A Reliable Method for the Selection of Exploitable Melanoma Archival Paraffin Embedded Tissues for Transcript Biomarker Profiling

The source tissue for biomarkers mRNA expression profiling of tumors has traditionally been fresh-frozen tissue. The adaptation of formalin-fixed, paraffin-embedded (FFPE) tissues for routine mRNA profiling would however be invaluable in view of their abundance and the clinical information related to them. However, their use in the clinic remains a challenge due to the poor quality of RNA extracted from such tissues. Here, we developed a method for the selection of melanoma archival paraffin-embedded tissues that can be reliably used for transcript biomarker profiling. For that, we used qRT-PCR to conduct a comparative study in matched pairs of frozen and FFPE melanoma tissues of the expression of 25 genes involved in angiogenesis/tumor invasion and 15 housekeeping genes. A classification method was developed that can select the samples with a good frozen/FFPE correlation and identify those that should be discarded on the basis of paraffin data for four reference genes only. We propose therefore a simple and inexpensive assay which improves reliability of mRNA profiling in FFPE samples by allowing the identification and analysis of “good” samples only. This assay which can be extended to other genes would however need validation at the clinical level and on independent tumor series

Effective DNA/RNA Co-Extraction for Analysis of MicroRNAs, mRNAs, and Genomic DNA from Formalin-Fixed Paraffin-Embedded Specimens

Background: Retrospective studies of archived human specimens, with known clinical follow-up, are used to identify predictive and prognostic molecular markers of disease. Due to biochemical differences, however, formalin-fixed paraffinembedded (FFPE) DNA and RNA have generally been extracted separately from either different tissue sections or from the same section by dividing the digested tissue. The former limits accurate correlation whilst the latter is impractical when utilizing rare or limited archived specimens. Principal Findings: For effective recovery of genomic DNA and total RNA from a single FFPE specimen, without splitting the proteinase-K digested tissue solution, we optimized a co-extraction method by using TRIzol and purifying DNA from the lower aqueous and RNA from the upper organic phases. Using a series of seven different archived specimens, we evaluated the total amounts of genomic DNA and total RNA recovered by our TRIzol-based co-extraction method and compared our results with those from two commercial kits, the Qiagen AllPrep DNA/RNA FFPE kit, for co-extraction, and the Ambion RecoverAll TM Total Nucleic Acid Isolation kit, for separate extraction of FFPE-DNA and-RNA. Then, to accurately assess the quality of DNA and RNA co-extracted from a single FFPE specimen, we used qRT-PCR, gene expression profiling and methylation assays to analyze microRNAs, mRNAs, and genomic DNA recovered from matched fresh and FFPE MCF10A cells. These experiments show that the TRIzol-based co-extraction method provides larger amounts of FFPE-DNA and –RNA tha

Gene Expression Profiles from Formalin Fixed Paraffin Embedded Breast Cancer Tissue Are Largely Comparable to Fresh Frozen Matched Tissue

BACKGROUND AND METHODS: Formalin Fixed Paraffin Embedded (FFPE) samples represent a valuable resource for cancer research. However, the discovery and development of new cancer biomarkers often requires fresh frozen (FF) samples. Recently, the Whole Genome (WG) DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay was specifically developed to profile FFPE tissue. However, a thorough comparison of data generated from FFPE RNA and Fresh Frozen (FF) RNA using this platform is lacking. To this end we profiled, in duplicate, 20 FFPE tissues and 20 matched FF tissues and evaluated the concordance of the DASL results from FFPE and matched FF material. METHODOLOGY AND PRINCIPAL FINDINGS: We show that after proper normalization, all FFPE and FF pairs exhibit a high level of similarity (Pearson correlation >0.7), significantly larger than the similarity between non-paired samples. Interestingly, the probes showing the highest correlation had a higher percentage G/C content and were enriched for cell cycle genes. Predictions of gene expression signatures developed on frozen material (Intrinsic subtype, Genomic Grade Index, 70 gene signature) showed a high level of concordance between FFPE and FF matched pairs. Interestingly, predictions based on a 60 gene DASL list (best match with the 70 gene signature) showed very high concordance with the MammaPrint® results. CONCLUSIONS AND SIGNIFICANCE: We demonstrate that data generated from FFPE material with the DASL assay, if properly processed, are comparable to data extracted from the FF counterpart. Specifically, gene expression profiles for a known set of prognostic genes for a specific disease are highly comparable between two conditions. This opens up the possibility of using both FFPE and FF material in gene expressions analyses, leading to a vast increase in the potential resources available for cancer research

Clinical relevance of DNA microarray analyses using archival formalin-fixed paraffin-embedded breast cancer specimens

Abstract Background The ability of gene profiling to predict treatment response and prognosis in breast cancers has been demonstrated in many studies using DNA microarray analyses on RNA from fresh frozen tumor specimens. In certain clinical and research situations, performing such analyses on archival formalin fixed paraffin-embedded (FFPE) surgical specimens would be advantageous as large libraries of such specimens with long-term follow-up data are widely available. However, FFPE tissue processing can cause fragmentation and chemical modifications of the RNA. A number of recent technical advances have been reported to overcome these issues. Our current study evaluates whether or not the technology is ready for clinical applications. Methods A modified RNA extraction method and a recent DNA microarray technique, cDNA-mediated annealing, selection, extension and ligation (DASL, Illumina Inc) were evaluated. The gene profiles generated from FFPE specimens were compared to those obtained from paired fresh fine needle aspiration biopsies (FNAB) of 25 breast cancers of different clinical subtypes (based on ER and Her2/neu status). Selected RNA levels were validated using RT-qPCR, and two public databases were used to demonstrate the prognostic significance of the gene profiles generated from FFPE specimens. Results Compared to FNAB, RNA isolated from FFPE samples was relatively more degraded, nonetheless, over 80% of the RNA samples were deemed suitable for subsequent DASL assay. Despite a higher noise level, a set of genes from FFPE specimens correlated very well with the gene profiles obtained from FNAB, and could differentiate breast cancer subtypes. Expression levels of these genes were validated using RT-qPCR. Finally, for the first time we correlated gene expression profiles from FFPE samples to survival using two independent microarray databases. Specifically, over-expression of ANLN and KIF2C, and under-expression of MAPT strongly correlated with poor outcomes in breast cancer patients. Conclusion We demonstrated that FFPE specimens retained important prognostic information that could be identified using a recent gene profiling technology. Our study supports the use of FFPE specimens for the development and refinement of prognostic gene signatures for breast cancer. Clinical applications of such prognostic gene profiles await future large-scale validation studies

Acquisition of biologically relevant gene expression data by Affymetrix microarray analysis of archival formalin-fixed paraffin-embedded tumours

Robust protocols for microarray gene expression profiling of archival formalin-fixed paraffin-embedded tissue (FFPET) are needed to facilitate research when availability of fresh-frozen tissue is limited. Recent reports attest to the feasibility of this approach, but the clinical value of these data is poorly understood. We employed state-of-the-art RNA extraction and Affymetrix microarray technology to examine 34 archival FFPET primary extremity soft tissue sarcomas. Nineteen arrays met stringent QC criteria and were used to model prognostic signatures for metastatic recurrence. Arrays from two paired frozen and FFPET samples were compared: although FFPET sensitivity was low (∼50%), high specificity (95%) and positive predictive value (92%) suggest that transcript detection is reliable. Good agreement between arrays and real time (RT)–PCR was confirmed, especially for abundant transcripts, and RT–PCR validated the regulation pattern for 19 of 24 candidate genes (overall R(2)=0.4662). RT–PCR and immunohistochemistry on independent cases validated prognostic significance for several genes including RECQL4, FRRS1, CFH and MET – whose combined expression carried greater prognostic value than tumour grade – and cmet and TRKB proteins. These molecules warrant further evaluation in larger series. Reliable clinically relevant data can be obtained from archival FFPET, but protocol amendments are needed to improve the sensitivity and broad application of this approach

Genetic Variations in the Regulator of G-Protein Signaling Genes Are Associated with Survival in Late-Stage Non-Small Cell Lung Cancer

The regulator of G-protein signaling (RGS) pathway plays an important role in signaling transduction, cellular activities, and carcinogenesis. We hypothesized that genetic variations in RGS gene family may be associated with the response of late-stage non-small cell lung cancer (NSCLC) patients to chemotherapy or chemoradiotherapy. We selected 95 tagging single nucleotide polymorphisms (SNPs) in 17 RGS genes and genotyped them in 598 late-stage NSCLC patients. Thirteen SNPs were significantly associated with overall survival. Among them, rs2749786 of RGS12 was most significant. Stratified analysis by chemotherapy or chemoradiation further identified SNPs that were associated with overall survival in subgroups. Rs2816312 of RGS1 and rs6689169 of RGS7 were most significant in chemotherapy group and chemoradiotherapy group, respectively. A significant cumulative effect was observed when these SNPs were combined. Survival tree analyses identified potential interactions between rs944343, rs2816312, and rs1122794 in affecting survival time in patients treated with chemotherapy, while the genotype of rs6429264 affected survival in chemoradiation-treated patients. To our knowledge, this is the first study to reveal the importance of RGS gene family in the survival of late-stage NSCLC patients

Genome-wide Gene Expression Profiling of Formalin-fixed Paraffin-Embedded Breast Cancer Core Biopsies Using Microarrays

The routine workflow for invasive cancer diagnostics includes biopsy processing by formalin fixation and paraffin embedding. It has been shown only recently that this kind of sample can be used for gene expression analysis with microarrays. To support this view, the authors conducted a microarray study using formalin-fixed paraffin-embedded (FFPE) core needle biopsies from breast cancers. Typically, for the 3′-biased chip type that was used, the probe sets interrogate sequences near the poly-A-tail of the transcripts, and this kind of probe turned out to be suitable to measure RNA levels in FFPE biopsies. For ER and HER2, the authors observed strong correlations between RNA levels and protein expression (p = 0.000003 and p = 0.0022). ER and HER2 classification of the biopsies by the RNA levels was feasible with high sensitivity and specificity (AUROC = 0.93 and AUROC = 0.96). Furthermore, a signature of 346 genes was identified that correlated with ER and a signature of 528 genes that correlated with HER2 protein status. Many of these genes (ER: 63%) could be confirmed by analysis of gene expression data from frozen tissues. The findings support the notion that clinically relevant information can be gained from microarray analyses of FFPE cancer biopsies. This opens new opportunities for biomarker detection studies and the integration of microarrays into the workflow of cancer diagnostics