Boxplot of the YMR distributions in normal lung samples and lung cancer samples.

<p>Microarray gene expression data sets from different reports with different platforms were used. The data sets were described as in Table S7.</p

Yin Yang Gene Expression Ratio Signature for Lung Cancer Prognosis

<div><p>Many studies have established gene expression-based prognostic signatures for lung cancer. All of these signatures were built from training data sets by learning the correlation of gene expression with the patients' survival time. They require all new sample data to be normalized to the training data, ultimately resulting in common problems of low reproducibility and impracticality. To overcome these problems, we propose a new signature model which does not involve data training. We hypothesize that the imbalance of two opposing effects in lung cancer cells, represented by Yin and Yang genes, determines a patient’s prognosis. We selected the Yin and Yang genes by comparing expression data from normal lung and lung cancer tissue samples using both unsupervised clustering and pathways analyses. We calculated the Yin and Yang gene expression mean ratio (YMR) as patient risk scores. Thirty-one Yin and thirty-two Yang genes were identified and selected for the signature development. In normal lung tissues, the YMR is less than 1.0; in lung cancer cases, the YMR is greater than 1.0. The YMR was tested for lung cancer prognosis prediction in four independent data sets and it significantly stratified patients into high- and low-risk survival groups (p = 0.02, HR = 2.72; p = 0.01, HR = 2.70; p = 0.007, HR = 2.73; p = 0.005, HR = 2.63). It also showed prediction of the chemotherapy outcomes for stage II & III. In multivariate analysis, the YMR risk factor was more successful at predicting clinical outcomes than other commonly used clinical factors, with the exception of tumor stage. The YMR can be measured in an individual patient in the clinic independent of gene expression platform. This study provided a novel insight into the biology of lung cancer and shed light on the clinical applicability.</p></div

Validation of YMR in four data sets by Kaplan-Meier estimates of the survivor function.

<p><b>A.</b> Free-recurrence time function curve (low risk n = 60; high risk n = 65) of the adenocarcinomas patients from Bhattacharjee <i>et al</i>. <b>B</b>. Overall survival time function curve of the adenocarcinomas patients (low risk n = 27; high risk n = 31) from Bild <i>et al</i>. <b>C</b>. Patient samples (low risk n = 248; high risk n = 194) of the DCC project. <b>D</b>. RNA-seq samples (low risk n = 121; high risk n = 137) from TCGA. Low YMR scores (in green) correspond to the highest predicted survival probability and high YMR scores (in red) correspond to the greatest predicted risk.</p

Effect of H89 on TPA-induced expression, nucleosomal response and chromatin remodeling of <i>TFF1</i>.

<p>Serum-starved MCF-7 cells were pre-treated or not with H89 prior to TPA stimulation for 15, 30, 45 and 60 min. A. Total RNA was isolated and quantified by real time RT-PCR. Fold change values, normalized to <i>CYP33</i> expression levels and time 0 values, are the mean of three independent experiments, and the error bars represent the standard deviation. B. Formaldehyde-crosslinked mononucleosomes were prepared and used in ChIP assays with antibodies against RNAPII S5ph. Equal amounts of input and immunoprecipitated DNAs were quantified by real-time quantitative PCR. The enrichment values of the <i>TFF1</i> enhancer (−10476) and UPE (−429) sequences are the mean of three independent experiments, and the error bars represent the standard deviation. C. Serum-starved MCF-7 cells were pre-treated or not with H89 prior to TPA stimulation for 15, 30, 45 and 60 min. Formaldehyde-crosslinked mononucleosomes were prepared and used in ChIP assays with antibodies against MSK1, MSK2, H3S10ph, H3S10phK14ac, 14-3-3ε, 14-3-3ζ, and BRG1. Equal amounts of input and immunoprecipitated DNAs were quantified by real-time quantitative PCR. The enrichment values of the <i>TFF1</i> enhancer (-10476) and UPE (-429) sequences are the mean of three independent experiments, and the error bars represent the standard deviation. *P≤0.05, **P≤0.01, ***P≤0.001, ns = P≥0.05 (Student’s paired t-test).</p

Identification and selection of Yin and Yang genes.

<p><b>A</b>. Clustering of gene identification. The probe sets are in rows and the samples are in columns. The expression indexes of all the 12,625 probe sets of the 100 samples were summarized by RMA algorithm and further normalized by itemwise Z-normalization. 74 upregulated genes (bottom half rows) and 108 (top half rows) down regulated genes in cancer tissues were selected from the 2D clustering regions. The preselected 74 and 108 probsets were displayed by clustering again. <b>B</b>. Yin (bottom) and Yang (top) genes selection by functional analysis. The two circles represent the two cores of functional effects of the Yin and the Yang. The genes highlighted by the same color are in the same interaction network.</p

FOS and JUN levels do not change with MSK1 or MSK2 knockdown in MCF-7 cells.

<p>MCF-7 cells were treated with scramble, MSK1, or MSK2 siRNA, serum starved for 72 h, and treated with TPA for 0 or 45 min. Protein lysates were analyzed by immunoblotting using antibodies against MSK1 (rabbit, Sigma), MSK2 (rabbit, Abcam ab99411), JUN, or FOS. Actin was used as a loading control.</p

Mitogen- and Stress-Activated Protein Kinases 1 and 2 Are Required for Maximal Trefoil Factor 1 Induction

<div><p>Mitogen- and stress-activated protein kinases 1 and 2 (MSK1 and MSK2), activated downstream of the ERK- and p38-mitogen-activated protein kinase pathways are involved in cell survival, proliferation and differentiation. Following mitogenic or stress stimuli, they mediate the nucleosomal response, which includes phosphorylation of histone H3 at serine 10 (H3S10ph) coupled with transcriptional activation of immediate-early genes. While MSK1 and MSK2 are closely related, their relative roles may vary with cellular context and/or stimuli. However, our knowledge of MSK2 recruitment to immediate-early genes is limited, as research has primarily focused on MSK1. Here, we demonstrate that both MSK1 and MSK2, regulate the phorbol ester 12-O-tetradecanoylphorbol-13-acetate induced expression of the breast cancer marker gene, trefoil factor 1 (<i>TFF1</i>), by phosphorylating H3S10 at its 5′ regulatory regions. The MSK-mediated phosphorylation of H3S10 promotes the recruitment of 14-3-3 isoforms and BRG1, the ATPase subunit of the BAF/PBAF remodeling complex, to the enhancer and upstream promoter elements of <i>TFF1</i>. The recruited chromatin remodeling activity leads to the RNA polymerase II carboxy-terminal domain phosphorylation at the <i>TFF1</i> promoter, initiating <i>TFF1</i> expression in MCF-7 breast cancer cells. Moreover, we show that MSK1 or MSK2 is recruited to <i>TFF1</i> regulatory regions, but as components of different multiprotein complexes.</p></div

Comparison of YMR to different signature models previously reported.

<p>Comparison of YMR to different signature models previously reported.</p

Yin genes.

<p>Yin genes.</p

Kaplan-Meier estimates of the survivor function of the gYMR signature in different group of patients of the DCC data set.

<p><b>A</b>. Stage I only (low risk n = 122; high risk n = 177). <b>B</b>. Stage I who received chemotherapy (low risk n = 13; high risk n = 28). <b>C</b>. Stage I who did not receive chemotherapy (low risk n = 79; high risk n = 95). <b>D</b>. Stage II & III only (low risk n = 63; high risk n = 78). <b>E</b>. Stage II & III who received chemotherapy (low risk n = 24; high risk n = 23). <b>F</b>. Stage II & III who did not receive chemotherapy (low risk n = 27; high risk n = 31). Low gYMR scores (in green) correspond to the highest predicted survival probability and high gYMR scores (in red) correspond to the greatest predicted risk.</p