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Transcriptome Sequencing Becoming Key Approach to Study Disease and Guide Treatment


By Monica Heger

Transcriptome sequencing is gaining ground as a method of choice for studying diseases such as cancer due to its ability to provide information on gene expression and alternative splicing events — information not available from exome sequencing or even whole-genome sequencing — researchers reported at last week's Beyond the Genome conference in Boston.

Advances in RNA-seq technology have enabled the method to become more widely used, Chad Nusbaum, co-director of the Genome Sequencing and Analysis program at the Broad Institute, said in a talk at the conference. RNA-seq methods are now strand-specific, read lengths are longer, and transcriptome assembly from RNA-seq reads is possible, he said.

Nonetheless, challenges still remain, such as scaling up so that many samples can be run at once, decreasing the amount of starting material needed, devising better methods of removing ribosomal RNA, and working with low-quality material, such as from formalin-fixed, paraffin-embedded tumors. Nusbaum added that researchers at the Broad, who recently evaluated some of the leading methods (IS 8/24/2010), are continuing to work on devising better approaches.

While improvements to the protocols are needed, researchers from the BC Cancer Agency recently used transcriptome sequencing, in conjunction with whole-genome sequencing, to help determine the best course of treatment for a patient with a rare form of adenocarcinoma of the tongue (IS 9/28/2010). Meanwhile, researchers from Boston University are using RNA-seq to study lung disease, and Genomic Health presented a poster at the conference on an RNA-seq protocol it is devising specifically for FFPE tumors. At the Advances in Genome Biology and Technology meeting earlier this year, the company presented preliminary results from a study in which it used the method on estrogen receptor-positive and -negative FFPE breast tumors that had been fixed seven to eight years earlier (IS 8/31/2010).

The main advantage of RNA-seq over exome or whole-genome sequencing is that the technique enables researchers to look at expression changes, said Rebecca Kusko, a PhD student in Avrum Spira's lab at Boston University. Kusko's team is sequencing the transcriptomes of 400 lung tissue samples from healthy and diseased patients, including those with interstitial lung disease and the airway and emphysema forms of chronic obstructive pulmonary disease.

The project is part of the Lung Genomics Research Consortium, a project sponsored by the National Heart, Lung, and Blood Institute. The samples analyzed are being provided by the Lung Tissue Research Consortium, also funded by NHLBI.

Aside from detecting expression levels, sequencing the transcriptome has allowed the group to see "alternative splicing events, evidence of transcript switching, and unannotated regions of the genome that are specific to the lung," Kusko said.

These events will be important down the road because alternative splicing events make for good disease biomarkers, and determining the isoforms that are expressed will help with drug development, she added.

The Boston team has already sequenced and analyzed about 42 samples on the Illumina Genome Analyzer and expects to have finished sequencing all 400 samples by January 2012. They are using a paired-end sequencing approach with read lengths of 75 base pairs. The project is currently the largest RNA-seq study of biopsy samples, Kusko added, which "makes the data unique," and will help "define how this type of analysis is done."


While transcriptome sequencing is still less costly than whole-genome sequencing and produces less data, Kusko said that the amount of data coming out of her group's experiments has still been "enormous," and figuring out how to analyze and interpret it has proven to be one of the major challenges of the project.

Transcriptome Sequencing in the Clinic

Steven Jones, associate director of the Genome Sciences Center at the BC Cancer Agency, discussed a study published in Genome Biology in August in which his team combined genome and transcriptomes sequencing to help guide treatment for tumors in the tongue.

Jones and colleagues sequenced the genome of the primary tumor and the transcriptome of a metastatic tumor that developed in the lung of a patient with a rare adenocarcinoma of the tongue.

The researchers initially found that the oncogene RET was highly amplified. While both the primary and metastatic tumors had numerous other mutations and copy number variations, because the RET oncogene was so highly amplified, and because there are known drugs that target that pathway, the doctors chose a drug to target the RET pathway. Within about four weeks, both the primary and metastatic tumors shrunk from 28 millimeters in size to 21 millimeters and from 27 millimeters to 22 millimeters, respectively.

"This supported our theory that RET was driving the growth of the tumor," Jones said. However, after five months, the patient began to show signs of drug resistance. A second transcriptome sequencing of the metastatic tumor revealed the expression of an additional oncogene, AKT1, which was not an important player initially, but was "now the second most highly expressed oncogene in the tumor," Jones said.

However, "what's relevant to know clinically is that the RET pathway is still highly active," said Jones. So, even though the patient was developing resistance, treatment should not be stopped, but instead, an additional drug that targets the AKT1 pathway should be added, he said.

While Jones said that the transcriptome data provided valuable information that helped the team to determine the important pathways involved in the spread of cancer, he saw transcriptome sequencing and whole-genome sequencing as being complementary to each other. "The genomic sequence would be able to determine whether expression changes correlated with known genetic changes correlating with the disease," he said, which "might also allow a more robust comparison with other tumors where the responses to drugs are known."

In addition, transcriptome sequencing is biased towards highly expressed genes, Jones added. So, genomic sequencing is a good way to get coverage of lowly expressed genes.

Whether transcriptome sequencing is used alone or in conjunction with whole-genome sequencing, researchers have become more interested in the technology. Strand-specific data allows researchers to find data they would otherwise not have gotten, and the longer reads are improving gene annotations, Nusbaum said in his talk. In addition, paired-end reads are helping to assemble even lowly expressed genes. "The toolkit is now coming together," he said.

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