News Releases
2008
Publications
related to DecisionDx-UM
Onken, et al. 2010.
An Accurate, Clinically Feasible Multi-Gene Expression Assay for Predicting Metastasis in Uveal Melanoma. Jrnl Mol Diagn, 12(4): 461-8.
Worley, et al. 2007.
Transcriptomic versus Chromosomal Prognostic Markers and Clinical Outcome in Uveal Melanoma Clin Cancer Res, 13(5): 1466-71.
Onken, et al. 2006.
Prognostic testing in uveal melanoma by transcriptomic profiling of fine needle biopsy specimens. Jrnl Mol Diagn; 8: 567-73.
Onken, et al. 2004.
Gene expression profiling in uveal melanoma reveals two molecular classes and predicts metastatic death. Cancer Res, 64: 7205-9.
AJCC Cancer Staging Manual, Version 7. 2010. Malignant Melanoma of the Uvea. 547-53.
Harbour. 2010. Molecular Prognostic Testing and Individualized Patient Care in Uveal Melanoma. Am J Ophthalmol, 148: 823–829.
Ainbinder, et al. 2009. The 7th edition AJCC staging system for eye cancer: an international language for ophthalmic oncology. Arch Pathol Lab Med, 133: 1197-8.
Harbour. 2011. Molecular research in uveal melanoma: ushering in a new standard of care. Retina Times, 29: 36-7.
Publications
related to DecisionDx-LGG
Noushmehr, et al. 2010. Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma. Cancer Cell, 17: 1–13.
Van den Bent. 2010. Interobserver variation of the histopathological diagnosis in clinical trials on glioma: a clinician's perspective. Acta Neuropathol, 120: 297–304.
Brat, et al. 2008. Diagnosis of Malignant Glioma: Role of Neuropathology. J Neurooncol, 89: 287-311.
Bruner, et al. 1997. Diagnostic Discrepancies and Their Clinical Impact in a Neuropathology Referral Practice. Cancer, 79(4): 796-803.
Coons, et al. 1997. Improving Diagnostic Accuracy and Interobserver Concordance in the Classification and Grading of Primary Gliomas. Cancer, 79(7): 1381-1393.
Aldape et al. 2000. Discrepancies in diagnoses of neuroepithelial neoplasms: the San Francisco Bay Area Adult Glioma Study. Cancer, 88: 2342–2349.
Publications
related to DecisionDx-GBM
Phillips, H, et al. 2006. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell, 9:157–173.
Van den Bent. 2010. Interobserver variation of the histopathological diagnosis in clinical trials on glioma: a clinician's perspective. Acta Neuropathol, 2010: 120:297–304.
Brat, et al. 2008. Diagnosis of Malignant Glioma: Role of Neuropathology. J Neuro Oncol, 89: 287-311.
Freije, W, et al. 2004. Gene expression profiling of gliomas strongly predicts survival. Cancer Res, 64: 6503–6510.
Nigro J, et al. 2005. Integrated array-comparative genomic hybridization and expression array profiles identify clinically relevant molecular subtypes of glioblastoma. Cancer Res, 65: 1678–1686.
Nutt, C, et al. 2003. Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res, 63: 1602–1607.
Sun, L, et al. 2006. Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain. Cancer Cell, 9: 287–300.
The Cancer Genome Atlas Research Network. 2008. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature, 455: 1061–1068.
Colman, et al. 2006. Meta-analysis of gene expression profiling data from glioblastoma tumor samples identifies a robust Multigene classifier predictive of survival. Proc Amer Assoc Cancer Res, Volume 47, Abstract # 5688.
Colman, et al. 2007. A robust Multigene classifier predictive of survival in patients with newly diagnosed glioblastoma. Proc Amer Assoc Cancer Res. Vol , Abstract #2700.
Aldape, et al. 2006. Meta-analysis of gene expression profiling data from glioblastoma tumor samples identifies a robust multigene classifier predictive of survival. Journal of the Society for Neuro-Oncology. Abstract GE-01.