Purpose: A major obstacle in chemotherapy is treatment failure due to anticancer drug resistance. The emergence of acquired resistance results from host factors and genetic or epigenetic changes in the cancer cells. The purpose of this study was to identify differentially expressed genes associated with acquisition of resistance in human gastric cancer cells.Experimental Design: We performed global gene expression analysis in the acquired drug-resistant gastric cancer cell lines to the commonly used drugs 5-fluorouracil, doxorubicin, and cisplatin using Affymetrix HG-U133A microarray. The gene expression patterns of 10 chemoresistant gastric cancer cell lines were compared with those of four parent cell lines using fold-change and Wilcoxon's test for data analysis.Results: We identified over 250 genes differentially expressed in 5-fluorouracil-, cisplatin-, or doxorubicin-resistant gastric cancer cell lines. Our expression analysis also identified eight multidrug resistance candidate genes that were associated with resistance to two or more of the tested chemotherapeutic agents. Among these, midkine (MDK), a heparin-binding growth factor, was overexpressed in all drug-resistant cell lines, strongly suggesting that MDK might contribute to multidrug resistance in gastric cancer cells.Conclusions: Our investigation provides comprehensive gene information associated with acquired resistance to anticancer drugs in gastric cancer cells and a basis for additional functional studies.

A major obstacle in treatment of epithelial ovarian cancer is chemoresistance. The aim of this study was to determine whether distinct gene expression profiles are associated with chemoresistance in epithelial ovarian carcinoma. We performed global gene expression analysis in 13 primary epithelial ovarian cancer tissues including 5 primary chemosensitive tumors and 8 primary chemoresistant tumors using Affymetrix HGU133A microarray. The gene expression patterns of chemosensitive tumors were compared with those of chemoresistant tumors using fold change. Validity of microarray results was examined by semiquantitative RT-PCR. We identified over 320 genes differentially expressed in chemoresistant epithelial ovarian cancer (> or = twofold). Upregulated genes in chemoresistant tumors included cell cycle regulating genes (TOP2A, BCAT1, CDCA8, CCNA2, CENPE), and genes with previously known mechanisms in tumorigenesis (S100A9, APOA1, RNF125, IFI16). Downregulated genes in chemoresistant tumors included genes related to cell adhesion (MUC5B, CITED2), transcription regulating genes (FOXD1, MAD1L1, PAX2), genes involving signal transduction (SOSTDC1, SNX1, SFRP1, FOXA2, PLK2), and stress protein gene (TP53AP1). These data show that gene expression profiling can discriminate primary chemoresistant from primary chemosensitive ovarian cancers. This type of molecular profiling could provide a basis for additional functional studies.

The Aurora-A kinase gene is frequently amplified and/or over-expressed in a variety of human cancers, leading to major efforts to develop therapeutic agents targeting this pathway. Here we demonstrate that Aurora-A is targeted for ubiquitination and subsequent degradation by the F-box protein FBXW7 in a process that is regulated by GSK3β. Using a series of truncated Aurora-A proteins and site directed mutagenesis, we identified distinct FBXW7 and GSK3β binding sites in Aurora-A. Mutation of critical residues in either site substantially disrupts degradation of Aurora-A. Furthermore, we show that loss of Pten results in the stabilization of Aurora-A by attenuating FBXW7-dependent degradation of Aurora-A through the AKT/GSK3β pathway. Moreover, radiation-induced tumor latency is significantly shortened in Fbxw7+/− Pten+/− mice as compared to either Fbxw7+/− or Pten+/− mice, indicating that Fbxw7 and Pten appear to cooperate in suppressing tumorigenesis. Our results establish a novel posttranslational regulatory network in which the Pten and Fbxw7 pathways appear to converge on the regulation of Aurora-A level.

Malignant pleural mesothelioma (MPM), a rare malignancy with a poor prognosis, is mainly caused by exposure to asbestos or other organic fibers, but the underlying genetic mechanism is not fully understood. Genetic alterations and causes for multiple primary cancer development including MPM are unknown. We used whole exome sequencing to identify somatic mutations in a patient with MPM and two additional primary cancers who had no evidence of venous, arterial, lymphovascular, or perineural invasion indicating dissemination of a primary lung cancer to the pleura. We found that the MPM had R282W, a key TP53 mutation, and genome-wide allelic loss or loss of heterozygosity, a distinct genomic alteration not previously described in MPM. We identified frequent inactivating SETDB1 mutations in this patient and in 68 additional MPM patients (mutation frequency: 10%, 7/69) by targeted deep sequencing. Our observations suggest the possibility of a new genetic mechanism in the development of either MPM or multiple primary cancers. The frequent SETDB1 inactivating mutations suggest there could be new diagnostic or therapeutic options for MPM.

Analysis of gene expression patterns in normal tissues and their perturbations in tumors can help to identify the functional roles of oncogenes or tumor suppressors and identify potential new therapeutic targets. Here, gene expression correlation networks were derived from 92 normal human lung samples and patient-matched adenocarcinomas. The networks from normal lung show that NKX2-1 is linked to the alveolar type 2 lineage, and identify PEBP4 as a novel marker expressed in alveolar type 2 cells. Differential correlation analysis shows that the NKX2-1 network in tumors includes pathways associated with glutamate metabolism, and identifies Vaccinia-related kinase (VRK1) as a potential drug target in a tumor-specific mitotic network. We show that VRK1 inhibition cooperates with inhibition of PARP signaling to inhibit growth of lung tumor cells. Targeting of genes that are recruited into tumor mitotic networks may provide a wider therapeutic window than that seen by inhibition of known mitotic genes.

Purpose To investigate the role of the PER3 circadian rhythm gene, located within the commonly deleted region of chromosome 1p36, in human breast cancer development. Patients and Methods The frequency of genetic alterations at 1p36 and PER3 gene copy number status were analyzed in 180 lymph node–negative breast cancers from patients who had received treatment with chemotherapy and/or tamoxifen. The expression levels of PER3 were also analyzed using published microarray profiles from > 400 breast cancer samples. Finally, the effect of loss of Per3 on tumor susceptibility was tested using two mouse models of breast cancer. Results Deletion of PER3 is directly related to tumor recurrence in patients with estrogen receptor (ER) – positive breast cancers treated with tamoxifen. Low expression of PER3 mRNA is associated with poor prognosis, particularly in a subset of tumors that are ER positive, and either luminal A or ERBB2-positive tumors. Mice deficient in Per3 showed increased susceptibility to breast cancer induced by carcinogen treatment or by overexpression of Erbb2. Conclusion Disruption of PER3 function may serve as an indicator of probability of tumor recurrence in patients with ER-positive tumors. Further investigations of this pathway may reveal links between deregulation of sleep homeostasis and breast tumorigenesis.

BackgroundGermline polymorphisms can influence gene expression networks in normal mammalian tissues and can affect disease susceptibility. We and others have shown that analysis of this genetic architecture can identify single genes and whole pathways that influence complex traits, including inflammation and cancer susceptibility. Whether germline variants affect gene expression in tumors that have undergone somatic alterations, and the extent to which these variants influence tumor progression, is unknown.ResultsUsing an integrated linkage and genomic analysis of a mouse model of skin cancer that produces both benign tumors and malignant carcinomas, we document major changes in germline control of gene expression during skin tumor development resulting from cell selection, somatic genetic events, and changes in the tumor microenvironment. The number of significant expression quantitative trait loci (eQTL) is progressively reduced in benign and malignant skin tumors when compared to normal skin. However, novel tumor-specific eQTL are detected for several genes associated with tumor susceptibility, including IL18 (Il18), Granzyme E (Gzme), Sprouty homolog 2 (Spry2), and Mitogen-activated protein kinase kinase 4 (Map2k4).ConclusionsWe conclude that the genetic architecture is substantially altered in tumors, and that eQTL analysis of tumors can identify host factors that influence the tumor microenvironment, mitogen-activated protein (MAP) kinase signaling, and cancer susceptibility.

IntroductionColorectal cancer is the third most common cancer in the world, a small fraction of which is represented by locally advanced rectal cancer (LARC). If not medically contraindicated, preoperative chemoradiotherapy, represent the standard of care for LARC patients. Unfortunately, patients shows a wide range of response rates in which approximately 20% has a complete pathological response, whereas in 20 to 40% the response is poor or absent.ResultsThe following specific gene signature, able to discriminate responders' patients from non-responders, were founded: AKR1C3, CXCL11, CXCL10, IDO1, CXCL9, MMP12 and HLA-DRA. These genes are mainly involved in immune system pathways and interact with drugs traditionally used in the adjuvant treatment of rectal cancer.DiscussionThe present study suggests that new ideas for therapy could be found not only limited to studying genes differentially expressed between the two groups of patients but deepening the mechanisms, associated to response, in which they are involved.MethodsGene expression studies performed by: Agostini et al., Rimkus et al. and Kim et al. have been merged through a meta-analysis of the raw data. Gene expression data-sets have been processed using A-MADMAN. Common differentially expressed gene (DEG) were identified through SAM analysis. To further characterize the identified DEG we deeply investigated its biological role using an integrative computational biology approach.