Bio

Bio


The Curtis laboratory couples innovative experimental approaches, high-throughput omic technologies, statistical inference and computational modeling to interrogate the evolutionary dynamics of tumor progression and therapeutic resistance. To this end, Dr. Curtis and her team have developed an integrated experimental and computational framework to measure clinically relevant patient-specific parameters and to measure clonal dynamics. Her research also aims to develop a systematic interpretation of genotype/phenotype associations in cancer by leveraging state-of-the-art technologies and robust data integration techniques. For example, using integrative statistical approaches to mine multiple data types she lead a seminal study that redefined the molecular map of breast cancer, revealing novel subgroups with distinct clinical outcomes and subtype-specific drivers.

Academic Appointments


Administrative Appointments


  • Co-Director, Molecular Tumor Board, Stanford Cancer Institute (2014 - Present)

Honors & Awards


  • Kavli Frontier of Science Fellow, National Academy of Science (USA) (2016)
  • AACR Career Development Award, AACR Triple Negative Breast Cancer Foundation - Carol's Crusade for a Cure Foundation (2016)
  • Institutional Seed Grant Recipient, American Cancer Society (2013)
  • Career Development Award, STOP Cancer (2012)
  • V Scholar Award, V Foundation for Cancer Research (2012)
  • Scholar-In-Training Award, American Association for Cancer Research (2009)

Professional Education


  • Postdoctoral Fellow, University of Cambridge, Computational Biology (2010)
  • PhD, University of Southern California, Molecular and Computational Biology (2007)
  • MS, University of Southern California, Bioinformatics and Computational Biology (2005)
  • MSc, University of Heidelberg, Germany, Molecular Biology (2003)

Community and International Work


  • The Cancer Genome Atlas, Data Analysis Working Groups

    Topic

    Cancer Genomics

    Partnering Organization(s)

    NCI/TCGA

    Location

    US

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    Yes

Research & Scholarship

Current Research and Scholarly Interests


We are particularly interested in elucidating tumor evolutionary dynamics, novel therapeutic targets, and the genotype to phenotype map in cancer. A unifying theme of our research is to exploit ‘omic’ data derived from clinically annotated samples in robust computational frameworks coupled with iterative experimental validation in order to advance our understanding of cancer systems biology. In particular, we employ advanced genomic techniques, computational and mathematical modeling, and elegant model systems in order to:
1.) Model the evolutionary dynamics of tumor progression and therapeutic resistance
2) Elucidate disease etiology and novel molecular targets through integrative analyses of high-throughput omic data
3) Develop techniques for the systems-level interpretation of genotype-phenotype associations in cancer

Teaching

2018-19 Courses


Stanford Advisees


Graduate and Fellowship Programs


Publications

All Publications


  • Between-region genetic divergence reflects the mode and tempo of tumor evolution. Nature genetics Sun, R., Hu, Z., Sottoriva, A., Graham, T. A., Harpak, A., Ma, Z., Fischer, J. M., Shibata, D., Curtis, C. 2017

    Abstract

    Given the implications of tumor dynamics for precision medicine, there is a need to systematically characterize the mode of evolution across diverse solid tumor types. In particular, methods to infer the role of natural selection within established human tumors are lacking. By simulating spatial tumor growth under different evolutionary modes and examining patterns of between-region subclonal genetic divergence from multiregion sequencing (MRS) data, we demonstrate that it is feasible to distinguish tumors driven by strong positive subclonal selection from those evolving neutrally or under weak selection, as the latter fail to dramatically alter subclonal composition. We developed a classifier based on measures of between-region subclonal genetic divergence and projected patient data into model space, finding different modes of evolution both within and between solid tumor types. Our findings have broad implications for how human tumors progress, how they accumulate intratumoral heterogeneity, and ultimately how they may be more effectively treated.

    View details for DOI 10.1038/ng.3891

    View details for PubMedID 28581503

  • A population genetics perspective on the determinants of intra-tumor heterogeneity. Biochimica et biophysica acta Hu, Z., Sun, R., Curtis, C. 2017; 1867 (2): 109-126

    Abstract

    Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

    View details for DOI 10.1016/j.bbcan.2017.03.001

    View details for PubMedID 28274726

  • Integrated genomic characterization of oesophageal carcinoma NATURE Kim, J., Bowlby, R., Mungall, A. J., Robertson, A. G., Odze, R. D., Cherniack, A. D., Shih, J., Pedamallu, C. S., Cibulskis, C., Dunford, A., Meier, S. R., Kim, J., Raphael, B. J., Wu, H., Wong, A. M., Willis, J. E., Bass, A. J., Derks, S., Garman, K., McCall, S. J., Wiznerowicz, M., Pantazi, A., Parfenov, M., Thorsson, V., Shmulevich, I., Dhankani, V., Miller, M., Sakai, R., Wang, K., Schultz, N., Shen, R., Arora, A., Weinhold, N., Sanchez-Vega, F., Kelsen, D. P., Zhang, J., Felau, I., Demchok, J., Rabkin, C. S., Camargo, M. C., Zenklusen, J. C., Bowen, J., Leraas, K., Lichtenberg, T. M., Curtis, C., Seoane, J. A., Ojesina, A. I., Beer, D. G., Gulley, M. L., Pennathur, A., Luketich, J. D., Zhou, Z., Weisenberger, D. J., Akbani, R., Lee, J., Liu, W., Mills, G. B., Zhang, W., Reid, B. J., Hinoue, T., Laird, P. W., Shen, H., Piazuelo, M. B., Schneider, B. G., McLellan, M., Taylor-Weiner, A., Cibulskis, C., Lawrence, M., Cibulskis, K., Stewart, C., Getz, G., Lander, E., Gabriel, S. B., Ding, L., McLellan, M. D., Miller, C. A., Appelbaum, E. L., Cordes, M. G., Fronick, C. C., Fulton, L. A., Mardis, E. R., Wilson, R. K., Schmidt, H. K., Fulton, R. S., Ally, A., Balasundaram, M., Bowlby, R., Carlsen, R., Chuah, E., Dhalla, N., Holt, R. A., Jones, S. J., Kasaian, K., Brooks, D., Li, H. I., Ma, Y., Marra, M. A., Mayo, M., Moore, R. A., Mungall, A. J., Mungall, K. L., Robertson, A. G., Schein, J. E., Sipahimalani, P., Tam, A., Thiessen, N., Wong, T., Cherniack, A. D., Shih, J., Pedamallu, C. S., Beroukhim, R., Bullman, S., Cibulskis, C., Murray, B. A., Saksena, G., Schumacher, S. E., Gabriel, S., Meyerson, M., Hadjipanayis, A., Kucherlapati, R., Pantazi, A., Parfenov, M., Ren, X., Park, P. J., Lee, S., Kucherlapati, M., Yang, L., Baylin, S. B., Hoadley, K. A., Weisenberger, D. J., Bootwalla, M. S., Lai, P. H., Van den Berg, D. J., Berrios, M., Holbrook, A., Akbani, R., Hwang, J., Jang, H., Liu, W., Weinstein, J. N., Lee, J., Lu, Y., Sohn, B. H., Mills, G., Seth, S., Protopopov, A., Bristow, C. A., Mahadeshwar, H. S., Tang, J., Song, X., Zhang, J., Laird, P. W., Hinoue, T., Shen, H., Cho, J., Defrietas, T., Frazer, S., Gehlenborg, N., Heiman, D. I., Lawrence, M. S., Lin, P., Meier, S. R., Noble, M. S., Doug Voet, D., Zhang, H., Kim, J., Polak, P., Saksena, G., Chin, L., Getz, G., Wong, A. M., Raphael, B. J., Wu, H., Lee, S., Park, P. J., Yang, L., Thorsson, V., Bernard, B., Iype, L., Miller, M., Reynolds, S. M., Shmulevich, I., Dhankani, V., Abeshouse, A., Arora, A., Armenia, J., Kundra, R., Ladanyi, M., Kjong-Van Lehmann, Gao, J., Sander, C., Schultz, N., Sanchez-Vega, F., Shen, R., Weinhold, N., Chakravarty, D., Zhang, H., Radenbaugh, A., Hegde, A., Akbani, R., Liu, W., Weinstein, J. N., Chin, L., Bristow, C. A., Lu, Y., Penny, R., Crain, D., Gardner, J., Curley, E., Mallery, D., Morris, S., Paulauskis, J., Shelton, T., Shelton, C., Bowen, J., Frick, J., Gastier-Foster, J. M., Gerken, M., Leraas, K. M., Lichtenberg, T. M., Ramirez, N. C., Wise, L., Zmuda, E., Tarvin, K., Saller, C., Park, Y. S., Button, M., Carvalho, A. L., Reis, R. M., Matsushita, M. M., Lucchesi, F., de Oliveira, A. T., Le, X., Paklina, O., Setdikova, G., Lee, J., Bennett, J., Iacocca, M., Huelsenbeck-Dill, L., Potapova, C. O., Voronina, O., Liu, O., Fulidou, V., Cates, C., Sharp, A., Behera, M., Force, S., Khuri, F., Owonikoko, T., Pickens, A., Ramalingam, S., Sica, G., Dinjens, W., van Nistelrooij, A., Wijnhoven, B., Sandusky, G., Stepa, S., Crain, D., Paulauskis, J., Penny, R., Gardner, J., Mallery, D., Morris, S., Shelton, T., Shelton, C., Curley, E., Juhl, I. H., Zornig, C., Kwon, S. Y., Kelsen, D., Kim, G. H., Bartlett, J., Parfitt, J., Chetty, R., Darling, G., Knox, J., Wong, R., El-Zimaity, H., Liu, G., Boussioutas, A., Park, D. Y., Kemp, R., Carlotti, C. G., da Cunha Tirapelli, D. P., Saggioro, F. P., Sankarankutty, A. K., Noushmehr, H., dos Santos, J. S., Trevisan, F. A., Eschbacher, J., Eschbacher, J., Dubina, M., Mozgovoy, E., Carey, F., Chalmers, S., Forgie, I., Godwin, A., Reilly, C., Madan, R., Naima, Z., Ferrer-Torres, D., Rathmell, W. K., Dhir, R., Luketich, J., Pennathur, A., Ajani, J. A., McCall, S. J., Janjigian, Y., Kelsen, D., Ladanyi, M., Tang, L., Camargo, M. C., Ajani, J. A., Cheong, J., Chudamani, S., Liu, J., Lolla, L., Naresh, R., Pihl, T., Sun, Q., Wan, Y., Wu, Y., Demchok, J. A., Felau, I., Ferguson, M. L., Shaw, K. R., Sheth, M., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J. C., Hutter, C. M., Sofia, H. J., Zhang, J. 2017; 541 (7636): 169-?

    Abstract

    Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies.

    View details for DOI 10.1038/nature20805

    View details for Web of Science ID 000396125500030

    View details for PubMedID 28052061

  • A p53 Super-tumor Suppressor Reveals a Tumor Suppressive p53-Ptpn14-Yap Axis in Pancreatic Cancer. Cancer cell Mello, S. S., Valente, L. J., Raj, N., Seoane, J. A., Flowers, B. M., McClendon, J., Bieging-Rolett, K. T., Lee, J., Ivanochko, D., Kozak, M. M., Chang, D. T., Longacre, T. A., Koong, A. C., Arrowsmith, C. H., Kim, S. K., Vogel, H., Wood, L. D., Hruban, R. H., Curtis, C., Attardi, L. D. 2017; 32 (4): 460–73.e6

    Abstract

    The p53 transcription factor is a critical barrier to pancreatic cancer progression. To unravel mechanisms of p53-mediated tumor suppression, which have remained elusive, we analyzed pancreatic cancer development in mice expressing p53 transcriptional activation domain (TAD) mutants. Surprisingly, the p5353,54 TAD2 mutant behaves as a "super-tumor suppressor," with an enhanced capacity to both suppress pancreatic cancer and transactivate select p53 target genes, including Ptpn14. Ptpn14 encodes a negative regulator of the Yap oncoprotein and is necessary and sufficient for pancreatic cancer suppression, like p53. We show that p53 deficiency promotes Yap signaling and that PTPN14 and TP53 mutations are mutually exclusive in human cancers. These studies uncover a p53-Ptpn14-Yap pathway that is integral to p53-mediated tumor suppression.

    View details for DOI 10.1016/j.ccell.2017.09.007

    View details for PubMedID 29017057

    View details for PubMedCentralID PMC5659188

  • A Big Bang model of human colorectal tumor growth. Nature genetics Sottoriva, A., Kang, H., Ma, Z., Graham, T. A., Salomon, M. P., Zhao, J., Marjoram, P., Siegmund, K., Press, M. F., Shibata, D., Curtis, C. 2015

    Abstract

    What happens in early, still undetectable human malignancies is unknown because direct observations are impractical. Here we present and validate a 'Big Bang' model, whereby tumors grow predominantly as a single expansion producing numerous intermixed subclones that are not subject to stringent selection and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors showed an absence of selective sweeps, uniformly high intratumoral heterogeneity (ITH) and subclone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear 'born to be bad', with subclone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH, with important clinical implications.

    View details for DOI 10.1038/ng.3214

    View details for PubMedID 25665006

  • Comprehensive molecular characterization of gastric adenocarcinoma NATURE Bass, A. J., Thorsson, V., Shmulevich, I., Reynolds, S. M., Miller, M., Bernard, B., Hinoue, T., Laird, P. W., Curtis, C., Shen, H., Weisenberger, D. J., Schultz, N., Shen, R., Weinhold, N., Keiser, D. P., Bowlby, R., Sipahimalani, P., Cherniack, A. D., Getz, G., Liu, Y., Noble, M. S., Pedamallu, C., Sougnez, C., Taylor-Weiner, A., Akbani, R., Lee, J., Liu, W., Mills, G. B., Yang, D., Zhang, W., Pantazi, A., Parfenov, M., Gulley, M., Piazuelo, M. B., Schneider, B. G., Kim, J., Boussioutas, A., Sheth, M., Demchok, J. A., Rabkin, C. S., Willis, J. E., Ng, S., Garman, K., Beer, D. G., Pennathur, A., Raphael, B. J., Wu, H., Odze, R., Kim, H. K., Bowen, J., Leraas, K. M., Lichtenberg, T. M., Weaver, L., McLellan, M., Wiznerowicz, M., Sakai, R., Getz, G., Sougnez, C., Lawrence, M. S., Cibulskis, K., Lichtenstein, L., Fisher, S., Gabriel, S. B., Lander, E. S., Ding, L., Niu, B., Ally, A., Balasundaram, M., Birol, I., Bowlby, R., Brooks, D., Butterfield, Y. S., Carlsen, R., Chu, A., Chu, J., Chuah, E., Chun, H. E., Clarke, A., Dhalla, N., Guin, R., Holt, R. A., Jones, S. J., Kasaian, K., Lee, D., Li, H. A., Lim, E., Ma, Y., Marra, M. A., Mayo, M., Moore, R. A., Mungall, A. J., Mungall, K. L., Nip, K. M., Robertson, A. G., Schein, J. E., Sipahimalani, P., Tam, A., Thiessen, N., Beroukhim, R., Carter, S. L., Cherniack, A. D., Cho, J., Cibulskis, K., DiCara, D., Frazer, S., Fisher, S., Gabriel, S. B., Gehlenborg, N., Heiman, D. I., Jung, J., Kim, J., Lander, E. S., Lawrence, M. S., Lichtenstein, L., Lin, P., Meyerson, M., Ojesina, A. I., Pedamallu, C. S., Saksena, G., Schumacher, S. E., Sougnez, C., Stojanov, P., Tabak, B., Taylor-Weiner, A., Voet, D., Rosenberg, M., Zack, T. I., Zhang, H., Zou, L., Protopopov, A., Santoso, N., Parfenov, M., Lee, S., Zhang, J., Mahadeshwar, H. S., Tang, J., Ren, X., Seth, S., Yang, L., Xu, A. W., Song, X., Pantazi, A., Xi, R., Bristow, C. A., Hadjipanayis, A., Seidman, J., Chin, L., Park, P. J., Kucherlapati, R., Akbani, R., Ling, S., Liu, W., Rao, A., Weinstein, J. N., Kim, S., Lee, J., Lu, Y., Mills, G., Hinoue, T., Weisenberger, D. J., Bootwalla, M. S., Lai, P. H., Shen, H., Triche, T., Van den Berg, D. J., Baylin, S. B., Herman, J. G., Getz, G., Chin, L., Liu, Y., Murray, B. A., Noble, M. S., Askoy, B. A., Ciriello, G., Dresdner, G., Gao, J., Gross, B., Jacobsen, A., Lee, W., Ramirez, R., Sander, C., Schultz, N., Senbabaoglu, Y., Sinha, R., Sumer, S. O., Sun, Y., Weinhold, N., Thorsson, V., Bernard, B., Iype, L., Kramer, R. W., Kreisberg, R., Miller, M., Reynolds, S. M., Rovira, H., Tasman, N., Shmulevich, I., Ng, S., Haussler, D., Stuart, J. M., Akbani, R., Ling, S., Liu, W., Rao, A., Weinstein, J. N., Verhaak, R. G., Mills, G. B., Leiserson, M. D., Raphael, B. J., Wu, H., Taylor, B. S., Black, A. D., Bowen, J., Carney, J. A., Gastier-Foster, J. M., Helsel, C., Leraas, K. M., Lichtenberg, T. M., McAllister, C., Ramirez, N. C., Tabler, T. R., Wise, L., Zmuda, E., Penny, R., Crain, D., Gardner, J., Lau, K., Curely, E., Mallery, D., Morris, S., Paulauskis, J., Shelton, T., Shelton, C., Sherman, M., Benz, C., Lee, J., Fedosenko, K., Manikhas, G., Voronina, O., Belyaev, D., Dolzhansky, O., Rathmell, W. K., Brzezinski, J., Ibbs, M., Korski, K., Kycler, W., Lazniak, R., Leporowska, E., Mackiewicz, A., Murawa, D., Murawa, P., Spychala, A., Suchorska, W. M., Tatka, H., Teresiak, M., Wiznerowicz, M., Abdel-Misih, R., Bennett, J., Brown, J., Iacocca, M., Rabeno, B., Kwon, S., Penny, R., Gardner, J., Kemkes, A., Mallery, D., Morris, S., Shelton, T., Shelton, C., Curley, E., Alexopoulou, I., Engel, J., Bartlett, J., Albert, M., Park, D., Dhir, R., Luketich, J., Landreneau, R., Janjigian, Y. Y., Kelsen, D. P., Cho, E., Ladanyi, M., Tang, L., McCall, S. J., Park, Y. S., Cheong, J., Ajani, J., Camargo, M. C., Alonso, S., Ayala, B., Jensen, M. A., Pihl, T., Raman, R., Walton, J., Wan, Y., Demchok, J. A., Eley, G., Shaw, K. R., Sheth, M., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J. C., Davidsen, T., Hutter, C. M., Sofia, H. J., Burton, R., Chudamani, S., Liu, J. 2014; 513 (7517): 202-209

    Abstract

    Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein-Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also known as PD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies.

    View details for DOI 10.1038/nature13480

    View details for Web of Science ID 000341362800044

    View details for PubMedID 25079317

  • Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Sottoriva, A., Spiteri, I., Piccirillo, S. G., Touloumis, A., Collins, V. P., Marioni, J. C., Curtis, C., Watts, C., Tavare, S. 2013; 110 (10): 4009-4014

    Abstract

    Glioblastoma (GB) is the most common and aggressive primary brain malignancy, with poor prognosis and a lack of effective therapeutic options. Accumulating evidence suggests that intratumor heterogeneity likely is the key to understanding treatment failure. However, the extent of intratumor heterogeneity as a result of tumor evolution is still poorly understood. To address this, we developed a unique surgical multisampling scheme to collect spatially distinct tumor fragments from 11 GB patients. We present an integrated genomic analysis that uncovers extensive intratumor heterogeneity, with most patients displaying different GB subtypes within the same tumor. Moreover, we reconstructed the phylogeny of the fragments for each patient, identifying copy number alterations in EGFR and CDKN2A/B/p14ARF as early events, and aberrations in PDGFRA and PTEN as later events during cancer progression. We also characterized the clonal organization of each tumor fragment at the single-molecule level, detecting multiple coexisting cell lineages. Our results reveal the genome-wide architecture of intratumor variability in GB across multiple spatial scales and patient-specific patterns of cancer evolution, with consequences for treatment design.

    View details for DOI 10.1073/pnas.1219747110

    View details for Web of Science ID 000316377400072

    View details for PubMedID 23412337

  • Single-Molecule Genomic Data Delineate Patient-Specific Tumor Profiles and Cancer Stem Cell Organization CANCER RESEARCH Sottoriva, A., Spiteri, I., Shibata, D., Curtis, C., Tavare, S. 2013; 73 (1): 41-49

    Abstract

    Substantial evidence supports the concept that cancers are organized in a cellular hierarchy with cancer stem cells (CSC) at the apex. To date, the primary evidence for CSCs derives from transplantation assays, which have known limitations. In particular, they are unable to report on the fate of cells within the original human tumor. Because of the difficulty in measuring tumor characteristics in patients, cellular organization and other aspects of cancer dynamics have not been quantified directly, although they likely play a fundamental role in tumor progression and therapy response. As such, new approaches to study CSCs in patient-derived tumor specimens are needed. In this study, we exploited ultradeep single-molecule genomic data derived from multiple microdissected colorectal cancer glands per tumor, along with a novel quantitative approach to measure tumor characteristics, define patient-specific tumor profiles, and infer tumor ancestral trees. We show that each cancer is unique in terms of its cellular organization, molecular heterogeneity, time from malignant transformation, and rate of mutation and apoptosis. Importantly, we estimate CSC fractions between 0.5% and 4%, indicative of a hierarchical organization responsible for long-lived CSC lineages, with variable rates of symmetric cell division. We also observed extensive molecular heterogeneity, both between and within individual cancer glands, suggesting a complex hierarchy of mitotic clones. Our framework enables the measurement of clinically relevant patient-specific characteristics in vivo, providing insight into the cellular organization and dynamics of tumor growth, with implications for personalized patient care.

    View details for DOI 10.1158/0008-5472.CAN-12-2273

    View details for Web of Science ID 000313019800006

    View details for PubMedID 23090114

  • The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups NATURE Curtis, C., Shah, S. P., Chin, S., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., Yuan, Y., Graef, S., Ha, G., Haffari, G., Bashashati, A., Russell, R., McKinney, S., Langerod, A., Green, A., Provenzano, E., Wishart, G., Pinder, S., Watson, P., Markowetz, F., Murphy, L., Ellis, I., Purushotham, A., Borresen-Dale, A., Brenton, J. D., Tavare, S., Caldas, C., Aparicio, S. 2012; 486 (7403): 346-352

    Abstract

    The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

    View details for DOI 10.1038/nature10983

    View details for Web of Science ID 000305466800033

    View details for PubMedID 22522925

    View details for PubMedCentralID PMC3440846

  • Higher Absolute Lymphocyte Counts Predict Lower Mortality from Early-Stage Triple-Negative Breast Cancer. Clinical cancer research : an official journal of the American Association for Cancer Research Afghahi, A., Purington, N., Han, S. S., Desai, M., Pierson, E., Mathur, M. B., Seto, T., Thompson, C. A., Rigdon, J., Telli, M. L., Badve, S. S., Curtis, C., West, R. B., Horst, K., Gomez, S. L., Ford, J. M., Sledge, G. W., Kurian, A. W. 2018

    Abstract

    Tumor-infiltrating lymphocytes (TILs) in pre-treatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer-specific mortality (BCM) and overall mortality (OM) in TNBC.Data on treatments and diagnostic tests from electronic medical records of two healthcare systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM and OM. For a subgroup with TILs data available, we explored the relationship between TILs and peripheral lymphocyte counts.1,463 Stage I-III TNBC patients were diagnosed from 2000-2014; 1113 (76%) received neoadjuvant/adjuvant chemotherapy within one year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC <1.0 K/μL). On multivariable analysis, higher minimum ALC, but not absolute neutrophil count, predicted lower OM (hazard ratio [HR]: 0.23, 95% confidence interval [CI]: 0.16-0.35) and BCM (HR: 0.19, CI: 0.11-0.34). Five-year probability of BCM was 15% for patients who were ever lymphopenic versus 4% for those who were not. An exploratory analysis (N=70) showed a significant association between TILs and higher peripheral lymphocyte counts during neoadjuvant chemotherapy.Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment.

    View details for DOI 10.1158/1078-0432.CCR-17-1323

    View details for PubMedID 29581131

  • Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells CANCER RESEARCH Gendelman, R., Xing, H., Mirzoeva, O. K., Sarde, P., Curtis, C., Feiler, H. S., McDonagh, P., Gray, J. W., Khalil, I., Korn, W. M. 2017; 77 (7): 1575-1585

    Abstract

    Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575-85. ©2017 AACR.

    View details for DOI 10.1158/0008-5472.CAN-16-0512

    View details for Web of Science ID 000398262400006

    View details for PubMedID 28087598

  • Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity. Cell stem cell Yan, K. S., Gevaert, O., Zheng, G. X., Anchang, B., Probert, C. S., Larkin, K. A., Davies, P. S., Cheng, Z. F., Kaddis, J. S., Han, A., Roelf, K., Calderon, R. I., Cynn, E., Hu, X., Mandleywala, K., Wilhelmy, J., Grimes, S. M., Corney, D. C., Boutet, S. C., Terry, J. M., Belgrader, P., Ziraldo, S. B., Mikkelsen, T. S., Wang, F., von Furstenberg, R. J., Smith, N. R., Chandrakesan, P., May, R., Chrissy, M. A., Jain, R., Cartwright, C. A., Niland, J. C., Hong, Y. K., Carrington, J., Breault, D. T., Epstein, J., Houchen, C. W., Lynch, J. P., Martin, M. G., Plevritis, S. K., Curtis, C., Ji, H. P., Li, L., Henning, S. J., Wong, M. H., Kuo, C. J. 2017; 21 (1): 78–90.e6

    Abstract

    Several cell populations have been reported to possess intestinal stem cell (ISC) activity during homeostasis and injury-induced regeneration. Here, we explored inter-relationships between putative mouse ISC populations by comparative RNA-sequencing (RNA-seq). The transcriptomes of multiple cycling ISC populations closely resembled Lgr5+ISCs, the most well-defined ISC pool, but Bmi1-GFP+cells were distinct and enriched for enteroendocrine (EE) markers, including Prox1. Prox1-GFP+cells exhibited sustained clonogenic growth in vitro, and lineage-tracing of Prox1+cells revealed long-lived clones during homeostasis and after radiation-induced injury in vivo. Single-cell mRNA-seq revealed two subsets of Prox1-GFP+cells, one of which resembled mature EE cells while the other displayed low-level EE gene expression but co-expressed tuft cell markers, Lgr5 and Ascl2, reminiscent of label-retaining secretory progenitors. Our data suggest that the EE lineage, including mature EE cells, comprises a reservoir of homeostatic and injury-inducible ISCs, extending our understanding of cellular plasticity and stemness.

    View details for DOI 10.1016/j.stem.2017.06.014

    View details for PubMedID 28686870

    View details for PubMedCentralID PMC5642297

  • Early mutation bursts in colorectal tumors. PloS one Zhao, J., Salomon, M. P., Shibata, D., Curtis, C., Siegmund, K., Marjoram, P. 2017; 12 (3)

    Abstract

    Tumor growth is an evolutionary process involving accumulation of mutations, copy number alterations, and cancer stem cell (CSC) division and differentiation. As direct observation of this process is impossible, inference regarding when mutations occur and how stem cells divide is difficult. However, this ancestral information is encoded within the tumor itself, in the form of intratumoral heterogeneity of the tumor cell genomes. Here we present a framework that allows simulation of these processes and estimation of mutation rates at the various stages of tumor development and CSC division patterns for single-gland sequencing data from colorectal tumors. We parameterize the mutation rate and the CSC division pattern, and successfully retrieve their posterior distributions based on DNA sequence level data. Our approach exploits Approximate Bayesian Computation (ABC), a method that is becoming widely-used for problems of ancestral inference.

    View details for DOI 10.1371/journal.pone.0172516

    View details for PubMedID 28257429

    View details for PubMedCentralID PMC5336211

  • Inferring Tumor Phylogenies from Multi-region Sequencing. Cell systems Hu, Z., Curtis, C. 2016; 3 (1): 12-14

    Abstract

    A new computational method illuminates the heterogeneity and evolutionary histories of cells within a tumor.

    View details for DOI 10.1016/j.cels.2016.07.007

    View details for PubMedID 27467243

  • Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer BREAST CANCER RESEARCH Hu, Z., Mao, J., Curtis, C., Huang, G., Gu, S., Heiser, L., Lenburg, M. E., Korkola, J. E., Bayani, N., Samarajiwa, S., Seoane, J. A., Dane, M. A., Esch, A., Feiler, H. S., Wang, N. J., Hardwicke, M. A., Laquerre, S., Jackson, J., Wood, K. W., Weber, B., Spellman, P. T., Aparicio, S., Wooster, R., Caldas, C., Gray, J. W. 2016; 18
  • Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer. Breast cancer research Hu, Z., Mao, J., Curtis, C., Huang, G., Gu, S., Heiser, L., Lenburg, M. E., Korkola, J. E., Bayani, N., Samarajiwa, S., Seoane, J. A., A Dane, M., Esch, A., Feiler, H. S., Wang, N. J., Hardwicke, M. A., Laquerre, S., Jackson, J., W Wood, K., Weber, B., Spellman, P. T., Aparicio, S., Wooster, R., Caldas, C., Gray, J. W. 2016; 18 (1): 70-?

    Abstract

    High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

    View details for DOI 10.1186/s13058-016-0728-y

    View details for PubMedID 27368372

    View details for PubMedCentralID PMC4930593

  • Many private mutations originate from the first few divisions of a human colorectal adenoma JOURNAL OF PATHOLOGY Kang, H., Salomon, M. P., Sottoriva, A., Zhao, J., Toy, M., Press, M. F., Curtis, C., Marjoram, P., Siegmund, K., Shibata, D. 2015; 237 (3): 355-362

    View details for DOI 10.1002/path.4581

    View details for Web of Science ID 000363211000009

    View details for PubMedID 26119426

  • Genomic profiling of breast cancers. Current opinion in obstetrics & gynecology Curtis, C. 2015; 27 (1): 34-39

    Abstract

    To describe recent advances in the application of advanced genomic technologies towards the identification of biomarkers of prognosis and treatment response in breast cancer.Advances in high-throughput genomic profiling such as massively parallel sequencing have enabled researchers to catalogue the spectrum of somatic alterations in breast cancers. These tools also hold promise for precision medicine through accurate patient prognostication, stratification, and the dynamic monitoring of treatment response. For example, recent efforts have defined robust molecular subgroups of breast cancer and novel subtype-specific oncogenes. In addition, previously unappreciated activating mutations in human epidermal growth factor receptor 2 have been reported, suggesting new therapeutic opportunities. Genomic profiling of cell-free tumor DNA and circulating tumor cells has been used to monitor disease burden and the emergence of resistance, and such 'liquid biopsy' approaches may facilitate the early, noninvasive detection of aggressive disease. Finally, single-cell genomics is coming of age and will contribute to an understanding of breast cancer evolutionary dynamics.Here, we highlight recent studies that employ high-throughput genomic technologies in an effort to elucidate breast cancer biology, discover new therapeutic targets, improve prognostication and stratification, and discuss the implications for precision cancer medicine.

    View details for DOI 10.1097/GCO.0000000000000145

    View details for PubMedID 25502431

  • Contributions to Drug Resistance in Glioblastoma Derived from Malignant Cells in the Sub-Ependymal Zone CANCER RESEARCH Piccirillo, S. G., Spiteri, I., Sottoriva, A., Touloumis, A., Ber, S., Price, S. J., Heywood, R., Francis, N., Howarth, K. D., Collins, V. P., Venkitaraman, A. R., Curtis, C., Marioni, J. C., Tavare, S., Watts, C. 2015; 75 (1): 194-202

    Abstract

    Glioblastoma, the most common and aggressive adult brain tumor, is characterized by extreme phenotypic diversity and treatment failure. Through fluorescence-guided resection, we identified fluorescent tissue in the sub-ependymal zone (SEZ) of patients with glioblastoma. Histologic analysis and genomic characterization revealed that the SEZ harbors malignant cells with tumor-initiating capacity, analogous to cells isolated from the fluorescent tumor mass (T). We observed resistance to supramaximal chemotherapy doses along with differential patterns of drug response between T and SEZ in the same tumor. Our results reveal novel insights into glioblastoma growth dynamics, with implications for understanding and limiting treatment resistance. Cancer Res; 75(1); 194-202. ©2014 AACR.

    View details for DOI 10.1158/0008-5472.CAN-13-3131

    View details for Web of Science ID 000347383000020

    View details for PubMedID 25406193

    View details for PubMedCentralID PMC4286248

  • The Breast Cancer Oncogene EMSY Represses Transcription of Antimetastatic microRNA miR-31 (vol 53, pg 806, 2014) MOLECULAR CELL Vire, E., Curtis, C., Davalos, V., Git, A., Robson, S., Villanueva, A., Vidal, A., Barbieri, I., Aparicio, S., Esteller, M., Caldas, C., Kouzarides, T. 2014; 54 (1): 203-203
  • Genome-driven integrated classification of breast cancer validated in over 7,500 samples Genome Biology Ali, R., Rueda, O. M., Chin, S., Curtis, C., Dunning, M. J., Aparicio, S., Caldas, C. 2014; 15 (8): 431
  • A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer. Molecular oncology Vollan, H. K., Rueda, O. M., Chin, S. F., Curtis, C., Turashvili, G., Shah, S., Lingjærde, O. C., Yuan, Y., Ng, C. K., Dunning, M. J., Dicks, E., Provenzano, E., Sammut, S., McKinney, S., Ellis, I. O., Pinder, S., Purushotham, A., Murphy, L. C., Kristensen, V. N., Brenton, J. D., Pharoah, P. D., Børresen-Dale, A. L., Aparicio, S., Caldas, C. 2014

    Abstract

    Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.

    View details for DOI 10.1016/j.molonc.2014.07.019

    View details for PubMedID 25169931

  • Precise inference of copy number alterations in tumor samples from SNP arrays BIOINFORMATICS Chen, G. K., Chang, X., Curtis, C., Wang, K. 2013; 29 (23): 2964-2970

    Abstract

    The accurate detection of copy number alterations (CNAs) in human genomes is important for understanding susceptibility to cancer and mechanisms of tumor progression. CNA detection in tumors from single nucleotide polymorphism (SNP) genotyping arrays is a challenging problem due to phenomena such as aneuploidy, stromal contamination, genomic waves and intra-tumor heterogeneity, issues that leading methods do not optimally address.Here we introduce methods and software (PennCNV-tumor) for fast and accurate CNA detection using signal intensity data from SNP genotyping arrays. We estimate stromal contamination by applying a maximum likelihood approach over multiple discrete genomic intervals. By conditioning on signal intensity across the genome, our method accounts for both aneuploidy and genomic waves. Finally, our method uses a hidden Markov model to integrate multiple sources of information, including total and allele-specific signal intensity at each SNP, as well as physical maps to make posterior inferences of CNAs. Using real data from cancer cell-lines and patient tumors, we demonstrate substantial improvements in accuracy and computational efficiency compared with existing methods.

    View details for DOI 10.1093/bioinformatics/btt521

    View details for Web of Science ID 000327508300002

    View details for PubMedID 24021380

  • The shaping and functional consequences of the microRNA landscape in breast cancer NATURE Dvinge, H., Git, A., Graef, S., Salmon-Divon, M., Curtis, C., Sottoriva, A., Zhao, Y., Hirst, M., Armisen, J., Miska, E. A., Chin, S., Provenzano, E., Turashvili, G., Green, A., Ellis, I., Aparicio, S., Caldas, C. 2013; 497 (7449): 378-382

    Abstract

    MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer.

    View details for DOI 10.1038/nature12108

    View details for Web of Science ID 000318952000040

    View details for PubMedID 23644459

  • Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling PLOS COMPUTATIONAL BIOLOGY Bilal, E., Dutkowski, J., Guinney, J., Jang, I. S., Logsdon, B. A., Pandey, G., Sauerwine, B. A., Shimoni, Y., Vollan, H. K., Mecham, B. H., Rueda, O. M., Tost, J., Curtis, C., Alvarez, M. J., Kristensen, V. N., Aparicio, S., Borresen-Dale, A., Caldas, C., Califano, A., Friend, S. H., Ideker, T., Schadt, E. E., Stolovitzky, G. A., Margolin, A. A. 2013; 9 (5)

    Abstract

    Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

    View details for DOI 10.1371/journal.pcbi.1003047

    View details for Web of Science ID 000320032100009

    View details for PubMedID 23671412

  • Systematic Analysis of Challenge-Driven Improvements in Molecular Prognostic Models for Breast Cancer SCIENCE TRANSLATIONAL MEDICINE Margolin, A. A., Bilal, E., Huang, E., Norman, T. C., Ottestad, L., Mecham, B. H., Sauerwine, B., Kellen, M. R., Mangravite, L. M., Furia, M. D., Vollan, H. K., Rueda, O. M., Guinney, J., Deflaux, N. A., Hoff, B., Schildwachter, X., Russnes, H. G., Park, D., Vang, V. O., Pirtle, T., Youseff, L., Citro, C., Curtis, C., Kristensen, V. N., Hellerstein, J., Friend, S. H., Stolovitzky, G., Aparicio, S., Caldas, C., Borresen-Dale, A. 2013; 5 (181)

    Abstract

    Although molecular prognostics in breast cancer are among the most successful examples of translating genomic analysis to clinical applications, optimal approaches to breast cancer clinical risk prediction remain controversial. The Sage Bionetworks-DREAM Breast Cancer Prognosis Challenge (BCC) is a crowdsourced research study for breast cancer prognostic modeling using genome-scale data. The BCC provided a community of data analysts with a common platform for data access and blinded evaluation of model accuracy in predicting breast cancer survival on the basis of gene expression data, copy number data, and clinical covariates. This approach offered the opportunity to assess whether a crowdsourced community Challenge would generate models of breast cancer prognosis commensurate with or exceeding current best-in-class approaches. The BCC comprised multiple rounds of blinded evaluations on held-out portions of data on 1981 patients, resulting in more than 1400 models submitted as open source code. Participants then retrained their models on the full data set of 1981 samples and submitted up to five models for validation in a newly generated data set of 184 breast cancer patients. Analysis of the BCC results suggests that the best-performing modeling strategy outperformed previously reported methods in blinded evaluations; model performance was consistent across several independent evaluations; and aggregating community-developed models achieved performance on par with the best-performing individual models.

    View details for DOI 10.1126/scitranslmed.3006112

    View details for Web of Science ID 000317720300005

    View details for PubMedID 23596205

  • Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling (vol 4, 161er6, 2012) SCIENCE TRANSLATIONAL MEDICINE Yuan, Y., Failmezger, H., Rueda, O. M., Ali, H. R., Graef, S., Chin, S., SCHWARZ, R. F., Curtis, C., DUNNING, M. J., Bardwell, H., Johnson, N., Doyle, S., Turashvili, G., Provenzano, E., Aparicio, S., Caldas, C., Markowetz, F. 2012; 4 (161)
  • Calling Sample Mix-Ups in Cancer Population Studies PLOS ONE Lynch, A. G., Chin, S., Dunning, M. J., Caldas, C., Tavare, S., Curtis, C. 2012; 7 (8)

    Abstract

    Sample tracking errors have been and always will be a part of the practical implementation of large experiments. It has recently been proposed that expression quantitative trait loci (eQTLs) and their associated effects could be used to identify sample mix-ups and this approach has been applied to a number of large population genomics studies to illustrate the prevalence of the problem. We had adopted a similar approach, termed 'BADGER', in the METABRIC project. METABRIC is a large breast cancer study that may have been the first in which eQTL-based detection of mismatches was used during the study, rather than after the event, to aid quality assurance. We report here on the particular issues associated with large cancer studies performed using historical samples, which complicate the interpretation of such approaches. In particular we identify the complications of using tumour samples, of considering cellularity and RNA quality, of distinct subgroups existing in the study population (including family structures), and of choosing eQTLs to use. We also present some results regarding the design of experiments given consideration of these matters. The eQTL-based approach to identifying sample tracking errors is seen to be of value to these studies, but requiring care in its implementation.

    View details for DOI 10.1371/journal.pone.0041815

    View details for Web of Science ID 000307378500009

    View details for PubMedID 22912679

    View details for PubMedCentralID PMC3415393

  • A Sparse Regulatory Network of Copy-Number Driven Gene Expression Reveals Putative Breast Cancer Oncogenes IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS Yuan, Y., Curtis, C., Caldas, C., Markowetz, F. 2012; 9 (4): 947-954

    Abstract

    Copy number aberrations are recognized to be important in cancer as they may localize to regions harboring oncogenes or tumor suppressors. Such genomic alterations mediate phenotypic changes through their impact on expression. Both cis- and transacting alterations are important since they may help to elucidate putative cancer genes. However, amidst numerous passenger genes, trans-effects are less well studied due to the computational difficulty in detecting weak and sparse signals in the data, and yet may influence multiple genes on a global scale. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream transcriptional targets in breast cancer. With respect to goodness of fit on both simulated and real data, the performance of sparse network inference is no worse than other state-of-the-art models but with the advantage of simultaneous feature selection and efficiency. The DNA-RNA interaction network helps to distinguish copy-number driven expression alterations from those that are copy-number independent. Further, our approach yields a quantitative copy-number dependency score, which distinguishes cis- versus trans-effects. When applied to a breast cancer data set, numerous expression profiles were impacted by cis-acting copy-number alterations, including several known oncogenes such as GRB7, ERBB2, and LSM1. Several trans-acting alterations were also identified, impacting genes such as ADAM2 and BAGE, which warrant further investigation.An R package named lol is available from www.markowetzlab.org/software/lol.html.

    View details for DOI 10.1109/TCBB.2011.105

    View details for Web of Science ID 000304147000002

    View details for PubMedID 21788678

  • The clonal and mutational evolution spectrum of primary triple-negative breast cancers NATURE Shah, S. P., Roth, A., Goya, R., Oloumi, A., Ha, G., Zhao, Y., Turashvili, G., Ding, J., Tse, K., Haffari, G., Bashashati, A., Prentice, L. M., Khattra, J., Burleigh, A., Yap, D., Bernard, V., McPherson, A., Shumansky, K., Crisan, A., Giuliany, R., Heravi-Moussavi, A., Rosner, J., Lai, D., Birol, I., Varhol, R., Tam, A., Dhalla, N., Zeng, T., Ma, K., Chan, S. K., Griffith, M., Moradian, A., Cheng, S. G., Morin, G. B., Watson, P., Gelmon, K., Chia, S., Chin, S., Curtis, C., Rueda, O. M., Pharoah, P. D., Damaraju, S., Mackey, J., Hoon, K., Harkins, T., Tadigotla, V., Sigaroudinia, M., Gascard, P., Tlsty, T., Costello, J. F., Meyer, I. M., Eaves, C. J., Wasserman, W. W., Jones, S., Huntsman, D., Hirst, M., Caldas, C., Marra, M. A., Aparicio, S. 2012; 486 (7403): 395-399

    Abstract

    Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.

    View details for DOI 10.1038/nature10933

    View details for Web of Science ID 000305466800042

    View details for PubMedID 22495314

  • Effects of BRCA2 cis-regulation in normal breast and cancer risk amongst BRCA2 mutation carriers BREAST CANCER RESEARCH Maia, A., Antoniou, A. C., O'Reilly, M., Samarajiwa, S., Dunning, M., Kartsonaki, C., Chin, S., Curtis, C. N., McGuffog, L., Domchek, S. M., Easton, D. F., Peock, S., Frost, D., Evans, D. G., Eeles, R., Izatt, L., Adlard, J., Eccles, D., Sinilnikova, O. M., Mazoyer, S., Stoppa-Lyonnet, D., Gauthier-Villars, M., Faivre, L., Venat-Bouvet, L., Delnatte, C., Nevanlinna, H., Couch, F. J., Godwin, A. K., Caligo, M. A., Barkardottir, R. B., Chen, X., Beesley, J., Healey, S., Caldas, C., Chenevix-Trench, G., Ponder, B. A. 2012; 14 (2)

    Abstract

    Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism.We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analyzed in vitro and in vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2,754 carriers.We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterized three cis-regulatory SNPs located at the promoter and two intronic regulatory elements which affect the binding of the transcription factors C/EBPα, HMGA1, D-binding protein (DBP) and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele hazard ratio (HR) = 0.85, 95% confidence interval (CI) = 0.72 to 1.00, P-trend = 0.048).Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2 which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele.

    View details for DOI 10.1186/bcr3169

    View details for Web of Science ID 000304771800038

    View details for PubMedID 22513257

  • Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer BIOINFORMATICS Yuan, Y., Rueda, O. M., Curtis, C., Markowetz, F. 2011; 27 (19): 2679-2685

    Abstract

    Copy number alterations (CNAs) associated with cancer are known to contribute to genomic instability and gene deregulation. Integrating CNAs with gene expression helps to elucidate the mechanisms by which CNAs act and to identify the transcriptional downstream targets of CNAs. Such analyses can help to sort functional driver events from the many accompanying passenger alterations. However, the way CNAs affect gene expression can vary in different cellular contexts, for example between different subtypes of the same cancer. Thus, it is important to develop computational approaches capable of inferring differential connectivity of regulatory networks in different cellular contexts.We propose a statistical deregulation model that integrates copy number and expression data of different disease subtypes to jointly model common and differential regulatory relationships. Our model not only identifies CNAs driving gene expression changes, but at the same time also predicts differences in regulation that distinguish one cancer subtype from the other. We implement our model in a penalized regression framework and demonstrate in a simulation study the feasibility and accuracy of our approach. Subsequently, we show that this model can identify both known and novel aspects of cross-talk between the ER and NOTCH pathways in ER-negative-specific deregulations, when compared with ER-positive breast cancer. This flexible model can be applied on other modalities such as methylation or microRNA and expression to disentangle cancer signaling pathways.The Bioconductor-compliant R package DANCE is available from www.markowetzlab.org/software/yinyin.yuan@cancer.org.uk; florian.markowetz@cancer.org.uk.

    View details for DOI 10.1093/bioinformatics/btr450

    View details for Web of Science ID 000295412200009

    View details for PubMedID 21804112

  • ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium EMBO MOLECULAR MEDICINE Holland, D. G., Burleigh, A., Git, A., Goldgraben, M. A., Perez-Mancera, P. A., Chin, S., Hurtado, A., Bruna, A., Ali, H. R., Greenwood, W., Dunning, M. J., Samarajiwa, S., Menon, S., Rueda, O. M., Lynch, A. G., McKinney, S., Ellis, I. O., Eaves, C. J., Carroll, J. S., Curtis, C., Aparicio, S., Caldas, C. 2011; 3 (3): 167-180

    Abstract

    The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGFβ on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.

    View details for DOI 10.1002/emmm.201100122

    View details for Web of Science ID 000288727200006

    View details for PubMedID 21337521

  • The importance of platform annotation in interpreting microarray data LANCET ONCOLOGY Dunning, M. J., Curtis, C., Barbosa-Morais, N. L., Caldas, C., Tavare, S., Lynch, A. G. 2010; 11 (8): 717-717

    View details for Web of Science ID 000281009500013

    View details for PubMedID 20688273

  • The pitfalls of platform comparison: DNA copy number array technologies assessed BMC GENOMICS Curtis, C., Lynch, A. G., Dunning, M. J., Spiteri, I., Marioni, J. C., Hadfield, J., Chin, S., Brenton, J. D., Tavare, S., Caldas, C. 2009; 10

    Abstract

    The accurate and high resolution mapping of DNA copy number aberrations has become an important tool by which to gain insight into the mechanisms of tumourigenesis. There are various commercially available platforms for such studies, but there remains no general consensus as to the optimal platform. There have been several previous platform comparison studies, but they have either described older technologies, used less-complex samples, or have not addressed the issue of the inherent biases in such comparisons. Here we describe a systematic comparison of data from four leading microarray technologies (the Affymetrix Genome-wide SNP 5.0 array, Agilent High-Density CGH Human 244A array, Illumina HumanCNV370-Duo DNA Analysis BeadChip, and the Nimblegen 385 K oligonucleotide array). We compare samples derived from primary breast tumours and their corresponding matched normals, well-established cancer cell lines, and HapMap individuals. By careful consideration and avoidance of potential sources of bias, we aim to provide a fair assessment of platform performance.By performing a theoretical assessment of the reproducibility, noise, and sensitivity of each platform, notable differences were revealed. Nimblegen exhibited between-replicate array variances an order of magnitude greater than the other three platforms, with Agilent slightly outperforming the others, and a comparison of self-self hybridizations revealed similar patterns. An assessment of the single probe power revealed that Agilent exhibits the highest sensitivity. Additionally, we performed an in-depth visual assessment of the ability of each platform to detect aberrations of varying sizes. As expected, all platforms were able to identify large aberrations in a robust manner. However, some focal amplifications and deletions were only detected in a subset of the platforms.Although there are substantial differences in the design, density, and number of replicate probes, the comparison indicates a generally high level of concordance between platforms, despite differences in the reproducibility, noise, and sensitivity. In general, Agilent tended to be the best aCGH platform and Affymetrix, the superior SNP-CGH platform, but for specific decisions the results described herein provide a guide for platform selection and study design, and the dataset a resource for more tailored comparisons.

    View details for DOI 10.1186/1471-2164-10-588

    View details for Web of Science ID 000273075400002

    View details for PubMedID 19995423

  • Drosophila melanogaster p53 has developmental stage-specific and sex-specific effects on adult life span indicative of sexual antagonistic pleiotropy AGING-US Waskar, M., Landis, G. N., Shen, J., Curtis, C., Tozer, K., Abdueva, D., Skvortsov, D., Tavare, S., Tower, J. 2009; 1 (11): 903-936

    Abstract

    Truncated and mutant forms ofp53 affect life span in Drosophila, nematodes and mice, however the role of wild-type p53 in aging remains unclear. Here conditional over-expression of both wild-type and mutant p53 transgenes indicated that, in adult flies, p53 limits life span in females but favors life span in males. In contrast, during larval development, moderate over-expression of p53 produced both male and female adults with increased life span. Mutations of the endogenous p53 gene also had sex-specific effects on life span under control and stress conditions: null mutation of p53 increased life span in females, and had smaller, more variable effects in males. These developmental stage-specific and sex-specific effects of p53 on adult life span are consistent with a sexual antagonistic pleiotropy model.

    View details for Web of Science ID 000276402700004

    View details for PubMedID 20157574

  • Swift: primary data analysis for the Illumina Solexa sequencing platform BIOINFORMATICS Whiteford, N., Skelly, T., Curtis, C., Ritchie, M. E., Loehr, A., Zaranek, A. W., Abnizova, I., Brown, C. 2009; 25 (17): 2194-2199

    Abstract

    Primary data analysis methods are of critical importance in second generation DNA sequencing. Improved methods have the potential to increase yield and reduce the error rates. Openly documented analysis tools enable the user to understand the primary data, this is important for the optimization and validity of their scientific work.In this article, we describe Swift, a new tool for performing primary data analysis on the Illumina Solexa Sequencing Platform. Swift is the first tool, outside of the vendors own software, which completes the full analysis process, from raw images through to base calls. As such it provides an alternative to, and independent validation of, the vendor supplied tool. Our results show that Swift is able to increase yield by 13.8%, at comparable error rate.

    View details for DOI 10.1093/bioinformatics/btp383

    View details for Web of Science ID 000269196000008

    View details for PubMedID 19549630

  • Product Length, Dye Choice, and Detection Chemistry in the Bead-Emulsion Amplification of Millions of Single DNA Molecules in Parallel ANALYTICAL CHEMISTRY Tiemann-Boege, I., Curtis, C., Shinde, D. N., Goodman, D. B., Tavare, S., Arnheim, N. 2009; 81 (14): 5770-5776

    Abstract

    The amplification of millions of single molecules in parallel can be performed on microscopic magnetic beads that are contained in aqueous compartments of an oil-buffer emulsion. These bead-emulsion amplification (BEA) reactions result in beads that are covered by almost-identical copies derived from a single template. The post-amplification analysis is performed using different fluorophore-labeled probes. We have identified BEA reaction conditions that efficiently produce longer amplicons of up to 450 base pairs. These conditions include the use of a Titanium Taq amplification system. Second, we explored alternate fluorophores coupled to probes for post-PCR DNA analysis. We demonstrate that four different Alexa fluorophores can be used simultaneously with extremely low crosstalk. Finally, we developed an allele-specific extension chemistry that is based on Alexa dyes to query individual nucleotides of the amplified material that is both highly efficient and specific.

    View details for DOI 10.1021/ac900633y

    View details for Web of Science ID 000268135000025

    View details for PubMedID 19601653

  • A screen of apoptosis and senescence regulatory genes for life span effects when over-expressed in Drosophila AGING-US Shen, J., Curtis, C., Tavare, S., Tower, J. 2009; 1 (2): 191-211

    Abstract

    Conditional expression of transgenes in Drosophila was produced using the Geneswitch system, wherein feeding the drug RU486/Mifepristone activates the artificial transcription factor Geneswitch. Geneswitch was expressed using the Actin5C promoter and this was found to yield conditional, tissue-general expression of a target transgene (UAS-GFP) in both larvae and adult flies. Nervous system-specific (Elav-GS) and fat body-specific Geneswitch drivers were also characterized using UAS-GFP. Fourteen genes implicated in growth, apoptosis and senescence regulatory pathways were over-expressed in adult flies or during larval development, and assayed for effects on adult fly life span. Over-expression of a dominant p53 allele (p53-259H) in adult flies using the ubiquitous driver produced increased life span in females but not males, consistent with previous studies. Both wingless and Ras activated form transgenes were lethal when expressed in larvae, and reduced life span when expressed in adults, consistent with results from other model systems indicating that the wingless and Ras pathways can promote senescence. Over-expression of the caspase inhibitor baculovirus p35 during larval development reduced the mean life span of male and female adults, and also produced a subset of females with increased life span. These experiments suggest that baculovirus p35 and the wingless and Ras pathways can have sex-specific and developmental stage-specific effects on adult Drosophila life span, and these reagents should be useful for the further analysis of the role of these conserved pathways in aging.

    View details for Web of Science ID 000276400900005

    View details for PubMedID 20157509

  • Explaining differences in saturation levels for Affymetrix GeneChip (R) arrays NUCLEIC ACIDS RESEARCH Skvortsov, D., Abdueva, D., Curtis, C., Schaub, B., Tavare, S. 2007; 35 (12): 4154-4163

    Abstract

    The experimental spike-in studies of microarray hybridization conducted by Affymetrix demonstrate a nonlinear response of fluorescence intensity signal to target concentration. Several theoretical models have been put forward to explain these data. It was shown that the Langmuir adsorption isotherm recapitulates a general trend of signal response to concentration. However, this model fails to explain some key properties of the observed signal. In particular, according to the simple Langmuir isotherm, all probes should saturate at the same intensity level. However, this effect was not observed in the publicly available Affymetrix spike-in data sets. On the contrary, it was found that the saturation intensities vary greatly and can be predicted based on the probe sequence composition. In our experimental study, we attempt to account for the unexplained variation in the observed probe intensities using customized fluidics scripts. We explore experimentally the effect of the stringent wash, target concentration and hybridization time on the final microarray signal. The washing effect is assessed by scanning chips both prior to and after the stringent wash. Selective labeling of both specific and non-specific targets allows the visualization and investigation of the washing effect for both specific and non-specific signal components. We propose a new qualitative model of the probe-target hybridization mechanism that is in agreement with observed hybridization and washing properties of short oligonucleotide microarrays. This study demonstrates that desorption of incompletely bound targets during the washing cycle contributes to the observed difference in saturation levels.

    View details for DOI 10.1093/nar/gkm348

    View details for Web of Science ID 000247817700026

    View details for PubMedID 17567617

  • Transcriptional profiling of MnSOD-mediated lifespan extension in Drosophila reveals a species-general network of aging and metabolic genes GENOME BIOLOGY Curtis, C., Landis, G. N., Folk, D., Wehr, N. B., Hoe, N., Waskar, M., Abdueva, D., Skvortsov, D., Ford, D., Luu, A., Badrinath, A., Levine, R. L., Bradley, T. J., Tavare, S., Tower, J. 2007; 8 (12)

    Abstract

    Several interventions increase lifespan in model organisms, including reduced insulin/insulin-like growth factor-like signaling (IIS), FOXO transcription factor activation, dietary restriction, and superoxide dismutase (SOD) over-expression. One question is whether these manipulations function through different mechanisms, or whether they intersect on common processes affecting aging.A doxycycline-regulated system was used to over-express manganese-SOD (MnSOD) in adult Drosophila, yielding increases in mean and maximal lifespan of 20%. Increased lifespan resulted from lowered initial mortality rate and required MnSOD over-expression in the adult. Transcriptional profiling indicated that the expression of specific genes was altered by MnSOD in a manner opposite to their pattern during normal aging, revealing a set of candidate biomarkers of aging enriched for carbohydrate metabolism and electron transport genes and suggesting a true delay in physiological aging, rather than a novel phenotype. Strikingly, cross-dataset comparisons indicated that the pattern of gene expression caused by MnSOD was similar to that observed in long-lived Caenorhabditis elegans insulin-like signaling mutants and to the xenobiotic stress response, thus exposing potential conserved longevity promoting genes and implicating detoxification in Drosophila longevity.The data suggest that MnSOD up-regulation and a retrograde signal of reactive oxygen species from the mitochondria normally function as an intermediate step in the extension of lifespan caused by reduced insulin-like signaling in various species. The results implicate a species-conserved net of coordinated genes that affect the rate of senescence by modulating energetic efficiency, purine biosynthesis, apoptotic pathways, endocrine signals, and the detoxification and excretion of metabolites.

    View details for DOI 10.1186/gb-2007-8-12-r262

    View details for Web of Science ID 000253451800010

    View details for PubMedID 18067683

  • Scambio, a novel guanine nucleotide exchange factor for Rho MOLECULAR CANCER Curtis, C., Hemmeryckx, B., Haataja, L., Senadheera, D., Groffen, J., Heisterkamp, N. 2004; 3