High-resolution profiling of histone methylations in the human genome.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

/pdf/identification-and-analysis-of-functional-elements-in-1-of-2o640l8ikl.pdf

Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

The epigenomics of cancer.

It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.

/pdf/dna-methylation-age-of-human-tissues-and-cell-types-528gzlrlkl.pdf

DNA methylation age of human tissues and cell types

We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in mammalian cells By obtaining over four billion bases of sequence from chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of mouse embryonic stem cells, neural progenitor cells and embryonic fibroblasts We find that lysine 4 and lysine 27 trimethylation effectively discriminates genes that are expressed, poised for expression, or stably repressed, and therefore reflect cell state and lineage potential Lysine 36 trimethylation marks primary coding and non-coding transcripts, facilitating gene annotation Trimethylation of lysine 9 and lysine 20 is detected at satellite, telomeric and active long-terminal repeats, and can spread into proximal unique sequences Lysine 4 and lysine 9 trimethylation marks imprinting control regions Finally, we show that chromatin state can be read in an allele-specific manner by using single nucleotide polymorphisms This study provides a framework for the application of comprehensive chromatin profiling towards characterization of diverse mammalian cell populations

/pdf/genome-wide-maps-of-chromatin-state-in-pluripotent-and-2gsrpe3xov.pdf

Genome-wide maps of chromatin state in pluripotent and lineage-committed cells

Control of developmental regulators by Polycomb in human embryonic stem cells.

Upon detection of antigen, CD4+ T helper (Th) cells can differentiate into a number of effector types that tailor the immune response to different pathogens Alternative Th1 and Th2 cell fates are specified by the transcription factors T-bet and GATA-3, respectively Only a handful of target genes are known for these two factors and because of this, the mechanism through which T-bet and GATA-3 induce differentiation toward alternative cell fates is not fully understood Here, we provide a genomic map of T-bet and GATA-3 binding in primary human T cells and identify their target genes, most of which are previously unknown In Th1 cells, T-bet associates with genes of diverse function, including those with roles in transcriptional regulation, chemotaxis and adhesion GATA-3 occupies genes in both Th1 and Th2 cells and, unexpectedly, shares a large proportion of targets with T-bet Re-complementation of T-bet alters the expression of these genes in a manner that mirrors their differential expression between Th1 and Th2 lineages These data show that the choice between Th1 and Th2 lineage commitment is the result of the opposing action of T-bet and GATA-3 at a shared set of target genes and may provide a general paradigm for the interaction of lineage-specifying transcription factors

https://www.pnas.org/content/pnas/106/42/17876.full.pdf

The transcription factors T-bet and GATA-3 control alternative pathways of T-cell differentiation through a shared set of target genes


 Background: Survival advantages with neoadjuvant chemotherapy (NACT) have been observed in patients (pts) with locally advanced breast cancer (BC) who achieve pathological complete response (pCR). Predicting risk of early recurrence in pts without pCR remains difficult. Circulating tumor DNA (ctDNA) may be a biomarker of neoadjuvant therapy response and recurrence. This study applied tumor genotyping of peripheral blood in pts with HER2− tumor BRCA-mutated (tBRCAm) BC treated with neoadjuvant niraparib. The relationship between ctDNA and tumor response was also characterized, with a focus on circulating TP53 mutant allelic frequency (MAF). Methods: Blood was collected from 21 pts enrolled in the study (NCT03329937) evaluating neoadjuvant niraparib in pts with localized HER2− tBRCAm BC. Pts received niraparib 200 mg once daily for two 28-day cycles. After 2 cycles, pts underwent surgery or received up to 6 cycles of niraparib and/or NACT prior to surgery. Blood samples were collected at screening, Cycle 1 Day 28 (C1D28), Cycle 2 Day 28 (C2D28), and pre-surgery. Ultrasound (USG) was done after each cycle and MRI after Cycle 2. Next-generation sequencing of cell-free plasma DNA was carried out using a proprietary target capture and analysis (Paweletz, Clin Cancer Res 2016). Results: ctDNA and TP53 mutations (TP53m) were detected at screening in 10/21 pts (47.6%). Across all 21 pts there was a correlation between TP53 MAF and baseline tumor stage (T) (mean [standard deviation], T1 0 [0], T2 0.05 [0.09], and T3 0.21 [0.12]; P=0.005). Linear regression modelling showed a positive correlation between tumor volume and baseline TP53 MAF (R2=0.206, P=0.0386). Baseline TP53 MAF also appeared to be associated with advanced disease stage (Table 1). Depletion of detectable TP53m from baseline was evident by C1D28 and persisted to pre-surgery (Table 2). This corresponded with decreases in tumor volume at C1D28 and further decreases at C2D28. Of 11 pts analyzed, 6 pts with >90% tumor volume decreases by MRI or USG at C2D28 had sustained TP53m depletion. Three pts had pCR; of these, 2 had sustained TP53m depletion (data unavailable for third pCR pt). Two pts with less robust tumor responses had increased pre-surgery TP53 MAF.
 Conclusions: We report the potential utility of ctDNA as a predictive biomarker for neoadjuvant niraparib response in pts with HER2− tBRCAm BC. Although sample size limited analysis of genes other than TP53, baseline ctDNA strongly correlated with tumor volume, and TP53 MAF was associated with tumor volume and trended towards association with disease stage. Longitudinal analysis of TP53 MAF suggested a correlation with niraparib response. Further study of ctDNA dynamics during NACT and correlation with pCR and long-term clinical outcomes is warranted. Funding: GlaxoSmithKline (GSK) study 213355; NCT03329937. Medical writing support was provided by Fishawack Indicia, part of Fishawack Health, funded by GSK.
 Table 1.Baseline TP53 MAF association with disease stage and subtypeTP53 MAFDisease Stage (I–III)Disease SubtypeStage IStage IIStage IIIHR+TNBC(n=8)(n=10)(n=3)(n=6)(n=15)Mean (SD)0.01 (0.02)0.07 (0.12)0.10 (0.05)0.02 (0.02)0.06 (0.10)HR, hormone receptor; MAF, mutant allelic frequency; SD, standard deviation; TNBC, triple-negative breast cancer.
 Table 2.TP53 MAF correlation with tumor volume decrease by ultrasound and MRIOutcomeScreeningCycle 1 Day 28 Cycle 2 Day 28 Pre-Surgeryn11997TP53 MAF, mean, (SD)0.09 (0.11)000.01 (0.02)n11112Percent change in tumor volume from baseline by MRI, mean (SD)-N/A*−72.6 (22.5)N/A*Percent change in tumor volume from baseline by ultrasound, mean (SD)-−60.8 (24.0)−80.6 (21.8)−95.9 (4.3)*MRI was only performed at Cycle 2 Day 28. MAF, mutant allelic frequency; MRI, magnetic resonance imaging; N/A, not applicable; SD, standard deviation.
 Citation Format: Ming Shan, Laura Spring, Minetta C Liu, Erika Hamilton, Hanna Irie, Cesar A Santa-Maria, Steven J Isakoff, James Reeves, Leif W Ellisen, Lee P Lim, Kavita Garg, Caterina Bertucci, Bin Feng, Hailei Zhang, Kaiming Sun, Julie R Graham, Erin Hofstatter, Hyo Han. Relationship between circulating tumor DNA and response to neoadjuvant niraparib in HER2-negative, BRCA-mutated breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-21.

Kaiming Sun

Papers

Control of developmental regulators by Polycomb in human embryonic stem cells.

The transcription factors T-bet and GATA-3 control alternative pathways of T-cell differentiation through a shared set of target genes

Abstract P5-13-21: Relationship between circulating tumor DNA and response to neoadjuvant niraparib in HER2-negative, BRCA-mutated breast cancer