A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers

Raw Text

Published: 20 August 2006

Scott L Carter 1 ,

Aron C Eklund 1 , 2 ,

Isaac S Kohane 1 ,

Lyndsay N Harris 3 &

…

Zoltan Szallasi 1 , 4

Show authors

Nature Genetics volume  38 ,  pages 1043–1048 ( 2006 ) Cite this article

15k Accesses

829 Citations

73 Altmetric

Metrics details

Abstract

We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Disentangling the roles of aneuploidy, chromosomal instability and tumour heterogeneity in developing resistance to cancer therapies Joana Reis Andrade , Annie Dinky Gallagher  …  Sarah Elizabeth McClelland Chromosome Research Open Access 18 September 2023

Osimertinib induces paraptosis and TRIP13 confers resistance in glioblastoma cells Lulu Hu , Ji Shi  …  Haozhe Piao Cell Death Discovery Open Access 05 September 2023

Chromosomal instability and inflammation: a catch-22 for cancer cells Anouk van den Brink , Maria F. Suarez Peredo Rodriguez  &  Floris Foijer Chromosome Research Open Access 10 August 2023

Access options

Access through your institution

Change institution

Buy or subscribe

Subscribe to this journal

Receive 12 print issues and online access

$209.00 per year

only $17.42 per issue

Learn more

Rent or buy this article

Prices vary by article type

from $1.95

to $39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Additional access options:

Log in

Learn about institutional subscriptions

Read our FAQs

Contact customer support

References

Sotiriou, C. et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J. Natl. Cancer Inst. 98 , 262–272 (2006). Article   CAS   Google Scholar

van de Vijver, M.J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347 , 1999–2009 (2002). Article   CAS   Google Scholar

van't Veer, L.J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415 , 530–536 (2002). Article   CAS   Google Scholar

Wang, Y. et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365 , 671–679 (2005). Article   CAS   Google Scholar

Bild, A.H. et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439 , 353–357 (2006). Article   CAS   Google Scholar

Bhattacharjee, A. et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl. Acad. Sci. USA 98 , 13790–13795 (2001). Article   CAS   Google Scholar

Phillips, H.S. et al. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 9 , 157–173 (2006). Article   CAS   Google Scholar

Lopez-Rios, F. et al. Global gene expression profiling of pleural mesotheliomas: overexpression of aurora kinases and P16/CDKN2A deletion as prognostic factors and critical evaluation of microarray-based prognostic prediction. Cancer Res. 66 , 2970–2979 (2006). Article   CAS   Google Scholar

Freije, W.A. et al. Gene expression profiling of gliomas strongly predicts survival. Cancer Res. 64 , 6503–6510 (2004). Article   CAS   Google Scholar

Pomeroy, S.L. et al. Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 415 , 436–442 (2002). Article   CAS   Google Scholar

Shipp, M.A. et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat. Med. 8 , 68–74 (2002). Article   CAS   Google Scholar

Nutt, C.L. et al. Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res. 63 , 1602–1607 (2003). CAS   PubMed   Google Scholar

Lengauer, C., Kinzler, K.W. & Vogelstein, B. Genetic instabilities in human cancers. Nature 396 , 643–649 (1998). Article   CAS   Google Scholar

Gollin, S.M. Mechanisms leading to chromosomal instability. Semin. Cancer Biol. 15 , 33–42 (2005). Article   CAS   Google Scholar

Draviam, V.M., Xie, S. & Sorger, P.K. Chromosome segregation and genomic stability. Curr. Opin. Genet. Dev. 14 , 120–125 (2004). Article   CAS   Google Scholar

Diaz, L.A., Jr. The current clinical value of genomic instability. Semin. Cancer Biol. 15 , 67–71 (2005). Article   CAS   Google Scholar

Pollack, J.R. et al. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc. Natl. Acad. Sci. USA 99 , 12963–12968 (2002). Article   CAS   Google Scholar

Tonon, G. et al. High-resolution genomic profiles of human lung cancer. Proc. Natl. Acad. Sci. USA 102 , 9625–9630 (2005). Article   CAS   Google Scholar

Garraway, L.A. et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436 , 117–122 (2005). Article   CAS   Google Scholar

Roschke, A.V. et al. Karyotypic complexity of the NCI-60 drug-screening panel. Cancer Res. 63 , 8634–8647 (2003). CAS   PubMed   Google Scholar

Heidebrecht, H.J. et al. Repp86: a human protein associated in the progression of mitosis. Mol. Cancer Res. 1 , 271–279 (2003). CAS   PubMed   Google Scholar

Kurasawa, Y., Earnshaw, W.C., Mochizuki, Y., Dohmae, N. & Todokoro, K. Essential roles of KIF4 and its binding partner PRC1 in organized central spindle midzone formation. EMBO J. 23 , 3237–3248 (2004). Article   CAS   Google Scholar

Mollinari, C. et al. PRC1 is a microtubule binding and bundling protein essential to maintain the mitotic spindle midzone. J. Cell Biol. 157 , 1175–1186 (2002). Article   CAS   Google Scholar

Costa, R.H. FoxM1 dances with mitosis. Nat. Cell Biol. 7 , 108–110 (2005). Article   CAS   Google Scholar

Wonsey, D.R. & Follettie, M.T. Loss of the forkhead transcription factor FoxM1 causes centrosome amplification and mitotic catastrophe. Cancer Res. 65 , 5181–5189 (2005). Article   CAS   Google Scholar

Ramaswamy, S., Ross, K.N., Lander, E.S. & Golub, T.R. A molecular signature of metastasis in primary solid tumors. Nat. Genet. 33 , 49–54 (2003). Article   CAS   Google Scholar

Whitfield, M.L. et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol. Biol. Cell 13 , 1977–2000 (2002). Article   CAS   Google Scholar

Gorgoulis, V.G. et al. Activation of the DNA damage checkpoint and genomic instability in human precancerous lesions. Nature 434 , 907–913 (2005). Article   CAS   Google Scholar

Whitfield, M.L., George, L.K., Grant, G.D. & Perou, C.M. Common markers of proliferation. Nat. Rev. Cancer 6 , 99–106 (2006). Article   CAS   Google Scholar

Download references

Acknowledgements

We thank A. Amon, D. Botstein, M. Meyerson and T. Ried for helpful suggestions, and Novartis for the NCI60 expression data. This work was supported in part by the US National Institutes of Health through grant 1PO1CA-092644-01 and the Department of Defense through grant W81XWH-04-1-0549. I.S.K. was supported in part by National Institutes of Health National Center for Biomedical Computing grant 5U54LM008748-02.

Author information

Authors and Affiliations

Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology (CHIP@HST), Harvard Medical School, Boston, 02115, Massachusetts, USA Scott L Carter, Aron C Eklund, Isaac S Kohane & Zoltan Szallasi

Laboratory of Functional Genomics, Brigham and Women's Hospital, Cambridge, 02139, Massachusetts, USA Aron C Eklund

Breast Disease Unit, Yale School of Medicine, New Haven, 06520-8032, Connecticut, USA Lyndsay N Harris

Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, DK-2800, Denmark Zoltan Szallasi

Authors

Scott L Carter View author publications You can also search for this author in PubMed   Google Scholar

Aron C Eklund View author publications You can also search for this author in PubMed   Google Scholar

Isaac S Kohane View author publications You can also search for this author in PubMed   Google Scholar

Lyndsay N Harris View author publications You can also search for this author in PubMed   Google Scholar

Zoltan Szallasi View author publications You can also search for this author in PubMed   Google Scholar

Contributions

S.L.C. and Z.S. conceived of and designed the study. S.L.C. carried out all the analysis. S.L.C. and Z.S. wrote the manuscript. A.C.E., I.S.K. and L.N.H. provided guidance and participated in the preparation of the manuscript.

Corresponding author

Correspondence to Zoltan Szallasi .

Ethics declarations

Competing interests

S.L.C., A.C.E. and Z.S. have applied for a patent on the diagnostic use of the chromosomal instability signature described in the manuscript.

Supplementary information

Supplementary Fig. 1

Relationship between functional aneuploidy and DNA-based measures of chromosomal abberations. (PDF 218 kb)

Supplementary Fig. 2

Total functional aneuploidy (tFA) is a significant predictor of clinical outcome in the four breast, lung and brain cancer data sets of 18 data sets evaluated. (PDF 48 kb)

Supplementary Fig. 3

Correlation between gene expression profiles and tFA is conserved in diverse human cancer data sets. (PDF 192 kb)

Supplementary Fig. 4

The CIN signature does not generate significant predictions of clinical outcome for 6 of 18 data sets evaluated. (PDF 47 kb)

Supplementary Fig. 5

The prognostic ability of cell cycle–regulated genes is dependent on CIN score. (PDF 130 kb)

Supplementary Fig. 6

Multivariate analysis of the CIN25 and proliferation signatures revealed that CIN25 was generally more relevant for risk stratification of cancer cohorts. (PDF 27 kb)

Supplementary Fig. 7

Removal of proliferation-associated genes from the CIN signature does not impair its predictive ability for clinical outcome. (PDF 591 kb)

Supplementary Table 1

Top 70 genes with the highest levels of consistent correlation with tFA in three cancer-associated data sets. (PDF 112 kb)

Supplementary Methods (PDF 107 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Carter, S., Eklund, A., Kohane, I. et al. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet 38 , 1043–1048 (2006). https://doi.org/10.1038/ng1861

Download citation

Received : 09 May 2006

Accepted : 17 July 2006

Published : 20 August 2006

Issue Date : 01 September 2006

DOI : https://doi.org/10.1038/ng1861

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Molecular characteristics of breast tumors in patients screened for germline predisposition from a population-based observational study Deborah F. Nacer Johan Vallon-Christersson Johan Staaf Genome Medicine (2023)

Pan-cancer analysis of whole-genome doubling and its association with patient prognosis Chie Kikutake Mikita Suyama BMC Cancer (2023)

Synthetic lethality prediction in DNA damage repair, chromatin remodeling and the cell cycle using multi-omics data from cell lines and patients. Magda Markowska Magdalena A. Budzinska Ewa Szczurek Scientific Reports (2023)

Osimertinib induces paraptosis and TRIP13 confers resistance in glioblastoma cells Lulu Hu Ji Shi Haozhe Piao Cell Death Discovery (2023)

Characterization of pancreatic cancer with ultra-low tumor mutational burden Taisuke Imamura Ryo Ashida Ken Yamaguchi Scientific Reports (2023)

Single Line Text

Published: 20 August 2006. Scott L Carter 1 , Aron C Eklund 1 , 2 , Isaac S Kohane 1 , Lyndsay N Harris 3 & … Zoltan Szallasi 1 , 4. Show authors. Nature Genetics volume  38 ,  pages 1043–1048 ( 2006 ) Cite this article. 15k Accesses. 829 Citations. 73 Altmetric. Metrics details. Abstract. We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors. This is a preview of subscription content, access via your institution. Relevant articles. Open Access articles citing this article. Disentangling the roles of aneuploidy, chromosomal instability and tumour heterogeneity in developing resistance to cancer therapies Joana Reis Andrade , Annie Dinky Gallagher  …  Sarah Elizabeth McClelland Chromosome Research Open Access 18 September 2023. Osimertinib induces paraptosis and TRIP13 confers resistance in glioblastoma cells Lulu Hu , Ji Shi  …  Haozhe Piao Cell Death Discovery Open Access 05 September 2023. Chromosomal instability and inflammation: a catch-22 for cancer cells Anouk van den Brink , Maria F. Suarez Peredo Rodriguez  &  Floris Foijer Chromosome Research Open Access 10 August 2023. Access options. Access through your institution. Change institution. Buy or subscribe. Subscribe to this journal. Receive 12 print issues and online access. $209.00 per year. only $17.42 per issue. Learn more. Rent or buy this article. Prices vary by article type. from $1.95. to $39.95. Learn more. Prices may be subject to local taxes which are calculated during checkout. Additional access options: Log in. Learn about institutional subscriptions. Read our FAQs. Contact customer support. References. Sotiriou, C. et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J. Natl. Cancer Inst. 98 , 262–272 (2006). Article   CAS   Google Scholar. van de Vijver, M.J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347 , 1999–2009 (2002). Article   CAS   Google Scholar. van't Veer, L.J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415 , 530–536 (2002). Article   CAS   Google Scholar. Wang, Y. et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365 , 671–679 (2005). Article   CAS   Google Scholar. Bild, A.H. et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439 , 353–357 (2006). Article   CAS   Google Scholar. Bhattacharjee, A. et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl. Acad. Sci. USA 98 , 13790–13795 (2001). Article   CAS   Google Scholar. Phillips, H.S. et al. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 9 , 157–173 (2006). Article   CAS   Google Scholar. Lopez-Rios, F. et al. Global gene expression profiling of pleural mesotheliomas: overexpression of aurora kinases and P16/CDKN2A deletion as prognostic factors and critical evaluation of microarray-based prognostic prediction. Cancer Res. 66 , 2970–2979 (2006). Article   CAS   Google Scholar. Freije, W.A. et al. Gene expression profiling of gliomas strongly predicts survival. Cancer Res. 64 , 6503–6510 (2004). Article   CAS   Google Scholar. Pomeroy, S.L. et al. Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 415 , 436–442 (2002). Article   CAS   Google Scholar. Shipp, M.A. et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat. Med. 8 , 68–74 (2002). Article   CAS   Google Scholar. Nutt, C.L. et al. Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res. 63 , 1602–1607 (2003). CAS   PubMed   Google Scholar. Lengauer, C., Kinzler, K.W. & Vogelstein, B. Genetic instabilities in human cancers. Nature 396 , 643–649 (1998). Article   CAS   Google Scholar. Gollin, S.M. Mechanisms leading to chromosomal instability. Semin. Cancer Biol. 15 , 33–42 (2005). Article   CAS   Google Scholar. Draviam, V.M., Xie, S. & Sorger, P.K. Chromosome segregation and genomic stability. Curr. Opin. Genet. Dev. 14 , 120–125 (2004). Article   CAS   Google Scholar. Diaz, L.A., Jr. The current clinical value of genomic instability. Semin. Cancer Biol. 15 , 67–71 (2005). Article   CAS   Google Scholar. Pollack, J.R. et al. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc. Natl. Acad. Sci. USA 99 , 12963–12968 (2002). Article   CAS   Google Scholar. Tonon, G. et al. High-resolution genomic profiles of human lung cancer. Proc. Natl. Acad. Sci. USA 102 , 9625–9630 (2005). Article   CAS   Google Scholar. Garraway, L.A. et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436 , 117–122 (2005). Article   CAS   Google Scholar. Roschke, A.V. et al. Karyotypic complexity of the NCI-60 drug-screening panel. Cancer Res. 63 , 8634–8647 (2003). CAS   PubMed   Google Scholar. Heidebrecht, H.J. et al. Repp86: a human protein associated in the progression of mitosis. Mol. Cancer Res. 1 , 271–279 (2003). CAS   PubMed   Google Scholar. Kurasawa, Y., Earnshaw, W.C., Mochizuki, Y., Dohmae, N. & Todokoro, K. Essential roles of KIF4 and its binding partner PRC1 in organized central spindle midzone formation. EMBO J. 23 , 3237–3248 (2004). Article   CAS   Google Scholar. Mollinari, C. et al. PRC1 is a microtubule binding and bundling protein essential to maintain the mitotic spindle midzone. J. Cell Biol. 157 , 1175–1186 (2002). Article   CAS   Google Scholar. Costa, R.H. FoxM1 dances with mitosis. Nat. Cell Biol. 7 , 108–110 (2005). Article   CAS   Google Scholar. Wonsey, D.R. & Follettie, M.T. Loss of the forkhead transcription factor FoxM1 causes centrosome amplification and mitotic catastrophe. Cancer Res. 65 , 5181–5189 (2005). Article   CAS   Google Scholar. Ramaswamy, S., Ross, K.N., Lander, E.S. & Golub, T.R. A molecular signature of metastasis in primary solid tumors. Nat. Genet. 33 , 49–54 (2003). Article   CAS   Google Scholar. Whitfield, M.L. et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol. Biol. Cell 13 , 1977–2000 (2002). Article   CAS   Google Scholar. Gorgoulis, V.G. et al. Activation of the DNA damage checkpoint and genomic instability in human precancerous lesions. Nature 434 , 907–913 (2005). Article   CAS   Google Scholar. Whitfield, M.L., George, L.K., Grant, G.D. & Perou, C.M. Common markers of proliferation. Nat. Rev. Cancer 6 , 99–106 (2006). Article   CAS   Google Scholar. Download references. Acknowledgements. We thank A. Amon, D. Botstein, M. Meyerson and T. Ried for helpful suggestions, and Novartis for the NCI60 expression data. This work was supported in part by the US National Institutes of Health through grant 1PO1CA-092644-01 and the Department of Defense through grant W81XWH-04-1-0549. I.S.K. was supported in part by National Institutes of Health National Center for Biomedical Computing grant 5U54LM008748-02. Author information. Authors and Affiliations. Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology (CHIP@HST), Harvard Medical School, Boston, 02115, Massachusetts, USA Scott L Carter, Aron C Eklund, Isaac S Kohane & Zoltan Szallasi. Laboratory of Functional Genomics, Brigham and Women's Hospital, Cambridge, 02139, Massachusetts, USA Aron C Eklund. Breast Disease Unit, Yale School of Medicine, New Haven, 06520-8032, Connecticut, USA Lyndsay N Harris. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, DK-2800, Denmark Zoltan Szallasi. Authors. Scott L Carter View author publications You can also search for this author in PubMed   Google Scholar. Aron C Eklund View author publications You can also search for this author in PubMed   Google Scholar. Isaac S Kohane View author publications You can also search for this author in PubMed   Google Scholar. Lyndsay N Harris View author publications You can also search for this author in PubMed   Google Scholar. Zoltan Szallasi View author publications You can also search for this author in PubMed   Google Scholar. Contributions. S.L.C. and Z.S. conceived of and designed the study. S.L.C. carried out all the analysis. S.L.C. and Z.S. wrote the manuscript. A.C.E., I.S.K. and L.N.H. provided guidance and participated in the preparation of the manuscript. Corresponding author. Correspondence to Zoltan Szallasi . Ethics declarations. Competing interests. S.L.C., A.C.E. and Z.S. have applied for a patent on the diagnostic use of the chromosomal instability signature described in the manuscript. Supplementary information. Supplementary Fig. 1. Relationship between functional aneuploidy and DNA-based measures of chromosomal abberations. (PDF 218 kb) Supplementary Fig. 2. Total functional aneuploidy (tFA) is a significant predictor of clinical outcome in the four breast, lung and brain cancer data sets of 18 data sets evaluated. (PDF 48 kb) Supplementary Fig. 3. Correlation between gene expression profiles and tFA is conserved in diverse human cancer data sets. (PDF 192 kb) Supplementary Fig. 4. The CIN signature does not generate significant predictions of clinical outcome for 6 of 18 data sets evaluated. (PDF 47 kb) Supplementary Fig. 5. The prognostic ability of cell cycle–regulated genes is dependent on CIN score. (PDF 130 kb) Supplementary Fig. 6. Multivariate analysis of the CIN25 and proliferation signatures revealed that CIN25 was generally more relevant for risk stratification of cancer cohorts. (PDF 27 kb) Supplementary Fig. 7. Removal of proliferation-associated genes from the CIN signature does not impair its predictive ability for clinical outcome. (PDF 591 kb) Supplementary Table 1. Top 70 genes with the highest levels of consistent correlation with tFA in three cancer-associated data sets. (PDF 112 kb) Supplementary Methods (PDF 107 kb) Rights and permissions. Reprints and Permissions. About this article. Cite this article. Carter, S., Eklund, A., Kohane, I. et al. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet 38 , 1043–1048 (2006). https://doi.org/10.1038/ng1861. Download citation. Received : 09 May 2006. Accepted : 17 July 2006. Published : 20 August 2006. Issue Date : 01 September 2006. DOI : https://doi.org/10.1038/ng1861. Share this article. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. This article is cited by. Molecular characteristics of breast tumors in patients screened for germline predisposition from a population-based observational study Deborah F. Nacer Johan Vallon-Christersson Johan Staaf Genome Medicine (2023) Pan-cancer analysis of whole-genome doubling and its association with patient prognosis Chie Kikutake Mikita Suyama BMC Cancer (2023) Synthetic lethality prediction in DNA damage repair, chromatin remodeling and the cell cycle using multi-omics data from cell lines and patients. Magda Markowska Magdalena A. Budzinska Ewa Szczurek Scientific Reports (2023) Osimertinib induces paraptosis and TRIP13 confers resistance in glioblastoma cells Lulu Hu Ji Shi Haozhe Piao Cell Death Discovery (2023) Characterization of pancreatic cancer with ultra-low tumor mutational burden Taisuke Imamura Ryo Ashida Ken Yamaguchi Scientific Reports (2023)