Shih Hsin Tu

Overexpression and Activation of the α9-Nicotinic Receptor During Tumorigenesis in Human Breast Epithelial Cells

BACKGROUND Large epidemiological cohort studies in the United States have indicated that active and passive smoking are associated with increased breast cancer risk. However, there was no direct evidence of an effect of tobacco carcinogens on the cellular molecules involved in breast tumorigenesis. METHODS Reverse transcription-polymerase chain reaction was used to determine the expression of all of the nicotinic acetylcholine receptor (nAChR) subunits in 50 human breast cancer samples and to determine the expression of the alpha9-nAChR subunit in 276 surgical and laser capture microdissected breast tumor vs normal tissue pairs. Stable MDA-MB-231 breast cancer cell lines were established in which expression of the alpha9-nAChR subunit was inhibited using short interfering RNA. MCF-10A normal human breast epithelial cells were established in which the alpha9-nAChR subunit could be conditionally overexpressed by removal of doxycycline from the culture fluid. Cell proliferation and soft agar assays and tumor growth in nude mice were used as measures of cell transformation. All statistical tests were two-sided. RESULTS In 186 (67.3%) of the 276 paired samples, alpha9-nAChR mRNA was expressed at (mean 7.84-fold) higher levels in breast cancers than in surrounding normal tissue. Stable expression of alpha9-nAChR short interfering RNA in MDA-MB-231 cells attenuated nicotine-stimulated proliferation and growth in soft agar and reduced tumor volume when the cells were introduced as xenografts in SCID mice (n = 5 mice per group; mean tumor volume at 6 weeks treatment in mice injected with Si alpha9 cells = 995.6 mm(3), in mice injected with parental cells = 2993.2 mm(3), difference = 1997.6 mm(3), 95% confidence interval [CI] = 1705 to 2290.2 mm(3), P = .009). Long-term treatment of MCF-10A normal breast epithelial cells with either nicotine or its active metabolite, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, triggered precancerous transformation as defined by soft agar assay. Inducible overexpression of alpha9-nAChR in MCF-10A cell xenografts in nude mice substantially increased tumor growth (n = 5 mice per group; DOX+, mean tumor volume without nicotine vs with nicotine = 266.2 vs 501.6 mm(3), difference = 235.4 mm(3), 95% CI = 112.7 to 358 mm(3), P = .009; DOX-, mean tumor volume without nicotine vs with nicotine = 621.2 vs 898.6 mm(3), difference = 277.4 mm(3), 95% CI = 98.1 to 456.7 mm(3), P = .016; mean tumor volume in the presence of nicotine, DOX+ vs DOX- = 501.6 vs 898.6 mm(3), difference = 397 mm(3), 95% CI = 241.3 to 552.6 mm(3), P = .009). CONCLUSION The alpha9-nAChR is important for nicotine-induced transformation of normal human breast epithelial cells.

Concurrent Gene Signatures for Han Chinese Breast Cancers

The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.

Luteolin sensitises drug-resistant human breast cancer cells to tamoxifen via the inhibition of cyclin E2 expression

Luteolin is a flavonoid that has been identified in many plant tissues and exhibits chemopreventive or chemosensitising properties against human breast cancer. However, the oncogenic molecules in human breast cancer cells that are inhibited by luteolin treatment have not been identified. This study found that the level of cyclin E2 (CCNE2) mRNA was higher in tumour cells (4.89-fold, (∗)P=0.005) than in normal paired tissue samples as assessed using real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis (n=257). Further, relatively high levels of CCNE2 protein expression were detected in tamoxifen-resistant (TAM-R) MCF-7 cells. These results showed that the level of CCNE2 protein expression was specifically inhibited in luteolin-treated (5μM) TAM-R cells, either in the presence or absence of 4-OH-TAM (100nM). Combined treatment with 4-OH-TAM and luteolin synergistically sensitised the TAM-R cells to 4-OH-TAM. The results of this study suggest that luteolin can be used as a chemosensitiser to target the expression level of CCNE2 and that it could be a novel strategy to overcome TAM resistance in breast cancer patients.

SP1-regulated p27/Kip1 gene expression is involved in terbinafine-induced human A431 cancer cell differentiation: An in vitro and in vivo study

In this study, the differentiation-promoting effects of terbinafine (Lamisil), TB) were investigated in human epithelioid squamous carcinoma (A431) cells. The polyhydroxyethylmethacrylate (poly-HEMA)- and type-I collagen-coated culture plate models were adapted to harvest the TB-induced differentiated cells by agitation of the suspension medium. We demonstrated that p27/Kip1, p21/Cip1 and the keratinocyte differentiation marker, human involucrin (hINV), were induced (>25 microM) in TB-induced differentiated A431 cells. Animal studies demonstrated that administration of TB (10 mg/kg body weight) inhibited A431-xenografted tumor growth through differentiation processes as evidenced by expression of pancytokeratin in tumor tissues. Immunocytochemical staining analysis showed that p27/Kip1, but not p21/Cip1, positive-stained cells were detected in the early-differentiated cells of TB-treated tumor tissues. SP1, which regulates p27/Kip1 expression, was induced by TB (>10 microM) in A431 cells. The TB-induced promoter activity and protein expression levels of p27/Kip1 were significantly attenuated by pretreatment with mithramycin A, a SP1 specific inhibitor. We also demonstrated that TB-induced differentiated A431 cells sorted from the poly-HEMA-coated culture plates were arrested in the G1 phase. TB-induced G1 arrest in the suspension-cultured cells was attenuated by mithramycin A pretreatment. Such results suggest that SP1 plays a critical role in the p27/Kip1 gene transcriptional activation that may be subsequently involved in the TB-induced A431 cancer cell differentiation process.

Prediction consistency and clinical presentations of breast cancer molecular subtypes for Han Chinese population

BackgroundBreast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) as well as clinical presentations of each molecualr subtype in Han Chinese population.MethodsIn all, 169 breast cancer samples (44 from Taiwan and 125 from China) of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) were retrieved for molecular subtype prediction.ResultsFor Sørlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD) remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed.ConclusionsWe suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective study with longer survival data is needed.

Quality of Life in Taiwanese Breast Cancer Survivors With Breast-conserving Therapy

BACKGROUND/PURPOSE Breast cancer is the most common female malignancy in Taiwan; however, quality of life (QOL) following breast cancer therapy remains rarely studied. The aim of the present study was to evaluate QOL among Taiwanese breast cancer patients with and without breast-conserving therapy. METHODS A total of 130 women with breast cancer (37 with breast-conserving therapy and 93 with modified radical mastectomy) were enrolled between August, 2004 and December, 2007 in a single center. Patients who underwent breast-conserving therapy were younger, less likely to be married, had a higher educational level, and were at an earlier clinical stage than those who underwent modified radical mastectomy. The traditional Chinese version of the European Organization for Research and Treatment of Cancer QLQ-C30 and QLQ-BR23 questionnaires were used as measuring instruments. Structural equation modeling with mean structural analysis, which evaluates configuration invariance and compares groups for latent functional/symptomatic factors, was constructed using a multi-indicators approach. RESULTS Patients with breast-conserving therapy reported worse global QOL status and role function scores and higher symptomatic scores for fatigue, pain, dyspnea, insomnia, appetite loss, breast and arm problem subscales than those without conserving therapy. In addition, age, marital status, hormone manipulation and postoperative adjuvant therapy were significant confounders for QOL. Measurement invariance was ascertained and the same QOL construct could be applied to Taiwanese subjects with and without breast-conserving therapy. CONCLUSION Our study suggests that breast-conserving therapy might be associated with worse perceived QOL for Taiwanese breast cancer survivors.

A model-based circular binary segmentation algorithm for the analysis of array CGH data

BackgroundCircular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-t test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent implementation utilizing a hybrid method and early stopping rules (hybrid CBS) to improve the performance in speed was subsequently proposed. However, a time analysis revealed that a major portion of computation time of the hybrid CBS was still spent on permutation. In addition, what the hybrid method provides is an approximation of the significance upper bound or lower bound, not an approximation of the significance of change-points itself.ResultsWe developed a novel model-based algorithm, extreme-value based CBS (eCBS), which limits permutations and provides robust results without loss of accuracy. Thousands of aCGH data under null hypothesis were simulated in advance based on a variety of non-normal assumptions, and the corresponding maximal-t distribution was modeled by the Generalized Extreme Value (GEV) distribution. The modeling results, which associate characteristics of aCGH data to the GEV parameters, constitute lookup tables (eXtreme model). Using the eXtreme model, the significance of change-points could be evaluated in a constant time complexity through a table lookup process.ConclusionsA novel algorithm, eCBS, was developed in this study. The current implementation of eCBS consistently outperforms the hybrid CBS 4× to 20× in computation time without loss of accuracy. Source codes, supplementary materials, supplementary figures, and supplementary tables can be found at http://ntumaps.cgm.ntu.edu.tw/eCBSsupplementary.

The in vivo antitumor effects on human COLO 205 cancer cells of the 4,7-dimethoxy-5-(2-propen-1-yl)-1,3-benzodioxole (apiole) derivative of 5-substituted 4,7-dimethoxy-5-methyl-l,3-benzodioxole (SY-1) isolated from the fruiting body of Antrodia camphorate.

CONTEXT The compound 4,7-dimethoxy-5-(2-propen-1-yl)-1,3-benzodioxole (apiole) has been isolated from several different plant species, including Petroselinum sativum. Our recent study found that apiole is a chemical derivative of 4,7-dimethoxy-5-methyl-l,3-benzodioxole (SY-1), which has been isolated from dried Antrodia camphorata (AC ) fruiting bodies, a traditional Chinese medicine with antitumor properties. AIMS Our previous in vitro study demonstrated that apiole inhibits the growth of human colon (COLO 205) cancer cells through the arrest of the cell cycle in G0/G1 phase. The in vivo antitumor effects of apiole were evaluated in this study. SETTING AND DESIGN Apiole was administered to mice at 1-30 mg/kg body weight through intraperitoneal (I.P.) injection three times per week (defined as a dosage of 1×-30×). MATERIALS AND METHODS The in vivo antitumor effects of apiole were evaluated in mice with xenografts of COLO 205 cells. STATISTICAL ANALYSIS All of the data are reported as the means ± S.E. Comparisons were performed with a one-way analysis of variance (ANOVA) followed by a Fishers least significant difference test. Significance was defined as P < 0.05. RESULTS Apiole (> 1×) markedly decreased the growth of COLO 205 human colon cancer cell tumor xenografts in an athymic nude mouse model system through the up-regulation of cell cycle regulators, such as p53, p21/Cip1, and p27/Kip1. The apiole-induced increase in G0/G1 phase cell cycle regulators was also associated with a significant decrease in the expression of cyclins D1 and D3. Surprisingly, statistically significantly higher tumor volumes were observed in mice that received 5× apiole compared with 30× apiole-treated mice (P < 0.05). No gross signs of toxicity were observed (e.g., body weight changes, general appearance, or individual organ effects) in any group. CONCLUSIONS Our results show, for the first time, the promising antitumor effects of apiole against colon tumors in an in vivo xenograft model.

Multiclass Prediction with Partial Least Square Regression for Gene Expression Data: Applications in Breast Cancer Intrinsic Taxonomy

Multiclass prediction remains an obstacle for high-throughput data analysis such as microarray gene expression profiles. Despite recent advancements in machine learning and bioinformatics, most classification tools were limited to the applications of binary responses. Our aim was to apply partial least square (PLS) regression for breast cancer intrinsic taxonomy, of which five distinct molecular subtypes were identified. The PAM50 signature genes were used as predictive variables in PLS analysis, and the latent gene component scores were used in binary logistic regression for each molecular subtype. The 139 prototypical arrays for PAM50 development were used as training dataset, and three independent microarray studies with Han Chinese origin were used for independent validation (n = 535). The agreement between PAM50 centroid-based single sample prediction (SSP) and PLS-regression was excellent (weighted Kappa: 0.988) within the training samples, but deteriorated substantially in independent samples, which could attribute to much more unclassified samples by PLS-regression. If these unclassified samples were removed, the agreement between PAM50 SSP and PLS-regression improved enormously (weighted Kappa: 0.829 as opposed to 0.541 when unclassified samples were analyzed). Our study ascertained the feasibility of PLS-regression in multi-class prediction, and distinct clinical presentations and prognostic discrepancies were observed across breast cancer molecular subtypes.

Identification of genes and pathways related to lymphovascular invasion in breast cancer patients: A bioinformatics analysis of gene expression profiles:

Surgery is the most effective treatment for breast cancer patients. However, some patients developed recurrence and distant metastasis after surgery. Adjuvant therapy is considered for high-risk patients depending on several prognostic markers, and lymphovascular invasion has become one of such prognostic markers that help physicians to identify the risk for distant metastasis and recurrence. However, the mechanism of lymphovascular invasion in breast cancer remains unknown. This study aims to unveil the genes and pathways that may involve in lymphovascular invasion in breast cancer. In total, 108 breast cancer samples were collected during surgery and microarray analysis was performed. Significance analysis of the microarrays and limma package for R were used to examine differentially expressed genes between lymphovascular invasion–positive and lymphovascular invasion–negative cases. Network and pathway analyses were mapped using the Ingenuity Pathway Analysis and the Database for Annotation, Visualization and Integrated Discovery. In total, 86 differentially expressed genes, including 37 downregulated genes and 49 upregulated genes were identified in lymphovascular invasion–positive patients. Among these genes, TNFSF11, IL6ST, and EPAS1 play important roles in cytokine–receptor interaction, which is the most enriched pathway related to lymphovascular invasion. Moreover, the results also suggested that an imbalance between extracellular matrix components and tumor micro-environment could induce lymphovascular invasion. Our study evaluated the underlying mechanisms of lymphovascular invasion, which may further help to assess the risk of breast cancer progression and identify potential targets of adjuvant treatment.