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(12) United States Patent (10) Patent No.: US 7.655,397 B2 Khan Et Al

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(12) United States Patent (10) Patent No.: US 7.655,397 B2 Khan Et Al USOO7655397B2 (12) United States Patent (10) Patent No.: US 7.655,397 B2 Khan et al. (45) Date of Patent: Feb. 2, 2010 (54) SELECTIONS OF GENES AND METHODS OF Li et al. Human Pathology. 2008. 39: 1792-1801.* USING THE SAME FOR DAGNOSIS AND Khan, J. et al. “Classification and diagnostic prediction of cancers FORTARGETING THE THERAPY OF using gene expression profiling and artificial neural networks'. SELECT CANCERS Nature Medicine, vol. 7, No. 6., pp. 673-679 (Jun. 2001). Peterson, C. et al., “JETNET 3.0—A versatile artificial neural net work package'. Computer Physics Communications, vol. 81, pp. (75) Inventors: Javed Khan, Derwood, MD (US); 185-220 (1994). Markus Ringnér, Lund (SE); Carsten Tusher, V. et al., “Significance analysis of microarrays applied to the Peterson, Lund (SE); Paul Meltzer, ionizing radiation response”., PNAS, vol. 98, No. 9, pp. 5116-5121 Rockville, MD (US) (Apr. 24, 2001). Van Gelder, R. et al., “Amplified RNA synthesized from limited (73) Assignee: The United States of America as quantities of heterogeneous cDNA'. Proc. Natl. Acad. Sci. USA, vol. represented by the Department of 87, No. 5, pp. 1663-1667 (Mar. 1990). Health and Human Services, Golub, T. etal. “Molecular Classification of Cancer, Class Discovery Washington, DC (US) and Class Prediction by Gene Expression Monitoring”, Science, 286:531-537 (1999). Gruvberger, S. et al., “Estrogen Receptor Status in Breast Cancer is (*) Notice: Subject to any disclaimer, the term of this Associated with Remarkably Distinct Gene Expression Patterns'. patent is extended or adjusted under 35 Cancer Research, 61:5979-5984 (2001). U.S.C. 154(b) by 0 days. Kwon, S. et al., “DNA Microarray Data Analysis for Cancer Classi fication Based on Stepwise Discriminant Analysis and Boyesian (21) Appl. No.: 10/159.563 Decision Theory”. Genome Informatics, 12:252-254 (2001). Cover page of Nature Medicine, vol. 7, No. 6, Jun. 2001 (received (22) Filed: May 31, 2002 Jun. 15, 2001). NHGRI Protocol, http://www.nhgrihih.gov/DIR/LGG/SK/HTML/ (65) Prior Publication Data protocol.html, 27 pages (Apr. 25, 2002). Furey et al., Bioinformatics, 16(10):906-914 (2000). US 2004/OOO9154A1 Jan. 15, 2004 Herrero et al., Bioinformatics, 17(2): 126-136 (2001). Muller et al., IEEE Transactions on Neural Networks, 12(2): 181-201 Related U.S. Application Data (2001). (63) Continuation-in-part of application No. 10/133,937, Raychaudhuri et al., Trends in Biotechnology, 19(5):189-193 (2001). GenBank Accession No. NM 000612, dated Oct. 31, 2000. filed on Apr. 25, 2002. Blast Alignment between GenBank Accession No. NM 000612 and SEQ ID No. 72, dated Aug. 16, 2007. (51) Int. Cl. Agilent Technology Webpage, dated Aug. 16, 2007. CI2O I/68 (2006.01) Image Consortium Record printed Aug. 15, 2007. CI2P 19/34 (2006.01) GenBank Accession No. N54901, dated Jan. 28, 1997. C7H 2L/02 (2006.01) GenBank Sequence Revision History page printed Aug. 15, 2007. GenCard Database Record IGF2 printed Aug. 15, 2007. C7H 2L/04 (2006.01) Sperduti et al., IEEE Transactions on Neural Networks, 8:714-735 (52) U.S. Cl. ......................... 435/6: 435/91.1435/91.2: (1997). 435/91.21: 435/91.5; 435/91.51; 536/23.5 Ancoca et al., “On the statistical assessment of classifiers using DNA microarray data'. BMC Bioinformatics, 7:387 (2006). (58) Field of Classification Search ..................... 435/6, Chen et al., “Diagnosis of the Small Round Blue Cell Tumors. Using 435/287.2, 283: 536/23.1, 24.3 Multiplex Polymerase Chain Reaction”, Journal of Molecular Diag See application file for complete search history. nostics, 9(1):80-88 (2007). Kim et al., “ECgene: genome annotation for alternative splicing'. (56) References Cited Nucleic Acids Research, 33: D75-D79 (2005). Mateos et al., “Supervised Neural Networks for Clustering Condi U.S. PATENT DOCUMENTS tions in DNA Array Data after Reducing Noise by Clustering Gene 6,794,137 B2 9/2004 Blumenberg Expression Profiles'. Microarray data analysis II, Kluwer Academic 7,062.384 B2 6, 2006 Rocke et al. Publ., pp. 91-103 (2002). 7,229,774 B2 6/2007 Chinnaiyan et al. U.S. Appl. No. 10/133,937 Office Action dated Jun. 10, 2008. 7,341,552 B2 3/2008 Zhang et al. * cited by examiner 7,370,021 B2 5, 2008 Reeve et al. 7,384,736 B2 6/2008 Hakonarson Primary Examiner Carla Myers 7,402.388 B2 7/2008 Gillis et al. (74) Attorney, Agent, or Firm Merchant & Gould P.C. 7,402,399 B2 7/2008 Mukherjeeietal. 2003/02O7278 A1 11, 2003 Khan et al. (57) ABSTRACT A method of diagnosing a disease that includes obtaining OTHER PUBLICATIONS experimental data on gene selections. The gene selection GeneCard for IGF2 via URL: <genecards.org/cgi-bin/carddisp. functions to characterize a cancer when the expression of that pl?gene=IGF2&snp=93 isnp>.* gene selection is compared to the identical selection from a GeneCard for CCND1 available via URL: <genecards.org/cgi-bin/ noncancerous cell or a different type of cancer cell. The carddisp.pl?gene–Cendl&snp=97isnp>.* invention also includes a method of targeting at least one ECgene Summary for CCND1 available via URL: <genome.ewha. product of agene that includes administration ofatherapeutic ac.kr/cgi-bin/ECquery.cgi?organism-human&query=CCND1>.* agent. The invention also includes the use of a gene selection ECgene Summary for IGF2 available via URL: <genome.ewha.ac. for diagnosing a cancer. kr/cgi-bin/ECquery.cgi?organism-human&query=IGF2).* Wang et al. Human Genetics. 2006. 120: 297-300.* 10 Claims, 9 Drawing Sheets U.S. Patent Feb. 2, 2010 Sheet 1 of 9 US 7.655,397 B2 FIG. 1 iter Genes O2 3 RedLice Dimensionality PSA 2F3 f3 110 rairing Waiator - - - - - - --- 11 Supervised Patieff Recognition viethod waiidating rairing Rank ata 3 n s ?ize Arofit of 33 U.S. Patent Feb. 2, 2010 Sheet 2 of 9 US 7.655,397 B2 26 22 1 Cci-roni . 21 operating wd-for system five fetwork 'cessor 230 interface WQcie input/output it 234 interface a 3. agglication ari i sk 38 five 2. U.S. Patent Feb. 2, 2010 Sheet 3 of 9 US 7.655,397 B2 Fig. 3 Experimenia Data Experimental Data / 35 Experimentai Resuits 325 316 Data input viodule ANN raining ANN regic wide vidue ANN Cefficient ANN Clive Siope Storage vicdaie iwise ANN Coefficief atabase Cutput Cata U.S. Patent Feb. 2, 2010 Sheet 4 of 9 US 7.655,397 B2 JOJue eluenbSpeuunS U.S. Patent Feb. 2, 2010 Sheet 5 Of 9 US 7.655,397 B2 3 9 st CN O CO CO w CN O SedueSpey SSeo-Su JOJedunN : U.S. Patent Feb. 2, 2010 Sheet 7 Of 9 US 7.655,397 B2 s U.S. Patent Feb. 2, 2010 Sheet 8 of 9 US 7.655,397 B2 x i. US 7,655,397 B2 1. 2 SELECTIONS OF GENES AND METHODS OF increasingly for diagnostic confirmation following the dis USING THE SAME FOR DIAGNOSIS AND covery of tumor-specific translocations such as EWS-FLI1; FORTARGETING THE THERAPY OF t(11:22)(q24:q12) in EWS, and the PAX3-FKHR; t(2:13) SELECT CANCERS (q35;q14) in alveolarrhabdomyosarcoma (ARMS). However, molecular markers do not always provide a definitive diag This application is a continuation in part of a U.S. patent nosis, as on occasion there is failure to detect the classical application Ser. No. 10/133,937 entitled “METHODS FOR translocations, due to either technical difficulties or the pres ANALYZING HIGH DIMENSIONAL DATA FOR CLAS ence of variant translocations. SIFYING, DIAGNOSING, PROGNOSTICATING, AND/ An example of a diagnostic method replete with Such prob OR PREDICTING DISEASES AND OTHER BIOLOGI 10 lems is the diagnostic method for Ewing sarcoma. Ewing CAL STATES, filed on Apr. 25, 2002. sarcoma is diagnosed by immunohistochemical evidence of MIC2 expression and lack of expression of the leukocyte FIELD OF THE INVENTION common antigen CD45 (excluding lymphoma), muscle-spe cific actin or myogenin (excluding RMS). However, reliance The invention relates generally to selections of genes 15 on detection of MIC2 alone can lead to incorrect diagnosis as expressed in a cancer cell that function to characterize a MIC2 expression occurs occasionally in other tumor types cancer, and methods of using the same for diagnosis and for including RMS and BL. targeting the therapy of select cancers. The invention also One objective factor that can, in certain circumstances, be relates generally to the use of Supervised pattern recognition entirely predictive of a diseased state is the genetic makeup of methods to classify and diagnose disease. More specifically, the individual. Genetic makeup of an individual cell can also the invention relates to the use of Supervised pattern recogni be considered in terms of the level of expression of the genes tion methods, such as artificial neural networks for the clas of that individual cell through gene expression data. sification, diagnosis, prognosis and prediction of disease DNA microarray technology is a recently developed high using high dimensional data, Such as gene expression profil throughput technology for monitoring gene expression at the ing data. 25 transcription level. Its use is akin to performing tens of thou sands of northern blots simultaneously, and has the potential BACKGROUND OF THE INVENTION for parallel integration of the expression levels of an entire genome. A DNA microarray consists of DNA probes immo Disease is generally diagnosed based on a myriad of fac bilized on a Solid Support Such as a glass microscope slide. tors, both objective and subjective, including but not limited 30 The DNA probes can be double stranded cDNA or short to symptoms, laboratory test values, demographic factors and (25mers) or long (50-70mers) oligonucleotides of known environmental factors.
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