Evaluation of Pm2.5 Influence on Human Lung Cancer Cells Using a Microfluidic Platform.

In this study, we developed a microfluidic device that is able to monitor cell biology under continuous PM2.5 treatment. The effects of PM2.5 on human alveolar basal epithelial cells, A549 cells, and uncovered several significant findings were investigated. The results showed that PM2.5 exposure did not lead to a notable decrease in cell viability, indicating that PM2.5 did not cause cellular injury or death. However, the study found that PM2.5 exposure increased the invasion and migration abilities of A549 cells, suggesting that PM2.5 might promote cell invasiveness. Results of RNA sequencing revealed 423 genes that displayed significant differential expression in response to PM2.5 exposure, with a particular focus on pathways associated with the generation of reactive oxygen species (ROS) and mitochondrial dysfunction. Real-time detection demonstrated an increase in ROS production in A549 cells after exposure to PM2.5. JC1 assay, which indicated a loss of mitochondrial membrane potential (ΔΨm) in A549 cells exposed to PM2.5. The disruption of mitochondrial membrane potential further supports the detrimental effects of PM2.5 on A549 cells. These findings highlight several adverse effects of PM2.5 on A549 cells, including enhanced invasion and migration capabilities, altered gene expression related to ROS pathways, increased ROS production and disruption of mitochondrial membrane potential. These findings contribute to our understanding of the potential mechanisms through which PM2.5 can impact cellular function and health.

Role of Epstein-Barr Virus in Breast Cancer: Correlation with Clinical Outcome and Survival Analysis.

Background: Breast cancer is the most prevalent cancer among women worldwide. The potential involvement of Epstein-Barr virus (EBV) in breast cancer pathogenesis has been a subject of debate, but its correlation with clinical outcomes remains uncertain. Methods: In this study, we collected 276 pathologically confirmed breast cancer tissue samples from the tissue bank of MacKay Memorial Hospital and the National Health Research Institutes in Taiwan. DNA was extracted from frozen tissue using The QIAamp DNA Mini Kit. The Taqman quantitative PCR method was employed to assess the EBV copy number per cell in these samples, using NAMALWA cells as a reference. We performed statistical analyses, including 2 × 2 contingency tables, Cox regression analysis, and Kaplan-Meier survival curves, to explore the association between clinicopathologic factors and survival outcomes in breast cancer patients. We analyzed both relapse survival, which reflects the period patients remain free from cancer recurrence post-treatment, and overall survival, which encompasses all-cause mortality. Results: Our results revealed a significant association between EBV status and relapse survival (hazard ratio: 2.75, 95% CI: 1.30, 5.86; p = 0.008) in breast cancer patients. However, no significant association was found in overall survival outcomes. Additionally, we observed significant associations between ER status and tumor histologic grade with both overall and relapse survival. Patients with EBV-positive tumors exhibited higher recurrence rates compared to those with EBV-negative tumors. Furthermore, we noted significant correlations between EBV status and HER-2 (p = 0.0005) and histological grade (p = 0.02) in our cohort of breast cancer patients. Conclusions: The presence of EBV in breast cancer tumors appears to exert an impact on patient outcomes, particularly concerning recurrence rates. Our findings highlight the significance of considering EBV status as a potential prognostic marker in breast cancer patients. Nonetheless, further research is essential to elucidate the underlying molecular mechanisms and develop novel therapeutic approaches.

Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity.

BACKGROUND: Chemosensitivity and tumor metastasis are two primary issues in cancer management. Cancer cells often exhibit a wide range of sensitivity to anti-cancer compounds. To gain insight on the genetic mechanism of drug sensitivity, one powerful approach is to employ the panel of 60 human cancer cell lines developed by the National Cancer Institute (NCI). Cancer cells also show a broad range of invasion ability. However, a genome-wide portrait on the contributing molecular factors to invasion heterogeneity is lacking. METHODS: Our lab performed an invasion assay on the NCI-60 panel. We identified invasion-associated (IA) genes by correlating our invasion profiling data with the Affymetrix gene expression data on NCI-60. We then employed the recently released chemosensitivity data of 99 anti-cancer drugs of known mechanism to investigate the gene-drug correlation, focusing on the IA genes. Afterwards, we collected data from four independent drug-testing experiments to validate our findings on compound response prediction. Finally, we obtained published clinical and molecular data from two recent adjuvant chemotherapy cohorts, one on lung cancer and one on breast cancer, to test the performance of our gene signature for patient outcome prediction. RESULTS: First, we found 633 IA genes from the invasion-gene expression correlation study. Then, for each of the 99 drugs, we obtained a subset of IA genes whose expression levels correlated with drug-sensitivity profiles. We identified a set of eight genes (EGFR, ITGA3, MYLK, RAI14, AHNAK, GLS, IL32 and NNMT) showing significant gene-drug correlation with paclitaxel, docetaxel, erlotinib, everolimus and dasatinib. This eight-gene signature (derived from NCI-60) for chemosensitivity prediction was validated by a total of 107 independent drug tests on 78 tumor cell lines, most of which were outside of the NCI-60 panel. The eight-gene signature predicted relapse-free survival for the lung and breast cancer patients (log-rank P = 0.0263; 0.00021). Multivariate Cox regression yielded a hazard ratio of our signature of 5.33 (95% CI = 1.76 to 16.1) and 1.81 (95% CI = 1.19 to 2.76) respectively. The eight-gene signature features the cancer hallmark epidermal growth factor receptor (EGFR) and genes involved in cell adhesion, migration, invasion, tumor growth and progression. CONCLUSIONS: Our study sheds light on the intricate three-way interplay among gene expression, invasion and compound-sensitivity. We report the finding of a unique signature that predicts chemotherapy survival for both lung and breast cancer. Augmenting the NCI-60 model with in vitro characterization of important phenotype-like invasion potential is a cost-effective approach to power the genomic chemosensitivity analysis.

Tissue-specific gene expression templates for accurate molecular characterization of the normal physiological states of multiple human tissues with implication in development and cancer studies.

BACKGROUND: To elucidate the molecular complications in many complex diseases, we argue for the priority to construct a model representing the normal physiological state of a cell/tissue. RESULTS: By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific Gene Expression Templates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis.Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity. CONCLUSIONS: These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.

Genome-wide expression links the electron transfer pathway of Shewanella oneidensis to chemotaxis.

BACKGROUND: By coupling the oxidation of organic substrates to a broad range of terminal electron acceptors (such as nitrate, metals and radionuclides), Shewanella oneidensis MR-1 has the ability to produce current in microbial fuel cells (MFCs). omcA, mtrA, omcB (also known as mtrC), mtrB, and gspF are some known genes of S. oneidensis MR-1 that participate in the process of electron transfer. How does the cell coordinate the expression of these genes? To shed light on this problem, we obtain the gene expression datasets of MR-1 that are recently public-accessible in Gene Expression Omnibus. We utilize the novel statistical method, liquid association (LA), to investigate the complex pattern of gene regulation. RESULTS: Through a web of information obtained by our data analysis, a network of transcriptional regulatory relationship between chemotaxis and electron transfer pathways is revealed, highlighting the important roles of the chemotaxis gene cheA-1, the magnesium transporter gene mgtE-1, and a triheme c-type cytochrome gene SO4572. CONCLUSION: We found previously unknown relationship between chemotaxis and electron transfer using LA system. The study has the potential of helping researchers to overcome the intrinsic metabolic limitation of the microorganisms for improving power density output of an MFC.

R331W Missense Mutation of Oncogene YAP1 Is a Germline Risk Allele for Lung Adenocarcinoma With Medical Actionability.

PURPOSE: Adenocarcinoma is the most dominant type of lung cancer in never-smoker patients. The risk alleles from genome-wide association studies have small odds ratios and unclear biologic roles. Here we have taken an approach featuring suitable medical actionability to identify alleles with low population frequency but high disease-causing potential. PATIENTS AND METHODS: Whole-genome sequencing was performed for a family with an unusually high density of lung adenocarcinoma with available DNA from the affected mother, four affected daughters, and one nonaffected son. Candidate risk alleles were confirmed by matrix-assisted laser desorption ionization time of flight mass spectroscopy. Validation was conducted in an external cohort of 1,135 participants without cancer and 1,312 patients with lung adenocarcinoma. Family follow-ups were performed by genotyping the relatives of the original proband and the relatives of the identified risk-allele carriers. Low-dose computed tomography scans of the chest were evaluated for lung abnormalities. RESULTS: YAP1 R331W missense mutation from the original family was identified and validated in the external controls and the cohort with lung adenocarcinoma. The YAP1 mutant-allele carrier frequency was 1.1% in patients with lung adenocarcinoma compared with 0.18% in controls (P = .0095), yielding an odds ratio (adjusted for age, sex, and smoking status) of 5.9. Among the relatives, YAP1-mutant carriers have overwhelmingly higher frequencies of developing lung adenocarcinoma or ground-glass opacity lung lesions than those who do not carry the mutation (10:0 v 1:7; P < .001). YAP1 mutation was shown to increase the colony formation ability and invasion potential of lung cancer cells. CONCLUSION: These results implicated YAP1 R331W as an allele predisposed for lung adenocarcinoma with high familial penetrance. Low-dose computed tomography scans may be recommended to this subpopulation, which is at high risk for lung cancer, for personalized prevention and health management.

Clustered genomic alterations in chromosome 7p dictate outcomes and targeted treatment responses of lung adenocarcinoma with EGFR-activating mutations.

PURPOSE: Although epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have been proven more effective for patients with lung adenocarcinoma with EGFR-activating mutation rather than wild type, the former group still includes approximately 30% nonresponders. The molecular basis of this substantial response heterogeneity is unknown. Our purpose was to seek molecular aberrations contributing to disease progression at the genome-wide level and identify the prognostic signature unique to patients with EGFR-activating mutation. PATIENTS AND METHODS: We first investigated the molecular differences between tumors with EGFR-activating mutation and wild-type tumors by conducting high-density array comparative genomic hybridization on a collection of 138 adenocarcinoma tissues. We then used an independent group of 114 patients to validate the clinical relevance of copy-number alterations (CNAs) in predicting overall and disease-free survival. Finally, focusing on 23 patients with EGFR mutation receiving EGFR-TKI treatment, we investigated the association between CNAs and response to EGFR-TKIs. RESULTS: We identified chromosome regions with differential CNAs between tumors with EGFR-activating mutation and wild-type tumors and found the aberration sites to cluster highly on chromosome 7p. A cluster of six representative chromosome 7p genes predicted overall and disease-free survival for patients with EGFR-activating mutation but not for those with wild type. Importantly, simultaneous presence of more genes with increased CNAs in this cluster correlated with less favorable response to EGFR-TKIs in patients with EGFR-activating mutation. CONCLUSION: Our results shed light on why responses to EGFR-TKIs are heterogeneous among patients with EGFR-activating mutation. They may lead to better patient management in this population.

A four-gene signature from NCI-60 cell line for survival prediction in non-small cell lung cancer.

PURPOSE: Metastasis is the main cause of mortality in non-small cell lung cancer (NSCLC) patients. Genes that can discriminate the invasion ability of cancer cells may become useful candidates for clinical outcome prediction. We identify invasion-associated genes through computational and laboratorial approach that supported this idea in NSCLC. EXPERIMENTAL DESIGN: We first conducted invasion assay to characterize the invasion abilities of NCI-60 lung cancer cell lines. We then systematically exploited NCI-60 microarray databases to identify invasion-associated genes that showed differential expression between the high and the low invasion cell line groups. Furthermore, using the microarray data of Duke lung cancer cohort (GSE 3141), invasion-associated genes with good survival prediction potentials were obtained. Finally, we validated the findings by conducting quantitative PCR assay on an in-house collected patient group (n = 69) and by using microarray data from two public western cohorts (n = 257 and 186). RESULTS: The invasion-associated four-gene signature (ANKRD49, LPHN1, RABAC1, and EGLN2) had significant prediction in three validation cohorts (P = 0.0184, 0.002, and 0.017, log-rank test). Moreover, we showed that four-gene signature was an independent prognostic factor (hazard ratio, 2.354, 1.480, and 1.670; P = 0.028, 0.014, and 0.033), independent of other clinical covariates, such as age, gender, and stage. CONCLUSION: The invasion-associated four-gene signature derived from NCI-60 lung cancer cell lines had good survival prediction power for NSCLC patients.