Molecular profiling of patient-derived breast cancer xenografts

IntroductionIdentification of new therapeutic agents for breast cancer (BC) requires preclinical models that reproduce the molecular characteristics of their respective clinical tumors. In this work, we analyzed the genomic and gene expression profiles of human BC xenografts and the corresponding patient tumors.MethodsEighteen BC xenografts were obtained by grafting tumor fragments from patients into Swiss nude mice. Molecular characterization of patient tumors and xenografts was performed by DNA copy number analysis and gene expression analysis using Affymetrix Microarrays.ResultsComparison analysis showed that 14/18 pairs of tumors shared more than 56% of copy number alterations (CNA). Unsupervised hierarchical clustering analysis showed that 16/18 pairs segregated together, confirming the similarity between tumor pairs. Analysis of recurrent CNA changes between patient tumors and xenografts showed losses in 176 chromosomal regions and gains in 202 chromosomal regions. Gene expression profile analysis showed that less than 5% of genes had recurrent variations between patient tumors and their respective xenografts; these genes largely corresponded to human stromal compartment genes. Finally, analysis of different passages of the same tumor showed that sequential mouse-to-mouse tumor grafts did not affect genomic rearrangements or gene expression profiles, suggesting genetic stability of these models over time.ConclusionsThis panel of human BC xenografts maintains the overall genomic and gene expression profile of the corresponding patient tumors and remains stable throughout sequential in vivo generations. The observed genomic profile and gene expression differences appear to be due to the loss of human stromal genes. These xenografts, therefore, represent a validated model for preclinical investigation of new therapeutic agents.

[1]  E. Sausville,et al.  Contributions of human tumor xenografts to anticancer drug development. , 2006, Cancer research.

[2]  H. Höfler,et al.  Intratumoral heterogeneity in breast carcinoma revealed by laser-microdissection and comparative genomic hybridization. , 1999, Cancer genetics and cytogenetics.

[3]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[4]  Jian Li,et al.  Estimation of tumor heterogeneity using CGH array data , 2009, BMC Bioinformatics.

[5]  B. Dutrillaux,et al.  Hormone escape is associated with genomic instability in a human prostate cancer model , 2009, International journal of cancer.

[6]  Alessandro De Luca,et al.  Xenografts of primary human gynecological tumors grown under the renal capsule of NOD/SCID mice show genetic stability during serial transplantation and respond to cytotoxic chemotherapy. , 2008, Gynecologic oncology.

[7]  T. Speed,et al.  Summaries of Affymetrix GeneChip probe level data. , 2003, Nucleic acids research.

[8]  Nicolas Stransky,et al.  Characterization of the recurrent 8p11-12 amplicon identifies PPAPDC1B, a phosphatase protein, as a new therapeutic target in breast cancer. , 2008, Cancer research.

[9]  A. Nobel,et al.  The molecular portraits of breast tumors are conserved across microarray platforms , 2006, BMC Genomics.

[10]  Emmanuel Barillot,et al.  Analysis of array CGH data: from signal ratio to gain and loss of DNA regions , 2004, Bioinform..

[11]  H. Fiebig,et al.  Human Tumor Xenografts and Explants , 2002 .

[12]  Joshua F. McMichael,et al.  Genome Remodeling in a Basal-like Breast Cancer Metastasis and Xenograft , 2010, Nature.

[13]  A. Vincent-Salomon,et al.  A New Model of Patient Tumor-Derived Breast Cancer Xenografts for Preclinical Assays , 2007, Clinical Cancer Research.

[14]  A. Vincent-Salomon,et al.  Calibration of immunohistochemistry for assessment of HER2 in breast cancer: results of the French Multicentre GEFPICS * Study , 2003, Histopathology.

[15]  F. Pépin,et al.  Stromal gene expression predicts clinical outcome in breast cancer , 2008, Nature Medicine.

[16]  Céline Rouveirol,et al.  VAMP: Visualization and analysis of array-CGH, transcriptome and other molecular profiles , 2006, Bioinform..

[17]  A. Maier,et al.  Clonogenic assay with established human tumour xenografts: correlation of in vitro to in vivo activity as a basis for anticancer drug discovery. , 2004, European journal of cancer.

[18]  A. Ashworth,et al.  Establishment and characterisation of a new breast cancer xenograft obtained from a woman carrying a germline BRCA2 mutation , 2010, British Journal of Cancer.

[19]  K. Garber From human to mouse and back: 'tumorgraft' models surge in popularity. , 2009, Journal of the National Cancer Institute.

[20]  R. Tibshirani,et al.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Farin Kamangar,et al.  Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[22]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[23]  T. Sørlie,et al.  Molecular profiling and characterization of luminal‐like and basal‐like in vivo breast cancer xenograft models , 2009, Molecular oncology.

[24]  J. Thiery,et al.  Integrated Genomic and Transcriptomic Analysis of Ductal Carcinoma In situ of the Breast , 2008, Clinical Cancer Research.

[25]  Ajay N. Jain,et al.  Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. , 2006, Cancer cell.

[26]  O. Myklebost,et al.  Preclinical xenograft models of human sarcoma show nonrandom loss of aberrations , 2012, Cancer.