Marion E. Meijer-van Gelder

Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer

BACKGROUND Genome-wide measures of gene expression can identify patterns of gene activity that subclassify tumours and might provide a better means than is currently available for individual risk assessment in patients with lymph-node-negative breast cancer. METHODS We analysed, with Affymetrix Human U133a GeneChips, the expression of 22000 transcripts from total RNA of frozen tumour samples from 286 lymph-node-negative patients who had not received adjuvant systemic treatment. FINDINGS In a training set of 115 tumours, we identified a 76-gene signature consisting of 60 genes for patients positive for oestrogen receptors (ER) and 16 genes for ER-negative patients. This signature showed 93% sensitivity and 48% specificity in a subsequent independent testing set of 171 lymph-node-negative patients. The gene profile was highly informative in identifying patients who developed distant metastases within 5 years (hazard ratio 5.67 [95% CI 2.59-12.4]), even when corrected for traditional prognostic factors in multivariate analysis (5.55 [2.46-12.5]). The 76-gene profile also represented a strong prognostic factor for the development of metastasis in the subgroups of 84 premenopausal patients (9.60 [2.28-40.5]), 87 postmenopausal patients (4.04 [1.57-10.4]), and 79 patients with tumours of 10-20 mm (14.1 [3.34-59.2]), a group of patients for whom prediction of prognosis is especially difficult. INTERPRETATION The identified signature provides a powerful tool for identification of patients at high risk of distant recurrence. The ability to identify patients who have a favourable prognosis could, after independent confirmation, allow clinicians to avoid adjuvant systemic therapy or to choose less aggressive therapeutic options.

Molecular Classification of Tamoxifen-Resistant Breast Carcinomas by Gene Expression Profiling

PURPOSE To discover a set of markers predictive for the type of response to endocrine therapy with the antiestrogen tamoxifen using gene expression profiling. PATIENTS AND METHODS The study was performed on 112 estrogen receptor-positive primary breast carcinomas from patients with advanced disease and clearly defined types of response (ie, 52 patients with objective response v 60 patients with progressive disease) from start of first-line treatment with tamoxifen. Main clinical end points are the effects of therapy on tumor size and time until tumor progression (progression-free survival [PFS]). RNA isolated from tumor samples was amplified and hybridized to 18,000 human cDNA microarrays. RESULTS Using a training set of 46 breast tumors, 81 genes were found to be differentially expressed (P < or = .05) between tamoxifen-responsive and -resistant tumors. These genes were involved in estrogen action, apoptosis, extracellular matrix formation, and immune response. From the 81 genes, a predictive signature of 44 genes was extracted and validated on an independent set of 66 tumors. This 44-gene signature is significantly superior (odds ratio, 3.16; 95% CI, 1.10 to 9.11; P = .03) to traditional predictive factors in univariate analysis and also significantly related with a longer PFS in univariate (hazard ratio, 0.54; 95% CI, 0.31 to 0.94; P = .03) as well as in multivariate analyses (P = .03). CONCLUSION Our data show that gene expression profiling can be used to discriminate between breast cancer patients with progressive disease and objective response to tamoxifen. Additional studies are needed to confirm if the predictive signature might allow identification of individual patients who could benefit from other (adjuvant) endocrine therapies.

Association of an Extracellular Matrix Gene Cluster with Breast Cancer Prognosis and Endocrine Therapy Response

Purpose: We previously discovered an extracellular matrix (ECM) gene cluster associated with resistance to first-line tamoxifen therapy of patients with metastatic breast cancer. In this study, we determined whether the six individual ECM genes [collagen 1A1 (COL1A1), fibronectin 1 (FN1), lysyl oxidase (LOX), secreted protein acidic cysteine-rich (SPARC), tissue inhibitor of metalloproteinase 3 (TIMP3), and tenascin C (TNC)] were associated with treatment response, prognosis, or both. Experimental Design: In 1,286 primary breast tumors, mRNA expression (quantitative real-time PCR) was related to clinicopathologic factors and disease outcome in univariate and multivariate analysis including traditional factors. Results:TIMP3, FN1, LOX, and SPARC expression levels (continuous variables) were significantly associated with distant metastasis-free survival (MFS) in 680 lymph node–negative untreated patients (P < 0.03). Using a calculated linear prognostic score, these patients were evenly divided into five prognostic groups with a significant difference in 10-year MFS of ∼40% between the two extreme prognostic groups. Furthermore, high TNC expression as continuous variable was associated with (a) shorter MFS in 139 estrogen receptor–positive and lymph node–positive patients who received adjuvant tamoxifen therapy (hazard ratio, 1.53; P = 0.001), and (b) no clinical benefit (odds ratio, 0.81; P = 0.035) and shorter progression-free survival (hazard ratio, 1.19; P = 0.002) in 240 patients in whom recurrence was treated with tamoxifen as first-line monotherapy. These results were also significant in multivariate analyses. Conclusion:FN1, LOX, SPARC, and TIMP3 expression levels are associated with the prognosis of patients with breast cancers, whereas TNC is associated with resistance to tamoxifen therapy. Further validation and functional studies are necessary to determine the use of these ECM genes in decisions regarding treatment and whether they can serve as targets for therapy.

Molecular profiling of platinum resistant ovarian cancer

The aim of this study is to discover a gene set that can predict resistance to platinum‐based chemotherapy in ovarian cancer. The study was performed on 96 primary ovarian adenocarcinoma specimens from 2 hospitals all treated with platinum‐based chemotherapy. In our search for genes, 24 specimens of the discovery set (5 nonresponders and 19 responders) were profiled in duplicate with 18K cDNA microarrays. Confirmation was done using quantitative RT‐PCR on 72 independent specimens (9 nonresponders and 63 responders). Sixty‐nine genes were differentially expressed between the nonresponders (n = 5) and the responders (n = 19) in the discovery phase. An algorithm was constructed to identify predictive genes in this discovery set. This resulted in 9 genes (FN1, TOP2A, LBR, ASS, COL3A1, STK6, SGPP1, ITGAE, PCNA), which were confirmed with qRT‐PCR. This gene set predicted platinum resistance in an independent validation set of 72 tumours with a sensitivity of 89% (95% CI: 0.68–1.09) and a specificity of 59% (95% CI: 0.47–0.71)(OR = 0.09, p = 0.026). Multivariable analysis including patient and tumour characteristics demonstrated that this set of 9 genes is independent for the prediction of resistance (p < 0.01). The findings of this study are the discovery of a gene signature that classifies the tumours, according to their response, and a 9‐gene set that determines resistance in an independent validation set that outperforms patient and tumour characteristics. A larger independent multicentre study should further confirm whether this 9‐gene set can identify the patients who will not respond to platinum‐based chemotherapy and could benefit from other therapies.

Bcar1/p130Cas Protein and Primary Breast Cancer: Prognosis and Response to Tamoxifen Treatment

Background: The product of the Bcar1/p130Cas (breast cancer resistance/p130Crk-associated substrate) gene causes resistance to antiestrogen drugs in human breast cancer cells in vitro. To investigate its role in clinical breast cancer, we determined the levels of Bcar1/p130Cas protein in a large series of primary breast carcinomas. Methods: We measured Bcar1/p130Cas protein in cytosol extracts from 937 primary breast carcinomas by western blot analysis. The levels of Bcar1/p130Cas protein were tested for associations and trends against clinicopathologic and patient characteristics, the lengths of relapse-free survival and overall survival (n = 775), and the efficacy of first-line treatment with tamoxifen for recurrent or metastatic disease (n = 268). Results: Bcar1/ p130Cas levels in primary tumors were associated with age/ menopausal status and the levels of estrogen receptor and progesterone receptor. In univariate survival analysis, higher Bcar1/p130Cas levels were associated with poor relapse-free survival and overall survival (both two-sided P = .04; log-rank test for trend). In multivariate analysis, a high level of Bcar1/p130Cas was independently associated with poor relapse-free survival and overall survival. The response to tamoxifen therapy in patients with recurrent disease was reduced in patients with primary tumors that expressed high

HOXB13-to-IL17BR expression ratio is related with tumor aggressiveness and response to tamoxifen of recurrent breast cancer : A retrospective study

PURPOSE A HOXB13-to-IL17BR expression ratio was previously identified to predict clinical outcome of breast cancer patients treated with adjuvant tamoxifen. However, this ratio may predict a tumors response to tamoxifen, its intrinsic aggressiveness, or both. PATIENTS AND METHODS We have measured the HOXB13 and IL17BR expression levels by real-time polymerase chain reaction in 1,252 primary breast tumor specimens. Expression levels were normalized to housekeeper gene levels and related to clinicopathologic factors for all patients. The primary objective of this study was to determine the relationship of a HOXB13-to-IL17BR ratio with tumor aggressiveness and/or with response to tamoxifen therapy in estrogen receptor (ER) -positive disease. We selected ER-positive tumors, and clinical end points for the HOXB13-to-IL17BR ratio were disease-free survival (DFS) in patients with primary breast cancer (N = 619) and progression-free survival (PFS) in patients with recurrent breast cancer treated with first-line tamoxifen monotherapy (N = 193). The odds ratio (OR) and hazard ratio (HR) and their 95% CI were calculated, and all P values were two-sided. RESULTS The HOXB13-to-IL17BR ratio was significantly associated with DFS and PFS. In multivariate analysis, HOXB13-to-IL17BR ratio expression levels were associated with a shorter DFS for node-negative patients only. Corrected for traditional predictive factors, the dichotomized HOXB13-to-IL17BR ratio was the strongest predictor in multivariate analysis for a poor response to tamoxifen therapy (OR = 0.16; 95% CI, 0.06 to 0.45; P < .001) and a shorter PFS (HR = 2.97; 95% CI, 1.82 to 4.86; P < .001). CONCLUSION High HOXB13-to-IL17BR ratio expression levels associate with both tumor aggressiveness and tamoxifen therapy failure.

Tumor tissue levels of tissue inhibitor of metalloproteinase-1 as a prognostic marker in primary breast cancer.

Purpose: In the present study, we investigated the association between tumor tissue levels of tissue inhibitor of metalloproteinase-1 (TIMP-1) and prognosis in patients with primary breast cancer and analyzed whether TIMP-1 may be useful as a prognostic marker in combination with urokinase plasminogen activator (uPA) and plasminogen activator inhibitor type-1 (PAI-1). Experimental Design: In cytosolic extracts of 2984 primary breast tumors, total levels of TIMP-1 were determined using an established, validated ELISA. Levels of uPA and PAI-1 have previously been determined in the extracts. Results: Univariate survival analysis showed a significant relationship between higher levels of TIMP-1 (continuous log-transformed variable) and poor prognosis [recurrence-free survival (RFS), overall survival (OS); P < 0.001]. Performing isotonic regression analysis, we identified a cut point to classify tumors as TIMP-1-low or TIMP-1-high. Using this cut point, high levels of TIMP-1 were significantly associated with shorter survival in univariate analysis, both in the total patient group (RFS, OS; P < 0.001), in the node-negative subgroup (RFS, hazard ratio = 1.28, P = 0.006), and in the node-positive subgroup (RFS, hazard ratio = 1.43, P < 0.001). In multivariate analysis, including uPA and PAI-1, TIMP-1 was significantly associated with shorter RFS, both when included as a continuous log-transformed (P = 0.03) and as a dichotomized variable (P = 0.002). Conclusions: This study validates previous findings that tumor tissue levels of TIMP-1 are associated with prognosis in patients with primary breast cancer. It confirms that TIMP-1 may be useful as a prognostic marker in combination with uPA/PAI-1 and adds substantial positive information on the use of TIMP-1 as a prognostic marker in breast cancer.

Association of DNA Methylation of Phosphoserine Aminotransferase with Response to Endocrine Therapy in Patients with Recurrent Breast Cancer

To understand the biological basis of resistance to endocrine therapy is of utmost importance in patients with steroid hormone receptor-positive breast cancer. Not only will this allow us prediction of therapy success, it may also lead to novel therapies for patients resistant to current endocrine therapy. DNA methylation in the promoter regions of genes is a prominent epigenetic gene silencing mechanism that contributes to breast cancer biology. In the current study, we investigated whether promoter DNA methylation could be associated with resistance to endocrine therapy in patients with recurrent breast cancer. Using a microarray-based technology, the promoter DNA methylation status of 117 candidate genes was studied in a cohort of 200 steroid hormone receptor-positive tumors of patients who received the antiestrogen tamoxifen as first-line treatment for recurrent breast cancer. Of the genes analyzed, the promoter DNA methylation status of 10 genes was significantly associated with clinical outcome of tamoxifen therapy. The association of the promoter hypermethylation of the strongest marker, phosphoserine aminotransferase (PSAT1) with favorable clinical outcome was confirmed by an independent quantitative DNA methylation detection method. Furthermore, the extent of DNA methylation of PSAT1 was inversely associated with its expression at the mRNA level. Finally, also at the mRNA level, PSAT1 was a predictor of tamoxifen therapy response. Concluding, our work indicates that promoter hypermethylation and mRNA expression of PSAT1 are indicators of response to tamoxifen-based endocrine therapy in steroid hormone receptor-positive patients with recurrent breast cancer.

MicroRNA-30c expression level is an independent predictor of clinical benefit of endocrine therapy in advanced estrogen receptor positive breast cancer

MicroRNAs (miRNAs) are small RNA molecules that modulate gene expression and which have been implicated in cancer. We evaluated whether five candidate predictive miRNAs, derived from a pilot study in which 249 miRNAs were assayed, were associated with clinical benefit of tamoxifen therapy in advanced breast cancer. These five miRNAs were measured in an independent series of 246 estrogen receptor (ER)-positive primary breast tumors of patients who received tamoxifen for advanced disease by quantitative Real Time PCR. Univariate analysis showed that higher expression levels of hsa-miR-30a-3p, hsa-miR-30c, and hsa-miR-182 were significantly associated with benefit of tamoxifen treatment and with longer PFS (all P-values <0.01). In multivariate analysis, corrected for the traditional predictive factors, only hsa-miRNA-30c was an independent predictor (P-value <0.01). Finally, in an attempt to understand the biology connected to this miRNA, Global testing pathway analysis showed an association of hsa-miRNA-30c expression with HER and RAC1 signaling pathways. We identified hsa-miRNA-30c as an independent predictor for clinical benefit of tamoxifen therapy in patients with advanced breast cancer. Assessment of tumor levels and connected pathways could be helpful to improve treatment strategies.

Identification of a putative protein-profile associating with tamoxifen therapy-resistance in breast cancer

Tamoxifen resistance is a major cause of death in patients with recurrent breast cancer. Current clinical factors can correctly predict therapy response in only half of the treated patients. Identification of proteins that are associated with tamoxifen resistance is a first step toward better response prediction and tailored treatment of patients. In the present study we intended to identify putative protein biomarkers indicative of tamoxifen therapy resistance in breast cancer using nano-LC coupled with FTICR MS. Comparative proteome analysis was performed on ∼5,500 pooled tumor cells (corresponding to ∼550 ng of protein lysate/analysis) obtained through laser capture microdissection (LCM) from two independently processed data sets (n = 24 and n = 27) containing both tamoxifen therapy-sensitive and therapy-resistant tumors. Peptides and proteins were identified by matching mass and elution time of newly acquired LC-MS features to information in previously generated accurate mass and time tag reference databases. A total of 17,263 unique peptides were identified that corresponded to 2,556 non-redundant proteins identified with ≥2 peptides. 1,713 overlapping proteins between the two data sets were used for further analysis. Comparative proteome analysis revealed 100 putatively differentially abundant proteins between tamoxifen-sensitive and tamoxifen-resistant tumors. The presence and relative abundance for 47 differentially abundant proteins were verified by targeted nano-LC-MS/MS in a selection of unpooled, non-microdissected discovery set tumor tissue extracts. ENPP1, EIF3E, and GNB4 were significantly associated with progression-free survival upon tamoxifen treatment for recurrent disease. Differential abundance of our top discriminating protein, extracellular matrix metalloproteinase inducer, was validated by tissue microarray in an independent patient cohort (n = 156). Extracellular matrix metalloproteinase inducer levels were higher in therapy-resistant tumors and significantly associated with an earlier tumor progression following first line tamoxifen treatment (hazard ratio, 1.87; 95% confidence interval, 1.25–2.80; p = 0.002). In summary, comparative proteomics performed on laser capture microdissection-derived breast tumor cells using nano-LC-FTICR MS technology revealed a set of putative biomarkers associated with tamoxifen therapy resistance in recurrent breast cancer.