Discovery of potential biomarkers for lung cancer classification based on human proteome microarrays using Stochastic Gradient Boosting approach.

PURPOSE: Early identification of lung cancer (LC) will considerably facilitate the intervention and prevention of LC. The human proteome micro-arrays approach can be used as a "liquid biopsy" to diagnose LC to complement conventional diagnosis, which needs advanced bioinformatics methods such as feature selection (FS) and refined machine learning models. METHODS: A two-stage FS methodology by infusing Pearson's Correlation (PC) with a univariate filter (SBF) or recursive feature elimination (RFE) was used to reduce the redundancy of the original dataset. The Stochastic Gradient Boosting (SGB), Random Forest (RF), and Support Vector Machine (SVM) techniques were applied to build ensemble classifiers based on four subsets. The synthetic minority oversampling technique (SMOTE) was used in the preprocessing of imbalanced data. RESULTS: FS approach with SBF and RFE extracted 25 and 55 features, respectively, with 14 overlapped ones. All three ensemble models demonstrate superior accuracy (ranging from 0.867 to 0.967) and sensitivity (0.917 to 1.00) in the test datasets with SGB of SBF subset outperforming others. The SMOTE technique has improved the model performance in the training process. Three of the top selected candidate biomarkers (LGR4, CDC34, and GHRHR) were highly suggested to play a role in lung tumorigenesis. CONCLUSION: A novel hybrid FS method with classical ensemble machine learning algorithms was first used in the classification of protein microarray data. The parsimony model constructed by the SGB algorithm with the appropriate FS and SMOTE approach performs well in the classification task with higher sensitivity and specificity. Standardization and innovation of bioinformatics approach for protein microarray analysis need further exploration and validation.

N-mytistoyltransferase 1 and 2 are potential tumor suppressors and novel targets of miR-182 in human non-small cell lung carcinomas.

BACKGROUND & AIMS: Non-small cell lung cancer (NSCLC) accounts for about 80% of lung cancer diagnoses across the world. Despite recent appreciable improvements in treatment plans for patients with NSCLC, the prognosis for those with the cancer still remains poor. Recently, a growing number of studies have shown that N-myristoyltransferases (NMTs) may be critical in carcinogenesis, however, the functional and clinical significance of this pathway in NSCLC remains unclear and requires further research. METHODS: Initially, we evaluated the expression levels of NMT1 or NMT2 in a clinical cohort comprising of 303 paired primary NSCLC tissues and matched normal mucosae by using ELISA. We subsequently performed a tissue microarray analysis (TMA) to confirm its expression pattern in an independent validation cohort (n = 78). Then, we used a publicly available KM plotter database (n = 1921) to evaluate the prognostic impact of NMT1 and NMT2 in NSCLC. Lastly, a series of in-vitro molecular/cellular and animal experiments were performed for mechanistic understanding of the role of N-myristoyltransferases in NSCLC. RESULTS: Our ELISA data revealed that the expression level of NMT1 and NMT2 was down-regulated in tumor tissues (n = 303, P < 0.0001), which was confirmed in an independent validation cohort by TMA (n = 78, P = 0.014 for NMT1 and P < 0.0001 for NMT2). On the other hand, patients with low expression of NMT1 or NMT2 had shorter overall survival (P = 0.013, HR = 0.85 for NMT1; P = 0.00059, HR = 0.8, for NMT2). Mechanistically, we revealed that the interaction and co-localization of NMT1 and NMT2 in NSCLC, and N-terminus of NMT1 and NMT2 was observed to be crucial for their interaction as well as for their catalytic activity. Moreover, we found that NMT1 can significantly promote the expression of NMT2 by enhancing its stability. We corroborated these findings by performing functional assays in which the knockout of NMT1 and NMT2 resulted in enhanced cell proliferation, migration and invasion as well as increased tumorxenograftgrowth. In addition, we identified miR-182 as a novel regulator of both NMT1 and NMT2. More specifically, the overexpression or inhibition of miR-182 modulated globe N-myristoylation level, contributed to phenotypic alterations in NSCLS cells. CONCLUSIONS: NMT1 and NMT2 can act as potential tumor suppressors in NSCLC, and the inhibition of miR-182 expression or therapeutic NMTs replenishment may be a promising treatment option for patients with NSCLC.

Restoring HOXD10 Exhibits Therapeutic Potential for Ameliorating Malignant Progression and 5-Fluorouracil Resistance in Colorectal Cancer.

Emerging evidence suggests that hypermethylation of HOXD10 plays an important role in human cancers. However, the biological and clinical impacts of HOXD10 overmethylation and its downstream targets in colorectal cancer remain unknown. We evaluated the methylation level of HOXD10 in paired cancer and normal tissues (n = 42) by using pyrosequencing, followed by validation of the methylation status of HOXD10 from The Cancer Genome Atlas (TCGA) datasets with 302 cancer tissues and 38 normal tissues. The biological function of HOXD10 was characterized in cell lines. We further evaluated the effects of HOXD10 and its targets on chemoresistance in our established resistant cell lines and clinical cohort (n = 66). HOXD10 was found frequently methylated in colorectal cancer, and its hypermethylation correlates with its low expression level, advanced disease, and lymph node metastasis. Functionally, HOXD10 acts as a tumor suppressor gene, in which HOXD10-expressing cells showed suppressed cell proliferation, colony formation ability, and migration and invasion capacity. Mechanistically, DNMT1, DNMT3B, and MeCP2 were recruited in the HOXD10 promoter, and demethylation by 5-Aza-2'-deoxycytidine (5-Aza-CdR) treatment or MeCP2 knockdown can sufficiently induce HOXD10 expression. HOXD10 regulates the expressions of miR-7 and IGFBP3 in a promoter-dependent manner. Restoration of the expression of HOXD10 in 5-fluorouracil (5-FU)-resistant cells significantly upregulates the expressions of miR-7 and IGFBP3 and enhances chemosensitivity to 5-FU. In conclusion, we provide novel evidence that HOXD10 is frequently methylated, silenced, and contributes to the development of colorectal cancers. Restoration of HOXD10 activates the expressions of miR-7 and IGFBP3 and results in an inhibited phenotype biologically, suggesting its potential therapeutic relevance in colorectal cancer (CRC).

An immunoscore nomogram for predicting survival in patients with oesophageal cancer.

This study aimed to construct and validate an immunoscore nomogram that may be used to predict the prognosis of oesophageal cancer. With the gene expression data of oesophageal cancer in a public database, we used CIBERSORT to estimate the fractions of 22 infiltrating immune cell types. We then built an immunoscore signature based on 12 types of infiltrating immune cells using the least absolute shrinkage and selection operator (LASSO) model. This immunoscore was used as an independent predictor in the prognostic model (training cohort: [hazard ratio (HR), 4.78; 95% confidence interval (CI), 2.64-8.67; P < 0.001], validation cohort: [HR, 2.15; 95% CI, 1.04-4.45; P = 0.040]). Subgroup analysis by clinical features showed that overall survival was significantly different between the high-immunoscore group and the low-immunoscore group. The predictors that constituted the individualized prediction nomogram were immunoscore, age, and tumour stage. The nomogram had good discrimination and calibration. Decision curve analysis showed that the immunoscore nomogram was clinically useful. Therefore, the novel immunoscore signature based on infiltrating immune cells can be used as a reliable predictor of the prognosis of oesophageal cancer, and the immunoscore nomogram is a convenient tool for predicting the survival of individual patients.

Cumulative Evidence for Associations between Genetic Variants and Risk of Esophageal Cancer.

BACKGROUND: A large number of studies have been conducted to investigate associations between genetic variants and esophageal cancer risk in the past several decades. However, findings from these studies have been generally inconsistent. We aimed to provide a summary of the current understanding of the genetic architecture of esophageal cancer susceptibility. METHODS: We performed a comprehensive field synopsis and meta-analysis to evaluate associations between 95 variants in 70 genes or loci and esophageal cancer risk using data from 304 eligible publications, including 104,904 cases and 159,797 controls, through screening a total of 21,328 citations. We graded levels of cumulative epidemiologic evidence of a significant association with esophageal cancer using the Venice criteria and false-positive report probability tests. We constructed functional annotations for these variants using data from the Encyclopedia of DNA Elements Project and other databases. RESULTS: Thirty variants were nominally significantly associated with esophageal cancer risk. Cumulative epidemiologic evidence of a significant association with overall esophageal cancer, esophageal squamous cell carcinoma, or esophageal adenocarcinoma was strong for 13 variants in or near 13 genes (ADH1B, BARX1, CDKN1A, CHEK2, CLPTM1L, CRTC1, CYP1A1, EGF, LTA, MIR34BC, PLCE1, PTEN, and PTGS2). Bioinformatics analysis suggested that these variants and others correlated with them might fall in putative functional regions. CONCLUSIONS: Our study summarizes the current literature on the genetic architecture of esophageal cancer susceptibility and identifies several potential polymorphisms that could be involved in esophageal cancer susceptibility. IMPACT: These findings provide direction for future studies to identify new genetic factors for esophageal cancer.

Development and Preliminary Validation of a Depression Assessment Tool for Maintenance Hemodialysis Patients.

Patients undergoing maintenance hemodialysis (MHD) are subject to a higher-than-usual prevalence of depressive disorders. However, the lack of consensus regarding the best assessment method remains an important problem. Thus, there is a clear need for more effective screening tools and an easily administered, disease-specific self-report measure of depression in MHD patients. After we developed and administered an initial depression inventory for MHD patients (I-DI-MHD), we created the DI-MHD and administered the DI-MHD and the Beck Depression Inventory (BDI) to 354 patients from four hospitals. Reliability, construct validity and receiver operator characteristic curves were assessed. The 17-item DI-MHD instrument displayed good internal consistency (Cronbach's alpha =0.893), provided excellent convergent validity, and correlated with the BDI scale (kappa =0.785, P <0.001). A factor analysis pattern matrix analysis showed that a four-factor model provided the best account of the data. Finally, the DI-MHD cutoff yielded a sensitivity of 0.97 and a specificity of 0.86, which were slightly better than the corresponding values for the BDI. The DI-MHD scale shows reasonable validity and reliability for assessing depression in MHD patients.

Toxicity responses of different organs of zebrafish (Danio rerio) to silver nanoparticles with different particle sizes and surface coatings.

Silver nanoparticles (AgNPs) in aquatic ecosystems are toxic to aquatic organisms. In this study, we aimed to investigate the toxicities and molecular mechanisms of AgNPs with different surface coatings (sodium citrate and polyvinylpyrrolidone) and particle sizes (20 nm and 100 nm) in the gills, intestines, and muscles of zebrafish after 96 h of exposure. Our results indicated that the contribution of particle size to AgNP toxicity was greater than that of the surface coating. Citrate-coated AgNPs were more toxic than polyvinylpyrrolidone-coated AgNPs, and 20-nm AgNPs were more toxic than 100-nm AgNPs. The toxic effects of AgNPs to the tissues were in the order intestines > gills > muscles. Differential expression of genes with the different AgNPs confirmed that they had toxic effects in the zebrafish tissues at the molecular level. Our comprehensive comparison of the toxicities of different AgNPs to aquatic ecosystems will be helpful for further risk assessments of AgNPs.

Association between green tea intake and risk of gastric cancer: a systematic review and dose-response meta-analysis of observational studies.

OBJECTIVE: To examine and quantify the potential dose-response relationship between green tea intake and the risk of gastric cancer. DESIGN: We searched PubMed, EMBASE, Web of Science, CBM, CNKI and VIP up to December 2015 without language restrictions. SETTING: A systematic review and dose-response meta-analysis of observational studies. SUBJECTS: Five cohort studies and eight case-control studies. RESULTS: Compared with the lowest level of green tea intake, the pooled relative risk (95 % CI) of gastric cancer was 1·05 (0·90, 1·21, I 2=20·3 %) for the cohort studies and the pooled OR (95 % CI) was 0·84 (0·74, 0·95, I 2=48·3 %) for the case-control studies. The pooled relative risk of gastric cancer was 0·79 (0·63, 0·97, I 2=63·8 %) for intake of 6 cups green tea/d, 0·59 (0·42, 0·82, I 2=1·0 %) for 25 years of green tea intake and 7·60 (1·67, 34·60, I 2=86·5 %) for drinking very hot green tea. CONCLUSIONS: Drinking green tea has a certain preventive effect on reducing the risk of gastric cancer, particularly for long-term and high-dose consumption. Drinking too high-temperature green tea may increase the risk of gastric cancer, but it is still unclear whether high-temperature green tea is a risk factor for gastric cancer. Further studies should be performed to obtain more detailed results, including other gastric cancer risk factors such as smoking and alcohol consumption and the dose of the effective components in green tea, to provide more reliable evidence-based medical references for the relationship between green tea and gastric cancer.

BTG1 expression correlates with pathogenesis, aggressive behaviors and prognosis of gastric cancer: a potential target for gene therapy.

Here, we found that BTG1 overexpression inhibited proliferation, migration and invasion, induced G2/M arrest, differentiation, senescence and apoptosis in BGC-823 and MKN28 cells (p < 0.05). BTG1 transfectants showed a higher mRNA expression of Cyclin D1 and Bax, but a lower mRNA expression of cdc2, p21, mTOR and MMP-9 than the control and mock (p < 0.05). After treated with cisplatin, MG132, paclitaxel and SAHA, both BTG1 transfectants showed lower mRNA viability and higher apoptosis than the control in both time- and dose-dependent manners (p < 0.05) with the hypoexpression of chemoresistance-related genes (slug, CD147, GRP78, GRP94, FBXW7 TOP1, TOP2 and GST-π). BTG1 expression was restored after 5-aza-2'-deoxycytidine treatment in gastric cancer cells. BTG1 expression was statistically lower in gastric cancer than non-neoplastic mucosa and metastatic cancer in lymph node (p < 0.05). BTG1 expression was positively correlated with depth of invasion, lymphatic and venous invasion, lymph node metastasis, TNM staging and worse prognosis (p < 0.05). The diffuse-type carcinoma showed less BTG1 expression than intestinal- and mixed-type ones (p < 0.05). BTG1 overexpression suppressed tumor growth and lung metastasis of gastric cancer cells by inhibiting proliferation, enhancing autophagy and apoptosis in xenograft models. It was suggested that down-regulated BTG1 expression might promote gastric carcinogenesis partially due to its promoter methylation. BTG1 overexpression might reverse the aggressive phenotypes and be employed as a potential target for gene therapy of gastric cancer.

Is allogeneic transplantation really the best treatment for FLT3/ITD-positive acute myeloid leukemia? A systematic review.

Fetal liver tyrosine kinase 3 (FLT3)-internal tandem duplications (ITDs) has been used as a powerful adverse prognostic indicator for acute myeloid leukemia (AML) in any age group. Evidence is mixed regarding the effects of allogeneic transplantation (allo-HSCT) in first complete remission (CR) for patients with FLT3/ITD AML. To fill this gap, this study provides a systematic review and meta-analysis of patients with FLT3/ITD AML receiving HSCT. A search of PubMed, Embase, and OVID yielded 1706 abstracts, two researchers screening the trials based on inclusion and exclusion criteria, and assessed the methodology quality independently. Meta-analysis showed that compared with chemotherapy, both allo-HSCT and autologous hematopoietic cell transplantation (auto-HSCT) can reduce the relapse rate (p < 0.01) and improve both the OS (p < 0.01) and DFS (p < 0.01). But when compared allo-HSCT with auto-HSCT, the OS (p = 0.27) and DFS (p = 0.19) have no statistical significance, and only the relapse indicator has statistical significance, p < 0.01. Based on the results, we can conclude that allo-HSCT is an efficient therapy approach for patients with FLT3/ITD AML. Chemotherapy cannot change the poor prognosis. Auto-HSCT can improve OS and DFS, but it cannot reduce the relapse rate.

Risk factors of stroke in Western and Asian countries: a systematic review and meta-analysis of prospective cohort studies.

BACKGROUND: There has been an increasing trend in the incidence of stroke worldwide in recent years, and the number of studies focusing on the risk factors for stroke has also increased every year. To comprehensively evaluate the risk factors of stroke identified in prospective Western and Asian cohort studies. METHODS: Population-based cohort studies on stroke were searched in databases (PubMed, EMBASE, Web of Science, Google Scholar, etc.), and the library of the Third Military Medical University was manually searched for relevant information. A meta-analysis of Western and Asian studies on risk factors was performed. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to assess the final group of cohort studies. RESULTS: After screening, 22 prospective cohort studies were included in the analyses of this investigation. Two factors, smoking and alcohol consumption, showed statistically significant differences between Western and Asian populations, and the results were as follows (W/A): 2.05 (95% CI, 1.68 ~ 2.49)/1.27 (95% CI, 1.04 ~ 1.55) and 0.89 (95% CI, 0.76 ~ 1.04)/1.28 (95% CI, 1.07 ~ 1.53). The factor BMI = 18.5-21.9 kg/m2 showed statistically significant differences only in Western populations, 0.96 (95% CI, 0.93 ~ 0.99); the factor SBP = 120-139 mm Hg showed statistically significant differences only in Asian populations, 2.29 (95% CI, 1.04 ~ 5.09). CONCLUSIONS: The prevalences of risk factors affect the stroke morbidity in Western and Asian populations, which may be biased by race. The meta-analysis of population-based studies suggests that different preventive measures should be adopted for Western and Asian population groups that are at high risk for stroke.

Application of Crossover Analysis-logistic Regression in the Assessment of Gene- environmental Interactions for Colorectal Cancer.

BACKGROUND: Analysis of gene-gene and gene-environment interactions for complex multifactorial human disease faces challenges regarding statistical methodology. One major difficulty is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes or environmental exposures. Based on our previous case-control study in Chongqing of China, we have found increased risk of colorectal cancer exists in individuals carrying a novel homozygous TT at locus rs1329149 and known homozygous AA at locus rs671. METHODS: In this study, we proposed statistical method- crossover analysis in combination with logistic regression model, to further analyze our data and focus on assessing gene-environmental interactions for colorectal cancer. RESULTS: The results of the crossover analysis showed that there are possible multiplicative interactions between loci rs671 and rs1329149 with alcohol consumption. Multi- factorial logistic regression analysis also validated that loci rs671 and rs1329149 both exhibited a multiplicative interaction with alcohol consumption. Moreover, we also found additive interactions between any pair of two factors (among the four risk factors: gene loci rs671, rs1329149, age and alcohol consumption) through the crossover analysis, which was not evident on logistic regression. CONCLUSIONS: In conclusion, the method based on crossover analysis-logistic regression is successful in assessing additive and multiplicative gene-environment interactions, and in revealing synergistic effects of gene loci rs671 and rs1329149 with alcohol consumption in the pathogenesis and development of colorectal cancer.

Identification of differentially expressed genes using multi-resolution wavelet transformation analysis combined with SAM.

Although many statistical methods have been proposed for identifying differentially expressed genes, the optimal approach has still not been resolved. Therefore, it is necessary to develop more efficient methods of finding differentially expressed genes while accounting for noise and false discovery rate (FDR). We propose a method based on multi-resolution wavelet transformation analysis combined with SAM for identifying differentially expressed genes by adjusting the Δ and computing the FDR. This method was applied to a microarray expression dataset from adenoma patients and normal subjects. The number of differentially expressed genes gradually reduced with an increasing Δ value, and the FDR was reduced after wavelet transformation. At a given Δ value, the FDR was also reduced before and after wavelet transformation. In conclusion, a greater number and quality of differentially expressed genes were detected using the method when compared to non-transformed data, and the FDRs were notably more controlled and reduced.

A multifactor dimensionality reduction-logistic regression model of gene polymorphisms and an environmental interaction analysis in cancer research.

BACKGROUND: Analysis of interactions between genes and the environment with complex multifactorial human disease faces important challenges. Limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes or environmental exposures are key problems. The aim of the study was to investigate the use of multifactor dimensionality reduction (MDR) and logistic regression models to analyze the effects of interactions between complex disease genes with other genes and with environmental factors and to compare the results of these two methods in interaction analysis. METHODS: In this case-control study, the two methods were applied to analog data of samples from 486 cancer patients and 514 control individuals by computer simulation, including 4 environment factors (E1~E4) and 8 gene polymorphism factors (G1~G8). Non-conditional logistic regression was used to analyze risk factors for cancer, and MDR and logistic regression were employed to analyze interactions under various conditions. RESULTS: MDR could find high-level interactions between genes and the environment (E3*G1*G7), but it could not find a main effect; conversely, logistic regression better analyzed the main effects (E3, G1, and G4) but was limited in its analysis of high-level interactions (E3*G1*G7). The results of these two methods with analog data show that the gene G1 site, the G4 site, E3, and the E3*G1*G7 interaction may be risk factors for occurrence of cancer. CONCLUSIONS: MDR and logistic regression, which are the two complementary methods, can be combined to analyze gene-gene (gene-environment) interactions with good results. This approach should help to determine the causes of diseases, such as chronic non-transmittable diseases like cancer.

[Analysis and quantitative assessment on the risks of diabetes at the community level in Chongqing].

OBJECTIVE: To investigate the correlation risk factors of diabetes over 16-year-olds at the community level in Chongqing and to set a quantitative criteria for determining risk for diabetes and to identify persons having potential risk. METHODS: 1981 cases with 1:2 matched controls were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road, Ciqikou, which were interviewed with a uniformed questionnaire. The risk factors of diabetes mellitus were analyzed with logistic regression, and to calculate the odds ratios of risk factors for diabetes. Different levels of risk exposure factors were converted into a risk scores, using statistical models. RESULTS: An individual health risk appraisal model of diabetes was established, applicable to individuals of different sex, age, health behavior,disease,and family history, for men, 13 risk factors including hyperlipidemia (14.995), coronary heart disease (6.689), family history of hypertension (4.005), smoking (3.111 ) etc. while for women, hyperlipidemia (12.426), family history of hypertension (3.986), stroke (2.714), liking sweets (1.244), about 15 risk factors, were entering the main effect model. The related risk scores were added to obtain a combined risk score to predict the individual's risk of diabetes in the future. CONCLUSION: The incidence of diabetes could be effectively reduced by changing the unhealthy lifestyle and curing the patient with the disease. Evidence was provided to persuade people change their unhealthy lifestyles and behaviors through health education. The results could also be used in community to improve their health services.

[Gene expression profiles in early stage of BALB/c 3T3 cells' transformation promoted with 12-O-tetradecanoylphorbol-13-acetate].

OBJECTIVE: To elucidate the potential molecular mechanism responsible for the early time of tumor promotion, gene expression profile was studied in the transformed BALB/c 3T3 cells induced by 12-O-tetradecanoylphorbol-13-acetate (TPA). METHODS: The two-stage cell transformation model was established by using the initiator of N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) and promoter of TPA. Cell proliferation was measured by trypan blue staining and cell cycle analysis was carried out by flow cytometry assay. A cDNA microarray representing 1 152 genes was used to investigate the gene expression profiles of BALB/c 3T3 cells exposed to TPA at 4 h and 24 h respectively. RESULTS: TPA could effectively inhibit cell proliferation and induce the G1 and S cell cycle arrested in the early time. Moreover 19 genes were found differentially expressed at least twofold in the TPA treated cells as compared with the control cells, 9 of them were upregulated and 10 downregulated. Most of the differentially expressed genes were involved in cell proliferation, differentiation or apoptosis, and related to ras or p53 signal transduction pathway. CONCLUSION: TPA could influence the transcriptional expression of some genes related to cell cycle modulation and ultimately result in the cell growth arrest.