Comparative Time-Dependent Analysis of Potential Inflammation Biomarkers in Lymphoma-Bearing SJL Mice

SJL mice colonized with RcsX lymphoma cells undergo a rapid inflammatory response associated with
biological and physiological effects including increased nitric oxide production and mutations in spleen
DNA. By 2 weeks postcolonization, these changes were accompanied by both up- and down-regulation
of a number of plasma proteins. In the experiments reported here, plasma from individual SJL mice
was analyzed at several time-points over the 2-week period to determine if there were sets of proteins
whose expression varied in concert and thus might serve as early biomarkers for inflammation-related
disorders. Samples were collected just prior to injection of the RcsX cells and then after 4, 8, and 12
days. Albumin and immunoglobulins were depleted, and the samples were resolved by 1D gel
electrophoresis. The gels were cut into 20 slices, and the proteins were digested in-gel with trypsin.
The digests were treated with iTRAQ reagents and then analyzed using LC/MS/MS. The resulting data
were processed with two software packages, that is, ProQuant and Spectrum Mill, and then subjected
to K-means cluster analysis (K = 4). The four clusters revealed a set of highly up-regulated proteins, a
set of progressively up-regulated proteins, a set with no major changes, and a set that declined. The
first cluster included haptoglobin and serum amyloid A; the second included groups with several
functions including protease inhibition, cell motility, and transport. The iTRAQ results for a selection
of the up-regulated proteins, including haptoglobin, hemopexin, serum amyloid P component, and
ceruloplasmin, were confirmed with Western blots. Prominent down-regulated proteins included
esterase-1, paraoxonase, and α-2-macroglobulin. Approximately 50% of the up-regulated proteins are
canonical acute phase proteins, while the remainder are regulated by the Nrf2 transcription factor.
Keywords: inflammation • SJL mouse • lymphoma • iTRAQ • tumor progression • biomarker • cluster analysis •
acute phase proteins