**Author details**

Ryoiti Kiyama1\*, Yun Zhu1 and Tei-ichiro Aoyagi2

\*Address all correspondence to: kiyama.r@aist.go.jp

1 Biomedical Research Institute, National Institute of Advanced Industrial Science and Tech‐ nology, Ibaraki, Japan

2 Ibaraki Medical Center, Tokyo Medical University, Ibaraki, Japan

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**Figure 6.** Stability of fluorescently labeled IgG. (A) Photostability of Fluolid-Orange- or Cy3-labeled IgG under irradia‐ tion for up to 150 sec with a laser beam at 488 nm. (B) Heat stability. Fluolid-Orange- or Cy3-labeled IgG was left in an

As discussed in Section 4.1, future diagnosis will be based on sufficient numbers of protein markers possibly obtained from signal transduction pathways, which will give a statistically significant decision even for cases where no decisive markers, such as disease-causing mutations or constitutive active proteins, are available. In the case of future therapeutics, multiple targets will also be considered to be an effective strategy. Signal transduction-based targeted therapeutics have already been developed for some diseases and drugs such as imatinib or Gleevec/Glivec, a small molecule inhibitor against activated tyrosine kinase activity by the Bcr-Abl fusion gene used for the treatment of chronic myelogenous leukemia, are available (Radford, 2002). Other monoclonal antibody-based drugs such as trastuzumab or Herceptin, which blocks a growth factor receptor HER2/neu (c-erbB-2) to treat breast cancer, and panitumumab or Vectibix, which blocks HER1 to treat colorectal cancer, have been developed based on signal-transduction. Although these drugs are effective, continuous use will sometimes generate drug-resistant cancer (Schenone et al., 2011). So, treatment with multiple targeting drugs will be important in future therapeutics and the same is true for the

environment of 100ºC and fluorescence was measured every 30 min. For details, see Zhu et al. (2011).

**4.3. Future therapeutics**

22 Renal Tumor

matched diagnostics about multiple targets.


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**Chapter 2**

**Signaling Pathways and Biomarkers in Renal Tumors**

Sunitinib malate (Sutent, Pfizer inc., New York, NY) is an orally administered, multitargeted inhibitor of tyrosine kinases, including vascular endothelial growth factor (VEGF) receptor, platelet-derived growth factor (PDGF) receptor, stem cell factor receptor (KIT), fms-like ty‐ rosine kinase (FLT) -3, CSF-1R, and RET. Since the introduction of sunitinib for patients with advanced renal tumor [1], significant objective responses of sunitnib have been revealed [2-6]. In a randomized, multicenter, phase III trial enrolled 750 patients with previously-un‐ treated metastatic renal tumor to receive either sunitinib or interferon (IFN) -α, sunitinib was superior to IFN-α in the objective response rate (47% *vs* 12%), progression-free survival time (11.0 *vs* 5.0 months), and overall survival time (26.4 *vs* 21.8 months) [3, 4]. Also in a Jap‐ anese, multicenter, phase II trial enrolled 51 patients with first-line and pretreated metastatic clear-cell renal tumor to recieve sinitinib, significant responses of sunitinib have been report‐ ed that objective response rate was 52.9%, the median progression-free survival time was 12.2 and 10.6 months, and the median overall survival time was 33.1 and 32.5 months in first-line and pretreated patients, respectively [5, 6]. Sunitinib is approved worldwide for first-line treatment of advanced clear-cell renal tumor. However, approximately half of pa‐ tients with advanced renal tumor do not see clinical benefits from sunitinib treatment. A prognostic marker is needed for selecting patients who will benefit most from sunitinib.

It has been advocated that the necessity of determining molecular and clinical biomarkers that may predict efficacy of sunitinib. The identification of biomarkers to predict response is urgently needed. This chapter provides a brief overview of the signaling pathways of renal tumors and introduces biomarkers to predict response to sunitinib of clinical variables.

> © 2013 Fujita et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 Fujita et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

Tetsuo Fujita, Masatsugu Iwamura,

http://dx.doi.org/10.5772/53787

**1. Introduction**

Kazumasa Matsumoto and Kazunari Yoshida

Additional information is available at the end of the chapter

