Expression of kinase genes in primary hyperparathyroidism; Adenoma versus hyperplastic parathyroid tissue. Pinhas P. Schachter1 M.D., Suhail Ayesh2 PhD, Tamar Schneider2, Morris Laster M.D., Abraham Czerniak1 M.D. and Abraham Hochberg2. Background.
Pinhas P. Schachter1 M.D., Suhail Ayesh2 PhD, Tamar Schneider2,
Morris Laster M.D., Abraham Czerniak1 M.D. and Abraham Hochberg2
Differentiation between parathyroid hyperplasia and adenoma is difficult and based on the surgeon’s skill. Microarrays and other sophisticated research tools generate information about differential gene expression in various tissues.
Exploration of genes that express differentially in one tissue will enable identification and perhaps development of new methods of preoperative or intraoperative diagnosis.
The ratio values that are considered significant (<0.5 or >1.5) suggest that genes up-regulated in parathyroid adenoma are those responsible for angiogenesis and production of blood vessels. Genes down-regulated in parathyroid adenoma and expressed in hyperplasia are related to a decrease in apoptosis. Moreover, an interesting gene expressed only in the hyperplasia sample is increased in relation to in vivo proliferation activities
expression profile that distinguishes a
Scott A. Armstrong1–4, Jane E. Staunton5, Lewis B. Silverman1,3,4, Rob Pieters6, Monique L. den Boer6, Mark
D. Minden7, Stephen E. Sallan1,3,4, Eric S. Lander5, Todd R. Golub1,3,4,5* & Stanley J. Korsmeyer2,4,8*
*These authors contributed equally to this work.
Clustering algorithms reveal that lymphoblastic leukemias with MLL translocations can clearly be separated from conventional acute lymphoblastic and acute myelogenous leukemias.
We propose that they constitute a distinct disease, denoted here as MLL, and show that the differences in gene expression are robust enough to classify leukemias correctly as MLL, acute lymphoblastic leukemia or acute myelogenous leukemia.
Establishing that MLL is a unique entity is critical, as it mandates the examination of
selectively expressed genes for urgently needed molecular targets.
Classification of ALL, MLL and AML on the basis of their gene expression profile. The error rate in class prediction (y axis) is plotted against the number of genes used to build the model (x axis).