Dataset Information

Inferring tumor progression from genomic heterogeneity.

ABSTRACT: Cancer progression in humans is difficult to infer because we do not routinely sample patients at multiple stages of their disease. However, heterogeneous breast tumors provide a unique opportunity to study human tumor progression because they still contain evidence of early and intermediate subpopulations in the form of the phylogenetic relationships. We have developed a method we call Sector-Ploidy-Profiling (SPP) to study the clonal composition of breast tumors. SPP involves macro-dissecting tumors, flow-sorting genomic subpopulations by DNA content, and profiling genomes using comparative genomic hybridization (CGH). Breast carcinomas display two classes of genomic structural variation: (1) monogenomic and (2) polygenomic. Monogenomic tumors appear to contain a single major clonal subpopulation with a highly stable chromosome structure. Polygenomic tumors contain multiple clonal tumor subpopulations, which may occupy the same sectors, or separate anatomic locations. In polygenomic tumors, we show that heterogeneity can be ascribed to a few clonal subpopulations, rather than a series of gradual intermediates. By comparing multiple subpopulations from different anatomic locations, we have inferred pathways of cancer progression and the organization of tumor growth.

SUBMITTER: Navin N

PROVIDER: S-EPMC2798832 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Inferring tumor progression from genomic heterogeneity.

Navin Nicholas N Krasnitz Alexander A Rodgers Linda L Cook Kerry K Meth Jennifer J Kendall Jude J Riggs Michael M Eberling Yvonne Y Troge Jennifer J Grubor Vladimir V Levy Dan D Lundin Pär P Månér Susanne S Zetterberg Anders A Hicks James J Wigler Michael M

Genome research 20091110 1

Cancer progression in humans is difficult to infer because we do not routinely sample patients at multiple stages of their disease. However, heterogeneous breast tumors provide a unique opportunity to study human tumor progression because they still contain evidence of early and intermediate subpopulations in the form of the phylogenetic relationships. We have developed a method we call Sector-Ploidy-Profiling (SPP) to study the clonal composition of breast tumors. SPP involves macro-dissecting ...[more]

PMID: 19903760

Similar Datasets

Project description:ImportanceComprehensive understanding of the genomic and gene-expression differences between retinoblastoma tumors from patients with bilateral disease may help to characterize risk and optimize treatment according to individual tumor characteristics.ObjectiveTo compare the genomic features between each eye and a specimen from an orbital relapse in patients with bilateral retinoblastoma.Design, setting, and participantsIn this case, 2 patients with retinoblastoma underwent upfront bilateral enucleation. Tumor samples were subjected to genomic and gene-expression analysis. Primary cell cultures were established from both of the tumors of 1 patient and were used for gene-expression studies.Main outcomes and measuresWhole-exome sequencing was performed on an Illumina platform for fresh tumor samples and DNA arrays (CytoScan or OncoScan) were used for paraffin-embedded samples and cell lines. Gene-expression analysis was performed using Agilent microarrays. Germinal and somatic alterations, copy number alterations, and differential gene expression were assessed.ResultsAfter initial bilateral enucleation, patient 1 showed massive choroidal and laminar optic nerve infiltration, while patient 2 showed choroidal and laminar optic nerve invasion. Patient 1 developed left-eye orbital recurrence and bone marrow metastasis less than 1 year after enucleation. Both ocular tumors showed gains on 1q and 6p but presented other distinct genomic alterations, including an additional gain in 2p harboring the N-myc proto-oncogene (MYCN) in the left tumor and orbital recurrence. Similar copy number alterations between the orbital recurrence and the left eye supported the origin of the relapse, with an additional 11q loss only detected in the orbital relapse. Specimens from patient 2 showed common copy number gains and losses, but further evolution rendered a 2p gain spanning MYCN in the left tumor. For this patient, microarray expression analysis showed differential expression of the MYCN and the forkhead box protein G1 (FOXG1) gene pathways between the left and right tumors.Conclusions and relevanceDifferential genomic and gene expression features were observed between tumors in 2 patients with bilateral disease, confirming intereye heterogeneity that might be considered if targeted therapies are used in such patients. Chromosomal alteration profile supported the origin of the orbital recurrence from the homolateral eye in 1 patient. Loss in chromosome 11q may have been associated with extraocular relapse in this patient.

Project description:BackgroundThe intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.Methods and findingsWe developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D) in solid tumors, termed the tumor ecosystem diversity index (EDI), using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3) breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2) breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52). Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.ConclusionsTo our knowledge, this is the first study to couple unbiased measures of microenvironmental heterogeneity with genomic alterations to predict breast cancer clinical outcome. We propose a clinically relevant role of microenvironmental heterogeneity for advanced breast tumors, and highlight that ecological statistics can be translated into medical advances for identifying a new type of biomarker and, furthermore, for understanding the synergistic interplay of microenvironmental heterogeneity with genomic alterations in cancer cells.

Project description:BackgroundHigh grade serous ovarian cancer is characterised by high initial response to chemotherapy but poor outcome in the long term due to acquired resistance. One of the main genetic features of this disease is TP53 mutation. The majority of TP53 mutated tumors harbor missense mutations in this gene, correlated with p53 accumulation. TP53 null tumors constitute a specific subgroup characterised by nonsense, frameshift or splice-site mutations associated to complete absence of p53 expression. Different studies show that this kind of tumors may have a worse prognosis than other TP53 mutated HGSC.MethodsIn this study, we sought to characterise the intra-tumor heterogeneity of a TP53 null HGSC consisting of six primary tumor samples, two intra-pelvic and four extra-pelvic recurrences using exome sequencing and comparative genome hybridisation.ResultsSignificant heterogeneity was found among the different tumor samples, both at the mutational and copy number levels. Exome sequencing identified 102 variants, of which only 42 were common to all three samples; whereas 7 of the 18 copy number changes found by CGH analysis were presented in all samples. Sanger validation of 20 variants found by exome sequencing in additional regions of the primary tumor and the recurrence allowed us to establish a sequence of the tumor clonal evolution, identifying those populations that most likely gave rise to recurrences and genes potentially involved in this process, like GPNMB and TFDP1. Using functional annotation and network analysis, we identified those biological functions most significantly altered in this tumor. Remarkably, unexpected functions such as microtubule-based movement and lipid metabolism emerged as important for tumor development and progression, suggesting its potential interest as therapeutic targets.ConclusionsAltogether, our results shed light on the clonal evolution of the distinct tumor regions identifying the most aggressive subpopulations and at least some of the genes that may be implicated in its progression and recurrence, and highlights the importance of considering intra-tumor heterogeneity when carrying out genetic and genomic studies, especially when these are aimed to diagnostic procedures or to uncover possible therapeutic strategies.

Dataset Information

Inferring tumor progression from genomic heterogeneity.

Publications

Inferring tumor progression from genomic heterogeneity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets