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Clinical and molecular heterogeneity of Alzheimer disease (AD) is increasingly recognized as a major factor impacting the diagnosis, the design of therapeutic interventions and clinical trials, and therefore possibly delaying the development of effective treatments for AD. We sought to determine whether cross-omics integration reveals molecular profiles of AD with clinical and biological relevance. By leveraging cross-omics approaches, we integrated high-throughput transcriptomic, proteomic, metabolomic, and lipidomic profiles from AD and control cases from multiple cortical regions and cohorts. We identified four distinct molecular profiles in which a specific profile was associated with significantly higher Clinical Dementia Rating (CDR) at death, shorter survival after onset, more severe neurodegeneration and astrogliosis, and decreased levels of metabolomic profiles. Its molecular signatures show significant dysregulation of synaptic genes indicating neuron/synapse losses and dysfunction at later stages of AD, and present in multiple cortical regions. Among other molecules, we found that the expression of alpha-synuclein (SNCA) andSNAP25were downregulated in this profile. Overall, our results suggest that AD has a more prominent synaptic loss and dysfunction associated with worse cognition. These novel molecular findings open the possibility for new biomarkers for the molecular staging of AD and potential therapeutic targets to ameliorate cognitive decline and AD progression.

ObjectivesNeuroinflammation signaling has been identified as an important hallmark of Alzheimer’s disease (AD) in addition to amyloid β plaques (Aβ) and neurofibrillary tangles (NFTs). However, the molecular mechanisms and biological processes of neuroinflammation remain unclear and have not well delineated using transcriptomics data available. Our objectives are to uncover the core neuroinflammation signaling pathways in AD using integrative network analysis on the transcriptomics data.Materials and methodsFrom a novel perspective, i.e., investigating weakly activated molecular signals (rather than the strongly activated molecular signals), we developed integrative and systems biology network analysis to uncover potential core neuroinflammation signaling targets and pathways in AD using the two large-scale transcriptomics datasets, i.e., Mayo Clinic (77 controls and 81 AD samples) and ROSMAP (97 controls and 260 AD samples).ResultsOur analysis identified interesting core neuroinflammation signaling pathways, which are not systematically reported in the previous studies of AD. Specifically, we identified 7 categories of signaling pathways implicated on AD and related to virus infection: immune response, x-core signaling, apoptosis, lipid dysfunctional, biosynthesis and metabolism, and mineral absorption signaling pathways. More interestingly, most of the genes in the virus infection, immune response, and x-core signaling pathways are associated with inflammation molecular functions. The x-core signaling pathways were defined as a group of 9 signaling proteins: MAPK, Rap1, NF-kappa B, HIF-1, PI3K-Akt, Wnt, TGF-beta, Hippo, and TNF, which indicated the core neuroinflammation signaling pathways responding to the low-level and weakly activated inflammation and hypoxia and leading to the chronic neurodegeneration. It is interesting to investigate the detailed signaling cascades of these weakly activated neuroinflammation signaling pathways causing neurodegeneration in a chronic process, and consequently uncover novel therapeutic targets for effective AD treatment and prevention.ConclusionsThe potential core neuroinflammation and associated signaling targets and pathways were identified using integrative network analysis on two large-scale transcriptomics datasets of AD.

The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain.We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ɛ4, and TREM2 risk variant carriers, and sporadic AD (sAD).We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration.AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation.APP/PSEN1/PSEN2 and TREM2 variant carriers show distinct metabolic changes. A total of 133 metabolites were differentially abundant in AD genetic groups. β-citrylglutamate is differentially abundant in autosomal dominant, TREM2, and sporadic AD. A 16-metabolite profile shows differences between Alzheimer's disease (AD) genetic groups. The identified metabolic profile is associated with duration of disease.

More than 50 mutations in the MAPT gene result in heterogeneous forms of frontotemporal lobar dementia with tau inclusions (FTLD-tau). However, early pathogenic events that lead to disease and the degree to which they are common across MAPT mutations remain poorly understood. The goal of this study is to determine whether there is a common molecular signature of FTLD-Tau. To do this, we analyzed genes differentially expressed in induced pluripotent stem cell (iPSC)–derived neurons that represent the three major categories of MAPT mutations: splicing (IVS10+16), exon 10 (p.P301L), and C-terminal (p.R406W) compared with isogenic controls. Here, we identified 275 genes that were commonly differentially expressed in MAPT IVS10+16, p.P301L, and p.R406W neurons. These genes were enriched in synaptic and endolysosomal pathways and neuronal development and were also altered in the presence of tau aggregation in a mouse model of tauopathy. The MAPT mutations commonly led to changes in genes and pathways sensitive to disruptions in calcium homeostasis. One of these genes, CALB1, plays a role in calcium dysregulation and is targeted by several FDA- approved drugs used to treat neurological symptoms. Finally, a subset of genes commonly differentially expressed across MAPT mutations were also dysregulated in brains from progressive supranuclear palsy patients, suggesting that molecular signatures relevant to genetic and sporadic forms of tauopathy are captured in a dish. The results from this study demonstrate that iPSC-derived neurons capture molecular processes that occur in human brains and can be used to pinpoint common molecular pathways involving synaptic and endolysosomal function and neuronal development, which may be regulated by disruptions in calcium homeostasis.

Whole genome sequencing (WGS) has enabled the discovery of genomic structural variants (SVs), including those targeting intergenic and intronic non-coding regions that eluded previous exome focused strategies. However, the field currently lacks an automated tool that analyzes SV candidates to identify recurrent SVs and their targeted sites (hotspot regions), visualizes these genomic events within the context of various functional elements, and evaluates their potential effect on gene expression. To address this, we developed SV-HotSpot, an automated tool that integrates SV candidates, copy number alterations, gene expression, and genome annotations (e.g. gene and regulatory elements) to discover, annotate, and visualize recurrent SVs and their targeted hotspot regions that may affect gene expression. We applied SV-HotSpot to WGS and matched transcriptome data from metastatic castration resistant prostate cancer patients and rediscovered recurrent SVs targeting coding and non-coding functional elements known to promote prostate cancer progression and metastasis. SV-HotSpot provides a valuable resource to integrate SVs, gene expression, and genome annotations for discovering biologically relevant SVs altering coding and non-coding genome. SV-HotSpot is available at https://github.com/ChrisMaherLab/SV-HotSpot.

Late-stage relapse (LSR) in patients with breast cancer (BC) occurs more than five years and up to 10 years after initial treatment and has less than 30% 5-year relative survival rate. Long non-coding RNAs (lncRNAs) play important roles in BC yet have not been studied in LSR BC. Here, we identify 1127 lncRNAs differentially expressed in LSR BC via transcriptome sequencing and analysis of 72 early-stage and 24 LSR BC patient tumors. Decreasing expression of the most up-regulated lncRNA, LINC00355, in BC and MCF7 long-term estrogen deprived cell lines decreases cellular invasion and proliferation. Subsequent mechanistic studies show that LINC00355 binds to MENIN and changes occupancy at the CDKN1B promoter to decrease p27Kip. In summary, this is a key study discovering lncRNAs in LSR BC and LINC00355 association with epigenetic regulation and proliferation in BC.

Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17–35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36–200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17–200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool.

BackgroundAutosomal-dominant Alzheimer’s disease (ADAD) is caused by pathogenic mutations in APP, PSEN1, and PSEN2, which usually lead to an early age at onset (MethodsWe obtained and sequenced RNA from brain cortex using standard protocols. Linear counts were obtained using the TOPMed pipeline; circular counts, using python package DCC. After stringent quality control (QC), we obtained the counts for PSEN1, PSEN2 and APP genes. Only circPSEN1 passed QC. We used DESeq2 to compare the counts across groups, correcting for biological and technical variables. Finally, we performed in-silico functional analyses using the Circular RNA interactome website and DIANA mirPath software.ResultsOur results show significant differences in gene counts of circPSEN1 in ADAD individuals, when compared to sporadic AD and controls (ADAD=22, AD=274, Controls=25 – ADADvsCO: log2FC=0.786, p=9.08×10-05, ADADvsAD: log2FC=0.576, p=2.00×10-03). The high gene counts are contributed by two circPSEN1 species (hsa_circ_0008521 and hsa_circ_0003848). No significant differences were observed in linear PSEN1 gene expression between cases and controls, indicating that this finding is specific to the circular forms. In addition, the high circPSEN1 levels do not seem to be specific to PSEN1 mutation carriers; the counts are also elevated in APP and PSEN2 mutation carriers. In-silico functional analyses suggest that circPSEN1 is involved in several pathways such as axon guidance (p=3.39×10−07), hippo signaling pathway (p=7.38×10−07), lysine degradation (p=2.48×10−05) or Wnt signaling pathway (p=5.58×10−04) among other KEGG pathways. Additionally, circPSEN1 counts were able to discriminate ADAD from sporadic AD and controls with an AUC above 0.70.ConclusionsOur findings show the differential expression of circPSEN1 is increased in ADAD. Given the biological function previously ascribed to circular RNAs and the results of our in-silico analyses, we hypothesize that this finding might be related to neuroinflammatory events that lead or that are caused by the accumulation of amyloid-beta.

SUMMARY The pathogenic mechanism by which dominant mutations in VCP cause multisystem proteinopathy (MSP), a rare neurodegenerative disease that presents as fronto-temporal lobar degeneration with TDP-43 inclusions (FTLD-TDP), remains unclear. To explore this, we inactivate VCP in murine postnatal forebrain neurons (VCP conditional knockout [cKO]). VCP cKO mice have cortical brain atrophy, neuronal loss, autophago-lysosomal dysfunction, and TDP-43 inclusions resembling FTLD-TDP pathology. Conditional expression of a single disease-associated mutation, VCP-R155C, in a VCP null background similarly recapitulates features of VCP inactivation and FTLD-TDP, suggesting that this MSP mutation is hypomorphic. Comparison of transcriptomic and proteomic datasets from genetically defined patients with FTLD-TDP reveal that progranulin deficiency and VCP insufficiency result in similar profiles. These data identify a loss of VCP-dependent functions as a mediator of FTLD-TDP and reveal an unexpected biochemical similarity with progranulin deficiency., Graphical abstract, In brief Wani et al. demonstrate that loss of neuronal VCP recapitulates FTLD-TDP pathology in mice. Conditional expression of a VCP-R155C mutation, associated with MSP1, also recapitulates FTLD-TDP consistent with its hypomorphic function. A transcriptomic and proteomic signature of VCP inactivation resembles a transcriptomic signature in brains of patients with GRN insufficiency.

Late-stage relapse (LSR) in patients with breast cancer (BC) occurs more than five years and up to 10 years after initial treatment and has less than 30% 5-year relative survival rate. Long non-coding RNAs (lncRNAs) play important roles in BC yet have not been studied in LSR BC. Here, we identify 1127 lncRNAs differentially expressed in LSR BC via transcriptome sequencing and analysis of 72 early-stage and 24 LSR BC patient tumors. Decreasing expression of the most up-regulated lncRNA, LINC00355, in BC and MCF7 long-term estrogen deprived cell lines decreases cellular invasion and proliferation. Subsequent mechanistic studies show that LINC00355 binds to MENIN and changes occupancy at the CDKN1B promoter to decrease p27

Colorectal cancer (CRC) is the most common gastrointestinal malignancy in the U.S.A. and approximately 50% of patients develop metastatic disease (mCRC). Despite our understanding of long non-coding RNAs (lncRNAs) in primary colon cancer, their role in mCRC and treatment resistance remains poorly characterized. Therefore, through transcriptome sequencing of normal, primary, and distant mCRC tissues we find 148 differentially expressed RNAs Associated with Metastasis (RAMS). We prioritize RAMS11 due to its association with poor disease-free survival and promotion of aggressive phenotypes in vitro and in vivo. A FDA-approved drug high-throughput viability assay shows that elevated RAMS11 expression increases resistance to topoisomerase inhibitors. Subsequent experiments demonstrate RAMS11-dependent recruitment of Chromobox protein 4 (CBX4) transcriptionally activates Topoisomerase II alpha (TOP2α). Overall, recent clinical trials using topoisomerase inhibitors coupled with our findings of RAMS11-dependent regulation of TOP2α supports the potential use of RAMS11 as a biomarker and therapeutic target for mCRC., The role of long non-coding RNAs (lncRNAs) in metastatic colorectal cancer (mCRC) and treatment resistance is unclear. Here, the authors use transcriptome sequencing of matched normal, primary, and metastatic CRC tissues to discover and validate that lncRNA RAMS11 promotes metastasis and resistance to topoisomerase inhibitors in mCRC.

Background Long noncoding RNAs (lncRNAs) are an emerging class of relatively underexplored oncogenic molecules with biological and clinical significance. Current inadequacies for stratifying patients with aggressive disease presents a strong rationale to systematically identify lncRNAs as clinical predictors in localized prostate cancer. Objective To identify RNA biomarkers associated with aggressive prostate cancer. Design, setting, and participants Radical prostatectomy microarray and clinical data was obtained from 910 patients in three published institutional cohorts: Mayo Clinic I ( N =545, median follow-up 13.8 yr), Mayo Clinic II ( N =235, median follow-up 6.7 yr), and Thomas Jefferson University ( N =130, median follow-up 9.6 yr). Outcome measurements and statistical analysis The primary clinical endpoint was distant metastasis-free survival. Secondary endpoints include prostate cancer-specific survival and overall survival. Univariate and multivariate Cox regression were used to evaluate the association of lncRNA expression and these endpoints. Results and limitations An integrative analysis revealed Prostate Cancer Associated Transcript-14 ( PCAT-14 ) as the most prevalent lncRNA that is aberrantly expressed in prostate cancer patients. Down-regulation of PCAT-14 expression significantly associated with Gleason score and a greater probability of metastatic progression, overall survival, and prostate cancer-specific mortality across multiple independent datasets and ethnicities. Low PCAT-14 expression was implicated with genes involved in biological processes promoting aggressive disease. In-vitro analysis confirmed that low PCAT-14 expression increased migration while overexpressing PCAT-14 reduced cellular growth, migration, and invasion. Conclusions We discovered that androgen-regulated PCAT-14 is overexpressed in prostate cancer, suppresses invasive phenotypes, and lower expression is significantly prognostic for multiple clinical endpoints supporting its significance for predicting metastatic disease that could be used to improve patient management. Patient summary We discovered that aberrant prostate cancer associated transcript-14 expression during prostate cancer progression is prevalent across cancer patients. Prostate cancer associated transcript-14 is also prognostic for metastatic disease and survival highlighting its importance for stratifying patients that could benefit from treatment intensification.

Immune checkpoint blockade (ICB) provides clinical benefit to a minority of patients with urothelial carcinoma (UC). The role of CD4+ T cells in ICB-induced antitumor activity is not well defined; however, CD4+ T cells are speculated to play a supportive role in the development of CD8+ T cells that kill tumor cells after recognition of tumor antigens presented by MHC class I. To investigate the mechanisms of ICB-induced activity against UC, we developed mouse organoid-based transplantable models that have histologic and genetic similarity to human bladder cancer. We found that ICB can induce tumor rejection and protective immunity with these systems in a manner dependent on CD4+ T cells but not reliant on CD8+ T cells. Evaluation of tumor infiltrates and draining lymph nodes after ICB revealed expansion of IFN-γ-producing CD4+ T cells. Tumor cells in this system express MHC class I, MHC class II, and the IFN-γ receptor (Ifngr1), but none were necessary for ICB-induced tumor rejection. IFN-γ neutralization blocked ICB activity, and, in mice depleted of CD4+ T cells, IFN-γ ectopically expressed in the tumor microenvironment was sufficient to inhibit growth of tumors in which the epithelial compartment lacked Ifngr1. Our findings suggest unappreciated CD4+ T cell-dependent mechanisms of ICB activity, principally mediated through IFN-γ effects on the microenvironment.

Specialized chromatin structures such as nucleosomes with specific histone modifications decorate exons in eukaryotic genomes, suggesting a functional connection between chromatin organization and the regulation of pre-mRNA splicing. Through profiling the functional location of Poly (ADP) ribose polymerase, we observed that it is associated with the nucleosomes at exon/intron boundaries of specific genes, suggestive of a role for this enzyme in alternative splicing. Poly (ADP) ribose polymerase has previously been implicated in the PARylation of splicing factors as well as regulation of the histone modification H3K4me3, a mark critical for co-transcriptional splicing. In light of these studies, we hypothesized that interaction of the chromatin-modifying factor, Poly (ADP) ribose polymerase with nucleosomal structures at exon–intron boundaries, might regulate pre-mRNA splicing. Using genome-wide approaches validated by gene-specific assays, we show that depletion of PARP1 or inhibition of its PARylation activity results in changes in alternative splicing of a specific subset of genes. Furthermore, we observed that PARP1 bound to RNA, splicing factors and chromatin, suggesting that Poly (ADP) ribose polymerase serves as a gene regulatory hub to facilitate co-transcriptional splicing. These studies add another function to the multi-functional protein, Poly (ADP) ribose polymerase, and provide a platform for further investigation of this protein’s function in organizing chromatin during gene regulatory processes.

Poly (ADP-ribose) polymerase-1 (PARP1) is a nuclear enzyme involved in DNA repair, chromatin remodeling and gene expression. PARP1 interactions with chromatin architectural multi-protein complexes (i.e. nucleosomes) alter chromatin structure resulting in changes in gene expression. Chromatin structure impacts gene regulatory processes including transcription, splicing, DNA repair, replication and recombination. It is important to delineate whether PARP1 randomly associates with nucleosomes or is present at specific nucleosome regions throughout the cell genome. We performed genome-wide association studies in breast cancer cell lines to address these questions. Our studies show that PARP1 associates with epigenetic regulatory elements genome-wide, such as active histone marks, CTCF and DNase hypersensitive sites. Additionally, the binding of PARP1 to chromatin genome-wide is mutually exclusive with DNA methylation pattern suggesting a functional interplay between PARP1 and DNA methylation. Indeed, inhibition of PARylation results in genome-wide changes in DNA methylation patterns. Our results suggest that PARP1 controls the fidelity of gene transcription and marks actively transcribed gene regions by selectively binding to transcriptionally active chromatin. These studies provide a platform for developing our understanding of PARP1's role in gene regulation.

Breast cancer is the second most common newly diagnosed cancer and the second leading cause of cancer death among women in the United States. Despite the proven benefits of adjuvant endocrine therapy in women with hormone receptor positive breast cancer, relapses still occur over 5 years after initial treatment with endocrine therapy, referred to as late-stage relapse. Currently, the mechanisms of driving late-stage relapse are poorly characterized. To date, breast cancer research has primarily focused on protein-coding genes thereby missing the emerging class of long intergenic non-coding RNAs (lncRNAs) that may serve as critical regulators of relapse. Furthermore, the current understanding of lncRNA function is still in its infancy representing a critical gap for translating lncRNA discoveries into real-world applications to benefit patient care. Several well-described examples indicate that lncRNAs may be master epigenetic regulators in cancer biology through their interactions with proteins regulating target gene expression. Therefore, we hypothesize that lncRNAs may interact with estrogen receptor alpha 1 (ESR1) to regulate genes promoting late-stage relapse. To address this, we performed a transcriptome analysis of tumors from a unique cohort of 24 patients that had late-stage relapse to discover a novel set of lncRNAs, most of which have not yet been characterized. Next, we used RNA Immunoprecipitation coupled with transcriptome sequencing (RIP-Seq) to identify transcripts bound to ESR1 in T47D cells. We discovered 217 lncRNAs bound to ESR1 of which 50 were up-regulated in late-stage breast cancer. We chose to focus the most up-regulated lncRNA in late-stage relapse. Since it is an unannotated lncRNA we will refer to it as 'LAte-Stage relapse ESR1-Bound lncRNA 1', or LASER-1. To further understand the interplay between LASER-1 and ESR1, cells endogenously expressing LASER-1 were subjected to partial digestion to preserve lncRNA and protein interactions. Protected RNA fragments were subsequently immunoprecipitated with ESR1 and quantified by qPCR to reveal specific ESR1 interaction sites within LASER-1. Next, we observed increased expression of LASER-1 in ER+ breast cancer cell lines. Notably, LASER-1 expression was elevated in MCF7 long-term estrogen deprived (MCF7 LTED) cells -- that have amplified ESR1 -- relative to parental MCF7 cells. To demonstrate that LASER-1 promotes oncogenic phenotypes we transiently silenced LASER-1 in two cell lines with high endogenous expression of LASER-1 (including MCF LTED) and observed a decrease in cellular proliferation and invasion. Subsequent gene expression analysis after silencing LASER-1 altered mRNA and protein levels of critical cell cycle genes (i.e., p27). Overall, this is the first study to discover ESR1 bound lncRNAs that may be contributing to late-stage relapse in breast cancer. In the short-term, our ongoing research may lead to significant breakthroughs establishing the importance of LASER-1 as a master regulator in late-stage relapse. In the longer-term, we envision this research may lead to the development of novel therapeutics targeting LASER-1 with the potential for rapid clinical translation. Citation Format: Maher CA, Silva-Fisher J, Eteleeb A, Tang C, Perou C, Reis-Filho JS, Mardis ER, Ellis MJ. Discovery and characterization of an estrogen bound LncRNA in late-Stage breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr GS2-01.

Breast cancer (BC) is the second most common newly diagnosed cancer and the second leading cause of cancer death among women in the United States. Despite the proven benefits of adjuvant endocrine therapy in women with hormone receptor positive BC, relapses still occur even after initial treatment with endocrine therapy for 5 years, referred to as late-stage relapse. Long non-coding RNAs (lncRNAs) have been shown to be dysregulated in breast cancer. Recent studies have also shown lncRNAs to function by interfacing with corresponding RNA binding proteins to play critical regulatory roles of diverse cellular processes. Therefore, we hypothesize that lncRNAs may interact with ER to regulate genes promoting late-stage relapse. To address this, we aimed to identify lncRNAs bound to the estrogen receptor alpha 1 protein (ESR1) that promote late-stage relapse breast cancer. We first used transcriptome sequencing to identify altered expression levels of lncRNAs between 72 primary tumors and 24 late-stage relapse breast cancer patients. We detected 1192 altered lncRNAs when comparing the metastatic to the primary samples (FDR Citation Format: Jessica Monique Silva-Fisher, Abdallah M. Eteleeb, Torsten Nielsen, Charles M. Perou, Jorge S. Reis-Filho, Mathew J. Ellis, Elaine R. Mardis, Christopher A. Maher. Discovery and characterization of late-stage breast cancer estrogen receptor alpha 1 bound long non-coding RNAs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2547. doi:10.1158/1538-7445.AM2017-2547

High-throughput mRNA sequencing (also known as RNA-Seq) promises to be the technique of choice for studying transcriptome profiles. This technique provides the ability to develop precise methodologies for transcript and gene expression quantification, novel transcript and exon discovery, and splice variant detection. One of the limitations of current RNA-Seq methods is the dependency on annotated biological features (e.g. exons, transcripts, genes) to detect expression differences across samples. This forces the identification of expression levels and the detection of significant changes to known genomic regions. Any significant changes that occur in unannotated regions will not be captured. To overcome this limitation, we developed a novel segmentation approach, Island-Based (IB), for analyzing differential expression in RNA-Seq and targeted sequencing (exome capture) data without specific knowledge of an isoform. The IB segmentation determines individual islands of expression based on windowed read counts that can be compared across experimental conditions to determine differential island expression. In order to detect differentially expressed genes, the significance of islands (p-values) are combined using Fisher's method. We tested and evaluated the performance of our approach by comparing it to the existing differentially expressed gene (DEG) methods: CuffDiff, DESeq, and edgeR using two benchmark MAQC RNA-Seq datasets. The IB algorithm outperforms all three methods in both datasets as illustrated by an increased auROC.

Breast cancer (BC) is the second most common newly diagnosed cancer and the second leading cause of cancer death among women in the United States. Around 70% of diagnosed BCs are estrogen receptor positive (ER+). Despite the proven benefits of adjuvant endocrine therapy in women with hormone receptor positive breast cancer, relapses still occur even after initial treatment with endocrine therapy for 5 years, referred to as late stage relapse. While existing studies have focused on the role of protein-coding genes, long non-coding RNAs (lncRNAs) are an emerging and under-characterized class of transcripts that have been shown to be dysregulated in breast cancer. Recently, lncRNAs have been shown to function by interfacing with corresponding RNA binding proteins to play critical regulatory roles in chromatin remodeling and diverse cellular processes by acting as decoys, guides, and scaffolds. As estrogen receptor expression is controlled mostly by epigenetic and post-transcriptional mechanisms, and very rarely at the genomic level, we hypothesize that lncRNAs may interact with ER to promote aggressive disease. To address this, we aimed to identify lncRNAs bound to the estrogen receptor alpha 1 (ESR1) that promote late stage breast cancer. To accomplish this, we first used transcriptome sequencing to identify altered expression levels of lncRNAs between primary tumors and late-stage relapse breast cancer patients. We detected 2086 altered lncRNAs when comparing the metastatic to the primary samples with an FDR Citation Format: Jessica M. Silva-Fisher, Abdallah M. Eteleeb, Torsten O. Nielsen, Charles M. Perou, Jorge S. Reis-Filho, Mathew J. Ellis, Elaine R. Mardis, Christopher A. Maher. Identification of estrogen receptor alpha 1 bound lncRNAs in aggressive breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 993.

Affymetrix® GeneChip® micro array design defines probe sets consisting of 11, 16, or 20 distinct 25 base pair (BP) probes for determining mRNA expression for a specific gene, which may be covered by one or more probe sets. Each probe has a corresponding perfect match (PM) and mismatch (MM) set. Traditional analytical techniques have either used the MM probes to determine the level of cross-hybridization or reliability of the PM probe, or have been completely ignored. Given the availability of reference genome sequences, we have reanalyzed the mapping of both PM and MM probes to reference genomes in transcript regions. Our results suggest that depending of the species of interest, 66%-93% of the PM probes can be used reliably in terms of single unique matches to the genome, while a small number of the MM probes (typically less than 1%) could be incorporated into the analysis. In addition, we have examined the mapping of PM and MM probes to five different human genome projects, resulting in approximately a 70% overlap of uniquely mapping PM probes, and a subset of 51 uniquely mapping MM probes commonly found in all five projects, 24 of which are found within annotated exonic regions. These results suggest that individual variation in transcriptome regions provides an additional complexity to micro array data analysis. Given these results, we conclude that the development of custom chip definition files (CDFs) should include MM probe sequences to provide the most effective means of transcriptome analysis of Affymetrix® GeneChip® arrays.

Results Computational analyses of the novel UTR sequences, focusing on RNA-binding protein (RNAbp) interaction motifs revealed strongly over-represented RNAbps with known roles in nervous system pathologies. We consider the implications of 3’UTR transcript extension and protein interaction in the context of axonal plasticity and the consequences of mis-regulation of this process during neurological disease.