Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer

Cancer shared this article with you from Inoreader Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer Via Latest Results for BMC Cancer Abstract Background Cervical cancer (CC) is one of the most common gynaecological cancers. The gene signature is believed to be reliable for predicting cancer patient survival. However, there is no relevant study on the relationship between the glycolysis-related gene (GRG) signature and overall survival (OS) of patients with CC. Methods We extracted the mRNA expression profiles of 306 tumour and 13 normal tissues from the University of California Santa Cruz (UCSC) Database. Then, we screened out differentially expressed glycolysis-related genes (DEGRGs) among these mRNAs. All patients were randomly divided into training cohort and validation cohort according to the ratio of 7: 3. Next, univariate and multivariate Cox regression analyses were carried out to select the GRG with predictive ability for the prognosis of the training cohort. Additionally, risk score model was constructed and validated it in the validation cohort. Results Six mRNAs were obtained that were associated with patient survival. The filtered mRNAs were classified into the protective type (GOT1) and the risk type (HSPA5, ANGPTL4, PFKM, IER3 and PFKFB4). Additionally, by constructing the prognostic risk score model, we found that the OS of the high-risk group was notably poorer, which showed good predictive ability both in training cohort and validation cohort. And the six-gene signature is a prognostic indicator independent of clinicopathological features. Through the verification of PCR, the results showed that compared with the normal cervial tissuses, the expression level of six mRNAs were significantly higher in the CC tissue, which was consistent with our findings. Conclusions We constructed a glycolysis-related six-gene signature to predict the prognosis of patients with CC using bioinformatics methods. We provide a thorough comprehension of the effect of glycolysis in patients with CC and provide new targets and ideas for individualized treatment. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Risk stratification for prediction of locoregional recurrence in patients with pathologic T1–2N0 breast cancer after mastectomy

Cancer shared this article with you from Inoreader Risk stratification for prediction of locoregional recurrence in patients with pathologic T1–2N0 breast cancer after mastectomy Via Latest Results for BMC Cancer Abstract Background Previous studies have revealed that nearly 15–20% of selected high-risk T1–2N0 breast cancers developed LRR after mastectomy. This study is aim to indentify the risk factors of locoregional recurrence (LRR) in patients with pathologic T1–2N0 breast cancer after mastectomy in a real-world and distinguish individuals who warrant postmastectomy radiotherapy (PMRT). Methods Female patients treated from 1999 to 2014 in National Cancer Center of China were retrospectively reviewed. A competing risk model was developed to estimate the cumulative incidence of LRR with death treated as a competing event. Results A total of 4841 patients were eligible. All underwent mastectomy plus axillary nodes dissection or sentinel node biopsy without PMRT. With a median follow-up of 56.4 months (range, 1–222 months), the 5-year LRR rate was 3.9%.Besides treatment era, age ≤ 40 years old (p < 0.001, hazard ratio [HR] = 2.262), tumor located in inner quadrant (p < 0.001, HR = 2.236), T2 stage (p = 0.020, HR = 1.419), and negative expressions of estrogen receptor (ER) and progesterone receptor (PR) (p = 0.032, HR = 1.485), were patients-related independent risk factors for LRR. The 5-year LRR rates were 1.7, 3.5, and 15.0% for patients with zero, 1–2, and 3–4 risk factors (p < 0.001). Conclusions Risk Stratification based on age, T stage, ER/PR status and tumor location can stratify patients with pT1–2 N0 breast cancer into subgroups with different risk of LRR. PMRT might be suggested for patients with 3–4 risk factors. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Association between five types of Tumor Necrosis Factor-α gene polymorphism and hepatocellular carcinoma risk: a meta-analysis

Cancer shared this article with you from Inoreader Association between five types of Tumor Necrosis Factor-α gene polymorphism and hepatocellular carcinoma risk: a meta-analysis Via Latest Results for BMC Cancer Abstract Background Research focusing on the relationship between five types of tumor necrosis factor-alpha (TNF-α) SNPs and the risk of hepatocellular carcinoma (HCC) were still controversial. Hereby, we performed a meta-analysis to determine the association between TNF-α promoter SNPs: -1031 T/C, − 863 C/A, − 857 C/T, − 308 G/A, and − 238 G/A with HCC risk. Methods We interrogated articles from journal database: PubMed, Pro-Quest, EBSCO, Science Direct, and Springer to determine the relationship between five types of SNPs in TNF-α gene with HCC risk. RevMan 5.3 software was used for analysis in fixed/random effect models. Results This meta-analysis included 23 potential articles from 2004 to 2018 with 3237 HCC cases and 4843 controls. We found that SNP − 863 C/A were associated with a significantly increased HCC risk (A vs C, OR = 1.31, 95% CI = 1.03–1.67). Similar results were obtained in − 857 C/T (TT/CT vs CC, OR = 1.31, 95% CI = 1.06–1.62), − 308 G/A (AA vs GG, OR = 3.14, 95% CI = 2.06–4.79), and − 238 G/A (AA vs GG, OR = 3.87, 95% CI = 1.32–11.34). While no associations were observed between SNP TNF-α − 1031 T/C and HCC risk. Conclusions The present meta-analysis showed that TNFα SNPs -863C/A, − 857 C/T, − 308 G/A, and − 238 G/A were associated with the risk of HCC. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

STAT3 regulates miR93-mediated apoptosis through inhibiting DAPK1 in renal cell carcinoma

Cancer shared this article with you from Inoreader STAT3 regulates miR93-mediated apoptosis through inhibiting DAPK1 in renal cell carcinoma Via Cancer Gene Therapy - Issue - nature.com science feeds View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients

Cancer shared this article with you from Inoreader Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients Via Latest Results for BMC Cancer Abstract Background The epithelial-mesenchymal transition (EMT) plays a pivotal role in various physiological processes, such as embryonic development, tissue morphogenesis, and wound healing. EMT also plays an important role in cancer invasion, metastasis, and chemoresistance. Additionally, EMT is partially responsible for chemoresistance in colorectal cancer (CRC). The aim of this research is to develop an EMT-based prognostic signature in CRC. Methods RNA-seq and microarray data, together with clinical information, were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. A total of 244 differentially expressed EMT-related genes (ERGs) were obtained by comparing the expression between normal and tumor tissues. An EMT-related signature of 11 genes was identified as crucially related to the overall survival (OS) of patients through univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and Cox regression analysis. Finally, we established a clinical nomogram to predict the survival possibility of CRC patients by integrating clinical characteristics and the EMT-related gene signature. Results Two hundred and forty-four differentially expressed ERGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that EMT-related signaling pathway genes were highly related to CRC. Kaplan-Meier analysis revealed that the 11-EMT signature could significantly distinguish high- and low-risk patients in both TCGA and GEO CRC cohorts. In addition, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusion We developed a novel EMT-related gene signature for the prognosis prediction of CRC patients, which could improve the individualized outcome prediction in CRC. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Overriding sorafenib resistance via blocking lipid metabolism and Ras by sphingomyelin synthase 1 inhibition in hepatocellular carcinoma

Cancer shared this article with you from Inoreader Overriding sorafenib resistance via blocking lipid metabolism and Ras by sphingomyelin synthase 1 inhibition in hepatocellular carcinoma Via Latest Results for Cancer Chemotherapy and Pharmacology Abstract Background The survival benefit of sorafenib, the most used drug for advanced hepatocellular carcinoma (HCC), is unsatisfactory due to the development of adaptive resistance. Exploring the mechanisms underlying sorafenib resistance is important to develop sensitizing strategy. Sphingomyelin synthase (SMS) plays a critical role in sphingolipid metabolism which is involved in oncogenesis and drug resistance. Methods SMS1 and SMS2 levels in HCC cells in response to prolonged chemotherapy were analyzed using ELISA. mRNA and protein levels of SMS in HCC and adjacent normal tissues were analyzed by ELISA and real-time PCR. The roles of SMS and its downstream targets were investigated using cellular and biochemical assays and mass spectrometry. Results SMS1, but not SMS2, was upregulated in HCC in response to sorafenib treatment, although HCC displayed similar RNA and protein level of SMS1 compared to adjacent normal liver tissues. Overexpression of SMS1 promoted HCC growth and migration, and alleviated sorafenib's toxicity. SMS1 inhibition via genetic and pharmacological approaches consistently resulted in inhibition of growth and migration, and apoptosis induction in sorafenib-resistance HCC cells. SMS1 inhibition also augmented the efficacy of sorafenib in sensitive HCC cells. SMS1 inhibition disrupted sphingolipid metabolism via accumulating ceramide and decreasing sphingomyelin, inducing mitochondrial dysfunction and oxidative stress, and decreasing Ras activity in resistant cells. Overexpression of constitutively active Ras reversed the inhibitory effects of SMS1 inhibition. Although SMS1 overexpression did not affect Ras expression and activity, Pearson correlation coefficient analysis of SMS1 and Ra s expression demonstrated that there was positive correlation between SMS1 and RAS (NRAS, R = 0.55, p < 0.01; KRAS, R = 0.44, p < 0.01). Conclusions Our work is the first to suggest that SMS1 plays a more important role in sorafenib resistance than tumorigenesis, and provides preclinical evidence to overcome sorafenib resistance with SMS1 inhibition in HCC. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.

Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma

Cancer shared this article with you from Inoreader Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma Via Latest Results for BMC Cancer Abstract Background Hepatocellular carcinoma (HCC) is among the deadliest forms of cancer. While RNA-binding proteins (RBPs) have been shown to be key regulators of oncogenesis and tumor progression, their dysregulation in the context of HCC remains to be fully characterized. Methods Data from the Cancer Genome Atlas - liver HCC (TCGA-LIHC) database were downloaded and analyzed in order to identify RBPs that were differentially expressed in HCC tumors relative to healthy normal tissues. Functional enrichment analyses of these RBPs were then conducted using the GO and KEGG databases to understand their mechanistic roles. Central hub RBPs associated with HCC patient prognosis were then detected through Cox regression analyses, and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, univariate and multivariate Cox regression analyses, and nomograms. Lastly, the relationship between individual hub RBPs and HCC patient overall survival (OS) was evaluated using Kaplan-Meier curves. Finally, find protein-coding genes (PCGs) related to hub RBPs were used to construct a hub RBP-PCG co-expression network. Results In total, we identified 81 RBPs that were differentially expressed in HCC tumors relative to healthy tissues (54 upregulated, 27 downregulated). Seven prognostically-relevant hub RBPs (SMG5, BOP1, LIN28B, RNF17, ANG, LARP1B, and NR0B1) were then used to generate a prognostic model, after which HCC patients were separated into high- and low-risk groups based upon resultant risk score values. In both the training and test datasets, we found that high-risk HCC patients exhibited decreased OS relative to low-risk patients, with time-dependent area under the ROC curve values of 0.801 and 0.676, respectively. This model thus exhibited good prognostic performance. We additionally generated a prognostic nomogram based upon these seven hub RBPs and found that four other genes were significantly correlated with OS. Conclusion We herein identified a seven RBP signature that can reliably be used to predict HCC patient OS, underscoring the prognostic relevance of these genes. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.