Gene Coexpression and miRNA Regulation: A Path to Early Intervention in Colorectal Cancer.

Early diagnosis and intervention are pivotal in reducing colorectal cancer (CRC) incidence and enhancing patient outcomes. In this study, we focused on three genes, AQP8, GUCA2B, and SPIB, which exhibit high coexpression and play crucial roles in suppressing early-stage CRC. Our objective was to identify key miRNAs that can mitigate CRC tumorigenesis and modulate the coexpression network involving these genes. We conducted a comprehensive analysis using large-scale tissue mRNA data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus to validate the coexpression of AQP8, GUCA2B, and SPIB, and to assess their diagnostic and prognostic significance in CRC. The mRNA-miRNA interactions were examined using MiRNet and the Encyclopedia of RNA Interactomes. Furthermore, using various molecular techniques, we conducted miRNA inhibitor transfection experiments in HCT116 cells to evaluate their effects on cell growth, migration, and gene/protein expression. Our findings revealed that, compared with normal tissues, AQP8, GUCA2B, and SPIB exhibited high coexpression and were downregulated in CRC, particularly during tumorigenesis. OncoMirs, hsa-miR-182-5p, and hsa-miR-27a-3p, were predicted to regulate these genes. MiRNA inhibition experiments in HCT116 cells demonstrated the inhibitory effects of miR-27a-3p and miR-182-5p on GUCA2B mRNA and protein expression. These miRNAs promoted the proliferation of CRC cells, possibly through their involvement in the GUCA2B-GUCY2C axis, which is known to promote tumor growth. While the expressions of AQP8 and SPIB were barely detectable, their regulatory relationship with hsa-miR-182-5p remained inconclusive. Our study confirms that hsa-miR-27a-3p and hsa-miR-182-5p are oncomiRs in CRC. These miRNAs may contribute to GUCY2C dysregulation by downregulating GUCA2B, which encodes uroguanylin. Consequently, hsa-miR-182-5p and hsa-miR-27a-3p show promise as potential targets for early intervention and treatment in the early stages of CRC.

Sleep Duration and Kidney Function - Does Weekend Sleep Matter?

Objective: Weekend sleep duration is linked to health issues, including mortality. However, how weekend sleep duration can impact chronic kidney disease (CKD) still needs to be understood. Therefore, we aimed to analyze how weekend sleep duration is associated with kidney function. Methods: This is a cross-sectional study. Data were obtained from the 2017-2018 National Health and Nutrition Examination Survey. We included 5362 study participants and categorized them into nine subgroups by sleep duration (short: ≤6 hours, normal: 6-9 hours, and long: ≥9 hours) on weekdays and weekends and analyzed for the respective association with renal function using stratified multivariable linear regression. Results: Weekend sleep duration for 9 hours or more was associated with decreasing estimated glomerular filtration rate (eGFR) levels by 2.8 to 6.4 mL/min/1.73 m2 among people with long to short weekday sleep duration compared with short weekday and weekend sleep durations (control group) after adjusting for demographic characteristics, body measurement, sleep quality, smoking, and comorbidities. The study population with short weekday sleep duration (sWK) and long weekend sleep duration (lWD) had the most significant decline in eGFR. For the study population with sWK, eGFR level significantly decreased by 1.1 mL/min/1.73 m2 as sleep duration on weekends increased by one hour. Conclusion: The underlying mediators of lWD and CKD could be the dysregulation of human behaviors, metabolism, or biological functions. Longer weekend sleep duration was linked to a decrease in eGFR levels. It warrants further study to clarify the mediators.

A co-regulatory network of SPIB, AQP8, and GUCA2B related to immune infiltration for early-stage colorectal cancer in silico and in vitro.

In early-stage colorectal cancer (CRC), AQP8, GUCA2B, and SPIB were important suppressor genes and frequently co-expressed. However, the underlying co-regulation effect remains unknown and need to be elucidated. We aimed to investigate the co-regulatory network of AQP8, GUCA2B, and SPIB in CRC using in vitro and in silico methods. Q-PCR, western blot, and immunohistochemistry were used to assess the co-regulatory network of the target genes in the HCT-116 cell line and fresh tumor tissues. Bioinformatical methods were used to validate the findings using the Cancer Genome Atlas COlon ADenocarcinoma and REctum ADenocarcinoma datasets, as well as large scale integrated data sets from Gene Expression Omnibus. In clinical CRC tissues, SPIB, AQP8, and GUCA2B were barely expressed compared to normal mucosa. When compared to 22 well-known genetic biomarkers, they are independent predictors of CRC identification with near 100% accuracy. In the co-regulatory network, they were co-upregulated at the mRNA and protein expression levels. AQP8, GUCA2B and SPIB were linked to immune cell infiltration and GUCA2B and SPIB were negatively associated with tumor purity. The co-regulatory network in miRNA-mRNA analysis was mediated by cancer-related microRNAs miR-182-5p and miR-27a-3. The functional analysis of the co-regulatory network's protein-protein interaction networks reveals three clusters and three major functions: complex interactions of transcription factors in mediating cytokine biology in T cells (SPIB cluster), guanylin, and Intestinal infectious diseases (GUCA2B cluster), and water channel activity balance (AQP8 cluster). The co-regulatory network of SPIB, AQP8, and GUCA2B was confirmed. MiR-27a-3p and miR-182-5p were two possible mediators. The mechanisms of SPIB, AQP8, GUCA2B, miR-182-5p, and miR-27a-3p in CRC merit further investigation.

Advancing breast cancer subtyping: optimizing immunohistochemical staining classification with insights from real-world Taiwanese data.

Gene expression signatures provide valuable information to guide postoperative treatment in breast cancer (BC) patients. However, genetic tests are prohibitively expensive for the majority of BC patients. Immunohistochemical staining (IHC) subtype classification system has been widely used for treatment guideline and is affordable to most BC patients. We aimed to revise immunohistochemical staining (IHC) subtyping to better match gene expression-based Prediction Analysis of Microarray 50 (PAM50) subtyping. Real world data of 372 BC patients were recruited in the Tri-Service General Hospital between Jan 2019 and Dec 2021. Clinical pathological information, blood, twelve pathological tissue slide samples, and fresh surgical tumor specimens were collected to examine IHC and PAM50. Current IHC subtyping (cIHC) tends to misclassify PAM50-based luminal A (lum A) to luminal B (lum B) by 35.81%, PAM50-lum B to PAM50-lum A by 9.09%, PAM50-Her2-enriched to lum B by 61.11%, PAM50-based Her2-enriched to lum B by 61.11%, and PAM50-based basal-like to lum B by 33.33%. We used random forest to identify estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her2), and Ki-67 status as the best indicators for revised IHC subtyping (rIHC4) and revised the classification rules by stratified analysis and prediction efficacy. rIHC4 increased the concordance rate for PAM50 subtypes from 68.3% to 74.7%. Both sensitivity and precision increased in most rIHC4 subtypes. Sensitivity increased from 33.3% to 87.4% in the Her2-enriched subtype; precision increased more evidently in the basal-like and lum B subtypes, from 71.4% to 83.3% and 57% to 65.1%, respectively. Our rIHC4 subtyping improved consistency with the PAM50 subtype, which could improve clinical management of BC patients without increasing medical expense.

Predictive Value of the Interaction between CEA and Hemoglobin in Neoadjuvant CCRT Outcomes in Rectal Cancer Patients.

The adoption of neoadjuvant concurrent chemoradiotherapy (CCRT) has reshaped the therapeutic landscape, but response prediction remains challenging. This study investigates the interaction between pre-CCRT carcinoembryonic antigen (CEA) and post-CCRT hemoglobin (Hb) levels in predicting the response of locally advanced rectal cancer (LARC) to CCRT. Retrospective data from 93 rectal cancer patients receiving neoadjuvant CCRT were analyzed. Univariate analyses assessed clinical factors associated with tumor regression grade (TRG) and T-stage outcomes. Machine learning identified predictive biomarkers. Interaction effects between CEA and Hb were explored through subgroup analyses. Post-CCRT Hb varied between pre-CCRT CEA groups. The interaction between pre-CCRT CEA and post-CCRT Hb influenced TRG. Males with normal pre-CCRT CEA and anemia showed better treatment responses. Females with elevated pre-CCRT CEA and post-CCRT anemia exhibited poorer responses. The interaction effect between them was significant, indicating that their relationship with TRG was not additive. Inflammatory biomarkers, WBC, neutrophil count, and post-CCRT platelet level correlated with CCRT response. Contrasting with previous findings, anemia was a predictor of better treatment response in males with normal pre-CCRT CEA. The interaction between pre-CCRT CEA and post-CCRT Hb levels predicts the response of LARC to CCRT. CEA, Hb, and sex should be considered when assessing treatment response. Inflammatory biomarkers contribute to response prediction. Understanding these complex relationships can enhance personalized treatment approaches in rectal cancer patients.

Verifying the accuracy of self-reported smoking behavior in female volunteer soldiers.

Smoking rates in the military are evaluated through questionnaire surveying. Because the accurate identification of smokers facilitates the provision of smoking cessation services, this study conducted urine cotinine concentration testing to verify the accuracy of self-reported smoking behavior by female volunteer soldiers and analyzed the effects of second-hand smoking on urine cotinine concentrations. This study is a cross-sectional study conducted using purposive sampling on female volunteer soldiers receiving training at the Taichung Recruit Training Center in May 2014. This study simultaneously collected questionnaires and urine samples, and urine samples were analyzed with an enzyme-linked immunosorbent assay. The self-reported smoking rate of female volunteer soldiers was 19.3%, whereas the smoking rate as determined by urine cotinine concentration testing was 26.3%, indicating an overall underestimation of 7.0%. Chi-square (χ2) goodness of fit test results indicated that the distribution of self-reported smoking behaviors and that verified from urine cotinine concentration testing were significantly different. The sensitivity of self-reported smoking behavior was 66.7% with a specificity of 97.6%. There was no significant association between second-hand smoking and urine cotinine concentrations. Questionnaire survey self-reporting methods could underestimate the smoking behavior of female volunteer soldiers and routine testing with biochemical verification is necessary.

Factors influencing smoking cessation counselors' intention to stay: An application of a conceptual model of intention to stay verified with path analysis.

Background: The Taiwanese military trains smoking cessation counselors to counsel officers and soldiers on quitting smoking as part time. The intention to stay among smoking cessation counselors affects the promotion of smoking cessation. This study investigated smoking cessation counselors' intention to stay by applying a conceptual model of intent to stay (CMIS) to analyze influencing factors. Methods: In this cross-sectional study, we applied the CMIS to design a questionnaire. We invited 577 smoking cessation counselors trained in the military from 2016 to 2017. The response rate was 46.7%, and the questionnaire responses of 260 military smoking cessation counselors were analyzed. We used path analysis to verify the relationships among the various aspects of the CMIS. Results: We determined that smoking cessation counselors' intention to stay is directly affected by job satisfaction (ß = 0.150, p = 0.014), job stress (ß = -0.225, p < 0.001), and institutional identification (ß = 0.431, p < 0.001). Career opportunities indirectly affect intention to stay through institutional identification, working environment indirectly affects intention to stay through job stress, and co-worker support and self-fulfillment indirectly affect intention to stay through job satisfaction and institutional identification. Our model could explain 36.7% of the variance in intent to stay among smoking cessation counselors. Conclusion: Our results suggest that relevant policies should be formulated to enhance smoking cessation counselors' recognition, affirmation, and sense of belonging as related to smoking cessation counseling work, thereby raising their institutional identification and promoting their intention to stay.

Association between serum uric acid levels and colonic diverticulosis in terms of sex.

BACKGROUND: The association between elevated serum uric acid (UA) levels and the risk of developing colonic diverticulosis has not yet been investigated. Thus, this cross-sectional study aimed to examine this correlation in individuals from Taiwan. METHODS: From Jan. 1, 2010, to Dec. 31, 2016., approximately 5,605 patients (aged >20 years) from Tri-Service General Hospital who met the inclusion criteria according to colonoscopy and laboratory test findings were included in this research. The correlation between serum UA levels and colonic diverticulosis was investigated via regression analyses. RESULTS: Participants with elevated serum UA levels were at a higher risk of colonic diverticulosis. The area under the curve for serum UA levels was significantly higher in women than in men (0.651 [95% confidence interval: 0.596-0.707] vs. 0.55 [0.507-0.593]). There were specific trends in female-specific indicators for colonic diverticulosis across increasing quartiles of serum UA levels. CONCLUSIONS: Patients with elevated serum UA levels should be cautious regarding the development of colonic diverticulosis disorder in female. Moreover, prospective studies may provide additional information on the relationship between elevated serum UA levels and colonic diverticulosis.

From GWAS to drug screening: repurposing antipsychotics for glioblastoma.

BACKGROUND: Glioblastoma is currently an incurable cancer. Genome-wide association studies have demonstrated that 41 genetic variants are associated with glioblastoma and may provide an option for drug development. METHODS: We investigated FDA-approved antipsychotics for their potential treatment of glioblastoma based on genome-wide association studies data using a 'pathway/gene-set analysis' approach. RESULTS: The in-silico screening led to the discovery of 12 candidate drugs. DepMap portal revealed that 42 glioma cell lines show higher sensitivities to 12 candidate drugs than to Temozolomide, the current standard treatment for glioblastoma. CONCLUSION: In particular, cell lines showed significantly higher sensitivities to Norcyclobenzaprine and Protriptyline which were predicted to bind targets to disrupt a certain molecular function such as DNA repair, response to hormones, or DNA-templated transcription, and may lead to an effect on survival-related pathways including cell cycle arrest, response to ER stress, glucose transport, and regulation of autophagy. However, it is recommended that their mechanism of action and efficacy are further determined.

Downregulation of AANAT by c-Fos in tubular epithelial cells with membranous nephropathy.

Melatonin is a hormone majorly secreted by the pineal gland and contributes to a various type of physiological functions in mammals. The melatonin production is tightly limited to the AANAT level, yet the most known molecular mechanisms underlying AANAT gene transcription is limited in the pinealocyte. Here, we find that c-Fos and cAMP-response element-binding protein (CREB) decreases and increases the AANAT transcriptional activity in renal tubular epithelial cell, respectively. Notably, c-Fos knockdown significantly upregulates melatonin levels in renal tubular cells. Functional results indicate that AANAT expression is decreased by c-Fos and resulted in enhancement of cell damage in albumin-injury cell model. We further find an inverse correlation between c-Fos and AANAT levels in renal tubular cells from experimental membranous nephropathy (MN) samples and clinical MN specimens. Our finding provides the molecular basis of c-Fos in transcriptionally downregulating expression of AANAT and melatonin, and elucidate the protective role of AANAT in preventing renal tubular cells death in albumin-injury cell model and MN progression.

Sleeping, Smoking, and Kidney Diseases: Evidence From the NHANES 2017-2018.

Study Objectives: Smoking and sleep are modifiable factors associated with the chronic kidney diseases. However, the interaction of smoking and sleep on the renal function are still unclear. Therefore, we aimed to evaluate the interactive impacts of smoking and sleep on the renal function. Methods: Data were obtained from the National Health and Nutrition Examination Survey. The study population were categorized into nine subgroups by smoking (smoking every day, sometimes, and non-smokers recently) and sleep duration (short duration ≤ 6 h, normal duration 6-9 h, and longer duration ≥ 9 h on the weekdays). Results: The study group with a short sleep duration had significantly higher serum cotinine and hydrocotinine levels compared with the other two sleep groups. After adjusting the demographic characteristics (age, race, body mass index, and marital status), sleep quality (snoring or breathing cessation), and comorbidities (diabetes mellitus, hypertension, high cholesterol, anemia, congestive heart failure, coronary heart disease, and stroke), non-smokers with short or long sleep duration had significant lower estimated glomerular filtration rate (eGFR) levels than the study group who smoked every day and slept ≤ 6 h. The effects of sleep duration on eGFR levels varied with smoking status. For the study group smoking every day, eGFR levels increased as sleep duration decreased, whereas for the study group smoking sometimes, eGFR levels increased as sleep duration increased. The U-shaped effects of eGFR levels were observed among non-smokers whose normal sleep duration was associated with better eGFR levels. Normal sleep duration was an important protective factor of the renal function for non-smokers than smokers. Conclusions: The effects of sleep duration on eGFR levels varied with smoking status. Normal sleep duration was a protective factor and more crucial for non-smokers than for smokers.

Gender Differences in the Extended Theory of Planned Behaviour on Smoking Cessation Intention in Young Soldiers.

BACKGROUND: The theory of planned behaviour (TPB) explanation of smoking cessation intentions consists of gender differences. The purpose of this study is to adopt the extended TPB to discuss factors influencing the smoking cessation intentions of young adult volunteer soldiers and to further compare the respective factors for both genders. METHODS: This is a cross-sectional study. Data were collected from 139 and 165 male and female volunteer soldiers who smoked, respectively. Research participants completed a self-administered questionnaire that comprised items pertaining to the participants' demographic characteristics, smoking behaviours, smoking cessation experiences, social environments, and TPB variables. RESULTS: Subjective norms (friends) are a positive key factor for young adult male (ß = 0.033, p = 0.012) and female (ß = 0.076, p < 0.001) volunteer soldiers' smoking cessation intentions, and perceived behavioural control is a key factor for male young (ß = 0.226, p = 0.040) adult volunteer soldiers' smoking cessation intention. The extended TPB accounted for 27.9% and 53.2% of the variance in the intention to quit smoking in the male and female volunteer soldiers, respectively. CONCLUSIONS: We suggest that smoking cessation strategies can reinforce gender-specific intervention strategies to assist young adult volunteer soldiers in smoking cessation.

Genetic co-expression networks contribute to creating predictive model and exploring novel biomarkers for the prognosis of breast cancer.

Genetic co-expression network (GCN) analysis augments the understanding of breast cancer (BC). We aimed to propose GCN-based modeling for BC relapse-free survival (RFS) prediction and to discover novel biomarkers. We used GCN and Cox proportional hazard regression to create various prediction models using mRNA microarray of 920 tumors and conduct external validation using independent data of 1056 tumors. GCNs of 34 identified candidate genes were plotted in various sizes. Compared to the reference model, the genetic predictors selected from bigger GCNs composed better prediction models. The prediction accuracy and AUC of 3 ~ 15-year RFS are 71.0-81.4% and 74.6-78% respectively (rfm, ACC 63.2-65.5%, AUC 61.9-74.9%). The hazard ratios of risk scores of developing relapse ranged from 1.89 ~ 3.32 (p < 10-8) over all models under the control of the node status. External validation showed the consistent finding. We found top 12 co-expressed genes are relative new or novel biomarkers that have not been explored in BC prognosis or other cancers until this decade. GCN-based modeling creates better prediction models and facilitates novel genes exploration on BC prognosis.

A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer.

BACKGROUND: Immunoglobulin-related genes are associated with the favorable prognosis of triple-negative breast cancer (TNBC) patients. We aimed to analyze the function and prognostic value of immunoglobulin lambda constant 2 (IGLC2) in TNBC patients. METHODS: We knocked down the gene expression of IGLC2 (IGLC2-KD) in MDA-MB-231 cells to evaluate the proliferation, migration, and invasion of tumors via 3-(4,5-Dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, wound healing, and transwell cell migration assay respectively. Relapse-free survival (RFS) and distant metastasis-free survival (DMFS) analyses were conducted using the KM plotter online tool. The GSE76275 data set was used to analyze the association of IGLC2 and clinical characteristics. A pathway enrichment analysis was conducted using the next-generation sequencing data of wild-type and IGLC2-KD MDA-MB-231 cells. RESULTS: The low gene expression of IGLC2 was related to unfavorable RFS, DMFS. The high expression of IGLC2 was exhibited in the basal-like immune-activated (BLIA) TNBC molecular subtype, which was immune-activated and showed excellent response to immune therapy. IGLC2 was positively correlated with programmed death-ligand 1 (PD-L1) as shown by Spearman correlation (r = 0.25, p < 0.0001). IGLC2 had a strong prognostic effect on lymph node-negative TNBC (RFS range: 0.31, q value= 8.2e-05; DMFS = 0.16, q value = 8.2e-05) but had no significance on lymph node-positive ones. The shRNA-mediated silencing of IGLC2 increased the proliferation, migration, and invasion of MDA-MB-231 cells. The results of pathway enrichment analysis showed that IGLC2 is related to the PI3K-Akt signaling pathway, MAPK signaling pathway, and extracellular matrix-receptor interaction. We confirmed that MDA-MB-231 tumor cells expressed IGLC2, subverting the traditional finding of generation by immune cells. CONCLUSIONS: IGLC2 linked with the proliferation, migration, and invasion of MDA-MB-231 cells. A high expression of IGLC2 was related to favorable prognosis for TNBC patients. IGLC2 may serve as a biomarker for the identification of TNBC patients who can benefit the most from immune checkpoint blockade treatment.

Usability of Wearable Devices With a Novel Cardiac Force Index for Estimating the Dynamic Cardiac Function: Observational Study.

BACKGROUND: Long-distance running can be a form of stress to the heart. Technological improvements combined with the public's gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied. OBJECTIVE: We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running. METHODS: This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs. RESULTS: The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = -2.702 - 0.096 × [waist circumference] - 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner's CFR varies with changes in activity. Since the runner's acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner's explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter. CONCLUSIONS: In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.

Six novel immunoglobulin genes as biomarkers for better prognosis in triple-negative breast cancer by gene co-expression network analysis.

Gene co-expression network analysis (GCNA) can detect alterations in regulatory activities in case/control comparisons. We propose a framework to detect novel genes and networks for predicting breast cancer recurrence. Thirty-four prognosis candidate genes were selected based on a literature review. Four Gene Expression Omnibus Series (GSE) microarray datasets (n = 920) were used to create gene co-expression networks based on these candidates. We applied the framework to four comparison groups according to node (+/-) and recurrence (+/-). We identified a sub-network containing two candidate genes (LST1 and IGHM) and six novel genes (IGHA1, IGHD, IGHG1, IGHG3, IGLC2, and IGLJ3) related to B cell-specific immunoglobulin. These novel genes were correlated with recurrence under the control of node status and were found to function as tumor suppressors; higher mRNA expression indicated a lower risk of recurrence (hazard ratio, HR = 0.87, p = 0.001). We created an immune index score by performing principle component analysis and divided the genes into low and high groups. This discrete index significantly predicted relapse-free survival (RFS) (high: HR = 0.77, p = 0.019; low: control). Public tool KM Plotter and TCGA-BRCA gene expression data were used to validate. We confirmed these genes are correlated with RFS and distal metastasis-free survival (DMFS) in triple-negative breast cancer (TNBC) and general breast cancer.

Risk analysis of colorectal cancer incidence by gene expression analysis.

BACKGROUND: Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction. OBJECTIVE: Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples. METHODS: We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues. RESULTS: Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method. CONCLUSIONS: Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis.

Predictors of Nicotine Dependence in Adolescents: Symptoms of Bipolar Disorder and Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: Bipolar disorder (BD) and attention-deficit/hyperactivity disorder (ADHD) have been associated with the use of cigarettes, but little is known about the impact of the subthreshold symptoms of BD or ADHD on the course of nicotine dependence. Identifying the links is essential for elucidating the pathway and supporting the development of nicotine prevention strategies for adolescents. METHODS: Participants (n = 3322) aged 15-17 years completed the Chinese version of the ADHD Self-Report Scale and the Mood Disorder Questionnaire. The modified Fagerström Tolerance Questionnaire was completed to measure their nicotine use or dependence. Mediation analyses were performed to explore the relationship of two predictors. RESULTS: The prevalence rates of cigarette smoking and nicotine dependence in this study were 14.4% and 2.3%, respectively. Male gender (odds ratio [OR] 2.30; 95% confidence interval [CI] 1.60-3.30), subclinical symptoms of ADHD (OR 1.34; 95% CI 1.04-1.71), clinical symptoms of ADHD (OR 1.69; 95% CI 1.08-2.66), and symptoms of BD (OR 1.59; 95% CI1.09 to 2.32) were associated with nicotine use. Male gender (OR 4.60; 95% CI 1.41-14.98) and symptoms of BD (OR 6.14; 95% CI 3.37-11.18), but not symptoms of ADHD, were associated with nicotine dependence. In mediation analyses, we found that the effect of ADHD symptoms was no longer significant after controlling for symptoms of BD, and the mediation ratio (PM) was 0.39. CONCLUSIONS: Our findings suggest that mood disturbances other than symptoms of ADHD are more likely to be a key predictor of nicotine dependence among adolescents. The conclusions may improve our understanding of the course of nicotine dependence and help to promote potential health policy for nicotine control among youths.

Verification of gene expression profiles for colorectal cancer using 12 internet public microarray datasets.

AIM: To verify gene expression profiles for colorectal cancer using 12 internet public microarray datasets. METHODS: Logistic regression analysis was performed, and odds ratios for each gene were determined between colorectal cancer (CRC) and controls. Twelve public microarray datasets of GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105, which included 519 cases of adenocarcinoma and 88 normal mucosa controls, were pooled and used to verify 17 selective genes from 3 published studies and estimate the external generality. RESULTS: We validated the 17 CRC-associated genes from studies by Chang et al (Model 1: 5 genes), Marshall et al (Model 2: 7 genes) and Han et al (Model 3: 5 genes) and performed the multivariate logistic regression analysis using the pooled 12 public microarray datasets as well as the external validation. The goodness-of-fit test of Hosmer-Lemeshow (H-L) showed statistical significance (P = 0.044) for Model 2 of Marshall et al in which observed event rates did not match expected event rates in subgroups of the model population. Expected and observed event rates in subgroups were similar, which are called well calibrated, in Models 1, 3 and 4 with non-significant P values of 0.460, 0.194 and 1.000 for H-L tests, respectively. A 7-gene model of CPEB4, EIF2S3, MGC20553, MS4A1, ANXA3, TNFAIP6 and IL2RB was pairwise selected, which showed the best results in logistic regression analysis (H-L P = 1.000, R (2) = 0.951, areas under the curve = 0.999, accuracy = 0.968, specificity = 0.966 and sensitivity = 0.994). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays.