A specific gene expression signature for visceral organ metastasis in breast cancer

BACKGROUND

Visceral organ metastasis is associated with poor survival outcomes in terms of metastasis free- and overall survival in breast carcinomas. Identification of a gene expression profile in tumours that selects a subpopulation of patients that is more likely to develop visceral organ metastases will help elucidate mechanisms for the development of distant metastases and could be of clinical value. With this study we aimed to determine genomic predictors that would help to distinguish breast cancer patients with more likelihood to develop visceral metastasis.

METHODS

Gene expression profiling data of 157 primary tumours from breast cancer patients who developed distant metastases were analyzed and differentially expressed genes between the group of tumours with visceral metastasis and the those without visceral metastases were identified. Published data were used to validate our findings. Multivariate logistic regression tests were applied to further investigate the association between the gene-expression-signature and clinical variables. Survival analyses were performed by the Kaplan-Meier method.

RESULTS

Fourteen differentially expressed genes (WDR6, CDYL, ATP6V0A4, CHAD, IDUA, MYL5, PREP, RTN4IP1, BTG2, TPRG1, ABHD14A, KIF18A, S100PBP and BEND3) were identified between the group of tumours with and without visceral metastatic disease. Five of these genes (CDYL, ATP6V0A4, PREP, RTN4IP1 and KIF18A) were up-regulated and the other genes were down-regulated. This gene expression signature was validated in the training and in the independent data set (p 2.13e- 08 and p 9.68e- 06, respectively). Multivariate analyses revealed that the 14-gene-expression-signature was associated with visceral metastatic disease (p 0.001, 95% CI 1.43-4.27), independent of other clinicopathologic features. This signature has been also found to be associated with survival status of the patients (p < .001).

CONCLUSION

We have identified an unique gene expression signature which is specific to visceral metastasis. This 14-gene-expression-signature may play a role in identifying the subgroup of patients with potential to develop visceral metastasis.

Epithelial-to-mesenchymal transition status of primary breast carcinomas and its correlation with metastatic behavior

Background

Epithelial-to-mesenchymal transition (EMT) has been implicated as an important step in the development of distant metastases. We therefore wished to study EMT status of primary breast carcinomas from patients who during follow-up developed distant metastases.

Methods

mRNA expression profiles of primary breast carcinoma samples (n = 151) from patients who developed metastatic disease were analyzed and EMT status was designated using a previously described EMT-core signature. EMT status of the primary tumor was correlated to clinicopathological characteristics, molecular subtypes, metastasis pattern, chemotherapy response and survival outcomes. In addition, using immunohistochemistry, the expression levels of several proteins implicated in EMT were studied (CDH1, CDH2, NAT1, SNAI2, TWIST1, VIM, and ZEB1) compared with the designated EMT status and survival.

Results

Utilizing the 130-gene-EMT-core signature, 66.2% of the primary tumors in the current study was assessed as EMT-activated. In contrast to our expectations, analyses revealed that 84.6% of Luminal A tumors, 65.1% of Luminal B tumors, and 55.6% of HER2-like had an activated EMT status, compared to only 25% of the basal-type tumors (p < 0.001). EMT status was not correlated to the pattern of metastatic disease, metastasis-specific survival, and overall survival. Similarly, there was not a significant association between EMT status of the primary tumor and chemotherapy response in the metastatic setting. Immunostaining for NAT1 and TWIST1 correlated with the EMT status (p 0.003 and p 0.047, respectively). Multivariate analyses showed that NAT1 and TWIST1 staining was significantly associated with EMT status regardless of the estrogen receptor status of the tumors (p values: 0.020 and 0.027, respectively).

Conclusions

The EMT status of breast cancers, as defined by the presence of a core EMT gene expression signature is associated with non-basal-type tumors, but not with the pattern of distant metastasis. Of several potential immunohistochemical EMT markers, only NAT1 and TWIST1 expression levels were associated with the gene expression-based EMT status.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-05089-5) contains supplementary material, which is available to authorized users.

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.

Validation of 70-gene prognosis signature in node-negative breast cancer

PURPOSE

The 70-gene prognosis signature (van't Veer et al., Nature 415(6871):530-536, 2002) may improve the selection of lymph node-negative breast cancer patients for adjuvant systemic therapy. Optimal validation of prognostic classifiers is of great importance and we therefore wished to evaluate the prognostic value of the 70-gene prognosis signature in a series of relatively recently diagnosed lymph node negative breast cancer patients.

METHODS

We evaluated the 70-gene prognosis signature in an independent representative series of patients with invasive breast cancer (N = 123; <55 years; pT1-2N0; diagnosed between 1996 and 1999; median follow-up 5.8 years) by classifying these patients as having a good or poor prognosis signature. In addition, we updated the follow-up of the node-negative patients of the previously published validation-series (Van de Vijver et al., N Engl J Med 347(25):1999-2009, 2002; N = 151; median follow-up 10.2 years). The prognostic value of the 70-gene prognosis signature was compared with that of four commonly used clinicopathological risk indexes. The endpoints were distant metastasis (as first event) free percentage (DMFP) and overall survival (OS).

RESULTS

The 5-year OS was 82 +/- 5% in poor (48%) and 97 +/- 2% in good prognosis signature (52%) patients (HR 3.4; 95% CI 1.2-9.6; P = 0.021). The 5-years DMFP was 78 +/- 6% in poor and 98 +/- 2% in good prognosis signature patients (HR 5.7; 95% CI 1.6-20; P = 0.007). In the updated series (N = 151; 60% poor vs. 40% good), the 10-year OS was 51 +/- 5% and 94 +/- 3% (HR 10.7; 95% CI 3.9-30; P < 0.01), respectively. The DMFP was 50 +/- 6% in poor and 86 +/- 5% in good prognosis signature patients (HR 5.5; 95% CI 2.5-12; P < 0.01). In multivariate analysis, the prognosis signature was a strong independent prognostic factor in both series, outperforming the clinicopathological risk indexes.

CONCLUSION

The 70-gene prognosis signature is also an independent prognostic factor in node-negative breast cancer patients for women diagnosed in recent years.

Prospective analysis of mRNA expression signatures as predictive tests in primary breast cancer

2531

Background: Preoperative chemotherapy is increasingly employed to treat primary breast cancer, allowing an ‘in vivo chemosensitivity test’. Markers which predict a pathological complete response are urgently needed to refine this strategy. This study was conducted to evaluate the use of gene expression profiling to predict response to neoadjuvant anthracycline- or taxane-based chemotherapy. Methods: Patients with operable or locally advanced HER2-negative breast cancer received preoperative chemotherapy: either dose- dense doxorubicin and cyclophosphamide (ddAC) or capecitabine and docetaxel (CD). Core needle biopsies were taken before treatment and gene expression profiling was performed using 35k oligo microarrays. Results: Gene expression profiles were obtained from pretreatment biopsies of 63 tumors. 27% of the patients achieved a (near) pathologic complete remission (pCR), 40% of the patients had a partial remission and 33% of the patients did not respond to chemotherapy. Based on the gene expression profiles, tumors were assigned to the previously identified “molecular subtypes” luminal, basal-like or ERBB2-like (Sorlie et al., PNAS 98: 10869, 2001). 13 out of 25 patients with a basal-like tumor (52%) achieved a complete remission, whereas for the luminal tumors a pCR was only obtained in 2 out of 29 patients. Using four published gene expression classifiers of response to chemotherapy, a reasonable separation between responders and non-responders could be observed for two of these. We also performed exploratory supervised classification analyses on our dataset to identify a novel classifier. This resulted in a classifier for response to therapy irrespective of the chemotherapy regimen used and a second classifier specifically associated with response to ddAC chemotherapy. We will perform validation of these classifiers in samples from patients that are currently being enrolled in the study. Conclusions: Basal-like tumors have a better response to neoadjuvant chemotherapy as compared to other tumor types. The identification of robust gene expression signatures for better response prediction may require larger patient groups and should probably be established separately for each of the molecular subtypes of breast cancer.

No significant financial relationships to disclose.

Prediction of response to neoadjuvant chemotherapy in breast cancer

20005

Background: Neoadjuvant chemotherapy is increasingly employed in operable breast cancer. Our initial studies on a cDNA array platform failed to identify gene expression patterns predicting response to neoadjuvant chemotherapy in breast cancer patients (J Clin Oncol 23:3331, 2005). Now we included more patients and used oligo microarrays. Methods: Patients with operable or locally advanced breast cancer were included in a randomized phase II study or received neoadjuvant chemotherapy off protocol. All except 7 patients began chemotherapy with 3 courses of dose-dense adriamycin and cyclophosphamide (ddAC) and response was evaluated by MRI. Patients with a response and a HER2-positive tumor were then randomized between either 3 additional courses of ddAC or six weekly courses of carboplatin, paclitaxel and trastuzumab (CPT). Patients without response were switched to CPT. Patients with HER2-negative tumors were randomized between 3 courses of either ddAC or capecitabine and docetaxel (CD). After evaluation, patients without response were switched to the alternative treatment arm. From all patients 14G core needle biopsies were taken before treatment and total RNA was isolated. Amplified mRNA was labeled and hybridized to 35k human oligo microarrays from our microarray facility. Results: So far, 77 patients have been included into the study. From 48 of these, good quality RNA from tissue with >50% tumor cells was isolated. 43 patients had received ddAC as initial chemotherapy; 32 of these had not been switched to another regimen. In a training set containing 11 pathological complete remissions (pCR) and 9 non-responders (NR) we could separate these groups by using 20 genes in a supervised classification and a 9-step cross validation. These results could be validated in an independent set of 11 samples (6 pCR, 5 NR). From 10 out of 11 samples, response status could be predicted correctly, independent from the treatment regimen. Although ER-positive tumors have a lower pCR rate than ER-negative ones, the steroid hormone receptors were not present in the classifier. Conclusions: We conclude that it should be possible to identify a reliable gene expression profile associated with response to adriamycin based neoadjuvant chemotherapy in breast cancer.

No significant financial relationships to disclose.