Gene sets for glioma classification

Details Gene sets for glioma classification Gene sets for glioma classification

2008-03-11

2008-03-11

Schultz, J. Douglas (Department: 1639)

Combinatorial chemistry technology: method, library, apparatus

Method of screening a library

C435S006120

Reexamination Certificate

active

10390343

ABSTRACT:
The present invention provides a number of gene markers whose expression is altered in various gliomas. In particular, by examining the expression these markers, one can accurately classify a glioma as glioblastoma multiforme (GM), anaplastic astrocytoma (AA), anaplastic oligodendroglioma (AO) or oligodendroglioma (OL). The diagnosis may be performed on nucleic acids, for example, using a DNA microarray, or on protein, for example, using immunologic means. Also disclosed are methods of therapy.

REFERENCES:
patent: 5635351 (1997-06-01), Feuerstein et al.
patent: 5994529 (1999-11-01), Feuerstein et al.
patent: 6268147 (2001-07-01), Beattie et al.
patent: 6492118 (2002-12-01), Abrams et al.
Fuller et al., Cancer Research 59:4228-4232 (1999).
Rhee et al., Oncology Reports 6:393-401 (1999).
Walker et al., Cancer Research 55(1): 20-23 (1999).
Moch et al., Adv. Anat. Pathol. 8(1): 14-20 (2001).
Sallinen et al., Cancer Research 60:6617-6622 (2000).
Rickman et al., Cancer Research 61:6885-6891 (2001).
Alizadeh et al., “Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling,”Nature403 (6769), 503-511, 2000.
Ben-Dor et al., “Tissue classification with gene expression profiles”J. Comput. Biol. 7(3-4): 559-583, 2000.
Bittner et al., “Molecular classification of cutaneous malignant melanoma by gene expression profiling,”Nature406 (6795), 536-40, 2000.
Borg and Groenen,In: Modern multidimensional scaling: Theory and applications. Springer, New York. 1997.
Daumas-Duport et al., “Grading of astrocytomas: a simple and reproducible methods,”Cancer62, 2152-2165, 1988.
Devroye et al.,A Probablistic Theory of Pattern Recognition, NY, Springer (Ed.), 1996.
Dougherty, “Small sample issues for microarray-based classification,”Comparative and Functional Genomics2:28-34, 2001.
Fuller et al., “Molecular classification of human diffuse gliomas by multidimensional scaling analysis of gene expression profiles parallels morphology-based classification, correlates with survival, and reveals clinically-relevant novel glioma subsets,”Brain Pathol., 12:108-116, 2002.
Fuller et al., “Reactivation of insulin-like growth factor binding protein 2 expression in glioblastoma multiforme: a revelation by parallel gene expression profiling,”Cancer Res. 59:4228-4232, 1999.
Golub et al., “Molecular classification of cancer: class discovery and class prediction by gene expression monitoring,”Science286:531-537, 1999.
Hedenfalk et al., “Gene-expression profiles in hereditary breast cancer,”N. Engl. J. Med., 244: 539-548, 2001.
Kendall and Gibbons,Rank Correlation Methods, Fifth Edition. Oxford University Press, New York. 1990.
Khan et al., “Classification and diagnosis prediction of cancers using gene expression profiling and artificial neural networks,”Nature Medicine7(6):673-679, 2001.
Kim et al., “Identification of combination gene sets for glioma classification,”Mol. Cancer Therapeutics, 1:1229-1236, 2002.
Kim et al., “Strong feature sets from small samples,”J. Comput. Biol. 9(1):129-148, 2002.
Kleihues and Cavenee,World Health Organization of Tumours of the Nervous System: Pathology and Genetics: Tumours of the nervous system,. New York: Oxford University Press, 2000.
Perou et al., “Molecular portraits of human breast tumours,”Nature406 (6797), 747-752, 2000.
Sterling et al.,How to Build a Beowulf: A Guide to Implementation and Application of PC Clusters, The MIT Press, Cambridge, Massachusetts. 1999.
Wang et al., “Tissue microarrays: applications in neuropathology research, diagnosis, and education,”Brain Pathol., 12:95-107, 2002.
Saxena et al., “Comparative molecular genetic profiles of anaplastic astrocytomas/glioblastomas multiforme and their subsequent recurrences,”Oncogene, 18:1385-1390, 1999.

Affiliated with

Also associated with

Rating

Gene sets for glioma classification does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Gene sets for glioma classification, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Gene sets for glioma classification will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3958925