Distinguishing Gastric/Esophageal Adenocarcinoma from Pancreatic Adenocarcinoma Using Methylation-Based Droplet Digital PCR.

The goal of this study was to develop a methylation-based droplet digital PCR to separate 2 cancer classes that do not have sensitive and specific immunohistochemical stains: gastric/esophageal and pancreatic adenocarcinomas. The assay used methylation-independent primers and methylation-dependent probes to assess a single differentially methylated CpG site; analyses of array data from The Cancer Genome Atlas network showed that high methylation at the cg06118999 probe supports the presence of cells originating from the stomach or esophagus (eg, as in gastric metastasis), whereas low methylation suggests that these cells are rare to absent (eg, pancreatic metastasis). On validation using formalin-fixed paraffin-embedded primary and metastatic samples from our institution, methylation-based droplet digital PCR targeting the corresponding CpG dinucleotide generated evaluable data for 60 of the 62 samples (97%) and correctly classified 50 of the 60 evaluable cases (83.3%), mostly adenocarcinomas from the stomach or pancreas. This ddPCR was created to be easy-to-interpret, rapid, inexpensive, and compatible with existing platforms at many clinical laboratories. We suggest that similarly accessible PCRs could be developed for other differentials in pathology that do not have sensitive and specific immunohistochemical stains.

Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma.

Recurrence of solid tumors renders patients vulnerable to advanced, treatment-refractory disease state with mutational and oncogenic landscape distinctive from initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profile barcoded tumor stem cell populations through therapy at tumor initiation, MRD, and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors show distinct patterns of recurrence in which clonal populations exhibit either a pre-existing fitness advantage or an equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing reveals a tumor-intrinsic immunomodulatory signature with prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from patients with GBM. Our results provide insight into the innate and therapy-driven dynamics of human GBM and the prognostic value of interrogating the MRD state in solid cancers.

Wnt activation as a therapeutic strategy in medulloblastoma.

Medulloblastoma (MB) is defined by four molecular subgroups (Wnt, Shh, Group 3, Group 4) with Wnt MB having the most favorable prognosis. Since prior reports have illustrated the antitumorigenic role of Wnt activation in Shh MB, we aimed to assess the effects of activated canonical Wnt signaling in Group 3 and 4 MBs. By using primary patient-derived MB brain tumor-initiating cell (BTIC) lines, we characterize differences in the tumor-initiating capacity of Wnt, Group 3, and Group 4 MB. With single cell RNA-seq technology, we demonstrate the presence of rare Wnt-active cells in non-Wnt MBs, which functionally retain the impaired tumorigenic potential of Wnt MB. In treating MB xenografts with a Wnt agonist, we provide a rational therapeutic option in which the protective effects of Wnt-driven MBs may be augmented in Group 3 and 4 MB and thereby support emerging data for a context-dependent tumor suppressive role for Wnt/ß-catenin signaling.

Telomere dysfunction cooperates with epigenetic alterations to impair murine embryonic stem cell fate commitment.

The precise relationship between epigenetic alterations and telomere dysfunction is still an extant question. Previously, we showed that eroded telomeres lead to differentiation instability in murine embryonic stem cells (mESCs) via DNA hypomethylation at pluripotency-factor promoters. Here, we uncovered that telomerase reverse transcriptase null (Tert-/-) mESCs exhibit genome-wide alterations in chromatin accessibility and gene expression during differentiation. These changes were accompanied by an increase of H3K27me3 globally, an altered chromatin landscape at the Pou5f1/Oct4 promoter, and a refractory response to differentiation cues. Inhibition of the Polycomb Repressive Complex 2 (PRC2), an H3K27 tri-methyltransferase, exacerbated the impairment in differentiation and pluripotency gene repression in Tert-/- mESCs but not wild-type mESCs, whereas inhibition of H3K27me3 demethylation led to a partial rescue of the Tert-/- phenotype. These data reveal a new interdependent relationship between H3K27me3 and telomere integrity in stem cell lineage commitment that may have implications in aging and cancer.

GABA promotes ß-cell proliferation, but does not overcome impaired glucose homeostasis associated with diet-induced obesity.

γ-Aminobutyric acid (GABA) administration has been shown to increase ß-cell mass, leading to a reversal of type 1 diabetes in mice. Whether GABA has any effect on ß cells of healthy and prediabetic/glucose-intolerant obese mice remains unknown. In the present study, we show that oral GABA administration ( ad libitum) to mice indeed increased pancreatic ß-cell mass, which led to a modest enhancement in insulin secretion and glucose tolerance. However, GABA treatment did not further increase insulin-positive islet area in high fat diet-fed mice and was unable to prevent or reverse glucose intolerance and insulin resistance. Mechanistically, whether in vivo or in vitro, GABA treatment increased ß-cell proliferation. In vitro, the effect was shown to be mediated via the GABAA receptor. Single-cell RNA sequencing analysis revealed that GABA preferentially up-regulated pathways linked to ß-cell proliferation and simultaneously down-regulated those networks required for other processes, including insulin biosynthesis and metabolism. Interestingly, single-cell differential expression analysis revealed GABA treatment gave rise to a distinct subpopulation of ß cells with a unique transcriptional signature, including urocortin 3 ( ucn3), wnt4, and hepacam2. Taken together, this study provides new mechanistic insight into the proliferative nature of GABA but suggests that ß-cell compensation associated with prediabetes overlaps with, and negates, its proliferative effects.-Untereiner, A., Abdo, S., Bhattacharjee, A., Gohil, H., Pourasgari, F., Ibeh, N., Lai, M., Batchuluun, B., Wong, A., Khuu, N., Liu, Y., Al Rijjal, D., Winegarden, N., Virtanen, C., Orser, B. A., Cabrera, O., Varga, G., Rocheleau, J., Dai, F. F., Wheeler, M. B. GABA promotes ß-cell proliferation, but does not overcome impaired glucose homeostasis associated with diet-induced obesity.

Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations.

The liver is the largest solid organ in the body and is critical for metabolic and immune functions. However, little is known about the cells that make up the human liver and its immune microenvironment. Here we report a map of the cellular landscape of the human liver using single-cell RNA sequencing. We provide the transcriptional profiles of 8444 parenchymal and non-parenchymal cells obtained from the fractionation of fresh hepatic tissue from five human livers. Using gene expression patterns, flow cytometry, and immunohistochemical examinations, we identify 20 discrete cell populations of hepatocytes, endothelial cells, cholangiocytes, hepatic stellate cells, B cells, conventional and non-conventional T cells, NK-like cells, and distinct intrahepatic monocyte/macrophage populations. Together, our study presents a comprehensive view of the human liver at single-cell resolution that outlines the characteristics of resident cells in the liver, and in particular provides a map of the human hepatic immune microenvironment.

Gene expression signatures prognostic for relapse in stage I testicular germ cell tumours.

OBJECTIVES: To identify differentially expressed genes between relapsed and non-relapsed clinical stage I testicular germ cell tumours (TGCTs). MATERIALS AND METHODS: We reviewed patients with clinical stage I non-seminoma and seminoma from an institutional database (2000-2012) who were managed by active surveillance. Patients with non-relapsed non-seminoma and non-relapsed seminoma were defined as being relapse-free after 2 and 3 years of surveillance, respectively. RNA extraction and gene expression analysis was performed on archival primary tumour samples and gene-set enrichment analysis (GSEA) was conducted in order to identify differentiating biological pathways. RESULTS: A total of 57 patients (relapsed non-seminoma, n = 12; relapsed seminoma, n =15; non-relapsed non-seminoma, n = 15; non-relapsed seminoma, n = 15) were identified, with a median (range) relapse time of 5.6 (2.5-18.1) and 19.3 (4.7-65.3) months in the relapsed non-seminoma and relapsed seminoma cohorts, respectively. A total of 1 039 differentially expressed genes were identified that separated relapsed and non-relapsed groups. In patients with relapse, GSEA revealed enrichment in pathways associated with differentiation, such as skeletal development (i.e. FGFR1, BMP4, GLI2, SPARC, COL2A1), tissue (i.e. BMP4, SPARC, COL13A1) and bone remodelling (i.e. CARTPT, GLI2, MGP). A discriminative gene expression profile between relapsed and non-relapsed cases was discovered when combining non-seminoma and seminoma samples using 10- and 30-probe signatures; however, this profile was not observed in the seminoma and non-seminoma cohorts individually. CONCLUSION: A discriminating signature for relapsed disease was identified for clinical stage I TGCT that we were not able to identify by histology alone. Further validation is required to determine if this signature provides independent prognostic information to standard pathological risk factors.

Discovery of biomarkers of endometrial receptivity through a minimally invasive approach: a validation study with implications for assisted reproduction.

OBJECTIVE: To determine whether a minimally invasive approach to sampling endometrial cells that can be applied during an active conception cycle can generate robust biomarker candidates for endometrial receptivity by genomewide gene expression profiling. DESIGN: Longitudinal study comparing gene expression profiles of cells isolated from uterine aspirates collected during the prereceptive and receptive phases of a natural cycle. SETTING: University-affiliated hospital. PATIENT(S): Healthy volunteers, ≤40 years of age, with regular menstrual cycles and no history of infertility. INTERVENTION(S): One menstrual cycle monitored with urinary kits to identify the luteinizing hormone (LH) surge; uterine aspirations collected at LH + 2 days (LH + 2) and at LH + 7; endometrial biopsy obtained on LH + 7; RNA extraction from the cellular material for gene expression profiling, and differential gene expression validated by NanoString assay and cross-validated against a publically available data set. MAIN OUTCOME MEASURE(S): Differentially expressed genes between LH + 2 and LH + 7 samples. RESULT(S): NanoString assay validated 96% of the 245 genes found differentially expressed at LH + 7. Unsupervised hierarchical clustering of aspiration and biopsy samples demonstrated the concordance of the sampling methods. A predictor gene cassette derived by a shrunken centroid class prediction technique correctly classified the receptive phase within an external data set. CONCLUSION(S): Uterine aspiration, which can be performed during an active conception cycle, identified robust candidate biomarkers of endometrial receptivity, and will enable their validation by direct correlation with clinical outcomes.

In vivo optical imaging of tumor and microvascular response to ionizing radiation.

Radiotherapy is a widely used cancer treatment. However, understanding how ionizing radiation affects tumor cells and their vasculature, particularly at cellular, subcellular, genetic, and protein levels, has been limited by an inability to visualize the response of these interdependent components within solid tumors over time and in vivo. Here we describe a new preclinical experimental platform combining intravital multimodal optical microscopy for cellular-level longitudinal imaging, a small animal x-ray microirradiator for reproducible spatially-localized millimeter-scale irradiations, and laser-capture microdissection of ex vivo tissues for transcriptomic profiling. Using this platform, we have developed new methods that exploit the power of optically-enabled microscopic imaging techniques to reveal the important role of the tumor microvasculature in radiation response of tumors. Furthermore, we demonstrate the potential of this preclinical platform to study quantitatively--with cellular and sub-cellular details--the spatio-temporal dynamics of the biological response of solid tumors to ionizing radiation in vivo.

Profiling microRNA expression with the Illumina BeadChip platform.

The complex mechanisms involved in the regulation of both gene and protein expressions are still being understood. When microarray technology was first introduced during the early to mid 1990s, they heralded a tremendous opportunity to study transcription on a global scale. Despite this promise, however, one thing that has become clear is that the expression of protein coding genes is not the only aspect of the transcriptome that researchers need pay attention to. Small noncoding RNAs, such as microRNAs, are now known to play a pivotal role in the control of both gene and protein expressions. Each microRNA may act upon a plurality of different targets, which makes the measurement of their expression levels a highly important part of understanding the entire cellular response. It has only been recently, however, that advancements and modifications to microarray technology have allowed us to study these important molecules in a high throughput and parallel manner.

Microarray-based DNA methylation profiling: technology and applications.

This work is dedicated to the development of a technology for unbiased, high-throughput DNA methylation profiling of large genomic regions. In this method, unmethylated and methylated DNA fractions are enriched using a series of treatments with methylation sensitive restriction enzymes, and interrogated on microarrays. We have investigated various aspects of the technology including its replicability, informativeness, sensitivity and optimal PCR conditions using microarrays containing oligonucleotides representing 100 kb of genomic DNA derived from the chromosome 22 COMT region in addition to 12 192 element CpG island microarrays. Several new aspects of methylation profiling are provided, including the parallel identification of confounding effects of DNA sequence variation, the description of the principles of microarray design for epigenomic studies and the optimal choice of methylation sensitive restriction enzymes. We also demonstrate the advantages of using the unmethylated DNA fraction versus the methylated one, which substantially improve the chances of detecting DNA methylation differences. We applied this methodology for fine-mapping of methylation patterns of chromosomes 21 and 22 in eight individuals using tiling microarrays consisting of over 340 000 oligonucleotide probe pairs. The principles developed in this work will help to make epigenetic profiling of the entire human genome a routine procedure.

CpG Island microarray probe sequences derived from a physical library are representative of CpG Islands annotated on the human genome.

An effective tool for the global analysis of both DNA methylation status and protein-chromatin interactions is a microarray constructed with sequences containing regulatory elements. One type of array suited for this purpose takes advantage of the strong association between CpG Islands (CGIs) and gene regulatory regions. We have obtained 20,736 clones from a CGI Library and used these to construct CGI arrays. The utility of this library requires proper annotation and assessment of the clones, including CpG content, genomic origin and proximity to neighboring genes. Alignment of clone sequences to the human genome (UCSC hg17) identified 9595 distinct genomic loci; 64% were defined by a single clone while the remaining 36% were represented by multiple, redundant clones. Approximately 68% of the loci were located near a transcription start site. The distribution of these loci covered all 23 chromosomes, with 63% overlapping a bioinformatically identified CGI. The high representation of genomic CGI in this rich collection of clones supports the utilization of microarrays produced with this library for the study of global epigenetic mechanisms and protein-chromatin interactions. A browsable database is available on-line to facilitate exploration of the CGIs in this library and their association with annotated genes or promoter elements.

Representation is faithfully preserved in global cDNA amplified exponentially from sub-picogram quantities of mRNA.

Analysis of transcript representation on gene microarrays requires microgram amounts of total RNA or DNA. Without amplification, such amounts are obtainable only from millions of cells. However, it may be desirable to determine transcript representation in few or even single cells in aspiration biopsies, rare population subsets isolated by cell sorting or laser capture, or micromanipulated single cells. Nucleic-acid amplification methods could be used in these cases, but it is difficult to amplify different transcripts in a sample without distorting quantitative relationships between them. Linear isothermal RNA amplification has been used to amplify as little as 10 ng of total cellular RNA, corresponding to the amount obtainable from thousands of cells, while still preserving the original abundance relationships. However, the available procedures require multiple steps, are labor intensive and time consuming, and have not been shown to preserve abundance information from smaller starting amounts. Exponential amplification, on the other hand, is a relatively simple technology, but is generally considered to bias abundance relationships unacceptably. These constraints have placed beyond current reach the secure and routine application of microarray analysis to single or small numbers of cells. Here we describe results obtained with a rapid and highly optimized global reverse transcription#150;PCR (RT-PCR) procedure. Contrary to prevalent expectations, the exponential approach preserves abundance relationships through amplification as high as 3 x 10(11)-fold. Further, it reduces by a million-fold the input amount of RNA needed for microarray analysis, and yields reproducible results from the picogram range of total RNA obtainable from single cells.