Pre-clinical validation of an RNA-based precision oncology platform for patient-therapy alignment in a diverse set of human malignancies resistant to standard treatments

Mundi, P. S.; Dela Cruz, F. S.; Grunn, A.; Diolaiti, D.; Mauguen, A.; Siddiquee, A.; You, D.; Realubit, R.; Karan, C.; Ortiz, M. V.; Accordino, M.; Aloni, Z.; Brogan, F.; Bruce, J.; Caescu, C. I.; Carvajal, R.; Crew, K.; Decastro, G.; Heaney, M.; Henick, B.; Hershman, D.; Hou, J.; Iwamoto, F.; Jurcic, J.; Kiran, P. R.; Kluger, M.; Kreisl, T.; Lamanna, N.; Lassman, A.; Lim, E.; Manji, G.; McKhann, G.; McKiernan, J.; Neugut, A.; Olive, K.; Rosenblat, T.; Schwartz, G. K.; Shu, C.; Sisti, M.; Tergas, A.; Vattakalam, R.; Welch, M.; Wenske, S.; Wright, J.; Hibshoosh, H.; Kalinsky, K.; Aburi, M.; Sim

doi:10.1101/2021.10.03.462951

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bioRxiv · 10.1101/2021.10.03.462951

Pre-clinical validation of an RNA-based precision oncology platform for patient-therapy alignment in a diverse set of human malignancies resistant to standard treatments

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Abstract

Predicting tumor sensitivity to antineoplastics remains an elusive challenge, with no methods demonstrating predictive power. Joint analysis of tumors--from patients with distinct malignancies who had progressed on multiple lines of therapy--and drug perturbation transcriptional profiles predicted sensitivity to 28 of 350 drugs, 26 of which (93%) were confirmed in low-passage, patient-derived xenograft (PDX) models. Drugs were prioritized based on their ability to either invert the activity of individual Master Regulator proteins, with available high-affinity inhibitors, or of the modules they comprise (Tumor-Checkpoints), based on de novo mechanism of action analysis. Of 138 PDX mice enrolled in 16 single and 18 multi-protein treatment arms, a disease control rate (DCR) of 68% and 91 %, and an objective response rate (ORR) of 12% and 17%, were achieved respectively, compared to 6% and 0% in the negative controls arm, with multi-protein drugs achieving significantly more durable responses. Thus, these approaches may effectively complement and expand current precision oncology approaches, as also illustrated by a case study.

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Mundi, P. S., Dela Cruz, F. S., Grunn, A., Diolaiti, D., Mauguen, A., Siddiquee, A., You, D., Realubit, R., Karan, C., Ortiz, M. V., Accordino, M., Aloni, Z., Brogan, F., Bruce, J., Caescu, C. I., Carvajal, R., Crew, K., Decastro, G., Heaney, M., Henick, B., Hershman, D., Hou, J., Iwamoto, F., Jurcic, J., Kiran, P. R., Kluger, M., Kreisl, T., Lamanna, N., Lassman, A., Lim, E., Manji, G., McKhann, G., McKiernan, J., Neugut, A., Olive, K., Rosenblat, T., Schwartz, G. K., Shu, C., Sisti, M., Tergas, A., Vattakalam, R., Welch, M., Wenske, S., Wright, J., Hibshoosh, H., Kalinsky, K., Aburi, M., Sim. 2021-10-03. Pre-clinical validation of an RNA-based precision oncology platform for patient-therapy alignment in a diverse set of human malignancies resistant to standard treatments. https://doi.org/10.1101/2021.10.03.462951

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