Neoplastic cell enrichment of tumor tissues using coring and laser microdissection for proteomic and genomic analyses of pancreatic ductal adenocarcinoma

BACKGROUND: The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses. METHODS: Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations. RESULTS: The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity. CONCLUSIONS: In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique

MethylC-analyzer: A comprehensive downstream pipeline for the analysis of genome-wide DNA methylation

DNA methylation is a crucial epigenetic modification involved in multiple biological processes and diseases. Current approaches for measuring genome-wide DNA methylation via bisulfite sequencing (BS-seq) include whole-genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), and enzymatic methyl-seq (EM-seq). The computational analysis tools available for BS-seq data include customized aligners for mapping bisulfite-converted reads and computational pipelines for downstream data analysis. Current post-alignment methylation tools are specialized for the interpretation of CG methylation, which is known to dominate mammalian genomes, however, non-CG methylation (CHG and CHH, where H refers to A, C, or T) is commonly observed in plants and fungi and is closely associated with gene regulation, transposon silencing, and plant development. Thus, we have developed a MethylC-analyzer to analyze and visualize post-alignment WGBS, RRBS, and EM-seq data focusing on CG. The tool is able to also analyze non-CG sites to enhance deciphering genomes of plants and fungi. By processing aligned data and gene location files, MethylC-analyzer generates a genome-wide view of methylation levels and methylation in user-specified genomic regions. The meta-plot, for example, allows the investigation of DNA methylation within specific genomic elements. Moreover, our tool identifies differentially methylated regions (DMRs) and investigates the enrichment of genomic features associated with variable methylation. MethylC-analyzer functionality is not limited to specific genomes, and we demonstrated its performance on both plant and human BS-seq data. MethylC-analyzer is a Python- and R-based program designed to perform comprehensive downstream analyses of methylation data, providing an intuitive analysis platform for scientists unfamiliar with DNA methylation analysis. It is available as either a standalone version for command-line uses or a graphical user interface (GUI) and is publicly accessible at https://github.com/RitataLU/MethylC-analyzer

Proteogenomic insights suggest druggable pathways in endometrial carcinoma

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC

ATACgraph: Profiling genome-wide chromatin accessibility from ATAC-seq

Assay for transposase-accessible chromatin using sequencing data (ATAC-seq) is an efficient and precise method for revealing chromatin accessibility across the genome. Most of the current ATAC-seq tools follow chromatin immunoprecipitation sequencing (ChIP-seq) strategies that do not consider ATAC-seq-specific properties. To incorporate specific ATAC-seq quality control and the underlying biology of chromatin accessibility, we developed a bioinformatics software named ATACgraph for analyzing and visualizing ATAC-seq data. ATACgraph profiles accessible chromatin regions and provides ATAC-seq-specific information including definitions of nucleosome-free regions (NFRs) and nucleosome-occupied regions. ATACgraph also allows identification of differentially accessible regions between two ATAC-seq datasets. ATACgraph incorporates the docker image with the Galaxy platform to provide an intuitive user experience via the graphical interface. Without tedious installation processes on a local machine or cloud, users can analyze data through activated websites using pre-designed workflows or customized pipelines composed of ATACgraph modules. Overall, ATACgraph is an effective tool designed for ATAC-seq for biologists with minimal bioinformatics knowledge to analyze chromatin accessibility. ATACgraph can be run on any ATAC-seq data with no limit to specific genomes. As validation, we demonstrated ATACgraph on human genome to showcase its functions for ATAC-seq interpretation. This software is publicly accessible and can be downloaded at https://github.com/RitataLU/ATACgraph

Transcriptome analysis of Dnmt3l knock-out mice derived multipotent mesenchymal stem/stromal cells during osteogenic differentiation

Multipotent mesenchymal stem/stromal cells (MSCs) exhibit great potential for cell-based therapy. Proper epigenomic signatures in MSCs are important for the maintenance and the subsequent differentiation potential. The DNA methyltransferase 3-like (DNMT3L) that was mainly expressed in the embryonic stem (ES) cells and the developing germ cells plays an important role in shaping the epigenetic landscape. Here, we report the reduced colony forming ability and impaire

Epigenetic regulation during cancer transitions across 11 tumour types

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasi

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease

Behavioral Epigenetics: Perspectives Based on Experience-Dependent Epigenetic Inheritance

Epigenetic regulation plays an important role in gene regulation, and epigenetic markers such as DNA methylation and histone modifications are generally described as switches that regulate gene expression. Behavioral epigenetics is defined as the study of how epigenetic alterations induced by experience and environmental stress may affect animal behavior. It studies epigenetic alterations due to environmental enrichment. Generally, molecular processes underlying epigenetic regulation in behavioral epigenetics include DNA methylation, post-translational histone modifications, noncoding RNA activity, and other unknown molecular processes. Whether the inheritance of epigenetic features will occur is a crucial question. In general, the mechanism underlying inheritance can be explained by two main phenomena: Germline-mediated epigenetic inheritance and interact epigenetic inheritance of somatic cells through germline. In this review, we focus on examining behavioral epigenetics based on its possible modes of inheritance and discuss the considerations in the research of epigenetic transgenerational inheritance

Blimp-1 molds the epigenetic architecture of IL-21-mediated autoimmune diseases through an autoregulatory circuit

Positive regulatory domain 1 (PRDM1) encodes B lymphocyte-induced maturation protein 1 (BLIMP1), also known as a master regulator of T cell homeostasis. We observed a negative relationship between Blimp-1 and IL-21 based on our previous data that Blimp-1 overexpression in T cells suppresses autoimmune diabetes while Blimp-1-deficient T cells contribute to colitis in NOD mice. Reanalysis of published data sets also revealed an inverse correlation between PRDM1 and IL21 in Crohn\u27s disease. Here, we illustrate that Blimp-1 repressed IL-21 by reducing chromatin accessibility and evicting an IL-21 activator, c-Maf, from the Il21 promoter. Moreover, Blimp-1 overexpression-mediated reduction in permissive chromatin structures at the Il21 promoter could override IL-21-accelerated autoimmune diabetogenesis in small ubiquitin-like modifier-defective c-Maf-transgenic mice. An autoregulatory feedback loop to harness IL-21 expression was unveiled by the evidence that IL-21 addition induced time-dependent Blimp-1 expression and subsequently enriched its binding to the Il21 promoter to suppress IL-21 overproduction. Furthermore, intervention of this feedback loop by IL-21 blockade, with IL-21R.Fc administration or IL-21 receptor deletion, attenuated Blimp-1 deficiency-mediated colitis and reinforced the circuit between Blimp-1 and IL-21 in the regulation of autoimmunity. We highlight the translation of Blimp-1-based epigenetic and transcriptomic profiles applicable to a personalized medicine approach in autoimmune diseases