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- All Subjects: Yellow fever virus
Description
Despite the approval of a Dengue virus (DV) vaccine in five endemic countries, dengue prevention would benefit from an immunization strategy highly immunogenic in young infants and not curtailed by viral interference. Problematically, infants younger than 9 year of age, whom are particularly prone to Dengue severe infection and death, cannot be immunized using current approved DV vaccine. The most important issues documented so far are the lack of efficiency and enhancement of the disease in young seronegative recipients, as well as uneven protection against the four DV serotypes. Based on data from clinical trials that showed enhanced performance of dengue vaccines when the host has previous anti-flaviviral immunity, I proposed here an attractive solution to complement the current vaccine: a recombinant measles vaccine vectoring dengue protective antigens to be administered to young infants. I hypothesized that recombinant measles virus expressing Dengue 2 and 4 antigens would successfully induce neutralizing responses against DV2 and 4 and the vaccine cocktail of this recombinant measles can prime anti-flaviviral neutralizing immunity. For this dissertation, I generated and performed preclinical immune assessment for four novel Measles-Dengue (MV-DV) vaccine candidates. I generated four MVs expressing the pre membrane (prM) and full length or truncated (90%) forms of the major envelope (E) from DV2 and DV4. Two virus, MVvac2-DV2(prME)N and MVvac2-DV4(prME), expressed high levels of membrane associated full-length E, while the other two viruses, MVvac2-DV2(prMEsol)N and MVvac2-DV4(prMEsol)N, expressed and secreted truncated, soluble E protein to its extracellular environment. The last two vectored vaccines proved superior anti-dengue neutralizing responses comparing to its corresponding full length vectors. Remarkably, when MVvac2-DV2/4(prMEsol)N recombinant vaccines were combined, the vaccine cocktail was able to prime cross-neutralizing responses against DV 1 and the relatively distant 17D yellow fever virus attenuated strain. Thus, I identify a promising DV vaccination strategy, MVvac2-DV2/4(prMEsol)N, which can prime broad neutralizing immune responses by using only two of the four available DV serotypes. The current MV immunization scheme can be advantageus to prime broad anti-flaviviral neutralizing immunity status, which will be majorly boosted by subsequent chimeric Dengue vaccine approaches.
ContributorsAbdelgalel, Rowida (Author) / Reyes del Valle, Jorge (Thesis advisor) / Mason, Hugh (Thesis advisor) / Lake, Douglas (Committee member) / Stout, Valerie (Committee member) / Frasch, Wayne (Committee member) / Arizona State University (Publisher)
Created2016
Description
Cancer researchers have traditionally used a handful of markers to understand the origin of tumors and to predict therapeutic response. Additionally, performing machine learning activities on disparate data sources of varying quality is fraught with inherent bias. The Caris Life Sciences Molecular Database (CMD) is an immense resource for discovery as it contains over 215,000 molecular profiles of tumors with consistently gathered clinical grade molecular data along with immense amounts of clinical outcomes data. This resource was leveraged to generate two artificial intelligence algorithms aiding in diagnosis and one for therapy selection.
The Molecular Disease Classifier (MDC) was trained on 34,352 cases and tested on 15,473 unambiguously diagnosed cases. The MDC predicted the correct tumor type out of thirteen possibilities in the labeled data set with sensitivity, specificity, PPV, and NPV of 90.5%, 99.2%, 90.5% and 99.2% respectively when considering up to 5 predictions for a case.
The availability of whole transcriptome data in the CMD prompted its inclusion into a new platform called MI GPSai (MI Genomic Prevalence Score). The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai can predict the correct tumor type out of 21 possibilities on 93% of cases with 94% accuracy. When considering the top two predictions for a case, the accuracy increases to 97%.
Finally, a 67 gene molecular signature predictive of efficacy of oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer was developed - FOLFOXai. The signature was predictive of survival in an independent real-world evidence (RWE) dataset of 412 patients who had received FOLFOX/BV in 1st line and inversely predictive of survival in RWE data from 55 patients who had received 1st line FOLFIRI. Blinded analysis of TRIBE2 samples confirmed that FOLFOXai was predictive of OS in both oxaliplatin-containing arms (FOLFOX HR=0.629, p=0.04 and FOLFOXIRI HR=0.483, p=0.02).
The Molecular Disease Classifier (MDC) was trained on 34,352 cases and tested on 15,473 unambiguously diagnosed cases. The MDC predicted the correct tumor type out of thirteen possibilities in the labeled data set with sensitivity, specificity, PPV, and NPV of 90.5%, 99.2%, 90.5% and 99.2% respectively when considering up to 5 predictions for a case.
The availability of whole transcriptome data in the CMD prompted its inclusion into a new platform called MI GPSai (MI Genomic Prevalence Score). The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai can predict the correct tumor type out of 21 possibilities on 93% of cases with 94% accuracy. When considering the top two predictions for a case, the accuracy increases to 97%.
Finally, a 67 gene molecular signature predictive of efficacy of oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer was developed - FOLFOXai. The signature was predictive of survival in an independent real-world evidence (RWE) dataset of 412 patients who had received FOLFOX/BV in 1st line and inversely predictive of survival in RWE data from 55 patients who had received 1st line FOLFIRI. Blinded analysis of TRIBE2 samples confirmed that FOLFOXai was predictive of OS in both oxaliplatin-containing arms (FOLFOX HR=0.629, p=0.04 and FOLFOXIRI HR=0.483, p=0.02).
ContributorsAbraham, Jim (Author) / Spetzler, David (Thesis advisor) / Frasch, Wayne (Thesis advisor) / Lake, Douglas (Committee member) / Compton, Carolyn (Committee member) / Arizona State University (Publisher)
Created2020