Background: TIAM2, a Rac guanine nucleotide exchange factor, is closely associated with cell adherence and migration. Here, we aimed to investigate the role of TIAM2 in non-small cell lung cancer (NSCLC) cells. Materials and Methods: A small interference RNA (siRNA) was introduced to silence the expression of TIAM2. Invasion and motility assays were then performed to assess the invasion and motility potential of NSCLC cells. GST-pull down assays were used to detect activation of Rac1. Results: TIAM2 was highly expressed in NSCLC cells. Knockdown of TIAM2 inhibited the invasion and motility, and suppressed activation of Rac1. Further experiments demonstrated that knockdown of TIAM2 could up-regulate the expression of E-cadherin, and downregulate the expression of MMP-3, Twist and Snail. Conclusions: Our data suggest that TIAM2 can promote invasion and motility of NSCLC cells. Activation of Rac1 and regulation of some EMT/invasion-related genes may be involved in the underlying processes.

Backgroung: Tumor microenvironment (TME) has gradually emerged as an important research topic in the fight against cancer. The immune system is a major contributing factor in TME, and investigations have revealed that tumors are partially infiltrated with numerous immune cell subsets.Method: We obtained transcriptome RNA-seq data from the the Cancer Genome Atlas databases for 521 patients with colon adenocarcinoma (COAD). ESTIMATE algorithms are then used to estimate the fraction of stromal and immune cells in COAD samples.Result: A total of 1109 stromal-immune score-related differentially expressed genes were identified and used to generate a highconfidence protein-protein interaction network and univariate COX regression analysis. C-X-C motif chemokine 10 (CXCL10) was identified as the core gene by intersection analysis of data from protein-protein interaction network and univariate COX regression analysis. Then, for CXCL10, we performed gene set enrichment analysis, survival analysis and clinical analysis, and we used CIBERSORT algorithms to estimate the proportion of tumor-infiltrating immune cells in COAD samples. Conclusion:We discovered that CXCL10 levels could be effective for predicting the prognosis of COAD patients as well as a clue that the status of TME is transitioning from immunological to metabolic activity, which provided additional information for COAD therapies.Abbreviations: COAD = colon adenocarcinoma, CRC = colorectal cancer, CXCL10 = C-X-C motif chemokine 10, DEGs = differentially expressed genes, GO = gene ontology, GSEA = gene set enrichment analysis, KEGG = Kyoto Encyclopedia of Genes and Genomes, M = metastasis, N = lymph node staging, PPI = protein-protein interaction, T = tumor infiltration depth, TCGA = the Cancer Genome Atlas, TICs = tumor-infiltrating immune cells, TME = tumor microenvironment.

Background: Despite advances in the treatment of breast cancer, there remains a significant clinical need for improved therapeutic strategies for patients with the most aggressive types of tumors. In particular, knowledge of the specific genes and pathways driving tumor growth in these patients would allow for treatment with therapeutics directed against these molecular targets. To this end, we reasoned that through the integrated analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and gene expression profiling we could understand the molecular mechanisms associated with an aggressive imaging phenotype and thus gain insight into potential therapeutic targets for these patients. Materials and Methods: We studied 61 patients with locally advanced breast cancer, for whom DCE-MRI scans and core biopsies were available prior to the start of neoadjuvant chemotherapy. To analyse the DCE-MRI data, we used Tofts' pharmacokinetic (PK) model to quantify the rate constant kep that governs the washout of contrast agent from the tumor extravascular extracellular space. We chose to focus on the PK parameter kep since our analysis showed that it can be estimated reliably from the low temporal resolution diagnostic DCE-MRI scans that are routinely performed in the clinic. We extracted mRNA from formalin fixed paraffin embedded core biopsy samples and measured gene expression using Affymetrix U133 whole genome arrays. Following normalization and pre-processing, we used significance analysis of microarrays (SAM) to determine which genes were statistically significantly correlated with median kep. Results: Using a local false discovery rate of 5% resulted in a total of 328 genes that were significantly positively correlated with median kep. These included copper transporter like solute carrier family31member2 (SLC31A2), cancer stem cell (CSC) related genes such as CD44, aldehyde dehydrogenase family 1 member A3 (ALDH1A3), and integrin alpha-6 (ITGA6), hypoxia regulated genes such as hypoxia inducible factor 1a (HIF1a), kinases such as eukaryotic translation initiation factor2-alpha kinases (EIF2AK2, EIF2AK1), and pyruvate dehydrogenase kinases (PDK1, PDK3). Discussion: Our results illustrate how functional imaging modalities such as DCE-MRI can be combined with gene expression profiling to provide insight into molecular targets that may have important therapeutic implications in breast cancer. We found that locally advanced breast cancers with high vascular permeability and/or blood flow, as quantified by the washout parameter median kep, were associated with an up-regulation of genes related to CSCs and copper metabolism, the latter of which is known to play a role in angiogenesis. In addition, up-regulation of hypoxia related genes such as HIF1a, EIF2AK1&2 and PDK1&3 may promote tumor survival and spread under stress. Our results suggest that locally advanced breast cancers with high vascular permeability and/or blood flow may benefit from therapies directed at one or more of these molecular targets. Furthermore, functional imaging with DCE-MRI may be helpful as a noninvasive means of selecting and monitoring therapy against these targets. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-01-01.