Synthetic peptides corresponding to the variable tandem repeat domain of the cancer-associated antigen MUC1 mucin are candidates for cancer vaccines. In our investigation mice were immunized via subcutaneous injection with poly(d,l-lactic-co-glycolic acid) (PLGA) microspheres containing a MUC1 mucin peptide. It was hypothesized that microencapsulation of the MUC1 mucin peptide would prime for antigen-specific Th1 responses while avoiding the need for traditional adjuvants and carrier proteins. Furthermore, an immunomodulator, monophosphoryl lipid A (MPLA), was incorporated into the peptide-loaded PLGA microspheres based on its ability to enhance Th1 responses. The results revealed T cell specific immune responses. The cytokine secretion profiles of the T cells consisted of high levels of interferon-gamma with undetectable levels of interleukin-4 and interleukin-10. Moreover, incorporation of MPLA in the MUC1 peptide-loaded PLGA microspheres resulted in an increase in interferon-gamma production. The antibody response was negative for IgM and IgG in the absence of MPLA; however, in the presence of MPLA antibody production was negative for IgM with a minimal IgG response consisting of IgG2a, IgG2b, and IgG3. Based on the antibody and cytokine profiles, it was concluded that MUC1 mucin peptide-loaded PLGA microspheres are capable of eliciting specific Th1 responses, which may be enhanced through the use of MPLA.

Metastasis is the most lethal aspect of cancer, yet current therapeutic strategies do not target its key rate-limiting steps. We have previously shown that the entry of cancer cells into the blood stream, or intravasation, is highly dependent upon in vivo cancer cell motility, making it an attractive therapeutic target. To systemically identify genes required for tumor cell motility in an in vivo tumor microenvironment, we established a novel quantitative in vivo screening platform based on intravital imaging of human cancer metastasis in ex ovo avian embryos. Utilizing this platform to screen a genome-wide shRNA library, we identified a panel of novel genes whose function is required for productive cancer cell motility in vivo, and whose expression is closely associated with metastatic risk in human cancers. The RNAi-mediated inhibition of these gene targets resulted in a nearly total (>99.5%) block of spontaneous cancer metastasis in vivo.

Extracellular vesicles (EVs) are highly abundant in human biofluids, containing a repertoire of macromolecules and biomarkers representative of the tissue of origin. EVs released by tumours can communicate key signals both locally and to distant sites to promote growth and survival or impact invasive and metastatic progression. Microscale flow cytometry of circulating EVs is an emerging technology that is a promising alternative to biopsy for disease diagnosis. However, biofluid-derived EVs are highly heterogeneous in size and composition, making their analysis complex. To address this, we developed a machine learning approach combined with EV microscale cytometry using tissue-and disease-specific biomarkers to generate predictive models. We demonstrate the utility of this novel extracellular vesicle machine learning analysis platform (EVMAP) to predict disease from patient samples by developing a blood test to identify high-grade prostate cancer and validate its performance in a prospective 215 patient cohort. Models generated using the EVMAP approach significantly improved the prediction of high-risk prostate cancer, highlighting the clinical utility of this diagnostic platform for improved cancer prediction from a blood test.

5530 Background: The accuracy of the extracellular vesicle-fingerprint score (EV-FPS) test to predict clinically significant prostate cancer (PCa; Gleason grade (GG) ≥ 3) from indolent disease (GG ≤ 2) and avoid unnecessary prostate biopsies was determined at the point of prostate biopsy decision. Methods: Clinical data, health information, and blood samples were collected from a prospective validation cohort of 415 men, without prior PCa diagnosis, referred to urology clinics for prostate biopsy or transurethral prostate surgery (June 2014-Dec 2016). The patient’s EV-FPS risk score was calculated by combining machine learning model-analyzed microflow cytometry data from EV biomarkers with logistic regression-analyzed patient-centric clinical features. The plasma-derived EV biomarkers were prostate-specific membrane antigen, polysialic acid and ghrelin-growth hormone receptor. The patient clinical features were; age, ethnicity, PCa family history, PSA levels, abnormal digital rectal examination (DRE) and prior negative prostate biopsy. Together, the biomarkers and clinical features provided specificity for clinically significant PCa. Results: The EV-FPS test identified clinically significant PCa patients with high accuracy (0.81 area under curve) at 95% sensitivity and 97% negative predictive value. Using a 7.85% probability cut-off after test validation; 95% of the patients with GG ≥ 3 would have been found before biopsy, 35% biopsies would have been avoided and diagnosis of GG ≥ 3 PCa would have been missed in only 5% of the cohort. Conclusions: This minimally invasive EV-FPS test accurately predicted clinically significant PCa in men with high EV-FPS risk scores, high PSA level and/or abnormal DRE. Therefore, men with low EV-FPS risk scores could potentially avoid unnecessary prostate biopsies. Clinical care cut-offs to calculate the number of biopsies that could have been avoided, and the percentage of GG ≥ 1 to GG ≥ 3 PCa that could have had a delayed diagnosis. [Table: see text]

While chemotherapy is a key treatment strategy for many solid tumors, it is rarely curative as patients will eventually become resistant. In this study, we sought to develop an effective suicide gene therapy approach for solid tumors that specifically exploits their unique transcriptional activation state. The tumor suppressor p53 is frequently mutated or dysregulated in cancer, and as a result the upstream signaling pathways activating p53 transcription are strongly upregulated. RNA-seq analysis has demonstrated that p53 transcription is significantly upregulated in almost all forms of cancer. Additionally, HCT116 cells lacking functional p53 display a 6-fold increase in p53 promoter activity when compared to its wild type p53 parent cell line. To exploit this, we have developed a Fusogenix FAST-LNP formulation to deliver a p53-driven inducible suicide gene, iCasp9, to solid tumors and destroy them upon activation with small molecule dimerizer, Rapamycin. To establish a proof-of-concept, plasmid encoding iCasp9 and luciferase under control of the p53 promoter was constructed and evaluated in a panel of cancer cell lines. While LNPs administered without Rapamycin or Rapamycin administered alone had no impact on cell viability, we observed greater than 90% apoptotic cell death when both were employed in a wide range of cancer cell lines with p53 deletions or mutations, as measured using cell viability assays, imaging assays, as well as Annexin V and TUNEL flow cytometry. Induction of iCasp9 protein expression and caspase-mediated apoptosis was confirmed using Western blot. No cell death was observed in cells with intact p53 such as human umbilical vein endothelial cells or the fibroblast cell line IMR-90. Next, we assessed the efficacy of FAST-LNPs containing p53-iCasp9 in xenograft PC-3 and H1299 models of human prostate cancer and lung cancer respectively. In some experiments, tumors were implanted subcutaneously in the flanks of 30 mice and allowed to grow to 500 mm3 before treatment by intravenous doses of 100 µg LNP twice per week during continuous low dosing of Rapamycin. We observed a rapid and dramatic reduction in tumor volume averaging 87% over the following 48 hours, with durable response. Tumors in control mice continued to grow exponentially. Overall survival of mice was extended 250% in the PC-3 cohort and 300% in the H1299 cohort. Optimization of number and concentration of LNP doses should allow for long term control of both localized and systemic disease. In conclusion, we describe a novel LNP gene therapy approach for the treatment of cancer with high selectivity for tumors with dysregulated p53 transcriptional activation. This approach has the potential to provide a highly efficacious alternative to current therapies for localized and advanced solid tumors. Citation Format: Douglas Wilson Brown, Arun Raturi, Prakash Bhandari, Deborah Sosnowski, Liliya Grin, Ping Wee, Hector Vega, Jennifer Gyoba, Maryam Hejazi, Jailal Ablack, Matthew Scholz, John D. Lewis. Selective ablation of solid tumors using a p53-targeted FAST-LNP gene therapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4069.