Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0023473 (chronic myeloid leukemia)
 18,916 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Despite the common use of immunohistochemistry in autopsy tissues, the stability of most proteins over extended time periods is unknown. The robustness of signal for 16 proteins (MMP1, MMP2, MMP3, MMP9, TIMP1, TIMP2, TIMP3, AGER, MSR, SCARB1, OLR1, CD36, LTF, LGALS3, LYZ, and DDOST) and two measures of advanced glycation end products (AGE, CML) was evaluated. Two formalin-fixed, paraffin-embedded human tissue arrays containing 16 tissues each were created to evaluate 48 hr of autolysis in a warm or cold environment. For these classes of proteins, matrix metalloproteinases and their inhibitors, scavenger receptors, and advanced glycation end product receptors, we saw no systematic diminution of signal intensity during a period of 24 hr. Analysis was performed by two independent observers and confirmed for a subset of proteins by digital analysis and Western blotting. We conclude that these classes of proteins degrade slowly and faithfully maintain their immunohistochemistry characteristics over at least a 24-hr time interval in devitalized tissues. This study supports the use of autopsy tissues with short postmortem intervals for immunohistochemical studies for diseases such as diabetic vascular disease, cancer, Alzheimer's disease, atherosclerosis, and other pathological states. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.
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PMID:Robust immunohistochemical staining of several classes of proteins in tissues subjected to autolysis. 1731 10

Currently, limited molecular markers exist that can determine where in the spectrum of chronic myeloid leukemia (CML) progression an individual patient falls at diagnosis. Gene expression profiles can predict disease and prognosis, but most widely used microarray analytical methods yield lengthy gene candidate lists that are difficult to apply clinically. Consequently, we applied a probabilistic method called Bayesian model averaging (BMA) to a large CML microarray dataset. BMA, a supervised method, considers multiple genes simultaneously and identifies small gene sets. BMA identified 6 genes (NOB1, DDX47, IGSF2, LTB4R, SCARB1, and SLC25A3) that discriminated chronic phase (CP) from blast crisis (BC) CML. In CML, phase labels divide disease progression into discrete states. BMA, however, produces posterior probabilities between 0 and 1 and predicts patients in "intermediate" stages. In validation studies of 88 patients, the 6-gene signature discriminated early CP from late CP, accelerated phase, and BC. This distinction between early and late CP is not possible with current classifications, which are based on known duration of disease. BMA is a powerful tool for developing diagnostic tests from microarray data. Because therapeutic outcomes are so closely tied to disease phase, these probabilities can be used to determine a risk-based treatment strategy at diagnosis.
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PMID:The derivation of diagnostic markers of chronic myeloid leukemia progression from microarray data. 1965 5