Additional file 6:Table S3. of Bmi-1 regulates stem cell-like properties of gastric cancer cells via modulating miRNAs

Frequencies of altered expression of Bmi-1,miR-21 and miR-34a in the 74 gastric cancer tissues. (XLS 14 kb

Additional file 5: Table S2. of Bmi-1 regulates stem cell-like properties of gastric cancer cells via modulating miRNAs

The correlation between Bmi-1 and stem cell markers in gastric cancer tissues. (XLS 14 kb

Additional file 3: Figure S2. of Bmi-1 regulates stem cell-like properties of gastric cancer cells via modulating miRNAs

Representative figures of Bmi-1 and several CSC-related proteins in gastric tumors, its surrounding normal tissues, and paired metastatic cancer samples. (DOC 6222 kb

Oxidative Stress-Related Genetic Polymorphisms Are Associated with the Prognosis of Metastatic Gastric Cancer Patients Treated with Epirubicin, Oxaliplatin and 5-Fluorouracil Combination Chemotherapy

<div><p>Background</p><p>Oxidative stress genes are related to cancer development and treatment response. In this study, we aimed to determine the predictive and prognostic roles of oxidative stress-related genetic polymorphisms in metastatic gastric cancer (MGC) patients treated with chemotherapy.</p><p>Methods</p><p>In this retrospective study, we genotyped nine oxidative stress-related single nucleotide polymorphisms (SNPs) in <i>NQO1</i>, <i>SOD2</i>, <i>SOD3</i>, <i>PON1</i>, <i>GSTP1</i>, <i>GSTT1</i>, and <i>NOS3</i> (rs1800566, rs10517, rs4880, rs1799895, rs662, rs854560, rs1695, rs2266637, rs1799983, respectively) in 108 consecutive MGC patients treated with epirubicin, oxaliplatin, and 5-fluorouracil (EOF) regimen as the first-line chemotherapy and analyzed the association between the genotypes and the disease control rate (DCR), progression-free survival (PFS), and overall survival (OS).</p><p>Results</p><p>We found that, in addition to a lower pathological grade (<i>p</i> = 0.017), <i>NQO1</i> rs1800566 CT/TT genotype was an independent predictive factor of poor PFS (hazard ratio [HR] = 1.97, 95% confidence interval [CI] = 1.23–3.16; <i>p</i> = 0.005). <i>PON1</i> rs662 AA/AG genotype was significantly associated with poor OS (HR = 1.95, 95% CI = 1.07–3.54; <i>p</i> = 0.029). No associations were detected between the nine SNPs and DCR.</p><p>Conclusions</p><p><i>NQO1</i> rs1800566 is an independent predictive factor of PFS for MGC patients treated with EOF chemotherapy, and <i>PON1</i> rs662 is a noteworthy prognostic factor of OS. Information on oxidative stress-related genetic variants may facilitate optimization of individualized chemotherapy in clinical practice.</p></div

Comparisons of Kaplan-Meier PFS and OS curve between <i>NQO1</i> rs1800566 and <i>PON1</i> rs662 genotypes among subgroups.

<p><b>(A, B)</b> PFS and OS for rs1800566 in dominant model. CT/TT carriers (dotted line, <i>n</i> = 70) have a significantly shorter PFS than CC carriers (solid line, <i>n</i> = 38). Median PFS for CC and CT/TT genotype: 231.0 <i>vs.</i> 156.0 days, <i>p</i> = 0.008, log-rank test; median OS: 565.0 <i>vs.</i> 444.0 days, <i>p</i> = 0.188, log-rank test. <b>(C, D)</b> PFS and OS among patients in rs662 genotype subgroups. GG carriers (dotted line, <i>n</i> = 42) live significantly longer than AA/AG carriers (solid line, <i>n</i> = 61). Median PFS for GG and AA/AG genotype: 166.0 <i>vs.</i> 178.0 days, <i>p</i> = 0.781, log-rank test; median OS: 565.0 <i>vs.</i> 299.0 months, <i>p</i> = 0.056, log-rank test.</p

Allele and genotype distribution in controlled and uncontrolled patients.

<p>*Presented as n (frequency).</p><p>**Fisher’s <i>p</i>-value for all genotype frequency comparisons between the controlled and uncontrolled patients, as well as allele frequency comparisons for rs854560, rs1799895, rs2266637.</p><p>***Odds ratio cannot be calculated for no uncontrolled patient carries T allele of rs854560 or A allele of rs2266637.</p><p>Allele and genotype distribution in controlled and uncontrolled patients.</p

Additional file 1: of The polycomb group protein EZH2 induces epithelial–mesenchymal transition and pluripotent phenotype of gastric cancer cells by binding to PTEN promoter

Materials and Methods. Table S1. Relationship between EZH2 expression and clinicopathologic parameters of gastric cancer patients. Table S2. Univariate and multivariate analysis of clinicopathological factors for disease-free survival in gastric cancer (qRT-PCR cohort). Table S3. Univariate and multivariate analysis of clinicopathological factors for overall survival in gastric cancer (qRT-PCR cohort). Table S4. Univariate and multivariate analysis of clinicopathological factors for overall survival in gastric cancer (IHC cohort). Table S5. Correlation analysis of expression of stem cell related factors with EZH2. Table S6. Primers and siRNA sequences used in this study. (DOCX 67 kb

Nine SNPs in the seven oxidative stress-related genes analyzed in the study.

<p>*HCB: Han Chinese Beijing. NA: Not available in dbSNP.</p><p>**HWE: Hardy-Weinberg equilibrium. HWE is tested in all patients.</p><p>Nine SNPs in the seven oxidative stress-related genes analyzed in the study.</p

Multivariate PFS and OS analysis with Cox regression.

<p>*Significant <i>p-</i>values (<i>p</i><0.05) are in bold.</p><p>**<i>P-</i>value is calculated in patients with classified pathological stage.</p><p>***Only rs662 and number of lesions are included in the OS analysis based on results in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116027#pone-0116027-t003" target="_blank">Table 3</a>.</p><p>HR: hazard ratio. NA: Not available.</p><p>Multivariate PFS and OS analysis with Cox regression.</p

PFS and OS analysis with Kaplan-Meier method and log-rank test.

<p>*Factors at <i>p</i><0.1 level enter into Cox regression analysis. <i>P-</i>values for further analysis (<i>p</i><0.1) are in bold.</p><p>**95% CI cannot be calculated as 3 out of 5 individuals in the subgroup are censored.</p><p>***ECOG is one of the first publicly funded cooperative groups to perform multi-center clinical trials for cancer research in USA. ECOG score is a commonly used scoring system for evaluating patients’ performance status.</p><p>PFS and OS analysis with Kaplan-Meier method and log-rank test.</p