Bioinformatics

The first step for developing any personalized therapy is analysing patient’s genome to identify cancer’s fingerprints in patients: Neoantigens. We integrated the state-of-the-art genomics tools in our software, Ginga, that serves as the starting point in our project. With Ginga, we are able to discover neoantigens that are presented uniquely in the surface of tumor cells. We validated our software with 8 patients data extracted from Sequence Read Archive (SRA) toolkit. Our software, the documentations and manual are online on our Github repository.

Vaccine Therapy

By having the neoantigens list, we then moved to the next stage: producing personalized vaccines. We used Encapsulin nanocarriers as a delivery platform for personalized cancer vaccine. We then used cell-free protein expression system for high throughput production of our personalized vaccine. We were able to demonstrate the efficiency of our cell-free expression system by expressing sfGFP and then measuring fluorescence. We then demonstrated the expression and purification of our vaccine production system by extensive measurements through SDS-PAGE and DLS measurements.

We then demonstrated the expression and purification of our vaccine production system by extensive measurements through SDS-PAGE and DLS measurements.

Further, we tested our constructed plasmid by incorporating OT1 coding sequence into our platform. The measurements from SDS-Page and Mass-spec clearly demonstrated our vaccine production and purification steps in our platform.

For full characterization of our Encapsulin platform, we then tested it by dendritic cell assays for uptaking Encapsulin and then explored the Encapsulin’s ability to mediate the neoantigen presentation on MHC-I complexes. We demonstrated the uptaken of Encapsulin by incorporating Promega’s lysine BODIPY to it and then performing SDS PAGE and fluorescently imaging the gel. For demonstration of neoantigen presentation, we incorporated the standard immunogenic OT-1 peptide to our Encapsulin platform and then measured the presentation through Immunostaining FACS. The results suggests high signal from anti-mouse H-2Kb-SIINFEKL, which reflects a strong presentation of the OT-1 SIINFEKL peptide on dendritic cells.

We also created a video of a 3D reconstruction of a dendritic cell using STEVE and Fuiji to represent the 3D shape of the dendritic cell following the encapsulin vaccine presentation. The video is presented below.

Vaccine Monitoring and Relapse Detection

We developed and optimized a Cas12a detection system coupled to an amplification step for rapid, sensitive and specific detection of blood biomarkers that would allow us to monitor the vaccine response of a patient, but also to alert the patient of a potential relapse. Our first accomplishment was to amplify the biomarkers directly from blood plasma.

Secondly, we could demonstrate that our system could detect with high specificity point mutations, regardless of the presence of the PAM sequence and at different concentrations.

Moreover, we demonstrated that our system yielded sufficient specificity in order to detect a point mutated sequence in a noisy background represented by the plasma and fragments that differ only by a point mutation from our target. This was demonstrated to be true in the presence of 100-folds more concentrated background. This is of great importance as part of our follow-up scheme, since it’s realistic to imagine that both the sequence coding for the normal peptide and the point-mutated one coding for the derived neoantigen circulate together in the bloodstream. More informations on this on the Results page for the follow-up.