Perspectives on Cancer Genome Profiling


Tumor Evolution: A Resistance Mechanism To Checkpoint Blockade Inhibitors

Tumor cells are readily targeted and destroyed by the body’s army of cytotoxic T cells.  Normally, checkpoint blockade proteins on the outer membrane of T cells, such as programmed death 1 (PD-1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), distinguish between “self” and “non-self” cells. Checkpoint blockade inhibitors (CBIs), such as anti-PD-L1 (pembrolizumab) and anti-CTLA-4 (ipilimumab), prevent this binding so that T cells may freely scrutinize the antigens presented on the cell surface to determine whether cell death should be initiated or not.

Each mutation within a tumor cell produces a unique antigen that is previously unrecognized by the immune system. As a result, these ‘neoantigens’ provoke an immune reaction specific to the tumor cells. Recent findings have indicated that patients with higher mutational load respond better and have a greater overall survival rate when treated with CBIs due to a correlation between mutation load and the production of mutation-derived neoantigens (MANAs) (Le et al. 2015).However, while many patients respond well to treatment with CBIs, more than 50% of patients progress after an initial response. This prognosis calls for a further understanding of the mechanisms associated with resistance to CBIs.

In her 2017 Cancer Discovery paper, Dr. Valsamo Anagostou retrospectively showed that lung cancer tumor cells deliberately alter the tumor microenvironment to evade immune recognition. Though previously there had been documented instances of resistance to CBIs, the mechanisms of tumor evolution were largely speculative prior to her study. Dr. Anagostou found that a subset of mutation-associated neoantigens (MANAs) was eliminated at the time of resistance in several cases of post-response progressive tumors. In response to these findings, we at PGDx, in a collaborative effort with Dr. Anagostou, matched the candidate neoantigens with mutational calls from the tumor samples using NGS-based whole exome sequencing (WES) and our ImmunoSelectTM assay. Combining PGDx’s highly accurate cancer exome analyses (CancerXOME™) with in silico neoantigen prediction, ImmunoSelect™ R functions to identify and prioritize the most relevant MANAs.

A recent webinar featuring Dr. Anagostou, along with PGDx’s own Dr. Maria Sevdali, takes a deep-dive look at the significance of this study. The results of Dr. Anagostou’s investigation demonstrated that a significant mechanism leading to CBI resistance included the elimination of key identifiable neoantigens through the absence of certain tumor subclones and chromosomal loss of truncal alterations. Most of the eliminated mutations are typically expressed in lung cancer and encode for neoantigens that, according to Dr. Anagostou, had a greater likelihood to confer MHC binding. In essence, the triggers for initiation of an immune response prior to the onset of resistance were likely the MANAs only present in eliminated tumor cells.

The identification of this mechanism of tumor evolution will have crucial implications for predicting response to immunotherapy. This newfound capability of eliminating both subclonal and truncal mutations demonstrates that these subgroups must be considered in addition to clonal alterations for the development of vaccines and other therapies. Currently, the only FDA-approved biomarker for response to immunotherapy is MSI, a marker for mismatch repair defect, potentially resulting in tumors with high mutation load. PGDx now offers MSI detection as an added feature of our popular tissue and plasma panels, PlasmaSelectTM 64 and CancerSelectTM125.  These targeted panels contain genes chosen specifically for clinical actionability. Also, coming soon is MutatorDetect, a tumor mutational burden assay to be available in tissue and plasma.