HALL: a comprehensive database for human aging and longevity studies.

Diverse individuals age at different rates and display variable susceptibilities to tissue aging, functional decline and aging-related diseases. Centenarians, exemplifying extreme longevity, serve as models for healthy aging. The field of human aging and longevity research is rapidly advancing, garnering significant attention and accumulating substantial data in recent years. Omics technologies, encompassing phenomics, genomics, transcriptomics, proteomics, metabolomics and microbiomics, have provided multidimensional insights and revolutionized cohort-based investigations into human aging and longevity. Accumulated data, covering diverse cells, tissues and cohorts across the lifespan necessitates the establishment of an open and integrated database. Addressing this, we established the Human Aging and Longevity Landscape (HALL), a comprehensive multi-omics repository encompassing a diverse spectrum of human cohorts, spanning from young adults to centenarians. The core objective of HALL is to foster healthy aging by offering an extensive repository of information on biomarkers that gauge the trajectory of human aging. Moreover, the database facilitates the development of diagnostic tools for aging-related conditions and empowers targeted interventions to enhance longevity. HALL is publicly available at https://ngdc.cncb.ac.cn/hall/index.

Lineage Landscape: a comprehensive database that records lineage commitment across species.

Commitment to specific cell lineages is critical for mammalian embryonic development. Lineage determination, differentiation, maintenance, and organogenesis result in diverse life forms composed of multiple cell types. To understand the formation and maintenance of living individuals, including human beings, a comprehensive database that integrates multi-omic information underlying lineage differentiation across multiple species is urgently needed. Here, we construct Lineage Landscape, a database that compiles, analyzes and visualizes transcriptomic and epigenomic information related to lineage development in a collection of species. This landscape draws together datasets that capture the ongoing changes in cell lineages from classic model organisms to human beings throughout embryonic, fetal, adult, and aged stages, providing comprehensive, open-access information that is useful to researchers of a broad spectrum of life science disciplines. Lineage Landscape contains single-cell gene expression and bulk transcriptomic, DNA methylation, histone modifications, and chromatin accessibility profiles. Using this database, users can explore genes of interest that exhibit dynamic expression patterns at the transcriptional or epigenetic levels at different stages of lineage development. Lineage Landscape currently includes over 6.6 million cells, 15 million differentially expressed genes and 36 million data entries across 10 species and 34 organs. Lineage Landscape is free to access, browse, search, and download at http://data.iscr.ac.cn/lineage/#/home.

The Heterogeneous Cellular States of Glioblastoma Stem Cells Revealed by Single Cell Analysis.

Glioblastoma stem cells (GSCs) contributed to the progression, treatment resistance, and relapse of glioblastoma (GBM). However, current researches on GSCs were performed usually outside the human tumor microenvironment, ignoring the importance of the cellular states of primary GSCs. In this study, we leveraged single-cell transcriptome sequencing data of 6 independent GBM cohorts from public databases, and combined lineage and stemness features to identify primary GSCs. We dissected the cell states of GSCs and correlated them with the clinical outcomes of patients. As a result, we constructed a cellular hierarchy where GSCs resided at the center. In addition, we identified and characterized 2 different and recurrent GSCs subpopulations: proliferative GSCs (pGSCs) and quiescent GSCs (qGSCs). The pGSCs showed high cell cycle activity, indicating rapid cell division, while qGSCs showed a quiescent state. Then we traced the processes of tumor development by pseudo-time analysis and tumor phylogeny, and found that GSCs accumulated throughout the whole tumor development period. During the process, pGSCs mainly contributed to the early stage and qGSCs were enriched in the later stage. Finally, we constructed an 8-gene prognostic signature reflecting pGSCs activity and found that patients whose tumors were enriched for the pGSC signature had poor clinical outcomes. Our study highlights the primary GSCs heterogeneity and its correlation to tumor development and clinical outcomes, providing the potential targets for GBM treatment.

Regeneration Roadmap: database resources for regenerative biology.

Regeneration plays an instrumental role in biological development and damage repair by constructing and replacing cells, tissues, and organs. Since regenerative capacity declines with age, promoting regeneration is heralded as a potential strategy for delaying aging. On this premise, mechanisms that regulate regeneration have been extensively studied across species and in different tissues. However, an open and comprehensive database collecting and standardizing the abundant data generated in regeneration research, such as high-throughput sequencing data, remains to be developed. In this work, we constructed Regeneration Roadmap to systematically and comprehensively collect such information over 2.38 million data entries across 11 species and 36 tissues, including regeneration-related genes, bulk and single-cell transcriptomics, epigenomics, and pharmacogenomics data. In this database, users can explore regulatory and expression changes of regeneration-associated genes in different species and tissues. Regeneration Roadmap provides the research community with a long-awaited and valuable data resource featuring convenient computing and visualizing tools, which is publicly available at https://ngdc.cncb.ac.cn/regeneration/index.

BMAL1 moonlighting as a gatekeeper for LINE1 repression and cellular senescence in primates.

Aging in humans is intricately linked with alterations in circadian rhythms concomitant with physiological decline and stem cell exhaustion. However, whether the circadian machinery directly regulates stem cell aging, especially in primates, remains poorly understood. In this study, we found that deficiency of BMAL1, the only non-redundant circadian clock component, results in an accelerated aging phenotype in both human and cynomolgus monkey mesenchymal progenitor cells (MPCs). Unexpectedly, this phenotype was mainly attributed to a transcription-independent role of BMAL1 in stabilizing heterochromatin and thus preventing activation of the LINE1-cGAS-STING pathway. In senescent primate MPCs, we observed decreased capacity of BMAL1 to bind to LINE1 and synergistic activation of LINE1 expression. Likewise, in the skin and muscle tissues from the BMAL1-deficient cynomolgus monkey, we observed destabilized heterochromatin and aberrant LINE1 transcription. Altogether, these findings uncovered a noncanonical role of BMAL1 in stabilizing heterochromatin to inactivate LINE1 that drives aging in primate cells.

Systematic investigation of the prognostic impact of clonal status of somatic mutations across multiple cancer types.

Tumors are genetically heterogeneous and many mutations are actually present in subclonal populations. The clonal status of mutations is valuable for accurate prognosis, clinical management. The aim of this study was to identify the clonal status of somatic mutations and systematically evaluate their prognostic values across various cancer types. We totally identified 227 clonal and 432 subclonal mutations contributed to prognosis and demonstrated the importance of clonal status in improving mutation-related clinical guidance. We further developed a customized multi-step approach to identify gene-specific prognostic patterns of clonal status at pan-cancer level and found some cancer-specific prognostic patterns. The 'subclonal-dependent risk' subpattern was one of the most common subpatterns, it usually accompanied by high genomic in-stability and high extent of intra-tumor heterogeneity and could be used to improve the accuracy of prognostic analysis. Our results revealed the importance of clonal status, especially subclonal mutation in clinical survival.

CancerSEA: a cancer single-cell state atlas.

High functional heterogeneity of cancer cells poses a major challenge for cancer research. Single-cell sequencing technology provides an unprecedented opportunity to decipher diverse functional states of cancer cells at single-cell resolution, and cancer scRNA-seq datasets have been largely accumulated. This emphasizes the urgent need to build a dedicated resource to decode the functional states of cancer single cells. Here, we developed CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/ or http://202.97.205.69/CancerSEA/), the first dedicated database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level. CancerSEA portrays a cancer single-cell functional state atlas, involving 14 functional states (including stemness, invasion, metastasis, proliferation, EMT, angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, hypoxia, inflammation and quiescence) of 41 900 cancer single cells from 25 cancer types. It allows querying which functional states are associated with the gene (or gene list) of interest in different cancers. CancerSEA also provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single-cell datasets. In summary, CancerSEA provides a user-friendly interface for comprehensively searching, browsing, visualizing and downloading functional state activity profiles of tens of thousands of cancer single cells and the corresponding PCGs/lncRNAs expression profiles.

A single-cell transcriptomic atlas of exercise-induced anti-inflammatory and geroprotective effects across the body.

Exercise benefits the whole organism, yet, how tissues across the body orchestrally respond to exercise remains enigmatic. Here, in young and old mice, with or without exercise, and exposed to infectious injury, we characterized the phenotypic and molecular adaptations to a 12-month exercise across 14 tissues/organs at single-cell resolution. Overall, exercise protects tissues from infectious injury, although more effectively in young animals, and benefits aged individuals in terms of inflammaging suppression and tissue rejuvenation, with structural improvement in the central nervous system and systemic vasculature being the most prominent. In vascular endothelial cells, we found that readjusting the rhythmic machinery via the core circadian clock protein BMAL1 delayed senescence and facilitated recovery from infectious damage, recapitulating the beneficial effects of exercise. Our study underscores the effect of exercise in reconstituting the youthful circadian clock network and provides a foundation for further investigating the interplay between exercise, aging, and immune challenges across the whole organism.

Decoding aging-dependent regenerative decline across tissues at single-cell resolution.

Regeneration across tissues and organs exhibits significant variation throughout the body and undergoes a progressive decline with age. To decode the relationships between aging and regenerative capacity, we conducted a comprehensive single-cell transcriptome analysis of regeneration in eight tissues from young and aged mice. We employed diverse analytical models to study tissue regeneration and unveiled the intricate cellular and molecular mechanisms underlying the attenuated regenerative processes observed in aged tissues. Specifically, we identified compromised stem cell mobility and inadequate angiogenesis as prominent contributors to this age-associated decline in regenerative capacity. Moreover, we discovered a unique subset of Arg1+ macrophages that were activated in young tissues but suppressed in aged regenerating tissues, suggesting their important role in age-related immune response disparities during regeneration. This study provides a comprehensive single-cell resource for identifying potential targets for interventions aimed at enhancing regenerative outcomes in the aging population.

Biomarkers of aging.

Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.

Single-Cell Transcriptomic Analysis Reveals the Crosstalk Propensity Between the Tumor Intermediate State and the CD8+ T Exhausted State to be Associated with Clinical Benefits in Melanoma.

Heterogeneous crosstalk between tumor cells and CD8+ T cells leads to substantial variation in clinical benefits from immunotherapy in melanoma. Due to spatial distribution and functional state heterogeneity, it is still unknown whether there is a crosstalk propensity between tumor cells and CD8+ T cells in melanoma, and how this crosstalk propensity affects the clinical outcome of patients. Using public single-cell transcriptome data, extensive heterogeneous functional states and ligand-receptor interactions of tumor cells and CD8+ T cells were revealed in melanoma. Furthermore, based on the association between cell-cell communication intensity and cell state activity in a single cell, we identified a crosstalk propensity between the tumor intermediate state and the CD8+ T exhausted state. This crosstalk propensity was further verified by pseudo-spatial proximity, spatial co-location, and the intra/intercellular signal transduction network. At the sample level, the tumor intermediate state and the CD8+ T exhausted state synergistically indicated better prognosis and both reduced in immunotherapy-resistant samples. The risk groups defined based on these two cell states could comprehensively reflect tumor genomic mutations and anti-tumor immunity information. The low-risk group had a higher BRAF mutation fraction as well as stronger antitumor immune response. Our findings highlighted the crosstalk propensity between the tumor intermediate state and the CD8+ T exhausted state, which may serve as a reference to guide the development of diagnostic biomarkers for risk stratification and therapeutic targets for new therapeutic strategies.

Identifying Key Somatic Copy Number Alterations Driving Dysregulation of Cancer Hallmarks in Lower-Grade Glioma.

Somatic copy-number alterations (SCNAs) are major contributors to cancer development that are pervasive and highly heterogeneous in human cancers. However, the driver roles of SCNAs in cancer are insufficiently characterized. We combined network propagation and linear regression models to design an integrative strategy to identify driver SCNAs and dissect the functional roles of SCNAs by integrating profiles of copy number and gene expression in lower-grade glioma (LGG). We applied our strategy to 511 LGG patients and identified 98 driver genes that dysregulated 29 cancer hallmark signatures, forming 143 active gene-hallmark pairs. We found that these active gene-hallmark pairs could stratify LGG patients into four subtypes with significantly different survival times. The two new subtypes with similar poorest prognoses were driven by two different gene sets (one including EGFR, CDKN2A, CDKN2B, INFA8, and INFA5, and the other including CDK4, AVIL, and DTX3), respectively. The SCNAs of the two gene sets could disorder the same cancer hallmark signature in a mutually exclusive manner (including E2F_TARGETS and G2M_CHECKPOINT). Compared with previous methods, our strategy could not only capture the known cancer genes and directly dissect the functional roles of their SCNAs in LGG, but also discover the functions of new driver genes in LGG, such as IFNA5, IFNA8, and DTX3. Additionally, our method can be applied to a variety of cancer types to explore the pathogenesis of driver SCNAs and improve the treatment and diagnosis of cancer.