A Nomogram to Predict Benign/Malignant Mediastinal Lymph Nodes Based on EBUS Sonographic Features.

Background: Endobronchial ultrasound (EBUS) sonographic features help identify benign/malignant lymph nodes while conducting transbronchial needle aspiration (TBNA). This study aims to identify risk factors for malignancy based on EBUS sonographic features and to estimate the risk of malignancy in lymph nodes by constructing a nomogram. Methods: 1082 lymph nodes from 625 patients were randomly enrolled in training (n = 760) and validation (n = 322) sets. The subgroup of EBUS-TBNA postoperative negative lymph nodes (n = 317) was randomly enrolled in a training (n = 224) set and a validation (n = 93) set. Logistic regression analysis was used to identify the EBUS features of malignant lymph nodes. A nomogram was formulated using the EBUS features in the training set and later validated in the validation set. Results: Multivariate analysis revealed that long-axis, short-axis, echogenicity, fusion, and central hilar structure (CHS) were the independent predictors of malignant lymph nodes. Based on these risk factors, a nomogram was constructed. Both the training and validation sets of 5 EBUS features nomogram showed good discrimination, with area under the curve values of 0.880 (sensitivity = 0.829 and specificity = 0.807) and 0.905 (sensitivity = 0.819 and specificity = 0.857). Subgroup multivariate analysis revealed that long-axis, echogenicity, and CHS were the independent predictors of malignancy outcomes of EBUS-TBNA postoperative negative lymph nodes. Based on these risk factors, a nomogram was constructed. Both the training and validation sets of 3 EBUS features nomogram showed good discrimination, with the area under the curve values of 0.890 (sensitivity = 0.882 and specificity = 0.786) and 0.834 (sensitivity = 0.930 and specificity = 0.636). Conclusions: Our novel scoring system based on two nomograms can be utilized to predict malignant lymph nodes.

Computed tomography radiomics signature via machine learning predicts RRM2 and overall survival in hepatocellular carcinoma.

Background: Radiomics can be used to noninvasively predict molecular markers to address the clinical dilemma that some patients cannot accept invasive procedures. This research evaluated the prognostic significance of the expression level of ribonucleotide reductase regulatory subunit M2 (RRM2) in individuals with hepatocellular carcinoma (HCC) and established a radiomics model for predicting the RRM2 expression level. Methods: Genomic data for HCC patients and corresponding computed tomography (CT) images were accessed at The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA), which were utilized for prognosis analysis, radiomic feature extraction and model construction, respectively. The maximum relevance minimum redundancy algorithm (mRMR) and recursive feature elimination (RFE) were used for feature selection. Following feature extraction, a logistic regression algorithm was fitted to establish a dichotomous model that predicts RRM2 gene expression. Establishment of the radiomics nomogram was carried out using the Cox regression model. Receiver operating characteristic (ROC) curve analysis was employed to assess the model performance. Clinical utility was determined by decision curve analysis (DCA). Results: High RRM2 expression acted as a risk factor for overall survival (OS) [hazard ratio (HR) =2.083, P<0.001] and was implicated in regulation of the immune response. Four optimal radiomics features were selected for prediction of RRM2 expression. A predictive nomogram was established using the clinical variables and radiomics score (RS), and the areas under the ROC curve (AUCs) of the time-dependent ROC curve of the model were 0.836, 0.757, and 0.729 for the 1-, 3-, and 5-year periods, respectively. DCA confirmed that the nomogram had good clinical usefulness. Conclusions: The RRM2 expression level in HCC can considerably affect prognosis of these patients. Expression levels of RRM2 and prognosis of HCC individuals can be predicted through radiomics features by utilizing CT scan data.

Inhibition of TNF-α and JNK Signaling Pathway Can Reduce Paclitaxel-Induced Apoptosis of Mouse Cardiomyocytes.

Paclitaxel (PTX) is a widely used chemotherapeutic drug for treating tumors. However, studies have shown that it can cause cardiac problems such as arrhythmia, myocarditis, chronic cardiomyopathy, and heart failure. Therefore, it is essential to study the mechanism behind the cardiotoxicity of PTX in tumor treatment. In this study, we initially injected PTX into mice to establish a myocardial cell apoptosis model to observe the degree of damage to mouse myocardium caused by PTX. Upon determining the levels of mouse myocardial creatine phosphokinase (CK), myokinase isoenzyme (CK-MB), aspartate transaminase (AST), and lactate dehydrogenase (LDH), we found that all of these levels showed apparent increases in mice treated with PTX. Further analyses of the TNF-α level and the expression of Jun N-terminal kinase (JNK) and Bcl-2 family-related proteins in myocardial tissue were performed. It was found that PTX increased the protein levels of TNF-α, Bax, p-JNK, and JNK in myocardial tissue but decreased the protein level of Bcl-2. After 1 month of PTX treatment in mice, we inhibited the expression of TNF-α and JNK proteins, which reduced the effect of paclitaxel on the apoptosis of mouse cardiomyocytes. The protein levels of Bax, p-JNK, and TNF-α in cardiomyocytes were reduced, while there was a relative increase in the Bcl-2 protein level. The findings suggested that inhibition of the NK signaling pathway and TNF-α can lessen the effect of PTX on mouse cardiomyocytes.

Downregulation of the enhancer of zeste homolog 1 transcriptional factor predicts poor prognosis of triple-negative breast cancer patients.

Background: Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer and lacks effective biomarkers. This study seeks to unravel the expression status and the prospective transcriptional mechanisms of EZH1/EZH2 in TNBC tissue samples. Moreover, another objective of this study is to reveal the prognostic molecular signatures for risk stratification in TNBC patients. Methods: To determine the expression status of EZH1/EZH2 in TNBC tissue samples, microarray analysis and immunohistochemistry were performed on in house breast cancer tissue samples. External mRNA expression matrices were used to verify its expression patterns. Furthermore, the prospective transcriptional mechanisms of EZH1/EZH2 in TNBC were explored by performing differential expression analysis, co-expression analysis, and chromatin immunoprecipitation sequencing analysis. Kaplan-Meier survival analysis and univariate Cox regression analysis were utilized to detect the prognostic molecular signatures in TNBC patients. Nomogram and time-dependent receiver operating characteristic curves were plotted to predict the risk stratification ability of the prognostic-signatures-based Cox model. Results: In-house TMAs (66 TNBC vs. 106 non-TNBC) and external gene microarrays, as well as RNA-seq datasets (1,135 TNBC vs. 6,198 non-TNBC) results, confirmed the downregulation of EZH1 at both the protein and mRNA levels (SMD = -0.59 [-0.80, -0.37]), as is opposite to that of EZH2 (SMD = 0.74 [0.40, 1.08]). The upregulated transcriptional target genes of EZH1 were significantly aggregated in the cell cycle pathway, where CCNA2, CCNB1, MAD2L1, and PKMYT1 were determined as key transcriptional targets. Additionally, the downregulated transcriptional targets of EZH2 were enriched in response to the hormone, where ESR1 was identified as the hub gene. The six-signature-based prognostic model produced an impressive performance in this study, with a training AUC of 0.753, 0.981, and 0.977 at 3-, 5-, and 10-year survival probability, respectively. Conclusion: EZH1 downregulation may be a key modulator in the progression of TNBC through negative transcriptional regulation by targeting CCNA2, CCNB1, MAD2L1, and PKMYT1.

Preoperative Neutrophil-BMI Ratio As a Promising New Marker for Predicting Tumor Outcomes in Colorectal Cancer.

Background: Inflammation and nutritional status are highly associated with colorectal cancer (CRC) prognosis. This study aimed to evaluate the prognostic value of the preoperative neutrophil-BMI ratio (NBR) in patients with CRC. Methods: A retrospective analysis was performed on 2471 patients with CRC who underwent surgical resection between 2004 and 2019. Patients were divided into two groups based on the cutoff value for NBR. Cox regression and Kaplan-Meier curves were used to evaluate overall survival (OS). Results: High NBR was associated with female sex, low BMI, colon, right-sided CRC, poor differentiation, T3 to 4 stage, M1 to 2 stage, high carcinoembryonic antigen (CEA) level, III-IV stage, microsatellite instability (MSI), and no adjuvant chemotherapy (all P < .05). The high NBR group had a shorter OS than the low NBR group. Female and right sided patients with CRC and with high NBR had a worse prognosis. Univariate Cox regression suggested that NBR was significantly associated with poor prognosis. Multivariate analysis confirmed that age (P = .019,HR:1.012), differentiation (P = .001,HR:1.306), TNM stage (P < .001,HR:2.432), CEA (P = .014,HR:1.001), and NBR (P < .001, HR: 3.309) were independent poor prognostic factors for OS. Subgroup univariate analysis indicated that female patients with high NBR had a worse prognosis. A nomogram composed of TNM stage, CEA, and NBR was developed, and internal validation was based on female patients with CRC. The nomogram provided good discrimination for both the training and validation sets, with area under the curve values of 0.79 and 0.769, respectively. Conclusions: High preoperative levels of NBR are indicators of poor prognosis in patients with CRC.

Clinical Significance of the HHLA2 Protein in Hepatocellular Carcinoma and the Tumor Microenvironment.

BACKGROUND: The protein "human endogenous retrovirus H long terminal repeat-associating 2" (HHLA2), a member of the B7 family, has been linked to cancer progression and immune responses. However, its functional role in hepatocellular carcinoma (HCC) remains unknown. METHODS: Bioinformatics was used to examine the potential roles of HHLA2 in HCC and the molecular pathways involved. Expression of HHLA2 and PD-L1 as well as the density of tumor-infiltrating lymphocytes (TILs) in tumoral areas were evaluated by immunohistochemistry and hematoxylin-eosin staining of 202 resected human HCC samples. Potential correlations of HHLA2 expression with pathological characteristics or prognosis of HCC patients were explored. Different types of immune microenvironment in HCC were defined based on HHLA2 expression and TIL density. RESULTS: High HHLA2 levels in HCC correlated with more advanced clinical cancer stage (P = 0.040), multiple tumors (P = 0.044), poor tumor differentiation (P = 0.048), microvascular invasion (P = 0.011) and hepatic capsule invasion (P = 0.047). HHLA2 levels correlated significantly with density of TILs, but not with PD-L1 levels. High HHLA2 levels were associated with worse prognosis. Intermediate and high TIL densities were independent predictors of better prognosis. Tumor microenvironments with type I (HHLA2 - high TILs +) or type IV (HHLA2 - low TILs +) were associated with better prognosis. CONCLUSION: HHLA2 level can independently predict worse prognosis and affect the tumor microenvironment in HCC, which may help guide immunotherapy against the cancer.

H Long Terminal Repeat-Associating 2 (HHLA2) is a Biomarker of Advanced Stage Hepatocellular Carcinoma and Promotes Tumor Cell Development In Vitro.

BACKGROUND Several risk factors contribute to the inflammation promoting hepatocellular carcinoma (HCC) development, but the underlying mechanisms are unknown. Human endogenous retrovirus H long terminal repeat-associating 2 (HHLA2), a B7 family member, is highly expressed in various malignant tumor tissues and is related to tumor progression and metastasis. MATERIAL AND METHODS Bioinformatics analysis was used to analyze the gene expression chip GSE33006 of HCC tissue in the GEO database, draw a heat map of differentially expressed genes, and analyze the GO pathway of gene function annotation. Then, we compared HCC tissues with para-carcinoma liver tissues from 55 patients for expression patterns and associations with HHLA2. Effects of HHLA2 knockdown were examined in the human HCC cell line HepG2 to explore effects of HHLA2 on HepG2 cells. RESULTS A significantly higher expression of HHLA2 at the mRNA and protein levels was detected in HCC tissues than in para-carcinoma liver tissues, which was similar to HHLA2 expression in the GSE33006 data. A higher expression of HHLA2 protein was associated with advanced cancer stage, tumor differentiation, and invasion of adjacent structures. In vitro knockdown of HHLA2 expression significantly increased HepG2 cell adhesion, promoted cell apoptosis, induced cell cycle arrest in the G1/S phase, and inhibited cell proliferation, migration, and invasion. CONCLUSIONS Our data indicated there was a higher expression of HHLA2 in HCC tissues than in para-carcinoma liver tissues, and HHLA2 plays a major role in the development and progression of HCC. Owing to its higher expression, HHLA2 is a potential prognostic biomarker for HCC.

Profiles of alternative splicing events in the diagnosis and prognosis of Gastric Cancer.

Background: Gastric cancer (GC) is a heterogeneous disease, and alternative splicing (AS) is a powerful universal transcriptional regulatory mechanism that contributes to the occurrence and development of cancer. However, the systematic analysis of AS events in GC is lacking; therefore, further studies are needed. Methods: Genome-wide analysis of AS events was performed using RNA-Seq data to evaluate the difference between GC and adjacent tissues at the AS level. Prognostic signatures based on differentially expressed alternative splicing (DEAS) events and a correlation network between DEAS and genes were built. Results: We identified 48,141 AS events, of which 2325 showed differential expression patterns. The parental genes before DEAS events play an essential role in regulating GC-related processes such as ribosome (FDR < 0.0001) and thermogenesis (FDR = 0.0002). There were 76 survival-associated DEAS cases. Stratifying patients according to the percent spliced in index value of six types of splicing patterns formed significant Kaplan-Meier curves in the overall survival analysis. A prognostic feature based on DEAS performed well for stratification in patients with GC. Conclusion: The present study will enrich our understanding regarding the distinction of GC and provide a generous amount of biomarkers and potential targets for the treatment of GC.

Risk scoring based on expression of long non­coding RNAs can effectively predict survival in hepatocellular carcinoma patients with or without fibrosis.

Patients with hepatocellular carcinoma (HCC) have different prognoses depending on whether or not they also have fibrosis. Since long non­coding RNAs (lncRNAs) affect tumor formation and progression, the present study aimed to investigate whether their expression might help predict the survival of patients with HCC. Expression profiles downloaded from The Cancer Genome Atlas database were examined to identify lncRNAs differentially expressed (DElncRNAs) between HCC patients with or without fibrosis. These DElncRNAs were then used to develop a risk scoring system to predict overall survival (OS) or recurrence­free survival (RFS). A total of 142 significant DElncRNAs were identified using data from 135 patients with fibrosis and 72 without fibrosis. For HCC patients with fibrosis, a risk scoring system to predict OS was constructed based on five lncRNAs (AL359853.1, Z93930.3, HOXA­AS3, AL772337.1 and AC012640.3), while the risk scoring system to predict RFS was based on 12 lncRNAs (PLCE1­AS1, Z93930.3, LINC02273, TRBV11­2, HHIP­AS1, AC004687.1, LINC01857, AC004585.1, AP000808.1, CU638689.4, AC090152.1 and AL357060.1). For HCC patients without fibrosis, the risk scoring system to predict OS was established based on seven lncRNAs (LINC00239, AC104971.4, AP006285.2, HOXA­AS3, AC079834.2, NRIR and LINC01929), and the system to predict RFS was based on five lncRNAs (AC021744.1, NRIR, LINC00487, AC005858.1 and AC107398.3). Areas under the receiver operating characteristic curves for all risk scoring systems exceeded 0.7. Uni­ and multivariate Cox analyses showed that the risk scoring systems were significant independent predictors of OS for HCC patients with fibrosis, or of OS and RFS for HCC patients without fibrosis, after adjusting for clinical factors. Functional enrichment analysis suggested that, depending on the risk scoring system, highly associated genes were involved in pathways mainly associated with the cell cycle, chemokines, Th17 cell differentiation or thermogenesis. The findings of the present study indicate that risk scoring systems based on lncRNA expression can effectively predict the OS of HCC patients with fibrosis as well as the OS or RFS of HCC patients without fibrosis.

Comprehensive analysis of biological networks and the eukaryotic initiation factor 4A-3 gene as pivotal in hepatocellular carcinoma.

Eukaryotic initiation factor 4A-3 (EIF4A3) is a core component of the exon junction complex (EJC). Abnormalities in EIF4A3 are associated with carcinogenesis. The present study aimed to determine the biological role of EIF4A3 in hepatocellular carcinoma (HCC). Our study is based on the analysis of HCC sequencing data from public databases. We first used the Gene Expression Profiling Interactive Analysis tool and ONCOMINE to analyze the EIF4A3 expression, and the results were validated in human clinical tissues by a quantitative real-time polymerase chain reaction, Western blot, and immunohistochemical. Then, we used cBioPortal to identify EIF4A3 alterations and function networks. Finally, we created a network of genes that were positively correlated with EIF4A3 using LinkedOmics, and analyzed this network using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. For the genes identified, we also analyzed the relevant kinase and transcription factor target networks as well as the protein-protein interaction networks. Our results show that EIF4A3 was overexpressed in HCC tissues in comparison with normal tissues, and high EIF4A3 expression was significantly associated with poor prognosis. Analysis of the functional networks of genes that were co-occurring with EIF4A3 amplification revealed connections with several chemokine signaling pathways. Furthermore, genes that positively correlated with EIF4A3 were mainly related to cell cycle and spliceosome pathways, several cell cycle regulatory kinases, and tumor-associated transcription factors. Finally, crosslinking-immunoprecipitation and high-throughput sequencing (CLIP-seq) data showed that EIF4A3 protein binds to multiple exon regions of the cell cycle regulatory genes cyclin-dependent kinases 1 and 2 and transcription factor E2F1. Our study unveils potential biological networks in HCC and the pivotal role of EIF4A3 as a bridging protein, highlighting the need for an in-depth study of EIF4A3 in carcinogenesis.

A twenty gene-based gene set variation score reflects the pathological progression from cirrhosis to hepatocellular carcinoma.

The molecular mechanism of the pathological progression from cirrhosis to hepatocellular carcinoma (HCC) remains elusive. In the present study, tissue samples from normal liver, cirrhosis and HCC were subjected to differentially gene expression analysis, weighted gene correlation network analysis to identify the twenty hub genes (TOP2A, CDC20, PTTG1, CDCA5, CCNB2, PRC1, KIF20A, SF3B4, HSP90AB1, FOXD2, PLOD3, CCT3, SETDB1, VPS45, SPDL1, RACGAP1, MED24, KIAA0101, ZNF282, and USP21) in the pathological progression from cirrhosis to HCC. Each sample was calculated a hub gene set variation analysis (HGSVA) score using Gene Set Variation Analysis, The HGSVA score significantly increased with progression from cirrhosis to HCC, and this result was validated in two independent data sets. Moreover, this score may be used as a blood-based marker for HCC and is an independent prognostic factor of recurrence-free survival (RFS) and overall survival (OS). High expression of the hub genes may be driven by hypomethylation. The twenty gene-based gene set variation score may reflect the pathological progression from cirrhosis to HCC and is an independent prognostic factor for both OS and RFS.

A nomogram to predict vascular invasion before resection of colorectal cancer.

Vascular invasion (VI) is an important feature for systemic recurrence and an indicator for the application of adjuvant therapy in colorectal cancer (CRC). Preoperative knowledge of VI is important in determining whether adjuvant therapy is necessary, as well as the adequacy of surgical resection. In the present study, a predictive nomogram for VI in patients with CRC was constructed. The prediction model consisted of 664 eligible patients with CRC, who were divided into a training set (n=468) and a validation set (n=196). Data were collected between August 2013 and April 2018. The feature selection model was established using the least absolute shrinkage and selection operator regression model. Multivariable logistic regression analysis was used to construct the predictive nomogram. The performance of the nomogram was evaluated by calibration, discrimination and clinical usefulness. Differentiation, computed tomography (CT)-based on N stage (CT N stage), hemameba and tumor distance from the anus (cm) were integrated into the nomogram. The nomogram exhibited good discrimination, with an area under the curve (AUC) of 0.731 and good calibration. Application of the nomogram in the validation cohort showed acceptable discrimination, with an AUC of 0.710 and good calibration. Decision curve analysis revealed that the nomogram was clinically useful. These findings suggests, to the best of our knowledge, that this may be the first nomogram for individual preoperative prediction of VI in patients with CRC, which may promote preoperative optimization strategies for this selected group of patients.

Postoperative morbidity and mortality after neoadjuvant chemotherapy versus upfront surgery for locally advanced gastric cancer: a propensity score matching analysis.

BACKGROUND: Cohort studies have shown that neoadjuvant chemotherapy (NAC) is not associated with increased risk of postoperative complications and mortality as compared to upfront surgery (SURG). OBJECTIVE: The aim of this study was to compare postoperative morbidity and mortality after NAC with SURG. PATIENTS AND METHODS: Patients who underwent gastrectomy with D2 lymphadenectomy for advanced gastric cancer (GC) between 2010 and 2017 were selected. The impact of neoadjuvant chemotherapy on surgical safety was investigated by using propensity score matching. RESULTS: Three hundred and seventy-seven patients were included. After propensity score matching, 86 patients in each group were matched. The percentage of patients with one or more complications was 10.5% in NAC group and 15.1% in SURG group (P=0.361), there was no mortality developed in either group. The total blood loss was significantly more in the NAC group than that in the SURG group (320.79 vs 243.37 ml, P<0.04). In univariate and multivariate of the matched cohort, sex, age (<70), BMI (<24), ASA grade, surgical procedure (open vs laparoscopy), gastrectomy extent, cTNM and Charlson index comorbidity were not associated with postoperative complications (all P>0.05). CONCLUSION: This study showed that postoperative morbidity and mortality were similar for NAC group and SURG group.

Associations between three XRCC1 polymorphisms and hepatocellular carcinoma risk: A meta-analysis of case-control studies.

Conflicting results have been obtained regarding the association between X-ray repair cross complementation group 1 (XRCC1) and susceptibility to hepatocellular carcinoma (HCC). In this study, associations between HCC and three polymorphisms (Arg194Trp, Arg280His, and Arg399Gln) were evaluated using a meta-analysis approach. PubMed, Web of Science, Cochrane Library, the Chinese National Knowledge Infrastructure, and the Wanfang standard database were systematically searched to identify all relevant case-control studies published through March 2018. A total of 32 case-control studies, including 13 that evaluated Arg194Trp, 14 that evaluated Arg280His, and 26 that evaluated Arg399Gln, were analyzed. In the entire study population, XRCC1 Arg399Gln was significantly associated not only with overall risk of HCC (homozygous model, OR = 1.61, 95% CI: 1.40-1.85, P < 0.05; recessive model, OR = 1.40, 95% CI: 1.23-1.59, P < 0.05) but also with the risk of HCC in Chinese patients (homozygous model, OR = 1.78, 95% CI: 1.53-2.08, P < 0.05; recessive model, OR = 1.47, 95% CI: 1.27-1.70, P < 0.05). Limiting the analysis to studies demonstrating Hardy-Weinberg equilibrium (HWE), the results were consistent and robust. Similarly, a significant association between XRCC1 Arg399Gln and HCC risk was found in healthy controls in the general population but not in hospital controls. Trial sequential analysis (TSA), false-positive report probabilities (FPRP), and combined genotype analysis revealed that XRCC1 Arg399Gln is mainly associated with susceptibility to liver cancer. However, there was no association between Arg194Trp or Arg280His and the risk of HCC. These results, indicating that the Arg399Gln polymorphism of XRCC1 is associated with the risk of HCC in the Chinese population, provide a basis for the development of improved detection and treatment approaches.

Fas-associated factor 1 inhibits tumor growth by suppressing Helicobacter pylori-induced activation of NF-κB signaling in human gastric carcinoma.

Loss of Fas-associated factor 1 (FAF1) may act as a pro-survival signal in diseased cells, but whether this is true in gastric carcinoma remains unclear. Here we report that FAF1 was expressed at low levels in gastric carcinoma tissues and cell lines, and its expression correlated with larger tumors, higher histology grade, higher TNM stage, tumor infiltration, and lymph node metastasis. Univariate analysis and survival curve analysis identified low FAF1 expression as a predictor of poor prognosis. FAF1 overexpression in HGC-27 gastric cancer cells induced cell apoptosis and inhibited cell proliferation and growth. It also reduced colony formation in vitro and tumor growth in mice. We found that Helicobacter pylori, a risk factor for gastric cancer, down-regulated FAF1 expression via NF-κB signaling. Knock-down of IKKß or p65 expression in gastric cancer cells reversed H. pylori-induced down-regulation of FAF1 expression and partially blocked H. pylori-induced secretion of inflammatory cytokines TNF-α and IL-8. Our results suggest that loss of FAF1 contributes to human gastric carcinogenesis by allowing H. pylori to activate NF-κB signaling.

The Relationship between Telomerase Activity and Clinicopathological Parameters in Colorectal Cancer: A Meta-Analysis.

BACKGROUND: Recently, accumulated research has found that the expression of telomerase activity (TA) was associated with colorectal cancer (CRC) advancement, whereas the TA prognostic effect in CRC patients is still controversial. AIMS: To investigate relationships between TA and CRC clinicopathological parameters. STUDY DESIGN: Meta-analysis study. METHODS: We searched published studies in databases, such as EMBASE, the Cochrane Library, PubMed, and Ovid databases (last search updated to October 2014) by meeting specified search criteria. The quality of the included studies was usually evaluated and a meta-analysis was implemented by Stata 12.0 software. We used an odds ratio (OR) with a 95% confidence interval (CI) to evaluate relationship strengths between TA and CRC clinicopathological parameters. RESULTS: In total, 11 studies (715 patients) were included to assess the relation between TA and metastasis-related parameters in CRC patients. The results indicate that a senior TA expression was connected with the existence of lymph node metastasis (180 patients; OR=2.85, 95% CI=1.40-5.81, p=0.004), and tumor site (522 patients; OR=2.93, 95% CI=1.29-6.67, p=0.010). However, a senior TA expression was not connected with tumor size (137 patients; OR=1.57, 95% CI=0.71-3.47, p=0.267), histological differentiation (570 patients; OR=1.28, 95% CI=0.78-2.09, p=0.332), depth of invasion (57 patients; OR=3.76, 95% CI=0.61-23.04, p=0.152), distant metastasis (123 patients; OR=1.76, 95% CI=0.54-5.74, p=0.346), and clinical stage of the cancer (543 patients; OR=1.59, 95% CI=0.74-3.38, p=0.232). CONCLUSION: This meta-analysis suggests that a positive TA was correlated with lymph node metastasis progression and tumor site of the CRC but did not correlate with other important clinicopathological parameters. TA can play a useful part in the prognosis and treatment of CRC patients, but further studies are required to confirm this.

Identification of pathways related to FAF1/H. pylori-associated gastric carcinogenesis through an integrated approach based on iTRAQ quantification and literature review.

Previously we showed that down-regulation of tumor suppressor FAF1 mRNA, potentially caused by H. pylori, correlated with increasing tumor differentiation and distant metastasis in gastric cancer. To identify molecular details about how FAF1 and H. pylori contribute to gastric carcinogenesis, we used the iTRAQ labeling approach involving LC-MS/MS to perform proteomic analysis of HGC-27 gastric cancer cells stably transfected with an FAF1 transgene and/or infected with H. pylori. Of the 2926 proteins examined, proteomics identified 157 for which the expression was altered as a result of FAF1 expression, 500 with altered expression as a result of H. pylori infection, and 246 with altered expression as a combined result of FAF1 expression and H. pylori infection. A literature review identified 21 proteins as being differentially expressed in H. pylori-associated gastric cancer in at least two studies. These two complementary analyses were combined in Ingenuity Pathway software, which predicted that FAF1/H. pylori-associated gastric carcinogenesis alters primarily biochemical pathways related to mitochondrial dysfunction, oxidative phosphorylation, integrin signaling, cholesterol/leucine metabolism and G2/M checkpoint regulation. Differential expression of key proteins in several of these pathways was validated by immunoblotting in HGC-27 cells. This integrated approach combining proteomics and literature searching may prove fruitful for elucidating how FAF1 expression and H. pylori infection affect gastric carcinogenesis. BIOLOGICAL SIGNIFICANCE: We established, for the first time, the proteomics databases of gastric cancer cell HGC-27 overexpressing FAF1 and infected with H. pylori through an integrated approach based on iTRAQ quantification and literature review, this strategy responded to the call for greater focus on data integration in primary/previous proteomic studies; and provided an integrated picture of the reference pathways and networks behind FAF1/H. pylori-associated gastric carcinogenesis, particularly pathways of mitochondrial dysfunction, oxidative phosphorylation, integrin signaling, cholesterol/leucine metabolism and G2/M checkpoint regulation.

Three ADIPOR1 Polymorphisms and Cancer Risk: A Meta-Analysis of Case-Control Studies.

BACKGROUND: Studies have come to conflicting conclusions about whether polymorphisms in the adiponectin receptor 1 gene (ADIPOR1) are associated with cancer risk. To help resolve this question, we meta-analyzed case-control studies in the literature. METHODS: PubMed, EMBASE, Cochrane Library, the Chinese Biological Medical Database and the Chinese National Knowledge Infrastructure Database were systematically searched to identify all case-control studies published through February 2015 examining any ADIPOR1 polymorphisms and risk of any type of cancer. Pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated. RESULTS: A total of 13 case-control studies involving 5,750 cases and 6,762 controls were analyzed. Analysis of the entire study population revealed a significant association between rs1342387(G/A) and overall cancer risk using a homozygous model (OR 0.82, 95%CI 0.72 to 0.94), heterozygous model (OR 0.84, 95%CI 0.76 to 0.93), dominant model (OR 0.85, 95%CI 0.75 to 0.97) and allele contrast model (OR 0.88, 95%CI 0.80 to 0.97). However, subgroup analysis showed that this association was significant only for Asians in the case of colorectal cancer. No significant associations were found between rs12733285(C/T) or rs7539542(C/G) and cancer risk, either in analyses of the entire study population or in analyses of subgroups. CONCLUSIONS: Our meta-analysis suggests that the ADIPOR1 rs1342387(G/A) polymorphism, but not rs12733285(C/T) or rs7539542(C/G), may be associated with cancer risk, especially risk of colorectal cancer in Asians. Large, well-designed studies are needed to verify our findings.

Screening and preliminary validation of miRNAs with the regulation of hTERT in colorectal cancer.

The overexpression of human telomerase reverse transcriptase (hTERT) has been associated with the invasion and metastasis of colorectal cancer (CRC) and has received extensive attention, although the underlying mechanism involved remains unclear. The aim of the present study was to screen and preliminarily validate new tumor­suppressor microRNAs (miRNAs) that potentially inhibit hTERT expression and to assess its clinical significance. Screening for downregulated miRNAs in CRC tissues was performed by retrieving and analysing microRNA microarray data. miRNA candidates were then filtered by bioinformatics analysis. The expression of miRNAs candidates was verified by quantitative polymerase chain reaction in the CRC and corresponding normal tissues. Immunohistochemistry (IHC) was used for the detection of hTERT protein expression. Spearman's correlation coefficient between miRNA candidates and hTERT protein expression was calculated (r) to identify hTERT-targeting miRNAs. A survival analysis was performed to assess the prognostic significance of hTERT-targeting miRNAs in CRC. Eight miRNAs with the potential to interact with hTERT were predicted: miR­29c-3p, miR­124-3p, miR­133a-3p, miR­133b, miR-138-5p, miR-150-5p, miR-378a-3p and miR-422a, respectively. Following detection of the miRNAs using RT-qPCR, miR-29c-3p was excluded. miR-138-5p and miR-422a were observed to potentially interact with hTERT (r=-0.362, P=0.001; r=-0.306, P=0.005, respectively). The Kaplan-Meier survival curves demonstrating high- vs. low-expression group of miR­422a showed a highly significant difference in CRC patients (P=0.024), which suggests that the downregulation of miR-422a was associated with a poorer prognosis. The results indicated that miR-138-5p and miR-422a potentially inhibited hTERT expression in CRC, and suggest a potential application of miR­422a in prognosis prediction and CRC treatment.