As the first financial quarter of the year came to a close, Affymetrix and Agilent, the microarray industry leaders, were on hand at the American Association of Cancer Research meeting held in Orlando, Fla.
So too were those on the second and third tiers of the industry, as well as many wannabes. All showed up seeking to provide products and services to a well-heeled customer segment, the 15,000 members of this association who represent a big part of the estimated $14.5 billion spent annually in the US on cancer-related research activities.
Microarrays are firmly established in cancer research laboratories, and the five-day meeting clearly reflected that — with literally hundreds of presentations, papers, and posters referencing the technology either directly or indirectly.
This technology for the massively parallel analysis of gene expression has been around in a commercial form for about a decade and cancer researchers have clearly been early adopters of the technology to the point where they are looking ahead to add new layers of tool-driven insight. The scientific discovery this platform has enabled is rippling the waters of medicine as scientists — and regulators — grapple with how to most beneficially harness the [thus-far, incalculable] predictive information it provides.
The insights gained from, first, the sequencing of the human genome, and then the almost daily roll call of species newly sequenced; coupled with the flood of data from almost a decade of microarray-based gene-expression profiling, are forcing a new approach that couples these tools with others.
For the highest levels of cancer research, that means a systemic approach to unraveling the multifaceted disease.
“We really don’t know how to most accurately interpret the information from microarrays, especially from independent cells from independent groups,” said Geoffrey Wahl, a professor in the gene-expression laboratory of the Salk Institute for Biological Studies of San Diego, who was program chairman for the conference. “When you look at [array data] with a systems perspective, then [it] makes sense. We are starting to parse the tumors into systems analytical approaches, so that we are looking at the pathways that are being expressed. Microarrays are providing a part of the picture, that’s transcription.”
To Wahl, however, the genome includes not only DNA, but RNA, the proteins that are expressed, the constellation of molecules expressed on the surface, and the constellation of molecules expressed in the intracellular environment.
“It’s mass unbiased analysis, it’s genomic interrogation,” said Wahl. “That’s the thing that we can’t forget about either.”
The “interrogation” Wahl referenced can now be carried out on archives of formalin-fixed, paraffin-embedded tissues.
The Fox Chase Cancer Center of Philadelphia announced during the conference that it had extracted RNA from formalin-fixed, paraffin-embedded tissue samples in a late-breaking paper submitted by Renata Coudry, a Fox Chase Center research pathologist.
The center used an Arcturus Bioscience reagent product to isolate and amplify RNA from archival specimens. Then, researchers used laser capture to microdissect colonic crypt tissues from the archived samples. They then developed genetic profiles for microarray analysis.
Others are using an older tissue array technology, making small cores of tissue arrayed on a substrate to create a platform for large-scale analysis.
At the Yale University School of Medicine, a team of Yale Cancer Center researchers used archived paraffin blocks of pancreatic tissues to create microarrays of 1.5-mm sliced cores that are then imaged on a custom-built instrument after staining and the inclusion of multiple fluors.
“We’re kinda, sorta doing microdissection,” said Gina Chung, an assistant professor of medical oncology at Yale.
The results of the research were presented in a paper, “Quantitative immunohistochemical analysis of VEGF expression on a pancreatic cancer tissue microarray.” The paper included the announcement of a set of algorithms to assess the arrays by way of fluorescent tags.
Anne Tsao, a medical oncology fellow at the MD Anderson Cancer Center in Houston, used tissue microarrays for a retrospective study conducted on archived tissues presented in an AACR poster entitled: “Smoking does not correlate with pAKT expression in NSCLC.”
Tissue arrays, Tsao said, are simple to use.
“You can squeeze hundreds of samples onto a slide, and any pathologist can do them,” she said.
For other researchers, another key microarray tool gaining use is comparative genomic hybridization.
Mark Basik, a surgeon at Jewish General Hospital of McGill University of Montreal, combined cDNA analysis and CGH on the same 16,000-spot cDNA microarray slides, to conduct research on herceptin-resistant breast cancer cell lines.
“This study illustrates the advantage of combined cDNA and CGH microarray analysis in prioritizing gene-expression changes in the study of anti-cancer therapy resistance,” the poster concluded.
“The idea of combining genomic alterations with gene expression as a method to understand the targets of drug resistance is not new,” said Basik. Now, “[w]e just have the technology to do it.” Abdel El Kahloun at the National Human Genome Research Institute, Basik said, spotted the arrays.
Basik said he would consider doing the research again, and had been investigating using Agilent’s oligonucleotide-based arrays instead. However, he said he didn’t think that the oligos-as-probes strategy is quite mature enough for the CGH technique.
“The thing about [oligos] is that you are hybridizing DNA to something that is smaller instead of something bigger and there might be splice variants,” he said. The study he presented used amplified clones of 200 mers to 250 mers.
In terms of other formats, he said, “I wouldn’t even try this at 25 mers,” he said. “But I’m sure that someone will try, and I’m sure Affy is trying it now.”
Affymetrix’s probes are designed at a length of 25 mers.
In another research effort combining platforms, Daniel Scott and a team of researchers from the University of Leeds, UK, and the department of biochemistry and molecular biology at Howard University in Washington, DC, presented a paper “A genetic and proteomic approach to identify factors involved in Tamoxifen responsiveness.”
The team used Affymetrix U133a GeneChips to look at 18,500 transcripts to compare gene expression in Tamoxifen-sensitive vs. Tamoxifen-resistant cells. Those results are now being confirmed by RT-PCR. Protein changes were analyzed via 2D gel analysis and mass spectrometry, with findings confirmed by Western blot analysis.
“Together these may provide an insight into pathways associated with Tamoxifen response and acquired resistance,” the group’s poster concluded.
The experience left the researcher a bit wiser about both platforms.
“Microarrays are a helluva lot easier,” said Scott. “Proteomics is lacking user-friendliness and, technically, it is a bit more long-winded.”
Still, he said his team found hundreds of genes differentially regulated at the mRNA level, while at the protein level, they found 10s of genes.
The limiting factor, he said, was the numbers of commercially available antibodies.
He hopes for a time when a manufacturer can put 20,000 antibodies on a chip.
“Hopefully,” he said, proteomics can capture a signal like a microarray does.
For other researchers, tool issues are simpler. It’s about cost.
Take, for example, Ellen Friday, a research associate in the Feist-Weiller Cancer Center of the Louisiana State University Health Sciences Center in Shreveport.
Friday was presenting a poster on research correlating the expression of VEGF in hematopoietic cell lines and said the next step in the research should include microarray analysis. Although the lab has access to an Affymetrix facility, she added that Affymetrix arrays would not be a first option.
“I would love to use their arrays [in this research],” said Ellen Friday, a postdoctoral researcher. “But they are too expensive to go on a fishing trip, to screen the number of samples we would like to screen.”
For another project, to do an initial screen, Friday said she spent $10,000 on Affymetrix chips, and another $3,000 on the processing. “This was a dose-time study and this was just enough to get a duplicate of each,” she said. “We made the investment in the hopes that something was going to fall out and we could then turn around and write a grant to get the money to do more times, to do more studies.”
Ellen said microarrays, however, are becoming a must-do in her line of research.
“When you send a grant to any review committee, it seems like the only comment that comes back is “Why don’t you do microarrays?” And they almost always suggest the Affy, which I think is because they were the first ones out there on the market, and I think everyone is more familiar with those.”
But, she said, she doesn’t have access to another technology. The cancer research center has an Affymetrix system, and has encouraged researchers with grants of just enough funds to cover the cost of five GeneChips.
“That’s just enough to whet your appetite,” she said, with a laugh as she added, “then, once you are hooked on running Affy, you will buy more, and you will run more, and the technicians will be busy, and . . .”
At the Georgetown University Medical Center, which has two Affymetrix instrument packages in place, Robert Clark, a professor of oncology, physiology, and biophysics at the Vince Lombardi Cancer Center, opts to do his fishing trips on nylon arrays, which cost less than $100 per chip.
“There is more variability, more background and there are other factors, but if you want to do something for a first-cut, quick-and-dirty experiment to find out what is going on, then these are much cheaper,” Clarke said.