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1.
Am J Transplant ; 19(1): 98-109, 2019 01.
Article in English | MEDLINE | ID: mdl-29985559

ABSTRACT

Noninvasive biomarkers are needed to monitor stable patients after kidney transplant (KT), because subclinical acute rejection (subAR), currently detectable only with surveillance biopsies, can lead to chronic rejection and graft loss. We conducted a multicenter study to develop a blood-based molecular biomarker for subAR using peripheral blood paired with surveillance biopsies and strict clinical phenotyping algorithms for discovery and validation. At a predefined threshold, 72% to 75% of KT recipients achieved a negative biomarker test correlating with the absence of subAR (negative predictive value: 78%-88%), while a positive test was obtained in 25% to 28% correlating with the presence of subAR (positive predictive value: 47%-61%). The clinical phenotype and biomarker independently and statistically correlated with a composite clinical endpoint (renal function, biopsy-proved acute rejection, ≥grade 2 interstitial fibrosis, and tubular atrophy), as well as with de novo donor-specific antibodies. We also found that <50% showed histologic improvement of subAR on follow-up biopsies despite treatment and that the biomarker could predict this outcome. Our data suggest that a blood-based biomarker that reduces the need for the indiscriminate use of invasive surveillance biopsies and that correlates with transplant outcomes could be used to monitor KT recipients with stable renal function, including after treatment for subAR, potentially improving KT outcomes.


Subject(s)
Biomarkers/blood , Graft Rejection/diagnosis , Kidney Transplantation , Adult , Aged , Algorithms , Biopsy , Female , Fibrosis/diagnosis , Glomerular Filtration Rate , Graft Rejection/blood , Graft Survival , Humans , Male , Middle Aged , Phenotype , Predictive Value of Tests , Treatment Outcome , Young Adult
2.
Cancer Epidemiol Biomarkers Prev ; 16(8): 1655-61, 2007 Aug.
Article in English | MEDLINE | ID: mdl-17684142

ABSTRACT

Despite the potential importance of the cell cycle and apoptosis pathways in brain tumor etiology, little has been published regarding brain tumor risk associated with common gene variants in these pathways. Using data from a hospital-based case-control study conducted by the National Cancer Institute between 1994 and 1998, we evaluated risk of glioma (n = 388), meningioma (n = 162), and acoustic neuroma (n = 73) with respect to 12 single nucleotide polymorphisms from 10 genes involved in apoptosis and cell cycle control: CASP8, CCND1, CCNH, CDKN1A, CDKN2A, CHEK1, CHEK2, MDM2, PTEN, and TP53. We observed significantly decreased risk of meningioma with the CASP8 Ex14-271A>T variant [odds ratio (OR)(AT), 0.8; 95% confidence interval (95% CI), 0.5-1.2; OR(AA), 0.5; 95% CI, 0.3-0.9; P(trend) = 0.03] and increased risk of meningioma with the CASP8 Ex13+51G>C variant (OR(GC), 1.4; 95% CI, 0.9-2.1; OR(CC), 3.6; 95% CI, 1.0-13.1; P(trend) = 0.04). The CT haplotype of the two CASP8 polymorphisms was associated with significantly increased risk of meningioma (OR, 1.7; 95% CI, 1.1-2.6), but was not associated with risk of glioma or acoustic neuroma. The CCND1 Ex4-1G>A variant was associated with increased risk for glioma, and the Ex8+49T>C variant of CCNH was associated with increased risk of glioma and acoustic neuroma. The MDM2 Ex12+162A>G variant was associated with significantly reduced risk of glioma. Our results suggest that common variants in the CASP8, CCND1, CCNH, and MDM2 genes may influence brain tumor risk. Future research in this area should include more detailed coverage of genes in the apoptosis/cell cycle control pathways.


Subject(s)
Apoptosis/genetics , Brain Neoplasms/genetics , Genes, cdc , Polymorphism, Single Nucleotide/genetics , Adolescent , Adult , Aged , Aged, 80 and over , Case-Control Studies , Caspase 8/genetics , Checkpoint Kinase 1 , Checkpoint Kinase 2 , Cyclin D , Cyclin H , Cyclin-Dependent Kinase Inhibitor p21/genetics , Cyclins/genetics , Exons/genetics , Female , Genes, Tumor Suppressor , Genes, p16 , Genes, p53/genetics , Genetic Variation/genetics , Glioma/genetics , Haplotypes , Humans , Male , Meningioma/genetics , Middle Aged , Neuroma, Acoustic/genetics , PTEN Phosphohydrolase/genetics , Protein Kinases/genetics , Protein Serine-Threonine Kinases/genetics , Proto-Oncogene Proteins c-mdm2/genetics , Risk Factors
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