Abstract
The clinical course of breast cancer varies from one patient to another. Currently, the choice of therapy relies on clinical parameters and histological and molecular tumor features. Alas, these markers are informative in only a subset of patients. Therefore, additional predictors of disease outcome would be valuable for treatment stratification. Extensive studies showed that the degree of variation of the nuclear DNA content, i.e., aneuploidy, determines prognosis. Our aim was to further elucidate the molecular basis of aneuploidy. We analyzed five diploid and six aneuploid tumors with more than 20 years of follow-up. By performing FISH with a multiplexed panel of 10 probes to enumerate copy numbers in individual cells, and by sequencing 563 cancer-related genes, we analyzed how aneuploidy is linked to intratumor heterogeneity. In our cohort, none of the patients with diploid tumors died of breast cancer during follow-up in contrast to four of six patients with aneuploid tumors (mean survival 86.4 months). The FISH analysis showed markedly increased genomic instability and intratumor heterogeneity in aneuploid tumors. MYC gain was observed in only 20% of the diploid cancers, while all aneuploid cases showed a gain. The mutation burden was similar in diploid and aneuploid tumors, however, TP53 mutations were not observed in diploid tumors, but in all aneuploid tumors in our collective. We conclude that quantitative measurements of intratumor heterogeneity by multiplex FISH, detection of MYC amplification and TP53 mutation could augment prognostication in breast cancer patients.
| Originalsprache | Englisch |
|---|---|
| Zeitschrift | Genes Chromosomes and Cancer |
| Jahrgang | 57 |
| Ausgabenummer | 4 |
| Seiten (von - bis) | 165-175 |
| Seitenumfang | 11 |
| ISSN | 1045-2257 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 01.04.2018 |
Fördermittel
1Section of Translational Surgical Oncology and Biobanking, Department of Surgery, University of Lu€beck, Lu€beck, Germany 2Genetics Branch, Center for Cancer Research, National Cancer Institute/National Institutes of Health, Bethesda, Maryland 3Department of Biological Sciences and Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 4Computational Biology Branch, National Center for Biotechnology Information/ National Institutes of Health, Bethesda, Maryland 5Department of Pathology and Oncology, Karolinska University Hospital and Karolinska Institute, Stockholm, Sweden This research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI and NLM. JO received a PROMOS scholarship from the German Academic Exchange Service. RM was supported by a Mildred Scheel postdoctoral scholarship of the German Cancer Aid (Deutsche Krebshilfe). ND was supported by a Ph.D. fellowship of the Ad Infinitum Foundation. RS was funded by U.S. National Institutes of Health award 1R21CA216452 and by Pennsylvania Dept. of Health Grant GBMF4554 #4100070287. The Pennsylvania Department of Health specifically disclaims responsibility for any analyses, interpretations or conclusions. The OncoVar libraries were sequenced in the CCR Sequencing Facility in Frederick (Dr. Tran). The authors would like to thank Go€rel So€derblom and Dr. Roland Sennerstam for the retrieval of archived tissue material and patient data, Dr. Anders Ho€o€g for the pathology review of tissue blocks, and Inger Bodin for cutting sections. We also thank Annette Lischka for retrieving and compiling clinical patient data, and Buddy Chen for the preparation of figures.
Strategische Forschungsbereiche und Zentren
- Profilbereich: Lübeck Integrated Oncology Network (LION)
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