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Methods for Gene Expression Profiling in Clinical Trials of Adjuvant Breast Cancer Therapy

Author's Affiliation: Division of Pathology, National Surgical Adjuvant Breast and Bowel Project Foundation, Pittsburgh, Pennsylvania

Requests for reprints: Soonmyung Paik, Division of Pathology, National Surgical Adjuvant Breast and Bowel Project, Four Allegheny Center, 5th Floor, East Commons Professional Building, Pittsburgh, PA 15212. Phone: 412-359-5013; Fax: 412-359-3239; E-mail: soon.paik{at}nsabp.org.

	Abstract

Top Abstract Gene Expression Profiling with... Real-time Reverse Transcription... cDNA-Mediated Annealing,... Conclusion Open Discussion References

 
Although endocrine therapy is highly effective in the treatment of endocrine receptor–positive breast cancer, chemotherapy has been shown to provide clinical benefit when added to tamoxifen. However, baseline risk after tamoxifen treatment is so low, especially in patients who are axillary node negative, that significant overtreatment will result if chemotherapy is given to every patient. Robust prognostic and predictive markers need to be developed to identify those at high risk of treatment failure. Although comprehensive gene expression profiling methods do offer promise, they require fresh or frozen tumor samples. To take advantage of existing archived tissue blocks with clinical follow-up collected from finished clinical trials, such as National Surgical Adjuvant Breast and Bowel Project trials B-20 and B-14, technologies that allow interrogation of archived blocks for gene expression profiling need to be realized. Recent developments in gene expression profiling technologies are discussed with their implications in clinical management of endocrine receptor–positive breast cancer.

Recent advances in genomics have provided tools that allow us to interrogate expression levels of entire genes in tumor cells. Studies using such tools have shown that there is tremendous heterogeneity in the molecular composition of breast cancer such that each tumor is unique, suggesting that treating every patient with same therapy probably is not the most ideal approach. However, these gene expression tools usually require very high quality RNA as a starting material. The main hurdle in identifying predictive markers for treatment benefit in the adjuvant setting, aside from the important issue of statistical power, is the lack of fresh frozen tumor tissue from large phase III adjuvant trials. Therefore, methods that allow gene expression profiling of formalin-fixed, paraffin-embedded tumor specimens, which are often fairly old, are in need. Several promising methods for gene expression profiling have been developed recently. Some of these methods will be reviewed briefly, with a focus on their potential in clinical applications.

The initial step in any gene expression profiling method is synthesis of cDNA from mRNA species extracted from the tumor tissue (Fig. 1). In the usual method of gene expression profiling, reverse transcription of the mRNA using an oligo-dT primer, designed to bind the polyadenylic acid tail of the molecule, is used to generate cDNA. In formalin-fixed tissue, the RNA has been modified by the addition of mono-methylol groups, especially to adenine, so that the oligo-dT primer cannot bind with high efficiency (Fig. 2; ref. 1). Furthermore, for unknown reasons, the RNA becomes heavily fragmented over time during storage of the blocks (2). These two problems significantly limit cDNA synthesis using RNA extracted from paraffin blocks. Several methods have been devised to overcome these limitations.

View larger version (14K): [in this window] [in a new window]   Fig. 1. Initial steps in gene expression profiling. Efficient annealing of oligo-dT primer to polyadenylic acid tail of mRNA is critical for efficient synthesis of cDNA, which is used in downstream steps for microarray or real-time quantitative PCR (Q-PCR).

View larger version (17K): [in this window] [in a new window]   Fig. 2. Problems of using RNA extracted from formalin-fixed, paraffin-embedded tissue for gene expression profiling. Chemical modification by formalin fixation (addition of mono-methylol groups to nucleotides) and fragmentation during storage prevent efficient annealing of oliogo-dT primer and reverse transcription.

	Gene Expression Profiling with Microarrays

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TransPlex whole transcript amplification kit (Rubicon Genomics, Inc., Ann Arbor, MI) bypasses the need for an intact polyadenylic acid tail by using random primers for cDNA synthesis. Adaptor-based PCR is used to amplify the cDNA. We have tested the performance of TransPlex kit by comparing gene expression in 14 cases of breast cancer with known estrogen receptor (ER) status for which the blocks were 10 years old. In microarray studies, percent present call is a term used to describe how many probes give out signal above background. In a typical experiment with fresh tumor tissue, one would expect a percent present call of 50%. Leave-one-out cross-validation is another validation method in which one case from the cohort is set aside and the rest of the cases are used to build a predictive model—in this case for ER status—and to see if the model predicts the status of the hold-out case correctly; this process is then repeated for all cases in the cohort. Percent present call in Affymetrix GeneChip X3P of 25% to 35% was achieved. The top most differentially expressed gene between ER+ and ER– groups detected by Affymetrix GeneChip was the ER gene. In the leave-one-out cross-validation, ER status (defined by immunohistochemistry) of all but one case was correctly classified. These data suggest that the TransPlex kit can be used for gene expression profiling of older paraffin blocks with high confidence. Because microarray assay allows interrogation of essentially all human genes at once, this method can be used for initial candidate gene selection.

	Real-time Reverse Transcription-PCR

Top Abstract Gene Expression Profiling with... Real-time Reverse Transcription... cDNA-Mediated Annealing,... Conclusion Open Discussion References

 
Unlike microarrays, which allow interrogation of all expressed genes but at the expense of low dynamic range, the real-time reverse transcription-PCR (RT-PCR) assay allows interrogation of the expression level of one gene at a time but with great accuracy and a wide dynamic range. Fragmented RNA extracted from paraffin blocks can be a reasonable substrate for real-time RT-PCR assay (3). However, gene-specific priming is required for cDNA synthesis for each gene target because cDNA synthesis for the entire species of mRNA using oligo-dT primed reverse transcription is not possible for the fragmented and chemically modified RNA. This means that the assay for each gene has to be done in a separate reaction tube from the point of cDNA synthesis. Highly accurate pipetting using robotics is therefore required for reproducible assay results. For this reason, when more than a handful of genes are to be assayed, fairly sophisticated laboratory facilities are required. In addition, Cronin et al. (2) have shown that absolute signal decreases significantly if blocks have been stored for long time, resulting in 100-fold reduction in signal if the block is 10 years old compared with freshly made block. However, careful normalization based on genes with minimal variation of expression level among different tumor samples can largely compensate for these differences in absolute signal (2).

In collaboration with Genomic Health, Inc. (Redwood City, CA), we have developed a multigene prognostic index for node-negative, ER-positive breast cancer treated with tamoxifen called OncotypeDx, based on 21 genes assayed by this method (3). To develop this assay, candidate genes (n = 250) were selected from literature and microarray data for breast cancer. These genes were tested in three independent cohort studies, including cases from the National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-20 (4). Univariate analysis showed that >40 genes correlated with clinical outcome in B-20 cohort. By selecting reproducible prognostic genes among three independent cohorts with robust PCR performances, a multivariate prognostic model called recurrence score was developed that included 16 cancer-related genes and 5 reference genes. Whereas the majority of genes, composed of 16 genes, are ER (ER, PGR, BCL2, and SCUBE2) and proliferation related (Ki67, STK15, Survivin, CCNB1, and MYBL2), there are other genes (HER2, GRB7, MMP11, CTSL2, GSTM1, CD68, and BACG1). The unscaled recurrence score (RSu) was calculated with the use of coefficient that is defined on the basis of regression analysis of gene expression. Recurrence score (RS) was rescaled from the unscaled recurrence score as follows: RS = 0 if Rsu < 0; RS = 20 x (Rsu-6.7) if 0 RSu 100; and RS = 100 if Rsu > 100. Final validation of the recurrence score was achieved by examination of its performance in a completely independent cohort from NSABP trial B-14, which was not used in the model building process (4). In the validation study, the assay was found to provide better and more reproducible indication of prognosis for ER-positive tumors in node-negative patients than age, tumor size, or histologic grade (3). Compared with National Comprehensive Cancer Network or St. Gallen criteria, recurrence score was able to categorize more patients into a low-risk group that had similar 10-year distant disease-free survival rates as low-risk groups identified by these criteria (Table 1).

	cDNA-Mediated Annealing, Selection, Extension, and Ligation

Top Abstract Gene Expression Profiling with... Real-time Reverse Transcription... cDNA-Mediated Annealing,... Conclusion Open Discussion References

 
One promising method is cDNA-mediated Annealing, Selection, extension, and Ligation (DASL) developed by Illumina (San Diego, CA; ref. 5). Based on its bead array platform, the DASL assay can monitor expression of up to 1,536 sequence targets (512 genes at 3 probes per gene) in 500 ng of total RNAs derived from formalin-fixed, paraffin-embedded tissue samples that have been stored for up to 12 years, according to the description of the company. The DASL assay monitors gene expression by targeting sequences in cDNAs with sets of query oligos composed of multiple parts. In addition to gene-specific sequences, the query oligos contain primer landing sites for PCR amplification and an address sequence for hybridization to the universal bead array. Because randomers are used in the cDNA synthesis and because the query oligos target cDNA sequences spanning only 50 bases, partially degraded RNAs can be used in the assay. In its design, the DASL assay resembles RT-PCR with highly multiplexed templates but with only three PCR primers. Because the oligos all share the same primers, and the amplicons are of a uniform size, the amplification step is expected to maintain an unbiased representation of transcript abundance.

We have assessed the performance of DASL using 24 cases of 10-year-old archived paraffin blocks with known ER status. ER, progesterone receptor, and insulin-like growth factor receptor were found to be significantly differentially expressed between ER+ and ER– tumors. On leave-one-out cross-validation using DASL results, 85% prediction accuracy was achieved for predicting ER status determined by immunohistochemistry. Given its low cost and the high capacity for multiplexing of the assay, DASL seems to be a very promising method that needs to be further evaluated.

	Conclusion

Top Abstract Gene Expression Profiling with... Real-time Reverse Transcription... cDNA-Mediated Annealing,... Conclusion Open Discussion References

 
Several options are available for gene expression profiling using RNA extracted from old formalin-fixed, paraffin-embedded tumor blocks. Whereas GeneChip analysis using TransPlex whole transcriptome amplification and DASL provide relatively inexpensive capability to profile >500 genes at once using a small amount of starting material (<200 ng RNA, usually requiring one to two 5-µm sections) and great discovery tools, real-time RT-PCR method is the preferred clinical assay platform based on excellent dynamic range of measurement and reproducibility.

	Open Discussion

Top Abstract Gene Expression Profiling with... Real-time Reverse Transcription... cDNA-Mediated Annealing,... Conclusion Open Discussion References

 
Dr. Myles Brown: Have you tried the Genomic Health gene set using DASL probes and tested whether that works as well as your assay?

Dr. Paik: One of the strengths of the Genomic Health assay is the dynamic range that it can provide, which is special to that active PCR because actually it is hybridized to the RNA. That is where it gets the signal. I don't think it is going to evolve as a clinical assay, but it is going to be a great initial screening tool. We think that the eventual commercialization of the assay will have to be RT-PCR, just to be reliable.

Dr. James Ingle: The relationship of HER2 and PR to outcome is a little disappointing in your data. Do you want to comment on that? From the molecular markers we have available, the only one that seems to be ready for prime time is ER. From the clinical data, you would expect some signal from the HER2 and the PR, so to see nothing—is anybody else surprised?

Dr. Paik: The main reason that HER2 and GRB7 are in the OncotypeDx assay panel is because in the model-building set using the tamoxifen treated arm from the B-20 trial, HER2 and GRB7 were among the top contenders. They were very significant prognosticators. In UB 410, it was a complete failure. It could be just a selection bias.

Dr. Mitch Dowsett: The recurrence score is much more prognostic based than it is tamoxifen response based. Had the NSABP and Genomic Health got together and said, what we want to do is to find a predictor of benefit from tamoxifen, certainly the resulting gene panel would come out differently weighted and with possibly many different genes. I think the proliferation genes are really dominant here in determining the prognostic aspect.

Dr. Paik: Yes, it is entirely possible that if you went that route, looking for tamoxifen-response genes from the beginning, you might find genes that did not have prognostic significance in the tamoxifen arm because that population all had a response to tamoxifen.

Dr. Stephen Johnston: Because it is prognostic rather than predictive, what is the bottom line here on how this will be used to help make clinical decisions? I had a patient from the States who was put on tamoxifen and had an OncotypeDx done. It was obviously being used to decide whether or not she was going to go onto chemotherapy. What is the guidance here about whether this assay is of use in making clinical decisions? What does it add over and above PR and HER2 status?

Dr. Paik: We didn't develop this as a predictive test for tamoxifen or endocrine therapy; we developed it as a prognostic test for tamoxifen-treated patients so that we can assess the baseline risk, which might aid in decision-making for chemotherapy. Luckily, it turned out to interact with the chemotherapy benefit, with patients with higher recurrence scores deriving more benefit from chemotherapy. So, for that decision making it might be useful. But for tamoxifen benefit it is simply an exploratory analysis. Because of the large confidence interval and low event rate, I don't think we can draw a line to say which patients should not get tamoxifen.

Dr. Ingle: Could we have a point-and-counterpoint discussion about the two different studies, the NASBP B-14 and the M.D. Anderson study [Clin Cancer Res 2005;11:3315–9], which did not corroborate the value of the 21-gene panel?

Dr. Paik: To me, there was no real contradiction between the two studies. If you look at the M.D. Anderson study, the assay performed as expected. ER correlated with PR, ER correlated with the IGFR, and HER2 correlated perfectly with GRB7. So it is not that the assay did not work; rather, in that clinical cohort the recurrence score did not predict recurrence. The same was true for tumor grading in that cohort, so it might be a patient selection issue.

Dr. Aman Buzdar: Yes, it was a small study in node-negative, receptor-positive patients who did not receive tamoxifen. That is one of the differences between that subgroup and the NSABP patients. The question is whether that is a self-selected subpopulation—because these were patients coming to M.D. Anderson for treatment who did not receive any systemic therapy—or is the recurrence score only predictive in the presence of tamoxifen therapy? That question cannot be answered clearly without running another cohort of patients with similar characteristics, patients who are ER positive and also node negative but did not receive any systemic therapy.

Dr. Dowsett: That is an extreme example of studies using these untreated populations as a control group, and yet they are untreated for special reasons. This sort of investigation needs to be done in the context of a randomized trial, or if you don't do it in the context of a randomized trial, you need to be very careful about the conclusions that you take from the data.

Dr. Paik: One has to realize that the OncotypeDx is not a perfect assay; it is definitely influenced by other factors. The ROC curve, the actual sensitivity and specificity of the assay, is not over 85%. So this is a method in evolution. I still regard it as a feasibility demonstration and nothing more.

Dr. Eric Winer: I was going to address Dr. Johnston's question a bit more by saying that on this side of the Atlantic, I don't know many academic breast cancer doctors who have embraced this assay wholeheartedly. On the other hand, I know many who have ordered it six to ten times over the past 6 months, and I would put myself in that group. The data from the prognostic standpoint are pretty solid. For a woman taking tamoxifen, this gives you information about her risk of distant recurrence at 5 and 10 years. The data are less solid in predicting the benefit of chemotherapy and in using it as a predictor of tamoxifen benefit.

Dr. Johnston: In terms of deciding who will get chemotherapy, other simple factors like age, tumor size, vascular invasion, quantitative level of ER, and so on, are already there for helping make that decision.

Dr. Winer: I agree with you. So how much better is this than a really good pathologist sitting next to you and giving you highly accurate tumor grading, quantitative ER, and good HER2? The problem is that level of pathology consult is not always available in the community. So what is potentially very helpful about this assay is the standardization.

Dr. Ingle: It ought to be added that we need to study this prospectively; such a study has been in the works for 2 years and will hopefully be starting up.

	Footnotes

 
Presented at the Fifth International Conference on Recent Advances and Future Directions in Endocrine Manipulation of Breast Cancer, June 13-14, 2005, Cambridge, Massachusetts.

Received 10/20/05; revised 11/28/05; accepted 11/29/05.

	References

Top Abstract Gene Expression Profiling with... Real-time Reverse Transcription... cDNA-Mediated Annealing,... Conclusion Open Discussion References

 

1. Masuda N, Ohnishi T, Kawamoto S, Monden M, Okubo K. Analysis of chemical modification of RNA from formalin-fixed samples and optimization of molecular biology applications for such samples. Nucleic Acids Res 1999;27:4436–43.[Abstract/Free Full Text]
2. Cronin M, Pho M, Dutta D, et al. Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am J Pathol 2004;164:35–42.[Abstract/Free Full Text]
3. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351:2817–26.[Abstract/Free Full Text]
4. Fisher B, Jeong JH, Bryant J, et al. Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials. Lancet 2004;364:858–68.[CrossRef][Medline]
5. Bibikova M, Talantov D, Chudin E, et al. Quantitative gene expression profiling in formalin-fixed, paraffin-embedded tissues using universal bead arrays. Am J Pathol 2004;165:1799–807.[Abstract/Free Full Text]

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