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1.  Accumulated metabolites of hydroxybutyric acid serve as diagnostic and prognostic biomarkers of ovarian high-grade serous carcinomas 
Cancer research  2015;76(4):796-804.
Ovarian cancer is a heterogeneous disease of low prevalence, but poor survival. Early diagnosis is critical for survival, but is often challenging because the symptoms of ovarian cancer are subtle and become apparent only during advanced stages of the disease. Therefore, the identification of robust biomarkers of early disease is a clinical priority. Metabolomic profiling is an emerging diagnostic tool enabling the detection of biomarkers reflecting alterations in tumor metabolism, a hallmark of cancer. In this study, we performed metabolomic profiling of serum and tumor tissue from 158 patients with high-grade serous ovarian cancer (HGSOC) and 100 control patients with benign or non-neoplastic lesions. We report metabolites of hydroxybutyric acid (HBA) as novel diagnostic and prognostic biomarkers associated with tumor burden and patient survival. The accumulation of HBA metabolites caused by HGSOC was also associated with reduced expression of succinic semialdehyde dehydrogenase (encoded by ALDH5A1), and with the presence of an epithelial-to-mesenchymal transition (EMT) gene signature, implying a role for these metabolic alterations in cancer cell migration and invasion. In conclusion, our findings represent the first comprehensive metabolomics analysis in HGSOC and propose a new set of metabolites as biomarkers of disease with diagnostic and prognostic capabilities.
doi:10.1158/0008-5472.CAN-15-2298
PMCID: PMC4762194  PMID: 26685161
biomarker; metabolism; ketone body; hydroxybutyric acid; ovarian high-grade serous carcinoma
2.  Ioncopy: a novel method for calling copy number alterations in amplicon sequencing data including significance assessment 
Oncotarget  2016;7(11):13236-13247.
Recently, it has been demonstrated that calling of copy number alterations (CNAs) from amplicon sequencing (AS) data is feasible. Most approaches, however, require non-tumor (germline) DNA for data normalization. Here, we present the method Ioncopy for CNA detection which requires no normal controls and includes a significance assessment for each detected alteration.
Ioncopy was evaluated in a cohort of 184 clinically annotated breast carcinomas. A total number of 252 amplifications were detected, of which 183 (72.6%) could be validated by a call of an additional amplicon interrogating the same gene. Moreover, a total number of 33 deletions were found, whereof 27 (81.8%) could be validated. Analyzing the 16 most frequently amplified genes, validation rates of over 89% could be achieved for 11 of these genes. 11 of the top 16 genes showed significant overexpression in the amplified tumors. 89.5% of the HER2-amplified tumors were GRB7 and STARD3 co-amplified, whereas 68.4% of the HER2-amplified tumors had additional MED1 amplifications. Correlations between CNAs measured by amplicons in HER2 exons 19, 20 and 21 were strong (all R > 0.93). AS based detection of HER2 amplifications had a sensitivity of 90.0% and a specificity of 98.8% compared to the gold standard of HER2 immunohistochemistry combined with in situ hybridization.
In summary, we developed and validated a novel method for detection and significance assessment of CNAs in amplicon sequencing data. Using Ioncopy, AS offers a straightforward and efficient approach to simultaneously analyze gene amplifications and gene deletions together with simple somatic mutations in a single assay.
doi:10.18632/oncotarget.7451
PMCID: PMC4914355  PMID: 26910888
targeted sequencing; amplicon sequencing; semiconductor sequencing; copy number alterations; breast cancer
3.  Prognostic impact of programmed cell death-1 (PD-1) and PD-ligand 1 (PD-L1) expression in cancer cells and tumor-infiltrating lymphocytes in ovarian high grade serous carcinoma 
Oncotarget  2015;7(2):1486-1499.
Aims
Antibodies targeting the checkpoint molecules programmed cell death 1 (PD-1) and its ligand PD-L1 are emerging cancer therapeutics. We systematically investigated PD-1 and PD-L1 expression patterns in the poor-prognosis tumor entity high-grade serous ovarian carcinoma.
Methods
PD-1 and PD-L1 protein expression was determined by immunohistochemistry on tissue microarrays from 215 primary cancers both in cancer cells and in tumor-infiltrating lymphocytes (TILs). mRNA expression was measured by quantitative reverse transcription PCR. An in silico validation of mRNA data was performed in The Cancer Genome Atlas (TCGA) dataset.
Results
PD-1 and PD-L1 expression in cancer cells, CD3+, PD-1+, and PD-L1+ TILs densities as well as PD-1 and PD-L1 mRNA levels were positive prognostic factors for progression-free (PFS) and overall survival (OS), with all factors being significant for PFS (p < 0.035 each), and most being significant for OS. Most factors also had prognostic value that was independent from age, stage, and residual tumor. Moreover, high PD-1+ TILs as well as PD-L1+ TILs densities added prognostic value to CD3+TILs (PD-1+: p = 0.002,; PD-L1+: p = 0.002). The significant positive prognostic impact of PD-1 and PD-L1 mRNA expression could be reproduced in the TCGA gene expression datasets (p = 0.02 and p < 0.0001, respectively).
Conclusions
Despite their reported immune-modulatory function, high PD-1 and PD-L1 levels are indicators of a favorable prognosis in ovarian cancer. Our data indicate that PD-1 and PD-L1 molecules are biologically relevant regulators of the immune response in high-grade serous ovarian carcinoma, which is an argument for the evaluation of immune checkpoint inhibiting drugs in this tumor entity.
PMCID: PMC4811475  PMID: 26625204
high grade serous carcinoma; ovarian; PD-1; PD-L1; tumor-infiltrating lymphocytes
4.  Comparison of targeted next-generation sequencing and Sanger sequencing for the detection of PIK3CA mutations in breast cancer 
Background
Phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha, PIK3CA, is one of the most frequently mutated genes in breast cancer, and the mutation status of PIK3CA has clinical relevance related to response to therapy.
The aim of our study was to investigate the mutation status of PIK3CA gene and to evaluate the concordance between NGS and SGS for the most important hotspot regions in exon 9 and 20, to investigate additional hotspots outside of these exons using NGS, and to correlate the PIK3CA mutation status with the clinicopathological characteristics of the cohort.
Methods
In the current study, next-generation sequencing (NGS) and Sanger Sequencing (SGS) was used for the mutational analysis of PIK3CA in 186 breast carcinomas.
Results
Altogether, 64 tumors had PIK3CA mutations, 55 of these mutations occurred in exons 9 and 20. Out of these 55 mutations, 52 could also be detected by Sanger sequencing resulting in a concordance of 98.4 % between the two sequencing methods. The three mutations missed by SGS had low variant frequencies below 10 %. Additionally, 4.8 % of the tumors had mutations in exons 1, 4, 7, and 13 of PIK3CA that were not detected by SGS. PIK3CA mutation status was significantly associated with hormone receptor-positivity, HER2-negativity, tumor grade, and lymph node involvement. However, there was no statistically significant association between the PIK3CA mutation status and overall survival.
Conclusions
Based on our study, NGS is recommended as follows: 1) for correctly assessing the mutation status of PIK3CA in breast cancer, especially for cases with low tumor content, 2) for the detection of subclonal mutations, and 3) for simultaneous mutation detection in multiple exons.
Electronic supplementary material
The online version of this article (doi:10.1186/s12907-015-0020-6) contains supplementary material, which is available to authorized users.
doi:10.1186/s12907-015-0020-6
PMCID: PMC4652376  PMID: 26587011
Next-generation sequencing; Breast cancer; Sanger sequencing; PIK3CA
5.  Constitutive phosphorylated STAT3-associated gene signature is predictive for trastuzumab resistance in primary HER2-positive breast cancer 
BMC Medicine  2015;13:177.
Background
The likelihood of recurrence in patients with breast cancer who have HER2-positive tumors is relatively high, although trastuzumab is a remarkably effective drug in this setting. Signal transducer and activator of transcription 3 protein (STAT3), a transcription factor that is persistently tyrosine-705 phosphorylated (pSTAT3) in response to numerous oncogenic signaling pathways, activates downstream proliferative and anti-apoptotic pathways. We hypothesized that pSTAT3 expression in HER2-positive breast cancer will confer trastuzumab resistance.
Methods
We integrated reverse phase protein array (RPPA) and gene expression data from patients with HER2-positive breast cancer treated with trastuzumab in the adjuvant setting.
Results
We show that a pSTAT3-associated gene signature (pSTAT3-GS) is able to predict pSTAT3 status in an independent dataset (TCGA; AUC = 0.77, P = 0.02). This suggests that STAT3 induces a characteristic set of gene expression changes in HER2-positive cancers. Tumors characterized as high pSTAT3-GS were associated with trastuzumab resistance (log rank P = 0.049). These results were confirmed using data from the prospective, randomized controlled FinHer study, where the effect was especially prominent in HER2-positive estrogen receptor (ER)-negative tumors (interaction test P = 0.02). Of interest, constitutively activated pSTAT3 tumors were associated with loss of PTEN, elevated IL6, and stromal reactivation.
Conclusions
This study provides compelling evidence for a link between pSTAT3 and trastuzumab resistance in HER2-positive primary breast cancers. Our results suggest that it may be valuable to add agents targeting the STAT3 pathway to trastuzumab for treatment of HER2-positive breast cancer.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-015-0416-2) contains supplementary material, which is available to authorized users.
doi:10.1186/s12916-015-0416-2
PMCID: PMC4522972  PMID: 26234940
Breast cancer; FinHer; HER2; Phosphorylated STAT3; Randomised trial; Trastuzumab resistance
6.  Classical pathology and mutational load of breast cancer – integration of two worlds 
Abstract
Breast cancer is a complex molecular disease comprising several biological subtypes. However, daily routine diagnosis is still based on a small set of well‐characterized clinico‐pathological variables. Here, we try to link the two worlds of surgical pathology and multilayered molecular profiling by analyzing the relationships between clinico‐pathological phenotypes and mutational loads of breast cancer. We evaluated the number of mutated genes with somatic non‐silent mutations in different subgroups of breast cancer based on clinico‐pathological, including immunohistochemical and tumour characteristics. The analysis was performed for a cohort of 687 primary breast cancer patients with mutational profiling, gene expression and clinico‐pathological data available from The Cancer Genome Atlas (TCGA) project. The number of mutated genes was strongly positively associated with higher tumour grade (p = 1.4e−14) and with the different immunohistochemical and PAM50 molecular subtypes of breast cancer (p = 1.4e−10 and p = 4.3e−10, respectively). We observed significant associations (|R| > 0.4) between the abundance of mutated genes and expression levels of genes related to proliferation in the overall cohort and hormone receptor positive cohort, including the Recurrence Score gene signature (e.g., MYBL2 and BIRC5). Specific mutated genes (TP53, NCOR1, NF1, PTPRD and RB1) were highly significantly associated with high loads of mutated genes. Multivariate analysis for overall survival (OS) revealed a worse survival for patients with high numbers of mutated genes (hazard ratio = 4.6, 95% CI: 1.0 – 20.0, p = 0.044). Here, we report a strong association of the number of mutated genes with immunohistochemical and PAM50 subtypes and tumour grade in breast cancer. We provide evidence that specific levels of the mutational load underlie different morphological and biological phenotypes, which collectively constitute the current basis of pathological diagnosis. Our study is a step towards genomics‐informed breast pathology and will provide a basis for future studies in this field bridging the gap between morphology, tumour biology and medical oncology.
doi:10.1002/cjp2.25
PMCID: PMC4939893  PMID: 27499907
breast cancer; clinical parameters; pathology; staging; tumour grade; tumour size; genetics; mutations; prognosis
7.  Tumor-infiltrating lymphocytes in breast cancer 
Oncoimmunology  2014;3:e27926.
We have prospectively validated in an independent clinical cohort the finding that elevated amounts of tumor-infiltrating lymphocytes in breast carcinoma tissues predict the response of patients to neoadjuvant chemotherapy. These results suggest that a robust tumor infiltration by T and B cells is a promising biomarker to define patients who might benefit from neoadjuvant chemotherapy.
doi:10.4161/onci.27926
PMCID: PMC4203634  PMID: 25340002
biological marker; breast cancer; neoadjuvant chemotherapy; response predictor
8.  The landscape of metastatic progression patterns across major human cancers 
Oncotarget  2014;6(1):570-583.
The majority of patients with solid malignancies die from metastatic burden. However, our current understanding of the mechanisms and resulting patterns of dissemination is limited. Here, we analyzed patterns of metastatic progression across 16 major cancer types in a cohort of 1008 patients with metastatic cancer autopsied between 2000 and 2013 to assess cancer specific progression patterns of disease and related risk predictions. The frequency and location of metastases were evaluated in and across 1) 16 major cancers, 2) smoking- and non-smoking-related cancers and 3) adeno- and squamous cell carcinoma. Associations between primary and secondary sites were analyzed by the fractional and the relative risk methods. We detected significantly different cancer specific patterns of metastatic progression with specific relative risk profiles for secondary site involvement. Histology and smoking etiology influenced these patterns. Backward analysis showed that metastatic patterns help to predict unknown primary sites. Solid malignancies maintain a unique and recurrent organ tropism to specific secondary sites which does not appear to be strongly influenced by advances in cancer medicine as shown by comparison with previous data sets. The delineated landscape of metastatic progression patterns is a comprehensive data resource to both clinical and basic scientists which aids fostering new hypotheses for cancer research and cancer therapies.
PMCID: PMC4381616  PMID: 25402435
autopsy; metastasis; systemic disease; carcinoma; solid tumor; cancer; survival
9.  MEK1 is associated with carboplatin resistance and is a prognostic biomarker in epithelial ovarian cancer 
BMC Cancer  2014;14:837.
Background
Primary systemic treatment for ovarian cancer is surgery, followed by platinum based chemotherapy. Platinum resistant cancers progress/recur in approximately 25% of cases within six months. We aimed to identify clinically useful biomarkers of platinum resistance.
Methods
A database of ovarian cancer transcriptomic datasets including treatment and response information was set up by mining the GEO and TCGA repositories. Receiver operator characteristics (ROC) analysis was performed in R for each gene and these were then ranked using their achieved area under the curve (AUC) values. The most significant candidates were selected and in vitro functionally evaluated in four epithelial ovarian cancer cell lines (SKOV-3-, CAOV-3, ES-2 and OVCAR-3), using gene silencing combined with drug treatment in viability and apoptosis assays. We collected 94 tumor samples and the strongest candidate was validated by IHC and qRT-PCR in these.
Results
All together 1,452 eligible patients were identified. Based on the ROC analysis the eight most significant genes were JRK, CNOT8, RTF1, CCT3, NFAT2CIP, MEK1, FUBP1 and CSDE1. Silencing of MEK1, CSDE1, CNOT8 and RTF1, and pharmacological inhibition of MEK1 caused significant sensitization in the cell lines. Of the eight genes, JRK (p = 3.2E-05), MEK1 (p = 0.0078), FUBP1 (p = 0.014) and CNOT8 (p = 0.00022) also correlated to progression free survival. The correlation between the best biomarker candidate MEK1 and survival was validated in two independent cohorts by qRT-PCR (n = 34, HR = 5.8, p = 0.003) and IHC (n = 59, HR = 4.3, p = 0.033).
Conclusion
We identified MEK1 as a promising prognostic biomarker candidate correlated to response to platinum based chemotherapy in ovarian cancer.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2407-14-837) contains supplementary material, which is available to authorized users.
doi:10.1186/1471-2407-14-837
PMCID: PMC4247127  PMID: 25408231
Ovarian cancer; Chemotherapy; Carboplatin; MEK
10.  Mutational profiles in triple-negative breast cancer defined by ultradeep multigene sequencing show high rates of PI3K pathway alterations and clinically relevant entity subgroup specific differences 
Oncotarget  2014;5(20):9952-9965.
Mutational profiling of triple-negative breast cancer (TNBC) by whole exome sequencing (WES) yielded a landscape of genomic alterations in this tumor entity. However, the clinical significance of these findings remains enigmatic. Further, integration of WES in routine diagnostics using formalin-fixed paraffin-embedded (FFPE) material is currently not feasible.
Therefore, we designed and validated a breast cancer specific gene panel for semiconductor-based sequencing comprising 137 amplicons covering mutational hotspots in 44 genes and applied this panel on a cohort of 104 well-characterized FFPE TNBC with complete clinical follow-up.
TP53 mutations were present in more than 80% of cases. PI3K pathway alterations (29.8%) comprising mainly PIK3CA mutations (22.1%) but also mutations and/or amplifications/deletions in other PI3K-associated genes (7.7%) were far more frequently observed, when compared to WES data. Alterations in MAPK signaling genes (8.7%) and cell-cycle regulators (14.4%) were also frequent. Mutational profiles were linked to TNBC subgroups defined by morphology and immunohistochemistry. Alterations in cell-cycle pathway regulators were linked with better overall (p=0.053) but not disease free survival.
Taken together, we could demonstrate that breast cancer targeted hotspot sequencing is feasible in a routine setting and yields reliable and clinically meaningful results. Mutational spectra were linked to clinical and immunohistochemically defined parameters.
PMCID: PMC4259450  PMID: 25296970
triple-negative breast cancer; next generation sequencing; immunohistochemistry; mutation profiling
11.  Preanalytical variables and performance of diagnostic RNA-based gene expression analysis in breast cancer 
Virchows Archiv  2014;465(4):409-417.
Prognostic multigene expression assays have become widely available to provide additional information to standard clinical parameters and to support clinicians in treatment decisions. In this study, we analyzed the impact of variations in tissue handling on the diagnostic EndoPredict test results. EndoPredict is a quantitative reverse transcription PCR assay conducted on RNA from formalin-fixed, paraffin-embedded (FFPE) tissue that predicts the likelihood of distant recurrence in patients with ER-positive/HER2-negative breast cancer. In this study, we performed a total of 138 EndoPredict assays to study the effects of preanalytical variables such as time to fixation, fixation time, tumor cell content, and section storage time on the EndoPredict test results. A time to fixation of up to 12 h and fixation of up to 5 days did not affect the results of the gene expression test. Paired samples of FFPE sections with tumor cell content ranging from 15 to 95 % and tumor-enriched samples showed a correlation coefficient of 0.97. Test results of tissue sections that have been stored for 12 months at +4 or +20 °C showed a correlation of 0.99 when compared to results of nonstored sections. In conclusion, preanalytical tissue handling is not a critical factor for diagnostic gene expression analysis with the EndoPredict assay. The test can therefore be easily integrated into the standard workflow of molecular pathology.
doi:10.1007/s00428-014-1652-0
PMCID: PMC4180906  PMID: 25218890
Breast cancer; Preanalytical; EndoPredict; Molecular pathology; Gene expression
12.  Co-expression of MET and CD47 is a novel prognosticator for survival of luminal-type breast cancer patients 
Oncotarget  2014;5(18):8147-8160.
Although luminal-type primary breast cancer can be efficiently treated, development of metastatic disease remains a significant clinical problem. We have previously shown that luminal-type circulating tumor cells (CTCs) co-expressing the tyrosine-kinase MET and CD47, a ligand involved in cancer cell evasion from macrophage scavenging, are able to initiate metastasis in xenografts. Here, we investigated the clinical relevance of MET-CD47 co-expression in 255 hormone receptor positive breast tumors by immunohistochemistry and found a 10.3-year mean overall-survival difference between MET-CD47 double-positive and double-negative patients (p<0.001). MET-CD47 co-expression defined a novel independent prognosticator for overall-survival by multivariate analysis (Cox proportional hazards model: HR: 4.1, p<0.002) and CD47 expression alone or in combination with MET was strongly associated with lymph node metastasis. Furthermore, flow cytometric analysis of metastatic patient blood revealed consistent presence of MET+CD47+ CTCs (range 0.8 – 33.3% of CTCs) and their frequency was associated with increased metastatic spread. Finally, primary uncultured CTCs with high MET+CD47+ content showed an enhanced capacity to initiate metastasis in mice. Detection and targeting of MET and CD47 may thus provide a rational basis for risk stratification and treatment of patients with luminal-type breast cancer.
PMCID: PMC4226673  PMID: 25230070
breast cancer; prognosis; biomarker; CD47; MET; metastasis; circulating tumor cells; metastasis-stem cell
13.  Gross cystic disease fluid protein 15 (GCDFP-15) expression in breast cancer subtypes 
BMC Cancer  2014;14:546.
Background
Gross cystic disease fluid protein 15 (GCDFP-15), which is regulated by the androgen receptor (AR), is a diagnostic marker for mammary differentiation in histopathology. We determined the expression of GCDFP-15 in breast cancer subtypes, its potential prognostic and predictive value, as well as its relationship to AR expression.
Methods
602 pre-therapeutic breast cancer core biopsies from the phase III randomized neoadjuvant GeparTrio trial (NCT00544765) were investigated for GCDFP-15 expression by immunohistochemistry. Expression data were correlated with disease-free (DFS) and overall survival (OS) time as well as pathological complete response (pCR) to neoadjuvant chemotherapy.
Results
239 tumors (39.7%) were GCDFP-15 positive. GCDFP-15 expression was positively linked to hormone receptor (HR) and HER2 positive tumor type, while most triple negative carcinomas were negative (p < 0.0001). GCDFP-15 was also strongly correlated to AR expression (p 0.001), and to the so-called molecular apocrine subtype (HR-/AR+, p < 0.0001). Higher rates of GCDFP-15 positivity were seen in tumors of lower grade (<0.0001) and negative nodal status (p = 0.008). GCDFP-15 positive tumors tended to have a more favourable prognosis than GCDFP-15 negative tumors (DFS (p = 0.052) and OS (p = 0.044)), which was not independent from other factors in multivariate analysis. GCDFP-15 expression was not linked to pCR. Histological apocrine differentiation was frequent in molecular apocrine carcinomas (60.7%), and was associated with GCDFP-15 within this group (p = 0.039).
Conclusions
GCDFP-15 expression is higher in tumors with favorable prognostic features. GCDFP-15 expression is further a frequent feature of AR positive tumors and the molecular apocrine subtype. It might have reduced sensitivity as a diagnostic marker for mammary differentiation in triple negative tumors as compared to HR or HER2 positive tumor types.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2407-14-546) contains supplementary material, which is available to authorized users.
doi:10.1186/1471-2407-14-546
PMCID: PMC4122770  PMID: 25070172
GCDFP-15; Breast cancer; Neoadjuvant chemotherapy; Apocrine; CUP
14.  Overexpression of the epithelial cell adhesion molecule is associated with a more favorable prognosis and response to platinum-based chemotherapy in ovarian cancer 
Journal of Gynecologic Oncology  2014;25(3):221-228.
Objective
Epithelial cell adhesion molecule (EpCAM) has experienced a renaissance lately as a binding site for targeted therapy as well as a prognostic marker in epithelial malignancies. Aim of this study was to study EpCAM as a potential prognostic marker in epithelial ovarian cancer (EOC).
Methods
EpCAM expression was assessed by immunohistochemistry on paraffin-embedded primary EOC-tissue samples. EpCAM overexpression was defined as an expression of EpCAM of 76% to 100%. Tissue samples and clinical data were systematically collected within the international and multicenter "Tumorbank Ovarian Cancer" network.
Results
Seventy-four patients, diagnosed with EOC between 1994 and 2009, were included in the study (median age, 56 years; range, 31 to 86 years). The majority of the patients (81.1%) presented with an advanced stage International Federation of Gynecology and Obstetrics (FIGO) III/IV disease. Histology was of the serous type in 41 patients (55.4%), endometrioid in 19 (25.6%), and mucinous in 14 (19%). EpCAM was overexpressed in 87.7%. Serous tumors overexpressed EpCAM significantly more often than mucinous tumors (87.8% vs. 78.6%, p=0.045); while no significant difference was noted between the other histological subgroups. EpCAM overexpression was significantly associated with a better progression free survival and higher response rates to platinum based chemotherapy (p=0.040 and p=0.048, respectively). EpCAM was identified as an independent prognostic marker for overall survival (p=0.022).
Conclusion
Our data indicate a significant association of EpCAM overexpression with a more favorable survival in EOC-patients. Serous cancers showed a significant EpCAM overexpression compared to mucinous types. Larger multicenter analyses are warranted to confirm these findings.
doi:10.3802/jgo.2014.25.3.221
PMCID: PMC4102741  PMID: 25045435
Epithelial cell adhesion molecule; Ovarian neoplasms; Survival
15.  Ambivalent role of pFAK-Y397 in serous ovarian cancer-a study of the OVCAD consortium 
Molecular Cancer  2014;13:67.
Background
Focal adhesion kinase (FAK) autophosphorylation seems to be a potential therapeutic target but little is known about the role and prognostic value of FAK and pFAK in epithelial ovarian cancer (EOC). Recently, we validated a gene signature classifying EOC patients into two subclasses and revealing genes of the focal adhesion pathway as significantly deregulated.
Methods
FAK expression and pFAK-Y397 abundance were elucidated by immunohistochemistry and microarray analysis in 179 serous EOC patients. In particular the prognostic value of phosphorylated FAK (pFAK-Y397) and FAK in advanced stage EOC was investigated.
Results
Multiple Cox-regression analysis showed that high pFAK abundance was associated with improved overall survival (HR 0.54; p = 0.034). FAK was positive in a total of 92.2% (n = 165) and high pFAK abundance was found in 36.9% (n = 66). High pFAK abundance (36.9% ; n = 66) was associated with either nodal positivity and/or distant metastasis (p = 0.030). Whole genome gene expression data revealed a connection of the FAK-pFAK-Y397 axis and the mTOR-S6K1 pathway, shown to play a major role in carcinogenesis.
Conclusion
The role of pFAK-Y397 remains controversial: although high pFAK-Y397 abundance is associated with distant and lymph node metastases, it is independently associated with improved overall survival.
doi:10.1186/1476-4598-13-67
PMCID: PMC3998046  PMID: 24655477
FAK; pFAK; Molecular subclassification; Immunohistochemistry; Prognosis; Ovarian cancer
16.  Prospective Validation of Immunological Infiltrate for Prediction of Response to Neoadjuvant Chemotherapy in HER2-Negative Breast Cancer – A Substudy of the Neoadjuvant GeparQuinto Trial 
PLoS ONE  2013;8(12):e79775.
Introduction
We have recently described an increased lymphocytic infiltration rate in breast carcinoma tissue is a significant response predictor for anthracycline/taxane-based neoadjuvant chemotherapy (NACT). The aim of this study was to prospectively validate the tumor-associated lymphocyte infiltrate as predictive marker for response to anthracycline/taxane-based NACT.
Patients and Methods
The immunological infiltrate was prospectively evaluated in a total of 313 core biopsies from HER2 negative patients of the multicenter PREDICT study, a substudy of the neoadjuvant GeparQuinto study. Intratumoral lymphocytes (iTuLy), stromal lymphocytes (strLy) as well as lymphocyte-predominant breast cancer (LPBC) were evaluated by histopathological assessment. Pathological complete response (pCR) rates were analyzed and compared between the defined subgroups using the exact test of Fisher.
Results
Patients with lymphocyte-predominant breast cancer (LPBC) had a significantly increased pCR rate of 36.6%, compared to non-LPBC patients (14.3%, p<0.001). LPBC and stromal lymphocytes were significantly independent predictors for pCR in multivariate analysis (LPBC: OR 2.7, p = 0.003, strLy: OR 1.2, p = 0.01). The amount of intratumoral lymphocytes was significantly predictive for pCR in univariate (OR 1.2, p = 0.01) but not in multivariate logistic regression analysis (OR 1.2, p = 0.11).
Conclusion
Confirming previous investigations of our group, we have prospectively validated in an independent cohort that an increased immunological infiltrate in breast tumor tissue is predictive for response to anthracycline/taxane-based NACT. Patients with LPBC and increased stromal lymphocyte infiltration have significantly increased pCR rates. The lymphocytic infiltrate is a promising additional parameter for histopathological evaluation of breast cancer core biopsies.
doi:10.1371/journal.pone.0079775
PMCID: PMC3846472  PMID: 24312450
17.  Prognostic impact of tumor infiltrating CD8+ T cells in association with cell proliferation in ovarian cancer patients - a study of the OVCAD consortium 
BMC Cancer  2013;13:422.
Background
Epithelial ovarian cancer is one of the most lethal gynecologic malignancies. Clinicopathological factors do not permit precise prognosis and cannot provide guidance to specific treatments. In this study we assessed tumor infiltrating CD8+ T cells in association with Ki67 proliferation index and evaluated their prognostic impact in EOC samples.
Methods
CD8+ cells and Ki67 proliferation index were immunohistochemically determined on tissue microarrays including 203 primary epithelial ovarian tumors. Additionally, CD8 gene expression was assessed with RT-qPCR. Correlations were analyzed using Pearson’s correlation coefficients, ANOVA or T-test, or Fischer’s exact tests. Prognostic impact was evaluated using the Kaplan-Meier method and Cox regression model.
Results
The density of CD8+ infiltrating lymphocytes did not correlate with tumor cell proliferation. Epithelial ovarian cancer patients with no Ki67+ cells in the tumor had a more than three times higher risk to die compared to the population with Ki67+ cells in the tumor (Hazard ratio (HR) = 3.34, 95%CI 1.59-7.04). High CD8+ cell infiltration was associated with improved overall survival (HR = 0.82, 95%CI 0.73-0.92).
Conclusions
The density of tumor infiltrating lymphocytes is independent of tumor cell proliferation. Ovarian cancer patients with Ki67- tumors showed a significantly reduced overall survival, presumably due to no or poor response to platinum-based chemotherapy. Moreover, the association of high densities of tumor infiltrating cytotoxic T lymphocytes with a better overall survival was confirmed.
doi:10.1186/1471-2407-13-422
PMCID: PMC3848589  PMID: 24044611
Epithelial ovarian cancer; Cytotoxic T cells; Tumor proliferation; Prognostic impact; Residual tumor
18.  From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis 
Microarrays  2013;2(3):243-264.
Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER) positive, human epidermal growth factor receptor (HER2) negative (ER+/HER2−) breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR)) to allow for assaying formalin-fixed, paraffin-embedded (FFPE) samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257) demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice.
doi:10.3390/microarrays2030243
PMCID: PMC5003465  PMID: 27605191
breast cancer; EndoPredict; multigene test; endocrine therapy
19.  New network topology approaches reveal differential correlation patterns in breast cancer 
BMC Systems Biology  2013;7:78.
Background
Analysis of genome-wide data is often carried out using standard methods such as differential expression analysis, clustering analysis and heatmaps. Beyond that, differential correlation analysis was suggested to identify changes in the correlation patterns between disease states. The detection of differential correlation is a demanding task, as the number of entries in the gene-by-gene correlation matrix is large. Currently, there is no gold standard for the detection of differential correlation and statistical validation.
Results
We developed two untargeted algorithms (DCloc and DCglob) that identify differential correlation patterns by comparing the local or global topology of correlation networks. Construction of networks from correlation structures requires fixing of a correlation threshold. Instead of a single cutoff, the algorithms systematically investigate a series of correlation thresholds and permit to detect different kinds of correlation changes at the same level of significance: strong changes of a few genes and moderate changes of many genes. Comparing the correlation structure of 208 ER- breast carcinomas and 208 ER+ breast carcinomas, DCloc detected 770 differentially correlated genes with a FDR of 12.8%, while DCglob detected 630 differentially correlated genes with a FDR of 12.1%. In two-fold cross-validation, the reproducibility of the list of the top 5% differentially correlated genes in 140 ER- tumors and in 140 ER+ tumors was 49% for DCloc and 33% for DCglob.
Conclusions
We developed two correlation network topology based algorithms for the detection of differential correlations in different disease states. Clusters of differentially correlated genes could be interpreted biologically and included the marker genes hydroxyprostaglandin dehydrogenase (PGDH) and acyl-CoA synthetase medium chain 1 (ACSM1) of invasive apocrine carcinomas that were differentially correlated, but not differentially expressed. Using random subsampling and cross-validation, DCloc and DCglob were shown to identify specific and reproducible lists of differentially correlated genes.
doi:10.1186/1752-0509-7-78
PMCID: PMC3848818  PMID: 23945349
Differential correlation; Microarray data; Breast cancer; Molecular subtypes; Differential co-expression
20.  The EndoPredict Gene-Expression Assay in Clinical Practice - Performance and Impact on Clinical Decisions 
PLoS ONE  2013;8(6):e68252.
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.
doi:10.1371/journal.pone.0068252
PMCID: PMC3694878  PMID: 23826382
21.  Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery 
Genome Medicine  2012;4(4):37.
Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.
doi:10.1186/gm336
PMCID: PMC3446265  PMID: 22546809
breast cancer; metabolomics; lipidomics; biomarker analysis
22.  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 
BMC Cancer  2013;13:215.
Background
In 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.
Methods
The 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.
Results
In 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).
Conclusion
As 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.
doi:10.1186/1471-2407-13-215
PMCID: PMC3646665  PMID: 23627572
HDAC; Breast cancer; Immunohistochemistry
23.  CognitionMaster: an object-based image analysis framework 
Diagnostic Pathology  2013;8:34.
Background
Automated image analysis methods are becoming more and more important to extract and quantify image features in microscopy-based biomedical studies and several commercial or open-source tools are available. However, most of the approaches rely on pixel-wise operations, a concept that has limitations when high-level object features and relationships between objects are studied and if user-interactivity on the object-level is desired.
Results
In this paper we present an open-source software that facilitates the analysis of content features and object relationships by using objects as basic processing unit instead of individual pixels. Our approach enables also users without programming knowledge to compose “analysis pipelines“ that exploit the object-level approach. We demonstrate the design and use of example pipelines for the immunohistochemistry-based cell proliferation quantification in breast cancer and two-photon fluorescence microscopy data about bone-osteoclast interaction, which underline the advantages of the object-based concept.
Conclusions
We introduce an open source software system that offers object-based image analysis. The object-based concept allows for a straight-forward development of object-related interactive or fully automated image analysis solutions. The presented software may therefore serve as a basis for various applications in the field of digital image analysis.
doi:10.1186/1746-1596-8-34
PMCID: PMC3626931  PMID: 23445542
Software; Open source; Image analysis; Object-based image analysis
24.  HER2 and ESR1 mRNA expression levels and response to neoadjuvant trastuzumab plus chemotherapy in patients with primary breast cancer 
Introduction
Recent 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.
Methods
HER2 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.
Results
Only 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.
Conclusions
Only 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.
doi:10.1186/bcr3384
PMCID: PMC3672694  PMID: 23391338
25.  Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization 
PLoS ONE  2012;7(12):e51862.
Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.
doi:10.1371/journal.pone.0051862
PMCID: PMC3522617  PMID: 23251644

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