Search

Altered RNA expression of repetitive sequences and retrotransposition are frequently seen in colorectal cancer, implicating a functional importance of repeat activity in cancer progression. We show the nucleoside reverse transcriptase inhibitor 3TC targets activities of these repeat elements in colorectal cancer preclinical models with a preferential effect in p53-mutant cell lines linked with direct binding of p53 to repeat elements. We translate these findings to a human phase II trial of single-agent 3TC treatment in metastatic colorectal cancer with demonstration of clinical benefit in 9 of 32 patients. Analysis of 3TC effects on colorectal cancer tumorspheres demonstrates accumulation of immunogenic RNA:DNA hybrids linked with induction of interferon response genes and DNA damage response. Epigenetic and DNA-damaging agents induce repeat RNAs and have enhanced cytotoxicity with 3TC. These findings identify a vulnerability in colorectal cancer by targeting the viral mimicry of repeat elements.Significance:Colorectal cancers express abundant repeat elements that have a viral-like life cycle that can be therapeutically targeted with nucleoside reverse transcriptase inhibitors (NRTI) commonly used for viral diseases. NRTIs induce DNA damage and interferon response that provide a new anticancer therapeutic strategy.This article is highlighted in the In This Issue feature, p. 1397

Supplementary Figure from Reverse Transcriptase Inhibition Disrupts Repeat Element Life Cycle in Colorectal Cancer

Supplementary Data from Reverse Transcriptase Inhibition Disrupts Repeat Element Life Cycle in Colorectal Cancer

Supplementary Figure S1. Senescence-activated SASP enhancers are marked by H3K4Me1 in proliferating IMR90 cells. Supplementary Figure S2. Reproducibility analyses of biological replicates for H3K27Ac and BRD4 ChIP-Seq. Supplementary Figure S3. Enhancer remodeling during oncogene-induced senescence parallels gene expression changes. Supplementary Figure S4. Genetic and pharmacologic inhibition of BRD4 impairs SASP gene expression during oncogene-induced senescence (OIS). Supplementary Figure S5. BRD4 couples enhancer remodeling to SASP gene expression during etoposide-induced senescence. Supplementary Figure S6. Systemic and cell-autonomous suppression of Brd4 impairs the immune surveillance of senescent hepatocytes.

Supplemental Methods from Development of siRNA Payloads to Target KRAS-Mutant Cancer

Co-culture of NK cells and P/shRen IMR90 cells.

Supplementary Methods, Figure Legends, References.

Lists of senescence-activated and senescence-inactivated TEs and SEs.

Supplemental References from Development of siRNA Payloads to Target KRAS-Mutant Cancer

Supplemental Figure and Table Legends from Development of siRNA Payloads to Target KRAS-Mutant Cancer

Supplemental Figure S1. Sensor-based generation of a functionally validated sh/siRNA library targeting Ras pathway genes. Figure S2. Validation of Sensor siRNAs targeting components in the MAPK pathway. Figure S3. Dose dependent off-target effects of sh/siRNAs. Figure S4. Sensor siRNA pooling effects. Figure S5. In vivo fluorescence reporter system. Table S1. Correlation of library reads and Sensor score.

Analysis of shRNA and endogenous miRNA representation.

Altered RNA expression of repetitive sequences and retrotransposition are frequently seen in colorectal cancer, implicating a functional importance of repeat activity in cancer progression. We show the nucleoside reverse transcriptase inhibitor 3TC targets activities of these repeat elements in colorectal cancer preclinical models with a preferential effect in p53-mutant cell lines linked with direct binding of p53 to repeat elements. We translate these findings to a human phase II trial of single-agent 3TC treatment in metastatic colorectal cancer with demonstration of clinical benefit in 9 of 32 patients. Analysis of 3TC effects on colorectal cancer tumorspheres demonstrates accumulation of immunogenic RNA:DNA hybrids linked with induction of interferon response genes and DNA damage response. Epigenetic and DNA-damaging agents induce repeat RNAs and have enhanced cytotoxicity with 3TC. These findings identify a vulnerability in colorectal cancer by targeting the viral mimicry of repeat elements.Significance:Colorectal cancers express abundant repeat elements that have a viral-like life cycle that can be therapeutically targeted with nucleoside reverse transcriptase inhibitors (NRTI) commonly used for viral diseases. NRTIs induce DNA damage and interferon response that provide a new anticancer therapeutic strategy.This article is highlighted in the In This Issue feature, p. 1397

Transcriptional profiling has defined pancreatic ductal adenocarcinoma (PDAC) into distinct subtypes with the majority being classical epithelial (E) or quasi-mesenchymal (QM). Despite clear differences in clinical behavior, growing evidence indicates these subtypes exist on a continuum with features of both subtypes present and suggestive of interconverting cell states. Here, we investigated the impact of different therapies being evaluated in PDAC on the phenotypic spectrum of the E/QM state. We demonstrate using RNA-sequencing and RNA-in situ hybridization (RNA-ISH) that FOLFIRINOX combination chemotherapy induces a common shift of both E and QM PDAC toward a more QM state in cell lines and patient tumors. In contrast, Vitamin D, another drug under clinical investigation in PDAC, induces distinct transcriptional responses in each PDAC subtype, with augmentation of the baseline E and QM state. Importantly, this translates to functional changes that increase metastatic propensity in QM PDAC, but decrease dissemination in E PDAC in vivo models. These data exemplify the importance of both the initial E/QM subtype and the plasticity of E/QM states in PDAC in influencing response to therapy, which highlights their relevance in guiding clinical trials.

Precise rare-cell technologies require the blood to be processed immediately or be stabilized with fixatives. Such restrictions limit the translation of circulating tumor cell (CTC)-based liquid biopsy assays that provide accurate molecular data in guiding clinical decisions. Here we describe a method to preserve whole blood in its minimally altered state by combining hypothermic preservation with targeted strategies that counter cooling-induced platelet activation. Using this method, whole blood preserved for up to 72 h can be readily processed for microfluidic sorting without compromising CTC yield and viability. The tumor cells retain high-quality intact RNA suitable for single-cell RT-qPCR as well as RNA-Seq, enabling the reliable detection of cancer-specific transcripts including the androgen-receptor splice variant 7 in a cohort of prostate cancer patients with an overall concordance of 92% between fresh and preserved blood. This work will serve as a springboard for the dissemination of diverse blood-based diagnostics., The current FDA-approved whole blood stabilization method for circulating tumor cell (CTC) isolation suffers from RNA degradation. Here the authors combine hypothermic preservation and antiplatelet strategies to stabilize whole blood up to 72 h without compromising CTC yield and RNA integrity.

We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

The detection of rare circulating tumor cells (CTCs) in the blood of cancer patients has the potential to be a powerful and noninvasive method for examining metastasis, evaluating prognosis, assessing tumor sensitivity to drugs, and monitoring therapeutic outcomes. In this study, we have developed an efficient strategy to isolate CTCs from the blood of breast cancer patients using a microfluidic immune-affinity approach. Additionally, to gain further access to these rare cells for downstream characterization, our strategy allows for easy detachment of the captured CTCs from the substrate without compromising cell viability or the ability to employ next generation RNA sequencing for the identification of specific breast cancer genes. To achieve this, a chemical ligand-exchange reaction was engineered to release cells attached to a gold nanoparticle coating bound to the surface of a herringbone microfluidic chip (NP-HBCTC-Chip). Compared to the use of the unmodified HBCTC-Chip, our approach provides several advantages, including enhanced capture efficiency and recovery of isolated CTCs.

Single-cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single-cell phenotypes have not been well defined. Combining single-cell RNA and protein analytics in studying the role of stromal cancer-associated fibroblasts (CAFs) in modulating heterogeneity in pancreatic cancer (pancreatic ductal adenocarcinoma [PDAC]) model systems, we have identified significant single-cell population shifts toward invasive epithelial-to-mesenchymal transition (EMT) and proliferative (PRO) phenotypes linked with mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 3 (STAT3) signaling. Using high-content digital imaging of RNA in situ hybridization in 195 PDAC tumors, we quantified these EMT and PRO subpopulations in 319,626 individual cancer cells that can be classified within the context of distinct tumor gland "units." Tumor gland typing provided an additional layer of intratumoral heterogeneity that was associated with differences in stromal abundance and clinical outcomes. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.

Oncogene-induced senescence is a potent barrier to tumorigenesis that limits cellular expansion following certain oncogenic events. Senescent cells display a repressive chromatin configuration thought to stably silence proliferation-promoting genes while simultaneously activating an unusual form of immune surveillance involving a secretory program referred to as the senescence-associated secretory phenotype (SASP). Here, we demonstrate that senescence also involves a global remodeling of the enhancer landscape with recruitment of the chromatin reader BRD4 to newly activated super-enhancers adjacent to key SASP genes. Transcriptional profiling and functional studies indicate that BRD4 is required for the SASP and downstream paracrine signaling. Consequently, BRD4 inhibition disrupts immune cell–mediated targeting and elimination of premalignant senescent cells in vitro and in vivo. Our results identify a critical role for BRD4-bound super-enhancers in senescence immune surveillance and in the proper execution of a tumor-suppressive program. Significance: This study reveals how cells undergoing oncogene-induced senescence acquire a distinctive enhancer landscape that includes formation of super-enhancers adjacent to immune-modulatory genes required for paracrine immune activation. This process links BRD4 and super-enhancers to a tumor-suppressive immune surveillance program that can be disrupted by small molecule inhibitors of the bromo and extra terminal domain family of proteins. Cancer Discov; 6(6); 612–29. ©2016 AACR. See related commentary by Vizioli and Adams, p. 576. This article is highlighted in the In This Issue feature, p. 561

Pancreatic ductal adenocarcinoma (PDAC) is one of the most devastating and painful cancers. It is often highly resistant to therapy owing to inherent chemoresistance and the desmoplastic response that creates a barrier of fibrous tissue preventing transport of chemotherapeutics into the tumor. The growth of the tumor in pancreatic cancer often leads to invasion of other organs and partial or complete biliary obstruction, inducing intense pain for patients and necessitating tumor resection or repeated stenting. Here, we have developed a delivery device to provide enhanced palliative therapy for pancreatic cancer patients by providing high concentrations of chemotherapeutic compounds locally at the tumor site. This treatment could reduce the need for repeated procedures in advanced PDAC patients to debulk the tumor mass or stent the obstructed bile duct. To facilitate clinical translation, we created the device out of currently approved materials and drugs. We engineered an implantable poly(lactic-co-glycolic)-based biodegradable device that is able to linearly release high doses of chemotherapeutic drugs for up to 60 days. We created five patient-derived PDAC cell lines and tested their sensitivity to approved chemotherapeutic compounds. These in vitro experiments showed that paclitaxel was the most effective single agent across all cell lines. We compared the efficacy of systemic and local paclitaxel therapy on the patient-derived cell lines in an orthotopic xenograft model in mice (PDX). In this model, we found up to a 12-fold increase in suppression of tumor growth by local therapy in comparison to systemic administration and reduce retention into off-target organs. Herein, we highlight the efficacy of a local therapeutic approach to overcome PDAC chemoresistance and reduce the need for repeated interventions and biliary obstruction by preventing local tumor growth. Our results underscore the urgent need for an implantable drug-eluting platform to deliver cytotoxic agents directly within the tumor mass as a novel therapeutic strategy for patients with pancreatic cancer. Keywords: Pancreatic cancer; Chemoresistance; Local delivery; Patient-derived xenograft; Paclitaxel; Poly(lactic-co-glycolic acid), National Institutes of Health (U.S.) (Grant P30-CA14051)

The lack of consensus on clinically relevant molecular subtypes by gene expression in high-grade serous ovarian carcinoma (HGSOC) creates a barrier to subtype-based clinical investigation for the development of targeted therapies. We previously discovered aberrant expression of noncoding repeat RNAs across epithelial cancers including ovarian (Ting, Science 2011), which can invoke innate immune responses in tumors (Chiappinelli, Cell 2015). Epigenetic alterations and loss of tumor suppressor function, especially p53, can derepress endogenous repetitive elements in cancer. Further, BRCA1 deficiency induces satellite repeat RNAs, which promote genomic instability via interacting with the BRCA1 complex (Zhu, Mol Cell 2018), highlighting their potential significance in HGSOC. Here we aim to comprehensively define the as yet uncharacterized “repeatome” in HGSOC to refine molecular subtypes and identify novel biomarkers and therapeutic targets. We developed a Total RNASeq platform and novel computational pipelines to quantify the repeatome (Solovyov, Cell Rep 2018). Results from RNASeq are validated in cell lines and human tumors with RNA in situ hybridization (RNA-ISH) using probes to specific repeat RNAs, and combined IHC is performed to quantify intratumoral immune subpopulations. Whole-exome sequencing is performed to link the repeatome with somatic mutations. To obtain a global landscape of the ovarian cancer repeatome, Total RNASeq was performed on 32 patient-derived ovarian cancer cell lines, 11 HGSOC PDX, and 11 additional ovarian cancer cell lines. We detect abundant repeat RNA expression from all major subclasses including retrotransposons, endogenous retroviruses, and satellites. HGSOC are enriched for satellite repeats compared with other cancers, most notably in BRCA-mutant HGSOC. Human satellite II (HSATII), a cancer-specific satellite, is strongly upregulated in HGSOC compared with fallopian tube epithelial cells and displays highly variable expression across different models. RNA-ISH for HSATII on human ovarian cancer tissue microarrays confirms the abundance and variation of HSATII. Additionally, the repeatome is altered in HGSOC following exposure to in vitro chemotherapy and epigenetic agents with distinct patterns of expression linked to specific agents. Additional RNAseq analysis using hierarchical clustering and principal component analysis are being used to understand the relationship of repeatome expression patterns with coding gene expression, somatic mutations, in vitro drug sensitivity, and clinical outcomes. Digital image analysis of repeat RNA-ISH expression and immune cell infiltrate quantitation will determine the link between tumor cell repeat RNA levels and the responding immune tumor microenvironment. Overall, these studies will define the undiscovered repeatome in HGSOC and provide a foundation for discovery of novel biomarkers and potential therapeutic strategies, particularly those to increase efficacy of immunotherapies. Citation Format: Rebecca L. Porter, Anna Szabolcs, Niyati Desai, Vishal Thapar, Raghav Mohan, Alexander Solovyov, David Pepin, Joyce Liu, Benjamin Greenbaum, David T. Ting. Repeatome profiling in high-grade serous ovarian cancer reveals abundant repeat noncoding RNA expression [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A66.

149 Background: Non-coding repeat RNAs in cancers are pervasive and “mimic” viruses with activation of pattern recognition receptors and the innate immune response. Many repeat RNAs replicate in cancer genomes through a reverse transcriptional intermediate analogous to retroviruses. Nucleoside reverse transcriptase inhibitors (NRTIs) block this retroviral life cycle to increases repeat RNAs in p53 mutant colon cancer cell cancer lines. We initiated a Phase 2 study of lamivudine (3TC) in TP53 mutant mCRC. Methods: Two-stage design with target accrual of 20 patients (pts) in stage 1 and total of 32. Eligibility: pts with p53 mutant refractory mCRC with progression on or intolerance to 5FU, oxaliplatin and irinotecan and anti-EGFR if RAS WT. RNA sequencing was performed on pre-treatment (tx) and on tx biopsy to evaluate for repeat RNA expression and expression of other genes linked to 3TC response/resistance. Radiation was allowed. 9 pts were treated with 3TC 150 mg po bid for 28-day cycles, the maximum FDA approved dose of 3TC in HIV. Subsequent pts were treated at 600 mg po bid, previously tested in P1 trials. Tumor assessments were performed every 8 weeks until documented disease progression by RECIST 1.1 criteria or drug intolerance. Results: 29/32 pts have been treated. Median age: 60 yrs. (27-82) 18 males, 11 females. 2/ 9 (22%) pts on standard 3TC dosing had stable disease (SD) on single agent 3TC with a duration of tx of 169 and 167 days, respectively. Both pts had an initial drop in CEA upon initiation of 3TC. Of the next 20 pts on high dose 3TC, 19 were evaluable. 4 had SD, for 110, 159, 130 and 228+ days. 14 pts had tx-related adverse events (TRAE). 1 pt with a definite Grade 1 TRAE (fatigue). No pts with Grade ≥3 TRAEs. We obtained pre-tx fresh frozen biopsies on 24/29 pts. Of those with SD, 4 had biopsies and differential expression identified significantly higher HSATII repeat RNA in pts with SD compared to PD. There was an association of decreased epigenetic gene expression in HSATII repeat RNA high tumors. Conclusions: This proof-of-concept study demonstrates the safety and activity of single-agent 3TC. Repeat RNA levels appear to correlate with clinical benefit and can be measured in biopsies. Further combination studies and correlatives are planned. Clinical trial information: NCT03144804.

Significance PDAC epithelial (E) and quasi-mesenchymal (QM) subtypes can be modulated by different therapies demonstrating the plasticity of PDAC cells that contributes to the heterogeneity of PDAC tumors and their intrinsic resistance to a broad spectrum of therapies. Understanding and monitoring the fluidity of PDAC E and QM states are critical to the development of improved clinical trial design to target these different subpopulations., Transcriptional profiling has defined pancreatic ductal adenocarcinoma (PDAC) into distinct subtypes with the majority being classical epithelial (E) or quasi-mesenchymal (QM). Despite clear differences in clinical behavior, growing evidence indicates these subtypes exist on a continuum with features of both subtypes present and suggestive of interconverting cell states. Here, we investigated the impact of different therapies being evaluated in PDAC on the phenotypic spectrum of the E/QM state. We demonstrate using RNA-sequencing and RNA-in situ hybridization (RNA-ISH) that FOLFIRINOX combination chemotherapy induces a common shift of both E and QM PDAC toward a more QM state in cell lines and patient tumors. In contrast, Vitamin D, another drug under clinical investigation in PDAC, induces distinct transcriptional responses in each PDAC subtype, with augmentation of the baseline E and QM state. Importantly, this translates to functional changes that increase metastatic propensity in QM PDAC, but decrease dissemination in E PDAC in vivo models. These data exemplify the importance of both the initial E/QM subtype and the plasticity of E/QM states in PDAC in influencing response to therapy, which highlights their relevance in guiding clinical trials.

Single cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single cell phenotypes have not been well defined. Combining single cell RNA and protein analytics in pancreatic cancer (PDAC) model systems, we demonstrated the role of stromal fibroblasts in shaping PDAC single cell heterogeneity towards invasive (EMT) and proliferative (PRO) phenotypes. Using highcontent digital imaging of RNA in situ hybridization in 195 tumors, we observed these EMT and PRO subpopulations in 319,626 individual cancer cells. Interestingly, we found these EMT and PRO subpopulations form distinct tumor gland “units” associated with differences in stromal abundance and patient survival. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.

Extracellular vesicles (EVs) carry RNA, DNA, proteins, and lipids. Specifically, tumor-derived EVs have the potential to be utilized as disease-specific biomarkers. However, a lack of methods to isolate tumor-specific EVs has limited their use in clinical settings. Here we report a sensitive analytical microfluidic platform (EVHB-Chip) that enables tumor-specific EV-RNA isolation within 3 h. Using the EVHB-Chip, we achieve 94% tumor-EV specificity, a limit of detection of 100 EVs per μL, and a 10-fold increase in tumor RNA enrichment in comparison to other methods. Our approach allows for the subsequent release of captured tumor EVs, enabling downstream characterization and functional studies. Processing serum and plasma samples from glioblastoma multiforme (GBM) patients, we can detect the mutant EGFRvIII mRNA. Moreover, using next-generation RNA sequencing, we identify genes specific to GBM as well as transcripts that are hallmarks for the four genetic subtypes of the disease., Extracellular vesicles can carry many different types of biological cargo and have been investigated as a biomarker for cancer diagnosis. Here the authors develop a microfluidic platform for rapid and sensitive isolation of tumor-specific extracellular vesicles.

CRISPR RNA-guided nucleases (RGNs) are widely used genome-editing reagents, but methods to delineate their genome-wide, off-target cleavage activities have been lacking. Here we describe an approach for global detection of DNA double-stranded breaks (DSBs) introduced by RGNs and potentially other nucleases. This method, called genome-wide, unbiased identification of DSBs enabled by sequencing (GUIDE-seq), relies on capture of double-stranded oligodeoxynucleotides into DSBs. Application of GUIDE-seq to 13 RGNs in two human cell lines revealed wide variability in RGN off-target activities and unappreciated characteristics of off-target sequences. The majority of identified sites were not detected by existing computational methods or chromatin immunoprecipitation sequencing (ChIP-seq). GUIDE-seq also identified RGN-independent genomic breakpoint 'hotspots'. Finally, GUIDE-seq revealed that truncated guide RNAs exhibit substantially reduced RGN-induced, off-target DSBs. Our experiments define the most rigorous framework for genome-wide identification of RGN off-target effects to date and provide a method for evaluating the safety of these nucleases before clinical use.

Monomeric CRISPR-Cas9 nucleases are widely used for targeted genome editing but can induce unwanted off-target mutations with high frequencies. Here we describe dimeric RNA-guided FokI Nucleases (RFNs) that recognize extended sequences and can edit endogenous genes with high efficiencies in human cells. The cleavage activity of an RFN depends strictly on the binding of two guide RNAs (gRNAs) to DNA with a defined spacing and orientation and therefore show improved specificities relative to wild-type Cas9 monomers. Importantly, direct comparisons show that RFNs guided by a single gRNA generally induce lower levels of unwanted mutations than matched monomeric Cas9 nickases. In addition, we describe a simple method for expressing multiple gRNAs bearing any 5′ end nucleotide, which gives dimeric RFNs a broad targeting range. RFNs combine the ease of RNA-based targeting with the specificity enhancement inherent to dimerization and are likely to be useful in applications that require highly precise genome editing.

All translated proteins end with a carboxylic acid commonly called the C-terminus. Many short functional sequences (minimotifs) are located on or immediately proximal to the C-terminus. However, information about the function of protein C-termini has not been consolidated into a single source. Here, we built a new "C-terminome" database and web system focused on human proteins. Approximately 3,600 C-termini in the human proteome have a minimotif with an established molecular function. To help evaluate the function of the remaining C-termini in the human proteome, we inferred minimotifs identified by experimentation in rodent cells, predicted minimotifs based upon consensus sequence matches, and predicted novel highly repetitive sequences in C-termini. Predictions can be ranked by enrichment scores or Gene Evolutionary Rate Profiling (GERP) scores, a measurement of evolutionary constraint. By searching for new anchored sequences on the last 10 amino acids of proteins in the human proteome with lengths between 3-10 residues and up to 5 degenerate positions in the consensus sequences, we have identified new consensus sequences that predict instances in the majority of human genes. All of this information is consolidated into a database that can be accessed through a C-terminome web system with search and browse functions for minimotifs and human proteins. A known consensus sequence-based predicted function is assigned to nearly half the proteins in the human proteome. Weblink: http://cterminome.bio-toolkit.com.

Multiple sequence alignment (MSA) is a vital problem in biology. Optimal alignment of multiple sequences becomes impractical even for a modest number of sequences since the general version of the problem is NP-hard. Because of the high time complexity of traditional MSA algorithms, even today's fast computers are not able to solve the problem for large number of sequences. In this paper we present a randomized algorithm to calculate distance matrices, which is a major step in many multiple sequence alignment algorithms. The basic idea employed is sampling (along the lines of). We also illustrate how to parallelize this algorithm. In Section we introduce the problem of multiple sequence alignments. In Section we provide a discussion on various methods that have been employed in the literature for Multiple Sequence Alignment. In this section we also introduce our new sampling approach. We extend our randomized algorithm to the case of non-uniform length sequences as well. We show that our algorithms are amenable to parallelism in Section. In Section we back up our claim of speedup and accuracy with empirical data and examples. In Section we provide some concluding remarks.

Objective. The human genome project has resulted in the generation of voluminous biological data. Novel computational techniques are called for to extract useful information from this data. One such technique is that of finding patterns that are repeated over many sequences (and possibly over many species). In this paper we study the problem of identifying meaningful patterns (i.e., motifs) from biological data, the motif search problem. Methods. The general version of the motif search problem is NP-hard. Numerous algorithms have been proposed in the literature to solve this problem. Many of these algorithms fall under the category of heuristics. We concentrate on exact algorithms in this paper. In particular, we concentrate on two different versions of the motif search problem and offer exact algorithms for them. Results. In this paper we present algorithms for two versions of the motif search problem. All of our algorithms are elegant and use only such simple data structures as arrays. For the first version of the problem described as Problem 1 in the paper, we present a simple sorting based algorithm, SMS (Simple Motif Search). This algorithm has been coded and experimental results have been obtained. For the second version of the problem (described in the paper as Problem 2), we present two different algorithms – a deterministic algorithm (called DMS) and a randomized algorithm (Monte Carlo algorithm). We also show how these algorithms can be parallelized.Conclusions. All the algorithms proposed in this paper are improvements over existing algorithms for these versions of motif search in biological sequence data. The algorithms presented have the potential of performing well in practice.

SummaryThe aberrant transcription factor EWS-FLI1 drives Ewing sarcoma, but its molecular function is not completely understood. We find that EWS-FLI1 reprograms gene regulatory circuits in Ewing sarcoma by directly inducing or repressing enhancers. At GGAA repeat elements, which lack evolutionary conservation and regulatory potential in other cell types, EWS-FLI1 multimers induce chromatin opening and create de novo enhancers that physically interact with target promoters. Conversely, EWS-FLI1 inactivates conserved enhancers containing canonical ETS motifs by displacing wild-type ETS transcription factors. These divergent chromatin-remodeling patterns repress tumor suppressors and mesenchymal lineage regulators while activating oncogenes and potential therapeutic targets, such as the kinase VRK1. Our findings demonstrate how EWS-FLI1 establishes an oncogenic regulatory program governing both tumor survival and differentiation.

In addition to large domains, many short motifs mediate functional post-translational modification of proteins as well as protein-protein interactions and protein trafficking functions. We have constructed a motif database comprising 312 unique motifs and a web-based tool for identifying motifs in proteins. Functional motifs predicted by MnM can be ranked by several approaches, and we validated these scores by analyzing thousands of confirmed examples and by confirming prediction of previously unidentified 14-3-3 motifs in EFF-1.

SummaryThe p53 tumor suppressor can restrict malignant transformation by triggering cell-autonomous programs of cell-cycle arrest or apoptosis. p53 also promotes cellular senescence, a tumor-suppressive program that involves stable cell-cycle arrest and secretion of factors that modify the tissue microenvironment. In the presence of chronic liver damage, we show that ablation of a p53-dependent senescence program in hepatic stellate cells increases liver fibrosis and cirrhosis associated with reduced survival and enhances the transformation of adjacent epithelial cells into hepatocellular carcinoma. p53-expressing senescent stellate cells release factors that skew macrophage polarization toward a tumor-inhibiting M1-state capable of attacking senescent cells in culture, whereas proliferating p53-deficient stellate cells secrete factors that stimulate polarization of macrophages into a tumor-promoting M2-state and enhance the proliferation of premalignant cells. Hence, p53 can act non-cell autonomously to suppress tumorigenesis by promoting an antitumor microenvironment, in part, through secreted factors that modulate macrophage function.

The problem of sorting has been studied extensively and many algorithms have been suggested in the literature for the problem. Literature on parallel sorting is abundant. Many of the algorithms proposed, though being theoretically important, may not perform satisfactorily in practice owing to large constants in their time bounds. The algorithms presented in this paper have the potential of being practical. We suggest some novel sorting mechanisms specific to the cell broadband engine. We try to utilize the specifics of its architecture in order to get the optimum performance. As part of our comparative analysis we juxtapose these algorithms with similar ones implemented on Itanium 2 processor as well as the Pentium 4 processor.

The problem of multiple sequence alignment (MSA) in biology has been studied extensively. In this paper we offer sampling based algorithms for MSA that are more accurate than existing algorithms. The performance of our algorithms has been evaluated using the standard BaliBase dataset [10]. We are able to improve the average alignment SP score for ClustalW [9] and MAFFT [6] by 16.39% and 12.2 %, respectively and the TC score by 55.4% and 46.9%, respectively using sampling. Given that ClustalW and MAFFT are some of the most accurate algorithms for MSA currently and are widely used, our algorithms would be of interest to biologists.

Pancreatic adenocarcinoma (PDAC) is a lethal disease with a rising incidence, expected to become the second cause of cancer death in the next 5 years. Despite advances in novel therapies for other malignancies, PDAC has remained a highly chemorefractory disease leading to inevitable disease recurrence in the vast majority of patients. The identification of the cellular mechanisms of chemoresistance unique to PDAC is of particular importance. Our prior work using single cell RNA-sequencing in pancreatic circulating tumor cells (CTCs) identified 878 genes enriched in CTCs compared to matched primary tumor cells. CTCs are thought to be enriched for cells with high metastatic potential, which we predict to have intrinsic chemoresistant behavior. We hypothesized that CTC enriched genes may identify a subpopulation of cells resistant to chemotherapy that could be used as a biomarker and novel therapeutic target. The neuroendocrine marker SV2 was found in both mouse and human pancreatic CTCs and was selected given its presence on cell membranes, providing a potential therapeutic target. We evaluated a panel of patient derived cell lines and identified an SV2 positive subpopulation comprising ∼1% of cells in 3 of 5 cell lines. Notably, only differentiated epithelioid PDAC cell lines contained an SV2 subpopulation, while this population is not present in poorly differentiated quasi-mesenchymal cell lines. We performed RNA-ISH for SV2 isoforms in an annotated PDAC tissue microarray demonstrating positive staining in 77% of samples (245/317). Interestingly, SV2 positivity was often focally positive in a subpopulation of cells at the basolateral region of ductal adenocarcinoma and was found in more differentiated morphology (69% well/moderate vs 31% poor/undifferentiated; p = 0.047). The presence of SV2 cells was associated with an improved disease free survival (HR: 0.49 p = 0.009) and overall survival (HR: 0.54 p = 0.018) even after correction in multivariate analysis. Analysis in both cell lines and tissue revealed SV2 positive cells were also found to have higher levels of the ALDH1 stem cell marker (Pearson coefficient = 0.92 in tissue). Initial in vivo treatment of human orthotopic xenografts with gemcitabine, reveal an enrichment of SV2 positive cells pointing to their potential role as the recalcitrant cancer cells treated with cytotoxic chemotherapy population. Together, this is consistent with prior work demonstrating classical epithelial PDAC has improved survival compared to quasi-mesenchymal tumors. However, almost all patients with classical epithelial PDAC will die from recurrent disease, and we have now shown SV2 as a potential marker that identifies the chemoresistant pancreatic cancer cells in this patient population. Ultimately, a more detailed characterization of the SV2 subpopulation in classical PDAC will help us develop novel targeted therapies to overcome chemoresistance. Citation Format: Daniela Dias-Santos, Matteo Ligorio, Kshitij Arora, Vishal Thapar, Olivia C. MacKenzie, Srinjoy Sil, Niyati Desai, Vikram Deshpande, Miguel N. Rivera, Cristina R. Ferrone, David T. Ting. Molecular subtyping of pancreatic adenocarcinoma identifies SV2 positive subpopulation in classical PDAC. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 609. doi:10.1158/1538-7445.AM2015-609

Clustered regularly interspaced short palindromic repeat (CRISPR)-CRISPR-associated (Cas) RNA-guided nucleases (RGNs) have been broadly adopted by the scientific community for use as robust genome editing tools. However, CRISPR-Cas RGNs have been demonstrated to exhibit high-frequency off-targets at sites with up to 5 mismatches from the intended target site, raising questions about their global specificity. We have developed a novel method called GUIDE-seq (for Genome-wide Unbiased Identification of DSBs enabled by Sequencing), based on the efficient integration of a double-stranded oligodeoxynucleotide (dsODN) tag followed by tag-specific amplification and high-throughput sequencing. We performed GUIDE-seq on 10 RGNs in 2 human cell lines and identified all known off-target cleavage sites of these RGNs as well as hundreds of additional novel sites. The number of off-target cleavage sites identified varied widely among these RGNs, and the majority of identified sites were not predicted by existing computational methods or ChIP-seq. GUIDE-seq provides a robust method for evaluating the genome-wide specificities of RGNs that will be useful for the clinical translation of these important and widely applicable genome editing reagents.

Text summarization is an important problem, which has numerous applications. This problem has been extensively studied and many approaches have been proposed in the literature for its solution. In this paper, we investigate a new approach that employs meta-search. In particular, summaries from several summarizers are evaluated and a new summary is formed from these summaries. Clearly, this meta-summarizer will produce a better summary than any of the others since it exploits the special features of all the sources. We have employed data from Document Understanding Conference 2002 (DUC-2002) and 5 different summarizers in our experiments. We have also created our own summarizer.

EZH2 is the catalytic component of the polycomb repressive complex 2 (PRC2), which also contains the non-catalytic subunits suppressor of zeste 12 (SUZ12) and embryonic ectoderm development (EED). This complex methylates histone H3 at lysine 27 (H3K27) which, together with H3K4 methylation, generates a bivalent “code” that primes genes for either expression or silencing. EZH2 is highly expressed in stem cells and many proliferating cells, downregulated in differentiated cells and frequently altered in cancer in ways that point to a context dependent role for this gene. For instance, overexpression of EZH2 has been described in prostate and breast cancer, where this overexpression is associated with invasive growth metastatic potential and poor clinical outcome. More recently, both gain and loss of function mutations of EZH2 were identified in human cancer. In particular, activating mutations of EZH2 affecting a tyrosine at position 641 located within the SET domain (Y641) were observed in lymphoma. In striking contrast to wild type EZH2 which catalyzes the monomethylation of H3K27 very efficiently and shows less efficient catalytic activity in the subsequent di- and trimethylation reactions, the mutation generates a neomorphic protein with enhanced catalytic activity and efficiency for di- and tri-methylation, hinting toward a “cooperation” of both wild type and mutant EZH2 to increase total H3K27me3 levels and representing a functional equivalent of EZH2 overexpression in human lymphoma. Gain of function mutations in EZH2 are frequent in Diffuse Large B-cell Lymphoma (DLBCL; 22%) and in Follicular Lymphoma (FL; 7%) and recent data implicate EZH2 as an oncogene in DLBCL and FL lymphomas. In contrast to DLBCL and FL, EZH2 mutations have so far never been identified in MYC-driven B-cell Non-Hodgkin Lymphoma (B-NHL), and EZH2 expression is suppressed in Burkitt’s Lymphoma (BL), a lymphoma for which a MYC translocation is pathognomonic, suggesting that in this context EZH2 could have a role different from its role in DLBCL and FL. We probed the role of EZH2 in MYC-driven lymphomagenesis by mimicking the loss of function mutations by RNAi mediated suppression of EZH2 and the gain of function mutations by over-expression of the Y641 mutant. Our results show that suppression of EZH2, but not overexpression of the EZH2 Y641 mutant, accelerates MYC-driven lymphomagenesis by attenuating apoptosis. Our model recapitulates the transcriptional signature of a subset of B-NHLs driven by MYC overactivation and EZH2 suppression. Taken together, our data imply EZH2 as a tumor suppressor in the context of MYC activation and thus raise a warning for the use of EZH2-targeted therapies in some B-NHLs subtypes. Disclosures No relevant conflicts of interest to declare.

In this paper we study the problem of identifying meaningful patterns (i.e., motifs) from biological data. The general version of this problem is NP-hard. Numerous algorithms have been proposed in the literature to solve this problem. Many of these algorithms fall under the category of approximation algorithms. We concentrate on exact algorithms in this paper. In particular, we concentrate on two different versions of the motif search problem and offer exact algorithms for two of them. The proposed algorithms perform better than some of the bestknown algorithms. * This research was supported in part by the NSF Grants CCR-9912395 and ITR0326155.