Matching Items (13)
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- All Subjects: Bioinformatics
- Creators: Stafford, Phillip
- Creators: Cartwright, Reed
Description
Immunotherapy has been revitalized with the advent of immune checkpoint blockade
treatments, and neo-antigens are the targets of immune system in cancer patients who
respond to the treatments. The cancer vaccine field is focused on using neo-antigens from
unique point mutations of genomic sequence in the cancer patient for making
personalized cancer vaccines. However, we choose a different path to find frameshift
neo-antigens at the mRNA level and develop broadly effective cancer vaccines based on
frameshift antigens.
In this dissertation, I have summarized and characterized all the potential frameshift
antigens from microsatellite regions in human, dog and mouse. A list of frameshift
antigens was validated by PCR in tumor samples and the mutation rate was calculated for
one candidate – SEC62. I develop a method to screen the antibody response against
frameshift antigens in human and dog cancer patients by using frameshift peptide arrays.
Frameshift antigens selected by positive antibody response in cancer patients or by MHC
predictions show protection in different mouse tumor models. A dog version of the
cancer vaccine based on frameshift antigens was developed and tested in a small safety
trial. The results demonstrate that the vaccine is safe and it can induce strong B and T cell
immune responses. Further, I built the human exon junction frameshift database which
includes all possible frameshift antigens from mis-splicing events in exon junctions, and I
develop a method to find potential frameshift antigens from large cancer
immunosignature dataset with these databases. In addition, I test the idea of ‘early cancer
diagnosis, early treatment’ in a transgenic mouse cancer model. The results show that
ii
early treatment gives significantly better protection than late treatment and the correct
time point for treatment is crucial to give the best clinical benefit. A model for early
treatment is developed with these results.
Frameshift neo-antigens from microsatellite regions and mis-splicing events are
abundant at mRNA level and they are better antigens than neo-antigens from point
mutations in the genomic sequences of cancer patients in terms of high immunogenicity,
low probability to cause autoimmune diseases and low cost to develop a broadly effective
vaccine. This dissertation demonstrates the feasibility of using frameshift antigens for
cancer vaccine development.
treatments, and neo-antigens are the targets of immune system in cancer patients who
respond to the treatments. The cancer vaccine field is focused on using neo-antigens from
unique point mutations of genomic sequence in the cancer patient for making
personalized cancer vaccines. However, we choose a different path to find frameshift
neo-antigens at the mRNA level and develop broadly effective cancer vaccines based on
frameshift antigens.
In this dissertation, I have summarized and characterized all the potential frameshift
antigens from microsatellite regions in human, dog and mouse. A list of frameshift
antigens was validated by PCR in tumor samples and the mutation rate was calculated for
one candidate – SEC62. I develop a method to screen the antibody response against
frameshift antigens in human and dog cancer patients by using frameshift peptide arrays.
Frameshift antigens selected by positive antibody response in cancer patients or by MHC
predictions show protection in different mouse tumor models. A dog version of the
cancer vaccine based on frameshift antigens was developed and tested in a small safety
trial. The results demonstrate that the vaccine is safe and it can induce strong B and T cell
immune responses. Further, I built the human exon junction frameshift database which
includes all possible frameshift antigens from mis-splicing events in exon junctions, and I
develop a method to find potential frameshift antigens from large cancer
immunosignature dataset with these databases. In addition, I test the idea of ‘early cancer
diagnosis, early treatment’ in a transgenic mouse cancer model. The results show that
ii
early treatment gives significantly better protection than late treatment and the correct
time point for treatment is crucial to give the best clinical benefit. A model for early
treatment is developed with these results.
Frameshift neo-antigens from microsatellite regions and mis-splicing events are
abundant at mRNA level and they are better antigens than neo-antigens from point
mutations in the genomic sequences of cancer patients in terms of high immunogenicity,
low probability to cause autoimmune diseases and low cost to develop a broadly effective
vaccine. This dissertation demonstrates the feasibility of using frameshift antigens for
cancer vaccine development.
ContributorsZhang, Jian (Author) / Johnston, Stephen Albert (Thesis advisor) / Chang, Yung (Committee member) / Stafford, Phillip (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2018
Description
Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
ContributorsOrr, Adam James (Author) / Cartwright, Reed (Thesis advisor) / Wilson, Melissa (Committee member) / Kusumi, Kenro (Committee member) / Taylor, Jesse (Committee member) / Pfeifer, Susanne (Committee member) / Arizona State University (Publisher)
Created2020
Pathways of Distinction Analysis of Liver Cancer Data: Genetic Differences Between Males and Females
Description
The Pathways of Distinction Analysis (PoDA) program calculates relationships between a given group of genes contained within a pathway, and a disease state. It was used here to investigate liver cancer, and to explore how genetic variability may contribute to the different rates of development of the disease in males and females. The goal of the study was to identify germline variation that differs by sex in hepatocellular carcinoma. Using the program, multiple pathways and genes were identified to have significant differences in their relationship to liver cancer in males and females. In animal studies, the genes which were identified using the PoDA analysis have been shown to impact liver cancer, often with different results for males and females. While these genes are often the focus in animal models, they are absent from current Genome Wide Association Studies (GWAS) catalogs for humans. By working to bridge the results of animal studies and human studies, the results help to identify the causes of liver cancer, and more specifically, the reason the disease affects males at much higher rates. The differences in pathways identified to be significant for the two sexes indicate the germline variance may play sex-specific roles in the development of hepatocellular carcinoma. Additionally, these results reinforce the capacity of the PoDA analysis to identify genes that may be missed by more traditional GWAS methods. This study lays the groundwork for further investigations into the identified genes and pathways, and how they behave differently within males and females.
ContributorsOlson, Erik Jon (Author) / Buetow, Kenneth (Thesis advisor) / Wilson, Melissa (Committee member) / Cartwright, Reed (Committee member) / Arizona State University (Publisher)
Created2021