Anti-C1QC monoclonal antibody, clone 3R9/2

Early detection is the key to improve the prognosis of kidney cancer. This study profiled and identified differentially expressed serum proteins in stage T1a renal cell carcinoma (RCC) using isobaric tags for relative and absolute quantification (iTRAQ)-based mass spectrometry. A total amount of 99 serum samples including 29 patients with ccRCC, 24 patients with a benign kidney mass, 28 patients with another type of urological tumor (20 cases of transitional cell carcinoma and 8 cases of prostate cancer or a male genital tumor), and 18 healthy controls were subjected to iTRAQ-based mass spectrometry. ProteinPilot software was used to identify the differentially expressed serum proteins in RCC compared to the other three populations. Hierarchical clustering analysis according to The Cancer Genome Atlas (TCGA) RCC database was then performed as the cross-platform validation. Immunohistochemistry was performed to verify the expression of selected proteins in tissue samples from these subjects. iTRAQ identified 27 differentially expressed serum proteins in the RCC patients, and 11 of these proteins were cross validated in RCC tissues from the TCGA database. The expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican was verified and associated with the tumor stage and/or grade. There were 27 differentially expressed proteins in early-stage RCC identified by iTRAQ; among them, the expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican were associated with the tumor stage and/or grade. Further studies are needed to confirm these data for their use as biomarkers for the early detection of RCC.

Rodent models for arthritis implicate a role for complement in disease development and progression. In humans, complement deposition has been observed in inflamed synovia of rheumatoid arthritis (RA) patients. In this study we analysed whether genetic variants of complement component C1q predispose to RA. We genotyped single nucleotide polymorphisms (SNPs) in and around the C1q genes, C1qA, C1qB and C1qC, in a Dutch set of 845 RA cases and 1046 controls. Replication was sought in a sample set from North America (868 cases/1193 controls), and a meta-analysis was performed in a combined samples set of 8000 cases and 23262 controls of European descent. We determined C1q serum levels in relation to C1q genotypes. In the discovery phase, five of the 13 SNPs tested in the C1q genes showed a significant association with RA. Additional analysis of the genomic area around the C1q genes revealed that the strongest associating SNPs were confined to the C1q locus. Within the C1q locus we observed no additional signal independent of the strongest associating SNP, rs292001 [odds ratio (OR)=0 center dot 72 (0 center dot 58-0 center dot 88), P=0 center dot 0006]. The variants of this SNP were associated with different C1q serum levels in healthy controls (P=0 center dot 006). Interestingly, this SNP was also associated significantly in genome-wide association studies (GWAS) from the North American Rheumatoid Arthritis Consortium study, confirming the association with RA [OR=0 center dot 83 (0 center dot 69-1 center dot 00), P=0 center dot 043]. Combined analysis, including integrated data from six GWAS studies, provides support for the genetic association. Genetic variants in C1q are correlated with C1q levels and may be a risk for the development of RA.