Signal transducer and activator of transcription 3-mediated CD133 up-regulation contributes to promotion of hepatocellular carcinoma

published_or_final_versio

When One Size Does Not Fit All: A Simple Statistical Method to Deal with Across-Individual Variations of Effects

In science, it is a common experience to discover that although the investigated effect is very clear in some individuals, statistical tests are not significant because the effect is null or even opposite in other individuals. Indeed, t-tests, Anovas and linear regressions compare the average effect with respect to its inter-individual variability, so that they can fail to evidence a factor that has a high effect in many individuals (with respect to the intra-individual variability). In such paradoxical situations, statistical tools are at odds with the researcher’s aim to uncover any factor that affects individual behavior, and not only those with stereotypical effects. In order to go beyond the reductive and sometimes illusory description of the average behavior, we propose a simple statistical method: applying a Kolmogorov-Smirnov test to assess whether the distribution of p-values provided by individual tests is significantly biased towards zero. Using Monte-Carlo studies, we assess the power of this two-step procedure with respect to RM Anova and multilevel mixed-effect analyses, and probe its robustness when individual data violate the assumption of normality and homoscedasticity. We find that the method is powerful and robust even with small sample sizes for which multilevel methods reach their limits. In contrast to existing methods for combining p-values, the Kolmogorov-Smirnov test has unique resistance to outlier individuals: it cannot yield significance based on a high effect in one or two exceptional individuals, which allows drawing valid population inferences. The simplicity and ease of use of our method facilitates the identification of factors that would otherwise be overlooked because they affect individual behavior in significant but variable ways, and its power and reliability with small sample sizes (<30–50 individuals) suggest it as a tool of choice in exploratory studies

An Integrated Approach to Identifying Cis-Regulatory Modules in the Human Genome

In eukaryotic genomes, it is challenging to accurately determine target sites of transcription factors (TFs) by only using sequence information. Previous efforts were made to tackle this task by considering the fact that TF binding sites tend to be more conserved than other functional sites and the binding sites of several TFs are often clustered. Recently, ChIP-chip and ChIP-sequencing experiments have been accumulated to identify TF binding sites as well as survey the chromatin modification patterns at the regulatory elements such as promoters and enhancers. We propose here a hidden Markov model (HMM) to incorporate sequence motif information, TF-DNA interaction data and chromatin modification patterns to precisely identify cis-regulatory modules (CRMs). We conducted ChIP-chip experiments on four TFs, CREB, E2F1, MAX, and YY1 in 1% of the human genome. We then trained a hidden Markov model (HMM) to identify the labels of the CRMs by incorporating the sequence motifs recognized by these TFs and the ChIP-chip ratio. Chromatin modification data was used to predict the functional sites and to further remove false positives. Cross-validation showed that our integrated HMM had a performance superior to other existing methods on predicting CRMs. Incorporating histone signature information successfully penalized false prediction and improved the whole performance. The dataset we used and the software are available at http://nash.ucsd.edu/CIS/

Clustered ChIP-Seq-defined transcription factor binding sites and histone modifications map distinct classes of regulatory elements

<p>Abstract</p> <p>Background</p> <p>Transcription factor binding to DNA requires both an appropriate binding element and suitably open chromatin, which together help to define regulatory elements within the genome. Current methods of identifying regulatory elements, such as promoters or enhancers, typically rely on sequence conservation, existing gene annotations or specific marks, such as histone modifications and p300 binding methods, each of which has its own biases.</p> <p>Results</p> <p>Herein we show that an approach based on clustering of transcription factor peaks from high-throughput sequencing coupled with chromatin immunoprecipitation (Chip-Seq) can be used to evaluate markers for regulatory elements. We used 67 data sets for 54 unique transcription factors distributed over two cell lines to create regulatory element clusters. By integrating the clusters from our approach with histone modifications and data for open chromatin, we identified general methylation of lysine 4 on histone H3 (H3K4me) as the most specific marker for transcription factor clusters. Clusters mapping to annotated genes showed distinct patterns in cluster composition related to gene expression and histone modifications. Clusters mapping to intergenic regions fall into two groups either directly involved in transcription, including miRNAs and long noncoding RNAs, or facilitating transcription by long-range interactions. The latter clusters were specifically enriched with H3K4me1, but less with acetylation of lysine 27 on histone 3 or p300 binding.</p> <p>Conclusion</p> <p>By integrating genomewide data of transcription factor binding and chromatin structure and using our data-driven approach, we pinpointed the chromatin marks that best explain transcription factor association with different regulatory elements. Our results also indicate that a modest selection of transcription factors may be sufficient to map most regulatory elements in the human genome.</p

Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms

Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability

Clinical outcomes and prognostic factors in patients with breast diffuse large B cell lymphoma; Consortium for Improving Survival of Lymphoma (CISL) study

<p>Abstract</p> <p>Background</p> <p>The breast is a rare extranodal site of non-Hodgkin lymphoma, and primary breast lymphoma (PBL) has been arbitrarily defined as disease localized to one or both breasts with or without regional lymph nodes involvement. The aim of this study was to evaluate the clinical outcomes in patients with diffuse large B cell lymphoma (DLBCL) and breast involvement, and to find the criteria of PBL reflecting the outcome and prognosis.</p> <p>Methods</p> <p>We retrospectively analyzed data from 68 patients, newly diagnosed with DLBCL and breast involvement at 16 Korean institutions between January 1994 and June 2009.</p> <p>Results</p> <p>Median age at diagnosis was 48 years (range, 20-83 years). Forty-three (63.2%) patients were PBL according to previous arbitrary criteria, sixteen (23.5%) patients were high-intermediate to high risk of international prognostic index. The patients with one extranodal disease in the breast (OED) with or without nodal disease were 49 (72.1%), and those with multiple extranodal disease (MED) were 19 (27.9%). During median follow-up of 41.5 months (range, 2.4-186.0 months), estimated 5-year progression-free survival (PFS) was 53.7 ± 7.6%, and overall survival (OS) was 60.3 ± 7.2%. The 5-year PFS and OS was significantly higher for patients with the OED group than those with the MED group (5-year PFS, 64.9 ± 8.9% vs. 27.5 ± 11.4%, p = 0.001; 5-year OS, 74.3 ± 7.6% vs. 24.5 ± 13.0%, p < 0.001). In multivariate analysis, MED (hazard ratio [HR], 3.61; 95% confidence interval [CI], 1.07-12.2) and fewer than four cycles of systemic chemotherapy with or without local treatments (HR, 4.47; 95% CI, 1.54-12.96) were independent prognostic factors for worse OS. Twenty-five (36.8%) patients experienced progression, and the cumulative incidence of progression in multiple extranodal sites or other than breasts and central nervous system was significantly different between the OED group and the MED group (5-year cumulative incidence, 9.7 ± 5.4% vs. 49.0 ± 15.1%, p = 0.001).</p> <p>Conclusions</p> <p>Our results show that the patients included in OED group, reflecting different treatment outcome, prognosis and pattern of progression, should be considered as PBL in the future trial. Further studies are warranted to validate our suggested criteria.</p

Luteolin decreases IGF-II production and downregulates insulin-like growth factor-I receptor signaling in HT-29 human colon cancer cells

<p>Abstract</p> <p>Background</p> <p>Luteolin is a 3',4',5,7-tetrahydroxyflavone found in various fruits and vegetables. We have shown previously that luteolin reduces HT-29 cell growth by inducing apoptosis and cell cycle arrest. The objective of this study was to examine whether luteolin downregulates the insulin-like growth factor-I receptor (IGF-IR) signaling pathway in HT-29 cells.</p> <p>Methods</p> <p>In order to assess the effects of luteolin and/or IGF-I on the IGF-IR signaling pathway, cells were cultured with or without 60 μmol/L luteolin and/or 10 nmol/L IGF-I. Cell proliferation, DNA synthesis, and IGF-IR mRNA levels were evaluated by a cell viability assay, [³H]thymidine incorporation assays, and real-time polymerase chain reaction, respectively. Western blot analyses, immunoprecipitation, and <it>in vitro </it>kinase assays were conducted to evaluate the secretion of IGF-II, the protein expression and activation of IGF-IR, and the association of the p85 subunit of phophatidylinositol-3 kinase (PI3K) with IGF-IR, the phosphorylation of Akt and extracellular signal-regulated kinase (ERK)1/2, and cell division cycle 25c (CDC25c), and PI3K activity.</p> <p>Results</p> <p>Luteolin (0 - 60 μmol/L) dose-dependently reduced the IGF-II secretion of HT-29 cells. IGF-I stimulated HT-29 cell growth but did not abrogate luteolin-induced growth inhibition. Luteolin reduced the levels of the IGF-IR precursor protein and IGF-IR transcripts. Luteolin reduced the IGF-I-induced tyrosine phosphorylation of IGF-IR and the association of p85 with IGF-IR. Additionally, luteolin inhibited the activity of PI3K activity as well as the phosphorylation of Akt, ERK1/2, and CDC25c in the presence and absence of IGF-I stimulation.</p> <p>Conclusions</p> <p>The present results demonstrate that luteolin downregulates the activation of the PI3K/Akt and ERK1/2 pathways via a reduction in IGF-IR signaling in HT-29 cells; this may be one of the mechanisms responsible for the observed luteolin-induced apoptosis and cell cycle arrest.</p

Colon cancer-derived oncogenic EGFR G724S mutant identified by whole genome sequence analysis is dependent on asymmetric dimerization and sensitive to cetuximab

Background: Inhibition of the activated epidermal growth factor receptor (EGFR) with either enzymatic kinase inhibitors or anti-EGFR antibodies such as cetuximab, is an effective modality of treatment for multiple human cancers. Enzymatic EGFR inhibitors are effective for lung adenocarcinomas with somatic kinase domain EGFR mutations while, paradoxically, anti-EGFR antibodies are more effective in colon and head and neck cancers where EGFR mutations occur less frequently. In colorectal cancer, anti-EGFR antibodies are routinely used as second-line therapy of KRAS wild-type tumors. However, detailed mechanisms and genomic predictors for pharmacological response to these antibodies in colon cancer remain unclear. Findings: We describe a case of colorectal adenocarcinoma, which was found to harbor a kinase domain mutation, G724S, in EGFR through whole genome sequencing. We show that G724S mutant EGFR is oncogenic and that it differs from classic lung cancer derived EGFR mutants in that it is cetuximab responsive in vitro, yet relatively insensitive to small molecule kinase inhibitors. Through biochemical and cellular pharmacologic studies, we have determined that cells harboring the colon cancer-derived G719S and G724S mutants are responsive to cetuximab therapy in vitro and found that the requirement for asymmetric dimerization of these mutant EGFR to promote cellular transformation may explain their greater inhibition by cetuximab than small-molecule kinase inhibitors. Conclusion: The colon-cancer derived G719S and G724S mutants are oncogenic and sensitive in vitro to cetuximab. These data suggest that patients with these mutations may benefit from the use of anti-EGFR antibodies as part of the first-line therapy

Multicenter retrospective analysis of 581 patients with primary intestinal non-hodgkin lymphoma from the Consortium for Improving Survival of Lymphoma (CISL)

<p>Abstract</p> <p>Background</p> <p>Primary intestinal non-Hodgkin lymphoma (NHL) is a heterogeneous disease with regard to anatomic and histologic distribution. Thus, analyses focusing on primary intestinal NHL with large number of patients are warranted.</p> <p>Methods</p> <p>We retrospectively analyzed 581 patients from 16 hospitals in Korea for primary intestinal NHL in this retrospective analysis. We compared clinical features and treatment outcomes according to the anatomic site of involvement and histologic subtypes.</p> <p>Results</p> <p>B-cell lymphoma (n = 504, 86.7%) was more frequent than T-cell lymphoma (n = 77, 13.3%). Diffuse large B-cell lymphoma (DLBCL) was the most common subtype (n = 386, 66.4%), and extranodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT) was the second most common subtype (n = 61, 10.5%). B-cell lymphoma mainly presented as localized disease (Lugano stage I/II) while T-cell lymphomas involved multiple intestinal sites. Thus, T-cell lymphoma had more unfavourable characteristics such as advanced stage at diagnosis, and the 5-year overall survival (OS) rate was significantly lower than B-cell lymphoma (28% versus 71%, P < 0.001). B symptoms were relatively uncommon (20.7%), and bone marrow invasion was a rare event (7.4%). The ileocecal region was the most commonly involved site (39.8%), followed by the small (27.9%) and large intestines (21.5%). Patients underwent surgery showed better OS than patients did not (5-year OS rate 77% versus 57%, P < 0.001). However, this beneficial effect of surgery was only statistically significant in patients with B-cell lymphomas (P < 0.001) not in T-cell lymphomas (P = 0.460). The comparison of survival based on the anatomic site of involvement showed that ileocecal regions had a better 5-year overall survival rate (72%) than other sites in consistent with that ileocecal region had higher proportion of patients with DLBCL who underwent surgery. Age > 60 years, performance status ≥ 2, elevated serum lactate dehydrogenase, Lugano stage IV, presence of B symptoms, and T-cell phenotype were independent prognostic factors for survival.</p> <p>Conclusions</p> <p>The survival of patients with ileocecal region involvement was better than that of patients with involvement at other sites, which might be related to histologic distribution, the proportion of tumor stage, and need for surgical resection.</p

Computational study of associations between histone modification and protein-DNA binding in yeast genome by integrating diverse information

<p>Abstract</p> <p>Background</p> <p>In parallel with the quick development of high-throughput technologies, <it>in vivo (vitro) </it>experiments for genome-wide identification of protein-DNA interactions have been developed. Nevertheless, a few questions remain in the field, such as how to distinguish true protein-DNA binding (functional binding) from non-specific protein-DNA binding (non-functional binding). Previous researches tackled the problem by integrated analysis of multiple available sources. However, few systematic studies have been carried out to examine the possible relationships between histone modification and protein-DNA binding. Here this issue was investigated by using publicly available histone modification data in yeast.</p> <p>Results</p> <p>Two separate histone modification datasets were studied, at both the open reading frame (ORF) and the promoter region of binding targets for 37 yeast transcription factors. Both results revealed a distinct histone modification pattern between the functional protein-DNA binding sites and non-functional ones for almost half of all TFs tested. Such difference is much stronger at the ORF than at the promoter region. In addition, a protein-histone modification interaction pathway can only be inferred from the functional protein binding targets.</p> <p>Conclusions</p> <p>Overall, the results suggest that histone modification information can be used to distinguish the functional protein-DNA binding from the non-functional, and that the regulation of various proteins is controlled by the modification of different histone lysines such as the protein-specific histone modification levels.</p