ABSTRACT
Fusion genes are well-known cancer drivers. However, most known oncogenic fusions are protein-coding, and very few involve non-coding sequences due to lack of suitable detection tools. We develop SFyNCS to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. The main advantage of this study is that we use somatic structural variations detected from genomic data to validate fusions detected from transcriptomic data. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We show that SFyNCS has superior sensitivity and specificity over existing algorithms through extensive benchmarking in cancer cell lines and patient samples. We then apply SFyNCS to 9565 tumor samples across 33 tumor types in The Cancer Genome Atlas cohort and detect a total of 165,139 fusions. Among them, 72% of the fusions involve non-coding sequences. We find a long non-coding RNA to recurrently fuse with various oncogenes in 3% of prostate cancers. In addition, we discover fusions involving two non-coding RNAs in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.
Subject(s)
Gene Fusion , Genomics , Neoplasms , Animals , Humans , Mice , Gene Expression Profiling , Genomics/methods , Neoplasms/genetics , Neoplasms/pathology , Oncogenes , TranscriptomeABSTRACT
Fusion genes are well-known cancer drivers. However, very few known oncogenic fusions involve non-coding sequences. We develop SFyNCS with superior performance to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. We validate fusions using somatic structural variations detected from the genomes. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We detect 165,139 fusions in 9,565 tumor samples across 33 tumor types in the Cancer Genome Atlas cohort. Among them, 72% of the fusions involve non-coding sequences and many are recurrent. We discover two long non-coding RNAs recurrently fused with various partner genes in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.
ABSTRACT
Activation of the stimulator of interferon genes (STING) pathway promotes antitumor immunity but STING agonists have yet to achieve clinical success. Increased understanding of the mechanism of action of STING agonists in human tumors is key to developing therapeutic combinations that activate effective innate antitumor immunity. Here, we report that malignant pleural mesothelioma cells robustly express STING and are responsive to STING agonist treatment ex vivo. Using dynamic single-cell RNA sequencing of explants treated with a STING agonist, we observed CXCR3 chemokine activation primarily in tumor cells and cancer-associated fibroblasts, as well as T-cell cytotoxicity. In contrast, primary natural killer (NK) cells resisted STING agonist-induced cytotoxicity. STING agonists enhanced migration and killing of NK cells and mesothelin-targeted chimeric antigen receptor (CAR)-NK cells, improving therapeutic activity in patient-derived organotypic tumor spheroids. These studies reveal the fundamental importance of using human tumor samples to assess innate and cellular immune therapies. By functionally profiling mesothelioma tumor explants with elevated STING expression in tumor cells, we uncovered distinct consequences of STING agonist treatment in humans that support testing combining STING agonists with NK and CAR-NK cell therapies.
