Judith Prinzler

Ki67 levels as predictive and prognostic parameters in pretherapeutic breast cancer core biopsies: a translational investigation in the neoadjuvant GeparTrio trial

BACKGROUND The proliferation marker Ki67 has been suggested as a promising cancer biomarker. As Ki67 needs an exact quantification, this marker is a prototype of a new generation of tissue-based biomarkers. In this study, we have systematically evaluated different cut points for Ki67 using three different clinical end points in a large neoadjuvant study cohort. PATIENTS AND METHODS We have evaluated pretherapeutic Ki67 levels by immunohistochemistry in 1166 breast cancer core biopsies from the neoadjuvant GeparTrio trial. We used the standardized cutoff-finder algorithm for three end points [response to neoadjuvant chemotherapy (pCR), disease-free (DFS) and overall-survival (OS)]. The analyses were stratified for hormone receptor (HR) and HER2 status by molecular subtype radar diagrams (MSRDs). RESULTS A wide range of Ki67 cut points between 3%-94% (for pCR), 6%-46% (for DFS) and 4%-58% (for OS) were significant. The three groups of Ki67 ≤ 15% versus 15.1%-35% versus >35% had pCR-rates of 4.2%, 12.8%, and 29.0% (P < 0.0005), this effect was also present in six of eight molecular subtypes. In MSRD, Ki67 was significantly linked to prognosis in uni- and multivariate analysis in the complete cohort and in HR-positive, but not triple-negative tumors. CONCLUSIONS Ki67 is a significant predictive and prognostic marker over a wide range of cut points suggesting that data-derived cut point optimization might not be possible. Ki67 could be used as a continuous marker; in addition, the scientific community could define standardized cut points for Ki67. Our analysis explains the variability observed for Ki67 cut points in previous studies; however, this should not be seen as weakness, but as strength of this marker. MSRDs are an easy new approach for visualization of biomarker effects on outcome across molecular subtypes in breast cancer. The experience with Ki67 could provide important information regarding the development and implementation of other quantitative biomarkers.

Differential expression of histone deacetylases HDAC1, 2 and 3 in human breast cancer - overexpression of HDAC2 and HDAC3 is associated with clinicopathological indicators of disease progression

BackgroundIn breast cancer, the role of epigenetic alterations including modifications of the acetylation status of histones in carcinogenesis has been an important research focus during the last years. An increased deacetylation of histones leads to increased cell proliferation, cell migration, angiogenesis and invasion. Class 1 histone deacetylases (HDAC) seem to be most important during carcinogenesis.MethodsThe immunhistochemical expression of HDAC1, 2 and 3 was analyzed on tissue microarrays (TMAs) from 238 patients with primary breast cancer. We analyzed the nuclear staining intensity (negative, weak, moderate, strong) as well as the percentage of positive tumor cells and calculated the immunoreactivity score (0–12). Expression was correlated with clinicopathological parameters and patient survival.ResultsIn this cohort, we found a differential positive expression of HDAC1, HDAC2 and HDAC3. HDAC2 and HDAC3 expression was significantly higher in less differentiated tumors: HDAC2 (n=207), p<0.001 and HDAC3 (n=220), p<0.001 and correlated with negative hormone receptor status: HDAC2 (n=206), p=0.02 and HDAC3 (n=219), p=0.04. Additionally, a high HDAC2 expression was significantly associated with an overexpression of HER2 (n=203, p=0.005) and the presence of nodal metastasis (n=200, p=0.04).HDAC1 was highly expressed in hormone receptor positive tumors (n=203; p<0.001).ConclusionAs a conclusion, our results show that the class-1 HDAC isoenzymes 1, 2 and 3 are differentially expressed in breast cancer. HDAC2 and HDAC3 are strongly expressed in subgroups of tumor with features of a more aggressive tumor type.

Decentral gene expression analysis for ER+/Her2− breast cancer: results of a proficiency testing program for the EndoPredict assay

Gene expression profiles provide important information about the biology of breast tumors and can be used to develop prognostic tests. However, the implementation of quantitative RNA-based testing in routine molecular pathology has not been accomplished, so far. The EndoPredict assay has recently been described as a quantitative RT-PCR-based multigene expression test to identify a subgroup of hormone–receptor-positive tumors that have an excellent prognosis with endocrine therapy only. To transfer this test from bench to bedside, it is essential to evaluate the test–performance in a multicenter setting in different molecular pathology laboratories. In this study, we have evaluated the EndoPredict (EP) assay in seven different molecular pathology laboratories in Germany, Austria, and Switzerland. A set of ten formalin-fixed paraffin-embedded tumors was tested in the different labs, and the variance and accuracy of the EndoPredict assays were determined using predefined reference values. Extraction of a sufficient amount of RNA and generation of a valid EP score was possible for all 70 study samples (100%). The EP scores measured by the individual participants showed an excellent correlation with the reference values, respectively, as reflected by Pearson correlation coefficients ranging from 0.987 to 0.999. The Pearson correlation coefficient of all values compared to the reference value was 0.994. All laboratories determined EP scores for all samples differing not more than 1.0 score units from the pre-defined references. All samples were assigned to the correct EP risk group, resulting in a sensitivity and specificity of 100%, a concordance of 100%, and a kappa of 1.0. Taken together, the EndoPredict test could be successfully implemented in all seven participating laboratories and is feasible for reliable decentralized assessment of gene expression in luminal breast cancer.

Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test

BackgroundEndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory.MethodsGene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability.ResultsPCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/μl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer’s laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units.ConclusionsThe EP test showed reproducible performance characteristics with good precision and negligible laboratory-to-laboratory variation. This study provides further evidence that the EP test is suitable for decentralized testing in specialized molecular pathological laboratories instead of a reference laboratory. This is a unique feature and a technical advance in comparison with existing RNA-based prognostic multigene expression tests.

Integration of metabolomics and expression of glycerol-3-phosphate acyltransferase (GPAM) in breast cancer-link to patient survival, hormone receptor status, and metabolic profiling

Changes in lipid metabolism are an important but not well-characterized hallmark of cancer. On the basis of our recent findings of lipidomic changes in breast cancer, we investigated glycerol-3-phosphate acyltransferase (GPAM), a key enzyme in the lipid biosynthesis of triacylglycerols and phospholipids. GPAM protein expression was evaluated and linked to metabolomic and lipidomic profiles in a cohort of human breast carcinomas. In addition, GPAM mRNA expression was analyzed using the GeneSapiens in silico transcriptiomics database. High cytoplasmic GPAM expression was associated with hormone receptor negative status (p = 0.013). On the protein (p = 0.048) and mRNA (p = 0.001) levels, increased GPAM expression was associated with a better overall survival. Metabolomic analysis by GC-MS showed that sn-glycerol-3-phosphate, the substrate of GPAM, was elevated in breast cancer compared to normal breast tissue. LC-MS based lipidomic analysis identified significantly higher levels of phospholipids, especially phosphatidylcholines in GPAM protein positive tumors. In conclusion, our results suggest that GPAM is expressed in human breast cancer with associated changes in the cellular metabolism, in particular an increased synthesis of phospholipids, the major structural component of cellular membranes.

The EndoPredict Gene-Expression Assay in Clinical Practice - Performance and Impact on Clinical Decisions

The validated EndoPredict assay is a novel tool to predict the risk of metastases of patients with estrogen receptor positive, HER2 negative breast cancer treated with endocrine therapy alone. It has been designed to integrate genomic and clinical information and includes clinico-pathological factors such as tumor size and nodal status. The test is feasible in a decentral setting in molecular pathology laboratories. In this project, we investigated the performance of this test in clinical practice, and performed a retrospective evaluation of its impact on treatment decisions in breast cancer. During one year, EndoPredict assays from 167 patients could be successfully performed. For retrospective evaluation of treatment decisions, a questionnaire was sent to the clinical partner. Regarding the molecular EP class, samples from 56 patients (33.5%) had a low-risk, whereas 111 patients (66.5%) showed a high-risk gene profile. After integration of the clinicopathological factors the combined clinical and molecular score (EPclin) resulted in a low-risk group of 77 patients (46.4%), while 89 (53.6%) had a high risk EPclin score. The EPclin-based estimated median 10-year-risk for metastases with endocrine therapy alone was 11% for the whole cohort. The median handling time averaged three days (range: 0 to 11 days), 59.3% of the tests could be performed in three or less than three days. Comparison of pre- and post-test therapy decisions showed a change of therapy in 37.7% of patients. 16 patients (12.3%) had a change to an additional chemotherapy while 25.4% of patients (n = 33) changed to an endocrine therapy alone. In 73 patients (56.2%) no change of therapy resulted. In 6.1% of patients (n = 8), the patients did not agree to the recommendation of the tumor board. Our results show that the EndoPredict assay could be routinely performed in decentral molecular pathology laboratories and the results markedly change treatment decisions.

HER2 and ESR1 mRNA expression levels and response to neoadjuvant trastuzumab plus chemotherapy in patients with primary breast cancer.

IntroductionRecent data suggest that benefit from trastuzumab and chemotherapy might be related to expression of HER2 and estrogen receptor (ESR1). Therefore, we investigated HER2 and ESR1 mRNA levels in core biopsies of HER2-positive breast carcinomas from patients treated within the neoadjuvant GeparQuattro trial.MethodsHER2 levels were centrally analyzed by immunohistochemistry (IHC), silver in situ hybridization (SISH) and qRT-PCR in 217 pretherapeutic formalin-fixed, paraffin-embedded (FFPE) core biopsies. All tumors had been HER2-positive by local pathology and had been treated with neoadjuvant trastuzumab/ chemotherapy in GeparQuattro.ResultsOnly 73% of the tumors (158 of 217) were centrally HER2-positive (cHER2-positive) by IHC/SISH, with cHER2-positive tumors showing a significantly higher pCR rate (46.8% vs. 20.3%, P <0.0005). HER2 status by qRT-PCR showed a concordance of 88.5% with the central IHC/SISH status, with a low pCR rate in those tumors that were HER2-negative by mRNA analysis (21.1% vs. 49.6%, P <0.0005). The level of HER2 mRNA expression was linked to response rate in ESR1-positive tumors, but not in ESR1-negative tumors. HER2 mRNA expression was significantly associated with pCR in the HER2-positive/ESR1-positive tumors (P = 0.004), but not in HER2-positive/ESR1-negative tumors.ConclusionsOnly patients with cHER2-positive tumors - irrespective of the method used - have an increased pCR rate with trastuzumab plus chemotherapy. In patients with cHER2-negative tumors the pCR rate is comparable to the pCR rate in the non-trastuzumab treated HER-negative population. Response to trastuzumab is correlated to HER2 mRNA levels only in ESR1-positive tumors. This study adds further evidence to the different biology of both subsets within the HER2-positive group.Introduction The human epidermal growth factor receptor 2 (HER2) is the prototype of a predictive biomarker for targeted treatment [1–8]. International initiatives have established the combination of immunohistochemistry (IHC) and in situ hybridization as the current gold standard [9, 10]. As an additional approach determination of HER2 mRNA expression is technically feasible in formalin-fixed paraffin-embedded (FFPE) tissue [11–13]. Crosstalk between the estrogen receptor (ER) and the HER2 pathway has been suggested based on cell culture and animal models [14]. Consequently, the 2011 St Gallen panel has pointed out that HER2-positive tumors should be divided into two groups based on expression of the ER [15].A retrospective analysis of the National Surgical Adjuvant Breast and Bowel Project (NSABP) B31 study has suggested that mRNA levels of HER2 and ESR1 might be relevant for the degree of benefit from adjuvant trastuzumab. By subpopulation treatment effect pattern plot (STEPP) analysis in ER-positive tumors, benefit from trastuzumab was shown to be restricted to those with higher levels of HER2 mRNA (S Paik, personal communication, results summarized in [15]).In our study we evaluated this hypothesis in the neoadjuvant setting in a cohort of 217 patients from the neoadjuvant GeparQuattro trial [5]. All patients had been HER2- positive by local pathology assessment and had received 24 to 36 weeks of neoadjuvant trastuzumab plus an anthracycline/taxane-based chemotherapy. For central evaluation we used three different methods, HER2 IHC, and HER2 silver in situ hybridization (SISH), as well as measurement of HER2 mRNA by quantitative real-time (qRT)-PCR [11].The primary objective of this analysis was to investigate if pathological complete response (pCR) rate in HER2-positive breast cancer would depend on the level of HER2 mRNA expression, with a separate analysis for HR-positive and -negative tumors. Central evaluation of the HER2 status showed that 27% of the tumors with HER2 overexpression by local pathology were HER2-negative. This enabled us to compare response rates in patients with HER2-positive and -negative tumors as a secondary objective.

Analysis of PIK3CA mutations in breast cancer subtypes.

Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit &agr; (PIK3CA) is a central element of a signaling pathway involved in cell proliferation, survival, and growth. Certain mutations in this pathway result in enhanced PI3K signaling, which is associated with oncogenic cellular transformation and cancer. The aims of this study were to characterize different types of PIK3CA mutations in exons 9 and 20 in a series of primary breast carcinomas and to correlate the results with clinicopathologic parameters and survival. We used frozen tissue samples and sequenced exons 9 and 20 for a series of 241 patients with a diagnosis of breast carcinoma. We found that 15.8% of the primary breast carcinomas possessed PIK3CA mutations in either exon 9 or exon 20. The rate of PIK3CA mutations was increased in HR+/HER2− tumors (18.6%), but this difference did not reach a statistical significance. The lowest rate of mutations was observed in HR+/HER2+ tumors (5.3%). No statistically significant association was found between the presence of PIK3CA mutations and the prognostic/clinical features of breast cancer, including histologic subtype, Her2 status, axillary lymph node involvement, tumor grade, and tumor stage. However, the presence of the H1047R mutation in 10 samples was associated with a statistically significantly worse overall survival. PIK3CA mutation was found to be a frequent genetic change in all breast cancer subtypes but occurred with the highest rate in HR+/HER2− tumors. Further studies are needed to validate the prognostic impact of different PIK3CA mutations.

Aldehyde dehydrogenase 1/epidermal growth factor receptor coexpression is characteristic of a highly aggressive, poor-prognosis subgroup of high-grade serous ovarian carcinoma

In models of triple-negative breast cancer (TNBC), it has recently been shown that the epidermal growth factor receptor (EGFR) pathway is up-regulated in the aldehyde dehydrogenase 1 (ALDH1)-positive cancer stem cell fraction. Because high-grade serous ovarian carcinoma (HGSC) reveals strong molecular similarities to TNBC, we aimed to investigate the potential link between ALDH1 and EGFR in this entity. Expression of ALDH1 was investigated in 131 primary HGSCs using immunohistochemistry. Expression data were correlated with EGFR expression as well as with clinicopathologic parameters and survival. Forty-two carcinomas (32.1%) were positive for ALDH1 protein expression. Data on EGFR expression were available for 112 tumors. In these cases ALDH1 was significantly linked to EGFR expression (P < .0001). ALDH1 positivity was a significant negative prognostic factor for overall survival both in univariate (P = .010) and in multivariate survival analyses (P = .041). Tumors that were positive for both ALDH1 and EGFR had an exceptionally bad prognosis as compared with carcinomas with 1 or both markers negative in univariate analysis (P < .0001) and in the multivariate setting (P = .004). Our study suggests that similar to TNBC, there is a link between ALDH1 and EGFR expression in HGSC. Double positivity for both markers identifies a subgroup of highly aggressive, poor-prognosis cancers for which alternative treatment options-potentially EGFR-targeting drugs-should be evaluated.

Comparison of the RNA-based EndoPredict multigene test between core biopsies and corresponding surgical breast cancer sections

Aim This study compared the perfomance of the RNA-based EndoPredict multigene test on core biopsies and surgical breast cancer specimens and analysed the influence of biopsy-induced tissue injuries on the test result. Methods 80 formalin-fixed paraffin-embedded samples comprising paired biopsies and surgical specimens from 40 ER-positive, HER2-negative patients were evaluated. Total RNA was extracted and the EndoPredict score was determined. Results RNA yield was considerably lower in core biopsies, but sufficient to measure the assay in all samples. The EndoPredict score was highly correlated between paired samples (Pearson r=0.92), with an excellent concordance of classification into a low or high risk of metastasis (overall agreement 95%). Conclusions The measurements are comparable between core biopsies and surgical sections, which suggest that the EndoPredict assay can be performed on core biopsy tissue. Inflammatory changes induced by presurgical biopsies had no significant effect on the RNA-based risk assessment in surgical specimens.