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Antibody validation
Jennifer Bordeaux, Allison W. Welsh, Seema Agarwal, Elizabeth Killiam, Maria T. Baquero, Jason A. Hanna, Valsamo K. Anagnostou, and David L. Rimm
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A moderate level of validation was observed for Companies 2–5. These companies also did not provide any in-depth descriptions of antibody validation procedures. Datasheets all included background on the target, as well as information on the immunogen. Three out of four companies included the complete sequence used and the fourth identified the region surrounding the phosphorylation site as the sequence used. These companies also provided recommended applications with starting dilutions, and all provided at least one example of the antibody successfully identifying its target in one of the recommended applications. WBs—either with transfected cells expressing the target or pre-incubation of the antibody with blocking peptide—were the most commonly shown antibody validation examples.

The highest levels of validation were seen for Companies 6 and 7. Company 6 describes its validation procedures for phospho-specific antibodies to include WB analysis in (i) multiple cell lines, (ii) peptide and phospho-peptide competition experiments, and (iii) analysis of site-directed mutants. It also strived to demonstrate lot-to-lot consistency aided by combination of two or more pre-qualified individual lots to create each batch to minimize batch-to-batch variability. Company 7 describes their stringent validation protocol for all antibodies to include testing of each antibody by WB, IP, IHC, IF, flow cytometry, and ELISA. It verifies the specificity and reproducibility of antibodies by using appropriate kinase-specific activators or inhibitors when available; testing against a large panel of cell lines with known target expression; phosphatase treatment for phospho-specificity; comparison to isotype control; verification in transfected cells, knockout cells, and siRNA-treated cells; utilizing blocking peptides to eliminate all signal; verifying correct subcellular localization or treatment-induced translocation; comparing new antibody lots to previous lots; providing optimal dilutions and buffers, as well as specifying both positive and negative control cell lines. For IHC, Company 7's antibodies are tested on paraffin-embedded cell pellets including cell pellets created after the cell lines are subjected to treatments known to induce signaling changes or treated with siRNA to block expression of the target. Tissue is treated with phosphatase to additionally test phospho-specificity on FFPE tissues. Xenografts with cell lines of known target expression or treatments to modulate expression are paraffin-embedded and then stained.

The datasheets for these companies include everything seen with Companies 2–5 plus additional examples of the successful use of their antibody. For example, Company 6 includes representative data for all validated applications with recommended antibody concentrations and includes flow cytometry, immunocytochemistry on a positive control cell line (including incubation with either the phospho-peptide or the non–phospho-peptide demonstrating signal absence only with the phospho-peptide), IHC of a positive control tissue, and a WB of a positive control cell line lysate also including detection after pre-incubation with the phospho- or non–phospho-specific peptides demonstrating a single band of the expected molecular weight with signal absent only after incubation with the phospho-specific peptide.

Antibodies purchased from Company 1 (which provided the minimal amount of information and no examples of successful use of the product) would require extensive validation by a researcher to demonstrate that the results describe only the target of interest; the company provides little in the way of assurances that it will work. Companies 2–5 all provide more information on their respective antibodies and include at least one example of the product successfully being used for at least one of their recommended applications with corresponding positive controls. While this is clearly preferable to Company 1's approach, these antibodies would still need to be validated by the researcher for target specificity in the application of interest and for lot-to-lot reproducibility. Company 6 describes the validation steps it uses to determine that its phospho-specific antibodies are both specific and reproducible. Furthermore, for each recommended application, an example of successful use is provided with corresponding inhibition by phospho-specific blocking peptides. Company 7 provides what we consider the gold standard for antibody validation. The extensive in-house testing described provides a high level of confidence that the antibodies it provides will work for all the applications that are recommended for the particular antibody. It also provides a greater level of confidence that results obtained will be specific for the described target and will be reproducible among antibody lots.

Even though Companies 6 and 7 provide extensive validation, the researcher is still obliged to confirm that the product gives specific and reproducible results in the cell lines or tissues of interest in the lab. Indeed, even the best companies cannot control what happens after the product leaves their door. Issues during shipping, inappropriate storage on or after arrival in the laboratory, and antibody contamination during usage are all potential sources of error in antibody-based testing. Thus vigilant and comprehensive controls should be done with each assay.

The Rimm Lab Algorithm for antibody validation for IHC/QIF

There are no uniform or enforceable standards for antibody validation. Unlike drugs—whose sale is prohibited without FDA approval—there is no federal agency governing what can be sold into the antibody-based assay market. In the future, we may see further FDA clearance of antibodies or more rigorous labeling and regulation of reagents to be used in clinical testing. However, to date, there is no universal standard. We therefore present our lab's approach (the Rimm Lab Algorithm) to the validation issue. Our approach is not sanctioned or approved by any governing body or by any trade association, and thus we are not so bold as to call this a “recommendation.” Instead, we provide what we feel is a compromise between rigor and lab economics that results in a level of evidence sufficient for data dissemination. Our algorithm for antibody validation (Figure 3) is especially focused for the end use application of IHC or QIF on paraffin-embedded tissues, but could be equally valid or modified for other antibody-based assays.

Our first line of evidence that an antibody is specific for the target of interest is done by WB. A variety of cell line lysates (or tissue homogenates) are selected, ideally with known levels of target expression such that both positive and negative cell lines are analyzed. Practically speaking, we often have no idea of target levels and select cell line series at random. Lines are often selected in such a way that we suspect some of the lines to be completely negative for the target protein (e.g., using fibroblast lines for epithelial targets). When true negative lines are not available, or when levels of target protein are highly dependent on growth conditions, we produce lysates of cell lines where the target protein has been knocked down using RNAi or lysates from cell lines typically null for the target that have been transfected for overexpression constructs. In a recent example, we have used inducible overexpression (A.W.W., unpublished data). An example of using siRNA to aid in validating an antibody is shown in Figure 4 for Stathmin (rabbit monoclonal; Epitomics, Burlingame, CA, USA), a microtubule-destabilizing protein. Lysates from BT-20 cells either mock-transfected or transfected with scrambled siRNA control or siRNA specific for Stathmin were analyzed by WB demonstrating loss of Stathmin expression (Figure 4A). BT-20 cells transfected with either scrambled or Stathmin siRNA were also fixed and decreased Stathmin expression was visualized with IF (Figure 4B). Additionally, when known target activators and inhibitors are available, lysates from treated cells can also be included when validating antibodies specific for a particular state (e.g., phosphorylation). Identification of a single band (or multiple bands if more than one isoform of the protein is expected to interact with the antibody) of the correct molecular weight only in cell lines expressing the target encourages further validation for use in IHC/QIF. An antibody demonstrating no binding on WB may still be specific for its intended target when in its native conformation and an IP experiment can be the next step in determining the specificity of the antibody if the goal is for use with IHC/QIF.

The second step in the validation of an antibody for IHC/QIF is to titer the antibody on a tissue microarray (TMA) comprised of FFPE cell line pellets corresponding to the identical cell lines used to first validate by WB in addition to patient tissue expected to express the target (for more information on the usefulness of TMAs, see References 39, and 40). A good antibody will have the following characteristics: (i) it will stain only the cell pellets expressing the target, (ii) the level of staining will decrease with increasing dilutions of the antibody, and (iii) it will demonstrate an expression pattern that is consistent with biological and mechanistic data in the published literature. The target expression seen with these first two steps should be quantified—we use ImageJ for quantification of WBs and AQUA for measuring the level of protein expression in each TMA spot—and then the results should show a strong correlation to each other. An example of an antibody meeting these conditions is shown in Figure 5 for ER-α (1D5 clone; Dako, Glostrup, Denmark). As expected from published literature, the staining on patient breast tissue is predominately nuclear (Figure 5A). Breast cell lines with varying ER expression levels (Figure 5B), as well as a calibration curve of recombinant ER protein, were analyzed by WB and the expression of ER protein (pg per µg of loaded cell lysate protein) was plotted against the expression level of ER as determined by IHC and quantified by AQUA demonstrating a strong correlation (R2 value of 0.91) between the two methods (Figure 5C).

The final step in validation of an antibody for any application is to demonstrate that the antibody is reproducible between assay runs and between lots. We accomplish this by using a TMA containing ~120 spots that is stained with each lot of the antibody. The target expression is quantified and a regression between the two scores for each spot is performed. A high correlation among multiple lots of the antibody is our final requirement for validation. An example of this is shown for an antibody to MAP-tau (United States Biological, Swampscott, MA, USA), where two different lots of the antibody were quantified with AQUA demonstrating a high correlation (Figure 6A). Each time the antibody is used on a different TMA, sections from this control TMA are stained in parallel as an additional staining control. The control TMA slide should always have a high correlation to previous experiments for a specific and reproducible antibody The example in Figure 6B shows inter-assay reproducibility of MENA (mouse MAb, clone 21; BD Transduction Laboratories, Franklin Lakes, NJ, USA).

These validation steps are relatively fast and inexpensive, but most importantly, they are comprehensive. This algorithm for antibody validation is somewhat similar to many other previously published approaches (13,18,36,41). These authors point out that one of the best controls for antibody validation is tissue from a knockout animal lacking the antigen altogether. When available, this tissue would be an excellent addition to any control TMA, but this is not available for every protein of interest and would be a time-consuming and expensive investment for the sole purpose of validating an antibody. Ideally, as suggested in a recent perspective by Alexander Kalyuzhny, we will one day have guidelines on the generation and use of antibodies (42) where all companies will be held to high standards for antibody validation and researchers can have greater confidence that their precious grant or clinical revenue dollars are not wasted on inaccurately labeled “vials of PBS” (36). For the meantime, however, the responsibility ultimately lies with the researcher or laboratory director to ensure that the antibodies used in their labs are validated for specificity and reproducibility.


The authors thank Elaine Alarid of the University of Wisconsin for provision of cells lines with inducible expression of ER-α. This work was supported by the National Institutes of Health (NIH; grant nos. CA139431, CA 114277, CA 110511, and CA 106709, to D.L.R.); the Susan G. Komen Foundation (grant no. KG090562, to D.L.R.); and the Department of Defense Breast Cancer Research Program [grant nos. 1W81XWH-06-1-0746 (to M.T.B.), 1W81XWH-08-1-0404 (to J.B.), and 1W81XWH-08-1-0784 (to A.W.W.)]. This paper is subject to the NIH Public Access Policy.

Competing interests

The authors declare no competing interests.

Address correspondence to David L. Rimm, Department of Pathology, Yale University School of Medicine, 310 Cedar St., PO Box 208023, New Haven, CT, 06520 USA. e-mail: [email protected]

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