Maurice P.H.M. Jansen

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.

Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen

BackgroundEstrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30–40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.ResultsWe developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29–3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.ConclusionWe have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.

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.

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.

Hallmarks of Aromatase Inhibitor Drug Resistance Revealed by Epigenetic Profiling in Breast Cancer

Aromatase inhibitors are the major first-line treatment of estrogen receptor-positive breast cancer, but resistance to treatment is common. To date, no biomarkers have been validated clinically to guide subsequent therapy in these patients. In this study, we mapped the genome-wide chromatin-binding profiles of estrogen receptor α (ERα), along with the epigenetic modifications H3K4me3 and H3K27me3, that are responsible for determining gene transcription (n = 12). Differential binding patterns of ERα, H3K4me3, and H3K27me3 were enriched between patients with good or poor outcomes after aromatase inhibition. ERα and H3K27me3 patterns were validated in an additional independent set of breast cancer cases (n = 10). We coupled these patterns to array-based proximal gene expression and progression-free survival data derived from a further independent cohort of 72 aromatase inhibitor-treated patients. Through this approach, we determined that the ERα and H3K27me3 profiles predicted the treatment outcomes for first-line aromatase inhibitors. In contrast, the H3K4me3 pattern identified was not similarly informative. The classification potential of these genes was only partially preserved in a cohort of 101 patients who received first-line tamoxifen treatment, suggesting some treatment selectivity in patient classification.

Integrated genomics of chemotherapy resistant ovarian cancer: a role for extracellular matrix, TGFbeta and regulating microRNAs

Epithelial ovarian cancer is the sixth most common cancer in women worldwide and the most important cause of death from gynaecological cancers in the Western world. Our explorative pathway analysis on seven published gene-sets associated with platinum resistance in ovarian cancer reveals TP53 and transforming growth factor beta as key genes. Furthermore, the extracellular matrix was associated with chemotherapy resistance in ovarian cancer as well as endocrine resistance in breast cancer. Pathway analysis again revealed transforming growth factor beta as a key gene regulating extracellular matrix gene expression. A model is presented based on literature linking transforming growth factor beta, extracellular matrix, integrin signalling, epithelial to mesenchymal transition and regulating microRNAs with a (bivalent) role in chemotherapy response.

Downregulation of SIAH2, an ubiquitin E3 ligase, is associated with resistance to endocrine therapy in breast cancer

Purpose In our microarray analysis we observed that Seven-in-Absentia Homolog 2 (SIAH2) levels were low in estrogen receptor (ER) positive breast tumors of patients resistant to first-line tamoxifen therapy. The aim of this study was to evaluate SIAH2 for its (a) predictive/prognostic value, and (b) functional role in endocrine therapy resistance. Patients and methods SIAH2 expression was measured with quantitative Real-Time-PCR (qRT-PCR) in 1205 primary breast tumor specimens and related to disease outcome. The functional role of SIAH2 was determined in human breast cancer cell lines ZR-75-1, ZR/HERc, and MCF7. Cell lines were treated with estrogen (E2), anti-estrogen ICI164.384 or epidermal growth factor (EGF). Moreover, MCF7 was treated with ICI164.384 after silencing SIAH2 expression. Results SIAH2 was not prognostic in 603 lymph node negative patients who had not received adjuvant systemic therapy. In multivariate analysis of ER-positive tumors of 235 patients with recurrent disease, SIAH2 as continuous variable, significantly predicted first-line tamoxifen treatment failure (OR = 1.48; P = 0.05) and progression-free survival (PFS) (HR = 0.79; P = 0.007). Furthermore, in primary breast cancer patients treated with adjuvant tamoxifen, SIAH2 predicted metastasis-free survival (MFS) (HR = 0.73; P = 0.005). In vitro experiments showed that SIAH2 silencing in MCF7 cells resulted in resistance to ICI164.384-treatment when compared with mock silenced cells (P = 0.008). Interestingly, in ZR cells transfected with EGFR (ZR/HERc), SIAH2 expression was induced by E2 but downregulated by EGF. Conclusion In primary breast tumor specimens as well as in vitro low SIAH2 levels associated with resistance to endocrine therapy. Moreover, SIAH2 expression showed an opposite regulation by E2 and EGF.

Serum proteomic patterns for ovarian cancer monitoring

We set out to discover ovarian cancer biomarkers useful for monitoring progression during and after chemotherapy and possibly for diagnosis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry was used to create serum protein profiles of ovarian cancer patients before chemotherapy or at progression (n= 51) (trial initiated by the Gynecological Cancer Cooperative Group of the European Organization for Research and Treatment of Cancer trial) that were compared with those of healthy individuals (n= 31). In addition, sera profiles from ovarian cancer patients after chemotherapy (n= 12) were compared with those of ovarian cancer patients at progression (n= 24). One of the discovered biomarkers was identified and subsequently confirmed and validated using enzyme-linked immunosorbent assay (ELISA). Eight primary (sens = 94%, spec = 97%, P< 0.0001) and seven progression tumor biomarkers (sens = 91%, spec = 97%, P< 0.0001) were discovered. In addition, we discovered eight potential progression monitoring biomarkers (sens = 75%, spec = 83%, P= 0.0008) of which one, a biomarker of 11.7 kd, was further identified as serum amyloid A1. Independent validation (ELISA) showed an elevated expression of this protein at relapse in four of the seven ovarian cancer patients tested. Combining the eight newly discovered progression monitoring biomarkers with CA125 resulted in a clear increase of the sensitivity (91–100%). These biomarkers, in combination with for instance CA125, should be validated in large ovarian cancer and control groups. The resulting multimarker assay could be suitable for disease monitoring during and after therapy and might also be useful for ovarian cancer screening.

Cell-free DNA mutations as biomarkers in breast cancer patients receiving tamoxifen

The aim was to identify mutations in serum cell-free DNA (cfDNA) associated with disease progression on tamoxifen treatment in metastatic breast cancer (MBC). Sera available at start of therapy, during therapy and at disease progression were selected from 10 estrogen receptor (ER)-positive breast cancer patients. DNA from primary tumor and normal tissue and cfDNA from minute amounts of sera were analyzed by targeted next generation sequencing (NGS) of 45 genes (1,242 exons). At disease progression, stop-gain single nucleotide variants (SNVs) for CREBBP (1 patient) and SMAD4 (1 patient) and non-synonymous SNVs for AKAP9 (1 patient), PIK3CA (2 patients) and TP53 (2 patients) were found. Mutations in CREBBP and SMAD4 have only been occasionally reported in breast cancer. All mutations, except for AKAP9, were also present in the primary tumor but not detected in all blood specimens preceding progression. More sensitive detection by deeper re-sequencing and digital PCR confirmed the occurrence of circulating tumor DNA (ctDNA) and these biomarkers in blood specimens.