Will the real mutation please stand up?

When a patient is diagnosed with cancer, a sample of the tumor is often analyzed to look for mutations that might guide the approach to targeted treatment of the disease. Jones et al. analyzed samples from more than 800 patients with 15 different cancer types and showed that this standard approach is not necessarily accurate without also analyzing a matched sample of normal DNA from the same patient. The authors found that, compared to analysis of paired samples, the standard tumor-only sequencing approach frequently identified mutations that were present in the patient’s normal tissues and were therefore not suitable for targeted therapy or, conversely, missed useful new mutations in the tumor.


Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients.
Get full access to this article

View all available purchase options and get full access to this article.

Already a Subscriber?

Supplementary Material


Fig. S1. Bioinformatic approach to classify somatic and germline mutations on the basis of the consequence of the alteration.
Fig. S2. Bioinformatic approach to classify somatic and germline mutations based on the affected protein domain.
Table S1. Genes analyzed in the targeted approach (provided in a separate Excel file).
Table S2. Summary of sequencing statistics (provided in a separate Excel file).
Table S3. Summary of performance characteristics of whole-exome and targeted analyses (provided in a separate Excel file).
Table S4. Characteristics of the tumor and normal samples (provided in a separate Excel file).
Table S5. Fraction of cases with somatic mutations in actionable genes (provided in a separate Excel file).
Table S6. Fraction of cases with evidence for clinical actionability in different tumor types (provided in a separate Excel file).
Table S7. Hereditary cancer predisposition genes (provided in a separate Excel file).
Table S8. Putative germline predisposing mutations (provided in a separate Excel file).
Table S9. Germline false-positive mutations in actionable genes (provided in a separate Excel file).


File (7-283ra53_sm.pdf)
File (


Van Allen E. M., Wagle N., Stojanov P., Perrin D. L., Cibulskis K., Marlow S., Jane-Valbuena J., Friedrich D. C., Kryukov G., Carter S. L., McKenna A., Sivachenko A., Rosenberg M., Kiezun A., Voet D., Lawrence M., Lichtenstein L. T., Gentry J. G., Huang F. W., Fostel J., Farlow D., Barbie D., Gandhi L., Lander E. S., Gray S. W., Joffe S., Janne P., Garber J., MacConaill L., Lindeman N., Rollins B., Kantoff P., Fisher S. A., Gabriel S., Getz G., Garraway L. A., Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine. Nat. Med. 20, 682–688 (2014).
Frampton G. M., Fichtenholtz A., Otto G. A., Wang K., Downing S. R., He J., Schnall-Levin M., White J., Sanford E. M., An P., Sun J., Juhn F., Brennan K., Iwanik K., Maillet A., Buell J., White E., Zhao M., Balasubramanian S., Terzic S., Richards T., Banning V., Garcia L., Mahoney K., Zwirko Z., Donahue A., Beltran H., Mosquera J. M., Rubin M. A., Dogan S., Hedvat C. V., Berger M. F., Pusztai L., Lechner M., Boshoff C., Jarosz M., Vietz C., Parker A., Miller V. A., Ross J. S., Curran J., Cronin M. T., Stephens P. J., Lipson D., Yelensky R., Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat. Biotechnol. 31, 1023–1031 (2013).
Garraway L. A., Jänne P. A., Circumventing cancer drug resistance in the era of personalized medicine. Cancer Discov. 2, 214–226 (2012).
Wagle N., Berger M. F., Davis M. J., Blumenstiel B., Defelice M., Pochanard P., Ducar M., Van Hummelen P., Macconaill L. E., Hahn W. C., Meyerson M., Gabriel S. B., Garraway L. A., High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing. Cancer Discov. 2, 82–93 (2012).
Dias-Santagata D., Akhavanfard S., David S. S., Vernovsky K., Kuhlmann G., Boisvert S. L., Stubbs H., McDermott U., Settleman J., Kwak E. L., Clark J. W., Isakoff S. J., Sequist L. V., Engelman J. A., Lynch T. J., Haber D. A., Louis D. N., Ellisen L. W., Borger D. R., Iafrate A. J., Rapid targeted mutational analysis of human tumours: A clinical platform to guide personalized cancer medicine. EMBO Mol. Med. 2, 146–158 (2010).
Kerick M., Isau M., Timmermann B., Sultmann H., Herwig R., Krobitsch S., Schaefer G., Verdorfer I., Bartsch G., Klocker H., Lehrach H., Schweiger M. R., Targeted high throughput sequencing in clinical cancer settings: Formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity. BMC Med. Genomics 4, 68 (2011).
Roychowdhury S., Iyer M. K., Robinson D. R., Lonigro R. J., Wu Y. M., Cao X., Kalyana-Sundaram S., Sam L., Balbin O. A., Quist M. J., Barrette T., Everett J., Siddiqui J., Kunju L. P., Navone N., Araujo J. C., Troncoso P., Logothetis C. J., Innis J. W., Smith D. C., Lao C. D., Kim S. Y., Roberts J. S., Gruber S. B., Pienta K. J., Talpaz M., Chinnaiyan A. M., Personalized oncology through integrative high-throughput sequencing: A pilot study. Sci. Transl. Med. 3, 111ra121 (2011).
Stegmeier F., Warmuth M., Sellers W. R., Dorsch M., Targeted cancer therapies in the twenty-first century: Lessons from imatinib. Clin. Pharmacol. Ther. 87, 543–552 (2010).
Amado R. G., Wolf M., Peeters M., Van Cutsem E., Siena S., Freeman D. J., Juan T., Sikorski R., Suggs S., Radinsky R., Patterson S. D., Chang D. D., Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J. Clin. Oncol. 26, 1626–1634 (2008).
Parsons D. W., Jones S., Zhang X., Lin J. C., Leary R. J., Angenendt P., Mankoo P., Carter H., Siu I. M., Gallia G. L., Olivi A., McLendon R., Rasheed B. A., Keir S., Nikolskaya T., Nikolsky Y., Busam D. A., Tekleab H., Diaz L. A., Hartigan J., Smith D. R., Strausberg R. L., Marie S. K., Shinjo S. M., Yan H., Riggins G. J., Bigner D. D., Karchin R., Papadopoulos N., Parmigiani G., Vogelstein B., Velculescu V. E., Kinzler K. W., An integrated genomic analysis of human glioblastoma multiforme. Science 321, 1807–1812 (2008).
Fumagalli D., Gavin P. G., Taniyama Y., Kim S. I., Choi H. J., Paik S., Pogue-Geile K. L., A rapid, sensitive, reproducible and cost-effective method for mutation profiling of colon cancer and metastatic lymph nodes. BMC Cancer 10, 101 (2010).
Lin M. T., Mosier S. L., Thiess M., Beierl K. F., Debeljak M., Tseng L. H., Chen G., Yegnasubramanian S., Ho H., Cope L., Wheelan S. J., Gocke C. D., Eshleman J. R., Clinical validation of KRAS, BRAF, and EGFR mutation detection using next-generation sequencing. Am. J. Clin. Pathol. 141, 856–866 (2014).
Wong N. A., Gonzalez D., Salto-Tellez M., Butler R., Diaz-Cano S. J., Ilyas M., Newman W., Shaw E., Taniere P., Walsh S. V.Association of Clinical Pathologists Molecular Pathology and Diagnostics Group, RAS testing of colorectal carcinoma—A guidance document from the Association of Clinical Pathologists Molecular Pathology and Diagnostics Group. J. Clin. Pathol. 67, 751–757 (2014).
Kraus C., Rau T. T., Lux P., Erlenbach-Wünsch K., Löhr S., Krumbiegel M., Thiel C. T., Stöhr R., Agaimy A., Croner R. S., Stürzl M., Hohenberger W., Hartmann A., Reis A., Comprehensive screening for mutations associated with colorectal cancer in unselected cases reveals penetrant and nonpenetrant mutations. Int. J. Cancer 136, E559–E568 (2015).
De Leeneer K., Coene I., Crombez B., Simkens J., Van den Broecke R., Bols A., Stragier B., Vanhoutte I., De Paepe A., Poppe B., Claes K., Prevalence of BRCA1/2 mutations in sporadic breast/ovarian cancer patients and identification of a novel de novo BRCA1 mutation in a patient diagnosed with late onset breast and ovarian cancer: Implications for genetic testing. Breast Cancer Res. Treat. 132, 87–95 (2012).
Sjöblom 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., Gazdar A. F., Hartigan J., Wu L., Liu C., Parmigiani G., Park B. H., Bachman K. E., Papadopoulos N., Vogelstein B., Kinzler K. W., Velculescu V. E., The consensus coding sequences of human breast and colorectal cancers. Science 314, 268–274 (2006).
Jones S., Zhang X., Parsons D. W., Lin J. C., Leary R. J., Angenendt P., Mankoo P., Carter H., Kamiyama H., Jimeno A., Hong S. M., Fu B., Lin M. T., Calhoun E. S., Kamiyama M., Walter K., Nikolskaya T., Nikolsky Y., Hartigan J., Smith D. R., Hidalgo M., Leach S. D., Klein A. P., Jaffee E. M., Goggins M., Maitra A., Iacobuzio-Donahue C., Eshleman J. R., Kern S. E., Hruban R. H., Karchin R., Papadopoulos N., Parmigiani G., Vogelstein B., Velculescu V. E., Kinzler K. W., Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321, 1801–1806 (2008).
Parsons D. W., Li M., Zhang X., Jones S., Leary R. J., Lin J. C., Boca S. M., Carter H., Samayoa J., Bettegowda C., Gallia G. L., Jallo G. I., Binder Z. A., Nikolsky Y., Hartigan J., Smith D. R., Gerhard D. S., Fults D. W., VandenBerg S., Berger M. S., Marie S. K., Shinjo S. M., Clara C., Phillips P. C., Minturn J. E., Biegel J. A., Judkins A. R., Resnick A. C., Storm P. B., Curran T., He Y., Rasheed B. A., Friedman H. S., Keir S. T., McLendon R., Northcott P. A., Taylor M. D., Burger P. C., Riggins G. J., Karchin R., Parmigiani G., Bigner D. D., Yan H., Papadopoulos N., Vogelstein B., Kinzler K. W., Velculescu V. E., The genetic landscape of the childhood cancer medulloblastoma. Science 331, 435–439 (2011).
Sausen M., Leary R. J., Jones S., Wu J., Reynolds C. P., Liu X., Blackford A., Parmigiani G., Diaz L. A., Papadopoulos N., Vogelstein B., Kinzler K. W., Velculescu V. E., Hogarty M. D., Integrated genomic analyses identify ARID1A and ARID1B alterations in the childhood cancer neuroblastoma. Nat. Genet. 45, 12–17 (2013).
Jones S., Wang T. L., Shih le-M., Mao T. L., Nakayama K., Roden R., Glas R., Slamon D., Diaz L. A., Vogelstein B., Kinzler K. W., Velculescu V. E., Papadopoulos N., Frequent mutations of chromatin remodeling gene ARID1A in ovarian clear cell carcinoma. Science 330, 228–231 (2010).
Wei X., Walia V., Lin J. C., Teer J. K., Prickett T. D., Gartner J., Davis S.NISC Comparative Sequencing Program, Stemke-Hale K., Davies M. A., Gershenwald J. E., Robinson W., Robinson S., Rosenberg S. A., Samuels Y., Exome sequencing identifies GRIN2A as frequently mutated in melanoma. Nat. Genet. 43, 442–446 (2011).
Cancer Genome Atlas Research Network, Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615 (2011).
Cancer Genome Atlas Research Network, Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 499, 43–49 (2013).
Cancer Genome Atlas Research Network, Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia, N. Engl. J. Med. 368, 2059–2074 (2013).
Gao Y. B., Chen Z. L., Li J. G., Hu X. D., Shi X. J., Sun Z. M., Zhang F., Zhao Z. R., Li Z. T., Liu Z. Y., Zhao Y. D., Sun J., Zhou C. C., Yao R., Wang S. Y., Wang P., Sun N., Zhang B. H., Dong J. S., Yu Y., Luo M., Feng X. L., Shi S. S., Zhou F., Tan F. W., Qiu B., Li N., Shao K., Zhang L. J., Zhang L. J., Xue Q., Gao S. G., He J., Genetic landscape of esophageal squamous cell carcinoma. Nat. Genet. 46, 1097–1102 (2014).
Shern J. F., Chen L., Chmielecki J., Wei J. S., Patidar R., Rosenberg M., Ambrogio L., Auclair D., Wang J., Song Y. K., Tolman C., Hurd L., Liao H., Zhang S., Bogen D., Brohl A. S., Sindiri S., Catchpoole D., Badgett T., Getz G., Mora J., Anderson J. R., Skapek S. X., Barr F. G., Meyerson M., Hawkins D. S., Khan J., Comprehensive genomic analysis of rhabdomyosarcoma reveals a landscape of alterations affecting a common genetic axis in fusion-positive and fusion-negative tumors. Cancer Discov. 4, 216–231 (2014).
Jiao Y., Pawlik T. M., Anders R. A., Selaru F. M., Streppel M. M., Lucas D. J., Niknafs N., Guthrie V. B., Maitra A., Argani P., Offerhaus G. J., Roa J. C., Roberts L. R., Gores G. J., Popescu I., Alexandrescu S. T., Dima S., Fassan M., Simbolo M., Mafficini A., Capelli P., Lawlor R. T., Ruzzenente A., Guglielmi A., Tortora G., de Braud F., Scarpa A., Jarnagin W., Klimstra D., Karchin R., Velculescu V. E., Hruban R. H., Vogelstein B., Kinzler K. W., Papadopoulos N., Wood L. D., Exome sequencing identifies frequent inactivating mutations in BAP1, ARID1A and PBRM1 in intrahepatic cholangiocarcinomas. Nat. Genet. 45, 1470–1473 (2013).
Zang Z. J., Cutcutache I., Poon S. L., Zhang S. L., McPherson J. R., Tao J., Rajasegaran V., Heng H. L., Deng N., Gan A., Lim K. H., Ong C. K., Huang D., Chin S. Y., Tan I. B., Ng C. C., Yu W., Wu Y., Lee M., Wu J., Poh D., Wan W. K., Rha S. Y., So J., Salto-Tellez M., Yeoh K. G., Wong W. K., Zhu Y. J., Futreal P. A., Pang B., Ruan Y., Hillmer A. M., Bertrand D., Nagarajan N., Rozen S., Teh B. T., Tan P., Exome sequencing of gastric adenocarcinoma identifies recurrent somatic mutations in cell adhesion and chromatin remodeling genes. Nat. Genet. 44, 570–574 (2012).
Cancer Genome Atlas Research Network, Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014).
Jiao Y., Shi C., Edil B. H., de Wilde R. F., Klimstra D. S., Maitra A., Schulick R. D., Tang L. H., Wolfgang C. L., Choti M. A., Velculescu V. E., Diaz L. A., Vogelstein B., Kinzler K. W., Hruban R. H., Papadopoulos N., DAXX/ATRX, MEN1, and mTOR pathway genes are frequently altered in pancreatic neuroendocrine tumors. Science 331, 1199–1203 (2011).
Li A., Swift M., Mutations at the ataxia-telangiectasia locus and clinical phenotypes of A–T patients. Am. J. Med. Genet. 92, 170–177 (2000).
1000 Genomes Project ConsortiumAbecasis G. R., Altshuler D., Auton A., Brooks L. D., Durbin R. M., Gibbs R. A., Hurles M. E., McVean G. A., A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
UK launches 1000,000-genome initiative. Cancer Discov. 3, OF6 (2013).
Human Longevity Inc. launches massive sequencing effort. Cancer Discov. 4, OF5 (2014).
Carter H., Chen S., Isik L., Tyekucheva S., Velculescu V. E., Kinzler K. W., Vogelstein B., Karchin R., Cancer-specific high-throughput annotation of somatic mutations: Computational prediction of driver missense mutations. Cancer Res. 69, 6660–6667 (2009).
Ng P. C., Henikoff S., Predicting deleterious amino acid substitutions. Genome Res. 11, 863–874 (2001).
Adzhubei I. A., Schmidt S., Peshkin L., Ramensky V. E., Gerasimova A., Bork P., Kondrashov A. S., Sunyaev S. R., A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).
Jones S., Chen W. D., Parmigiani G., Diehl F., Beerenwinkel N., Antal T., Traulsen A., Nowak M. A., Siegel C., Velculescu V. E., Kinzler K. W., Vogelstein B., Willis J., Markowitz S. D., Comparative lesion sequencing provides insights into tumor evolution. Proc. Natl. Acad. Sci. U.S.A. 105, 4283–4288 (2008).
Needleman S. B., Wunsch C. D., A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48, 443–453 (1970).
Marchler-Bauer A., Lu S., Anderson J. B., Chitsaz F., Derbyshire M. K., DeWeese-Scott C., Fong J. H., Geer L. Y., Geer R. C., Gonzales N. R., Gwadz M., Hurwitz D. I., Jackson J. D., Ke Z., Lanczycki C. J., Lu F., Marchler G. H., Mullokandov M., Omelchenko M. V., Robertson C. L., Song J. S., Thanki N., Yamashita R. A., Zhang D., Zhang N., Zheng C., Bryant S. H., CDD: A Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res. 39, D225–D229 (2011).
Landrum M. J., Lee J. M., Riley G. R., Jang W., Rubinstein W. S., Church D. M., Maglott D. R., ClinVar: Public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 42, D980–D985 (2014).
Couch F. J., Weber B. L., Mutations and polymorphisms in the familial early-onset breast cancer (BRCA1) gene. Hum. Mutat. 8, 8–18 (1996).
Fokkema I. F., Taschner P. E., Schaafsma G. C., Celli J., Laros J. F., den Dunnen J. T., LOVD v.2.0: The next generation in gene variant databases. Hum. Mutat. 32, 557–563 (2011).
Petitjean A., Mathe E., Kato S., Ishioka C., Tavtigian S. V., Hainaut P., Olivier M., Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: Lessons from recent developments in the IARC TP53 database. Hum. Mutat. 28, 622–629 (2007).
Thompson B. A., Spurdle A. B., Plazzer J. P., Greenblatt M. S., Akagi K., Al-Mulla F., Bapat B., Bernstein I., Capellá G., den Dunnen J. T., du Sart D., Fabre A., Farrell M. P., Farrington S. M., Frayling I. M., Frebourg T., Goldgar D. E., Heinen C. D., Holinski-Feder E., Kohonen-Corish M., Robinson K. L., Leung S. Y., Martins A., Moller P., Morak M., Nystrom M., Peltomaki P., Pineda M., Qi M., Ramesar R., Rasmussen L. J., Royer-Pokora B., Scott R. J., Sijmons R., Tavtigian S. V., Tops C. M., Weber T., Wijnen J., Woods M. O., Macrae F., Genuardi M.InSiGHT, Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database. Nat. Genet. 46, 107–115 (2014).

Information & Authors


Published In

Science Translational Medicine
Volume 7 | Issue 283
April 2015

Submission history

Received: 18 January 2015
Accepted: 6 March 2015


Request permissions for this article.


We thank V. Adleff and L. D. Wood for technical assistance and J. R. Eshelman, R. H. Hruban, and members of our laboratories for helpful discussions. Funding: This work was supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Commonwealth Foundation, American Association for Cancer Research Stand Up To Cancer–Dream Team Translational Cancer Research grant, John G. Ballenger Trust, FasterCures Research Acceleration Award, Swim Across America, and U.S. NIH grant CA121113. Author contributions: S.J. designed the study, performed analyses, and wrote the paper. V.A., K.L., S.P.-L., M.N., D.R.R., M.K., E.P., K.G.G., D.M., and T.Z. performed analyses; M.S. and S.V.A. performed analyses and wrote the paper. M.S., B.C., and L.K. performed experiments. L.A.D. and V.E.V. designed the study, performed analyses, provided funding, and wrote the paper. Competing interests: Some of the work described in this publication is included in a pending patent application. L.A.D. and V.E.V. are cofounders of Personal Genome Diagnostics and are members of its Scientific Advisory Board and Board of Directors. L.A.D. and V.E.V. own Personal Genome Diagnostics stock, which is subject to certain restrictions under university policy. The terms of these arrangements are managed by the Johns Hopkins University in accordance with its conflict of interest policies.



Siân Jones
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Valsamo Anagnostou
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Karli Lytle
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Sonya Parpart-Li
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Monica Nesselbush
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
David R. Riley
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Manish Shukla
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Bryan Chesnick
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Maura Kadan
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Eniko Papp
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Kevin G. Galens
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Derek Murphy
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Theresa Zhang
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Lisa Kann
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Mark Sausen
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Samuel V. Angiuoli
Personal Genome Diagnostics, Baltimore, MD 21224, USA.
Luis A. Diaz, Jr.
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Victor E. Velculescu* [email protected]
The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.


*Corresponding author. E-mail: [email protected]

Metrics & Citations


Article Usage


Export citation

Select the format you want to export the citation of this publication.

Cited by
  1. Clinical cancer genomic profiling, Nature Reviews Genetics, 22, 8, (483-501), (2021).
  2. Actionable data for precision oncology: Framing trustworthy evidence for exploratory research and clinical diagnostics, Social Science & Medicine, 272, (113760), (2021).
  3. Identification of germline cancer predisposition variants during clinical ctDNA testing, Scientific Reports, 11, 1, (2021).
  4. Implication of ferroptosis in aging, Cell Death Discovery, 7, 1, (2021).
  5. Identification of the TP53 p.R337H Variant in Tumor Genomic Profiling Should Prompt Consideration of Germline Testing for Li-Fraumeni Syndrome , JCO Global Oncology, 7, (1141-1150), (2021).
  6. Clinical Validation of Whole Genome Sequencing for Cancer Diagnostics, The Journal of Molecular Diagnostics, 23, 7, (816-833), (2021).
  7. Use of Treatment-Focused Tumor Sequencing to Screen for Germline Cancer Predisposition, The Journal of Molecular Diagnostics, (2021).
  8. Cancer chemopreventive role of fisetin: Regulation of cell signaling pathways in different cancers, Pharmacological Research, (105784), (2021).
  9. The optimization of combinatorial drug therapies: Strategies and laboratorial platforms, Drug Discovery Today, (2021).
  10. Exceptional response to the ALK and ROS1 inhibitor lorlatinib and subsequent mechanism of resistance in relapsed ALK F1174L-mutated neuroblastoma , Molecular Case Studies, 7, 4, (a006064), (2021).
  11. See more

View Options

Get Access

Log in to view the full text

AAAS Log in

AAAS login provides access to Science for AAAS members, and access to other journals in the Science family to users who have purchased individual subscriptions.

Log in via OpenAthens.
Log in via Shibboleth.

More options

Register for free to read this article

As a service to the community, this article is available for free. Login or register for free to read this article.

View options

PDF format

Download this article as a PDF file

Download PDF







Share article link

Share on social media