64 Cancer testis antigen co-expression landscape in solid tumors. (9th November 2020)

• Record Type: Journal Article
• Authors: Seager, RJ; Roey, Erik Van; Gao, Shuang; Andreas, Jonathan; Giamo, Vincent; Burgher, Blake; Lenzo, Felicia; Nesline, Mary; DePietro, Paul; Wang, Yirong; Glenn, Sean; Zhang, Shengle; Conroy, Jeffrey; Pabla, Sarabjot
• Is Part Of: Journal for immunotherapy of cancer. Volume 8(2020)Supplement 3
• Page Start: A69
• Page End: A69
• Publication Date: 2020-11-09
• Subjects: Cancer -- Immunotherapy -- Periodicals; Cancer -- Immunological aspects -- Periodicals; Tumors -- Immunological aspects -- Periodicals; Immunotherapy -- Periodicals; 616.99406105
• DOI: 10.1136/jitc-2020-SITC2020.0064
• Languages: English
• ISSNs: 2051-1426

Abstract

Abstract : Background: Cancer testis antigens (CTAs) are tumor antigens that have a highly tissue-restricted expression but are often expressed in diverse malignancies. With their highly immunogenic expression limited to tumor cells, CTAs have become a prime target for cancer vaccinations and T-cell-based therapy with chimeric T-cell receptors. In this study, we investigated the landscape of 17 CTA (NY-ESO-1, LAGE-1A, and 15 other CTAs) in the context of the tumor immune microenvironment of real-world clinical tumors spanning multiple histologies. Methods: RNA-seq was performed on 5450 FFPE tumors, and the expression of each of the 17 CTAs were classified as Positive (nRPM≥20) or Negative (nRPM<20). Pearson correlation analysis was conducted on the nRPM values for each CTA to determine co-expression relationships between any of the 17 CTAs. In order to visualize patterns in the CTA expression landscape, heatmap analysis was performed, using hierarchical clustering with Pearson's correlation as a distance measure to reveal patterns in CTA status across all samples and CTAs. Results: 5450 tumor samples analyzed in this study spanned 39 histologic types of tumor and were predominantly composed of lung cancer (40.4%) followed by colorectal cancer (10.6%) and breast cancer (8.6%). Positive CTA prevalence ranged from 2.4% (GAGE13) to 31.5% (XAGE1B). A high degree of significant correlation between the expression of all CTAs was observed, with only GAGE10, XAGE1B, MLANA, MAGEA4, GAGE13, and SSX2 having a no significant correlation with at least one other CTA. Three key groups of co-expressed CTAs were observed: 1) NY-ESO-1, LAGE-1A, MAGEA12, MAGEA3, MAGEA1, MAGEA10, and MAGEA4 (0.36≤R≤0.82); 2) GAGE12J, GAGE2, GAGE1, GAGE13 (0.58≤R≤0.72); 3) SSX2, BAGE, MAGEC2 (0.4≤R≤0.58). The three remaining CTAs (GAGE10, XAGE1B, and MLANA) had little or no (R<0.22) correlation with any other CTA or each other. Clustering CTAs across all samples revealed three CTA expression clusters: 1) samples that express a collection of multiple CTAs; 2) samples that express mostly XAGE1B, over-represented by lung cancer (p=1.51e-296); 3) samples that express mostly GAGE10, over-represented by neuroendocrine tumors (p=1.64e-05). Conclusions: Across multiple cancer subtypes, the expression of a CTA occurs in the context of other CTAs, and specific groups of CTAs are likely to co-express, forming expression patterns characteristic to tumor subgroups. These findings provide a scientific base for selecting appropriate CTAs and designing multiplex vaccination in immunotherapies of a variety of tumors. Further studies are needed to understand the relationship of these CTAs with traditional and emerging immune-oncology biomarkers.