Envisagenics, a biotechnology company driven by artificial intelligence, announced today the publication of the results of a study in the journal Molecular Systems Biology. This study evaluates the effectiveness of the company’s artificial intelligence and machine learning (AI/ML) platform, SpliceCore, in triple-negative breast cancer (TNBC). The study demonstrates the utility of AI/ML for target discovery in TNBC and for the identification of functional and verifiable splice-switching oligonucleotides (SSOs), crucial for the development of RNA-based therapies. The results also validate its potential to address a disease as challenging as TNBC, a particularly aggressive cancer that affects approximately 200,000 patients annually, with a five-year survival rate of only 20%. The detailed results of the study, titled “Development and validation of AI/ML-derived splice-switching oligonucleotides”, are available in the publication.
SSOs are synthetic antisense oligonucleotide compounds that directly act on pre-mRNA to regulate the expression of unique alternative splicing isoforms for cancer cells, which are key in cancer progression and metastasis. Although promising as a therapeutic approach to inhibit cancer growth, the identification of functional SSOs through traditional methods is costly and time-consuming.
“This study bridges the gap between computational predictions and experimental validation, positioning AI/ML as a critical force in validating RNA targets and advancing SSO therapeutic development,” said Martin Akerman, PhD, CTO and co-founder of Envisagenics.
In the study, Envisagenics achieved the following milestones:
– Used their proprietary platform, SpliceCore, to identify new therapeutic targets along with their corresponding modulatory SSOs and the specific splicing factors affected in pre-mRNA by these SSOs.
– Conducted a retrospective validation of the SpliceCore algorithm using known functional SSOs.
– Validated a previously unidentified target in TNBC, exon 13 of NEDD4L (NEDD4Le13), discovered through the SpliceCore platform.
– Demonstrated the efficacy of targeting NEDD4Le13 with an AI/ML-designed SSO, showing its ability to attenuate proliferative and migratory tendencies of TNBC cells by downregulating the transforming growth factor beta (TGFβ) pathway, a key player in tumor invasion and metastasis.
– Discovered a new mechanism of TGFβ pathway regulation through alternative splicing in cancer.
“For patients with TNBC and other difficult-to-treat diseases, this study illustrates the utility of SpliceCore in discovering new therapeutic targets from patient RNA sequencing data,” said Dr. Akerman. “Our findings affirm the strength and reliability of the platform and shed light on previously unrecognized avenues for therapeutic intervention.”