Aging induces changes in cancer formation and microbial content in a murine model of bladder cancer.

Bladder cancer (BCa) incidence is tightly linked to aging. Older patients with BCa present with higher grade tumors and have worse outcomes on Bacillus-Calmette-Guerin (BCG) immunotherapy. Aging is also known to result in changes in the gut microbiome over mammalian lifespan, with recent studies linking alterations in the gut microbiome to changes in tumor immunity. There is limited information on the microbiome in BCa models though, despite known links to aging and immunotherapy. The purpose of this study was to evaluate how aging impacts tumor formation, inflammation, and the microbiome of mice given the model BCa carcinogen N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN). We hypothesized old animals would have larger, more inflamed tumors and a shift in their fecal microbiome compared to their younger counterparts. Young (~8-week-old) or old (~78-week-old) C57Bl/6J animals were administered 0.05% BBN in drinking water for 16 weeks and then euthanized or allowed to progress for an additional 4 weeks. After 16 weeks of BBN, old mice had higher bladder to body weight ratio than young mice, and also muscle invasive tumors, which were not seen in their young counterparts. Old animals also had increased innate immune recruitment, but CD4+/CD8+ T cell recruitment did not appear different. BBN dramatically altered the microbiome in both sets of animals as measured by ß-diversity, including changes in multiple genera of bacteria. These data suggest old mice have a differential response to BBN-induced BCa. Given the median age of patients with BCa, understanding how the aged phenotype interacts with BCa is imperative.

Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors.

Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed a computer-assisted approach to resistance gene-guided genome mining that allows users to query large databases for BGCs that putatively make compounds that have targets of therapeutic interest. Working with the MycoCosm genome database, we have applied this approach to look for SM BGCs that target the proteasome ß6 subunit, the target of the proteasome inhibitor fellutamide B, or HMG-CoA reductase, the target of cholesterol reducing therapeutics such as lovastatin. Our approach proved effective, finding known fellutamide and lovastatin BGCs as well as fellutamide- and lovastatin-related BGCs with variations in the SM genes that suggest they may produce structural variants of fellutamides and lovastatin. Gratifyingly, we also found BGCs that are not closely related to lovastatin BGCs but putatively produce novel HMG-CoA reductase inhibitors. ONE-SENTENCE SUMMARY: A new computer-assisted approach to resistance gene-directed genome mining is reported along with its use to identify fungal biosynthetic gene clusters that putatively produce proteasome and HMG-CoA reductase inhibitors.

Functional inhibition of the RNA-binding protein HuR sensitizes triple-negative breast cancer to chemotherapy.

Chemotherapy remains the standard treatment for triple-negative breast cancer (TNBC); however, chemoresistance compromises its efficacy. The RNA-binding protein Hu antigen R (HuR) could be a potential therapeutic target to enhance the chemotherapy efficacy. HuR is known to mainly stabilize its target mRNAs, and/or promote the translation of encoded proteins, which are implicated in multiple cancer hallmarks, including chemoresistance. In this study, a docetaxel-resistant cell subline (231-TR) was established from the human TNBC cell line MDA-MB-231. Both the parental and resistant cell lines exhibited similar sensitivity to the small molecule functional inhibitor of HuR, KH-3. Docetaxel and KH-3 combination therapy synergistically inhibited cell proliferation in TNBC cells and tumor growth in three animal models. KH-3 downregulated the expression levels of HuR targets (e.g., ß-Catenin and BCL2) in a time- and dose-dependent manner. Moreover, KH-3 restored docetaxel's effects on activating Caspase-3 and cleaving PARP in 231-TR cells, induced apoptotic cell death, and caused S-phase cell cycle arrest. Together, our findings suggest that HuR is a critical mediator of docetaxel resistance and provide a rationale for combining HuR inhibitors and chemotherapeutic agents to enhance chemotherapy efficacy.

Exploring Gut Microbiome in Predicting the Efficacy of Immunotherapy in Non-Small Cell Lung Cancer.

We performed various analyses on the taxonomic and functional features of the gut microbiome from NSCLC patients treated with immunotherapy to establish a model that may predict whether a patient will benefit from immunotherapy. We collected 65 published whole metagenome shotgun sequencing samples along with 14 samples from our previous study. We systematically studied the taxonomical characteristics of the dataset and used both the random forest (RF) and the multilayer perceptron (MLP) neural network models to predict patients with progression-free survival (PFS) above 6 months versus those below 3 months. Our results showed that the RF classifier achieved the highest F-score (85.2%) and the area under the receiver operating characteristic curve (AUC) (95%) using the protein families (Pfam) profile, and the MLP neural network classifier achieved a 99.9% F-score and 100% AUC using the same Pfam profile. When applying the model trained in the Pfam profile directly to predict the treatment response, we found that both trained RF and MLP classifiers significantly outperformed the stochastic predictor in F-score. Our results suggested that such a predictive model based on functional (e.g., Pfam) rather than taxonomic profile might be clinically useful to predict whether an NSCLC patient will benefit from immunotherapy, as both the F-score and AUC of functional profile outperform that of taxonomic profile. In addition, our model suggested that interactive biological processes such as methanogenesis, one-carbon, and amino acid metabolism might be important in regulating the immunotherapy response that warrants further investigation.

Nano pom-poms prepared exosomes enable highly specific cancer biomarker detection.

Extracellular vesicles (EVs), particularly nano-sized small EV exosomes, are emerging biomarker sources. However, due to heterogeneous populations secreted from diverse cell types, mapping exosome multi-omic molecular information specifically to their pathogenesis origin for cancer biomarker identification is still extraordinarily challenging. Herein, we introduced a novel 3D-structured nanographene immunomagnetic particles (NanoPoms) with unique flower pom-poms morphology and photo-click chemistry for specific marker-defined capture and release of intact exosome. This specific exosome isolation approach leads to the expanded identification of targetable cancer biomarkers with enhanced specificity and sensitivity, as demonstrated by multi-omic exosome analysis of bladder cancer patient tissue fluids using the next generation sequencing of somatic DNA mutations, miRNAs, and the global proteome (Data are available via ProteomeXchange with identifier PXD034454). The NanoPoms prepared exosomes also exhibit distinctive in vivo biodistribution patterns, highlighting the highly viable and integral quality. The developed method is simple and straightforward, which is applicable to nearly all types of biological fluids and amenable for enrichment, scale up, and high-throughput exosome isolation.

Evaluation of the Durability of the Immune Humoral Response to COVID-19 Vaccines in Patients With Cancer Undergoing Treatment or Who Received a Stem Cell Transplant.

Importance: The durability of the antibody response to COVID-19 vaccines in patients with cancer undergoing treatment or who received a stem cell transplant is unknown and may be associated with infection outcomes. Objective: To evaluate anti-SARS-CoV-2 spike protein receptor binding domain (anti-RBD) and neutralizing antibody (nAb) responses to COVID-19 vaccines longitudinally over 6 months in patients with cancer undergoing treatment or who received a stem cell transplant (SCT). Design, Setting, and Participants: In this prospective, observational, longitudinal cross-sectional study of 453 patients with cancer undergoing treatment or who received an SCT at the University of Kansas Cancer Center in Kansas City, blood samples were obtained before 433 patients received a messenger RNA (mRNA) vaccine (BNT162b2 or mRNA-1273), after the first dose of the mRNA vaccine, and 1 month, 3 months, and 6 months after the second dose. Blood samples were also obtained 2, 4, and 7 months after 17 patients received the JNJ-78436735 vaccine. For patients receiving a third dose of an mRNA vaccine, blood samples were obtained 30 days after the third dose. Interventions: Blood samples and BNT162b2, mRNA-1273, or JNJ-78436735 vaccines. Main Outcomes and Measures: Geometric mean titers (GMTs) of the anti-RBD; the ratio of GMTs for analysis of demographic, disease, and treatment variables; the percentage of neutralization of anti-RBD antibodies; and the correlation between anti-RBD and nAb responses to the COVID-19 vaccines. Results: This study enrolled 453 patients (mean [SD] age, 60.4 [13,1] years; 253 [56%] were female). Of 450 patients, 273 (61%) received the BNT162b2 vaccine (Pfizer), 160 (36%) received the mRNA-1273 vaccine (Moderna), and 17 (4%) received the JNJ-7846735 vaccine (Johnson & Johnson). The GMTs of the anti-RBD for all patients were 1.70 (95% CI, 1.04-2.85) before vaccination, 18.65 (95% CI, 10.19-34.11) after the first dose, 470.38 (95% CI, 322.07-686.99) at 1 month after the second dose, 425.80 (95% CI, 322.24-562.64) at 3 months after the second dose, 447.23 (95% CI, 258.53-773.66) at 6 months after the second dose, and 9224.85 (95% CI, 2423.92-35107.55) after the third dose. The rate of threshold neutralization (≥30%) was observed in 203 of 252 patients (80%) 1 month after the second dose and in 135 of 166 patients (81%) 3 months after the second dose. Anti-RBD and nAb were highly correlated (Spearman correlation coefficient, 0.93 [0.92-0.94]; P < .001). Three months after the second dose, anti-RBD titers were lower in male vs female patients (ratio of GMTs, 0.52 [95% CI, 0.34-0.81]), patients older than 65 years vs patients 50 years or younger (ratio of GMTs, 0.38 [95% CI, 0.25-0.57]), and patients with hematologic malignant tumors vs solid tumors (ratio of GMTs, 0.40 [95% CI, 0.20-0.81]). Conclusions and Relevance: In this cross-sectional study, after 2 doses of an mRNA vaccine, anti-RBD titers peaked at 1 month and remained stable over the next 6 months. Patients older than 65 years of age, male patients, and patients with a hematologic malignant tumor had low antibody titers. Compared with the primary vaccine course, a 20-fold increase in titers from a third dose suggests a brisk B-cell anamnestic response in patients with cancer.

Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations.

Colorectal cancer (CRC) is one of the most common types of cancer with a high mortality rate. Colonoscopy is the preferred procedure for CRC screening and has proven to be effective in reducing CRC mortality. Thus, a reliable computer-aided polyp detection and classification system can significantly increase the effectiveness of colonoscopy. In this paper, we create an endoscopic dataset collected from various sources and annotate the ground truth of polyp location and classification results with the help of experienced gastroenterologists. The dataset can serve as a benchmark platform to train and evaluate the machine learning models for polyp classification. We have also compared the performance of eight state-of-the-art deep learning-based object detection models. The results demonstrate that deep CNN models are promising in CRC screening. This work can serve as a baseline for future research in polyp detection and classification.

Prospective correlation between the patient microbiome with response to and development of immune-mediated adverse effects to immunotherapy in lung cancer.

BACKGROUND: Though the gut microbiome has been associated with efficacy of immunotherapy (ICI) in certain cancers, similar findings have not been identified for microbiomes from other body sites and their correlation to treatment response and immune related adverse events (irAEs) in lung cancer (LC) patients receiving ICIs. METHODS: We designed a prospective cohort study conducted from 2018 to 2020 at a single-center academic institution to assess for correlations between the microbiome in various body sites with treatment response and development of irAEs in LC patients treated with ICIs. Patients must have had measurable disease, ECOG 0-2, and good organ function to be included. Data was collected for analysis from January 2019 to October 2020. Patients with histopathologically confirmed, advanced/metastatic LC planned to undergo immunotherapy-based treatment were enrolled between September 2018 and June 2019. Nasal, buccal and gut microbiome samples were obtained prior to initiation of immunotherapy +/- chemotherapy, at development of adverse events (irAEs), and at improvement of irAEs to grade 1 or less. RESULTS: Thirty-seven patients were enrolled, and 34 patients were evaluable for this report. 32 healthy controls (HC) from the same geographic region were included to compare baseline gut microbiota. Compared to HC, LC gut microbiota exhibited significantly lower α-diversity. The gut microbiome of patients who did not suffer irAEs were found to have relative enrichment of Bifidobacterium (p = 0.001) and Desulfovibrio (p = 0.0002). Responders to combined chemoimmunotherapy exhibited increased Clostridiales (p = 0.018) but reduced Rikenellaceae (p = 0.016). In responders to chemoimmunotherapy we also observed enrichment of Finegoldia in nasal microbiome, and increased Megasphaera but reduced Actinobacillus in buccal samples. Longitudinal samples exhibited a trend of α-diversity and certain microbial changes during the development and resolution of irAEs. CONCLUSIONS: This pilot study identifies significant differences in the gut microbiome between HC and LC patients, and their correlation to treatment response and irAEs in LC. In addition, it suggests potential predictive utility in nasal and buccal microbiomes, warranting further validation with a larger cohort and mechanistic dissection using preclinical models. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03688347 . Retrospectively registered 09/28/2018.

The long noncoding RNA lnc-HLX-2-7 is oncogenic in Group 3 medulloblastomas.

BACKGROUND: Medulloblastoma (MB) is an aggressive brain tumor that predominantly affects children. Recent high-throughput sequencing studies suggest that the noncoding RNA genome, in particular long noncoding RNAs (lncRNAs), contributes to MB subgrouping. Here we report the identification of a novel lncRNA, lnc-HLX-2-7, as a potential molecular marker and therapeutic target in Group 3 MBs. METHODS: Publicly available RNA sequencing (RNA-seq) data from 175 MB patients were interrogated to identify lncRNAs that differentiate between MB subgroups. After characterizing a subset of differentially expressed lncRNAs in vitro and in vivo, lnc-HLX-2-7 was deleted by CRISPR/Cas9 in the MB cell line. Intracranial injected tumors were further characterized by bulk and single-cell RNA-seq. RESULTS: Lnc-HLX-2-7 is highly upregulated in Group 3 MB cell lines, patient-derived xenografts, and primary MBs compared with other MB subgroups as assessed by quantitative real-time, RNA-seq, and RNA fluorescence in situ hybridization. Depletion of lnc-HLX-2-7 significantly reduced cell proliferation and 3D colony formation and induced apoptosis. Lnc-HLX-2-7-deleted cells injected into mouse cerebellums produced smaller tumors than those derived from parental cells. Pathway analysis revealed that lnc-HLX-2-7 modulated oxidative phosphorylation, mitochondrial dysfunction, and sirtuin signaling pathways. The MYC oncogene regulated lnc-HLX-2-7, and the small-molecule bromodomain and extraterminal domain family‒bromodomain 4 inhibitor Jun Qi 1 (JQ1) reduced lnc-HLX-2-7 expression. CONCLUSIONS: Lnc-HLX-2-7 is oncogenic in MB and represents a promising novel molecular marker and a potential therapeutic target in Group 3 MBs.

Relating Gut Microbiome and Its Modulating Factors to Immunotherapy in Solid Tumors: A Systematic Review.

Background: Gut microbiome is proved to affect the activity of immunotherapy in certain tumors. However, little is known if there is universal impact on both the treatment response and adverse effects (AEs) of immune checkpoint inhibitors (ICIs) across multiple solid tumors, and whether such impact can be modulated by common gut microbiome modifiers, such as antibiotics and diet. Methods: A systematic search in PubMed followed by stringent manual review were performed to identify clinical cohort studies that evaluated the relevance of gut microbiome to ICIs (response and/or AEs, 12 studies), or association of antibiotics with ICIs (17 studies), or impact of diet on gut microbiome (16 studies). Only original studies published in English before April 1st, 2020 were used. Qualified studies identified in the reference were also included. Results: At the phylum level, patients who had enriched abundance in Firmicutes and Verrucomicrobia almost universally had better response from ICIs, whereas those who were enriched in Proteobacteria universally presented with unfavorable outcome. Mixed correlations were observed for Bacteroidetes in relating to treatment response. Regarding the AEs, Firmicutes correlated to higher incidence whereas Bacteroidetes were clearly associated with less occurrence. Interestingly, across various solid tumors, majority of the studies suggested a negative association of antibiotic use with clinical response from ICIs, especially within 1-2 month prior to the initiation of ICIs. Finally, we observed a significant correlation of plant-based diet in relating to the enrichment of "ICI-favoring" gut microbiome (P = 0.0476). Conclusions: Gut microbiome may serve as a novel modifiable biomarker for both the treatment response and AEs of ICIs across various solid tumors. Further study is needed to understand the underlying mechanism, minimize the negative impact of antibiotics on ICIs, and gain insight regarding the role of diet so that this important lifestyle factor can be harnessed to improve the therapeutic outcomes of cancer immunotherapy partly through its impact on gut microbiome.

Targeting the interaction between RNA-binding protein HuR and FOXQ1 suppresses breast cancer invasion and metastasis.

Patients diagnosed with metastatic breast cancer have a dismal 5-year survival rate of only 24%. The RNA-binding protein Hu antigen R (HuR) is upregulated in breast cancer, and elevated cytoplasmic HuR correlates with high-grade tumors and poor clinical outcome of breast cancer. HuR promotes tumorigenesis by regulating numerous proto-oncogenes, growth factors, and cytokines that support major tumor hallmarks including invasion and metastasis. Here, we report a HuR inhibitor KH-3, which potently suppresses breast cancer cell growth and invasion. Furthermore, KH-3 inhibits breast cancer experimental lung metastasis, improves mouse survival, and reduces orthotopic tumor growth. Mechanistically, we identify FOXQ1 as a direct target of HuR. KH-3 disrupts HuR-FOXQ1 mRNA interaction, leading to inhibition of breast cancer invasion. Our study suggests that inhibiting HuR is a promising therapeutic strategy for lethal metastatic breast cancer.

3D cell culture stimulates the secretion of in vivo like extracellular vesicles.

For studying cellular communications ex-vivo, a two-dimensional (2D) cell culture model is currently used as the "gold standard". 2D culture models are also widely used in the study of RNA expression profiles from tumor cells secreted extracellular vesicles (EVs) for tumor biomarker discovery. Although the 2D culture system is simple and easily accessible, the culture environment is unable to represent in vivo extracellular matrix (ECM) microenvironment. Our study observed that 2D- culture derived EVs showed significantly different profiles in terms of secretion dynamics and essential signaling molecular contents (RNAs and DNAs), when compared to the three-dimensional (3D) culture derived EVs. By performing small RNA next-generation sequencing (NGS) analysis of cervical cancer cells and their EVs compared with cervical cancer patient plasma EV-derived small RNAs, we observed that 3D- culture derived EV small RNAs differ from their parent cell small RNA profile which may indicate a specific sorting process. Most importantly, the 3D- culture derived EV small RNA profile exhibited a much higher similarity (~96%) to in vivo circulating EVs derived from cervical cancer patient plasma. However, 2D- culture derived EV small RNA profile correlated better with only their parent cells cultured in 2D. On the other hand, DNA sequencing analysis suggests that culture and growth conditions do not affect the genomic information carried by EV secretion. This work also suggests that tackling EV molecular alterations secreted into interstitial fluids can provide an alternative, non-invasive approach for investigating 3D tissue behaviors at the molecular precision. This work could serve as a foundation for building precise models employed in mimicking in vivo tissue system with EVs as the molecular indicators or transporters. Such models could be used for investigating tumor biomarkers, drug screening, and understanding tumor progression and metastasis.

Hepatocyte nuclear receptor SHP suppresses inflammation and fibrosis in a mouse model of nonalcoholic steatohepatitis.

Nonalcoholic fatty liver disease (NAFLD) is a burgeoning health problem worldwide, ranging from nonalcoholic fatty liver (NAFL, steatosis without hepatocellular injury) to the more aggressive nonalcoholic steatohepatitis (NASH, steatosis with ballooning, inflammation, or fibrosis). Although many studies have greatly contributed to the elucidation of NAFLD pathogenesis, the disease progression from NAFL to NASH remains incompletely understood. Nuclear receptor small heterodimer partner (Nr0b2, SHP) is a transcriptional regulator critical for the regulation of bile acid, glucose, and lipid metabolism. Here, we show that SHP levels are decreased in the livers of patients with NASH and in diet-induced mouse NASH. Exposing primary mouse hepatocytes to palmitic acid and lipopolysaccharide in vitro, we demonstrated that the suppression of Shp expression in hepatocytes is due to c-Jun N-terminal kinase (JNK) activation, which stimulates c-Jun-mediated transcriptional repression of Shp Interestingly, in vivo induction of hepatocyte-specific SHP in steatotic mouse liver ameliorated NASH progression by attenuating liver inflammation and fibrosis, but not steatosis. Moreover, a key mechanism linking the anti-inflammatory role of hepatocyte-specific SHP expression to inflammation involved SHP-induced suppression of NF-κB p65-mediated induction of chemokine (C-C motif) ligand 2 (CCL2), which activates macrophage proinflammatory polarization and migration. In summary, our results indicate that a JNK/SHP/NF-κB/CCL2 regulatory network controls communications between hepatocytes and macrophages and contributes to the disease progression from NAFL to NASH. Our findings may benefit the development of new management or prevention strategies for NASH.

GRASPx: efficient homolog-search of short peptide metagenome database through simultaneous alignment and assembly.

BACKGROUND: Metagenomics is a cultivation-independent approach that enables the study of the genomic composition of microbes present in an environment. Metagenomic samples are routinely sequenced using next-generation sequencing technologies that generate short nucleotide reads. Proteins identified from these reads are mostly of partial length. On the other hand, de novo assembly of a large metagenomic dataset is computationally demanding and the assembled contigs are often fragmented, resulting in the identification of protein sequences that are also of partial length and incomplete. Annotation of an incomplete protein sequence often proceeds by identifying its homologs in a database of reference sequences. Identifying the homologs of incomplete sequences is a challenge and can result in substandard annotation of proteins from metagenomic datasets. To address this problem, we recently developed a homology detection algorithm named GRASP (Guided Reference-based Assembly of Short Peptides) that identifies the homologs of a given reference protein sequence in a database of short peptide metagenomic sequences. GRASP was developed to implement a simultaneous alignment and assembly algorithm for annotation of short peptides identified on metagenomic reads. The program achieves significantly improved recall rate at the cost of computational efficiency. In this article, we adopted three techniques to speed up the original version of GRASP, including the pre-construction of extension links, local assembly of individual seeds, and the implementation of query-level parallelism. RESULTS: The resulting new program, GRASPx, achieves >30X speedup compared to its predecessor GRASP. At the same time, we show that the performance of GRASPx is consistent with that of GRASP, and that both of them significantly outperform other popular homology-search tools including the BLAST and FASTA suites. GRASPx was also applied to a human saliva metagenome dataset and shows superior performance for both recall and precision rates. CONCLUSIONS: In this article we present GRASPx, a fast and accurate homology-search program implementing a simultaneous alignment and assembly framework. GRASPx can be used for more comprehensive and accurate annotation of short peptides. GRASPx is freely available at http://graspx.sourceforge.net/ .

SFA-SPA: a suffix array based short peptide assembler for metagenomic data.

UNLABELLED: The determination of protein sequences from a metagenomic dataset enables the study of metabolism and functional roles of the organisms that are present in the sampled microbial community. We had previously introduced algorithm and software for the accurate reconstruction of protein sequences from short peptides identified on nucleotide reads in a metagenomic dataset. Here, we present significant computational improvements to the short peptide assembly algorithm that make it practical to reconstruct proteins from large metagenomic datasets containing several hundred million reads, while maintaining accuracy. The improved computational efficiency is achieved using a suffix array data structure that allows for fast querying during the assembly process, and a significant redesign of assembly steps that enables multi-threaded execution. AVAILABILITY AND IMPLEMENTATION: The program is available under the GPLv3 license from sourceforge.net/projects/spa-assembler.

GRASP: guided reference-based assembly of short peptides.

Protein sequences predicted from metagenomic datasets are annotated by identifying their homologs via sequence comparisons with reference or curated proteins. However, a majority of metagenomic protein sequences are partial-length, arising as a result of identifying genes on sequencing reads or on assembled nucleotide contigs, which themselves are often very fragmented. The fragmented nature of metagenomic protein predictions adversely impacts homology detection and, therefore, the quality of the overall annotation of the dataset. Here we present a novel algorithm called GRASP that accurately identifies the homologs of a given reference protein sequence from a database consisting of partial-length metagenomic proteins. Our homology detection strategy is guided by the reference sequence, and involves the simultaneous search and assembly of overlapping database sequences. GRASP was compared to three commonly used protein sequence search programs (BLASTP, PSI-BLAST and FASTM). Our evaluations using several simulated and real datasets show that GRASP has a significantly higher sensitivity than these programs while maintaining a very high specificity. GRASP can be a very useful program for detecting and quantifying taxonomic and protein family abundances in metagenomic datasets. GRASP is implemented in GNU C++, and is freely available at http://sourceforge.net/projects/grasp-release.

Genome-wide methylated CpG island profiles of melanoma cells reveal a melanoma coregulation network.

Metastatic melanoma is a malignant cancer with generally poor prognosis, with no targeted chemotherapy. To identify epigenetic changes related to melanoma, we have determined genome-wide methylated CpG island distributions by next-generation sequencing. Melanoma chromosomes tend to be differentially methylated over short CpG island tracts. CpG islands in the upstream regulatory regions of many coding and noncoding RNA genes, including, for example, TERC, which encodes the telomerase RNA, exhibit extensive hypermethylation, whereas several repeated elements, such as LINE 2, and several LTR elements, are hypomethylated in advanced stage melanoma cell lines. By using CpG island demethylation profiles, and by integrating these data with RNA-seq data obtained from melanoma cells, we have identified a co-expression network of differentially methylated genes with significance for cancer related functions. Focused assays of melanoma patient tissue samples for CpG island methylation near the noncoding RNA gene SNORD-10 demonstrated high specificity.

Epigenetic regulation of microRNA genes and the role of miR-34b in cell invasion and motility in human melanoma.

Invasive melanoma is the most lethal form of skin cancer. The treatment of melanoma-derived cell lines with 5-aza-2'-deoxycytidine (5-Aza-dC) markedly increases the expression of several miRNAs, suggesting that the miRNA-encoding genes might be epigenetically regulated, either directly or indirectly, by DNA methylation. We have identified a group of epigenetically regulated miRNA genes in melanoma cells, and have confirmed that the upstream CpG island sequences of several such miRNA genes are hypermethylated in cell lines derived from different stages of melanoma, but not in melanocytes and keratinocytes. We used direct DNA bisulfite and immunoprecipitated DNA (Methyl-DIP) to identify changes in CpG island methylation in distinct melanoma patient samples classified as primary in situ, regional metastatic, and distant metastatic. Two melanoma cell lines (WM1552C and A375 derived from stage 3 and stage 4 human melanoma, respectively) were engineered to ectopically express one of the epigenetically modified miRNA: miR-34b. Expression of miR-34b reduced cell invasion and motility rates of both WM1552C and A375, suggesting that the enhanced cell invasiveness and motility observed in metastatic melanoma cells may be related to their reduced expression of miR-34b. Total RNA isolated from control or miR-34b-expressing WM1552C cells was subjected to deep sequencing to identify gene networks around miR-34b. We identified network modules that are potentially regulated by miR-34b, and which suggest a mechanism for the role of miR-34b in regulating normal cell motility and cytokinesis.