The promoters of human cell cycle genes integrate signals from two tumor suppressive pathways during cellular transformation

Deciphering regulatory events that drive malignant transformation represents a major challenge for systems biology. Here we analyzed genome-wide transcription profiling of an in-vitro transformation process. We focused on a cluster of genes whose expression levels increased as a function of p53 and p16INK4A tumor suppressors inactivation. This cluster predominantly consists of cell cycle genes and constitutes a signature of a diversity of cancers. By linking expression profiles of the genes in the cluster with the dynamic behavior of p53 and p16INK4A, we identified a promoter architecture that integrates signals from the two tumor suppressive channels and that maps their activity onto distinct levels of expression of the cell cycle genes, which in turn, correspond to different cellular proliferation rates. Taking components of the mitotic spindle as an example, we experimentally verified our predictions that p53-mediated transcriptional repression of several of these novel targets is dependent on the activities of p21, NFY and E2F. Our study demonstrates how a well-controlled transformation process allows linking between gene expression, promoter architecture and activity of upstream signaling molecules.Comment: To appear in Molecular Systems Biolog

p53 Plays a Role in Mesenchymal Differentiation Programs, in a Cell Fate Dependent Manner

Background: The tumor suppressor p53 is an important regulator that controls various cellular networks, including cell differentiation. Interestingly, some studies suggest that p53 facilitates cell differentiation, whereas others claim that it suppresses differentiation. Therefore, it is critical to evaluate whether this inconsistency represents an authentic differential p53 activity manifested in the various differentiation programs. Methodology/Principal Findings: To clarify this important issue, we conducted a comparative study of several mesenchymal differentiation programs. The effects of p53 knockdown or enhanced activity were analyzed in mouse and human mesenchymal cells, representing various stages of several differentiation programs. We found that p53 downregulated the expression of master differentiation-inducing transcription factors, thereby inhibiting osteogenic, adipogenic and smooth muscle differentiation of multiple mesenchymal cell types. In contrast, p53 is essential for skeletal muscle differentiation and osteogenic re-programming of skeletal muscle committed cells. Conclusions: These comparative studies suggest that, depending on the specific cell type and the specific differentiatio

E2F1-Mediated Induction of NFYB Attenuates Apoptosis via Joint Regulation of a Pro-Survival Transcriptional Program

<div><p>The E2F1 transcription factor regulates cell proliferation and apoptosis through the control of a considerable variety of target genes. Previous work has detailed the role of other transcription factors in mediating the specificity of E2F function. Here we identify the NF-YB transcription factor as a novel direct E2F1 target. Genome-wide expression analysis of the effects of NFYB knockdown on E2F1-mediated transcription identified a large group of genes that are co-regulated by E2F1 and NFYB. We also provide evidence that knockdown of NFYB enhances E2F1-induced apoptosis, suggesting a pro-survival function of the NFYB/E2F1 joint transcriptional program. Bioinformatic analysis suggests that deregulation of these NFY-dependent E2F1 target genes might play a role in sarcomagenesis as well as drug resistance.</p></div

NFYB is a direct E2F1 target.

<p>(A) Real-time PCR analysis of NFYB mRNA levels at four and eight hours after E2F1 induction in U2OS ER-E2F1 cells. Cells were serum starved for twenty four hours prior to addition of 80 nM OHT. (B) Western blot of NFYB and GAPDH protein levels. U2OS ER-E2F1 cells were induced with 80nM OHT for eight and twenty four hours following twenty four hour serum starvation. Lysates were analyzed by SDS-PAGE/Western blot and probed with anti-NFYB and anti-GAPDH antibodies (loading control). (C) U2OS ER-E2F1 cells were serum starved for twenty four hours followed by induction with 80nM OHT for seven hours. Chromatin immunoprecipitation was performed with anti-HA antibody for detection of ER-HA E2F1 binding to the NFYB promoter and IGX1 repeats (negative control).</p

Identification of NFYB-dependent E2F1 target genes.

<p>(A) Real-time PCR analysis of NFYB mRNA levels following siRNA transfection. U2OS ER-E2F1 cells were transfected with two siRNAs targeting NFYB or two negative control siRNAs at 100nM. Cells were serum starved for twenty four hours followed by 80nM OHT induction for four or eight hours. (B) Western blot analysis of NFYB protein levels following E2F1 activation. U2OS ER-E2F1 cells transfected with siRNA targeting NFYB or control were serum starved for twenty four hours followed by OHT induction at eight, twenty four, and forty eight hours. Lysates were analyzed by SDS-PAGE/Western blot and probed with anti-NFYB and anti-GAPDH antibodies (loading control). (C) Microarray analysis of the effect of NFYB knockdown on E2F1-mediated transcription. Samples were processed in the same manner as in Fig 2A and analyzed using Human U133A 2.0 expression microarrays. Heatmap represents the results of hierarchical clustering of 224 probes that showed at least 1.3-fold increase or 0.7-fold decrease in expression of compared to control following NFYB knockdown at eight hours. Real-time PCR validation of target gene expression decrease for SIVA1 (D), SFRP1 (E), FOLH1 (F), and PRKCZ (G) following NFYB knockdown. Samples were processed in the same manner as Fig 2A. * denotes p<0.05, ** denotes p<0.01, *** denotes p<0.001, **** denotes p<0.0001.</p

NFYB signature overexpression associates with drug therapy resistance.

<p>(A) Oncomine analysis demonstrating upregulation of genes from the NFYB-dependent E2F1 signature in in irinotecan resistant cell lines compared to irinotecan sensitive cell lines. (B) Oncomine analysis demonstrating upregulation of genes from the NFYB-dependent E2F1 signature in panobinostat resistant cell lines compared to panobinostat sensitive cell lines.</p

NFYB-dependent E2F1 targets.

<p>(A) ChIP analysis of E2F1 binding to target gene promoters. U2OS ER-HA E2F1 cells were serum starved for twenty four hours followed by 80nM OHT induction for seven hours. Immunoprecipitation was performed with anti-HA antibody for detection of ER-HA E2F1 binding to the SFRP1, PRKCZ, FOLH1 promoters and to IGX1 repeats (negative control). (B) Real-time PCR analysis of NFYB expression. U2OS ER-E2F1 cells were infected with lentviruses encoding the NFYB cDNA tagged with V5. A stable line was selected using blasticidin resistance for two weeks. This NFYB overexpression line is denoted as NFYB. The parental U2OS ER-E2F1 line is denoted as “parental”. Cell lines were serum starved for twenty four hours followed by 80nM OHT induction for eight hours. (C) Western blot analysis of ectopic NFYB expression following establishment of stable NFYB overexpression cell line. Lysates were analyzed by western blotting of NFYB transgene levels using an anti-V5 antibody, and GAPDH. Samples were processed in the same manner as in Fig 3B. Real-time PCR analysis of SFRP1 (D) and FOLH1 (E) in U2OS ER-E2F1 in parental and NFYB overexpressing U2OS ER-E2F1 cell lines. Samples were processed in the same manner as in Fig 3B.</p

CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data.

Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions of individual cell types to the physiological states of the tissue. Current approaches that address tissue heterogeneity have drawbacks. Experimental techniques, such as fluorescence-activated cell sorting, and single cell RNA sequencing are expensive. Computational approaches that use expression data from heterogeneous samples are promising, but most of the current methods estimate either cell-type proportions or cell-type-specific expression profiles by requiring the other as input. Although such partial deconvolution methods have been successfully applied to tumor samples, the additional input required may be unavailable. We introduce a novel complete deconvolution method, CDSeq, that uses only RNA-Seq data from bulk tissue samples to simultaneously estimate both cell-type proportions and cell-type-specific expression profiles. Using several synthetic and real experimental datasets with known cell-type composition and cell-type-specific expression profiles, we compared CDSeq's complete deconvolution performance with seven other established deconvolution methods. Complete deconvolution using CDSeq represents a substantial technical advance over partial deconvolution approaches and will be useful for studying cell mixtures in tissue samples. CDSeq is available at GitHub repository (MATLAB and Octave code): https://github.com/kkang7/CDSeq

Glypican 6 is a putative biomarker for metastatic progression of cutaneous melanoma.

Due to the poor prognosis of advanced metastatic melanoma, it is crucial to find early biomarkers that help identify which melanomas will metastasize. By comparing the gene expression data from primary and cutaneous melanoma samples from The Cancer Genome Atlas (TCGA), we identified GPC6 among a set of genes whose expression levels can distinguish between primary melanoma and regional cutaneous/subcutaneous metastases. Glypicans are thought to play a role in tumor growth by regulating the signaling pathways of Wnt, Hedgehogs, fibroblast growth factors (FGFs), and bone morphogenetic proteins (BMPs). We showed that GPC6 expression was up-regulated in a melanoma cell line compared to normal melanocytes and in metastatic melanoma compared to primary melanoma. Furthermore, GPC6 expression was positively correlated with genes largely involved in cell adhesion and migration in both melanoma samples and in RNA-seq samples from other TCGA tumors. Our results suggest that GPC6 may play a role in tumor metastatic progression. In TCGA melanoma samples, we also showed that GPC6 expression was negatively correlated with miR-509-3p, which has previously been shown to function as a tumor suppressor in various cancer cell lines. We overexpressed miR-509-3p in A375 melanoma cells and showed that GPC6 expression was significantly suppressed. This result suggested that GPC6 was a putative target of miR-509-3p in melanoma. Together, our findings identified GPC6 as an early biomarker for melanoma metastatic progression, one that can be regulated by miR-509-3p