Identification of cell surface proteins as potential immunotherapy targets in 12 pediatric cancers

Abstract

Technological advances now allow us to rapidly produce CARs and other antibody-derived therapeutics targeting cell surface receptors. To maximize the potential of these new technologies, relevant extracellular targets must be identified. The Pediatric Oncology Branch of the NCI curates a freely accessible database of gene expression data for both pediatric cancers and normal tissues, through which we have defined discrete sets of over-expressed transcripts in 12 pediatric cancer subtypes as compared to normal tissues. We coupled gene expression profiles to current annotation databases (i.e., Affymetrix, Gene Ontology, Entrez Gene), in order to categorize transcripts by their sub-cellular location. In this manner we generated a list of potential immune targets expressed on the cell surface, ranked by their difference from normal tissue. Global differences from normal between each of the pediatric tumor types studied varied, indicating that some malignancies expressed transcript sets that were more highly diverged from normal tissues than others. The validity of our approach is seen by our findings for pre-B cell ALL, where targets currently in clinical trials were top-ranked hits (CD19, CD22). For some cancers, reagents already in development could potentially be applied to a new disease class, as exemplified by CD30 expression on sarcomas. Moreover, several potential new targets shared among several pediatric solid tumors are herein identified, such as MCAM (MUC18), metadherin (MTDH), and glypican-2 (GPC2). These targets have been identified at the mRNA level and are yet to be validated at the protein level. The safety of targeting these antigens has yet to be demonstrated and therefore the identified transcripts should be considered preliminary candidates for new CAR and therapeutic antibody targets. Prospective candidate targets will be evaluated by proteomic analysis including Westerns and immunohistochemistry of normal and tumor tissues.

Keywords: Ewing’s sarcoma; cancer antigens; glioblastoma; hepatoblastoma; neuroblastoma; osteosarcoma; rhabdomyosarcoma; sarcoma.

Figure 1

T-Statistic overview of the top 25 tumor-specific transcripts. For each disease category (listed on the x-axis), the range of T-statistic values for the 25 membrane proteins most different from normal tissue, along with their average and quartiles, is represented as a box and whisker plot.

Figure 2

Frequency of hits across disease category. Transcripts appearing in the pediatric Top 25 were often shared between disease types. All of the transcripts expressed in more than three (A), or at least three (B), cancer types are listed. The x-axis lists the individual gene, and the stacked boxes represent presence of that transcript in the Top 25 for that disease type.