Gene expression analysis in biomarker research and early drug development using function tested reverse transcription quantitative real-time PCR assays.

The identification of new biomarkers is essential in the implementation of personalized health care strategies that offer new therapeutic approaches with optimized and individualized treatment. In support of hypothesis generation and testing in the course of our biomarker research an online portal and respective function-tested reverse transcription quantitative real-time PCR assays (RT-qPCR) facilitated the selection of relevant biomarker genes. We have established workflows applicable for convenient high throughput gene expression analysis in biomarker research with cell lines (in vitro studies) and xenograft mouse models (in vivo studies) as well as formalin-fixed paraffin-embedded tissue (FFPET) sections from various human research and clinical tumor samples. Out of 92 putative biomarker candidate genes selected in silico, 35 were shown to exhibit differential expression in various tumor cell lines. These were further analysed by in vivo xenograft mouse models, which identified 13 candidate genes including potential response prediction biomarkers and a potential pharmacodynamic biomarker. Six of these candidate genes were selected for further evaluation in FFPET samples, where optimized RNA isolation, reverse transcription and qPCR assays provided reliable determination of relative expression levels as precondition for differential gene expression analysis of FFPET samples derived from projected clinical studies. Thus, we successfully applied function tested RT-qPCR assays in our biomarker research for hypothesis generation with in vitro and in vivo models as well as for hypothesis testing with human FFPET samples. Hence, appropriate function-tested RT-qPCR assays are available in biomarker research accompanying the different stages of drug development, starting from target identification up to early clinical development. The workflow presented here supports the identification and validation of new biomarkers and may lead to advances in efforts to achieve the goal of personalized health care.

Subtyping Of Triple Negative Breast Carcinoma On The Basis Of RTK Expression.

Background: "Triple-negative breast cancers" (TNBC) comprise a heterogeneous group of about 15% of invasive BCs lacking the expression of estrogen and progesterone receptors (ER, PR) and the expression of HER2 (ERBB2) and are therefore no established candidates for targeted treatment options in BC, i.e., endocrine and anti-HER2 therapy. The aim of the present study was to use gene expression profiling and immunohistochemical (IHC) characterization to identify receptor tyrosine kinase (RTK) profiles that would allow patient stratification for the purposes of target-oriented personalized tumor therapy in TNBC. Methods: Twenty-nine cases of TNBC selected according to routine diagnostic IHC/cytogenetic criteria were examined by reverse transcription polymerase chain reaction (RT-PCR). RTK mRNA expression profiles were generated for a total of 31 tumor-relevant biomarkers, mainly belonging to the IGF- and EGF-receptor families but also including biomarkers related to downstream signaling. Protein expression of selected biomarkers was investigated by IHC. Results: Hierarchical cluster analysis revealed a dichotomous differentiation pattern amongst TNBCs. A significant difference in gene expression was observed for 16 of the 31 RTK-associated tumor relevant biomarkers between the two newly identified TNBC subgroups. The findings were verified at the posttranslational level by the IHC data. The RTKs HER4, IGF-1R and IGF-2R and the hormone receptors ER and PR below the IHC detection limit play a central role in the differentiation of the two TNBC subgroups. Observed survival was reported as Kaplan-Meier estimates and point towards an improved survival of patients with RTK-high with superior three-year survival rate of 100% compared to RTK-low gene signatures with superior three-year survival rate of 60% (log-rank test, p-value = 0.022). Conclusion: Gene-expression and IHC analysis of the EGF and IGF receptor families and biomarkers associated with downstream signaling point to the existence of two distinct TNBC subtypes. The RTKs HER4, IGF-1R, IGF-2R and the hormone receptors ER and PR appear to be of particular importance here. Based on survival analysis the differentiation of TNBC with RTK-high and RTK-low gene signatures seems to be of prognostic relevance. Additionally, correlation analysis of the relationship between RTKs and ER suggests co-regulatory mechanisms that may have potential significance in new therapeutic approaches.

An optimized workflow for improved gene expression profiling for formalin-fixed, paraffin-embedded tumor samples.

BACKGROUND: Whole genome microarray gene expression profiling is the 'gold standard' for the discovery of prognostic and predictive genetic markers for human cancers. However, suitable research material is lacking as most diagnostic samples are preserved as formalin-fixed, paraffin-embedded tissue (FFPET). We tested a new workflow and data analysis method optimized for use with FFPET samples. METHODS: Sixteen breast tumor samples were split into matched pairs and preserved as FFPET or fresh-frozen (FF). Total RNA was extracted and tested for yield and purity. RNA from FFPET samples was amplified using three different commercially available kits in parallel, and hybridized to Affymetrix GeneChip® Human Genome U133 Plus 2.0 Arrays. The array probe set was optimized in silico to exclude misdesigned and misannotated probes. RESULTS: FFPET samples processed using the WT-Ovation™ FFPE System V2 (NuGEN) provided 80% specificity and 97% sensitivity compared with FF samples (assuming values of 100%). In addition, in silico probe set redesign improved sequence detection sensitivity and, thus, may rescue potentially significant small-magnitude gene expression changes that could otherwise be diluted by the overall probe set background. CONCLUSION: In conclusion, our FFPET-optimized workflow enables the detection of more genes than previous, nonoptimized approaches, opening new possibilities for the discovery, validation, and clinical application of mRNA biomarkers in human diseases.

Thymidine phosphorylase, dihydropyrimidine dehydrogenase and thymidylate synthase mRNA expression in primary colorectal tumors-correlation to tumor histopathology and clinical follow-up.

AIM: Evaluation of thymidine phosphorylase (TP), dihydropyrimidine dehydrogenase (DPD), and thymidylate synthase (TS) mRNA levels in formalin-fixed, and paraffin-embedded tissues of patients with colorectal cancer and their prognostic and/or predictive value. MATERIALS AND METHODS: Total RNA was isolated from microdissected, formalin-fixed, and paraffin-embedded tissues (controls and tumor) and subjected to quantitative RT-PCR (QRT-PCR) in the LightCycler system. Resulting mRNA levels correlated to tumor histology (n=102) and the clinical follow-up in patients treated by resection alone (n=40) and by resection plus adjuvant 5-FU-based chemotherapy (n=52). RESULTS: Correlation to histopathological parameters revealed a significant association between tumor stage and the TP mRNA level (T and N category and UICC) as well as the TP:DPD (T and N category and UICC) and TS:DPD (T category) ratio. In addition, tumor differentiation was correlated to the TS mRNA level and the TS:DPD ratio. Finally, the TS:DPD ratio was a prognostic marker for overall survival in patients receiving resection alone (p=0.032). Moreover, a high TP:DPD ratio (>8.1; p=0.002) and, marginally, low DPD (<8.2; p=0.05) mRNA levels significantly correlated to disease-free survival. CONCLUSION: We present a novel, standardized approach for TP, DPD, and TS mRNA quantification in archival tissue specimens and applied this to a large series of primary colorectal tumors. Correlations to histopathological parameters and clinical follow-up revealed an association of TP, DPD and TS mRNA expression patterns with tumor stage and suggested new prognostic and predictive markers for patients with colorectal cancer.