MSI Analysis and the Application of Therapies Based on 2018 Nobel Immuno-Oncology Work

The 2018 Nobel Prize in Physiology and Medicine was awarded to James P. Allison of the United States and Tasuku Honjo of Japan for their work to identify pathways in the immune system that can be used to attack cancer cells (1). Although immunotherapy for cancer has been a goal for many decades, Dr. Allison and Dr. Honjo succeeded through their manipulation of “checkpoint inhibitor” pathways to target cancer cells.

Immune checkpoint inhibitor drugs have been effective in cancers such as aggressive metastatic melanoma, some lung cancers, kidney, bladder and head and neck cancers. These therapies have succeeded in pushing many aggressive cancers below detectable limits, though these cases are notably not relapse-free or necessarily “cured” (2,3).

One challenge in implementing immunotherapy in a cancer treatment regime is the need to understand the genetic makeup of the tumor. Certain tumors, with specific genetic features, are far more likely to respond to immune checkpoint therapy than others. For this reason, Microsatellite Instability (MSI) analysis has become an increasingly relevant tool in genetic and immuno-oncology research.

What is MSI Analysis?

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Determination of Antibody Mechanism of Action Using IdeS

Monoclonal antibodies (mAbs) have been widely used to eliminate undesired cells via various mechanisms, including antibody-dependent cell-mediated cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC) and programmed cell death (PCD). Unlike the Fc-dependent mechanism of ADCC and CDC, certain antibody–antigen interactions can evoke direct PCD via apoptosis or oncosis. Previously, researchers have reported the specific killing of undifferentiated human embryonic stem cells (hESC) by mAb84 (IgM) via oncosis (1)

In a recent publication (2), a monoclonal antibody (mAb), TAG-A1 (A1), was generated to selectively kill residual undifferentiated human embryonic stem cells (hESC). One of the many experimental tools used to characterize the mechanism of oncosis was the fragmention of the A1 antibody with IdeS and papain.

Papain digestion of IgG produces Fab fragments in the presence of reducing agent. F(ab)2 fragments of A1 were produced using IdeS Protease.

The results indicate that both Fab_A1 and F(ab)2_A1 bind to hESC but only F(ab)2_A1 retained hESC killing. Hence bivalency, but not Fc-domain, is essential for A1 killing on hESC.

  1. Choo, A.B. et al. (2008) Selection against undifferentiated human embryonic stem cells by a cytotoxic antibody recognizing podocalyxin-like protein-1. Stem Cells  26, 1454.
  2. Zheng, J.Y. et al. (2017) Excess reactive oxygen species production mediates monoclonal antibody-induced human embryonic stem cell death via oncosis. Cell Death and Differentiation 24, 546–58.

Further reading about IdeS Protease is available here.

Analysis of a biosimilar mAb using Mass Spectrometry

Several pharmaceutical companies have biosimilar versions of therapeutic mAbs in development. Biosimilars can promise significant cost savings for patients, but the unavoidable differences
between the original and thencopycat biologic raise questions regarding product interchangeability. Both innovator mAbs and biosimilars are heterogeneous populations of variants characterized by differences in glycosylation,oxidation, deamidation, glycation, and aggregation state. Their heterogeneity could potentially affect target protein binding through the F´ab domain, receptor binding through the Fc domain, and protein aggregation.

As more biosimilar mAbs gain regulatory approval, having clear framework for a rapid characterization of innovator and biosimilar products to identify clinically relevant differences is important. A recent reference (1) applied a comprehensive mass spectrometry (MS)-based strategy using bottom-up, middle-down, and intact strategies. These data were then integrated with ion mobility mass spectrometry (IM-MS) and collision-induced unfolding (CIU) analyses, as well as data from select biophysical techniques and receptor binding assays to comprehensively evaluate biosimilarity between Remicade and Remsima.

The authors observed that the levels of oxidation, deamidation, and mutation of individual amino acids were remarkably similar. they found different levels of C-terminal truncation, soluble protein aggregates, and glycation that all likely have a limited clinical impact.  Importantly, they identified more than 25 glycoforms for each product and observed glycoform population differences.

Overall the use of mass spectrometry-based analysis provides rapid and robust analytical information vital for biosimilar development. They demonstrated the utility of our multiple-attribute monitoring workflow using the model mAbs Remicade and Remsima and have provided a template for analysis of future mAb biosimilars.

1. Pisupati, K. et. al. (2017) A Multidimensional Analytical Comparison of Remicade and the Biosimilar Remsima. Anal. Chem 89, 38–46.