We are engaged in developments of biomarkers based on nucleic acids, and analysis of biological features relevant to biomarker developments.
1.Developments of biomarkers based on nucleic acids.
It is important to describe patient status accurately for proper diagnosis. One of diagnostic methods for cancer is biomarker, biological substance which accurately surrogate pathological parameter(s) of a patient. Exploration of new biomarkers is one of the major topics of the current cancer research. In particular, molecular targeted drugs are often effective and administrated only to cancer subtypes defined by genetic aberration. This is a good example of "personalized medicine", i.e., decision of therapy based on genetic information of patients (Figure 1). We intend to invent new biomarkers based on nucleic acids. Two approaches are being undertaken: detection of rare mutation alleles derived from tumor cells in peripheral blood; prognosis prediction by gene expression profiling.
a. Non-invasive personalized medicine based on mutation detection in peripheral blood
Gefitinib is a good example of "personalized medicine." it is only used for lung cancer with activating EGFR mutations. An important concern in clinical practice is that biopsy to obtain tumor samples is often difficult. In particular, biopsy for advanced or resistant cases is very difficult, and repeated sampling is almost impossible. A non-invasive technique such as detection of tumor DNA in peripheral blood is desirable. There are several approaches to detect tumor cells (circulating tumor cell, CTC) or tumor DNA (circulating tumor DNA, ctDNA) in blood. We introduced a technique named BEAMing (beads, emulsion, amplification, matnetics) (Dressman et al., PNAS, 100, 8817, 2003), and used it for detection of EGFR mutations in plasma of lung cancer patients (Taniguchi et al., 2011). In addition to its high sensitivity, BEAMing allows the digital quantification of mutant alleles. All patients treated with gefitinib develop resistance to the agent, and half of them are due to T790M resistant EGFR mutation. With BEAMing, the fractions of the T790M resistant cancer cells can be estimated through ratio of activating and resistant mutations. It should be noted that BEAMing and next-generation sequencers are based on the same technological principle. The mutations are sought with massively repeated sequencing of the EGFR gene fragments. We have already set up an assay system with Ion Torrent Personal Genome Machine, and are confirming its feasibility for EGFR mutation detection with Department of Thoracic Oncology.
b. Gene expression profiling
Gene expression profiling is one of the genomic approaches, measuring expression levels of a large number of genes simultaneously. DNA chip or DNA microarrays are the most popular technique. Instead, we developed a high-throughput quantitative PCR technique named adaptor-tagged competitive PCR (ATAC-PCR) (Kato, 1997), and had conducted analysis of more than 1,500 solid tumor tissues. The expression data and accompanying clinical information are stored in Cancer Gene Expression Database (CGED, http://lifesciencedb.jp/cged). The major outcomes include prediction of prognosis (Iwao et al. 2002) and docetaxel response (Iwao-Koizumi et al. 2005) in breast cancer, and prediction of prognosis in glioma (Shirahata et al. 2009) (Figure 3). We continue the studies to develop the outcomes into diagnostic systems. In particular, we converted the diagnostic system of glioma into that based on real time PCR (Kawarazaki et al. 2010), and now are confirming its performance with samples in the Kitano Hospital, the National Cancer Center Hospital and Tokyo Women's Medical University Hospital. From a collection of genes related to docetaxel resistance, we identified RPN2 as a potential target for drug development (Homma et al. 2008). siRNA against RPN2 enhanced the anti-cancer activity of docetaxel. This is a good example of drug target discovery through gene expression profiling.
2. Cancer research with the next generation sequencer
The next generation sequencers are currently the most important technical breakthrough in bioscience and biotechnology. The cost for sequencing is now less than 1/100,000 of that with the conventional sequencer. It is now possible to sequence genomes of individuals. The cost for the full genetic information of an individual is roughly 500,000 yen, and we can expect decrease in a order of magnitude in the next two or three years. Under these circumstances, OMCCCD (Osaka Medical Center for Cancer and Cardiovascular Diseases) finished discussions on the ethical issues in 2009, and made the laboratory of genome informatics to handle the whole genome information of individual patients. Our research focus is gastric, colorectal and lung cancers with genetic predispositions or very rare phenotypes.
3. Genetic structure of the human cancer tissues
The human cancer is usually considered as developed by clonal expansion of a single malignant cell. In reality, most of the cancer tissues consist of a number of malignant cells with different genome alterations and biological characteristics. We found that there were lung cancer tissues with a mixture of EGFR mutation-positive and negative tumor cells (Taniguchi et al., 2008) (Figure 4). Gefitinib is an anti-cancer drug targeted to EGFR, and effective with lung cancer with EGFR mutation. Patients with such tissues were less responsive to gefftinib than those only with EGFR-mutated cells. As exemplified with this case, the intratumor heterogeneity of cancer cells would be a cause of anti-cancer drug resistance. We also found that some liver metastasis of colorectal cancer contained two or more cancer cell subpopulations of unique genotypes (Goranova et al., 2011).
| Fig.1.Personalized medicine.
Detection of activating EGFR mutation in plasma of a lung cancer patient with massively repeated sequencing. Horizontal axis, sequence of EGFR exon 19; vertical axis, proportion of insertion/deletion (%). The 15 base-deletion is detected.
|Fig.3. Kaplan-Meier analysis of glioma patients stratified with our prognosis predictor. All patients were stage IV.
|Fig.4. Genetic intratumor heterogeneity in lung cancer.