Networking of differentially expressed genes in human cancer cells resistant to methotrexate

BACKGROUND: The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). METHODS: Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. RESULTS: Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. CONCLUSIONS: Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX.

Cell fusion reprogramming leads to a specific hepatic expression pattern during mouse bone marrow derived hepatocyte formation In Vivo

The fusion of bone marrow (BM) hematopoietic cells with hepatocytes to generate BM derived hepatocytes (BMDH) is a natural process, which is enhanced in damaged tissues. However, the reprogramming needed to generate BMDH and the identity of the resultant cells is essentially unknown. In a mouse model of chronic liver damage, here we identify a modification in the chromatin structure of the hematopoietic nucleus during BMDH formation, accompanied by the loss of the key hematopoietic transcription factor PU.1/Sfpi1 (SFFV proviral integration 1) and gain of the key hepatic transcriptional regulator HNF-1A homeobox A (HNF-1A/Hnf1a). Through genome-wide expression analysis of laser captured BMDH, a differential gene expression pattern was detected and the chromatin changes observed were confirmed at the level of chromatin regulator genes. Similarly, Tranforming Growth Factor-β1 (TGF-β1) and neurotransmitter (e.g. Prostaglandin E Receptor 4 [Ptger4]) pathway genes were over-expressed. In summary, in vivo BMDH generation is a process in which the hematopoietic cell nucleus changes its identity and acquires hepatic features. These BMDHs have their own cell identity characterized by an expression pattern different from hematopoietic cells or hepatocytes. The role of these BMDHs in the liver requires further investigation.

Validation of an instrument to evaluate quality of life in the aging population: WHOQOL-AGE.

BACKGROUND: There is a need for short, specific instruments that assess quality of life (QOL) adequately in the older adult population. The aims of the present study were to obtain evidence on the validity of the inferences that could be drawn from an instrument to measure QOL in the aging population (people 50+ years old), and to test its psychometric properties. METHODS: The instrument, WHOQOL-AGE, comprised 13 positive items, assessed on a five-point rating scale, and was administered to nationally representative samples (n = 9987) from Finland, Poland, and Spain. Cronbach's alpha was employed to assess internal consistency reliability, whereas the validity of the questionnaire was assessed by means of factor analysis, graded response model, Pearson's correlation coefficient and unpaired t-test. Normative values were calculated across countries and for different age groups. RESULTS: The satisfactory goodness-of-fit indices confirmed that the factorial structure of WHOQOL-AGE comprises two first-order factors. Cronbach's alpha was 0.88 for factor 1, and 0.84 for factor 2. Evidence supporting a global score was found with a second-order factor model, according to the goodness-of-fit indices: CFI = 0.93, TLI = 0.91, RMSEA = 0.073. Convergent validity was estimated at r = 0.75 and adequate discriminant validity was also found. Significant differences were found between healthy individuals (74.19 ± 13.21) and individuals with at least one chronic condition (64.29 ± 16.29), supporting adequate known-groups validity. CONCLUSIONS: WHOQOL-AGE has shown good psychometric properties in Finland, Poland, and Spain. Therefore, considerable support is provided to using the WHOQOL-AGE to measure QOL in older adults in these countries, and to compare the QOL of older and younger adults.