James C. Stephans

Measurement of Gene Expression in Archival Paraffin-Embedded Tissues : Development and Performance of a 92-Gene Reverse Transcriptase-Polymerase Chain Reaction Assay

Throughout the last decade many laboratories have shown that mRNA levels in formalin-fixed and paraffin-embedded (FPE) tissue specimens can be quantified by reverse transcriptase-polymerase chain reaction (RT-PCR) techniques despite the extensive RNA fragmentation that occurs in tissues so preserved. We have developed RT-PCR methods that are sensitive, precise, and that have multianalyte capability for potential wide use in clinical research and diagnostic assays. Here it is shown that the extent of fragmentation of extracted FPE tissue RNA significantly increases with archive storage time. Probe and primer sets for RT-PCR assays based on amplicons that are both short and homogeneous in length enable effective reference gene-based data normalization for cross comparison of specimens that differ substantially in age. A 48-gene assay used to compare gene expression profiles from the same breast cancer tissue that had been either frozen or FPE showed very similar profiles after reference gene-based normalization. A 92-gene assay, using RNA extracted from three 10- micro m FPE sections of archival breast cancer specimens (dating from 1985 to 2001) yielded analyzable data for these genes in all 62 tested specimens. The results were substantially concordant when estrogen receptor, progesterone receptor, and HER2 receptor status determined by RT-PCR was compared with immunohistochemistry assays for these receptors. Furthermore, the results highlight the advantages of RT-PCR over immunohistochemistry with respect to quantitation and dynamic range. These findings support the development of RT-PCR analysis of FPE tissue RNA as a platform for multianalyte clinical diagnostic tests.

Whole Transcriptome RNA-Seq Analysis of Breast Cancer Recurrence Risk Using Formalin-Fixed Paraffin-Embedded Tumor Tissue

RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts.

Identification of a novel aspartic-like protease differentially expressed in human breast cancer cell lines

Four different human breast cancer cell lines were examined to search for genes associated with tumor growth and metastasis. Each of these cell lines, MDA-MB-453, MCF-7, MDA-MB-231 and MDA-MB-435, displays different phenotypic characteristics ranging from poorly to highly tumorigenic and metastatic. The differences in gene expression profiles of these cell lines generated by differential display technique should allow one to identify candidates as putative oncogenes or tumor/metastasis suppressor genes. A novel cDNA expressed in the highly tumorigenic and metastatic cell line, MDA-MB-435, was identified and isolated by this approach. The function for this gene, designated ALP56 (aspartic-like protease 56 kDa), in tumor progression is suggested by the homology of the encoded protein to aspartic proteases, such as cathepsin D. The amino acid residues in two catalytic domains of this family are highly conserved in those domains of ALP56. Northern hybridization indicated that the expression of ALP56 is associated with growth and metastasis of MDA-MB-435 tumors in immunodeficient mice. In situ hybridization of biopsies from breast cancer and colon cancer patients indicated that ALP56 is upregulated in human primary tumors and liver metastasis. These results suggest that this novel gene correlates with human tumor progression.

The Molecular Biology of Heparan Sulfate Fibroblast Growth Factor Receptorsa

Two distinct classes of cell surface FGF-binding proteins have been identified. These receptors differ in both mode of interaction and in affinity for the FGFs. cDNAs that encode the low-affinity receptor were isolated from a hamster kidney cell line cDNA library by expression cloning. Transfected cells that contained these heparan sulfate proteoglycan FGF receptor cDNAs were enriched for by panning on basic FGF-coated plates. The analogous human cDNA was isolated from a hepatoma cell line cDNA library. The homology of our hamster cDNAs to the previously described murine integral membrane proteoglycan syndecan, together with an exact amino acid sequence match of our human-cDNA-encoded product to human syndecan, clearly indicates the identity of these independently isolated proteoglycans. Further confirmation that the expressed molecule serves as a proteoglycan core protein was achieved by immunoprecipitation of 35SO4-labeled material from solubilized transfected cells. Nitrous acid treatment and chondroitinase digestion revealed that 77% of the label was associated with heparan sulfate chains and 22% with chondroitin sulfate chains. These heparan sulfate chains contributed to the fivefold increase in the total heparan sulfate found to be present on the surface of the transfected cells compared with cells transfected with a vector lacking the cDNA insert.

Fusion transcript discovery in formalin-fixed paraffin-embedded human breast cancer tissues reveals a link to tumor progression.

The identification of gene fusions promises to play an important role in personalized cancer treatment decisions. Many rare gene fusion events have been identified in fresh frozen solid tumors from common cancers employing next-generation sequencing technology. However the ability to detect transcripts from gene fusions in RNA isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissues, which exist in very large sample repositories for which disease outcome is known, is still limited due to the low complexity of FFPE libraries and the lack of appropriate bioinformatics methods. We sought to develop a bioinformatics method, named gFuse, to detect fusion transcripts in FFPE tumor tissues. An integrated, cohort based strategy has been used in gFuse to examine single-end 50 base pair (bp) reads generated from FFPE RNA-Sequencing (RNA-Seq) datasets employing two breast cancer cohorts of 136 and 76 patients. In total, 118 fusion events were detected transcriptome-wide at base-pair resolution across the 212 samples. We selected 77 candidate fusions based on their biological relevance to cancer and supported 61% of these using TaqMan assays. Direct sequencing of 19 of the fusion sequences identified by TaqMan confirmed them. Three unique fused gene pairs were recurrent across the 212 patients with 6, 3, 2 individuals harboring these fusions respectively. We show here that a high frequency of fusion transcripts detected at the whole transcriptome level correlates with poor outcome (P<0.0005) in human breast cancer patients. This study demonstrates the ability to detect fusion transcripts as biomarkers from archival FFPE tissues, and the potential prognostic value of the fusion transcripts detected.

Abstract 4859: Tumor and normal classification of formalin-fixed, paraffin-embedded (FFPE) specimens by transcriptome RNA-seq

We have used RNA-seq to profile and compare normal and cancerous human breast tissue. FFPE breast specimens from a total of 24 patients, 12 normal (N) and 12 tumor (T) specimens from surgical resections, were analyzed on an Illumina9s GA IIx sequencer. Whole transcriptome RNA-Seq libraries were prepared after depletion of ribosomal RNA by a protocol developed at Genomic Health Inc. (GHI). The analysis was multiplexed across two flow cells using barcoding, with two specimens per sequencing lane (1 T and 1 closely age-matched N library from a different patient). FFPE tissue archive times ranged from 10 to 13 years and they were also closely matched within each lane. To evaluate reproducibility, triplicate libraries were created from 4 of the specimens and analyzed within and across flow cells. Libraries yielded, on average, 19 million 51 bp sequences. R 2 values obtained from replicate libraries prepared from the same patient RNA were > 0.9 within and between flow cells. More than 80% of known genes in the human genome were detected in all patients. Several thousand intergenic transcripts were identified by an algorithm developed at GHI. A negative binomial model with tag-wise estimates of dispersion was applied to the known genes and intergenic regions. Inter-patient count variance is generally higher in the set of intergenic sequences than in the set of gene (RefSeq) sequences. Thousands of gene (RefSeq) and intergenic sequences were found to be differentially expressed between T and N tissues. We sought to build classifiers based on flow cell #1 data that could stratify T and N tissues when applied to flow cell #2 data. Sets of genes and intergenic regions were selected for analysis based on high inter-patient count variance. Support vector machine classifiers were trained and then applied to the data from flow cell #2, and also to another GHI tumor/normal RNA-Seq study. Either a set of 100 genes (RefSeq), or a set of 70 intergenic sequences accurately distinguished tumor and normal tissues. Our results offer further evidence of the potential of RNA-Seq for discovery of biomarkers. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4859. doi:10.1158/1538-7445.AM2011-4859

18 – Differential display

Publisher Summary This chapter discusses the technique of differential display (DD). It is a powerful technique to compare patterns of gene expression in ribonucleic acid (RNA) samples of different types or under different biological conditions. DD produces partial cDNA fragments by a combination of reverse transcription (RT) and polymerase chain reaction (PCR) of randomly primed RNA. Changes in the expression level of genes are identified after separation of cDNAs on sequencing-type gels. in comparison to the conventional differential and subtractive gene cloning methods, the DD technique offers several advantages. Moreover, it requires only small amounts of RNA and is very rapid. Though it is an effective technique, certain drawbacks are associated with the DD technique. This chapter highlights the aspects of sample preparation and the use of several control steps in the DD technique, which together markedly decrease the number of false positives. The chapter also mentions the aspects of the time-consuming postdifferential display work to validate putative candidate genes. Toward the end, the chapter presents certain problems of using the DD technique that will be faced in future.