Inferring clonal expansion and cancer stem cell dynamics from DNA methylation patterns in colorectal cancers.
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ABSTRACT:
SUBMITTER: Siegmund KD
PROVIDER: S-EPMC2651202 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPotential therapeutic use of mesenchymal stem cells (MSCs) is likely to require large-scale in vitro expansion of the cells before transplantation. MSCs from adipose tissue can be cultured extensively until senescence. However, little is known on the differentiation potential of adipose stem cells (ASCs) upon extended culture and on associated epigenetic alterations. We examined the adipogenic differentiation potential of clones of human ASCs in early passage culture and upon senescence, and determined whether senescence was associated with changes in adipogenic promoter DNA methylation.ResultsASC clones cultured to senescence display reduced adipogenic differentiation capacity in vitro, on the basis of limited lipogenesis and reduced transcriptional upregulation of FABP4 and LPL, two adipogenic genes, while LEP and PPARG2 transcription remains unaffected. In undifferentiated senescent cells, PPARG2 and LPL expression is unaltered, whereas LEP and FABP4 transcript levels are increased but not in all clones. Bisulfite sequencing analysis of DNA methylation reveals overall relative stability of LEP, PPARG2, FABP4 and LPL promoter CpG methylation during senescence and upon differentiation. Mosaicism in methylation profiles is maintained between and within ASC clones, and any CpG-specific methylation change detected does not necessarily relate to differentiation potential. One exception to this contention is CpG No. 21 in the LEP promoter, whose senescence-related methylation may impair upregulation of the gene upon adipogenic stimulation.ConclusionSenescent ASCs display reduced in vitro differentiation ability and transcriptional activation of adipogenic genes upon differentiation induction. These restrictions, however, cannot in general be attributed to specific changes in DNA methylation at adipogenic promoters. There also seems to be a correlation between CpGs that are hypomethylated and important transcription factor binding sites.
| S-EPMC1892011 | biostudies-literature
Project description:BackgroundADAMs (a disintegrin and metalloproteinase) have long been associated with tumor progression. Recent findings indicate that members of the closely related ADAMTS (ADAMs with thrombospondin motifs) family are also critically involved in carcinogenesis. Gene silencing through DNA methylation at CpG loci around e.g. transcription start or enhancer sites is a major mechanism in cancer development. Here, we aimed at identifying genes of the ADAM and ADAMTS family showing altered DNA methylation in the development or colorectal cancer (CRC) and other epithelial tumors.MethodsWe investigated potential changes of DNA methylation affecting ADAM and ADAMTS genes in 117 CRC, 40 lung cancer (LC) and 15 oral squamous-cell carcinoma (SCC) samples. Tumor tissue was analyzed in comparison to adjacent non-malignant tissue of the same patients. The methylation status of 1145 CpGs in 51 ADAM and ADAMTS genes was measured with the HumanMethylation450 BeadChip Array. ADAMTS16 protein expression was analyzed in CRC samples by immunohistochemistry.ResultsIn CRC, we identified 72 CpGs in 18 genes which were significantly affected by hyper- or hypomethylation in the tumor tissue compared to the adjacent non-malignant tissue. While notable/frequent alterations in methylation patterns within ADAM genes were not observed, conspicuous changes were found in ADAMTS16 and ADAMTS2. To figure out whether these differences would be CRC specific, additional LC and SCC tissue samples were analyzed. Overall, 78 differentially methylated CpGs were found in LC and 29 in SCC. Strikingly, 8 CpGs located in the ADAMTS16 gene were commonly differentially methylated in all three cancer entities. Six CpGs in the promoter region were hypermethylated, whereas 2 CpGs in the gene body were hypomethylated indicative of gene silencing. In line with these findings, ADAMTS16 protein was strongly expressed in globlet cells and colonocytes in control tissue but not in CRC samples. Functional in vitro studies using the colorectal carcinoma cell line HT29 revealed that ADAMTS16 expression restrained tumor cell proliferation.ConclusionsWe identified ADAMTS16 as novel gene with cancer-specific promoter hypermethylation in CRC, LC and SCC patients implicating ADAMTS16 as potential biomarker for these tumors. Moreover, our results provide evidence that ADAMTS16 may have tumor suppressor properties.
| S-EPMC6080380 | biostudies-literature
Project description: Not available
| S-EPMC10845933 | biostudies-literature
Project description:The HIV latent reservoir exhibits slow decay on antiretroviral therapy (ART), impacted by homeostatic proliferation and activation. How these processes contribute to the total dynamic while also producing the observed profile of sampled latent clone sizes is unclear. An agent-based model was developed that tracks individual latent clones, incorporating homeostatic proliferation of cells and activation of clones. The model was calibrated to produce observed latent reservoir dynamics as well as observed clonal size profiles. Simulations were compared to previously published latent HIV integration data from 5 adults and 3 children. The model simulations reproduced reservoir dynamics as well as generating residual plasma viremia levels (pVL) consistent with observations on ART. Over 382 Latin Hypercube Sample simulations, the median latent reservoir grew by only 0.3 log10 over the 10 years prior to ART initiation, after which time it decreased with a half-life of 15 years, despite number of clones decreasing at a faster rate. Activation produced a maximum size of genetically intact clones of around one million cells. The individual simulation that best reproduced the sampled clone profile, produced a reservoir that decayed with a 13.9 year half-life and where pVL, produced mainly from proliferation, decayed with a half-life of 10.8 years. These slow decay rates were achieved with mean cell life-spans of only 14.2 months, due to expansion of the reservoir through proliferation and activation. Although the reservoir decayed on ART, a number of clones increased in size more than 4,000-fold. While small sampled clones may have expanded through proliferation, the large sizes exclusively arose from activation. Simulations where homeostatic proliferation contributed more to pVL than activation, produced pVL that was less variable over time and exhibited fewer viral blips. While homeostatic proliferation adds to the latent reservoir, activation can both add and remove latent cells. Latent activation can produce large clones, where these may have been seeded much earlier than when first sampled. Elimination of the reservoir is complicated by expanding clones whose dynamic differ considerably to that of the entire reservoir.
| S-EPMC8722732 | biostudies-literature
Project description:CpG island (CGI) hypermethylation at discrete loci is a prevalent cancer-promoting abnormality in sporadic colorectal carcinomas (S-CRCs). We investigated genome-wide CGI methylation in inflammatory bowel disease (IBD)-associated CRCs (IBD-CRCs).Methylation microarray analyses were conducted on seven IBD-CRCs, 17 S-CRCs, and eight normal control colonic tissues from patients without CRC or IBD. CGI methylator phenotype (CIMP), a surrogate marker for widespread cancer-specific CGI hypermethylation, was examined in 30 IBD-CRCs and 43 S-CRCs.The genome-wide CGI methylation pattern of IBD-CRCs was CIMP status-dependent. Based on methylation array data profiling of all autosomal loci, CIMP(+) IBD-CRCs grouped together with S-CRCs, while CIMP(-) IBD-CRCs grouped together with control tissues. CIMP(-) IBD-CRCs demonstrated less methylation than did age-matched CIMP(-) S-CRCs at autosomal CGIs (z-score -0.17 vs. 0.09, P = 3 × 10(-3)) and CRC-associated hypermethylation target CGIs (z-score -0.43 vs. 0.68, P = 1 × 10(-4)). Age-associated hypermethylation target CGIs were significantly overrepresented in CGIs that were hypermethylated in S-CRCs (P = 1 × 10(-192)), but not in CGIs that were hypermethylated in IBD-CRCs (P = 0.11). In contrast, KRAS mutation prevalence was similar between IBD-CRCs and S-CRCs. Notably, CIMP(+) prevalence was significantly higher in older than in younger IBD-CRC cases (50.0 vs. 4.2, P = 0.02), but not in S-CRC cases (9.7 vs. 16.7, P = 0.92).Cancer-specific CGI hypermethylation and age-associated CGI hypermethylation are diminished in IBD-CRCs relative to S-CRCs, while the KRAS mutation rate is comparable between these cancers. CGI hypermethylation appears to play only a minor role in IBD-associated carcinogenesis. We speculate that aging, rather than inflammation per se, promotes CIMP(+) CRCs in IBD patients.
| S-EPMC3214229 | biostudies-literature
Project description:Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG correlations in DNA methylation, in addition to single site variability, during cervical carcinogenesis. We demonstrate how the study of changes in DNA methylation covariation patterns across normal, intra-epithelial neoplasia and invasive cancer allows the identification of CpG sites that indicate the risk of neoplastic transformation in stages prior to neoplasia. Importantly, we show that the covariation in DNA methylation at these risk CpG loci is maximal immediately prior to the onset of cancer, supporting the view that high epigenetic diversity in normal cells increases the risk of cancer. Consistent with this, we observe that invasive cancers exhibit increased covariation in DNA methylation at the risk CpG sites relative to normal tissue, but lower levels relative to pre-cancerous lesions. We further show that the identified risk CpG sites undergo preferential DNA methylation changes in relation to human papilloma virus infection and age. Results are validated in independent data including prospectively collected samples prior to neoplastic transformation. Our data are consistent with a phase transition model of carcinogenesis, in which epigenetic diversity is maximal prior to the onset of cancer. The model and algorithm proposed here may allow, in future, network biomarkers predicting the risk of neoplastic transformation to be identified.
| S-EPMC4091688 | biostudies-literature
Project description:BACKGROUND:It is generally believed that DNA methylation, as one of the most important epigenetic modifications, participates in the regulation of gene expression and plays an important role in the development of cancer, and there exits epigenetic heterogeneity among cancers. Therefore, this study tried to screen for reliable prognostic markers for different cancers, providing further explanation for the heterogeneity of cancers, and more targets for clinical transformation studies of cancer from epigenetic perspective. METHODS:This article discusses the epigenetic heterogeneity of cancer in detail. Firstly, DNA methylation data of seven cancer types were obtained from Illumina Infinium HumanMethylation 450?K platform of TCGA database. Then, differential methylation analysis was performed in the promotor region. Secondly, pivotal gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes obtained from two networks were integrated as candidate markers for the prognosis model. Finally, we used the univariate and multivariate COX regression models to select specific independent prognostic markers for each cancer, and studied the risk factor of these genes by doing survival analysis. RESULTS:First, the cancer type-specific gene markers were obtained by differential methylation analysis and they were found to be involved in different biological functions by enrichment analysis. Moreover, specific and common diagnostic markers for each type of cancer was sorted out and Kaplan-Meier survival analysis showed that there was significant difference in survival between the two risk groups. CONCLUSIONS:This study screened out reliable prognostic markers for different cancers, providing a further explanation for the heterogeneity of cancer at the DNA methylation level and more targets for clinical conversion studies of cancer.
| S-EPMC6937830 | biostudies-literature
Project description:Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling. Here we present genome-wide reference maps of the associated DNA methylation dynamics. We used a meta-epigenomic approach that combines DNA methylation profiles across many small pools of cells and performed single-cell methylome sequencing to assess cell-to-cell heterogeneity. The resulting dataset identified characteristic differences between HSCs derived from fetal liver, cord blood, bone marrow, and peripheral blood. We also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors, characterized immature multi-lymphoid progenitors, and detected progressive DNA methylation differences in maturing megakaryocytes. We linked these patterns to gene expression, histone modifications, and chromatin accessibility, and we used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data. Our results contribute to a better understanding of human hematopoietic stem cell differentiation and provide a framework for studying blood-linked diseases.
| S-EPMC5145815 | biostudies-literature
Project description:The signature of early cancer dynamics on the spatial arrangement of tumour cells is poorly understood, and yet could encode information about how sub-clones grew within the expanding tumour. Novel methods of quantifying spatial tumour data at the cellular scale are required to link evolutionary dynamics to the resulting spatial architecture of the tumour. Here, we propose a framework using first passage times of random walks to quantify the complex spatial patterns of tumour cell population mixing. First, using a simple model of cell mixing we demonstrate how first passage time statistics can distinguish between different pattern structures. We then apply our method to simulated patterns of mutated and non-mutated tumour cell population mixing, generated using an agent-based model of expanding tumours, to explore how first passage times reflect mutant cell replicative advantage, time of emergence and strength of cell pushing. Finally, we explore applications to experimentally measured human colorectal cancer, and estimate parameters of early sub-clonal dynamics using our spatial computational model. We infer a wide range of sub-clonal dynamics, with mutant cell division rates varying between 1 and 4 times the rate of non-mutated cells across our sample set. Some mutated sub-clones emerged after as few as 100 non-mutant cell divisions, and others only after 50,000 divisions. The majority were consistent with boundary driven growth or short-range cell pushing. By analysing multiple sub-sampled regions in a small number of samples, we explore how the distribution of inferred dynamics could inform about the initial mutational event. Our results demonstrate the efficacy of first passage time analysis as a new methodology in spatial analysis of solid tumour tissue, and suggest that patterns of sub-clonal mixing can provide insights into early cancer dynamics.
| S-EPMC10035892 | biostudies-literature
Project description:BackgroundIt is possible to infer the past of populations by comparing genomes between individuals. In general, older populations have more genomic diversity than younger populations. The force of selection can also be inferred from population diversity. If selection is strong and frequently eliminates less fit variants, diversity will be limited because new, initially homogeneous populations constantly emerge.Methodology and resultsHere we translate a population genetics approach to human somatic cancer cell populations by measuring genomic diversity within and between small colorectal cancer (CRC) glands. Control tissue culture and xenograft experiments demonstrate that the population diversity of certain passenger DNA methylation patterns is reduced after cloning but subsequently increases with time. When measured in CRC gland populations, passenger methylation diversity from different parts of nine CRCs was relatively high and uniform, consistent with older, stable lineages rather than mixtures of younger homogeneous populations arising from frequent cycles of selection. The diversity of six metastases was also high, suggesting dissemination early after transformation. Diversity was lower in DNA mismatch repair deficient CRC glands, possibly suggesting more selection and the elimination of less fit variants when mutation rates are elevated.Conclusion/significanceThe many hitchhiking passenger variants observed in primary and metastatic CRC cell populations are consistent with relatively old populations, suggesting that clonal evolution leading to selective sweeps may be rare after transformation. Selection in human cancers appears to be a weaker than presumed force after transformation, consistent with the observed rarity of driver mutations in cancer genomes. Phenotypic plasticity rather than the stepwise acquisition of new driver mutations may better account for the many different phenotypes within human tumors.
| S-EPMC3125304 | biostudies-literature