Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. However the difficulty in evaluating whether these candidate genes drive tumour progression remains a major challenge. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved invasion suppressors. This includes constituents of the cohesin complex, which can either promote individual or collective invasion, depending on the severity of effect on cohesin function.
A Genetic Analysis of Tumor Progression in Drosophila Identifies the Cohesin Complex as a Suppressor of Individual and Collective Cell Invasion.
Cell line
View SamplesThe Mre11 complex (Mre11, Rad50, and Nbs1) and Chk2 have been implicated in the DNA damage response, an inducible process required for the suppression of malignancy. The Mre11 complex is predominantly required for repair and checkpoint activation in S phase, while Chk2 governs apoptosis. We examined the relationship between the Mre11 complex and Chk2 in the DNA damage response via the establishment of Nbs1B/B Chk2-/- and Mre11ATLD1/ATLD1 Chk2-/- mice. Chk2 deficiency did not modify the checkpoint defects or chromosomal instability of Mre11 complex mutants; however, the double mutant mice exhibited synergistic defects in DNA damage-induced p53 regulation and apoptosis. Nbs1B/B Chk2-/- and Mre11ATLD1/ATLD1 Chk2-/- mice were also predisposed to tumors. In contrast, DNA-PKcs deficient mice, in which G1-specific chromosome breaks are present, did not exhibit synergy with Chk2-/- mutants. These data suggest that Chk2 suppresses the oncogenic potential of DNA damage arising during S and G2 phases of the cell cycle.
Chk2 suppresses the oncogenic potential of DNA replication-associated DNA damage.
No sample metadata fields
View SamplesIn the clinical setting, mutations in the CFTR gene enhance the inflammatory response to P. aeruginosa (PA01) infection, but measurements of the inflammatory response to pathogen stimulation by isolated airway epithelia can yield variable results. In this series, we exposed CFBE41o- cells over-expressing F508/F508 CFTR and CFBE41o- cells rescued with wt-CFTR to P. aeruginosa biofilms. P. aeruginosa elicited a more robust increase in cytokine and chemokine expression (e.g., IL-8, CXCL2, CXCL3, CXCR4 and TNF-) in CFBE-wt-CFTR cells compared to CFBE-F508-CFTR cells. These results demonstrate that CFBE41o- cells complemented with wt-CFTR mount a more robust inflammatory response to P. aeruginosa than CFBE41o- F508/F508-CFTR cells.
Does the F508-CFTR mutation induce a proinflammatory response in human airway epithelial cells?
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
PIK3CA(H1047R) induces multipotency and multi-lineage mammary tumours.
Specimen part, Treatment
View SamplesThis study examined the effect of early pregnancy on the gene expression profiles of stromal and various epithelial mammary cell subpopulations in mice.
PIK3CA(H1047R) induces multipotency and multi-lineage mammary tumours.
Specimen part
View SamplesThis study examined the gene expression profile of mammary tumors derived from Lgr5- and K8-positive cell-of-origins
PIK3CA(H1047R) induces multipotency and multi-lineage mammary tumours.
Specimen part
View SamplesThis study examined the effect of mutant PIK3CAH1047R expression in mammary subsets of preneoplastic mammary glands from Lgr5-creERT2/PIK3CA H1047R mice
PIK3CA(H1047R) induces multipotency and multi-lineage mammary tumours.
Specimen part, Treatment
View SamplesThis study examined the effect of mutant PIK3CAH1047R expression in mammary subsets of preneoplastic mammary glands from K8-creERT2/PIK3CA H1047R mice
PIK3CA(H1047R) induces multipotency and multi-lineage mammary tumours.
Treatment, Time
View SamplesWhile the hypothalamo-pituitary-adrenal axis (HPA) activates a general stress response by increasing glucocorticoid (Gc) synthesis, biological stress resulting from infections triggers the inflammatory response through production of cytokines. The pituitary gland integrates some of these signals by responding to the pro-inflammatory cytokines IL6 and LIF and to a negative Gc feedback loop. The present work used whole-genome approaches to define the LIF/STAT3 regulatory network and to delineate cross-talk between this pathway and Gc action. Genome-wide ChIP-chip identified 3 449 STAT3 binding sites, whereas 2 396 genes regulated by LIF and/or Gc were found by expression profiling. Surprisingly, LIF on its own changed expression of only 85 genes but the joint action of LIF and Gc potentiated the expression of more than a thousand genes. Accordingly, activation of both LIF and Gc pathways also potentiated STAT3 and GR recruitment to many STAT3 targets. Our analyses revealed an unexpected gene cluster that requires both stimuli for delayed activation: 83% of the genes in this cluster are involved in different cell defense mechanisms. Thus, stressors that trigger both general stress and inflammatory responses lead to activation of a stereotypic innate cellular defense response.
Regulatory network analyses reveal genome-wide potentiation of LIF signaling by glucocorticoids and define an innate cell defense response.
Specimen part, Time
View SamplesBackground: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Methods: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set). Results: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. Conclusion: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion.
Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples.
Time
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