Great challenges in molecular medicine: toward personalized medicine

GENE HUNTING, SIGNALING NETWORK, AND MOLECULAR MEDICINE In the 20th century, most researchers investigated WNT signaling in cell and developmental biology by using model animals, such as Drosophila, Xenopus, and mouse. However, I was confident that WNT signaling should be investigated for clinical application by using human samples or cell lines. In 1998, I, together with post-doctoral fellows, started a human WNTome project to comprehensively clone and characterize novel human genes encoding WNT signaling molecules and to establish a “human WNT research” platform (Figure 1A). My group reported the molecular cloning and characterization of FZD1, FZD3, FZD4, FZD6, FZD7, FZD8, FZD10, GIPC2, GIPC3, MFRP, NKD1, NKD2, VANGL1, WNT3A, WNT5B, WNT6, WNT7B, WNT8A, WNT9A (WNT14), WNT9B (WNT14B), and WNT10A as the major products of the human WNTome project [reviewed in Katoh (2002a)] and of other novel human genes, such as FGF20, RhoU, RhoV, and SOX17, as byproducts of the human WNTome project. Most human genes that encode WNT signaling components had been cloned and characterized by 2002, whereas thousands of novel human genes outside of the WNT field still remained to be discovered. In 2003, colleagues and I started a post-WNTome project to identify and characterize novel human genes encoding adhesion molecules, transmembrane proteins, epigenetic regulators, and transcription factors (Figure 1A). My group reported in silico identification and characterization of novel human genes, such as ANO1 (TMEM16A), ANO2 (TMEM16B), ANO3 (TMEM16C), ANO4 (TMEM16D), ANO5 (TMEM16E), ANO6 (TMEM16F), ANO7 (TMEM16G), ANO8 (TMEM16H), ASXL2, ASXL3, BCL9L, CDC50A (TMEM30A), CDC50B (TMEM30B), CDC50C (TMEM30C), CRB2, DACT1 (DAPPER1), DACT2 (DAPPER2), DIXDC1, FAT4, FMNL1, FMNL2, FMNL3, FOXR1 (FOXN5), FOXR2 (FOXN6), HES2, HES3, HES5, JMJD1C (TRIP8), JMJD2A (KDM4A), JMJD2B (KDM4B), JMJD2C (KDM4C), JMJD2D (KDM4D), KIF27, MPP7, PRICKLE1, and PRICKLE2. The human WNTome and postWNTome projects were gene-hunting adventures that utilized molecular biology and computational biology, respectively. Interand intra-cellular signaling networks were simplified to a secondary picture consisting of nodes and edges. Nodes correspond to genes, mRNAs, proteins, or micro-RNAs (miRNAs), while edges correspond to their interactions. I then shifted my interest from the nodes to the edges and the whole picture. In 2007, my laboratory started a stem-cell signaling network project to elucidate mutual interactions of the WNT, FGF, Notch, Hedgehog, TGF-β, and BMP signaling cascades (Figure 1A) (Katoh and Katoh, 2007, 2009; Katoh and Nakagama, 2013). Recently, I was appointed as the chief editor of Frontiers in Molecular Medicine, a subor specialty journal of Frontiers in Cell and Developmental Biology. I would like to contribute to the global scientific community through Frontiers in Molecular Medicine, which aims to address the gap between cell and developmental biology and clinical medicine and to promote development of novel diagnostics and therapeutics for a variety of human diseases, including cancers, cardiovascular diseases, diabetes mellitus, eye diseases, inflammatory bowel diseases, kidney diseases, liver diseases, neurological diseases, and respiratory diseases.


MOLECULAR MEDICINE TARGETED TO THE REGULATORY SIGNALING NETWORK
Mouse mammary tumor virus (MMTV) integrates at the Wnt1, Wnt3,Wnt10b,Fgf3,Fgf4, or Fgf10 loci and induces mammary tumorigenesis [Dickson et al., 1984;Nusse et al., 1984;reviewed in Katoh (2002b)]. WNT signals are transduced through Frizzled (FZD) receptors and LRP5/6 or ROR1/2 co-receptors at both the canonical and non-canonical signaling cascades (Katoh and Katoh, 2007). Canonical WNT signals regulate cell fate (Clevers, 2006) in co-operation with FGF and Notch signals, while non-canonical WNT signals regulate cell morphogenesis and motility (Chien et al., 2009) in co-operation with FGF, TGF-β, and Hedgehog signals. The WNT, FGF, Notch, Hedgehog, and TGF-β signaling cascades constitute the stem cell signaling network, which orchestrates fetal development and post-natal homeostasis, whereas dysregulation of the stem cell signaling network causes a variety of hereditary and sporadic diseases (Katoh and Katoh, 2007).
The WNT, FGF, Notch, Hedgehog, and TGF-β signaling network is the tip of the iceberg for the regulatory signaling network that consists of signaling cascades via RTKs, GPCRs and other receptors ( Figure 1B). Mutual interactions of this regulatory signaling network should be comprehensively investigated for the development and optimization of therapeutics.

MOLECULAR MEDICINE TARGETED TO CELL BIOLOGY
Cellular adhesion, cellular polarity, cellular proliferation, cellular survival, chromatin modification, cilia formation, DNA repair, endocytosis, exocytosis, and transcriptional regulation are all major topics in cell and developmental biology and molecular medicine ( Figure 1B).
Forkhead-box (FOX) family members are DNA-binding proteins with a FOX domain that consists of two wing-like loops and three α-helices (Carlsson and Mahlapuu, 2002;Katoh and Katoh, 2004a;Hannenhalli and Kaestner, 2009). Because FOX proteins are involved in transcriptional regulation and DNA repair , germ-line mutations in the FOX family of genes cause hereditary diseases, such as Axenfeld-Rieger syndrome; lymphedema-distichiasis syndrome; blepharophimosis, ptosis and epicanthus inversus syndrome; and speech and language disorder (Lehmann et al., 2003). Somatic mutations in the FOX family of genes, including gene amplifications, point mutations, and translocations, occur in a variety of human cancers . My group identified and characterized the FOXR1 (FOXN5) gene within a cancer-associated deleted region in human chromosome 11q23.3 in 2004 (Katoh and Katoh, 2004c); Santo et al. later reported a FOXR1-MLL1 fusion caused by an intrachromosomal deletion in neuroblastoma in 2012 (Santo et al., 2012).
Extracellular DNA and circulating miRNAs are key topics in translational medicine (Wittmann and Jäck, 2010;Turchinovich et al., 2012), and epigenetics play a key role in cancerous and noncancerous diseases (Ordovás and Smith, 2010;Baylin and Jones, 2011). I recently underlined diagnostic techniques utilizing circulating miRNAs in exosomes and microsomes, therapeutics utilizing siRNAs in polymer-based hydrogel nanoparticles and therapeutics targeted to a field of epigenetic alterations (Katoh, 2013b). Manuscripts on a various aspects of cell and developmental biology that are applicable for molecular medicine are also welcome for publication in Frontiers in Molecular Medicine.

THE THREE-LAYER STRUCTURE OF OMICS MEDICINE: BIO-BANKS, DATABASES, AND A COMPREHENSIVE KNOWLEDGEBASE
Genomics, transcriptomics, proteomics and metabolomics are representative "omics" disciplines of life science that deal with the entirety of genes, transcripts, proteins, and metabolites, respectively. Omics medicine is an emerging discipline of medical science that produces large amounts of omics data on genetics, genomics, epigenetics, transcriptomics, proteomics, and metabolomics. Here, I propose my personal view on the three-layer structure of omics medicine ( Figure 1B). The first layer of omics medicine corresponds to clinical medicine that involves with patients' care and clinical sampling of blood and tissues (bio-banks). The second layer of omics medicine corresponds to basic medicine that produces cutting-edge data by using conventional molecular biology technologies, as well as high-throughput omics data using microarrays and nextgeneration sequencing technologies. The third layer of omics medicine corresponds to translational medicine, which develops novel diagnostics and therapeutics. Bioinformatics used to generate curated databases from high-throughput raw data by using algorithms (techint) is classified into the second layer, while bioinformatics used to generate a knowledgebase from manuscripts and curated databases using either human intelligence or a Watsontype supercomputer (humint) is classified into the third layer. I was engaged in clinical medicine as a physician from 1986 to 1990 and in basic medicine on WNT and FGF signaling cascades from 1990 to 2002 and have been engaged in translational medicine on the WNT, FGF, Hedgehog, Notch, TGF-β and BMP signaling cascades since 2003. The emergence of molecular biology evoked a great rotation from clinical medicine to basic medicine in the 20th century, while computer and internet technologies, an aging demography and governmental financial burdens have been promoting a rotation from basic medicine to translational medicine in the 21st century.
Industry also consists of three layers. The first layer of industry includes agriculture, forestry, fishery, and mining; the second layer of industry includes manufacturing and construction; the third layer of industry includes financial business, commerce, service, information, and health care. The Industrial Revolution caused a shift from the first layer of industry to the second layer of industry during the 18th and 19th centuries, while the Internet Revolution and Lehman Shock promoted the prevalence of commodity-assembly manufacturing to reduce personnel expenses and material costs, causing another rotation from the second layer of industry to the third layer of industry in the 21st century.
There are many analogies between the three-layer structure and development process of omics medicine and those of industry. Internet technology enabled the outsourcing of diagnostics and therapeutic optimization, which are known as telemedicine. Microarray and next-generation sequencing technologies concentrated the production of highthroughput data to world-class institutes or companies to reduce personnel and consumable expenses. Because the internet and high-throughput technologies are able to promote a leap from the first layer to the third layer of omics medicine, the global scientific community appears destined to move toward translational medicine.
Clinical medicine, basic medicine and translational medicine are responsible for the establishment and maintenance of bio-banks, databases and a comprehensive knowledgebase, respectively ( Figure 1B). All of these aspects are mutually dependent and indispensable for clinical sequencing and molecular medicine in the era of personalized medicine. I am convinced that balanced support for clinical medicine, basic medicine and translational medicine are mandatory for the mechanistic elucidation of human diseases and the development of diagnostics and therapeutics.

Masaru Katoh is supported by the National Cancer Center Research and Development
Fund.