Sequential Visible-Light Photoactivation and Palladium Catalysis Enabling Enantioselective [4+2] Cycloadditions

Catalytic asymmetric cycloadditions of reactive ketene intermediates provide new opportunities for the production of chiral heterocyclic molecules. Though known for over 100 years, ketenes still remain underexplored in the field of transition-metal (TM)-catalyzed asymmetric cycloadditions because (1) ketenes, as highly electron-deficient species, are possibly unstable to low-valence TMs (i.e., decarbonylation or aggregation) and (2) the conventional thermal synthesis of ketenes from acyl chlorides and amines may be incompatible with TM catalysis (i.e., reactive acyl chloride and amine hydrochloride byproducts). Herein, we detail the unprecedented asymmetric [4+2] cycloaddition of vinyl benzoxazinanones with a variety of ketene intermediates via sequential visible-light photoactivation and palladium catalysis. It is well demonstrated that the traceless and transient generation of ketenes from α-diazoketones through visible-light-induced Wolff rearrangement is important for the success of present cycloaddition. Furthermore, chiral palladium catalysts with a new, chiral hybrid P, S ligand enable asymmetric cycloaddition with high reaction selectivity and enantiocontrol

Sequential Visible-Light Photoactivation and Palladium Catalysis Enabling Enantioselective [4+2] Cycloadditions

Catalytic asymmetric cycloadditions of reactive ketene intermediates provide new opportunities for the production of chiral heterocyclic molecules. Though known for over 100 years, ketenes still remain underexplored in the field of transition-metal (TM)-catalyzed asymmetric cycloadditions because (1) ketenes, as highly electron-deficient species, are possibly unstable to low-valence TMs (i.e., decarbonylation or aggregation) and (2) the conventional thermal synthesis of ketenes from acyl chlorides and amines may be incompatible with TM catalysis (i.e., reactive acyl chloride and amine hydrochloride byproducts). Herein, we detail the unprecedented asymmetric [4+2] cycloaddition of vinyl benzoxazinanones with a variety of ketene intermediates via sequential visible-light photoactivation and palladium catalysis. It is well demonstrated that the traceless and transient generation of ketenes from α-diazoketones through visible-light-induced Wolff rearrangement is important for the success of present cycloaddition. Furthermore, chiral palladium catalysts with a new, chiral hybrid P, S ligand enable asymmetric cycloaddition with high reaction selectivity and enantiocontrol

Hierarchical Clustering of Breast Cancer Methylomes Revealed Differentially Methylated and Expressed Breast Cancer Genes

<div><p>Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs) and the hypomethylation of the megabase-sized partially methylated domains (PMDs) are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI) was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma) dataset. They were characterized with differentially hypermethylated <i>XIST</i> promoter, reduced expression of <i>XIST</i>, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.</p></div

Difference in the distribution of DNA methylation levels of HMRs between normal breast and breast tumor samples in WGBS and TCGA BRCA datasets.

<p>The number of HMRs that had sufficient coverage of CpG sites on HumanMethylation450 BeadChip that were used in the plots and the total number of HMRs were provided beside the HMR cluster ID. The effect size for the difference between normal and tumor samples is provided as the d value. General consideration of small, medium and large effect has d values of 0.2, 0.5 and 0.8 respectively. (A) Promoter HMRs. (B) Intragenic HMRs.</p

Hierarchical clustering of promoter, intragenic and intergenic HMRs according to their DNA methylation levels in the seven breast methylomes.

<p>Coloring indicates methylation levels from low (blue) to high (red). Eight distinctive HMR clusters were indicated in each of the three genomic locations. (A) Promoter HMRs. The A-1 cluster represents the promoter HMRs that were consistently lowly methylated in all seven samples. (B) Intragenic HMRs. The B-1, B-2 and B-3 clusters were hypomethylated in one or both cancer cell lines (MCF7 and HCC1954), while other samples remain methylated. (C) Intergenic HMRs. The C-1, C-2 and C-3 clusters were hypomethylated in one or both cancer cell lines (MCF7 and HCC1954), while other samples remain methylated.</p

Distribution of differential methylation levels of gene promoters for under-expressed, over-expressed and not differentially expressed genes between breast cancer cell lines (MCF7 and HCC1954) and normal breast samples (NB and HMEC).

<p>The differential methylation and differential gene expression between breast cancer cell lines and normal samples were negative correlated in A-3, A-6 and A-8 promoter HMRs. In other HMR clusters, the distributions of differential methylation levels among under-expressed (Under), over-expressed (Over) and not differentially expressed (No DE) genes were similar in form.</p

Distribution of DNA methylation levels of MCF7 and HMEC enhancers and/or heterochromatins in the seven breast methylomes.

<p>The genomic regions characterized as enhancer (Enc) or heterochromatin (Htc) in HMEC and MCF7 by ChromHMM were re-annotated as regions that were (A) enhancer in HMEC and MCF7 (B) heterochromatin in HMEC and MCF7, (C) enhancer in HMEC and heterochromatin in MCF7, and (D) enhancer in MCF7 and heterochromatin in HMEC.</p

Distribution of differential methylation levels of gene promoters for under-expressed, over-expressed and not differentially expressed genes between breast cancer samples and normal breast samples of the TCGA BRCA datasets.

<p>The differential methylation and differential gene expression between breast cancer cell lines and normal samples were negatively-correlated in A-3, A-6 and A-8 HMRs as observed in the WGBS samples (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118453#pone.0118453.g003" target="_blank">Fig. 3</a>).</p

Hypomethylation of megabase-sized PMDs in breast tumors and cell lines.

<p>We used chromosome 16 as an examples to illustrate the (A) extent of differential methylation between NB and the other six WGBS datasets, and (B) average predicted PMD size (Kb) along the chromosome. (C) ChIP-chip assay in MCF7 showed PMDs were specifically enriched with H3K27me3 modification. (D) RNA-seq experiments showed genes located within PMDs and extremely large PMDs (> 1 Mb) have very low expression (represented as counts per million, CPM) than those outside PMDs.</p

WGBS of a normal breast (NB), three primary breast tumors (BT089, BT126 and BT198), a mammary epithelial cell line (HMEC) and two breast cancer cell lines (MCF7 an HCC1954).

<p>(A) Circos representation of genome-wide DNA methylation levels in the seven breast samples. The data represent the average methylation levels for all of the CpGs in 56,779 50 Kb windows. Coloring indicates methylation levels from low (green) to high (red). (B) The proportion of CpG sites in the DNA that were lowly (< 20%), intermediately (20% ~ 80%) and highly (> 80%) methylated in the seven samples. (C) The proportion of CpG sites in the CGI that were lowly (< 20%), intermediately (20% ~ 80%) and highly (> 80%) methylated in the seven samples. (D) Heatmap representation of average methylation levels of 10 Kb windows with different CpG densities. The CpG density was expressed as the number of CpG sites per 100 bp of nucleotide sequence. Coloring indicates methylation levels from low (green) to high (red). (E) The distribution of the DNA methylation levels of CGI in promoter (TSS ± 1 Kb), intragenic and intergenic regions.</p