Additional file 1 of Assessing the effects of tempol on renal fibrosis, inflammation, and oxidative stress in a high-salt diet combined with 5/6 nephrectomy rat model: utilizing oxidized albumin as a biomarker

Supplementary Material

Clusters of miRNA-target genes by their correlation coefficients.

<p>The heat map representation of the correlation patterns for the miRNA targets. The 267 differentially expressed target mRNAs, including 63 up-regulated targets and 204 down-regulated targets, were used to cluster the miRNAs. Rows of the heat map represent target mRNAs, and columns represent the miRNAs. Red squares indicate negative correlations, purple squares indicate positive correlations and white spots (colorless) indicate that there is no correlation.</p

The log₂ FC values of the three miRNAs in 19 cancer types.

<p>Fold change is the ratio of the median signals between cancer tissue and normal tissue. Abbreviations: FC, Fold change; PRAD, Prostate adenocarcinoma; BLCA, Bladder urothelial carcinoma; CHOL, Cholangiocarcinoma; COAD, Colon adenocarcinoma; ESCA, Esophageal carcinoma; HNSC, Head and neck squamous cell carcinoma; KICH, Kidney chromophobe; KIRC, Kidney renal clear cell carcinoma; KIRP, Kidney renal papillary cell carcinoma; LIHC, Liver hepatocellular carcinoma; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma; PCPG, Pheochromocytoma and paraganglioma; READ, Rectal adenocarcinoma; STAD, Stomach adenocarcinoma; THCA, Thyroid carcinoma; THYM, Thymoma; PAAD, Pancreatic adenocarcinoma; and SKCM, Skin cutaneous melanoma. * The indicated miRNA expressed differentially in a cancer.</p

Correlations between the expressions of the three miRNAs and clinical features.

<p>Abbreviation: <i>r</i>_<i>s</i>, Spearman’s rank correlation coefficient</p><p>Correlations between the expressions of the three miRNAs and clinical features.</p

Candidate miRNAs for PCa biomarkers.

<p>Candidate miRNAs for PCa biomarkers.</p

Brief overview of the datasets.

<p>Abbreviations: TU, tumor sample; N, non-tumor sample; NA, not available; in the last column, the pairs, TU and N samples were from the same patient. TU(1): 72 tumor samples included 50 organ-confined PCa samples and 22 malignant trans-urethral resection of the PCa (TURP-PCa) samples. The numbers 5(2) indicate that the Gleason score was 5 for 2 PCa cases, the same as for the others.</p><p>Brief overview of the datasets.</p

Searching strategy.

<p>Searching strategy.</p

Common target genes and biological pathways of the three miRNAs.

<p>The purple oval represents <i>RIMS3</i>; the three blue ovals represent the three miRNAs; black straight lines indicate the target effect of miRNAs on gene; dotted lines indicate the involvement of the miRNAs in PANTHER pathways, and their colors reflect the significances of -log₁₀ transformed <i>p</i> values for the pathways.</p

TCGA data for the three differentially expressed miRNAs in prostate primary solid tumor (n = 498) and normal solid tissue (n = 52).

<p>(A) The expression levels of miR-182 in prostate primary solid tumor and normal solid tissue. (B) The expression levels of miR-200c in prostate primary solid tumor and normal solid tissue. (C) The expression levels of miR-145 in prostate primary solid tumor and normal solid tissue. The expression level values were calculated using log_<b>2</b> transformed RPM values.</p

RTK/ERK Pathway under Natural Selection Associated with Prostate Cancer

<div><p>Prostate cancer (PCa) is a global disease causing large numbers of deaths every year. Recent studies have indicated the RTK/ERK pathway might be a key pathway in the development of PCa. However, the exact association and evolution-based mechanism remain unclear. This study was conducted by combining genotypic and phenotypic data from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa) with related databases such as the HapMap Project and Genevar. In this analysis, expression of quantitative trait loci (eQTLs) analysis, natural selection and gene-based pathway analysis were involved. The pathway analysis confirmed the positive relationship between PCa risk and several key genes. In addition, combined with the natural selection, it seems that 4 genes (EGFR, ERBB2, PTK2, and RAF1) with five SNPs (rs11238349, rs17172438, rs984654, rs11773818, and rs17172432) especially rs17172432, might be pivotal factors in the development of PCa. The results indicate that the RTK/ERK pathway under natural selection is a key link in PCa risk. The joint effect of the genes and loci with positive selection might be one reason for the development of PCa. Dealing with all the factors simultaneously might give insight into prevention and aid in predicting the success of potential therapies for PCa.</p></div