Antibody Specificity Vs. Cross-Reactivity

Does Monoclonal Mean Monospecific? A Crisis in Antibody Specificity

Highly specific antibodies are integral to a large number of exciting projects. From understanding physiological processes to life-changing antibody-based diagnostics and therapy, antibody-powered research is at the forefront of innovation in the life sciences. We love antibodies because they offer unprecedented specificity and selectivity. But what if they don’t?

In this article, we’re looking at the importance of antibody specificity, the reproducibility crisis, and how antibody validation can prevent enormous time and money waste.

Are Your Antibodies Genuinely Specific?

Depending on your method and target, there are three main types of antibodies:

Hybridoma monoclonal antibodies are accurate and generally offer solid reproducibility. However, they are prone to genetic drift and usually come at a higher cost.

Recombinant cloned antibodies ensure better reproducibility but are currently not as widely available as other types.

Finally, polyclonal antibodies, which bind multiple epitopes, offer clonal and biophysical diversity. This increases their sensitivity in certain assays and boosts their stability. While polyclonal antibodies are the most controversial of the three types, ignoring their advantages means missing out on a “fit-for-purpose” tool.

One question remains:

What happens when a reagent known for its specificity and reproducibility turns out not to be specific enough?

We now have a wider range of antibodies than ever before. Our validation tools have also improved. But with the increasing popularity of antibody characterization and evaluation methods, we are finding that some of the reagents are not nearly as specific as we thought.

In a 2018 study, 185 hybridomas were examined to assess potential genetic diversity (the existence of which had been anecdotally known for decades). 31.9% of the hybridomas examined contained additional productive chains that affect antibody properties such as specificity, binding signal, and signal-to-noise ratio. (Bradbury et al., 2018)

Here at engine, we performed a similar experiment using three commercially available antibodies. Using our hEXselect arrays, we detected multiple positive hits, identifying both specific and non-specific binding. One would assume that a monoclonal antibody is monospecific – but for one in three reagents, this is not the case. To do good science, we need high-quality data that we can trust. If antibodies, a reagent we rely on for specificity, are not specific enough, the cost can be devastating:

The Cost Of Off-Target Specificity

Antibodies are the backbone of breakthrough research. A tremendous amount of effort, time, and money investment depends on these high-quality reagents. Off-target specificity can jeopardize the entire experiment or diagnostic pipeline.

Inaccurate Results

False-positive and false-negative results are part of the research and diagnostic process. When an antibody cross-reacts with an unrelated protein, the accuracy of the immunoassay decreases. This can slow down your research and negatively impact journals when it is time to publish. Just as proper antibody validation improves the chances of an article being accepted, its absence has a negative impact. (Gautron et al., 2019) This is not surprising, of course, since inaccuracy in raw data affects the overall quality of research.

Time and Money Sink

The financial impact of reproducibility cannot be overstated. Decades of research effort and investment can go down the drain due to insufficient validation.

The discovery of the estrogen receptor β is a particularly striking example. The receptor was reported to be homologous with the pharmacological target for breast cancer, ERα, and represented a new hope for endocrine treatment. Twenty years of research were in vain, however, when it was found that of the 13 anti-ERβ antibodies, only one had sufficient specificity. In other words, ERβ protein expression was not associated with breast cancer, which misled researchers. (Andersson et al., 2017)

And this is not the only case where the lack of adequate validation has had devastating consequences. One study estimated losses due to off-target specificity and non-reproducibility at $1.7 billion in 2019. (Berglund et al., 2008)

Ultimately, inadequate antibody reagents are detrimental to a successful scientific endeavour. Whether you are exploring disease mechanisms or developing biomarker tests, proper characterization and validation prevents these disastrous outcomes.

How Our Protein Arrays Can Help!

Protein arrays allow us to understand protein interactions without bias or high cost. Our antibody specificity service screens more than 10,000 potential antigens that your antibody reagent could bind to. These proteins are not selected based on hypothesis, so you get an overall view of potential off-target specificity. We can also include the antigen you want to detect in the array to further validate the antibody.

And we already know that it works. High-density protein array technology has proven to be a fast and efficient validation method in the past. (Kijanka et al. 2009) When we performed our own analysis of the binding patterns of commercially available antibodies. The results using our hEXselect array confirmed once again that protein arrays are a valuable tool for detecting off-target activity.

The assays are performed in a single run, requiring only µl of sample. We provide full access to data and scientific discussion and keep our service affordable in the interest of a better, more accurate landscape in immunohistochemistry.

Final Thoughts

The understanding, diagnosis, and treatment of disease are increasingly dependent on antibodies. Antibody screening is an excellent way to ensure consistent assays and reduce the financial burden of off-target reactivity. With our engine protein array service, we can test your reagent against >10,000 potential antigens. And we only need some µl of your antibody!

Validating antibodies using protein arrays protects you from developing flawed assays, producing unreliable data, compromising academic reputation, and investing time and money in your research. Let us help you achieve better, more accurate, and more reproducible results!

Interested in more information? Download our result presentation detailing the specificity of commercial antibodies, or contact our experts to schedule a free brainstorming session.


  • Bradbury, A., Trinklein, N. D., Thie, H., Wilkinson, I. C., Tandon, A. K., Anderson, S., Bladen, C. L., Jones, B., Aldred, S. F., Bestagno, M., Burrone, O., Maynard, J., Ferrara, F., Trimmer, J. S., Görnemann, J., Glanville, J., Wolf, P., Frenzel, A., Wong, J., Koh, X. Y., … Dübel, S. (2018). When monoclonal antibodies are not monospecific: Hybridomas frequently express additional functional variable regions. mAbs, 10(4), 539–546. https://doi.org/10.1080/19420862.2018.1445456
  • Gautron L. (2019). On the Necessity of Validating Antibodies in the Immunohistochemistry Literature. Frontiers in neuroanatomy, 13, 46. https://doi.org/10.3389/fnana.2019.00046
  • Andersson, S., Sundberg, M., Pristovsek, N., Ibrahim, A., Jonsson, P., Katona, B., Clausson, C. M., Zieba, A., Ramström, M., Söderberg, O., Williams, C., & Asplund, A. (2017). Insufficient antibody validation challenges oestrogen receptor beta research. Nature communications, 8, 15840. https://doi.org/10.1038/ncomms15840
  • Berglund, L., Björling, E., Oksvold, P., Fagerberg, L., Asplund, A., Szigyarto, C. A., Persson, A., Ottosson, J., Wernérus, H., Nilsson, P., Lundberg, E., Sivertsson, A., Navani, S., Wester, K., Kampf, C., Hober, S., Pontén, F., & Uhlén, M. (2008). A genecentric Human Protein Atlas for expression profiles based on antibodies. Molecular & cellular proteomics : MCP, 7(10), 2019–2027. https://doi.org/10.1074/mcp.R800013-MCP200
  • Kijanka, G., Ipcho, S., Baars, S., Chen, H., Hadley, K., Beveridge, A., Gould, E., & Murphy, D. (2009). Rapid characterization of binding specificity and cross-reactivity of antibodies using recombinant human protein arrays. Journal of immunological methods, 340(2), 132–137. https://doi.org/10.1016/j.jim.2008.10.008

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