Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.

Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.

Suppressor T helper type 17 cell responses in intestinal transplant recipients with allograft rejection.

BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSION: We show that ITx rejection is associated with increased polarized cells that express a Th17-like phenotype concurrent with regulatory purinergic markers.

NSC243928 Treatment Induces Anti-Tumor Immune Response in Mouse Mammary Tumor Models.

NSC243928 induces cell death in triple-negative breast cancer cells in a LY6K-dependent manner. NSC243928 has been reported as an anti-cancer agent in the NCI small molecule library. The molecular mechanism of NSC243928 as an anti-cancer agent in the treatment of tumor growth in the syngeneic mouse model has not been established. With the success of immunotherapies, novel anti-cancer drugs that may elicit an anti-tumor immune response are of high interest in the development of novel drugs to treat solid cancer. Thus, we focused on studying whether NSC243928 may elicit an anti-tumor immune response in the in vivo mammary tumor models of 4T1 and E0771. We observed that NSC243928 induced immunogenic cell death in 4T1 and E0771 cells. Furthermore, NSC243928 mounted an anti-tumor immune response by increasing immune cells such as patrolling monocytes, NKT cells, B1 cells, and decreasing PMN MDSCs in vivo. Further studies are required to understand the exact mechanism of NSC243928 action in inducing an anti-tumor immune response in vivo, which can be used to determine a molecular signature associated with NSC243928 efficacy. NSC243928 may be a good target for future immuno-oncology drug development for breast cancer.

Lymphocyte antigen 6K signaling to aurora kinase promotes advancement of the cell cycle and the growth of cancer cells, which is inhibited by LY6K-NSC243928 interaction.

Lymphocyte antigen 6K (LY6K) is a small GPI-linked protein that is normally expressed in testes. Increased expression of LY6K is significantly associated with poor survival outcomes in many solid cancers, including cancers of the breast, ovary, gastrointestinal tract, head and neck, brain, bladder, and lung. LY6K is required for ERK-AKT and TGF-ß pathways in cancer cells and is required for in vivo tumor growth. In this report, we describe a novel role for LY6K in mitosis and cytokinesis through aurora B kinase and its substrate histone H3 signaling axis. Further, we describe the structural basis of the molecular interaction of small molecule NSC243928 with LY6K protein and the disruption of LY6K-aurora B signaling in cell cycle progression due to LY6K-NSC243928 interaction. Overall, disruption of LY6K function via NSC243928 led to failed cytokinesis, multinucleated cells, DNA damage, senescence, and apoptosis of cancer cells. LY6K is not required for vital organ function, thus inhibition of LY6K signaling is an ideal therapeutic approach for hard-to-treat cancers that lack targeted therapy such as triple-negative breast cancer.

StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit.

Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, phenomics, and proteomics, attempts to integrate and mine such datasets remain limited in scope. Developing hybrid intelligence solutions that combine human intelligence in the scientific domain and disease biology with the ability to mine multiple databases simultaneously may help augment drug target discovery and identify novel drug-indication associations. We believe that integrating different data sources using a singular numerical scoring system in a hybrid intelligent framework could help to bridge these different omics layers and facilitate rapid drug target prioritization for studies in drug discovery, development or repositioning. Herein, we describe our prototype of the StarGazer pipeline which combines multi-source, multi-omics data with a novel target prioritization scoring system in an interactive Python-based Streamlit dashboard. StarGazer displays target prioritization scores for genes associated with 1844 phenotypic traits, and is available via https://github.com/AstraZeneca/StarGazer.

Enhancing the REMBRANDT MRI collection with expert segmentation labels and quantitative radiomic features.

Malignancy of the brain and CNS is unfortunately a common diagnosis. A large subset of these lesions tends to be high grade tumors which portend poor prognoses and low survival rates, and are estimated to be the tenth leading cause of death worldwide. The complex nature of the brain tissue environment in which these lesions arise offers a rich opportunity for translational research. Magnetic Resonance Imaging (MRI) can provide a comprehensive view of the abnormal regions in the brain, therefore, its applications in the translational brain cancer research is considered essential for the diagnosis and monitoring of disease. Recent years has seen rapid growth in the field of radiogenomics, especially in cancer, and scientists have been able to successfully integrate the quantitative data extracted from medical images (also known as radiomics) with genomics to answer new and clinically relevant questions. In this paper, we took raw MRI scans from the REMBRANDT data collection from public domain, and performed volumetric segmentation to identify subregions of the brain. Radiomic features were then extracted to represent the MRIs in a quantitative yet summarized format. This resulting dataset now enables further biomedical and integrative data analysis, and is being made public via the NeuroImaging Tools & Resources Collaboratory (NITRC) repository ( https://www.nitrc.org/projects/rembrandt_brain/ ).

A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer's disease.

Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer's disease (LOAD) over a relatively short period of time (12-48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.

Molecular predictors of response to pembrolizumab in thymic carcinoma.

Thymic carcinoma is rare and has a poorer prognosis than thymomas. The treatment options are limited after failure of platinum-based chemotherapy. We previously performed a single-center phase II study of pembrolizumab in patients with advanced thymic carcinoma, showing a 22.5% response rate. Here, we characterize the genomic and transcriptomic profile of thymic carcinoma samples from 10 patients (5 non-responders versus 5 responders) in this cohort, with the main aim of identifying potential predictors of response to immunotherapy. We find that expression of PDL1 and alterations in genes or pathways that correlated with PD-L1 expression (CYLD and BAP1) could be potential predictors for response or resistance to immunotherapy in patients with advanced thymic carcinoma. Our study provides insights into potential predictive markers/pathways to select patients with thymic carcinoma for anti-PD-1 immunotherapy.

SPTBN1 inhibits inflammatory responses and hepatocarcinogenesis via the stabilization of SOCS1 and downregulation of p65 in hepatocellular carcinoma.

Background: Spectrin, beta, non-erythrocytic 1 (SPTBN1), an adapter protein for transforming growth factor beta (TGF-ß) signaling, is recognized as a tumor suppressor in the development of hepatocellular carcinoma (HCC); however, the underlying molecular mechanisms of this tumor suppression remain obscure. Methods: The effects on expression of pro-inflammatory cytokines upon the inhibition or impairment of SPTBN1 in HCC cell lines and liver tissues of Sptbn1+/- and wild-type (WT) mice were assessed by analyses of quantitative real-time reverse-transcription polymerase chain reaction (QRT-PCR), enzyme linked immunosorbent assay (ELISA), Western blotting and gene array databases from HCC patients. We investigated the detailed molecular mechanisms underlying the inflammatory responses by immunoprecipitation-Western blotting, luciferase reporter assay, chromatin immunoprecipitation quantitative real time PCR (ChIP-qPCR), immunohistochemistry (IHC) and electrophoretic mobility shift assay (EMSA). The proportion of myeloid-derived suppressor cells in liver, spleen, bone marrow and peripheral blood samples from WT and Sptbn1+/- mice were measured by fluorescence-activated cell sorting (FACS) analysis. Further, the hepatocacinogenesis and its correlation with inflammatory microenvironment by loss of SPTBN1/SOCS1 and induction of p65 were analyzed by treating WT and Sptbn1+/- mice with 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC). Results: Loss of SPTBN1 in HCC cells upregulated the expression of pro-inflammatory cytokines including interleukin-1α (IL-1α), IL-1ß, and IL-6, and enhanced NF-κB transcriptional activation. Mechanistic analyses revealed that knockdown of SPTBN1 by siRNA downregulated the expression of suppressor of cytokine signaling 1 (SOCS1), an E3 ligase of p65, and subsequently upregulated p65 accumulation in the nucleus of HCC cells. Restoration of SOCS1 abrogated this SPTBN1 loss-associated elevation of p65 in HCC cells. In human HCC tissues, SPTBN1 gene expression was inversely correlated with gene expression of IL-1α, IL-1ß and IL-6. Furthermore, a decrease in the levels of SPTBN1 gene, as well as an increase in the gene expression of IL-1ß or IL-6 predicted shorter relapse free survival in HCC patients, and that HCC patients with low expression of SPTBN1 or SOCS1 protein is associated with poor survival. Heterozygous loss of SPTBN1 (Sptbn1+/- ) in mice markedly upregulated hepatic expression of IL-1α, IL-1ß and IL-6, and elevated the proportion of myeloid-derived suppressor cells (MDSCs) and CD4+CD25+Foxp3+ regulatory T cells (Foxp3+Treg) cells in the liver, promoting hepatocarcinogenesis of mouse fed by DDC. Conclusions: Our findings provided evidence that loss of SPTBN1 in HCC cells increases p65 protein stability via the inhibition of SOCS1 and enhances NF-κB activation, stimulating the release of inflammatory cytokines, which are critical molecular mechanisms for the loss of SPTBN1-induced liver cancer formation. Reduced SPTBN1 and SOCS1 predict poor outcome in HCC patients.

High mRNA expression of LY6 gene family is associated with overall survival outcome in pancreatic ductal adenocarcinoma.

Pancreatic cancer ranks one of the worst in overall survival outcome with a 5 year survival rate being less than 10%. Pancreatic cancer faces unique challenges in its diagnosis and treatment, such as the lack of clinically validated biomarkers and the immensely immunosuppressive tumor microenvironment. Recently, the LY6 gene family has received increasing attention for its multi-faceted roles in cancer development, stem cell maintenance, immunomodulation, and association with more aggressive and hard-to-treat cancers. A detailed study of mRNA expression of LY6 gene family and its association with overall survival (OS) outcome in pancreatic cancers is lacking. We used publicly available clinical datasets to analyze the mRNA expression of a set of LY6 genes and its effect on OS outcome in the context of the tumor microenvironment and immunomodulation. We used web-based tools Kaplan-Meier Plotter, cBioPortal, Oncomine and R-programming to analyze copy number alterations, mRNA expression and its association with OS outcome in pancreatic cancer. These analyses demonstrated that high expression of LY6 genes is associated with OS and disease free survival (DFS) outcome. High expression of LY6 genes and their association with OS outcome is dependent on the composition of tumor microenvironment. Considering that LY6 proteins are anchored to the outer cell membrane or secreted, making them readily accessible, these findings highlight the potential of LY6 family members in the future of pancreatic cancer diagnosis and treatment.

Rejection of intestinal allotransplants is driven by memory T helper type 17 immunity and responds to infliximab.

Intestinal transplantation (ITx) can be life-saving for patients with advanced intestinal failure experiencing complications of parenteral nutrition. New surgical techniques and conventional immunosuppression have enabled some success, but outcomes post-ITx remain disappointing. Refractory cellular immune responses, immunosuppression-linked infections, and posttransplant malignancies have precluded widespread ITx application. To shed light on the dynamics of ITx allograft rejection and treatment resistance, peripheral blood samples and intestinal allograft biopsies from 51 ITx patients with severe rejection, alongside 37 stable controls, were analyzed using immunohistochemistry, polychromatic flow cytometry, and reverse transcription-PCR. Our findings inform both immunomonitoring and treatment. In terms of immunomonitoring, we found that while ITx rejection is associated with proinflammatory and activated effector memory T cells in the blood, evidence of treatment efficacy can only be found in the allograft itself, meaning that blood-based monitoring may be insufficient. In terms of treatment, we found that the prominence of intra-graft memory TNF-α and IL-17 double-positive T helper type 17 (Th17) cells is a leading feature of refractory rejection. Anti-TNF-α therapies appear to provide novel and safer treatment strategies for refractory ITx rejection; with responses in 14 of 14 patients. Clinical protocols targeting TNF-α, IL-17, and Th17 warrant further testing.

Type 3 innate lymphoid cells are associated with a successful intestinal transplant.

Although innate lymphoid cells (ILCs) play fundamental roles in mucosal barrier functionality and tissue homeostasis, ILC-related mechanisms underlying intestinal barrier function, homeostatic regulation, and graft rejection in intestinal transplantation (ITx) patients have yet to be thoroughly defined. We found protective type 3 NKp44+ ILCs (ILC3s) to be significantly diminished in newly transplanted allografts, compared to allografts at 6 months, whereas proinflammatory type 1 NKp44- ILCs (ILC1s) were higher. Moreover, serial immunomonitoring revealed that in healthy allografts, protective ILC3s repopulate by 2-4 weeks postoperatively, but in rejecting allografts they remain diminished. Intracellular cytokine staining confirmed that NKp44+ ILC3 produced protective interleukin-22 (IL-22), whereas ILC1s produced proinflammatory interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α). Our findings about the paucity of protective ILC3s immediately following transplant and their repopulation in healthy allografts during the first month following transplant were confirmed by RNA-sequencing analyses of serial ITx biopsies. Overall, our findings show that ILCs may play a key role in regulating ITx graft homeostasis and could serve as sentinels for early recognition of allograft rejection and be targets for future therapies.

The Long Noncoding RNA CCAT2 Induces Chromosomal Instability Through BOP1-AURKB Signaling.

BACKGROUND & AIMS: Chromosomal instability (CIN) is a carcinogenesis event that promotes metastasis and resistance to therapy by unclear mechanisms. Expression of the colon cancer-associated transcript 2 gene (CCAT2), which encodes a long noncoding RNA (lncRNA), associates with CIN, but little is known about how CCAT2 lncRNA regulates this cancer enabling characteristic. METHODS: We performed cytogenetic analysis of colorectal cancer (CRC) cell lines (HCT116, KM12C/SM, and HT29) overexpressing CCAT2 and colon organoids from C57BL/6N mice with the CCAT2 transgene and without (controls). CRC cells were also analyzed by immunofluorescence microscopy, γ-H2AX, and senescence assays. CCAT2 transgene and control mice were given azoxymethane and dextran sulfate sodium to induce colon tumors. We performed gene expression array and mass spectrometry to detect downstream targets of CCAT2 lncRNA. We characterized interactions between CCAT2 with downstream proteins using MS2 pull-down, RNA immunoprecipitation, and selective 2'-hydroxyl acylation analyzed by primer extension analyses. Downstream proteins were overexpressed in CRC cells and analyzed for CIN. Gene expression levels were measured in CRC and non-tumor tissues from 5 cohorts, comprising more than 900 patients. RESULTS: High expression of CCAT2 induced CIN in CRC cell lines and increased resistance to 5-fluorouracil and oxaliplatin. Mice that expressed the CCAT2 transgene developed chromosome abnormalities, and colon organoids derived from crypt cells of these mice had a higher percentage of chromosome abnormalities compared with organoids from control mice. The transgenic mice given azoxymethane and dextran sulfate sodium developed more and larger colon polyps than control mice given these agents. Microarray analysis and mass spectrometry indicated that expression of CCAT2 increased expression of genes involved in ribosome biogenesis and protein synthesis. CCAT2 lncRNA interacted directly with and stabilized BOP1 ribosomal biogenesis factor (BOP1). CCAT2 also increased expression of MYC, which activated expression of BOP1. Overexpression of BOP1 in CRC cell lines resulted in chromosomal missegregation errors, and increased colony formation, and invasiveness, whereas BOP1 knockdown reduced viability. BOP1 promoted CIN by increasing the active form of aurora kinase B, which regulates chromosomal segregation. BOP1 was overexpressed in polyp tissues from CCAT2 transgenic mice compared with healthy tissue. CCAT2 lncRNA and BOP1 mRNA or protein were all increased in microsatellite stable tumors (characterized by CIN), but not in tumors with microsatellite instability compared with nontumor tissues. Increased levels of CCAT2 lncRNA and BOP1 mRNA correlated with each other and with shorter survival times of patients. CONCLUSIONS: We found that overexpression of CCAT2 in colon cells promotes CIN and carcinogenesis by stabilizing and inducing expression of BOP1 an activator of aurora kinase B. Strategies to target this pathway might be developed for treatment of patients with microsatellite stable colorectal tumors.

Integrated copy number and miRNA expression analysis in triple negative breast cancer of Latin American patients.

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.

Genome sequencing analysis of blood cells identifies germline haplotypes strongly associated with drug resistance in osteosarcoma patients.

BACKGROUND: Osteosarcoma is the most common malignant bone tumor in children. Survival remains poor among histologically poor responders, and there is a need to identify them at diagnosis to avoid delivering ineffective therapy. Genetic variation contributes to a wide range of response and toxicity related to chemotherapy. The aim of this study is to use sequencing of blood cells to identify germline haplotypes strongly associated with drug resistance in osteosarcoma patients. METHODS: We used sequencing data from two patient datasets, from Inova Hospital and the NCI TARGET. We explored the effect of mutation hotspots, in the form of haplotypes, associated with relapse outcome. We then mapped the single nucleotide polymorphisms (SNPs) in these haplotypes to genes and pathways. We also performed a targeted analysis of mutations in Drug Metabolizing Enzymes and Transporter (DMET) genes associated with tumor necrosis and survival. RESULTS: We found intronic and intergenic hotspot regions from 26 genes common to both the TARGET and INOVA datasets significantly associated with relapse outcome. Among significant results were mutations in genes belonging to AKR enzyme family, cell-cell adhesion biological process and the PI3K pathways; as well as variants in SLC22 family associated with both tumor necrosis and overall survival. The SNPs from our results were confirmed using Sanger sequencing. Our results included known as well as novel SNPs and haplotypes in genes associated with drug resistance. CONCLUSION: We show that combining next generation sequencing data from multiple datasets and defined clinical data can better identify relevant pathway associations and clinically actionable variants, as well as provide insights into drug response mechanisms.

The REMBRANDT study, a large collection of genomic data from brain cancer patients.

The Rembrandt brain cancer dataset includes 671 patients collected from 14 contributing institutions from 2004-2006. It is accessible for conducting clinical translational research using the open access Georgetown Database of Cancer (G-DOC) platform. In addition, the raw and processed genomics and transcriptomics data have also been made available via the public NCBI GEO repository as a super series GSE108476. Such combined datasets would provide researchers with a unique opportunity to conduct integrative analysis of gene expression and copy number changes in patients alongside clinical outcomes (overall survival) using this large brain cancer study.

viGEN: An Open Source Pipeline for the Detection and Quantification of Viral RNA in Human Tumors.

An estimated 17% of cancers worldwide are associated with infectious causes. The extent and biological significance of viral presence/infection in actual tumor samples is generally unknown but could be measured using human transcriptome (RNA-seq) data from tumor samples. We present an open source bioinformatics pipeline viGEN, which allows for not only the detection and quantification of viral RNA, but also variants in the viral transcripts. The pipeline includes 4 major modules: The first module aligns and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral-gene level thus allowing for downstream differential expression analysis of viral genes between case and controls groups. The fourth module calls variants in these viruses. To the best of our knowledge, there are no publicly available pipelines or packages that would provide this type of complete analysis in one open source package. In this paper, we applied the viGEN pipeline to two case studies. We first demonstrate the working of our pipeline on a large public dataset, the TCGA cervical cancer cohort. In the second case study, we performed an in-depth analysis on a small focused study of TCGA liver cancer patients. In the latter cohort, we performed viral-gene quantification, viral-variant extraction and survival analysis. This allowed us to find differentially expressed viral-transcripts and viral-variants between the groups of patients, and connect them to clinical outcome. From our analyses, we show that we were able to successfully detect the human papilloma virus among the TCGA cervical cancer patients. We compared the viGEN pipeline with two metagenomics tools and demonstrate similar sensitivity/specificity. We were also able to quantify viral-transcripts and extract viral-variants using the liver cancer dataset. The results presented corresponded with published literature in terms of rate of detection, and impact of several known variants of HBV genome. This pipeline is generalizable, and can be used to provide novel biological insights into microbial infections in complex diseases and tumorigeneses. Our viral pipeline could be used in conjunction with additional type of immuno-oncology analysis based on RNA-seq data of host RNA for cancer immunology applications. The source code, with example data and tutorial is available at: https://github.com/ICBI/viGEN/.

EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer.

About 70% of all breast cancers are estrogen receptor alpha positive (ER+; ESR1). Many are treated with antiestrogens. Unfortunately, de novo 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.

Genomic comparison of early-passage conditionally reprogrammed breast cancer cells to their corresponding primary tumors.

Conditionally reprogrammed cells (CRCs) are epithelial cells that are directly isolated from patients' specimens and propagated in vitro with feeder cells and a Rho kinase inhibitor. A number of these cells have been generated from biopsies of breast cancer patients, including ductal carcinoma in situ and invasive carcinomas. The characterization of their genomic signatures is essential to determine their ability to reflect the natural biology of their tumors of origin. In this study, we performed the genomic characterization of six newly established invasive breast cancer CRC cultures in comparison to the original patients' primary breast tumors (PBT) from which they derived. The CRCs and corresponding PBTs were simultaneously profiled by genome-wide array-CGH, targeted next generation sequencing and global miRNA expression to determine their molecular similarities in the patterns of copy number alterations (CNAs), gene mutations and miRNA expression levels, respectively. The CRCs' epithelial cells content and ploidy levels were also evaluated by flow cytometry. A similar level of CNAs was observed in the pairs of CRCs/PBTs analyzed by array-CGH, with >95% of overlap for the most frequently affected cytobands. Consistently, targeted next generation sequencing analysis showed the retention of specific somatic variants in the CRCs as present in their original PBTs. Global miRNA profiling closely clustered the CRCs with their PBTs (Pearson Correlation, ANOVA paired test, P<0.05), indicating also similarity at the miRNA expression level; the retention of tumor-specific alterations in a subset of miRNAs in the CRCs was further confirmed by qRT-PCR. These data demonstrated that the human breast cancer CRCs of this study maintained at early passages the overall copy number, gene mutations and miRNA expression patterns of their original tumors. The further characterization of these cells by other molecular and cellular phenotypes at late cell passages, are required to further expand their use as a unique and representative ex-vivo tumor model for basic science and translational breast cancer studies.