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Pediatric high-grade glioma is a heterogeneous group of highly malignant tumors of the central nervous system, with a median overall survival of less than two years after diagnosis, demanding novel treatment options. One innovative approach is gene therapy, which has so far been hampered for cancer treatment owing to the lack of a system targeting tumor cells specifically. To overcome this limitation, we established a novel strategy for gene therapy, combining tumor cell-specific adeno-associated virus (AAV) variants with oncogene-specific CRISPR-Cas nucleases. We screened 177 different Cas9/gRNA combinations targeting the genes encoding H3K27M or BRAFV600E, and identified highly specific nucleases that edited the oncogenic allele but left the respective WT loci intact, which we validated by PCR amplicon sequencing. Next, we intravenously injected an AAV library engineered to encode its own capsid DNA into mice harboring patient-derived xenograft tumors driven by H3K27M or BRAFV600E. After 21 days, we resected neoplasms and separated mCherry-labeled tumor cells from normal surrounding cells by fluorescence-activated cell sorting. Using the DNA from tumor cells as template, we generated a second AAV library, which was utilized in another round of in vivo selection. At the end of each screen, DNA from tumor cells, surrounding cells, and control tissues (liver and spleen) was analyzed by amplicon sequencing. Strikingly, we identified multiple AAV variants that were highly and recurrently enriched in the analyzed tumor tissues. We are currently validating these variants by intravenously injecting selected, GFP-encoding AAVs to tumor-bearing mice and by subsequently analyzing their distribution throughout the aforementioned tissues. We will combine oncogene-specific nucleases with these validated AAV variants and analyze their anti-tumoral efficacy in a preclinical setting. Furthermore, we plan to adapt this approach to allografted mice, evaluating its feasibility and efficacy in syngeneic models.

Proteins are nature’s most versatile molecular machines. Deep neural networks trained on large protein datasets have recently been used to tackle the unmet complexity of protein sequence–function relationships. The implicit knowledge contained in these networks represents a powerful, but thus far inaccessible, resource for understanding protein biology. Here, we show that occlusion-based sensitivity analysis can leverage the knowledge present in deep-neural-network-based protein sequence classifiers to identify functionally relevant parts of proteins. We first validated our approach by successfully predicting positions that mediate small molecule binding or catalytic activity across different protein classes. Next, we inferred the impact of point mutations on the activity of ERK and HRas, signalling factors frequently deregulated in cancer. Finally, we used our approach to identify engineering hotspots in CRISPR–Cas9 and anti-CRISPR protein AcrIIA4. Our work demonstrates how implicit knowledge in neural networks can be harnessed for protein functional dissection and protein engineering. Deep neural networks are a powerful tool for predicting protein function, but identifying the specific parts of a protein sequence that are relevant to its functions remains a challenge. An occlusion-based sensitivity technique helps interpret these deep neural networks, and can guide protein engineering by locating functionally relevant protein positions.

Parvoviruses are highly attractive templates for the engineering of safe, efficient, and specific gene therapy vectors, as best exemplified by adeno-associated virus (AAV). Another candidate that currently garners increasing attention is human bocavirus 1 (HBoV1). Notably, HBoV1 capsids can cross-package recombinant (r)AAV2 genomes, yielding rAAV2/HBoV1 chimeras that specifically transduce polarized human airway epithelia (pHAEs). Here, we largely expanded the repertoire of rAAV/BoV chimeras, by assembling packaging plasmids encoding the capsid genes of four additional primate bocaviruses, HBoV2–4 and GBoV (Gorilla BoV). Capsid protein expression and efficient rAAV cross-packaging were validated by immunoblotting and qPCR, respectively. Interestingly, not only HBoV1 but also HBoV4 and GBoV transduced pHAEs as well as primary human lung organoids. Flow cytometry analysis of pHAEs revealed distinct cellular specificities between the BoV isolates, with HBoV1 targeting ciliated, club, and KRT5+ basal cells, whereas HBoV4 showed a preference for KRT5+ basal cells. Surprisingly, primary human hepatocytes, skeletal muscle cells, and T cells were also highly amenable to rAAV/BoV transduction. Finally, we adapted our pipeline for AAV capsid gene shuffling to all five BoV isolates. Collectively, our chimeric rAAV/BoV vectors and bocaviral capsid library represent valuable new resources to dissect BoV biology and to breed unique gene therapy vectors. Keywords: adeno-associated virus, AAV, bocavirus, BoV, capsid engineering