Irina Klaman

Molecular Profiling of Laser-Microdissected Matched Tumor and Normal Breast Tissue Identifies Karyopherin α2 as a Potential Novel Prognostic Marker in Breast Cancer

Purpose: The aim of the present study was to identify human genes that might prove useful in the diagnosis and therapy of primary breast cancer. Experimental Design: Twenty-four matched pairs of invasive ductal breast cancer and corresponding benign breast tissue were investigated by a combination of laser microdissection and gene expression profiling. Differential expression of candidate genes was validated by dot blot analysis of cDNA in 50 pairs of matching benign and malignant breast tissue. Cellular expression of candidate genes was further validated by RNA in situ hybridization, quantitative reverse transcription-PCR, and immunohistochemistry using tissue microarray analysis of 272 nonselected breast cancers. Multivariate analysis of factors on overall survival and recurrence-free survival was done. Results: Fifty-four genes were found to be up-regulated and 78 genes were found to be down-regulated. Dot blot analysis reduced the number of up-regulated genes to 15 candidate genes that showed at least a 2-fold overexpression in >15 of 50 (30%) tumor/normal pairs. We selected phosphatidic acid phosphatase type 2 domain containing 1A (PPAPDC1A) and karyopherin α2 (KPNA2) for further validation. PPAPDC1A and KPNA2 RNA was up-regulated (fold change >2) in 84% and 32% of analyzed tumor/normal pairs, respectively. Nuclear protein expression of KPNA2 was significantly associated with shorter overall survival and recurrence-free survival. Testing various multivariate Cox regression models, KPNA2 expression remained a highly significant, independent and adverse risk factor for overall survival. Conclusions: Gene expression profiling of laser-microdissected breast cancer tissue revealed novel genes that may represent potential molecular targets for breast cancer therapy and prediction of outcome.

An expression module of WIPF1-coexpressed genes identifies patients with favorable prognosis in three tumor types.

Wiskott–Aldrich syndrome (WAS) predisposes patients to leukemia and lymphoma. WAS is caused by mutations in the protein WASP which impair its interaction with the WIPF1 protein. Here, we aim to identify a module of WIPF1-coexpressed genes and to assess its use as a prognostic signature for colorectal cancer, glioma, and breast cancer patients. Two public colorectal cancer microarray data sets were used for discovery and validation of the WIPF1 co-expression module. Based on expression of the WIPF1 signature, we classified more than 400 additional tumors with microarray data from our own experiments or from publicly available data sets according to their WIPF1 signature expression. This allowed us to separate patient populations for colorectal cancers, breast cancers, and gliomas for which clinical characteristics like survival times and times to relapse were analyzed. Groups of colorectal cancer, breast cancer, and glioma patients with low expression of the WIPF1 co-expression module generally had a favorable prognosis. In addition, the majority of WIPF1 signature genes are individually correlated with disease outcome in different studies. Literature gene network analysis revealed that among WIPF1 co-expressed genes known direct transcriptional targets of c-myc, ESR1 and p53 are enriched. The mean expression profile of WIPF1 signature genes is correlated with the profile of a proliferation signature. The WIPF1 signature is the first microarray-based prognostic expression signature primarily developed for colorectal cancer that is instrumental in other tumor types: low expression of the WIPF1 module is associated with better prognosis.

Systematic identification and molecular characterization of genes differentially expressed in breast and ovarian cancer

The identification of novel disease‐associated genes in gynaecological tumours has important implications for understanding the process of tumourigenesis and the development of novel treatment regimens. cDNA libraries from disease tissues may represent a valuable source to identify such genes. Recently, a bio‐informatic procedure based on an ‘electronic Northern’ approach was established to screen expressed sequence tag (EST) libraries for genes differentially expressed in tumour and normal tissues, and identified 450 candidate genes differentially expressed in breast and ovarian cancer. In this report, the validation of an initial set of 40 candidate genes, which were selected due to their localization in chromosomal regions frequently altered in gynaecological tumours, is described. Differential expression of 29 of these genes, including three uncharacterized novel genes, was confirmed by applying cancer profiling arrays with 106 matched pairs of tumour/normal cDNAs and quantitative reverse transcription‐polymerase chain reaction (RT‐PCR) on 60 clinical specimens. The majority of these differentially expressed genes have not been described previously in the context of breast and ovarian cancer, and may constitute novel diagnostic markers for these tumour entities. Copyright

Transcriptional census of 36 microdissected colorectal cancers yields a gene signature to distinguish UICC II and III

UICC stage II and III colorectal cancers (CRC) differ fundamentally in prognosis and therapeutic concepts. To analyze differential gene expression between both stages and to establish a relationship between molecular background and clinical presentation, tumor material from 36 unselected consecutive patients presenting with sporadic CRC, 18 UICC stage II and 18 UICC stage III, were laser microdissected to separate epithelial tumor cells. Gene expression levels were measured using U133A Affymetrix gene arrays. Twelve CRC associated signal transduction pathways as well as all 22,000 probe sets were screened for differential gene expression. We identified a signature consisting of 45 probe sets that allowed discrimination between UICC stage II and stage III with a rate of correct classification of about 80%. The most distinctive elements in this signature were the gene GSTP‐binding elongation factor (GSPT2) and the transcription factor HOXA9. Differential expression of these genes was confirmed by quantitative real‐time polymerase chain reaction (p(HOXA9) = 0.04, p(GSTP2) = 0.02). Despite the reliability of the presented data, there was no substantial differential expression of genes in cancer‐related pathways. However, the comparison with recently published data corroborates the 45 gene signature showing structural agreement in the direction of fold changes of gene expression levels for our set of genes chosen to discriminate between both stages.

Genome-wide expression patterns of invasion front, inner tumor mass and surrounding normal epithelium of colorectal tumors

Colorectal tumors have characteristic genome-wide expression patterns that allow their distinction from normal colon epithelia and facilitate clinical prognosis. The expression heterogeneity within a primary colorectal tumor has not been studied on a genome scale yet. Here we investigated three compartments of colorectal tumors, the invasion front, the inner tumor mass, and surrounding normal epithelial tissue by microdissection and microarray-based expression profiling. In both tumor compartments many genes were differentially expressed when compared to normal epithelium. The sets of significantly deregulated genes in both compartments overlapped to a large extent and revealed various interesting known and novel pathways that could have contributed to tumorigenesis. Cells from the invasion front and inner tumor mass, however, did not show significant differences in their expression profile, neither on the single gene level nor on the pathway level. Instead, gene expression differences between individuals are more pronounced as all patient-matched tumor samples clustered in close proximity to each other. With respect to invasion front and inner tumor mass we conclude that the specific tumor cell micro-environment does not have a strong influence on expression patterns: largely similar genome-wide expression programs operate in the invasion front and interior compartment of a colorectal tumor.

Overexpression of SERBP1 (Plasminogen activator inhibitor 1 RNA binding protein) in human breast cancer is correlated with favourable prognosis

BackgroundPlasminogen activator inhibitor 1 (PAI-1) overexpression is an important prognostic and predictive biomarker in human breast cancer. SERBP1, a protein that is supposed to regulate the stability of PAI-1 mRNA, may play a role in gynaecological cancers as well, since upregulation of SERBP1 was described in ovarian cancer recently. This is the first study to present a systematic characterisation of SERBP1 expression in human breast cancer and normal breast tissue at both the mRNA and the protein level.MethodsUsing semiquantitative realtime PCR we analysed SERBP1 expression in different normal human tissues (n = 25), and in matched pairs of normal (n = 7) and cancerous breast tissues (n = 7). SERBP1 protein expression was analysed in two independent cohorts on tissue microarrays (TMAs), an initial evaluation set, consisting of 193 breast carcinomas and 48 normal breast tissues, and a second large validation set, consisting of 605 breast carcinomas. In addition, a collection of benign (n = 2) and malignant (n = 6) mammary cell lines as well as breast carcinoma lysates (n = 16) were investigated for SERBP1 expression by Western blot analysis. Furthermore, applying non-radioisotopic in situ hybridisation a subset of normal (n = 10) and cancerous (n = 10) breast tissue specimens from the initial TMA were analysed for SERBP1 mRNA expression.ResultsSERBP1 is not differentially expressed in breast carcinoma compared to normal breast tissue, both at the RNA and protein level. However, recurrence-free survival analysis showed a significant correlation (P = 0.008) between abundant SERBP1 expression in breast carcinoma and favourable prognosis. Interestingly, overall survival analysis also displayed a tendency (P = 0.09) towards favourable prognosis when SERBP1 was overexpressed in breast cancer.ConclusionsThe RNA-binding protein SERBP1 is abundantly expressed in human breast cancer and may represent a novel breast tumour marker with prognostic significance. Its potential involvement in the plasminogen activator protease cascade warrants further investigation.

A RNA signature with high sensitivity and specificity discriminating between responder and nonresponder to cetuximab monotherapy in colorectal cancer.

e14049 Background: Patients (pts) with advanced, metastatic colorectal cancer (CRC) and wild-type KRAS mutation status benefit from anti EGFR antibodies cetuximab (CE) and panitumumab. Pts with CRC of UICC stage III do not benefit from CE plus FOLFOX irrespectively of the KRAS mutation status. There is a high medical need for new biomarkers that can differentiate between responder (R) and non-responder (NR) to CE therapy in the adjuvant setting. METHODS We established a panel of 148 stable, passagable CRC xenografts from 240 primary CRC tumors of all four stages (Becker et al. EORTC-NCI-AACR meeting, Berlin Nov. 2010). All xenografts were characterized by histological and molecular methods including Affymetrix array profiling and KRAS, BRAF, PIK3CA mutation analysis. Pharmacological experiments were carried out with 68 models (8 stage I, 22 stage II, 29 stage III, 9 stage IV tumors) testing therapy response to CE. In the CE group 18/68 animals responded to treatment of 50mg/kg/d given over 14 days. T/C <20 responders, T/C>20 non-responder. We isolated RNA from all 18 R and 18 NR control tumors. Labeled and amplified cDNAs (Ambion) was hybridized onto Affymetrix U133 Plus 2.0 arrays. Raw cel files were condensed (FARMS). Feature selection and classification was performed using the random forest algorithm and SVM in a nested bootstrap approach. RESULTS We identified a panel of signatures containing between 20 to 300 RNA markers discriminating between R and NR. The best signature containing 300 probesets showed a prospective sensitivity (S+) of 82.78% and a prospective specificity (S-) of 84.0%. A signature of 21 probesets has a S+ of 79% and a S- of 77.78%. We also assigned the response data of the mouse models to the original human tumors and developed corresponding RNA signatures that discriminated successfully the two human tumor groups and proving our model. CONCLUSIONS We have developed highly accurate RNA signatures predicting response to CE in xenograft models carrying human CRC tumors of all four stages. This signature, if successfully validated in a larger cohort, could be applied to pts with CRC stage II and III for predicting response to CE with a PPV of 64% and a NPV of 93%.

Korrelation von Genexpressionsprofilen mit prognostisch relevanten Parametern beim kolorektalen Karzinom

Gene expression profiling is a new powerful tool to obtain additional information from the patient’s prognosis compared to established classifications like e.g. TNM and UICC as shown for other tumor entities. The aim of this study was to identify prognostic signatures for patients with colorectal cancer of all UICC subgroups, especially for patients with versus without lymph node metastasis (N0 vs. N +), and for patients with versus without distant metastasis (M0 vs. M +). We applied Affymetrix GeneChips (33,000 genes) and Laser Capture Microdissection (LCM) in 25 patients with colorectal cancer. Hierarchical cluster analysis discriminates characteristic expression patterns from normal mucosae and cancer tissues (tumor-cluster) of the central (ZT) and the invasion front (IF). A characteristic pattern for N+ could be identified within the tumorcluster. Significant correlation of tumor-clusters and UICC classification and M0 vs. M+ was not found. To obtain additional information to the established prognostic parameters by gene expression profiling in colorectal cancer, expression data have to be correlated with clinicopathological data and the number of patients has to be expanded.