Epigenome reprogramming through H3K27 and H3K4 trimethylation as a resistance mechanism to DNA methylation inhibition in BRAFV600E-mutated colorectal cancer.

PURPOSE: BRAFV600E-mutated colorectal cancer (CRC) exhibits a strong correlation with DNA hypermethylation suggesting this subgroup of tumors presents unique epigenomic phenotypes. Nonetheless, 5-azacitidine, which inhibits DNA methyltransferase activity, is not efficacious in BRAFV600E CRC in vivo. EXPERIMENTAL DESIGN: We randomized and treated mice implanted with patient-derived tumor xenografts harboring BRAFV600E mutation with control, 5-azacitidine, vemurafenib (BRAF inhibitor), or the combination. Comprehensive epigenomic profiling was conducted on control and 5-azacitidine-treated tumor samples, including DNA methylation, histone modifications, chromatin accessibility, and gene expression. Combinations of epigenetic agents were explored in preclinical BRAFV600E CRC models. RESULTS: A profound reduction of DNA methylation levels upon 5-azacitidine treatment was confirmed, however, transcriptional repression was not relieved. This study unbiasedly explored the adaptive engagement of other epigenomic modifications upon 5-azacitidine treatment. A loss of histone acetylation and a gain of histone methylations, including H3K27 and H3K4 trimethylation, were observed around these hypomethylated regions suggesting the involvement of polycomb repressive complex (PRC) activity around the genome with loss of DNA methylation, therefore maintaining the repression of key tumor suppressor genes. Combined inhibition of PRC activity through EZH2 inhibitor with 5-azacitidine treatment additively improved efficacies in BRAFV600E CRC cells. CONCLUSIONS: In conclusion, DNA hypomethylation by 5-azacitidine exhibits a close association with H3K27me3 and PRC activity in BRAFV600E CRC, and simultaneous blockade of DNMT and EZH2 holds promise as a potential therapeutic strategy for patients with BRAFV600E-mutated CRC.

Alignment-free method for DNA sequence clustering using Fuzzy integral similarity.

A larger amount of sequence data in private and public databases produced by next-generation sequencing put new challenges due to limitation associated with the alignment-based method for sequence comparison. So, there is a high need for faster sequence analysis algorithms. In this study, we developed an alignment-free algorithm for faster sequence analysis. The novelty of our approach is the inclusion of fuzzy integral with Markov chain for sequence analysis in the alignment-free model. The method estimate the parameters of a Markov chain by considering the frequencies of occurrence of all possible nucleotide pairs from each DNA sequence. These estimated Markov chain parameters were used to calculate similarity among all pairwise combinations of DNA sequences based on a fuzzy integral algorithm. This matrix is used as an input for the neighbor program in the PHYLIP package for phylogenetic tree construction. Our method was tested on eight benchmark datasets and on in-house generated datasets (18 s rDNA sequences from 11 arbuscular mycorrhizal fungi (AMF) and 16 s rDNA sequences of 40 bacterial isolates from plant interior). The results indicate that the fuzzy integral algorithm is an efficient and feasible alignment-free method for sequence analysis on the genomic scale.

Alignment-free similarity analysis for protein sequences based on fuzzy integral.

Sequence comparison is an essential part of modern molecular biology research. In this study, we estimated the parameters of Markov chain by considering the frequencies of occurrence of the all possible amino acid pairs from each alignment-free protein sequence. These estimated Markov chain parameters were used to calculate similarity between two protein sequences based on a fuzzy integral algorithm. For validation, our result was compared with both alignment-based (ClustalW) and alignment-free methods on six benchmark datasets. The results indicate that our developed algorithm has a better clustering performance for protein sequence comparison.