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Cancer genome sequencing

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Shipitsin, M.; Willson, J. K. V.; Sukumar, S.; Polyak, K.; Park, B. H.; Pethiyagoda, C. L.; Pant, P. V. K.; Ballinger, D. G.; Sparks, A. B.; Hartigan, J.; Smith, D. R.; Suh, E.; Papadopoulos, N.; Buckhaults, P.; Markowitz, S. D.; Parmigiani, G.; Kinzler, K. W.; Velculescu, V. E.; Vogelstein, B. (2007). "The Genomic Landscapes of Human Breast and Colorectal Cancers".
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degradation technique. Following these landmark papers, over 20 years later ‘Second Generation’ high-throughput next generation sequencing (HT-NGS) was born followed by ‘Third Generation HT-NGS technology’ in 2010. The figures to the right illustrate the general biological pipeline and companies involved in second and third generation HT-NGS sequencing.
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shared mutations amongst tumors, cluster around known oncogenes, and are tend to be non-silent. Passenger mutations, which are not important in the progression of the disease, are randomly distributed throughout the genome. It has been estimated that the average tumor carries c.a. 80 somatic mutations, fewer than 15 of which are expected to be drivers.
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A personal-genomics analysis requires further functional characterization of the detected mutant genes, and the development of a basic model of the origin and progression of the tumor. This analysis can be used to make pharmacological treatment recommendations. As of February 2012, this has only been
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A major goal of cancer genome sequencing is to identify driver mutations: genetic changes which increase the mutation rate in the cell, leading to more rapid tumor evolution and metastasis. It is difficult to determine driver mutations from DNA sequence alone; but drivers tend to be the most commonly
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Since even non-cancerous cells accumulate somatic mutations, it is necessary to compare sequence of the tumor to a matched normal tissue in order to discover which mutations are unique to the cancer. In some cancers, such as leukemia, it is not practical to match the cancer sample to a normal tissue,
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The first report of cancer genome sequencing appeared in 2006. In this study 13,023 genes were sequenced in 11 breast and 11 colorectal tumors. A subsequent follow up was published in 2007 where the same group added just over 5,000 more genes and almost 8,000 transcript species to complete the exomes
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The TCGA is a multi-institutional effort to understand the molecular basis of cancer through genome analysis technologies, including large-scale genome sequencing techniques. Hundreds of samples are being collected, sequenced and analyzed. Currently the cancer tissue being collected include: central
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Cancer genome sequencing can be used to provide clinically relevant information in patients with rare or novel tumor types. Translating sequence information into a clinical treatment plan is highly complicated, requires experts of many different fields, and is not guaranteed to lead to an effective
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The Cancer Genome Anatomy Project (CGAP) was first funded in 1997 with the goal of documenting the sequences of RNA transcripts in tumor cells. As technology improved, the CGAP expanded its goals to include the determination of gene expression profiles of cancerous, precancerous and normal tissues.
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Sjoblom, T.; Jones, S.; Wood, L. D.; Parsons, D. W.; Lin, J.; Barber, T. D.; Mandelker, D.; Leary, R. J.; Ptak, J.; Silliman, N.; Szabo, S.; Buckhaults, P.; Farrell, C.; Meeh, P.; Markowitz, S. D.; Willis, J.; Dawson, D.; Willson, J. K. V.; Gazdar, A. F.; Hartigan, J.; Wu, L.; Liu, C.; Parmigiani,
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A large-scale screen for somatic mutations in breast and colorectal tumors showed that many low-frequency mutations each make small contribution to cell survival. If cell survival is determined by many mutations of small effect, it is unlikely that genome sequencing will uncover a single "Achilles
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It has been estimated that discovery of all somatic mutations in a tumor would require 30-fold sequencing coverage of the tumor genome and a matched normal tissue. By comparison, the original draft of the human genome had approximately 65-fold coverage. To facilitate further improvement in somatic
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Wood, L. D.; Parsons, D. W.; Jones, S.; Lin, J.; Sjoblom, T.; Leary, R. J.; Shen, D.; Boca, S. M.; Barber, T.; Ptak, J.; Silliman, N.; Szabo, S.; Dezso, Z.; Ustyanksky, V.; Nikolskaya, T.; Nikolsky, Y.; Karchin, R.; Wilson, P. A.; Kaminker, J. S.; Zhang, Z.; Croshaw, R.; Willis, J.; Dawson, D.;
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Cancer genome sequencing utilizes the same technology involved in whole genome sequencing. The history of sequencing has come a long way, originating in 1977 by two independent groups - Fredrick Sanger’s enzymatic didoxy DNA sequencing technique and the Allen Maxam and Walter Gilbert chemical
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The Cancer Genome Projects goal is to identify sequence variants and mutations critical in the development of human cancers. The project involves the systematic screening of coding genes and flanking splice junctions of all genes in the human genome for acquired mutations in human cancers. To
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The power of cancer genome sequencing lies in the heterogeneity of cancers and patients. Most cancers have a variety of subtypes and combined with these ‘cancer variants’ are the differences between a cancer subtype in one individual and in another individual. Cancer genome sequencing allows
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The components of the TCGA research network include: Biospecimen Core Resources, Genome Characterization Centers, Genome Sequencing Centers, Proteome Characterization Centers, a Data Coordinating Center, and Genome Data Analysis Centers. Each cancer type will undergo comprehensive genomic
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Clinically significant properties of tumors, including drug resistance, are sometimes caused by large-scale rearrangements of the genome, rather than single mutations. In this case, information about single nucleotide variants will be of limited utility.
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Cancers are heterogeneous populations of cells. When sequence data is derived from a whole tumor, information about the differences in sequence and expression pattern between cells is lost. This difficulty can be ameliorated by single-cell analysis.
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mutation detection in cancer, the Sequencing Quality Control Phase 2 Consortium has established a pair of tumor-normal cell lines as community reference samples and data sets for the benchmarking of cancer mutation detections.
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Similar to whole genome sequencing, the information generated from this technique include: identification of nucleotide bases (DNA or RNA), copy number and sequence variants, mutation status, and structural changes such as
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investigate these events, the discovery sample set will include DNA from primary tumor, normal tissue (from the same individuals) and cancer cell lines. All results from this project are amalgamated and stored within the
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The ICGC’s goal is “To obtain a comprehensive description of genomic, transcriptomic and epigenomic changes in 50 different tumor types and/or subtypes which are of clinical and societal importance across the globe”.
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These cellular factions could only have been identified through cancer genome sequencing, showing the information that sequencing can yield, and the complexity and heterogeneity of a tumor within one individual.
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clinicians and oncologists to identify the specific and unique changes a patient has undergone to develop their cancer. Based on these changes, a personalized therapeutic strategy can be undertaken.
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et al. identified cellular fractions characterized by common mutational changes to illustrate the heterogeneity of a particular tumor pre- and post-treatment vs. normal blood in one individual.
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of a single, homogeneous or heterogeneous group of cancer cells. It is a biochemical laboratory method for the characterization and identification of the DNA or RNA sequences of cancer cell(s).
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G.; Park, B. H.; Bachman, K. E.; Papadopoulos, N.; Vogelstein, B.; Kinzler, K. W.; Velculescu, V. E. (2006). "The Consensus Coding Sequences of Human Breast and Colorectal Cancers".
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heel" target for anti-cancer drugs. However, somatic mutations tend to cluster in a limited number of signalling pathways, which are potential treatment targets.
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data from many different research groups. As of December 2011, the ICGC includes 45 committed projects and has data from 2,961 cancer genomes available.
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of 11 breast and colorectal tumors. The first whole cancer genome to be sequenced was from cytogenetically normal acute myeloid leukaemia by Ley
2125:"Aneuploidy approaching a perfect score in predicting and preventing cancer: highlights from a conference held in Oakland, CA in January, 2004" 411: 199: 126: 451: 278: 158:
changes. Identification and characterization of all these changes can be accomplished through various cancer genome sequencing strategies.
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to form a representation of the chromosomes being sequenced. With cancer genomes, this is usually done by aligning the reads to the human
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Historically, cancer genome sequencing efforts has been divided between transcriptome-based sequencing projects and DNA-centered efforts.
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funded by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). Combined with these efforts, the
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A big contribution to cancer death and failed cancer treatment is clonal evolution at the cytogenetic level, for example as seen in
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characterization and analysis. The data and information generated is freely available through the projects TCGA data portal.
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The two main projects focused on complete cancer characterization in individuals, heavily involving sequencing include the
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The process of tumorigenesis that transforms a normal cell to a cancerous cell involve a series of complex genetic and
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Garson OM; et al. (July 1989). "Cytogenetic studies of 103 patients with acute myelogenous leukemia in relapse".
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is the set of detected genomic variants not related to the cancer under study. (The term is a play on the name
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Joseph R. Testa; et al. (September 1979). "Evolution of Karyotypes in Acute Nonlymphocytic Leukemia".
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nervous system, breast, gastrointestinal, gynecologic, head and neck, hematologic, thoracic, and urologic.
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Wood, L.D.; et al. (November 2007). "The genomic landscapes of human breast and colorectal cancers".
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done for patients clinical trials designed to assess the personal genomics approach to cancer treatment.
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Francis S. Collins and Anna D. Barker. "Mapping the Cancer Genome". Scientific American, February 2007
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Kohane, I. S.; Masys, D. R.; Altman, R. B. (2006). "The Incidentalome: A Threat to Genomic Medicine".
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sequencing technology. Three major third generation platforms include Pacific Biosciences
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The work-flow of the sequencing of a tumor from biopsy to treatment recommendation.
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Unlike whole genome (WG) sequencing which is typically from blood cells, such as
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Cancer genome sequencing is not limited to WG sequencing and can also include
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The CGAP published the largest publicly available collection of cancer
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in November 2008. The first breast cancer tumor was sequenced by Shah
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in October 2009, the first lung and skin tumors by Pleasance
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As with any genome sequencing project, the reads must be
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in January 2010, and the first prostate tumors by Berger
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Cancer Gene Sequencing Raises New Medical Ethics Issues
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Cgap.nci.nih.gov 442:Precision medicine 303: 259: 251: 166:Clinical Relevance 117:Sanger Institute's 93:in February 2011. 1835:(6822): 860–921. 1775:(7239): 719–724. 1432:(111): 111ra121. 585:(5797): 268–274. 437:Polony sequencing 273:by ligation, and 2275: 2205: 2199: 2193: 2192: 2164: 2155: 2154: 2144: 2120: 2114: 2113: 2077: 2068: 2067: 2057: 2032:(5897): 1801–6. 2017: 2011: 2010: 1984: 1956: 1945: 1944: 1934: 1910: 1904: 1903: 1893: 1876:(9): 1151–1160. 1861: 1855: 1854: 1844: 1842:10.1038/35057062 1826: 1817: 1811: 1810: 1800: 1760: 1749: 1748: 1738: 1706: 1700: 1699: 1689: 1679: 1647: 1641: 1640: 1630: 1620: 1588: 1582: 1581: 1571: 1546:(7382): 506–10. 1531: 1522: 1521: 1493: 1487: 1486: 1466: 1460: 1459: 1449: 1417: 1404: 1403: 1393: 1383: 1359: 1348: 1347: 1337: 1313: 1307: 1306: 1296: 1264: 1258: 1257: 1247: 1223: 1217: 1216: 1206: 1166: 1160: 1159: 1157: 1156: 1145: 1134: 1133: 1131: 1130: 1114: 1108: 1107: 1105: 1104: 1089: 1083: 1072: 1066: 1065: 1063: 1062: 1051: 1045: 1044: 1034: 1010: 1004: 1003: 978:(5315): 1023–4. 967: 961: 960: 950: 925:(7333): 214–20. 910: 904: 903: 893: 861: 855: 854: 844: 827:(7278): 184–90. 812: 806: 805: 795: 778:(7265): 809–13. 763: 757: 756: 746: 703: 697: 696: 662: 633: 627: 626: 573: 567: 566: 556: 524: 518: 517: 507: 497: 473: 351:treatment plan. 311:reference genome 2283: 2282: 2278: 2277: 2276: 2274: 2273: 2272: 2263:Cancer genomics 2253: 2252: 2214: 2209: 2208: 2200: 2196: 2166: 2165: 2158: 2122: 2121: 2117: 2079: 2078: 2071: 2019: 2018: 2014: 1982:10.1.1.218.5477 1958: 1957: 1948: 1912: 1911: 1907: 1863: 1862: 1858: 1824: 1819: 1818: 1814: 1762: 1761: 1752: 1708: 1707: 1703: 1649: 1648: 1644: 1590: 1589: 1585: 1533: 1532: 1525: 1495: 1494: 1490: 1471:Cancer Research 1468: 1467: 1463: 1419: 1418: 1407: 1361: 1360: 1351: 1328:(23): 3215–31. 1315: 1314: 1310: 1266: 1265: 1261: 1225: 1224: 1220: 1181:(7291): 993–8. 1168: 1167: 1163: 1154: 1152: 1147: 1146: 1137: 1128: 1126: 1125:on July 2, 2013 1116: 1115: 1111: 1102: 1100: 1099:on July 2, 2013 1091: 1090: 1086: 1081:Wayback Machine 1073: 1069: 1060: 1058: 1053: 1052: 1048: 1012: 1011: 1007: 969: 968: 964: 912: 911: 907: 876:(7278): 191–6. 863: 862: 858: 814: 813: 809: 765: 764: 760: 721:(7218): 66–72. 705: 704: 700: 660:10.1.1.218.5477 635: 634: 630: 575: 574: 570: 539:(7189): 872–6. 526: 525: 521: 475: 474: 470: 465: 373: 357: 336: 324: 295: 243: 234: 221: 208: 188: 168: 152: 147: 145:Societal Impact 99: 63:gene expression 32:James D. 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Craig Venter 12: 11: 5: 2281: 2279: 2271: 2270: 2268:DNA sequencing 2265: 2255: 2254: 2251: 2250: 2245: 2240: 2235: 2230: 2225: 2220: 2213: 2212:External links 2210: 2207: 2206: 2194: 2175:(2): 212–215. 2156: 2115: 2069: 2012: 1946: 1905: 1856: 1812: 1750: 1701: 1642: 1583: 1523: 1504:(2): 187–202. 1488: 1477:(9): 3619–27. 1461: 1405: 1368:Genome Biology 1349: 1308: 1259: 1218: 1161: 1135: 1109: 1084: 1067: 1046: 1025:(24): 1801–3. 1005: 962: 905: 856: 807: 758: 698: 628: 568: 519: 467: 466: 464: 461: 460: 459: 454: 449: 447:Pyrosequencing 444: 439: 434: 429: 424: 419: 414: 409: 404: 399: 394: 389: 384: 379: 372: 369: 356: 353: 335: 332: 294: 291: 242: 239: 233: 230: 220: 217: 207: 204: 187: 184: 167: 164: 151: 148: 146: 143: 135:transcriptomic 98: 95: 13: 10: 9: 6: 4: 3: 2: 2280: 2269: 2266: 2264: 2261: 2260: 2258: 2249: 2246: 2244: 2241: 2239: 2236: 2234: 2231: 2229: 2226: 2224: 2221: 2219: 2216: 2215: 2211: 2203: 2198: 2195: 2190: 2186: 2182: 2178: 2174: 2170: 2163: 2161: 2157: 2152: 2148: 2143: 2138: 2134: 2130: 2126: 2119: 2116: 2111: 2107: 2103: 2099: 2095: 2091: 2087: 2083: 2076: 2074: 2070: 2065: 2061: 2056: 2051: 2047: 2043: 2039: 2035: 2031: 2027: 2023: 2016: 2013: 2008: 2004: 2000: 1996: 1992: 1988: 1983: 1978: 1974: 1970: 1967:(5853): 8–9. 1966: 1962: 1955: 1953: 1951: 1947: 1942: 1938: 1933: 1928: 1924: 1920: 1916: 1909: 1906: 1901: 1897: 1892: 1887: 1883: 1879: 1875: 1871: 1867: 1860: 1857: 1852: 1848: 1843: 1838: 1834: 1830: 1823: 1816: 1813: 1808: 1804: 1799: 1794: 1790: 1786: 1782: 1778: 1774: 1770: 1766: 1759: 1757: 1755: 1751: 1746: 1742: 1737: 1732: 1728: 1724: 1721:(4): 413–35. 1720: 1716: 1712: 1705: 1702: 1697: 1693: 1688: 1683: 1678: 1673: 1669: 1665: 1661: 1657: 1653: 1646: 1643: 1638: 1634: 1629: 1624: 1619: 1614: 1610: 1606: 1603:(12): 104–8. 1602: 1598: 1594: 1587: 1584: 1579: 1575: 1570: 1565: 1561: 1557: 1553: 1549: 1545: 1541: 1537: 1530: 1528: 1524: 1519: 1515: 1511: 1507: 1503: 1499: 1492: 1489: 1484: 1480: 1476: 1472: 1465: 1462: 1457: 1453: 1448: 1443: 1439: 1435: 1431: 1427: 1423: 1416: 1414: 1412: 1410: 1406: 1401: 1397: 1392: 1387: 1382: 1377: 1373: 1369: 1365: 1358: 1356: 1354: 1350: 1345: 1341: 1336: 1331: 1327: 1323: 1319: 1312: 1309: 1304: 1300: 1295: 1290: 1286: 1282: 1279:(4): 683–92. 1278: 1274: 1270: 1263: 1260: 1255: 1251: 1246: 1241: 1238:(2): 159–70. 1237: 1233: 1229: 1222: 1219: 1214: 1210: 1205: 1200: 1196: 1192: 1188: 1184: 1180: 1176: 1172: 1165: 1162: 1150: 1144: 1142: 1140: 1136: 1124: 1120: 1113: 1110: 1098: 1094: 1088: 1085: 1082: 1078: 1075: 1071: 1068: 1056: 1050: 1047: 1042: 1038: 1033: 1028: 1024: 1020: 1016: 1009: 1006: 1001: 997: 993: 989: 985: 981: 977: 973: 966: 963: 958: 954: 949: 944: 940: 936: 932: 928: 924: 920: 916: 909: 906: 901: 897: 892: 887: 883: 879: 875: 871: 867: 860: 857: 852: 848: 843: 838: 834: 830: 826: 822: 818: 811: 808: 803: 799: 794: 789: 785: 781: 777: 773: 769: 762: 759: 754: 750: 745: 740: 736: 732: 728: 724: 720: 716: 712: 708: 702: 699: 694: 690: 686: 682: 678: 674: 670: 666: 661: 656: 652: 648: 644: 640: 632: 629: 624: 620: 616: 612: 608: 604: 600: 596: 592: 588: 584: 580: 572: 569: 564: 560: 555: 550: 546: 542: 538: 534: 530: 523: 520: 515: 511: 506: 501: 496: 491: 487: 483: 479: 472: 469: 462: 458: 455: 453: 450: 448: 445: 443: 440: 438: 435: 433: 430: 428: 425: 423: 420: 418: 415: 413: 410: 408: 405: 403: 400: 398: 395: 393: 390: 388: 385: 383: 380: 378: 375: 374: 370: 368: 366: 365:incidentaloma 362: 361:incidentalome 355:Incidentalome 354: 352: 348: 344: 340: 333: 331: 327: 322: 318: 314: 312: 308: 299: 293:Data Analysis 292: 290: 288: 284: 280: 276: 272: 268: 263: 255: 247: 240: 238: 231: 229: 225: 218: 216: 214: 205: 203: 201: 197: 193: 185: 183: 179: 177: 173: 165: 163: 159: 157: 149: 144: 142: 140: 136: 132: 128: 123: 121: 118: 113: 111: 106: 102: 96: 94: 92: 88: 84: 80: 74: 72: 68: 64: 60: 56: 55:transcriptome 52: 47: 45: 41: 35: 33: 29: 24: 22: 18: 2197: 2172: 2168: 2135:(6): 823–8. 2132: 2128: 2118: 2088:(5): 535–7. 2085: 2081: 2029: 2025: 2015: 1964: 1960: 1922: 1918: 1908: 1873: 1869: 1859: 1832: 1828: 1815: 1772: 1768: 1718: 1714: 1704: 1662:(2): 560–4. 1659: 1655: 1645: 1600: 1596: 1586: 1543: 1539: 1501: 1497: 1491: 1474: 1470: 1464: 1429: 1425: 1371: 1367: 1325: 1321: 1311: 1276: 1272: 1262: 1235: 1231: 1221: 1178: 1174: 1164: 1153:. Retrieved 1127:. Retrieved 1123:the original 1112: 1101:. Retrieved 1097:the original 1087: 1070: 1059:. Retrieved 1049: 1022: 1018: 1008: 975: 971: 965: 922: 918: 908: 873: 869: 859: 824: 820: 810: 775: 771: 761: 718: 714: 701: 642: 638: 631: 582: 578: 571: 536: 532: 522: 488:(10): e254. 485: 482:PLOS Biology 481: 471: 432:Oncogenomics 360: 358: 349: 345: 341: 337: 328: 323: 319: 315: 304: 264: 260: 235: 226: 222: 209: 189: 180: 169: 160: 153: 124: 114: 107: 103: 100: 90: 86: 82: 78: 75: 48: 44:fusion genes 36: 25: 16: 15: 707:Timothy Ley 334:Limitations 2257:Categories 2129:Cell Cycle 1925:: 407–30. 1374:(8): R82. 1155:2013-09-14 1151:. Icgc.org 1129:2013-09-14 1103:2013-09-14 1061:2013-09-14 463:References 156:epigenetic 139:epigenetic 1977:CiteSeerX 677:0036-8075 655:CiteSeerX 607:0036-8075 307:assembled 281:, Oxford 112:in 2003. 2189:16835427 2151:15197343 2110:39302093 2102:15877064 2064:18772397 1999:17932254 1941:21639794 1900:34504347 1851:11237011 1807:19360079 1745:21698376 1578:22237025 1456:22133722 1400:20696054 1344:17158741 1303:17320506 1213:20393554 1077:Archived 957:21307934 900:20016485 851:20016488 802:19812674 753:18987736 685:17932254 623:10805017 615:16959974 563:18421352 514:17803354 371:See also 30:'s and 2055:2848990 2034:Bibcode 2026:Science 2007:7586573 1969:Bibcode 1961:Science 1891:8532138 1798:2821689 1777:Bibcode 1736:3189340 1664:Bibcode 1637:1422003 1605:Bibcode 1569:3267864 1548:Bibcode 1518:2766243 1447:3476478 1391:2945784 1294:3894624 1254:8861899 1204:2902243 1183:Bibcode 1041:8961968 1000:5832728 992:9173535 972:Science 948:3075885 927:Bibcode 891:3145108 842:2880489 780:Bibcode 744:2603574 723:Bibcode 693:7586573 647:Bibcode 639:Science 587:Bibcode 579:Science 541:Bibcode 505:1964779 131:genomic 97:History 19:is the 2187:  2149:  2108:  2100:  2062:  2052:  2005:  1997:  1979:  1939:  1898:  1888:  1849:  1829:Nature 1805:  1795:  1769:Nature 1743:  1733:  1696:265521 1694:  1687:392330 1684:  1635:  1628:431765 1625:  1576:  1566:  1540:Nature 1516:  1483:476688 1481:  1454:  1444:  1398:  1388:  1342:  1301:  1291:  1252:  1211:  1201:  1175:Nature 1039:  998:  990:  955:  945:  919:Nature 898:  888:  870:Nature 849:  839:  821:Nature 800:  772:Nature 751:  741:  715:Nature 691:  683:  675:  657:  621:  613:  605:  561:  533:Nature 512:  502:  285:, and 91:et al. 87:et al. 83:et al. 79:et al. 2106:S2CID 2003:S2CID 1825:(PDF) 996:S2CID 689:S2CID 619:S2CID 67:miRNA 51:exome 2223:CGAP 2185:PMID 2169:JAMA 2147:PMID 2098:PMID 2060:PMID 1995:PMID 1937:PMID 1896:PMID 1847:PMID 1803:PMID 1741:PMID 1692:PMID 1656:PNAS 1633:PMID 1597:PNAS 1574:PMID 1514:PMID 1479:PMID 1452:PMID 1396:PMID 1340:PMID 1299:PMID 1273:Cell 1250:PMID 1232:Cell 1209:PMID 1037:PMID 988:PMID 953:PMID 896:PMID 847:PMID 798:PMID 749:PMID 681:PMID 673:ISSN 611:PMID 603:ISSN 559:PMID 510:PMID 359:The 176:Ding 137:and 125:The 115:The 42:and 2177:doi 2173:296 2137:doi 2090:doi 2050:PMC 2042:doi 2030:321 1987:doi 1965:318 1927:doi 1886:PMC 1878:doi 1837:doi 1833:409 1793:PMC 1785:doi 1773:458 1731:PMC 1723:doi 1682:PMC 1672:doi 1623:PMC 1613:doi 1564:PMC 1556:doi 1544:481 1506:doi 1442:PMC 1434:doi 1386:PMC 1376:doi 1330:doi 1289:PMC 1281:doi 1277:128 1240:doi 1199:PMC 1191:doi 1179:464 1027:doi 980:doi 976:267 943:PMC 935:doi 923:470 886:PMC 878:doi 874:463 837:PMC 829:doi 825:463 788:doi 776:461 739:PMC 731:doi 719:456 665:doi 643:318 595:doi 583:314 549:doi 537:452 500:PMC 490:doi 2259:: 2183:. 2171:. 2159:^ 2145:. 2131:. 2127:. 2104:. 2096:. 2086:23 2084:. 2072:^ 2058:. 2048:. 2040:. 2028:. 2024:. 2001:. 1993:. 1985:. 1975:. 1963:. 1949:^ 1935:. 1923:12 1921:. 1917:. 1894:. 1884:. 1874:39 1872:. 1868:. 1845:. 1831:. 1827:. 1801:. 1791:. 1783:. 1771:. 1767:. 1753:^ 1739:. 1729:. 1719:52 1717:. 1713:. 1690:. 1680:. 1670:. 1660:74 1658:. 1654:. 1631:. 1621:. 1611:. 1601:74 1599:. 1595:. 1572:. 1562:. 1554:. 1542:. 1538:. 1526:^ 1512:. 1502:40 1500:. 1475:39 1473:. 1450:. 1440:. 1428:. 1424:. 1408:^ 1394:. 1384:. 1372:11 1370:. 1366:. 1352:^ 1338:. 1326:20 1324:. 1320:. 1297:. 1287:. 1275:. 1271:. 1248:. 1236:87 1234:. 1230:. 1207:. 1197:. 1189:. 1177:. 1173:. 1138:^ 1035:. 1023:88 1021:. 1017:. 994:. 986:. 974:. 951:. 941:. 933:. 921:. 917:. 894:. 884:. 872:. 868:. 845:. 835:. 823:. 819:. 796:. 786:. 774:. 770:. 747:. 737:. 729:. 717:. 713:. 687:. 679:. 671:. 663:. 653:. 641:. 617:. 609:. 601:. 593:. 581:. 557:. 547:. 535:. 531:. 508:. 498:. 484:. 480:. 313:. 289:. 269:, 133:, 65:, 53:, 46:. 2191:. 2179:: 2153:. 2139:: 2133:3 2112:. 2092:: 2066:. 2044:: 2036:: 2009:. 1989:: 1971:: 1943:. 1929:: 1902:. 1880:: 1853:. 1839:: 1809:. 1787:: 1779:: 1747:. 1725:: 1698:. 1674:: 1666:: 1639:. 1615:: 1607:: 1580:. 1558:: 1550:: 1520:. 1508:: 1485:. 1458:. 1436:: 1430:3 1402:. 1378:: 1346:. 1332:: 1305:. 1283:: 1256:. 1242:: 1215:. 1193:: 1185:: 1158:. 1132:. 1106:. 1064:. 1043:. 1029:: 1002:. 982:: 959:. 937:: 929:: 902:. 880:: 853:. 831:: 804:. 790:: 782:: 755:. 733:: 725:: 695:. 667:: 649:: 625:. 597:: 589:: 565:. 551:: 543:: 516:. 492:: 486:5

Index

whole genome sequencing
J. Craig Venter
James D. Watson
chromosomal translocations
fusion genes
exome
transcriptome
end-sequence profiling
gene expression
miRNA
alternative splicing
expressed sequence tags
Sanger Institute's
Cancer Genome Project
International Cancer Genome Consortium
genomic
transcriptomic
epigenetic
epigenetic
acute myeloid leukaemia
Ding
Cancer Genome Project
the Cancer Genome Atlas
International Cancer Genome Consortium
COSMIC cancer database


Roche/454 Pyro-sequencing
ABI/SOLiD sequencing
Illumina’s bridge amplification

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