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. Author manuscript; available in PMC: 2012 Mar 20.
Published in final edited form as: Int J Cancer. 2011 Jan 6;129(5):1075–1086. doi: 10.1002/ijc.25763

Figure 6.

Figure 6

ERK2 inhibition significantly attenuates human epithelioid MM (HMESO) growth in SCID mice. (A) In the first experiment, shERK1, shERK2 and shControl stable MM lines were injected subcutaneously at 4 sites per mouse (N=4 mice or 16 tumors per group), and tumor growth was measured over 28 days. shERK1 significantly (p≤0.05) different from shCon at 19, 21, and 23, days; shERK2 significantly (p<0.05) different from shCon at all time points except 14 and 28 days. Rate of tumor growth for shERK2 group differed significantly from shCon group, whereas rate of tumor growth for shERK1 group did not differ significantly from shCon group (B) In the second experiment, shERK2 and shCon MM lines were injected subcutaneously as described above (N=5 mice or 20 tumors per group), and tumor growth was evaluated over 54 days (p≤0.05 at all time points). (C) Tumor sections were stained using an antibody to Ki-67, a marker of G1–G2 phase entry 22 and TUNEL staining for necrosis/apoptosis 22. Upper row shows dissecting microscope pictures and lower row shows higher magnification (40X) pictures of the same tumor by light microscopy. Hematoxylin and eosin (H&E) staining shows the characteristic biphasic and epithelioid patterns of human MMs. Black bar = 1 mm (upper row); Black bar = 50 μm (lower row). (D) ERK1 or ERK2 inhibition attenuates human fibrosarcomatoid MM (PPMMill) growth in SCID mice as compared to shCon. Data for two separate graphs shown in (D) were generated in a single experiment, to avoid overlap between shERK1 and shERK2 two separate graphs are provided. The difference in tumor growth rates between different groups in in vivo experiments (A, B, D) was assessed using a hierarchical regression model to take into account the correlation between repeated measurements on the same tumor and multiple tumors in the same animal. In this analysis, the regression coefficient describing tumor growth is modeled as a function of treatment group as well as random variation due to differences between animals and tumors on the same animal.