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Figure 2. Optimization of protein extraction from RLT Plus samples. Due to the various additives in the sample buffer there is marked incompatibility with most of the normally used protein quantification methods. The Total Protein assay was therefore used, as it is insensitive to high SDS concentrations. The standard curve was generated using JJN3 cell line extracts at 0.25 mg/mL concentration, and serial dilutions thereof. Each capillary contained one sample of a known concentration. Results were visualized as virtual gels (A) and the numbers correspond to the areas under the curves of the peaks (B). A standard curve was generated, plotting the result for each capillary quantification (C). Amount of protein obtained from each sample (D). Comparison of results from Calnexin, Cyclin D2, GAPDH and Ikaros quan- tification in the U266 cell line, from which protein extracts were obtained by RLT Plus and RIPA extraction, and visualized as virtual blots or two distinct dilutions of the sample (E), and one dilution extracted with both protocols visualized as peaks (F).
Nano-scale protein quantification in multiple myeloma
many solid and hematologic malignancies, including MM;14 Calnexin, which forms endoplasmic reticulum and is upregulated in MM relative to normal plasma cells in genetically identical twin samples;15 and DDX21 or RIPK1, with known involvement in several tumors.16–18 In addi- tion, proteins involved in the mechanism of action of antimyeloma drugs were included: Cereblon, Ikaros, Aiolos for immunomodulatory drugs; XAF1 for melpha- lan; and PSME1 for bortezomib.19–22
At the protein level, PSME1 and Calnexin showed the highest median level of expression, while HSP90 was the most strongly expressed mRNA (Figure 4A,B). Conversely, proteins Cyclin D1, Cyclin D2 and c-myc had the lowest
AB
C
median level of expression, and CRBN, RIPK1 and XAF1 were the least expressed mRNA.
In general, the expression of mRNA was more homoge- nous than that of proteins, as indicated by the higher coef- ficients of variation for the latter (Figure 4C). In fact, the coefficients of variation were significantly lower than those for c-myc, DDX21, HSP90, IKZF1 and PSME1 mRNA than for their respective encoded proteins. The highest variability in expression, both at the mRNA and protein levels, was observed for CCND2/Cyclin D2 and CCND1/Cyclin D1, as well as for c-myc protein.
Next, we analyzed the correlation between the two lev- els of gene expression, mRNA and protein. Interestingly,
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