Comparison of univariate and multivariate gene set analysis in acute lymphoblastic leukemia

Effect of dietary polyunsaturated fatty acid and antioxidant supplementation on the transcriptional level of genes involved in lipid and energy metabolism in swine

Porcine fat traits depend mostly on the interaction between nutritional and genetic factors. However, the pathways and biological processes influenced by this interaction are still poorly known in pigs, although they can have a huge impact on meat quality traits. The present research provides new knowledge insight into the effect of four diets (D1 = standard diet; D2 = linseed supplementation; D3 = linseed, vitamin E and selenium supplementation; D4 = linseed and plant-derived polyphenols supplementation) on the expression of 24 candidate genes selected for their role in lipid and energy metabolism. The data indicated that 10 out of 24 genes were differentially expressed among diets, namely ACACA, ADIPOQ, ADIPOR1, CHREBP (MLXPL), ELOVL6, FASN, G6PD, PLIN2, RXRA and SCD. Results from the univariate analysis displayed an increased expression of ACACA, ADIPOQ, ADIPOR1, CHREBP, ELOVL6, FASN, PLIN2, RXRA and SCD in D4 compared to D2. Similarly, ACACA, ADIPOQ, ADIPOR1, ELOVL6 and SCD were highly expressed in D4 compared to D3, while no differences were observed in D2-D3 comparison. Moreover, an increased expression of G6PD and ELOVL6 genes in D4 compared to D1 was observed. Results from the multivariate analysis confirmed that D2 was not different from D3 and that ACACA, SCD and FASN expression made D4 different from D2 and D3. Comparing D4 and D1, the expression levels of ELOVL6 and ACACA were the most influenced. This research provides evidence that the addition of both n-3 PUFA and polyphenols, derived from linseed, grape-skin and oregano supplementation in the diets, stimulates the expression of genes involved in lipogenesis and in oxidative processes. Results evidenced a greater effect on gene expression of the diet added with both plant extracts and n-3 PUFA, resulting in an increased expression of genes coding for fatty acid synthesis, desaturation and elongation in pig Longissimus thoracis muscle.

Digital gene expression profiling analysis of childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most commonly diagnosed malignancy in children. It is a heterogeneous disease, and is determined by multiple gene alterations and chromosomal rearrangements. To improve current understanding of the underlying molecular mechanisms of ALL, the present study profiled genome‑wide digital gene expression (DGE) in a population of children with ALL in China. Using second‑generation sequencing technology, the profiling revealed that 2,825 genes were upregulated and 1,952 were downregulated in the ALL group. Based on the DGE profiling data, the present study further investigated seven genes (WT1, RPS26, MSX1, CD70, HOXC4, HOXA5 and HOXC6) using reverse transcription‑quantitative polymerase chain reaction analysis. Gene Ontology analysis suggested that the differentially expressed genes were predominantly involved in immune cell differentiation, metabolic processes and programmed cell death. The results of the present study provided novel insights into the gene expression patterns in children with ALL.

A null model for Pearson coexpression networks

Gene coexpression networks inferred by correlation from high-throughput profiling such as microarray data represent simple but effective structures for discovering and interpreting linear gene relationships. In recent years, several approaches have been proposed to tackle the problem of deciding when the resulting correlation values are statistically significant. This is most crucial when the number of samples is small, yielding a non-negligible chance that even high correlation values are due to random effects. Here we introduce a novel hard thresholding solution based on the assumption that a coexpression network inferred by randomly generated data is expected to be empty. The threshold is theoretically derived by means of an analytic approach and, as a deterministic independent null model, it depends only on the dimensions of the starting data matrix, with assumptions on the skewness of the data distribution compatible with the structure of gene expression levels data. We show, on synthetic and array datasets, that the proposed threshold is effective in eliminating all false positive links, with an offsetting cost in terms of false negative detected edges.

Allogeneic hemopietic stem cell transplants for the treatment of B cell acute lymphocytic leukemia

OBJECTIVE

Explore the feasibility of allo- hemopietic stem cell transplants in treating patients with B cell acute lymphocytic leukemia.

METHODS

Between september 2006 and February 2011, fifteen patients with B cell acute lymphocytic leukemia (ALL) were treated by allo-hemopietic stem cell transplants (HSCT). Stem cell sources were peripheral blood. Six patients were conditioned by busulfan (BU) and cyclophosphamide (CY) and nine patients were conditioned with TBI and cyclophosphamide (CY). Graft versus host disease (GVHD) prophylaxis regimen consisted of cyclosporine A (CSA), methotrex ate (MTX) and mycophenolatemofetil (MMF).

RESULTS

Patients received a median of 7.98×10⁸·kg⁻¹ (5.36-12.30×10⁸·kg⁻¹) mononuclear cells (MNC). The median time of ANC>0.5×10⁹/L was day 12 (10-15), and PLT>20.0×10⁹/L was day 13 (11-16). Extensive acute GVHD occurred in 6 (40.0%) patients, and extensive chronic GVHD was recorded in 6 (40.0%) patients. Nine patients were alive after 2.5-65 months follow-up.

CONCLUSION

Allogeneic stem cell transplant could be effective in treating patients with B cell acute lymphocytic leukemia.