This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Kakiuchi, S. Articles by Nakamura, Y. Search for Related Content PubMed PubMed Citation Articles by Kakiuchi, S. Articles by Nakamura, Y.

---

Angiogenesis, Metastasis, and the Cellular Microenvironment

Genome-Wide Analysis of Organ-Preferential Metastasis of Human Small Cell Lung Cancer in Mice¹

¹ Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan;
² Laboratory for Medical Informatics, SNP Research Center, Riken (Institute of Physical and Chemical Research), Tokyo, Japan; and
³ Department of Internal Medicine and Molecular Therapeutics, The University of Tokushima School of Medicine, Tokushima, Japan

Requests for reprints: Yusuke Nakamura, Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. Phone: 81-3-5449-5372; Fax: 81-3-5449-5433. E-mail: yusuke{at}ims.u-tokyo.ac.jp

	Abstract

Top Notes Abstract Introduction Results Discussion Materials and Methods References

 
Although a number of molecules have been implicated in the process of cancer metastasis, the organ-selective nature of cancer cells is still poorly understood. To investigate this issue, we established a metastasis model in mice with multiple organ dissemination by i.v. injection of human small cell lung cancer (SBC-5) cells. We analyzed gene-expression profiles of 25 metastatic lesions from four organs (lung, liver, kidney, and bone) using a cDNA microarray representing 23,040 genes and extracted 435 genes that seemed to reflect the organ specificity of the metastatic cells and the cross-talk between cancer cells and microenvironment. Furthermore, we discovered 105 genes that might be involved in the incipient stage of secondary-tumor formation by comparing the gene-expression profiles of metastatic lesions classified according to size (<1 or >2 mm) as either "micrometastases" or "macrometastases." This genome-wide analysis should contribute to a greater understanding of molecular aspects of the metastatic process in different microenvironments, and provide indicators for new strategies to predict and prevent metastasis.

Key Words: metastasis • microenvironment • small cell lung cancer • expression profile • therapeutic target

	Introduction

Top Notes Abstract Introduction Results Discussion Materials and Methods References

 
Metastasis is the major cause of death due to cancer. Because no absolutely effective methods for curing metastatic tumors are available at present, novel strategies for prevention of metastasis are urgently needed to improve the prognosis and quality of life for cancer patients. Metastases occur in sequential steps that include invasion of cancer cells from the primary site to blood vessels or the lymphatic system, survival in the circulation, intravascular transfer to distant organs, attachment to endothelial cells, extravasation into the parenchyma, and outgrowth into a secondary tumor with neovascularization (1–4).

Molecular interactions between cancer cells and their microenvironment(s) play important roles throughout the multiple steps of metastasis (5). Blood flow and other environmental factors influence the dissemination of cancer cells to specific organs (6). However, the organ specificity of metastasis (i.e., some organs preferentially permit migration, invasion, and growth of specific cancer cells, but others do not) is a crucial determinant of metastatic outcome, and proteins involved in the metastatic process are considered to be promising therapeutic targets.

More than a century ago, Stephen Paget suggested that the distribution of metastases was not determined by chance, but rather that certain tumor cells ("seed") are likely to have an affinity for the microenvironment of specific organs ("soil") and that metastases occur only when the seed and soil are compatible (7). Various molecules such as adhesion molecules, cytokines, chemokines, hormones, and hormone receptors play important roles in preferential metastasis (1, 8–10), but the precise mechanisms determining seed and soil compatibility remain unsolved.

To examine the cellular and molecular bases of organ-specific metastasis, we have established models of metastasis to multiple organs by i.v. injection of eight different human lung cancer cell lines to severe combined immune deficiency (SCID) mice devoid of natural killer (NK) cells (11, 12). In the work reported here, by means of a cDNA microarray consisting of 23,040 genes, we analyzed the gene-expression profiles of 25 metastatic lesions present in murine lung, liver, kidney, and bone following i.v. injection of human small cell lung cancer (SCLC) (SBC-5) cells. In the process, we identified candidate genes that may affect or determine organ specificity of the metastatic cells, as well as genes involved in progression from micrometastasis to macrometastasis. Genes in both categories represent potential molecular targets for prevention of metastasis in humans.

	Results

Top Notes Abstract Introduction Results Discussion Materials and Methods References

 
Metastasis of Human SCLC Cell Line SBC-5 in NK Cell-Depleted SCID Mice
As we reported previously, i.v. injection of SBC-5 cells into SCID mice lacking NK cells caused metastases to multiple organs (11, 13). To compare gene-expression profiles of 25 selected metastatic lesions (10 in lung, 5 in liver, 5 in kidney, and 5 in bone), we collected pure populations of cancer cells by laser-capture microdissection. Histopathological features of each of the 25 lesions are shown in Fig. 1, A–D, and in Table 1. Three of the 10 lung foci developed in subpleura, and 5 were accompanied by intravascular embolization. The distribution of metastases in lung was similar to that found in another experimental model of metastasis published elsewhere (2). All bone metastases were accompanied by the osteolytic changes commonly observed in human SCLCs (11). As in human cases, metastases in murine kidney were smaller than those arising in other organs.

View larger version (158K): [in this window] [in a new window]   FIGURE 1. Histopathology of metastatic lesions (H&E stain). A. Lung (x100). B. Liver (x100). C. Kidney (x100). D. Bone (x40). E. Cancer cells arrested in the pulmonary artery not by the size restriction but by adhesive interactions (x100). F. Proliferation of multicellular tumor emboli in the pulmonary artery, initial minimal penetration of cancer cells through the arteriolar walls (arrow), and invasion of the cancer cells to the lung parenchyma (x100). A, artery; Al, alveolus; CV, central vein; Gl, glomerulus; T, renal tubule; B, bone; BM, basement membrane.

Cluster Analysis of Gene-Expression Profiles of the 25 Metastatic Lesions
To identify genes that were specifically expressed in each of the four metastasized organs, we performed random permutation tests; this is an appropriate strategy for distinguishing two known subgroups. We used the following combinations: 10 lung metastases versus all 15 others; 5 liver metastases versus all 20 others; 5 kidney metastases versus all 20 others; and 5 bone metastases versus all 20 others. Table 2 lists 435 genes, the median ratios of which between the two groups were >2 with P values <0.05, among the 23,040 genes examined on the microarray. Hierarchical clustering of these 435 genes separated the four organ-specific groups of metastatic lesions very clearly (Fig. 2).

View larger version (78K): [in this window] [in a new window]   FIGURE 2. Cluster analysis of 25 metastatic lesions. Horizontal row, single gene; vertical column, metastatic lesion. Red indicates a high level of expression relative to the mean; blue indicates a low level of expression relative to the mean. Highly expressed genes in lung metastases (a), in kidney metastases (b), in bone metastases (c), and in liver metastases (d). The lists of the genes specifically expressed in each of the four metastasized organs (a–d) are shown in Table 2, a–d, respectively.

	Discussion

Top Notes Abstract Introduction Results Discussion Materials and Methods References

For the elucidation of the cross-talk between cancer cells and microenvironment in each organ and a comprehensive survey of the factors regulating organ-specific metastasis, we performed cDNA-microarray analyses of the metastatic foci of human SCLC (SBC-5) developed in four different murine organs (lung, liver, kidney, and bone) and compared gene-expression profiles among 25 of these lesions. The expression patterns fell into four categories, each of which reflected a specific organ. The 435 genes that distinguished these four groups were extracted by statistical analysis and classified into 12 categories on the basis of known biological functions (Table 2). Among them, genes belonging to the cell-cell signaling category included growth-factor receptors, cytokines, and chemokines. FGFR1 and FST were highly expressed in cells metastasized in bone. FGFR1 is a receptor for fibroblast growth factors (FGFs) and its downstream signals influence mitogenesis and differentiation. Because FGFs are expressed abundantly in bone tissue (16), the microenvironment of bone is likely to be suitable for survival and proliferation of cancer cells that express FGFR1. In SCLCs, metastatic cells in bone are predominantly osteolytic. FST, an activin antagonist that can inhibit bone formation (17), might promote the bone absorption caused by metastatic cells and contribute to the release of the growth factors such as FGFs that are stored in bone tissue. This bidirectional interaction between tumor cells and the bone microenvironment seems to be important for developing bone metastasis. PTHLH (alias PTHrP: parathyroid hormone related-peptide), a key mediator of osteolytic metastasis (16), was expressed by the tumor cells in all four metastatic sites we examined. Expression levels of PTHLH in bone metastases tended to be higher than in other affected organs, but the difference was not statistically significant (P = 0.057).

Chemokines, secreted peptides that control the homing of leukocytes, are considered to contribute to the directional migration of cancer cells that express chemokine receptors on their surfaces (1, 8). Three chemokine receptors, CCR4, CCR5, and CCR9, were expressed in all 25 metastatic lesions (data not shown), with no significant differences of expression levels. In the gene-expression database of 24 normal human adult tissues we reported recently, SCYA4 (CCL4), one of the ligands of CCR5, was expressed preferentially in lung, liver, lymph nodes, bone marrow, adipose tissue, and spleen (18). Because lung, liver, lymph nodes, and bone marrow are major targets for metastasis of SCLC, CCL4/CCR5 interaction may contribute to the organ-preferential metastasis of the SCLC cells.

Adhesion, detachment, and aggregation of tumor cells seem to play important roles in achieving metastasis. Although most circulating cancer cells are arrested in capillary beds because of size restrictions (3), we observed adherence to the walls of pre-capillary vessels that were much larger in diameter than the cancer cells (Fig. 1E). A number of molecules involved in cell-cell or cell-matrix adhesion, such as integrins and selectins, appear to mediate the adhesion of cancer cells to the vessel wall in specific organs (10). Consequently, the adhesive interaction between cancer cells and endothelium is likely to be associated with the organ selectivity of metastasis. Our data suggest that lectin, a family of ß-galactoside-binding proteins implicated in modulating cell-cell and cell-matrix interactions, may play an important role in organ preference because one member of this molecular family, LGALS1, is highly expressed in pulmonary metastases and another, LGALS9, in renal metastases. In addition, LGALS3 has shown an association with pulmonary metastasis of osteosarcoma (19), and its binding protein LGALS3BP, an indicator of the metastatic propensity of lung cancer (20), was also highly expressed in pulmonary metastases in our murine model.

A number of genes associated with the cytoskeleton or with cell motility were differentially expressed among the four organ groups. Especially in pulmonary metastatic foci, actin isoforms and related genes such as RHOC, ARPC4, PFN1, and PTK9L were expressed more strongly than in metastatic lesions of the other three organs. RHOC is a member of the Ras-related GTP-binding protein family and regulates reorganization of the actin cytoskeleton; its enhanced expression has been associated with pulmonary metastasis of melanoma cells (21). ARPC4 and PFN1 are implicated in directional movement of cells by promoting actin polymerization and controlling formation of filopodia and lamellipodia (22). On the other hand, PTK9L is associated with actin depolymerization. Therefore, up-regulation of these genes might reflect active cellular movement of cancer cells. Because cellular movement is essential for migration and invasion of cancer cells, genes involved in the cellular cytoskeleton and motility may well contribute to metastasis. In addition, a number of genes having various functions such as remodeling of the ECM, or participating in immune responses or signal transduction, were differentially expressed in each metastatic site.

The gene expression of cancer cells could be influenced by the microenvironment of each organ where they metastasized. Consequently, this list includes genes, the expression of which was altered by the cross-talk between cancer cells and host microecology in secondary site. In this model, it is difficult to distinguish initial difference and post-metastatic alteration of gene expression; however, many of the genes listed here had already been associated with cancer invasion and metastasis, several with respect to metastasis to specific organs. For example, ITBG4, SDC1, C3, MT2A, and CALM, which were predominantly expressed in pulmonary metastases in our murine model, have been associated with pulmonary metastasis of neoplasms originating outside the lung (10, 19, 21, 23, 24).

In vivo videomicroscopy studies have revealed that early phases of the metastatic process are completed quite efficiently through sequential steps, whereas growth phases of metastatic cells are very inefficient. Those observations suggest that regulators of tumor growth at secondary sites should be key targets for preventing metastasis (3, 25). To clarify the mechanism(s) operating later in the process of metastasis, we applied random permutation tests to compare lung-metastatic nodules classified according to the growth step from micrometastasis to macrometastasis (see "Materials and Methods").

The 105 genes that were differentially expressed between the two groups were classified according to their function. A number of genes involved in the cell motility, cell adhesion, and ECM remodeling were predominantly expressed in micrometastasis. For example, HSPB3, ACTB, ACTA2, TMSB10, MYH7, FLNA, and ARPC4, the expressions of which were elevated in micrometastasis, coordinately form lamellipodia and new adhesion sites at the leading edge of the invading cells, and move the cell forward by contraction of actomyosin-based cytoskeletal filaments (22). MMP1, which encodes a secreted enzyme that breaks down interstitial collagens (types I, II, and III), was also up-regulated in the smaller lesions. On the other hand, none of the genes belonging to the categories documented above were highly expressed in the larger lesions. Enhanced expression of these genes in the smaller lesions might reflect active cellular movement and invasion of cancer cells in micrometastasis. Because the differential expression of 105 genes between the two groups might reflect differences in the biological features of these tumors, further investigations of nearly half of the genes of unknown functions listed here should provide important insights into the progression from micrometastasis to macrometastasis.

In summary, we identified dozens of molecules that might be associated with organ-preferential metastasis or with tumor progression from micrometastasis to macrometastasis. Our results support the notion that metastasis is a complicated, multistep phenomenon and that each step requires several key molecules. Further analysis using clinical materials might help to clarify the mechanism of organ-specific metastasis and to further define the genes of importance. This should eventually lead to molecular target-based chemotherapy and prevention of metastasis.

	Materials and Methods

Top Notes Abstract Introduction Results Discussion Materials and Methods References

 
Cell Line
Human SCLC cell line SBC-5 was kindly provided by Dr. K. Hiraki (Okayama University, Okayama, Japan). The SBC-5 cells were maintained in Eagle's MEM supplemented with 10% fetal bovine serum (Life Technologies, Inc., Grand Island, NY), gentamycin (Schering-Plough, Osaka, Japan), and 4 mM HEPES.

Reagent
Anti-mouse interleukin 2 receptor ß-chain monoclonal antibody, TM-ß1 (IgG2b), was supplied by Drs. M. Miyasaka and T. Tanaka (Osaka University, Osaka, Japan) (26). None of this material contained endotoxins, as judged by the Limulus amoebocyte assay (Seikagaku Kogyo, Tokyo, Japan; minimum detection level 0.1 ng/ml).

Animals
Male SEB-17/Icr-scid mice, 6–8 weeks old, were obtained from Charles River Laboratories (Yokohama, Japan) and maintained under specific pathogen-free conditions throughout the experiment. Experiments were performed following the ethical guidelines of our university.

Experimental Metastasis of SBC-5 in Mice Lacking NK Cells
To facilitate the metastasis of human SBC-5, NK cells were depleted in SCID mice by i.p. injection of TM-ß1Ab (1 mg/1 ml in PBS/mouse) 2 days before inoculation of tumor cells (12). The tumor cells were first harvested and washed with Ca²⁺- and Mg²⁺-free PBS; cell viability was determined by the trypan blue exclusion test, and only cell suspensions showing >90% viability were used. We injected 0.3 ml of tumor-cell suspension (1–5 x 10⁶ cells) into the lateral tail vein of non-anesthetized mice. The mice were sacrificed 35 days after inoculation, and four organs (lung, liver, kidney, and bone tissues) containing macroscopic lesions were excised, embedded in TissueTek OCT medium (Sakura, Tokyo, Japan), and snap frozen at -80°C.

Laser-Capture Microdissection
We prepared 8-µm-thick frozen sections, which were fixed in 70% ethanol for 30 s, stained with H&E, and dehydrated first with 99.5% ethanol for 5 min and then with xylene for 1 min. The stained tissues were observed microscopically; 25 metastatic lesions (10 lung, 5 liver, 5 kidney, and 5 bone tumors) were selected for laser-capture microdissection with a PixCell II LCM system, according to the manufacturer's protocols (Arcturus Engineering, Mountain View, CA).

RNA Extraction and T7-Based RNA Amplification
Total RNA was extracted from each captured cancer tissue using the RNeasy mini kit (Qiagen, Valencia, CA) and RNase-free DNase according to the manufacturer's protocols. Total RNAs extracted from each of the 25 metastatic lesions were subjected to T7-based RNA amplification, as described previously (27). Two rounds of amplification yielded 40–200 µg of aRNA (over 100,000-fold) from each sample. Aliquots (2.5 µg) of a RNA from individual lesions (test probes) and from mixture of aRNAs from all 25 lesions (a control probe) were labeled respectively with Cy5-dCTP or Cy3-dCTP.

cDNA Microarrays
Our "genome-wide" cDNA microarray system contains 23,040 cDNAs selected from the UniGene database of the National Center for Biotechnology Information (28). Fabrication of the microarray, hybridization, washing, and detection of signal intensities were described previously (27). To normalize the amount of mRNA between tumors and controls, the Cy5/Cy3 ratio for each gene's expression was adjusted so that the averaged Cy5/Cy3 ratio of 52 housekeeping genes was equal to 1. We assigned a cut-off value to each microarray slide, using a variance analysis. Genes, the Cy3 or Cy5 signal intensities of which were lower than the cut-off values, were excluded from further investigation. We also excluded data from genes where the signal/noise ratio was <3.

Cross-Hybridization of Mouse Messenger RNA
To assess the influence of contamination of normal mouse mRNA, we microdissected normal mouse cells in individual organs and hybridized on the human cDNA microarrays by the same method as described above.

Cluster Analysis of Gene-Expression Profiles
To identify genes that were expressed differently among the four types of metastatic tissue, we applied random-permutation tests to estimate the ability of each gene to distinguish between two groups (each organ-specific metastasis versus the mixture of metastases in the other three organs). The comparative combinations were as follows: (a) 10 lung metastases versus 15 metastases in three other organs; (b) 5 liver metastases versus 20 others; (c) 5 kidney metastases versus 20 others; and (d) 5 bone metastases versus 20 others. Mean (µ) and standard () deviations were calculated from the log-transformed relative expression ratios of each gene in both groups. A discrimination score (DS) for each gene was defined as follows:

The samples were randomly permutated 10,000 times for each pair of groups. Because the DS data set of each gene showed a normal distribution, we calculated a P value for the user-defined grouping (29).

A hierarchical clustering analysis was applied to the 25 metastatic loci and the 435 genes extracted by the random permutation tests, using Web-available software ("Cluster" and "TreeView") written by M. Eisen. (http://genome-www5.stanford.edu/MicroArray/SMD/restech.html).

Identification of Genes Differentially Expressed Between Micrometastasis and Macrometastasis
To compare gene-expression profiles between small and large metastatic foci, we also applied a random permutation test to 9 of the 10 lesions in lung: 5 that were <1 mm (average size: 0.60 mm, SD: 0.22); and 4 that were >2 mm (average: 2.40 mm, SD: 0.32) (29). To determine the size of the tumors, we first sliced each lesion from the top to the bottom (8 µm thick) and measured the maximum axis of the largest tumor section. The Union Internationale Centre le Cancer advocates the use of the term micrometastasis to denote in humans a metastatic lesion smaller than or equal to 2 mm in diameter (30, 31). As there is no definition of this term for the mouse, we more strictly defined micrometastasis as a lesion smaller than 1 mm in diameter.

	Notes

Top Notes Abstract Introduction Results Discussion Materials and Methods References

 
¹ "Research for the Future" Program Grant of The Japan Society for the Promotion of Science (no. 00L01402) to Y.N.

Received November 12, 2002; revised March 17, 2003; accepted April 4, 2003.

	References

Top Notes Abstract Introduction Results Discussion Materials and Methods References

 

1. Chambers, A. F., Groom, A. C., and MacDonald, I. C. Dissemination and growth of cancer cells in metastatic sites. Nat. Rev. Cancer, 2: 563–572, 2002.[Medline]
2. Cameron, M. D., Schmidt, E. E., Kerkvliet, N., Nadkarni, K. V., Morris, V. L., Groom, A. C., Chambers, A. F., and MacDonald, I. C. Temporal progression of metastasis in lung: cell survival, dormancy, and location dependence of metastatic inefficiency. Cancer Res., 60: 2541–2546, 2000.[Abstract/Free Full Text]
3. Al-Mehdi, A. B., Tozawa, K., Fisher, A. B., Shientag, L., Lee, A., and Muschel, R. J. Intravascular origin of metastasis from the proliferation of endothelium-attached tumor cells: a new model for metastasis. Nat. Med., 6: 100–102, 2000.[Medline]
4. Fidler, I. J., Yano, S., Zhang, R. D., Fujimaki, T., and Bucana, C. D. The seed and soil hypothesis: vascularisation and brain metastases. Lancet Oncol., 3: 53–57, 2002.[Medline]
5. Liotta, L. A. and Kohn, E. C. The microenvironment of the tumour-host interface. Nature, 411: 375–379, 2001.[Medline]
6. Weiss, L. Comments on hematogenous metastatic patterns in humans as revealed by autopsy. Clin. & Exp. Metastasis, 10: 191–199, 1992.[Medline]
7. Paget, S. The distribution of secondary growths in cancer of the breast. 1889. Cancer Metastasis Rev., 8: 98–101, 1989.[Medline]
8. Muller, A., Homey, B., Soto, H., Ge, N., Catron, D., Buchanan, M. E., McClanahan, T., Murphy, E., Yuan, W., Wagner, S. N., Barrera, J. L., Mohar, A., Verastegui, E., and Zlotnik, A. Involvement of chemokine receptors in breast cancer metastasis. Nature, 410: 50–56, 2001.[Medline]
9. Yano, S., Nishioka, Y., Nokihara, H., and Sone, S. Macrophage colony-stimulating factor gene transduction into human lung cancer cells differentially regulates metastasis formations in various organ microenvironments of natural killer cell-depleted SCID mice. Cancer Res., 57: 784–790, 1997.[Abstract/Free Full Text]
10. Abdel-Ghany, M., Cheng, H. C., Elble, R. C., and Pauli, B. U. The breast cancer ß 4 integrin and endothelial human CLCA2 mediate lung metastasis. J. Biol. Chem., 276: 25438–25446, 2001.[Abstract/Free Full Text]
11. Miki, T., Yano, S., Hanibuchi, M., and Sone, S. Bone metastasis model with multiorgan dissemination of human small-cell lung cancer (SBC-5) cells in natural killer cell-depleted SCID mice. Oncol. Res., 12: 209–217, 2000.[Medline]
12. Yano, S., Nishioka, Y., Izumi, K., Tsuruo, T., Tanaka, T., Miyasaka, M., and Sone, S. Novel metastasis model of human lung cancer in SCID mice depleted of NK cells. Int. J. Cancer, 67: 211–217, 1996.[Medline]
13. Sone, S., Inamura, N., Nii, A., and Ogura, T. Heterogeneity of human lymphokine (IL-2)-activated killer (LAK) precursors and regulation of their LAK induction by blood monocytes. Int. J. Cancer, 42: 428–434, 1988.[Medline]
14. Nicolson, G. L. Paracrine and autocrine growth mechanisms in tumor metastasis to specific sites with particular emphasis on brain and lung metastasis. Cancer Metastasis Rev., 12: 325–343, 1993.[Medline]
15. Radinsky, R. Modulation of tumor cell gene expression and phenotype by the organ-specific metastatic environment. Cancer Metastasis Rev., 14: 323–338, 1995.[Medline]
16. Mundy, G. R. Metastasis to bone: causes, consequences and therapeutic opportunities. Nat. Rev. Cancer, 2: 584–593, 2002.[Medline]
17. Ebara, S. and Nakayama, K. Mechanism for the action of bone morphogenetic proteins and regulation of their activity. Spine, 27: S10–S15, 2002.[Medline]
18. Saito-Hisaminato, A., Katagiri, T., Kakiuchi, S., Nakamura, T., Tsunoda, T., and Nakamura, Y. Genome-wide profiling of gene expression in 29 normal human tissues with a cDNA microarray. DNA Res., 9: 35–45, 2002.[Abstract]
19. Khanna, C., Khan, J., Nguyen, P., Prehn, J., Caylor, J., Yeung, C., Trepel, J., Meltzer, P., and Helman, L. Metastasis-associated differences in gene expression in a murine model of osteosarcoma. Cancer Res., 61: 3750–3759, 2001.[Abstract/Free Full Text]
20. Marchetti, A., Tinari, N., Buttitta, F., Chella, A., Angeletti, C. A., Sacco, R., Mucilli, F., Ullrich, A., and Iacobelli, S. Expression of 90K (Mac-2 BP) correlates with distant metastasis and predicts survival in stage I non-small cell lung cancer patients. Cancer Res., 62: 2535–2539, 2002.[Abstract/Free Full Text]
21. Clark, E. A., Golub, T. R., Lander, E. S., and Hynes, R. O. Genomic analysis of metastasis reveals an essential role for RhoC. Nature, 406: 532–535, 2000.[Medline]
22. Lauffenburger, D. A. and Horwitz, A. F. Cell migration: a physically integrated molecular process. Cell, 84: 359–369, 1996.[Medline]
23. Dong, G., Loukinova, E., Chen, Z., Gangi, L., Chanturita, T. I., Liu, E. T., and Van Waes, C. Molecular profiling of transformed and metastatic murine squamous carcinoma cells by differential display and cDNA microarray reveals altered expression of multiple genes related to growth, apoptosis, angiogenesis, and the NF-B signal pathway. Cancer Res., 61: 4797–4808, 2001.[Abstract/Free Full Text]
24. Hirabayashi, K., Numa, F., Suminami, Y., Murakami, A., Murakami, T., and Kato, H. Altered proliferative and metastatic potential associated with increased expression of syndecan-1. Tumour Biol., 19: 454–463, 1998.[Medline]
25. Pantel, K., Cote, R. J., and Fodstad, O. Detection and clinical importance of micrometastatic disease. J. Natl. Cancer Inst., 91: 1113–1124, 1999.[Abstract/Free Full Text]
26. Tanaka, T., Kitamura, F., Nagasaka, Y., Kuida, K., Suwa, H., and Miyasaka, M. Selective long-term elimination of natural killer cells in vivo by an anti-interleukin 2 receptor ß chain monoclonal antibody in mice. J. Exp. Med., 178: 1103–1107, 1993.[Abstract/Free Full Text]
27. Okabe, H., Satoh, S., Kato, T., Kitahara, O., Yanagawa, R., Yamaoka, Y., Tsunoda, T., Furukawa, Y., and Nakamura, Y. Genome-wide analysis of gene expression in human hepatocellular carcinomas using cDNA microarray: identification of genes involved in viral carcinogenesis and tumor progression. Cancer Res., 61: 2129–2137, 2001.[Abstract/Free Full Text]
28. Kitahara, O., Furukawa, Y., Tanaka, T., Kihara, C., Ono, K., Yanagawa, R., Nita, M. E., Takagi, T., Nakamura, Y., and Tsunoda, T. Alterations of gene expression during colorectal carcinogenesis revealed by cDNA microarrays after laser-capture microdissection of tumor tissues and normal epithelia. Cancer Res., 61: 3544–3549, 2001.[Abstract/Free Full Text]
29. Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., Bloomfield, C. D., and Lander, E. S. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science, 286: 531–537, 1999.[Abstract/Free Full Text]
30. Hermanek, P., Hutter, R. V., Sobin, L. H., and Wittekind, C. International Union Against Cancer. Classification of isolated tumor cells and micrometastasis. Cancer, 86: 2668–2673, 1999.[Medline]
31. Guinebretiere, J. M. and Contesso, G. "Micrometastases": the pathologist's point of view. Bull. Cancer, 88: 549–550, 555–560, 2001.[Medline]

This article has been cited by other articles:

				T. Kato, N. Sato, A. Takano, M. Miyamoto, H. Nishimura, E. Tsuchiya, S. Kondo, Y. Nakamura, and Y. Daigo Activation of Placenta-Specific Transcription Factor Distal-less Homeobox 5 Predicts Clinical Outcome in Primary Lung Cancer Patients Clin. Cancer Res., April 15, 2008; 14(8): 2363 - 2370. [Abstract] [Full Text] [PDF]

				H. Ogino, S. Yano, S. Kakiuchi, H. Muguruma, K. Ikuta, M. Hanibuchi, H. Uehara, K. Tsuchida, H. Sugino, and S. Sone Follistatin Suppresses the Production of Experimental Multiple-Organ Metastasis by Small Cell Lung Cancer Cells in Natural Killer Cell-Depleted SCID Mice Clin. Cancer Res., February 1, 2008; 14(3): 660 - 667. [Abstract] [Full Text] [PDF]

				N. Ishikawa, A. Takano, W. Yasui, K. Inai, H. Nishimura, H. Ito, Y. Miyagi, H. Nakayama, M. Fujita, M. Hosokawa, et al. Cancer-Testis Antigen Lymphocyte Antigen 6 Complex Locus K Is a Serologic Biomarker and a Therapeutic Target for Lung and Esophageal Carcinomas Cancer Res., December 15, 2007; 67(24): 11601 - 11611. [Abstract] [Full Text] [PDF]

				M. Taniwaki, A. Takano, N. Ishikawa, W. Yasui, K. Inai, H. Nishimura, E. Tsuchiya, N. Kohno, Y. Nakamura, and Y. Daigo Activation of KIF4A as a Prognostic Biomarker and Therapeutic Target for Lung Cancer Clin. Cancer Res., November 15, 2007; 13(22): 6624 - 6631. [Abstract] [Full Text] [PDF]

				C. Wang, R. Navab, V. Iakovlev, Y. Leng, J. Zhang, M.-S. Tsao, K. Siminovitch, D. R. McCready, and S. J. Done Abelson Interactor Protein-1 Positively Regulates Breast Cancer Cell Proliferation, Migration, and Invasion Mol. Cancer Res., October 1, 2007; 5(10): 1031 - 1039. [Abstract] [Full Text] [PDF]

				S. Hayama, Y. Daigo, T. Yamabuki, D. Hirata, T. Kato, M. Miyamoto, T. Ito, E. Tsuchiya, S. Kondo, and Y. Nakamura Phosphorylation and Activation of Cell Division Cycle Associated 8 by Aurora Kinase B Plays a Significant Role in Human Lung Carcinogenesis Cancer Res., May 1, 2007; 67(9): 4113 - 4122. [Abstract] [Full Text] [PDF]

				T. Yamabuki, A. Takano, S. Hayama, N. Ishikawa, T. Kato, M. Miyamoto, T. Ito, H. Ito, Y. Miyagi, H. Nakayama, et al. Dikkopf-1 as a Novel Serologic and Prognostic Biomarker for Lung and Esophageal Carcinomas Cancer Res., March 15, 2007; 67(6): 2517 - 2525. [Abstract] [Full Text] [PDF]

				C. Suzuki, K. Takahashi, S. Hayama, N. Ishikawa, T. Kato, T. Ito, E. Tsuchiya, Y. Nakamura, and Y. Daigo Identification of Myc-associated protein with JmjC domain as a novel therapeutic target oncogene for lung cancer Mol. Cancer Ther., February 1, 2007; 6(2): 542 - 551. [Abstract] [Full Text] [PDF]

				S. Hayama, Y. Daigo, T. Kato, N. Ishikawa, T. Yamabuki, M. Miyamoto, T. Ito, E. Tsuchiya, S. Kondo, and Y. Nakamura Activation of CDCA1-KNTC2, Members of Centromere Protein Complex, Involved in Pulmonary Carcinogenesis Cancer Res., November 1, 2006; 66(21): 10339 - 10348. [Abstract] [Full Text] [PDF]

				C. Suzuki, Y. Daigo, N. Ishikawa, T. Kato, S. Hayama, T. Ito, E. Tsuchiya, and Y. Nakamura ANLN Plays a Critical Role in Human Lung Carcinogenesis through the Activation of RHOA and by Involvement in the Phosphoinositide 3-Kinase/AKT Pathway Cancer Res., December 15, 2005; 65(24): 11314 - 11325. [Abstract] [Full Text] [PDF]

				C. Furukawa, Y. Daigo, N. Ishikawa, T. Kato, T. Ito, E. Tsuchiya, S. Sone, and Y. Nakamura Plakophilin 3 Oncogene as Prognostic Marker and Therapeutic Target for Lung Cancer Cancer Res., August 15, 2005; 65(16): 7102 - 7110. [Abstract] [Full Text] [PDF]

				T. Kato, Y. Daigo, S. Hayama, N. Ishikawa, T. Yamabuki, T. Ito, M. Miyamoto, S. Kondo, and Y. Nakamura A Novel Human tRNA-Dihydrouridine Synthase Involved in Pulmonary Carcinogenesis Cancer Res., July 1, 2005; 65(13): 5638 - 5646. [Abstract] [Full Text] [PDF]

				B. L. Eckhardt, B. S. Parker, R. K. van Laar, C. M. Restall, A. L. Natoli, M. D. Tavaria, K. L. Stanley, E. K. Sloan, J. M. Moseley, and R. L. Anderson Genomic Analysis of a Spontaneous Model of Breast Cancer Metastasis to Bone Reveals a Role for the Extracellular Matrix Mol. Cancer Res., January 1, 2005; 3(1): 1 - 13. [Abstract] [Full Text] [PDF]

				S. Kakiuchi, Y. Daigo, N. Ishikawa, C. Furukawa, T. Tsunoda, S. Yano, K. Nakagawa, T. Tsuruo, N. Kohno, M. Fukuoka, et al. Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839) Hum. Mol. Genet., December 15, 2004; 13(24): 3029 - 3043. [Abstract] [Full Text] [PDF]

				C. Suzuki, Y. Daigo, T. Kikuchi, T. Katagiri, and Y. Nakamura Identification of COX17 as a Therapeutic Target for Non-Small Cell Lung Cancer Cancer Res., November 1, 2003; 63(21): 7038 - 7041. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Kakiuchi, S. Articles by Nakamura, Y. Search for Related Content PubMed PubMed Citation Articles by Kakiuchi, S. Articles by Nakamura, Y.