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A variety of genetic alterations are considered hallmarks of cancer development and progression. The Ikaros gene family, encoding for key transcription factors in hematopoietic development, provides several examples as genetic defects in these genes are associated with the development of different types of leukemia. However, the complex patterns of expression of isoforms in Ikaros family genes has prevented their use as clinical markers. In this study, we propose the use of the expression profiles of the Ikaros isoforms to classify various hematological tumor diseases. We have standardized a quantitative PCR protocol to estimate the expression levels of the Ikaros gene exons. Our analysis reveals that these levels are associated with specific types of leukemia and we have found differences in the levels of expression relative to five interexonic Ikaros regions for all diseases studied. In conclusion, our method has allowed us to precisely discriminate between B-ALL, CLL and MM cases. Differences between the groups of lymphoid and myeloid pathologies were also identified in the same way. [ABSTRACT FROM AUTHOR]

There is considerable insight into pathways and genes associated with heat-stress conditions. Most genes involved in stress response have been identified using mutant screens or gene knockdowns. Yet, there is limited understanding of the temporal dynamics of global gene expression in stressful environments. Here, we studied global gene expression profiles during 12 hours of heat stress in the nematode C. elegans. Using a high-resolution time series of increasing stress exposures, we found a distinct shift in gene expression patterns between 3-4 hours into the stress response, separating an initially highly dynamic phase from a later relatively stagnant phase. This turning point in expression dynamics coincided with a phenotypic turning point, as shown by a strong decrease in movement, survival and, progeny count in the days following the stress. Both detectable at transcriptional and phenotypic level, this study pin-points a relatively small time frame during heat stress at which enough damage is accumulated, making it impossible to recover the next few days.

In high-throughput molecular profiling studies, genotype labels can be wrongly assigned at various experimental steps; the resulting mislabeled samples seriously reduce the power to detect the genetic basis of phenotypic variation. We have developed an approach to detect potential mislabeling, recover the "ideal" genotype and identify "best-matched" labels for mislabeled samples. On average, we identified 4% of samples as mislabeled in eight published datasets, highlighting the necessity of applying a "data cleaning" step before standard data analysis., Competing Interests: The authors have declared that no competing interests exist.