Finding the best therapy match for a tumor is a challenge—not only because there are so many treatment options to choose from, but also because of the high complexity of tumor biology.
Sequencing technologies, especially state-of-the-art next generation sequencing (NGS) methods, allow precise characterization of differences between tumor and healthy tissues. However, NGS is expensive, and data are often hard to interpret, so its application in cancer therapy is lagging behind.
From plant breeding to tumor analysis
To get NGS ready for routine diagnostic applications, researchers at GenXPro developed an alternative RNA sequencing strategy called Massive Analysis of cDNA Ends, or MACE-Seq. With a background on genomic analysis of cultivated plants that often have 4, 6, or even more sets of chromosomes, they were already experienced with analyzing complex genetic information.
To reduce the complexity of their data, they first switched from analysing DNA to RNA, shifting their focus to genetic information that is actually expressed—and therefore relevant—at a given time. Still, sample and data processing of entire transcriptomes is far too complex to be applied in routine work.
Reducing complexity—but with care
The challenge of course is to reduce complexity while still obtaining meaningful data. MACE takes advantage of scientific findings showing that the majority of allelic differences within a gene are located in the 3’ ends and untranslated regions (UTRs) of a transcript, where most of the binding sites for regulatory elements influencing mRNA stability have been identified.
In tumor cells, these regulatory regions have been shown to be particularly short, allowing oncogenes to evade regulation by small RNAs.
Digging deep into mutational hot spots
Focusing on the 3’ end (corresponding to about 10–15% of the average transcript) means that the sequence coverage—or depth of information—of mutations in this region obtained during sequencing is several times higher with the same number of reads.
“Many tumor diagnostic labs have started using small desktop NGS instruments,” Björn Rotter, PhD, Chief Scientific Officer at GenXPro, explains. “However, the capacity of these instruments is limited: in one run, you can sequence the entire transcriptome of a single sample. With MACE, each run provides relevant information of the 3’ hotspot region of 4-6 patients, enabling a broader use of NGS in diagnostics.”
Eliminating PCR bias in NGS
But this is only one feature of MACE. In combination with GenXPro’s proprietary TrueQuant technology, each mRNA is unambiguously barcoded. These barcodes, or unique molecular identifiers (UMIs), are part of the adapter primers that are ligated to each fragment during the sample preparation procedure.
“The use of UMI barcodes has several advantages,” Björn points out. “First, we can eliminate bias from the PCR reactions performed during NGS sample preparation. Even if some fragments amplify better than others, we only count them once, because they all have the same barcode. Second, the software automatically chooses the reads with the best data quality.”
From single genes to molecular patterns
More importantly, UMI barcodes enable precise quantification of transcripts, regardless of expression level. “Even mRNAs present in very few copies, such as receptors or transcription factors, are reliably detected,” Björn says. “A well-known example is the epidermal growth factor receptor, or EGFR, an important target for cancer therapy.”
However, in tumor biology, looking at single transcripts can be misleading. Biochemical pathways are complex and often redundant, and tumor cells under selective pressure of a therapeutic drug evade therapy by switching between alternative pathways.
“To better address the complexity of cancer, we are looking at molecular patterns rather than individual mutations,” Björn points out. “With MACE, we can detect and quantify 25,000 mRNAs in a sample, which is 10-20 times more than our competitors can.”
“Our next big goal is to correlate these molecular patterns to activity spectra of compounds already used in cancer therapy,” Björn explains. “Using this approach, we have already successfully identified a therapy for metastasized sarcoma based on changes in drug target transcript patterns. Now, we are building a virtual molecular tumor board database to facilitate recommendations for cancer drugs or drug combinations.”
Looking at tissue archives and small RNAs
Current scientific efforts include a comparison of formalin-fixed, paraffin-embedded (FFPE) samples with untreated, fresh material. FFPE is a frequently used method for tissue archiving that preserves tissue morphology, but severely damages RNA. “Interestingly, as with MACE, we are only looking at the 3’ end of each mRNA, the damage caused by FFPE embedding does not seem to impair our data,” Björn points out.
Another area of interest is the sequencing of small RNAs—the interaction partners binding to the 3’ untranslated regions. Small RNAs are often used as diagnostic biomarkers and are isolated from so-called liquid biopsy samples such as blood or urine. “As they are typically present only at low concentrations, NGS sample preparation of small RNAs is challenging,” Björn says. “Therefore, we have developed a one-tube, gel-free procedure with optimized recovery that, for the first time, enabled next-generation sequencing of microRNAs from only 100 µL sample—blood, plasma, urine, or even exotic liquid biopsies such as aqueous humor from individual human eyes.”
GenXPro first started offering MACE and small RNA technologies as part of their NGS services. “Now that more and more researchers have access to NGS instruments, we have developed kits and user-friendly analysis software for easy integration into existing workflows,” Björn explains. “Sample datasets are available on our website for free download.”
Learn more about the applications of MACE and RNAseq strategy in NGS by visiting GenXPro’s website here.