Abstract 26P
Background
Tumor-derived genetic alterations can regulate tumor microenvironment (TME) and host immune responses via activation of oncogenic pathways. Therefore, detection of somatic mutations associated with TME and tumor immunity may be useful in identifying patients who could benefit from immunotherapy. Immune checkpoint inhibitors (ICIs), a type of immunotherapy, are considered to be the emerging standard of care for various cancers. However, biomarkers that can help in predicting response to ICIs remain unknown.
Methods
To identify genetic markers associated with sensitivity to ICIs, we established a transcriptome-based predictive model followed by integrative genomics analyses. The impact of in silico derived biomarkers on the TME and response to ICIs was then assessed using in vitro assays and an in vivo mouse model study.
Results
We generated a transcriptome signature associated with response to ICIs based on a small but well-defined immunotherapy study (GSE78220) and applied the signature to large melanoma cohort data from The Cancer Genome Atlas (TCGA) by estimating transcriptome similarity. Based on the analysis, TCGA melanoma cohort was classified into potential responders and non-responders, and subsequent genomic interrogation revealed that the distribution of splicing factor SF3B1 mutations was significantly higher in potential responders. Furthermore, comparative analyses based on patients genotypes and loss- and gain-of-function studies based on manipulation of SF3B1 mutations revealed that SF3B1 mutations promoted transcriptional reprogramming in response to ICIs. To substantiate these results in vivo, we established a syngeneic mouse model, wherein immune resistant B16F10 melanoma cells were implanted into mice. Strikingly, in comparison to mice bearing wild-type SF3B1 tumors, mice bearing mutant SF3B1 tumors showed improved TME and immune profiles suitable for immunotherapy, which were characterized by accumulation of CD4 and CD8 T cells, activated dendritic cells, and concomitant induction of immune effectors.
Conclusions
Our findings suggest that SF3B1 mutations serve as biomarkers that can used to preemptively predict response to ICIs and ensure rational use of immunotherapy in cancer patients.
Legal entity responsible for the study
Korea Research Institute of Chemical Technology (KRICT).
Funding
This work was supported by the Korea Research Institute of Chemical Technology grant [KK2231-20]; and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) [2022R1C1C100616211].
Disclosure
All authors have declared no conflicts of interest.