Intestinal transplant (ITx) rejection is associated with memory T helper type 17 cell (Th17) infiltration of grafted tissues. Modulation of Th17 effector cell response is facilitated by T regulatory ...(Treg) cells, but a phenotypic characterization of this process is lacking in the context of allograft rejection.
Flow cytometry was performed to examine the expression of surface receptors, cytokines, and transcription factors in Th17 and Treg cells in ITx control (n = 34) and rejection patients (n = 23). To elucidate key pathways guiding the rejection biology, we utilized RNA sequencing (RNAseq) and assessed epigenetic stability through pyrosequencing of the Treg-specific demethylated region (TSDR).
We found that intestinal allograft rejection is characterized by Treg cellular infiltrates, which are polarized toward Th17-type chemokine receptor, ROR-γt transcription factor expression, and cytokine production. These Treg cell subsets have maintained epigenetic stability, as defined by FoxP3-TSDR methylation status, but displayed upregulation of functional Treg and purinergic signaling genes by RNAseq analysis such as CD39, in keeping with suppressor Th17 properties.
We show that ITx rejection is associated with increased polarized cells that express a Th17-like phenotype concurrent with regulatory purinergic markers.
G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression ...arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information.
G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability.
G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available at: https://gdoc.georgetown.edu .
Triple Negative Breast Cancer (TNBC), a clinically aggressive subtype of breast cancer, disproportionately affects African American (AA) women when compared to non-Hispanic Whites (NHW). ...MiRNAs(miRNAs) play a critical role in these tumors, through the regulation of cancer driver genes. In this study, our goal was to characterize and compare the patterns of miRNA expression in TNBC of AA (n = 27) and NHW women (n = 30). A total of 256 miRNAs were differentially expressed between these groups, and distinct from the ones observed in their respective non-TNBC subtypes. Fifty-five of these miRNAs were mapped in cytobands carrying copy number alterations (CNAs); 26 of them presented expression levels concordant with the observed CNAs. Receiving operating characteristic (ROC) analysis showed a good power (AUC ≥ 0.80; 95% CI) for over 65% of the individual miRNAs and a high combined power with superior sensitivity and specificity (AUC = 0.88 (0.78-0.99); 95% CI) of the 26 miRNA panel in discriminating TNBC between these populations. Subsequent miRNA target analysis revealed their involvement in the interconnected PI3K/AKT, MAPK and insulin signaling pathways. Additionally, three miRNAs of this panel were associated with early age at diagnosis. Altogether, these findings indicated that there are different patterns of miRNA expression between TNBC of AA and NHW women and that their mapping in genomic regions with high levels of CNAs is not merely physical, but biologically relevant to the TNBC phenotype. Once validated in distinct cohorts of AA women, this panel can potentially represent their intrinsic TNBC genome signature.
About 70% of all breast cancers are estrogen receptor alpha positive (ER+; ESR1). Many are treated with antiestrogens. Unfortunately,
and acquired resistance to antiestrogens is common but the ...underlying mechanisms remain unclear. Since growth of cancer cells is dependent on adequate energy and metabolites, the metabolomic profile of endocrine resistant breast cancers likely contains features that are deterministic of cell fate. Thus, we integrated data from metabolomic and transcriptomic analyses of ER+ MCF7-derived breast cancer cells that are antiestrogen sensitive (LCC1) or resistant (LCC9) that resulted in a gene-metabolite network associated with EGR1 (early growth response 1). In human ER+ breast tumors treated with endocrine therapy, higher EGR1 expression was associated with a more favorable prognosis. Mechanistic studies showed that knockdown of EGR1 inhibited cell growth in both cells and EGR1 overexpression did not affect antiestrogen sensitivity. Comparing metabolite profiles in LCC9 cells following perturbation of EGR1 showed interruption of lipid metabolism. Tolfenamic acid, an anti-inflammatory drug, decreased EGR1 protein levels and synergized with antiestrogens in inhibiting cell proliferation in LCC9 cells. Collectively, these findings indicate that EGR1 is an important regulator of breast cancer cell metabolism and is a promising target to prevent or reverse endocrine resistance.
Background One-third of estrogen (ER+) and/or progesterone receptor-positive (PGR+) breast tumors treated with Tamoxifen (TAM) do not respond to initial treatment, and the remaining 70% are at risk ...to relapse in the future. Estrogen-related receptor gamma (ESRRG, ERRgamma) is an orphan nuclear receptor with broad, structural similarities to classical ER that is widely implicated in the transcriptional regulation of energy homeostasis. We have previously demonstrated that ERRgamma induces resistance to TAM in ER+ breast cancer models, and that the receptor's transcriptional activity is modified by activation of the ERK/MAPK pathway. We hypothesize that hyper-activation or over-expression of ERRgamma induces a pro-survival transcriptional program that impairs the ability of TAM to inhibit the growth of ER+ breast cancer. The goal of the present study is to determine whether ERRgamma target genes are associated with reduced distant metastasis-free survival (DMFS) in ER+ breast cancer treated with TAM. Methods Raw gene expression data was obtained from 3 publicly available breast cancer clinical studies of women with ER+ breast cancer who received TAM as their sole endocrine therapy. ERRgamma target genes were selected from 2 studies that published validated chromatin immunoprecipitation (ChIP) analyses of ERRgamma promoter occupancy. Kaplan-Meier estimation was used to determine the association of ERRgamma target genes with DMFS, and selected genes were validated in ER+, MCF7 breast cancer cells that express exogenous ERRgamma. Results Thirty-seven validated receptor target genes were statistically significantly altered in women who experienced a DM within 5 years, and could classify several independent studies into poor vs. good DMFS. Two genes (EEF1A2 and PPIF) could similarly separate ER+, TAM-treated breast tumors by DMFS, and their protein levels were measured in an ER+ breast cancer cell line model with exogenous ERRgamma. Finally, expression of ERRgamma and these two target genes are elevated in models of ER+ breast cancer with hyperactivation of ERK/MAPK. Conclusions ERRgamma signaling is associated with poor DMFS in ER+, TAM-treated breast cancer, and ESRRG, EEF1A2, and PPIF comprise a 3-gene signaling node that may contribute to TAM resistance in the context of an active ERK/MAPK pathway. Keywords: Estrogen-related receptor gamma, Tamoxifen, ER+ breast cancer, MAPK, Apoptosis
Triple negative breast cancer (TNBC), a clinically aggressive breast cancer subtype, affects 15–35% of women from Latin America. Using an approach of direct integration of copy number and global ...miRNA profiling data, performed simultaneously in the same tumor specimens, we identified a panel of 17 miRNAs specifically associated with TNBC of ancestrally characterized patients from Latin America, Brazil. This panel was differentially expressed between the TNBC and non-TNBC subtypes studied (
p
≤ 0.05, FDR ≤ 0.25), with their expression levels concordant with the patterns of copy number alterations (CNAs), present mostly frequent at 8q21.3-q24.3, 3q24-29, 6p25.3-p12.2, 1q21.1-q44, 5q11.1-q22.1, 11p13-p11.2, 13q12.11-q14.3, 17q24.2-q25.3 and Xp22.33-p11.21. The combined 17 miRNAs presented a high power (AUC = 0.953 (0.78–0.99);95% CI) in discriminating between the TNBC and non-TNBC subtypes of the patients studied. In addition, the expression of 14 and 15 of the 17miRNAs was significantly associated with tumor subtype when adjusted for tumor stage and grade, respectively. In conclusion, the panel of miRNAs identified demonstrated the impact of CNAs in miRNA expression levels and identified miRNA target genes potentially affected by both CNAs and miRNA deregulation. These targets, involved in critical signaling pathways and biological functions associated specifically with the TNBC transcriptome of Latina patients, can provide biological insights into the observed differences in the TNBC clinical outcome among racial/ethnic groups, taking into consideration their genetic ancestry.
Recent studies suggest that microRNAs show promise as excellent biomarkers for breast cancer; however there is still a high degree of variability between studies making the findings difficult to ...interpret. In addition to blood, ductal lavage (DL) and nipple aspirate fluids represent an excellent opportunity for biomarker detection because they can be obtained in a less invasive manner than biopsies and circumvent the limitations of evaluating blood biomarkers with regards to tissue of origin specificity. In this study, we have investigated for the first time, through a real-time PCR array, the expression of 742 miRNAs in the ductal lavage fluid collected from 22 women with unilateral breast tumors. We identified 17 differentially expressed miRNAs between tumor and paired normal samples from patients with ductal breast carcinoma. Most of these miRNAs have various roles in breast cancer tumorigenesis, invasion and metastasis, therapeutic response, or are associated with several clinical and pathological characteristics of breast tumors. Moreover, some miRNAs were also detected in other biological fluids of breast cancer patients such as serum (miR-23b, -133b, -181a, 338-3p, -625), plasma (miR-200a), and breast milk (miR-181a). A systems biology analysis of these differentially expressed miRNAs points out possible pathways and cellular processes previously described as having an important role in breast cancer such as Wnt, ErbB, MAPK, TGF-β, mTOR, PI3K-Akt, p53 signaling pathways. We also observed a difference in the miRNA expression with respect to the histological type of the tumors. In conclusion, our findings suggest that miRNA analysis of breast ductal fluid is feasible and potentially very useful for the detection of breast cancer.
Metabolomics is an emerging omics science that has demonstrated its fast gaining importance as a powerful profiling tool for determining an individual's response to a foreign stimulus such as a drug, ...toxin, or environmental change; or as an indicator of disease progression. Such small molecule profiles can used as biological markers of disease, and provide an indicator of drug efficacy or toxicity. Several studies have demonstrated that the results of any single omics analysis may not be sufficient to decode extremely complex biological mechanisms. Researchers have developed a translational research workflow to enable researchers to perform cutting-edge integrative analysis of metabolomics data with transcriptomics (gene expression) data using knowledge-driven networks. This network based view of interconnected functional partners can provide valuable new insight about the underlying biochemical processes and pathways associated with the phenotype of interest. To demonstrate the usefulness and strength of the methodology, researchers have tested it on a multi-omics profiling dataset from NCI-60 breast cancer cell lines to explore the biological dynamics of breast cancer.
Biologically accurate mouse models of human cancer have become important tools for the study of human disease. The anatomical location of various target organs, such as brain, pancreas, and prostate, ...makes determination of disease status difficult. Imaging modalities, such as magnetic resonance imaging, can greatly enhance diagnosis, and longitudinal imaging of tumor progression is an important source of experimental data. Even in models where the tumors arise in areas that permit visual determination of tumorigenesis, longitudinal anatomical and functional imaging can enhance the scope of studies by facilitating the assessment of biological alterations, (such as changes in angiogenesis, metabolism, cellular invasion) as well as tissue perfusion and diffusion. One of the challenges in preclinical imaging is the development of infrastructural platforms required for integrating in vivo imaging and therapeutic response data with ex vivo pathological and molecular data using a more systems-based multiscale modeling approach. Further challenges exist in integrating these data for computational modeling to better understand the pathobiology of cancer and to better affect its cure. We review the current applications of preclinical imaging and discuss the implications of applying functional imaging to visualize cancer progression and treatment. Finally, we provide new data from an ongoing preclinical drug study demonstrating how multiscale modeling can lead to a more comprehensive understanding of cancer biology and therapy.
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