DeepChrome: deep-learning for predicting gene expression from histone modifications.

MOTIVATION: Histone modifications are among the most important factors that control gene regulation. Computational methods that predict gene expression from histone modification signals are highly desirable for understanding their combinatorial effects in gene regulation. This knowledge can help in developing 'epigenetic drugs' for diseases like cancer. Previous studies for quantifying the relationship between histone modifications and gene expression levels either failed to capture combinatorial effects or relied on multiple methods that separate predictions and combinatorial analysis. This paper develops a unified discriminative framework using a deep convolutional neural network to classify gene expression using histone modification data as input. Our system, called DeepChrome, allows automatic extraction of complex interactions among important features. To simultaneously visualize the combinatorial interactions among histone modifications, we propose a novel optimization-based technique that generates feature pattern maps from the learnt deep model. This provides an intuitive description of underlying epigenetic mechanisms that regulate genes. RESULTS: We show that DeepChrome outperforms state-of-the-art models like Support Vector Machines and Random Forests for gene expression classification task on 56 different cell-types from REMC database. The output of our visualization technique not only validates the previous observations but also allows novel insights about combinatorial interactions among histone modification marks, some of which have recently been observed by experimental studies. AVAILABILITY AND IMPLEMENTATION: Codes and results are available at www.deepchrome.org CONTACT: yanjun@virginia.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Recurrent chimeric fusion RNAs in non-cancer tissues and cells.

Gene fusions and their products (RNA and protein) were once thought to be unique features to cancer. However, chimeric RNAs can also be found in normal cells. Here, we performed, curated and analyzed nearly 300 RNA-Seq libraries covering 30 different non-neoplastic human tissues and cells as well as 15 mouse tissues. A large number of fusion transcripts were found. Most fusions were detected only once, while 291 were seen in more than one sample. We focused on the recurrent fusions and performed RNA and protein level validations on a subset. We characterized these fusions based on various features of the fusions, and their parental genes. They tend to be expressed at higher levels relative to their parental genes than the non-recurrent ones. Over half of the recurrent fusions involve neighboring genes transcribing in the same direction. A few sequence motifs were found enriched close to the fusion junction sites. We performed functional analyses on a few widely expressed fusions, and found that silencing them resulted in dramatic reduction in normal cell growth and/or motility. Most chimeras use canonical splicing sites, thus are likely products of 'intergenic splicing'. We also explored the implications of these non-pathological fusions in cancer and in evolution.

[Changes of proliferation and angiogenesis of residual tumor in rabbit lung after radiofrequency ablation].

OBJECTIVE: To observe the changes of proliferation and angiogenesis of residual tumor in rabbit lung after radiofrequency ablation (RFA). METHODS: The model of VX2 tumor in rabbit lung was established by injection of tissue block suspension. 64 New Zealand White rabbits bearing VX2 tumor were assigned randomly to the control group (n = 10) and the RFA group (n = 48). During the RFA procedure, residual tumors were achieved by controlling the range of electrode expanding, output power and treatment time. At several points of time, Ki-67 labeling index (Ki-67LI) and microvessel density (MVD) of the residual tumors were calculated by immunohistochemical detection. RESULTS: Ki-67LI of the control group was 45.3% ± 2.1%. Ki-67LI of the RFA group at the first, 3 and 5 day were 56.4% ± 3.4%, 60.1% ± 4.1% and 59.8% ± 2.4% respectively, significantly higher than that of the control group; however, at the seventh, 9, 14 and 21 day, they were 45.4% ± 2.0%, 46.2% ± 3.4%, 45.1% ± 4.4% and 47.8% ± 3.9% respectively, no significant difference compared with the control group. The control group MVD was 28.9 ± 2.9. MVD of the RFA group at third, 5 and 7 day were 36.8 ± 2.6, 55.6 ± 4.8 and 51.5 ± 2.8 respectively, significantly higher than that of the control group; however, at the first, 9, 14 and 21 day were 27 ± 2.8, 29.2 ± 3.2, 30 ± 2.8 and 28.8 ± 3.1 respectively, no significant difference compared with the control group. CONCLUSIONS: The proliferation and angiogenesis of pulmonary residual tumor exhibit a transient increase phenomenon after RFA.

An integrated approach to blood-based cancer diagnosis and biomarker discovery.

Disrupted or abnormal biological processes responsible for cancers often quantitatively manifest as disrupted additive and multiplicative interactions of gene/protein expressions correlating with cancer progression. However, the examination of all possible combinatorial interactions between gene features in most case-control studies with limited training data is computationally infeasible. In this paper, we propose a practically feasible data integration approach, QUIRE (QUadratic Interactions among infoRmative fEatures), to identify discriminative complex interactions among informative gene features for cancer diagnosis and biomarker discovery directly based on patient blood samples. QUIRE works in two stages, where it first identifies functionally relevant gene groups for the disease with the help of gene functional annotations and available physical protein interactions, then it explores the combinatorial relationships among the genes from the selected informative groups. Based on our private experimentally generated data from patient blood samples using a novel SOMAmer (Slow Off-rate Modified Aptamer) technology, we apply QUIRE to cancer diagnosis and biomarker discovery for Renal Cell Carcinoma (RCC) and Ovarian Cancer (OVC). To further demonstrate the general applicability of our approach, we also apply QUIRE to a publicly available Colorectal Cancer (CRC) dataset that can be used to prioritize our SOMAmer design. Our experimental results show that QUIRE identifies gene-gene interactions that can better identify the different cancer stages of samples, as compared to other state-of-the-art feature selection methods. A literature survey shows that many of the interactions identified by QUIRE play important roles in the development of cancer.

[Change of ERCC1 expression of residual VX2 squamous carcinoma cells in rabbit lung after radiofrequency ablation].

BACKGROUND AND OBJECTIVE: Residual carcinoma cells play an important role in the result of radiofrequency ablation (RFA) of pulmonary malignancies, and Platinum-based adjuvant chemotherapy is one of the important treatment regimen to reduce residual carcinoma cells after RFA. ERCC1 (excision repair cross-complementation group 1) is an important factor affecting Platinum-based chemotherapy effects. Residual carcinoma cells exhibit some changes of their features after RFA; however, there is no report about the change of their ERCC1 expression by now. This study focused on the change of ERCC1 expression in residual VX2 squamous carcinoma cells in rabbit lung after RFA. METHODS: The model of VX2 squamous carcinoma in rabbit lung was established by injection of tissue block suspension. Fifty-eight New Zealand White rabbits with VX2 squamous carcinoma were randomly divided into the control group (n=10) and the RFA group (n=48). During the RFA procedure in these models, residual carcinoma cells were achieved by controlling the range of electrode expanding, power output and treatment time. At different points of time, the positive rates of ERCC1 expression in residual carcinoma were detected by immunohistochemistry. RESULTS: Comparing with the control group, the positive rate of ERCC1 expression in residual carcinoma in RFA group increases transiently within 1 d to 5 d (53.7% ± 1.6% & 32.9% ± 2.5%), and 5 d later, it decline to the level of the control group. CONCLUSIONS: The ERCC1 expression of residual pulmonary carcinoma increase within 5 d after RFA. Thus platinum-based adjuvant chemotherapy may be ineffective in this period.

Systematic prediction of human membrane receptor interactions.

Membrane receptor-activated signal transduction pathways are integral to cellular functions and disease mechanisms in humans. Identification of the full set of proteins interacting with membrane receptors by high-throughput experimental means is difficult because methods to directly identify protein interactions are largely not applicable to membrane proteins. Unlike prior approaches that attempted to predict the global human interactome, we used a computational strategy that only focused on discovering the interacting partners of human membrane receptors leading to improved results for these proteins. We predict specific interactions based on statistical integration of biological data containing highly informative direct and indirect evidences together with feedback from experts. The predicted membrane receptor interactome provides a system-wide view, and generates new biological hypotheses regarding interactions between membrane receptors and other proteins. We have experimentally validated a number of these interactions. The results suggest that a framework of systematically integrating computational predictions, global analyses, biological experimentation and expert feedback is a feasible strategy to study the human membrane receptor interactome.

Combined inhibition of PLC{gamma}-1 and c-Src abrogates epidermal growth factor receptor-mediated head and neck squamous cell carcinoma invasion.

PURPOSE: Mortality from head and neck squamous cell carcinoma (HNSCC) is usually associated with locoregional invasion of the tumor into vital organs, including the airway. Understanding the signaling mechanisms that abrogate HNSCC invasion may reveal novel therapeutic targets for intervention. The purpose of this study was to investigate the efficacy of combined inhibition of c-Src and PLCgamma-1 in the abrogation of HNSCC invasion. EXPERIMENTAL DESIGN: PLCgamma-1 and c-Src inhibition was achieved by a combination of small molecule inhibitors and dominant negative approaches. The effect of inhibition of PLCgamma-1 and c-Src on invasion of HNSCC cells was assessed in an in vitro Matrigel-coated transwell invasion assay. In addition, the immunoprecipitation reactions and in silico database mining was used to examine the interactions between PLCgamma-1 and c-Src. RESULTS: Here, we show that inhibition of PLCgamma-1 or c-Src with the PLC inhibitor U73122 or the Src family inhibitor AZD0530 or using dominant-negative constructs attenuated epidermal growth factor (EGF)-stimulated HNSCC invasion. Furthermore, EGF stimulation increased the association between PLCgamma-1 and c-Src in HNSCC cells. Combined inhibition of PLCgamma-1 and c-Src resulted in further attenuation of HNSCC cell invasion in vitro. CONCLUSIONS: These cumulative results suggest that PLCgamma-1 and c-Src activation contribute to HNSCC invasion downstream of EGF receptor and that targeting these pathways may be a novel strategy to prevent tumor invasion in HNSCC.