BackgroundGefitinib was the first epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) approved for the treatment of advanced non-small cell lung cancer (NSCLC). Few treatment options are available for NSCLC patients who have responded to gefitinib treatment and demonstrated tumor progression. The present study was conducted to evaluate the efficacy and toxicity of the 2nd EGFR-TKI administration.MethodsWe retrospectively analyzed 11 patients who had obtained a partial response (PR) or stable disease (SD) with gefitinib treatment and were re-treated with EGFR-TKI after failure of the initial gefitinib treatment.ResultsThree patients (27%) were treated with gefitinib as the 2nd EGFR-TKI, and 8 patients (73%) received erlotinib. Only one patient (9%) showed PR, 7 (64%) achieved SD, and 3 (27%) had progressive disease. The disease control rate was 73% (95% CI, 43% - 91%) and the median progression-free survival was 3.4 months (95% CI, 2 - 5.2). The median overall survival from the beginning of the 2nd EGFR-TKI and from diagnosis were 7.3 months (95% CI, 2.7 - 13) and 36.7 months (95% CI, 23.6 - 43.9), respectively. No statistical differences in PFS or OS were observed between gefitinib and erlotinib as the 2nd EGFR-TKI (PFS, P = 0.23 and OS, P = 0.052). The toxicities associated with the 2nd EGFR-TKI were generally acceptable and comparable to those observed for the initial gefitinib therapy.ConclusionsOur results indicate that a 2nd EGFR-TKI treatment can be an effective treatment option for gefitinib responders.

Cox regression is commonly used to predict the outcome by the time to an event of interest and in addition, identify relevant features for survival analysis in cancer genomics. Due to the high-dimensionality of high-throughput genomic data, existing Cox models trained on any particular dataset usually generalize poorly to other independent datasets. In this paper, we propose a network-based Cox regression model called Net-Cox and applied Net-Cox for a large-scale survival analysis across multiple ovarian cancer datasets. Net-Cox integrates gene network information into the Cox's proportional hazard model to explore the co-expression or functional relation among high-dimensional gene expression features in the gene network. Net-Cox was applied to analyze three independent gene expression datasets including the TCGA ovarian cancer dataset and two other public ovarian cancer datasets. Net-Cox with the network information from gene co-expression or functional relations identified highly consistent signature genes across the three datasets, and because of the better generalization across the datasets, Net-Cox also consistently improved the accuracy of survival prediction over the Cox models regularized by or . This study focused on analyzing the death and recurrence outcomes in the treatment of ovarian carcinoma to identify signature genes that can more reliably predict the events. The signature genes comprise dense protein-protein interaction subnetworks, enriched by extracellular matrix receptors and modulators or by nuclear signaling components downstream of extracellular signal-regulated kinases. In the laboratory validation of the signature genes, a tumor array experiment by protein staining on an independent patient cohort from Mayo Clinic showed that the protein expression of the signature gene FBN1 is a biomarker significantly associated with the early recurrence after 12 months of the treatment in the ovarian cancer patients who are initially sensitive to chemotherapy. Net-Cox toolbox is available at http://compbio.cs.umn.edu/Net-Cox/.

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HtrA1 belongs to a family of serine proteases found in organisms ranging from bacteria to humans. Bacterial HtrA1 (DegP) is a heat shock-induced protein that behaves as a chaperone at low temperature and as a protease at high temperature to help remove unfolded proteins during heat shock. In contrast to bacterial HtrA1, little is known about the function of human HtrA1. Here, we report the first evidence that human HtrA1 is a microtubule-associated protein and modulates microtubule stability and cell motility. Intracellular HtrA1 is localized to microtubules in a PDZ (PSD95, Dlg, ZO1) domain-dependent, nocodazole-sensitive manner. During microtubule assembly, intracellular HtrA associates with centrosomes and newly polymerized microtubules. In vitro, purified HtrA1 promotes microtubule assembly. Moreover, HtrA1 cosediments and copurifies with microtubules. Purified HtrA1 associates with purified ␣-and ␤-tubulins, and immunoprecipitation of endogenous HtrA1 results in coprecipitation of ␣-, ␤-, and ␥-tubulins. Finally, downregulation of HtrA1 promotes cell motility, whereas enhanced expression of HtrA1 attenuates cell motility. These results offer an original identification of HtrA1 as a microtubule-associated protein and provide initial mechanistic insights into the role of HtrA1 in theregulation of cell motility by modulating microtubule stability.

Nonessential tRNA modifications by methyltransferases are evolutionarily conserved and have been reported to stabilize mature tRNA molecules and prevent rapid tRNA decay (RTD). The tRNA modifying enzymes, NSUN2 and METTL1, are mammalian orthologs of yeast Trm4 and Trm8, which are required for protecting tRNA against RTD. A simultaneous overexpression of NSUN2 and METTL1 is widely observed among human cancers suggesting that targeting of both proteins provides a novel powerful strategy for cancer chemotherapy. Here, we show that combined knockdown of NSUN2 and METTL1 in HeLa cells drastically potentiate sensitivity of cells to 5-fluorouracil (5-FU) whereas heat stress of cells revealed no effects. Since NSUN2 and METTL1 are phosphorylated by Aurora-B and Akt, respectively, and their tRNA modifying activities are suppressed by phosphorylation, overexpression of constitutively dephosphorylated forms of both methyltransferases is able to suppress 5-FU sensitivity. Thus, NSUN2 and METTL1 are implicated in 5-FU sensitivity in HeLa cells. Interfering with methylation of tRNAs might provide a promising rationale to improve 5-FU chemotherapy of cancer.