Gene expression profiles for predicting the efficacy of the anticancer drug 5-fluorouracil in breast cancer

Roles of CCR10/CCL27-CCL28 axis in tumour development: mechanisms, diagnostic and therapeutic approaches, and perspectives

Cancer is now one of the major causes of death across the globe. The imbalance of cytokine and chemokine secretion has been reported to be involved in cancer development. Meanwhile, CC chemokines have received considerable interest in cancer research. CCR10, as the latest identified CC chemokine receptor (CCR), has been implicated in the recruitment and infiltration of immune cells, especially lymphocytes, into epithelia such as skin via ligation to two ligands, CCL27 and CCL28. Other than homoeostatic function, several mechanisms have been shown to dysregulate CCR10/CCL27-CCL28 expression in the tumour microenvironment. As such, these receptors and ligands mediate T-cell trafficking in the tumour microenvironment. Depending on the types of lymphocytes recruited, CCR10/CCL27-CCL28 interaction has been shown to play conflicting roles in cancer development. If they were T helper and cytotoxic T cells and natural killer cells, the role of this axis would be tumour-suppressive. In contrast, if CCR10/CCL27-CCL28 recruited regulatory T cells, cancer-associated fibroblasts or myeloid-derived suppressor cells, it would lead to tumour progression. In addition to the trafficking of lymphocytes and immune cells, CCR10 also leads to the migration of tumour cells or endothelial cells (called angiogenesis and lymphangiogenesis) to promote tumour metastasis. Furthermore, CCR10 signalling triggers tumour-promoting signalling such as PI3K/AKT and mitogen-activated protein kinase/extracellular signal-regulated kinase, resulting in tumour cell growth. Since CCR10/CCL27-CCL28 is dysregulated in the tumour tissues, it is suggested that analysis and measurement of them might predict tumour development. Finally, it is hoped using therapeutic approaches based on this axis might increase our knowledge to overcome tumour progression.

FAM46A expression is elevated in glioblastoma and predicts poor prognosis of patients

OBJECTIVE

To study the expression of FAM46A in glioblastoma (GBM) and analyze its significance in predicting the prognosis of patients.

MATERIALS AND METHODS

mRNA expression and clinical data of patients with GBM were retrieved from ONCOMINE databases and The Cancer Genome Atlas (TCGA) database. Immunohistochemistry was performed in a tissue microarray including 110 GBM cases and 12 normal controls to determine the expression of FAM46A protein. Then, Kaplan-Meier curve and Cox regression model were used to investigate the relationship between FAM46A expression and clinical outcome. Coexpressed genes of FAM46A were analyzed by Linked Omics, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG).

RESULTS

Upregulated expression of FAM46A was found in both TCGA and our cohort. High FAM46A expression was associated with the poor prognosis of patients with GBM and could be identified as an independent risk factor for overall survival (HR = 1.652, p = 0.022). Further bioinformatics analysis revealed that FAM46A might be involved in cell motility and endoplasmic reticulum proteostasis and stress to promote GBM progression.

CONCLUSION

Our findings suggest that increased expression of FAM46A in GBM is a novel biomarker for predicting poor outcome of patients and that targeting FAM46A may serve as a potential therapy for this disease.

Identification of the potential biomarkers in patients with glioma: a weighted gene co-expression network analysis

Glioma is the most common brain tumor with high mortality. However, there are still challenges for the timely and accurate diagnosis and effective treatment of the tumor. One hundred and twenty-one samples with grades II, III and IV from the Gene Expression Omnibus database were used to construct gene co-expression networks to identify hub modules closely related to glioma grade, and performed pathway enrichment analysis on genes from significant modules. In gene co-expression network constructed by 2345 differentially expressed genes from 121 gene expression profiles for glioma, we identified the black and blue modules that associated with grading. The module preservation analysis based on 118 samples indicates that the two modules were replicable. Enrichment analysis showed that the extracellular matrix genes were enriched for blue module, while cell division genes were enriched for black module. According to survival analysis, 21 hub genes were significantly up-regulated and one gene was significantly down-regulated. What’s more, IKBIP, SEC24D, and FAM46A are the genes with little attention among the 22 hub genes. In this study, IKBIP, SEC24D, and FAM46A related to glioma were mentioned for the first time to the current knowledge, which might provide a new idea for us to study the disease in the future. IKBIP, SEC24D and FAM46A among the 22 hub genes identified that are related to the malignancy degree of glioma might be used as new biomarkers to improve the diagnosis, treatment and prognosis of glioma.

Phosphatidylinositol 4-phosphate adaptor protein 2 accelerates the proliferation and invasion of hepatocellular carcinoma cells by enhancing Wnt/β-catenin signaling

Phosphatidylinositol 4-phosphate adaptor protein 2 (FAPP2) has been recently identified as a tumor-associated regulator that is closely related to tumorigenesis. Yet, the precise role of FAPP2 in hepatocellular carcinoma (HCC) is still largely unknown. This study was designed to determine the function and molecular mechanisms of FAPP2 in HCC. Elevated expression of FAPP2 commonly occurred in the tumor tissue of HCC compared with normal controls. High expression of FAPP2 was also detected in HCC cell lines and its knockdown markedly decreased the proliferation, colony formation and invasion of HCC cells. Upregulation of FAPP2 by using a FAPP2 expression vector markedly promoted the proliferation, colony formation and invasion of HCC cells. FAPP2 was found to promote the activation of Wnt/β-catenin signaling. Importantly, inhibition of Wnt/β-catenin signaling abrogated the FAPP2 overexpression-conferred oncogenic effect in HCC cells. In addition, xenograft tumor experiments revealed that knockdown of FAPP2 significantly decreased the tumorigenicity of HCC cells in vivo. Taken together, the data of our study reported a tumor-promotion function of FAPP2 in HCC and demonstrate that knockdown of FAPP2 was capable of suppressing HCC cell proliferation and invasion through downregulation of Wnt/β-catenin signaling. This study indicated that FAPP2 might be an attractive candidate anticancer target for HCC.

Ellagic acid induces cell cycle arrest and apoptosis through TGF-β/Smad3 signaling pathway in human breast cancer MCF-7 cells

Breast cancer represents the second leading cause of cancer-related deaths among women worldwide and preventive therapy could reverse or delay the devastating impact of this disease. Ellagic acid (EA), a dietary flavonoid polyphenol which is present in abundance in pomegranate, muscadine grapes, walnuts and strawberries, has been shown to inhibit cancer cells proliferation and induce apoptosis. Here, we investigated the growth inhibitory effects of EA on MCF-7 breast cancer cells. In the present study, we first found that EA inhibits the proliferation of MCF-7 breast cancer cells mainly mediated by arresting cell cycle in the G0/G1 phase. Moreover, gene expression profiling of MCF-7 breast cancer cell line treated with EA for 6, 12 and 24 h was performed using cDNA microarray. A total of 4,738 genes were found with a >2.0-fold change after 24 h of EA treatment. Among these genes, 2,547 were downregulated and 2,191 were upregulated. Furthermore, the changes of 16 genes, which belong to TGF-β/Smads signaling pathway, were confirmed by real-time RT-PCR and/or western blot analysis. TGF-β/Smads signaling pathway was found as the potential molecular mechanism of EA to regulate breast cancer cell cycle arrest in vitro. Therefore, the regulation of TGF-β/Smads pathway in breast cancer cells could be a novel therapeutic approach for the treatment of patients with breast cancer. Further studies with in vitro models, as well as an analysis of additional human samples, are still needed to confirm the molecular mechanisms of EA in inhibition or prevention of breast cancer growth.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

5-Fluorouracil induced intestinal mucositis via nuclear factor-κB activation by transcriptomic analysis and in vivo bioluminescence imaging

5-Fluorouracil (5-FU) is a commonly used drug for the treatment of malignant cancers. However, approximately 80% of patients undergoing 5-FU treatment suffer from gastrointestinal mucositis. The aim of this report was to identify the drug target for the 5-FU-induced intestinal mucositis. 5-FU-induced intestinal mucositis was established by intraperitoneally administering mice with 100 mg/kg 5-FU. Network analysis of gene expression profile and bioluminescent imaging were applied to identify the critical molecule associated with 5-FU-induced mucositis. Our data showed that 5-FU induced inflammation in the small intestine, characterized by the increased intestinal wall thickness and crypt length, the decreased villus height, and the increased myeloperoxidase activity in tissues and proinflammatory cytokine production in sera. Network analysis of 5-FU-affected genes by transcriptomic tool showed that the expression of genes was regulated by nuclear factor-κB (NF-κB), and NF-κB was the central molecule in the 5-FU-regulated biological network. NF-κB activity was activated by 5-FU in the intestine, which was judged by in vivo bioluminescence imaging and immunohistochemical staining. However, 5-aminosalicylic acid (5-ASA) inhibited 5-FU-induced NF-κB activation and proinflammatory cytokine production. Moreover, 5-FU-induced histological changes were improved by 5-ASA. In conclusion, our findings suggested that NF-κB was the critical molecule associated with the pathogenesis of 5-FU-induced mucositis, and inhibition of NF-κB activity ameliorated the mucosal damage caused by 5-FU.