Integration of the viral DNA into host chromosomes was found in most of the hepatitis B virus (HBV)–related hepatocellular carcinomas (HCCs). Here we devised a massive anchored parallel sequencing (MAPS) method using next-generation sequencing to isolate and sequence HBV integrants. Applying MAPS to 40 pairs of HBV–related HCC tissues (cancer and adjacent tissues), we identified 296 HBV integration events corresponding to 286 unique integration sites (UISs) with precise HBV–Human DNA junctions. HBV integration favored chromosome 17 and preferentially integrated into human transcript units. HBV targeted genes were enriched in GO terms: cAMP metabolic processes, T cell differentiation and activation, TGF beta receptor pathway, ncRNA catabolic process, and dsRNA fragmentation and cellular response to dsRNA. The HBV targeted genes include 7 genes (PTPRJ, CNTN6, IL12B, MYOM1, FNDC3B, LRFN2, FN1) containing IPR003961 (Fibronectin, type III domain), 7 genes (NRG3, MASP2, NELL1, LRP1B, ADAM21, NRXN1, FN1) containing IPR013032 (EGF-like region, conserved site), and three genes (PDE7A, PDE4B, PDE11A) containing IPR002073 (3′, 5′-cyclic-nucleotide phosphodiesterase). Enriched pathways include hsa04512 (ECM-receptor interaction), hsa04510 (Focal adhesion), and hsa04012 (ErbB signaling pathway). Fewer integration events were found in cancers compared to cancer-adjacent tissues, suggesting a clonal expansion model in HCC development. Finally, we identified 8 genes that were recurrent target genes by HBV integration including fibronectin 1 (FN1) and telomerase reverse transcriptase (TERT1), two known recurrent target genes, and additional novel target genes such as SMAD family member 5 (SMAD5), phosphatase and actin regulator 4 (PHACTR4), and RNA binding protein fox-1 homolog (C. elegans) 1 (RBFOX1). Integrating analysis with recently published whole-genome sequencing analysis, we identified 14 additional recurrent HBV target genes, greatly expanding the HBV recurrent target list. This global survey of HBV integration events, together with recently published whole-genome sequencing analyses, furthered our understanding of the HBV–related HCC. Integration of the hepatitis B virus (HBV) into the human liver cells was found in most of the related hepatocellular carcinomas (HCCs). Here, taking the recent advances in high-throughput sequencing, we devised an efficient and cost-effective method that we named massive anchored parallel sequencing (MAPS) method, to conduct a global survey of HBV integration events in 40 pairs of HBV–related HCC tissues (cancer and adjacent tissues). We identified 286 unique integration sites (UISs) with precise HBV–Human DNA junctions. We identified a higher number of HBV integration events in cancer adjacent tissues than in HCC tissues, suggesting a clonal expansion process during HCC development. We also found that fibronectin and its related genes (fibronectin type III-like fold domain containing genes) were frequently targeted by HBV. Fibronectin is a protein produced abundantly by the liver cells and also serves as a linker in the extracellular matrix. Our findings might suggest a role for the disruption of fibronectin and associated cellular matrix in HBV related liver cancers. We also identified 14 additional recurrent HBV target genes, greatly expanding the HBV recurrent target list. This study would add significantly to our understanding of HCC development.

SOX2 is an important stem cell marker and plays important roles in development and carcinogenesis. However, the role of SOX2 in Epithelial-Mesenchymal Transition has not been investigated. We demonstrated, for the first time, that SOX2 is involved in the Epithelial-Mesenchymal Transition (EMT) process as knock downof SOX2 in colorectal cancer (CRC) SW620 cells induced a Mesenchymal-Epithelial Transition (MET) process with recognized changes in the expression of key genes involved in the EMT process including E-cadherin and vimentin. In addition, we provided a link between SOX2 activity and the WNT pathway by showing that knock down of SOX2 reduced the WNT pathway activity in colorectal cancer (CRC) cells. We further demonstrated that SOX2 is involved in cell migration and invasion in vitro and in metastasis in vivo for CRC cells, and that the process might be mediated through the MMP2 activity. Finally, an IHC analysis of 44 cases of colorectal cancer patients suggested that SOX2 is a prognosis marker for metastasis of colorectal cancers.

The androgen receptor (AR) plays important roles in the development of male phenotype and in different human diseases including prostate cancers. The AR can act either as a promoter or a tumor suppressor depending on cell types. The AR proliferative response program has been well studied, but its prohibitive response program has not yet been thoroughly studied. Previous studies found that PC3 cells expressing the wild-type AR inhibit growth and suppress invasion. We applied expression profiling to identify the response program of PC3 cells expressing the AR (PC3-AR) under different growth conditions (i.e. with or without androgens and at different concentration of androgens) and then applied the newly developed ChIP-seq technology to identify the AR binding regions in the PC3 cancer genome. A surprising finding was that the comparison of MOCK-transfected PC3 cells with AR-transfected cells identified 3,452 differentially expressed genes (two fold cutoff) even without the addition of androgens (i.e. in ethanol control), suggesting that a ligand independent activation or extremely low-level androgen activation of the AR. ChIP-Seq analysis revealed 6,629 AR binding regions in the cancer genome of PC3 cells with an FDR (false discovery rate) cut off of 0.05. About 22.4% (638 of 2,849) can be mapped to within 2 kb of the transcription start site (TSS). Three novel AR binding motifs were identified in the AR binding regions of PC3-AR cells, and two of them share a core consensus sequence CGAGCTCTTC, which together mapped to 27.3% of AR binding regions (1,808/6,629). In contrast, only about 2.9% (190/6,629) of AR binding sites contains the canonical AR matrix M00481, M00447 and M00962 (from the Transfac database), which is derived mostly from AR proliferative responsive genes in androgen dependent cells. In addition, we identified four top ranking co-occupancy transcription factors in the AR binding regions, which include TEF1 (Transcriptional enhancer factor), GATA (GATA transcription factors), OCT (octamer transcription factors) and PU1 (PU.1 transcription factor). Our data provide a valuable data set in understanding the molecular basis for growth inhibition response program of the AR in prostate cancer cells, which can be exploited for developing novel prostate cancer therapeutic strategies.

CHI3L1 (YKL40) is a secreted glycoprotein and elevated serum CHI3L1 level has been proved to be associated with poor prognosis in many human cancers. However, the mechanism of how CHI3L1 causes poor prognosis in cancers is still unknown. Here, considering that CHI3L1 is a liver specific/enriched protein, we use hepatocellular carcinoma as a model to study the function of CHI3L1. We showed that, both in vivo and in vitro, overexpression of CHI3L1 could promote liver cancer cells growth, migration and invasion. We then used RNA-seq to analyze the expression profiles of CHI3L1 overexpressed in two HCC cell lines and found that CHI3L1 overexpression affected genes that were involved in cell-cell adhesion, extracellular exosome and adherens junction. Western blot analysis further revealed that CHI3L1 could activate TGF-β signal pathways. Our data added new understanding of the mechanism of CHI3L1’s action. 1) CHI3L1 promoted cancer cell proliferation by regulating cell cycles; 2) CHI3L1 promoted cancer cell invasion and metastasis; 3) CHI3L1 regulate liver cancer potentially by regulating the TGF-β signaling pathways; 4) CHI3L1 has direct kinase activities or activate kinase to phosphorylate SMAD2, SMAD3.

Global analysis of H3K4me3 and H3K27me3 profiles in glioblastoma stem cells and identification of SLC17A7 as a bivalent tumor suppressor gene Global analysis of H3K4me3 and H3K27me3 profiles in glioblastoma stem cells and identification of SLC17A7 as a bivalent tumor suppressor gene

Chemotherapy with carboplatin and paclitaxel is the standard treatment for ovarian cancer patients. Although most patients initially respond to this treatment, few are cured. Resistance to chemotherapy is the major cause of treatment failure. We applied a quantitative proteomic approach based on ICAT/MS/MS technology to analyze tissues harvested at primary debulking surgery before the initiation of combination chemotherapy in order to identify potential naive or intrinsic chemotherapy response proteins in ovarian cancers. We identified 44 proteins that are overexpressed, and 34 proteins that are underexpressed in the chemosensitive tissue compared to the chemoresistant tissue. The overexpressed proteins identified in the chemoresistant tissue include 10 proteins (25.6%) belonging to the extracellular matrix (ECM), including decorin, versican, basigin (CD147), fibulin-1, extracellular matrix protein 1, biglycan, fibronectin 1, dermatopontin, alpha-cardiac actin (smooth muscle actin), and an EGF-containing fibulin-like extracellular matrix protein 1. Interesting proteins identified as overexpressed in the chemosensitive tissue include gamma-catenin (junction plakoglobin) and delta-catenin, tumor suppressor p53-binding protein 1 (53BP1), insulin-like growth factor-binding protein 2 (IGFBP2), proliferating cell nuclear antigen (PCNA), annexin A11, and 53 kDa selenium binding protein 1. Integrative analysis with expression profiling data of eight chemoresistant tissues and 13 chemosensitive tissues revealed that 16 proteins showed consistent changes at both the protein and the RNA levels. These include P53 binding protein 1, catenin delta 1 and plakoglobin, EGF-containing fibulin-like extracellular matrix protein 1 and voltage-dependent anion-selective channel protein 1. Our results suggest that chemotherapy response may be determined by multiple and complex system properties involving extracellular–matrix, cell adhesion and junction proteins.