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Query: UNIPROT:P01034 (cystatin C)
 3,397 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Based on the incidence survey of leukemia and aplastic anemia (AA) from 1986 to 1988, Case control studies (1257 new leukemia cases and 339 new AA cases) were carried out according to the type of leukemia and AA in order to better understand the epidemiologic characteristics of the diseases. Controls were matched randomly (age, sex and ethnic group) from the same population. The data were analyzed with the conditional Logistic multi-regression model and calculated on an IBM-PC/XT. The risk factors of M2a were found to be X-rays, antipyretics, benzene, pesticides and bimolane; that of M3 was chloramphenicol; that of M5 was X-rays; and that of other ANLLs was phenylbutazone. The risk factors of ALL were chloramphenicol, phenylbutazone and family members with cancer; those of CML were X-rays and hepatitis; those of CLL were chloramphenicol and benzene; those of AAA were antipyretics and hepatitis; and that of CAA ws X-rays.
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PMID:[Risk factors analysis of leukemia and aplastic anemia in China. Chinese Epidemiologic Study Group of Leukemia and Aplastic Anemia]. 139 36

Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring. This work proposes a mixture of feature relevance experts as a method for identifying marker genes and illustrates the idea using published data from samples labeled as acute lymphoblastic and myeloid leukemia (ALL, AML). A feature relevance expert implements an algorithm that calculates how well a gene distinguishes samples, reorders genes according to this relevance measure, and uses a supervised learning method [here, support vector machines (SVMs)] to determine the generalization performances of different nested gene subsets. The mixture of three feature relevance experts examined implement two existing and one novel feature relevance measures. For each expert, a gene subset consisting of the top 50 genes distinguished ALL from AML samples as completely as all 7,070 genes. The 125 genes at the union of the top 50s are plausible markers for a prototype decision support system. Chromosomal aberration and other data support the prediction that the three genes at the intersection of the top 50s, cystatin C, azurocidin, and adipsin, are good targets for investigating the basic biology of ALL/AML. The same data were employed to identify markers that distinguish samples based on their labels of T cell/B cell, peripheral blood/bone marrow, and male/female. Selenoprotein W may discriminate T cells from B cells. Results from analysis of transcription profiling data from tumor/nontumor colon adenocarcinoma samples support the general utility of the aforementioned approach. Theoretical issues such as choosing SVM kernels and their parameters, training and evaluating feature relevance experts, and the impact of potentially mislabeled samples on marker identification (feature selection) are discussed.
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PMID:Identifying marker genes in transcription profiling data using a mixture of feature relevance experts. 1124 94

Chromosome bands 1p36 and 3p21 are known to be recurring breakpoints in therapy-related (t-) leukemia. We identified a recurring translocation, t(1;3)(p36;p21), in eight patients with various hematologic malignancies: three patients with ALL, one with chronic myelogenous leukemia (CML) in accelerated phase (AP), two with MDS, and two with AML(M3). Five of the eight patients had a history of chemotherapy, including alkylating agents in three, before the translocation was detected. In two of these five patients, the t(1;3)(p36;p21) emerged only at relapse or in the accelerated phase of CML. The karyotypes of the patients were complex, including -7 and structural abnormalities of 5q, 6q, 7q, 9p, and 11q23. Survival time varied among patients (25 days to more than 16 years). Using FISH with 13 1p35-36 cosmid probes (tel-FB12-CA5-G7-FD2-CB1-ED8-FD9-G32-AE3-G50-AD8-GG4-G43-cen), we delineated the 1p36 breakpoint in two patients with MDS and ALL as lying between FB12 and FD2 (between BAC47P3 and PAC963K15), with a small deletion near the breakpoint in both cases. In the patient with MDS, there was also a deletion at 3p21.3, as detected with the cosmid probe cosNRL9. The results of the present study suggest that t(1;3)(p36;p21) in hematologic diseases is associated with prior exposure to mutagens, including alkylating agents.
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PMID:t(1;3)(p36;p21) is a recurring therapy-related translocation. 1197 52