As a positive control, we included an antibody against MDR1/pgp


As a positive control, we included an antibody against MDR1/pgp. generate large-scale antibody libraries by phage display and identification of antigens by IP/MS. We first tested the ability of SPS to detect changes in surface expression of a single specific protein. The expression of the poliovirus receptor CD155, the antigen for scFv 5d11, was knocked down in HT1080 cells and confirmed via western blot and immunofluorescent microscopy (Figure 1A & B). We compared the relative binding for a 10-scFv SPS, including 5d11, for both anti-PVR siRNA-treated HT1080 cells and HT1080 cells treated with a scrambled control (Figure 1C). SPS profiling revealed a marked difference (t-test, p=0.00008) of 5d11 fluorescence in anti-PVR siRNA treated HT1080 cells when compared to scramble siRNA control. In contrast, there was no significant difference observed in binding for the other surface antigens in the subset of scFvs employed. These findings indicated that SPS could detect specific differences in surface expression of HT1080 cells and served as a proof of principle for use of this technology. Open in a separate window Fig. 1 SPS can detect altered expression of controlled knockdown for PVRMCF7 replicate comparison of (70 scFv SPS profile). Dashed line indicates 2-fold difference in binding threshold. Three scFvs that met criteria in the original SPS screen did MTC1 not repeat in a confirmatory screen. MCF7 vs. HT1080 SPS comparison shows numerous differences in scFv antigen binding. (circle)scFv change in binding during initial experiment, (triangle)= indicate scFvs demonstrating significant difference in antigen binding repeating in secondary screen and are designated as potential biomarkers. Immunocytochemistry for scFv 2a8 and 2f8 signals for 30 individual samples performed in triplicate of HT-1080 and MCF7 cells from three separate experiments. We next applied our 70 scFv SPS panel to two unrelated cell lines, expecting a large amount of variation in their surface proteomes, to determine if SPS could distinguish between the two. SPS comparison of HT1080 fibrosarcoma and MCF7 breast adenocarcinoma cells yielded 7 reproducible hits NPI64 (indicated by triangle, Figure 2B). We expected that SPS comparing cells of distinct lineage would be markedly different in their surface proteome and about 10% of the scFvs applied showed reproducible and significant differences. While there are numerous similarities in SPS between these two cell lines, we focused primarily on differences in surface binding as these represent candidates for potentially distinguishing biomarkers. We tested the ability of scFvs identified by SPS to distinguish between HT1080 and MCF7 cell lines. We selected 2a8 and 2f8 (two scFvs that showed the largest difference in SPS) for use in fluorescent immunocytochemistry of samples of MCF7 and HT1080 cells and provided the resulting fluorescence signals to an observer blinded to the identity of the cell samples. 10 samples per cell line were assayed on three separate days to determine if day-to-day NPI64 experimental variation affects scFv binding levels. Each individual sample consists of three wells containing 20,000 cells per well for a total of 30 samples. The average of these samples was used by the scorer to correctly identify 100% of the 60 total samples as being of either MCF7 or NPI64 HT1080 based on the relative binding of 2a8 and 2f8. Figure 2C shows the average binding of single chain markers (sem) for this experiment and clearly shows the difference in fluorescence signal for these scFvs between HT1080 and MCF7 cell samples. These findings indicate that scFvs identified by SPS can distinguish between these cell lines. SPS identifies CD44 as a biomarker that distinguishes MCF7 from NCI/ADR-RES cells We next applied SPS to two cell lines of differing drug resistance: MCF7 vs. NCI/ADR-RES, previously shown to have.