The HER2 extracellular domain shed in blood (HER2
) is reported to rise and fall in parallel with HER2+ breast cancer behavior. In this study, we evaluated the clinical relevance of plasma HER2
...values in patients with metastatic breast cancer treated in the SAKK22/99 trial comparing trastuzumab monotherapy followed by trastuzumab-chemotherapy combination at progression versus upfront combination therapy.
Quantitative assessment of plasma HER2
was performed in 133 patients at baseline; after 2-24 h; at 3 weeks; at first response evaluation (8-9 weeks); and at tumor progression. Associations with tumor characteristics, disease course and trial treatment were evaluated.
Baseline HER2
levels were stable within 24 h after the first trastuzumab injection. These plasma values correlated positively with the HER2 gene ratio (r
= 0.39, P < 0.001) and HER2 protein expression levels (r
= 0.36, P < 0.001) but not with ER/PR status of the primary tumor. HER2
baseline levels were positively associated with the presence of visceral disease (P = 0.05) and poor patients' outcome (Cox-regression: P = 0.009). Patients with high baseline levels (> 35 ng/ml) had the worst overall survival (P = 0.03) if treated with upfront combination therapy. Conversely, patients with low HER2
baseline values (< 15 ng/ml) had longer time to progression on combined trastuzumab-chemotherapy when first treated with trastuzumab monotherapy (P = 0.02). Monitoring HER2
levels during the course of the trial revealed significant time (P = 0.001) and time-treatment arm interactions (P = 0.0007). Under upfront trastuzumab alone, the HER2
levels remained stable until just before disease progression. In patients responding to combination treatment HER2
levels decreased to > 20%.
Plasma HER2
levels in patients with metastatic breast cancer reflect HER2 disease status. This robust biomarker might help identifying patients without visceral disease profiting from a sequential treatment's modality. Monitoring HER2
levels during trastuzumab monotherapy could help defining the optimal time to introduce chemotherapy.
Registration Number by ClinicalTrials.gov: NCT00004935, Trial number: SAKK22/99. Registered on 27 January 2003.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background: The implementation of novel technologies such as array comparative genomic hybridization (aCGH) and next-generation sequencing has led to a deeper understanding of the genomic ...nature of cancer. However, these analyses have classically been done without respecting intra-tumor heterogeneity. Here, we applied a methodology that allows us analyzing the genomic profile of distinct tumor populations from individual tumors and their clonal evolution during the progression to castration-resistant disease. Methods: Matched pre- and post- hormone treated fresh frozen and/or formalin fixed prostate cancer samples were selected from our biobank. Clonal tumor populations were flow-sorted according to their nuclear DNA content. Sorted tumor populations were subjected to whole genome CGH and to full exome sequencing analyses by the use of Agilent SurePrint 2x400k microarrays and the SureSelect All Exon Kit, respectively. Results: The genomic analyses of the tumor samples underscore the presence of significant intra-tumoral heterogeneity. The analysis of matched tumor specimens allowed us to identify two particular patterns of tumor evolution during the progression after treatment: First, a more parallel pattern of tumor evolution, in which the ancestor population is breeding multiple aneuploid tumor clones. In this case, only the 2N ancestor population is able to withstand therapy by the acquisition of few specific genomic aberrations whereas the aneuploid populations are eradicated. Second, a more sequential pattern of tumor evolution with a tumor population that evolves out of a continuous line of clones. This population shows increasing signs of genomic instability over time, with a punctual event of chromothripsis (a massive destruction and rearrangement of chromosomal structures) resulting in castration-resistant clonal tumor populations. Conclusions: Genomic profiling of distinct clonal tumor populations during prostate cancer progression allows for analysis of intra-tumoral heterogeneity and the underlying clonal evolution. Importantly, this approach identifies genomic aberrations that were selected for under the pressure of hormone ablation therapy.
Citation Format: Joël R. Gsponer, Tanja Dietsche, Alexander Rufle, Elisabeth Lenkiewicz, Tobias Zellweger, Alexander Bachmann, Daniel D. Von Hoff, M T. Barrett, Cyrill Rentsch, Christian Ruiz, Lukas Bubendorf. The genomic evolution of prostate cancer under the selective pressure of anti-androgen therapy. abstract. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3181. doi:10.1158/1538-7445.AM2013-3181
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