tissues, they may reflect the tissue-specific fine-tuning of the common ageing-associated processes. The present study can be utilised as a resource when selecting and prioritising lncRNAs for further functional analyses.

A human tissue-specific transcriptomic analysis reveals a complex relationship between aging, cancer, and cellular senescence.

Aging is the biggest risk factor for cancer, but the mechanisms linking these two processes remain unclear. Using GTEx and TCGA data, we compared genes differentially expressed with age and genes differentially expressed in cancer among nine human tissues. In most tissues, aging and cancer gene expression pattern changed in the opposite direction. The exception was thyroid and uterus, where we found transcriptomic changes in the same direction in aging and in their corresponding cancers. The overlapping sets between genes differentially expressed with age and genes differentially expressed in cancer across tissues were enriched for several processes, mainly cell cycle and the immune system. Moreover, cellular senescence signatures, derived from a meta-analysis, changed in the same direction as aging in human tissues and in the opposite direction of cancer signatures. Therefore, transcriptomic changes in aging and in cellular senescence might relate to a decrease in cell proliferation, while cancer transcriptomic changes shift toward enhanced cell division. Our results highlight the complex relationship between aging and cancer and suggest that, while in general aging processes might be opposite to cancer, the transcriptomic links between human aging and cancer are tissue-specific.