New Technologies to Further Genomics in Clinical Research

Rapidly evolving technologies in genomic research and the accessibility of genomic data within recent years have significantly changed biomedical research. Identification of small noncoding RNAs and their implication in healthy and disease states, faster and less expensive sequencing technology, and next-generation sequencing (NGS) have paved the way for genomics from basic research into clinical diagnostics. Clinical genomics is the application of large-scale, high-throughput genomic technologies in clinical settings to gain a better understanding of healthy and disease states. Genomic evaluation and gene-based testing will expand diagnostics into early detection and predisposition, and help to predict the best possible therapy for patients.

Next-generation sequencing

The tremendous advances in NGS technologies have made the sequencing of entire genomes faster and more economical. This high-throughput method has revolutionized genomic research, including gene expression profiling, small noncoding RNA identification and profiling, as well as epigenetic modifications. However, researchers often focus on a small section of the genome, specific exons, and distinct pathways to understand cellular mechanism in healthy and complex diseases such as cancer, diabetes, and neurological and cardiovascular diseases. Genomic testing is, to a limited extent, already part of some clinical routines, such as genetic testing for BRCA1 and BRCA2 mutations to evaluate the risk of breast and ovarian cancers in women with a family history of these diseases.1 Also, pharmacogenomics is gaining a more important role in clinical settings. In 2005, the FDA approved the first broad pharmacogenomics test for UGT1A1*28 polymorphism to determine irinotecan-induced gastrointestinal and bone marrow toxicity. Irinotecan is the key component of the standard firstline treatment for advanced colon cancer and rectal cancer, and the UGT1A1 test detects a change in the DNA of a gene that encodes for a protein involved in the metabolism of irinotecan.2

Increasing interest in personalized medicine and pharmacogenomics demonstrates the potential and the limitations of NGS. Despite the drastic reduction in the cost of NGS, it is impossible to sequence and analyze a large patient cohort to obtain statistically meaningful data at a reasonable cost and time frame.

Targeted resequencing

The low sample throughput of NGS technologies still prevents large-scale molecular profiling studies. Use of a targeted resequencing strategy is an alternative because complete genome sequencing is often not necessary. The sequencing of genomic regions that are involved, or are thought to be involved, in diseases shows promising outcomes. Once identified, the targeted resequencing of the disease gene pathway allows the researcher to analyze a large patient/sample cohort at a lower cost to obtain meaningful clinical data.

Resequencing technologies for large-scale studies need to be accurate and cost-efficient, and produce manageable amounts of data. Furthermore, critical parameters of genome-scale sequence enrichment are the specific enrichment of different loci relatively independent from their size and automation of the process with a simple work flow. The automation of the sequence enrichment process also guarantees a small error rate and reliable results.

Figure 1 - a) Geniom RT Analyzer. b) Step 1: The genomic DNA is isolated. 2: The genomic DNA is fragmented and adapters are ligated. 3: The fragments are hybridized to capture probes on arrays, whose base sequences correspond to the target sequences. 4: Through stringent washing, nonspecific fragments are removed, and the specific fragments can be eluted. 5: The selected and enriched fragments are available for high-throughput sequencing.

The majority of sequence enrichment technologies utilize a similar principle. The genomic target sequence is captured via hybridization to oligonucleotides; unspecific DNA is removed; and the remaining target DNA is amplified with polymerase chain reaction (PCR) and long-range PCR, a time-consuming and error-prone amplification method. Two techniques using microarray as a sequence-capture tool for NGS have been described thus far. HybSelect™ (febit holding gmbh, Heidelberg, Germany) uses compartmentalized microfluidic biochips that contain eight channels for separate samples. The corresponding Geniom® RT Analyzer platform (febit) (Figure 1a) shortens the hybridization time to 16 hr, followed by washing steps to remove unwanted sequences. Finally, the library fragments are eluted for sequencing without further amplification to avoid PCR amplification-involved bias (Figure 1b). The automation of this platform requires only 15 min of hands-on time and provides high enrichment factors and accuracy.3

Summerer and colleagues used 50-mer DNA probes in tiling arrays to capture the cancer-related genes BRCA1 and TP53 and 1000 regions of 500 bp containing reference single-nucleotide polymorphisms (SNPs) for NGS on analyzer platform A. The overall enrichment factors were over 1000-fold with 97% or more of the target region being covered. A 100% concordance of the 99% SNP calling rate was shown for HybSelect sequence enrichment and sequencing compared to the sequencing-only process.4

Schracke et al. resequenced 68 genes from three major pathways of Escherichia coli. The authors used a microfluidic array (Geniom Biochip), consisting of eight arrays with 15,624 individual DNA oligonucleotides (50 mers) features, for the HybSelect sequence enrichment. The DNA synthesis was performed in the Geniom One Instrument, which utilizes microfluidics for light-activated oligonucleotide synthesis. The hybridization and all washing steps were carried out in the fully automated Geniom RT Analyzer, and eluted target DNA was resequenced on analyzer A. The results showed good data reproducibility and low error rates for HybSelect. Furthermore, this technology demonstrates sufficient capacity for multiplexing experiments.5

Several laboratories currently use HybSelect sequence-capture technnology to investigate different diseases. An ongoing study determines genes involved in the development and progression of malignant brain cancer. The Geniom Biochip (human cancer biochip for HybSelect) features 115 genes identified by the Wellcome Trust Sanger Institute (Cambridge, U.K.) as being associated with the most common cancer types. A second study focuses on the discovery of biomarkers for Alzheimer's disease.

These and further studies will promote the routine application of the user-friendly and high-throughput HybSelect technology for clinical trials and pharmacogenomics.

MicroRNA (miRNA) profiling

MiRNAs are a class of small, noncoding RNAs that have been implicated in developmental, physiological, and pathological processes. Deregulated miRNAs are identified in a variety of diseases, especially cancer. Thus, deregulated miRNAs have been found in cancerous tissue and, more recently, in the blood cells of cancer patients. Due to their stability in body fluids and their tissue, disease, and disease-progression specific profiles, serum miRNAs are seen as novel and very specific biomarkers.

A recent study identified with 95% accuracy 27 significantly deregulated miRNA blood cell samples of non-small-cell lung cancer patients compared to healthy volunteers. Total RNA was isolated from blood samples, and the miRNA expression was evaluated with the Geniom RT Analyzer platform using the Geniom Biochip miRNA homo sapiens. Each array contains seven replicates of 866 miRNAs and miRNA star sequences as annotated in the Sanger miRBase 12.0. The Geniom Biochips are available as customized biochips or capture probe design based on the latest sequence data available in the miRBase. febit currently offers catalog biochips covering the recently updated Sanger miRBase 14.0, which contains more than 10,000 entries. Both customized and catalog biochips allow the identification of individual miRNAs as well as complete miRNA signatures with high accuracy. Together with the corresponding Geniom RT Analyzer platform, this high-sample-throughput technology can be used for large-scale clinical studies. Importantly, blood samples from patients and volunteers are easily accessible. The proof-of-concept was published in October 2009.6

A second study, using the same Geniom Biochip miRNA homo sapiens and the Geniom RT Analyzer platform, investigated the miRNA expression profile in patients with relapse-remitting multiple sclerosis, a chronic inflammatory demyelinating disease of the central nervous system, compared to healthy controls. The investigators identified with high accuracy 48 miRNA biomarkers out of 866 human miRNAs to be deregulated in multiple sclerosis patients. MiRNAs have the potential to serve as diagnostic biomarkers for multiple sclerosis, and further studies will evaluate whether miRNAs will be reliable biomarkers for the different pathogenetic subtypes of multiple sclerosis.7

Further studies will also determine the miRNA profiles for other diseases and monitor their progression and therapy. Large-scale clinical trials will verify the new findings, and eventually miRNA profiles will be implemented in clinical routine testing, meeting the demand for a cost-effective, sophisticated, accurate, and high-performance technology with minimal hands-on time.

References

  1. Fackenthal, J.D.; Olopade, O.I. Breast cancer risk associated with BRCA1 and BRCA2 in diverse populations. Nat. Rev. Cancer2007, 12, 937–48.
  2. Iyer, L.; Das, S.; Janisch, L.; Wen, M.; Ramírez, J.; Karrison, T.; Fleming, G.F.; Vokes, E.E.; Schilsky, R.L.; Ratain, M.J. UGT1A1*28 polymorphism as a determinant of irinotecan disposition and toxicity. Pharmacogenomics J.2002, 2, 43–7.
  3. Summerer, D. Enabling technologies of genomic-scale sequence enrichment for targeted high-throughput sequencing. Genomics 2009, Aug 29 [Epub ahead of print].
  4. Summerer, D.; Wu, H.; Haase, B., Cheng, Y.; Schracke, N.; Stähler, C.F.; Chee, M.S.; Stähler, P.F.; Beier, M. Microarray-based multicycle-enrichment of genomic subsets for targeted next-generation sequencing. Genome Res. 2009, 9, 1616–21.
  5. Schracke, N.; Kornmeyer, T.; Kränzle, M.; Stähler, P.F.; Summerer, D.; Beier, M. Specific sequence selection and next generation resequencing of 68 E. coli genes using HybSelect. New Biotechnology  2009, Sep 6 [Epub ahead of print].
  6. Keller, A.; Leidinger, P.; Borries, A.; Wendschlag, A.; Wucherpfennig, F.; Scheffler, M.; Huwer, H.; Lenhof, H.P.; Meese, E. miRNAs in lung cancer—studying complex fingerprints in patient’s blood cells by microarray experiments. BMCCancer 2009, Oct 6, 9, 353.
  7. Keller, A.; Leidinger, P.; Lange, J.; Borries, A.; Schroers, H.; Scheffler, M.; Lenhof, H.P.; Ruprecht, K.; Meese, E. Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsingremitting disease from healthy controls. PLoS One 2009, 4(10), e7440.

Mr. Staehler is Chief Scientific Officer and Vice President of Marketing and Sales, febit holding gmbh, Im Neuenheimer Feld 519, 69120 Heidelberg, Germany; tel.: +49 6221 6510300; e-mail: [email protected].