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Real-World Data Validation of Association Between Immunoregulatory Molecules Expression and Targetable Cancer Genes

Looking into future design of clinical trials in a tissue-agnostic fashion
24 Feb 2020
Translational research

There may be a role for combining targets identified by next-generation sequencing along with patterns of immunoregulatory molecules expression to better guide future design of clinical trials in various cancer types in a tissue-agnostic fashion according to an independent, validated real-world dataset of immunoregulatory molecules in the presence of certain gene mutations. The findings were presented during the 2020 ASCO-SITC Clinical Immuno-Oncology Symposium held from 6 to 8 February in Orlando, FL, US.  

Targeting actionable genes and using immunotherapy have increased treatment options. A group of investigators from the University of South Florida, H. Lee Moffitt Cancer Center & Research Institute in Tampa, FL, US, ImmunityBio and NantHealth previously reported that some immunoregulatory molecules are found differentially regulated in the presence of certain gene mutations regardless of cancer subtype. Furthermore, they validated a subset of these associations in an independent, real-world dataset with distinct clinicopathological characteristics. 

They previously identified 2740 patients from The Cancer Genome Atlas (TCGA) programme with at least one potentially oncogenic mutation within an established 50-gene hotspot panel. Differential expression of 10 immunoregulatory molecules was analyzed between mutant vs. wild-type.  

To ensure observed significant associations were not confounded by tumour-type, differential immunoregulatory molecules expression within mutant-enriched tumour-types was compared to that of mutant vs. wild-type. By using the NantHealth external database of 2739 unselected clinical cases, the study team now validated these associations. 

Within the TCGA cohort, 19 of 50 gene mutations were found to be significantly associated with ≥1 immunoregulatory molecules expression. In many, the mutant effect-size was larger than that of tumour-type. As an example, the study team highlighted head and neck carcinomas that are highly enriched for CDKN2A mutations (OR = 4.9, p = 4.3e-9), yet CDKN2A mutations are more associated with CTLA4 expression than head and neck carcinoma histology (t = 7.0 vs. 5.4). Of these 15 associations, 6 were validated within the independent later-stage NantHealth cohort. Most notably, CDKN2A mutation was validated as associated with increased PD-1 and CTLA-4 expression while KRAS and APC mutations were validated as associated with decreased PD-L1/2 expression. 

The authors concluded that presented differential checkpoint expression patterns are strongly associated with mutation status and are not primarily driven by tissue-type, which have been further validated by an external database. Strategies combining genomic targets have been shown to yield success as well as using immunotherapies. In order to better guide design of future clinical trials in a tissue-agnostic fashion, there may be a role for combining targetable cancer genes with immunoregulatory molecules expression. 

 

Reference  

Adashek JJ, Szeto CW, Reddy SK, et al. Real-world data validation for differential expression of immunoregulatory molecules and targetable cancer genes may provide therapeutic insights into agnostic-driven trial designs. J Clin Oncol 2020; 38:(suppl 5; abstr 10).   

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