Birte Hellwig

A Comprehensive Analysis of Human Gene Expression Profiles Identifies Stromal Immunoglobulin κ C as a Compatible Prognostic Marker in Human Solid Tumors

Purpose: Although the central role of the immune system for tumor prognosis is generally accepted, a single robust marker is not yet available. Experimental Design: On the basis of receiver operating characteristic analyses, robust markers were identified from a 60-gene B cell–derived metagene and analyzed in gene expression profiles of 1,810 breast cancer; 1,056 non–small cell lung carcinoma (NSCLC); 513 colorectal; and 426 ovarian cancer patients. Protein and RNA levels were examined in paraffin-embedded tissue of 330 breast cancer patients. The cell types were identified with immunohistochemical costaining and confocal fluorescence microscopy. Results: We identified immunoglobulin κ C (IGKC) which as a single marker is similarly predictive and prognostic as the entire B-cell metagene. IGKC was consistently associated with metastasis-free survival across different molecular subtypes in node-negative breast cancer (n = 965) and predicted response to anthracycline-based neoadjuvant chemotherapy (n = 845; P < 0.001). In addition, IGKC gene expression was prognostic in NSCLC and colorectal cancer. No association was observed in ovarian cancer. IGKC protein expression was significantly associated with survival in paraffin-embedded tissues of 330 breast cancer patients. Tumor-infiltrating plasma cells were identified as the source of IGKC expression. Conclusion: Our findings provide IGKC as a novel diagnostic marker for risk stratification in human cancer and support concepts to exploit the humoral immune response for anticancer therapy. It could be validated in several independent cohorts and carried out similarly well in RNA from fresh frozen as well as from paraffin tissue and on protein level by immunostaining. Clin Cancer Res; 18(9); 2695–703. ©2012 AACR.

Biomarker Discovery in Non–Small Cell Lung Cancer: Integrating Gene Expression Profiling, Meta-analysis, and Tissue Microarray Validation

Purpose: Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multigene signatures in clinical practice is unclear, and the biologic importance of individual genes is difficult to assess, as the published signatures virtually do not overlap. Experimental Design: Here, we describe a novel single institute cohort, including 196 non–small lung cancers (NSCLC) with clinical information and long-term follow-up. Gene expression array data were used as a training set to screen for single genes with prognostic impact. The top 450 probe sets identified using a univariate Cox regression model (significance level P < 0.01) were tested in a meta-analysis including five publicly available independent lung cancer cohorts (n = 860). Results: The meta-analysis revealed 14 genes that were significantly associated with survival (P < 0.001) with a false discovery rate <1%. The prognostic impact of one of these genes, the cell adhesion molecule 1 (CADM1), was confirmed by use of immunohistochemistry on tissue microarrays from 2 independent NSCLC cohorts, altogether including 617 NSCLC samples. Low CADM1 protein expression was significantly associated with shorter survival, with particular influence in the adenocarcinoma patient subgroup. Conclusions: Using a novel NSCLC cohort together with a meta-analysis validation approach, we have identified a set of single genes with independent prognostic impact. One of these genes, CADM1, was further established as an immunohistochemical marker with a potential application in clinical diagnostics. Clin Cancer Res; 19(1); 194–204. ©2012 AACR.

ERBB2 and TOP2A in Breast Cancer: A Comprehensive Analysis of Gene Amplification, RNA Levels, and Protein Expression and Their Influence on Prognosis and Prediction

Purpose: The prognostic and predictive relevance of epidermal growth factor receptor 2 (ERBB2) and topoisomerase II α (TOP2A) have long been a matter of debate. However, the correlation of DNA amplification, RNA levels, and protein expression and their prognostic role and association with anthracycline responses in node-negative breast cancer have not yet been evaluated. Experimental Design: We first analyzed TOP2A and ERBB2 at the levels of gene amplification, and RNA and protein expression, and studied their correlations. Additionally, TOP2A and ERBB2 were analyzed in 782 node-negative breast carcinomas in patients who did not receive systemic therapy and in 80 patients treated with epirubicin and cyclophosphamide (EC) prior to surgery. Results: TOP2A gene amplification did not correlate with protein expression (P = 0.283) and showed an association with gene expression with only borderline significance (P = 0.047). By contrast, TOP2A RNA levels correlated with protein expression (P < 0.001). TOP2A gene expression was significantly associated with the metastasis-free interval (MFI; P < 0.001) and was associated with complete remission in patients treated with EC (P = 0.002). In contrast to TOP2A, ERBB2 gene amplification correlated with RNA level (P < 0.001) and protein expression (P < 0.001). ERBB2 gene expression was associated with the MFI only in estrogen receptor–positive carcinomas, whereas ERBB2 protein expression (P = 0.032) was associated with MFI in the entire cohort. Conclusions: Overall, our study indicates that the TOP2A RNA level is a good prognostic marker and is also associated with a favorable response to anthracyclin-based therapy. By contrast, ESR1 was associated with poorer responses to anthracyclin-based therapy, whereas the association with ERBB2 RNA was not significant. Clin Cancer Res; 16(8); 2391–401. ©2010 AACR.

The prognostic relevance of tumour-infiltrating plasma cells and immunoglobulin kappa C indicates an important role of the humoral immune response in non-small cell lung cancer

A prognostic impact of immunoglobulin kappa C (IGKC) expression has been described in cancer. We analysed the influence of B-cell and plasma cell markers, as well as IGKC expression, in non-small lung cancer (NSCLC) using immunohistochemistry on a tissue microarray. IGKC protein expression was independently associated with longer survival, with particular impact in the adenocarcinoma subgroup. Moreover, a correlation was seen with CD138+ cells, but not with CD20. CD138 expression revealed a comparable association with survival. In conclusion, IGKC expression in stroma-infiltrating plasma cells is a prognostic marker in NSCLC, supporting emerging treatment concepts that exploit the humoral immune response.

Loss of circadian clock gene expression is associated with tumor progression in breast cancer.

Several studies suggest a link between circadian rhythm disturbances and tumorigenesis. However, the association between circadian clock genes and prognosis in breast cancer has not been systematically studied. Therefore, we examined the expression of 17 clock components in tumors from 766 node-negative breast cancer patients that were untreated in both neoadjuvant and adjuvant settings. In addition, their association with metastasis-free survival (MFS) and correlation to clinicopathological parameters were investigated. Aiming to estimate functionality of the clockwork, we studied clock gene expression relationships by correlation analysis. Higher expression of several clock genes (e.g., CLOCK, PER1, PER2, PER3, CRY2, NPAS2 and RORC) was found to be associated with longer MFS in univariate Cox regression analyses (HR<1 and FDR-adjusted P < 0.05). Stratification according to molecular subtype revealed prognostic relevance for PER1, PER3, CRY2 and NFIL3 in the ER+/HER2- subgroup, CLOCK and NPAS2 in the ER-/HER2- subtype, and ARNTL2 in HER2+ breast cancer. In the multivariate Cox model, only PER3 (HR = 0.66; P = 0.016) and RORC (HR = 0.42; P = 0.003) were found to be associated with survival outcome independent of established clinicopathological parameters. Pairwise correlations between functionally-related clock genes (e.g., PER2-PER3 and CRY2-PER3) were stronger in ER+, HER2- and low-grade carcinomas; whereas, weaker correlation coefficients were observed in ER- and HER2+ tumors, high-grade tumors and tumors that progressed to metastatic disease. In conclusion, loss of clock genes is associated with worse prognosis in breast cancer. Coordinated co-expression of clock genes, indicative of a functional circadian clock, is maintained in ER+, HER2-, low grade and non-metastasizing tumors but is compromised in more aggressive carcinomas.

Expression of aurora kinase A is associated with metastasis-free survival in node-negative breast cancer patients.

BackgroundInhibitors targeting the cell cycle-regulated aurora kinase A (AURKA) are currently being developed. Here, we examine the prognostic impact of AURKA in node-negative breast cancer patients without adjuvant systemic therapy (n = 766).MethodsAURKA was analyzed using microarray-based gene-expression data from three independent cohorts of node-negative breast cancer patients. In multivariate Cox analyses, the prognostic impact of age, histological grade, tumor size, estrogen receptor (ER), and HER2 were considered.ResultsPatients with higher AURKA expression had a shorter metastasis-free survival (MFS) in the Mainz (HR 1.93; 95% CI 1.34 – 2.78; P < 0.001), Rotterdam (HR 1.95; 95% CI 1.45– 2.63; P<0.001) and Transbig (HR 1.52; 95% CI 1.14–2.04; P=0.005) cohorts. AURKA was also associated with MFS in the molecular subtype ER+/HER2- carcinomas (HR 2.10; 95% CI 1.70–2.59; P<0.001), but not in ER-/HER2- nor in HER2+ carcinomas. In the multivariate Cox regression adjusted to age, grade and tumor size, AURKA showed independent prognostic significance in the ER+/HER2- subtype (HR 1.73; 95% CI 1.24–2.42; P=0.001). Prognosis of patients in the highest quartile of AURKA expression was particularly poor. In addition, AURKA correlated with the proliferation metagene (R=0.880; P<0.001), showed a positive association with grade (P<0.001), tumor size (P<0.001) and HER2 (P<0.001), and was inversely associated with ER status (P<0.001).ConclusionsAURKA is associated with worse prognosis in estrogen receptor positive breast carcinomas. Patients with the highest AURKA expression (>75% percentile) have a particularly bad prognosis and may profit from therapy with AURKA inhibitors.

Glycerophospholipid profile in oncogene-induced senescence.

Alterations in lipid metabolism and in the lipid composition of cellular membranes are linked to the pathology of numerous diseases including cancer. However, the influence of oncogene expression on cellular lipid profile is currently unknown. In this work we analyzed changes in lipid profiles that are induced in the course of ERBB2-expression mediated premature senescence. As a model system we used MCF-7 breast cancer cells with doxycycline-inducible expression of NeuT, an oncogenic ERBB2 variant. Affymetrix gene array data showed NeuT-induced alterations in the transcription of many enzymes involved in lipid metabolism, several of which (ACSL3, CHPT1, PLD1, LIPG, MGLL, LDL and NPC1) could be confirmed by quantitative realtime PCR. A study of the glycerophospholipid and lyso-glycerophospholipid profiles, obtained by high performance liquid chromatography coupled to Fourier-transform ion cyclotron resonance-mass spectrometry revealed senescence-associated changes in numerous lipid species, including mitochondrial lipids. The most prominent changes were found in PG(34:1), PG(36:1) (increased) and LPE(18:1), PG(40:7) and PI(36:1) (decreased). Statistical analysis revealed a general trend towards shortened phospholipid acyl chains in senescence and a significant trend to more saturated acyl chains in the class of phosphatidylglycerol. Additionally, the cellular cholesterol content was elevated and accumulated in vacuoles in senescent cells. These changes were accompanied by increased membrane fluidity. In mitochondria, loss of membrane potential along with altered intracellular distribution was observed. In conclusion, we present a comprehensive overview of altered cholesterol and glycerophospholipid patterns in senescence, showing that predominantly mitochondrial lipids are affected and lipid species less susceptible to peroxidation are increased.

The lung-specific proteome defined by integration of transcriptomics and antibody-based profiling

The combined action of multiple cell types is essential for the physiological function of the lung, and increased awareness of the molecular constituents characterizing each cell type is likely to advance the understanding of lung biology and disease. In the current study, we used genome‐wide RNA sequencing of normal lung parenchyma and 26 additional tissue types, combined with antibody‐based protein profiling, to localize the expression to specific cell types. Altogether, 221 genes were found to be elevated in the lung compared with their expression in other analyzed tissues. Among the gene products were several well‐known markers, but also several proteins previously not described in the context of the lung. To link the lungspecific molecular repertoire to human disease, survival associations of pneumocyte‐specific genes were assessed by using transcriptomics data from 7 nonsmall‐cell lung cancer (NSCLC) cohorts. Transcript levels of 10 genes (SFTPB, SFTPC, SFTPD, SLC34A2, LAMP3, CACNA2D2, AGER, EMP2, NKX2‐1, and NAPSA) were significantly associated with survival in the adenocarcinoma subgroup, thus qualifying as promising biomarker candidates. In summary, based on an integrated omics approach, we identified genes with elevated expression in lung and localized corresponding protein expression to different cell types. As biomarker candidates, these proteins may represent intriguing starting points for further exploration in health and disease.—Lindskog, C., Fagerberg, L., Hallström, B., Edlund, K., Hellwig, B., Rahnenführer, J., Kampf, C., Uhlén, M., Pontén, F., Micke, P., The lung‐specific proteome defined by integration of transcriptomics and antibody‐based profiling. FASEB J. 28, 5184–5196 (2014). www.fasebj.org

Optimal Strategies for Sequential Validation of Significant Features from High-Dimensional Genomic Data

High-dimensional genomic studies play a key role in identifying critical features that are significantly associated with a phenotypic outcome. The two most important examples are the detection of (1) differentially expressed genes from genome-wide gene expression studies and (2) single-nucleotide polymorphisms (SNPs) from genome-wide association studies. Such experiments are often associated with high noise levels, and the validity of statistical conclusions suffers from low sample size compared to large number of features. The corresponding multiple testing problem calls for the identification of optimal strategies for controlling the numbers of false discoveries and false nondiscoveries. In addition, a frequent validation problem is that features identified as important in one study are often less so in another study. Adjustment for multiple testing in both studies separately increases the risk of missing the crucial features even further. These problems can be addressed by sequential validation strategies, where only significant features identified in one study enter as candidates in the next study. The quality associated with different studies, for example, in terms of noise levels, may vary considerably. By performing simulation studies it is possible to demonstrate that the optimal order for this stepwise procedure is to sort experimental studies according to their quality in descending order. The impact of the method for multiple testing adjustment (Bonferroni-Holm, FDR) was also analyzed. Finally, the sequential validation strategy was applied to three large breast cancer studies with gene expression measurements, confirming the crucial impact of the order of the validation steps in a real-world application.

Epsin Family Member 3 and Ribosome-Related Genes Are Associated with Late Metastasis in Estrogen Receptor-Positive Breast Cancer and Long-Term Survival in Non-Small Cell Lung Cancer Using a Genome-Wide Identification and Validation Strategy

Background In breast cancer, gene signatures that predict the risk of metastasis after surgical tumor resection are mainly indicative of early events. The purpose of this study was to identify genes linked to metastatic recurrence more than three years after surgery. Methods Affymetrix HG U133A and Plus 2.0 array datasets with information on metastasis-free, disease-free or overall survival were accessed via public repositories. Time restricted Cox regression models were used to identify genes associated with metastasis during or after the first three years post-surgery (early- and late-type genes). A sequential validation study design, with two non-adjuvantly treated discovery cohorts (n = 409) and one validation cohort (n = 169) was applied and identified genes were further evaluated in tamoxifen-treated breast cancer patients (n = 923), as well as in patients with non-small cell lung (n = 1779), colon (n = 893) and ovarian (n = 922) cancer. Results Ten late- and 243 early-type genes were identified in adjuvantly untreated breast cancer. Adjustment to clinicopathological factors and an established proliferation-related signature markedly reduced the number of early-type genes to 16, whereas nine late-type genes still remained significant. These nine genes were associated with metastasis-free survival (MFS) also in a non-time restricted model, but not in the early period alone, stressing that their prognostic impact was primarily based on MFS more than three years after surgery. Four of the ten late-type genes, the ribosome-related factors EIF4B, RPL5, RPL3, and the tumor angiogenesis modifier EPN3 were significantly associated with MFS in the late period also in a meta-analysis of tamoxifen-treated breast cancer cohorts. In contrast, only one late-type gene (EPN3) showed consistent survival associations in more than one cohort in the other cancer types, being associated with worse outcome in two non-small cell lung cancer cohorts. No late-type gene was validated in ovarian and colon cancer. Conclusions Ribosome-related genes were associated with decreased risk of late metastasis in both adjuvantly untreated and tamoxifen-treated breast cancer patients. In contrast, high expression of epsin (EPN3) was associated with increased risk of late metastasis. This is of clinical relevance considering the well-understood role of epsins in tumor angiogenesis and the ongoing development of epsin antagonizing therapies.