Integrative molecular and functional profiling of ERBB2-amplified breast cancers identifies new genetic dependencies

Overexpression of the receptor tyrosine kinase ERBB2 (also known as HER2) occurs in around 15% of breast cancers and is driven by amplification of the ERBB2 gene. ERBB2 amplification is a marker of poor prognosis, and although anti-ERBB2-targeted therapies have shown significant clinical benefit, de novo and acquired resistance remains an important problem. Genomic profiling has demonstrated that ERBB2+ve breast cancers are distinguished from ER+ve and 'triple-negative' breast cancers by harbouring not only the ERBB2 amplification on 17q12, but also a number of co-amplified genes on 17q12 and amplification events on other chromosomes. Some of these genes may have important roles in influencing clinical outcome, and could represent genetic dependencies in ERBB2+ve cancers and therefore potential therapeutic targets. Here, we describe an integrated genomic, gene expression and functional analysis to determine whether the genes present within amplicons are critical for the survival of ERBB2+ve breast tumour cells. We show that only a fraction of the ERBB2-amplified breast tumour lines are truly addicted to the ERBB2 oncogene at the mRNA level and display a heterogeneous set of additional genetic dependencies. These include an addiction to the transcription factor gene TFAP2C when it is amplified and overexpressed, suggesting that TFAP2C represents a genetic dependency in some ERBB2+ve breast cancer cells.

ER Status and Immune Module Are Central Determinants of HER2 Amplified Infiltrative Breast Carcinoma Prognosis and Pathologic Complete Response

IntroductionGene expression profiling of invasive breast cancer has resulted in highlighting three main categories of breast cancer [luminal, basal, HER2] with very specific features. It has been shown that these subtypes differ in their response to neaoadjuvant systemic treatment, axillary lymph node involvement, metastasis pattern and time to metastasis. The aim of this study was to focus on gene-expression profile analysis of HER2 positive breast carcinoma to assess how the molecular subtype classification applies to the HER2+ve samples; whether subgroups of patients that have different prognosis can be identified and how subgroups can be identified that differ with respect to the likelihood to achieve pathologic complete response (pCR) after neoadjuvant systemic treatment?Materials and MethodWe selected breast carcinomas reported to have a HER2+ve status (IHC and CISH) from patients treated between January 1990 and December 2006 at the Netherlands Cancer Institute. 113 tumor samples were hybridized on the Human Genome Oligo Set Version 3.0 arrays. We identified 205 HER2+ve samples from 4 public microarrays datasets and 33 HER2+ve samples from one public neoadjuvant systemic treatment microarrays dataset.ResultsWe applied the molecular subtype classification to the whole datasets and found major classification instability. 43.3% of the HER2+ve samples were classified as “HER2 subtype”, 26% as “basal-like subtype”, and 21.9% as “luminal-like subtype”. The molecular subtype classification was not correlated to prognosis. Of the prognostic variables tested, only ER status was to the development of distant metastasis (IHC, HR=0.53 [0.36-0.77], p=0.0009). We identified a set of 109 ReporterID's highly enriched in gene ontology annotations link to the Immune Response and correlated to the prognosis of HER2+ve breast carcinoma (Inactivated Immune Module, HR=4.21 [1.94-9.17], logrank pvalue=8.1E-05). The Immune Module Signature was associated with prognosis of the HER2+ve samples in both ER positive and ER negative breast cancer. We validated this Immune Module signature combined with ER status on 205 independent samples.We applied the same classification tree to 33 samples from patients who were assessed for response to neo-adjuvant systemic chemotherapy (Anthracyclin-based) and showed an association between the Immune Module Signature combined with ER status and pCR rate (ER+ve Inactivated Immune Module 12.5% pCR, ER-ve Activated Immune Module 70% pCR, pvalue=0.1).ConclusionWe have shown that HER2+ve breast cancer samples often are not classified as HER2-like by gene expression profiling and that ER (IHC) status determines two major subgroups. We provide new evidence that an immune response relate gene expression classifier has prognostic impact in HER2+ve breast cancer; and that this classifier is potentially correlated to the pCR rate after neoadjuvant systemic treatment in HER2+ve breast cancer.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4037.

Integrative Molecular Profiling of Triple Negative Breast Cancers Identifies Potential Therapeutic Targets Including Amplifications of FGFR2

Triple negative breast cancers (TNBCs) have a relatively poor prognosis emphasising the need to identify new subtype specific target therapies. Based on the concept of oncogene addiction, we searched for potential therapeutic targets by identifying genes consistently over-expressed when amplified in TNBC. Fifty six TNBCs were subjected to high resolution tiling path microarray-based comparative genomic hybridisation (aCGH); out of these cases, 24 were also subjected to genome-wide microarray-based mRNA expression analysis. TNBCs showed a high level of genetic instability, with recurrent regions of amplification (>4 copies) included multiple regions on 1q and 8q, 3q25, 10p14, 10q26, 13q34, 15q26 and 19q12-19q13. Integration of aCGH and expression data revealed 38 genes that were significantly overexpressed when amplified. This list includes known oncogenes and potential therapeutic targets, such as MCL1 (1q21.2), FGFR2 (10q26.3), BUB3 (10q26.3), RAB20 (13q34), PKN1 (19p13.12), and NOTCH3 (19p13.12). To validate FGFR2 as a therapeutic target, we screened a panel of cell lines, by western blotting and aCGH, and identified two TNBC cell lines with FGFR2 amplification. In these cell lines FGFR2 was constitutively active in a ligand independent manner, and RNA interference-mediated silencing of FGFR2 selectively decreased survival of cell lines harbouring FGFR2 amplification. Likewise FGFR2 amplified cell lines were highly sensitive to FGFR tyrosine kinase inhibitor PD173074 (IC50 <20nM). Treatment with PD173074 induced apoptosis in amplified cell lines, as did treatment with PI3 kinase inhibitors LY294002 and BEZ-235 suggesting that apoptosis resulted from inhibition of AKT signalling. Examination of publically available CGH data sets confirmed FGFR2 amplification in 4% (5/124 95%CI 1.3-9.2%) of TNBC, with no cases of FGFR2 amplification in other subtypes (0/150, p=0.02). Our results suggest that FGFR2 amplification is a therapeutic target in a small subset of TNBCs.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 3147.

Different effects of insulin-like growth factor-1 receptor expression on prognosis of estrogen receptor positive versus triple-negative invasive ductal breast carcinoma

3546

Background: The insulin-like growth factor type 1 receptor (IGF-1R) is involved in progression and sensitivity to systemic treatment of breast cancer. Moreover, targeted inhibition of IGF-1R is likely to be beneficial in systemic treatment. However, it is unknown how to select patients for IGF-1R targeted therapy. Therefore, we studied the relation between IGF-1R expression and prognosis in invasive ductal breast carcinomas. Methods: Immunohistochemistry was performed on tumor tissue of a consecutive cohort of 429 female patients treated for operable primary invasive ductal breast carcinoma. TMA sections were stained with antibodies against IGF1-R, insulin receptor (IR), ER, PR, HER-2, epidermal growth factor receptor (EGFR) and phosphorylated-Akt (p-Akt). Cytoplasmic and membranous IGF-1R staining were scored separately, as the relevance of IGF-1R cellular localization is yet unknown. Associations between IGF-1R expression with clinical and tumor characteristics were evaluated in a multivariate Cox regression model. To study in more detail the prognostic role of IGF-1R expression in triple negative invasive ductal carcinomas (TN IDCs), 51 TN IDCs from the series described above were combined with 64 TN IDCs from an independent dataset with similar patient and clinico-pathological characteristics. Results: Patients with tumors expressing both ER and cytoplasmic IGF-1R have a longer disease free survival (HR = 0.20; 95% CI 0.07 - 0.63; p-value = 0.006) and breast cancer specific survival (HR = 0.20, 95% CI 0.07 - 0.63, p-value = 0.002), independent of other known prognostic factors. Conversely, in the combined series of 105 TN IDCs, cytoplasmic IGF-1R expression was associated with a shorter disease free survival (HR = 2.29; 95% CI 1.08 - 4.48, p-value = 0.03). In a multivariate model including known prognostic factors, cytoplasmic IGF-1R expression was nearly significantly related to a shorter disease free survival (HR 2.06; 95% CI 0.95 - 4.47; p = 0.07). Conclusions: The favorable versus unfavorable association with prognosis of IGF-1R expression in ER positive versus TN IDCs may provide new opportunities to select patients for IGF-1R targeted therapy.

No significant financial relationships to disclose.

Microarray-based determination of ER, PR and HER2 receptor status: validation and comparison with IHC assessments

Abstract #3007

Background
 In breast cancer patients the level of expression of estrogen receptor (ER), progesterone receptor (PR) and HER2 is predictive for prognosis and/or treatment response. However, differences in assessment methods and interpretation can substantially affect the accuracy and reproducibility of the results. Previously, we have determined the association between immunohistochemistry (IHC) and mRNA levels for ER, PR and HER2, and have confirmed the accuracy of microarray readout on >400 samples. In the current study we describe the use of this microarray based readout on prospectively collected samples. We compared these readouts with multiple IHC and fluorescent in situ hybridization (FISH) assessments generated in various hospitals and a CLIA-certified reference laboratory and developed a microarray based test called TargetPrint™.
 Methods
 Gene expression data for ER, PR and HER2 were obtained by analysis of 100 breast carcinomas that have been collected prospectively within the RASTER study. Samples were stratified as receptor positive or negative using thresholds for ER, PR and HER2 mRNA levels. IHC assessment was performed (1) according to local standards of the hospital from where the sample originated, (2) by the central laboratory of the Netherlands Cancer Institute, and (3) at an independent reference laboratory using FDA-approved procedures and ASCO/CAP guidelines. A tumor was classified positive for ER and PR when ≥10% of tumor cells showed positive staining. HER2 IHC status was scored as 0, 1+, 2+ or 3+; a score of 3+ was considered positive. In case of 2+ samples, a FISH was performed to assess final HER2 amplification status. The cohort used in this study was pre-selected to include about two-third ER and PR positive samples and one-third HER2 positive samples.
 Results
 Multiple microarray readouts were highly reproducible (Pearson correlation 0.991) and resulted in 67, 61 and 39 percent positive samples for ER, PR and HER2, respectively. Comparison of microarray results with IHC (including FISH for HER2) performed at the three centers indicated highly similar results for receptor readout with a concordance of 92, 93 and 92% for ER; 84, 81 and 86% for PR; and 93, 95 and 94% for HER2. Overall misclassification rates between microarray and IHC readout were low for ER (0.08) and HER2 (0.06) and quite low for PR (0.14), and were comparable to the misclassification rates between the three IHC methods.
 Conclusion
 A microarray-based assessment of ER, PR and HER2 in relation to mRNA levels gives results comparable to multiple IHC methods and FISH and provides an objective and more quantitative assessment of tumor receptor status than IHC alone. Using TargetPrint™ for microarray readouts for hormone and HER2 receptor in addition to standard IHC will improve molecular characterization of breast cancer tissue.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 3007.

Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types

Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualising treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them.