Matching Items (12)
Filtering by
- All Subjects: Cancer
- Creators: Borges, Chad
Description
Cancer claims hundreds of thousands of lives every year in US alone. Finding ways for early detection of cancer onset is crucial for better management and treatment of cancer. Thus, biomarkers especially protein biomarkers, being the functional units which reflect dynamic physiological changes, need to be discovered. Though important, there are only a few approved protein cancer biomarkers till date. To accelerate this process, fast, comprehensive and affordable assays are required which can be applied to large population studies. For this, these assays should be able to comprehensively characterize and explore the molecular diversity of nominally "single" proteins across populations. This information is usually unavailable with commonly used immunoassays such as ELISA (enzyme linked immunosorbent assay) which either ignore protein microheterogeneity, or are confounded by it. To this end, mass spectrometric immuno assays (MSIA) for three different human plasma proteins have been developed. These proteins viz. IGF-1, hemopexin and tetranectin have been found in reported literature to show correlations with many diseases along with several carcinomas. Developed assays were used to extract entire proteins from plasma samples and subsequently analyzed on mass spectrometric platforms. Matrix assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) mass spectrometric techniques where used due to their availability and suitability for the analysis. This resulted in visibility of different structural forms of these proteins showing their structural micro-heterogeneity which is invisible to commonly used immunoassays. These assays are fast, comprehensive and can be applied in large sample studies to analyze proteins for biomarker discovery.
ContributorsRai, Samita (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Borges, Chad (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
Background: High risk types of human papillomavirus (HPV) are known to cause cancer, including cervical (99%) and oropharyngeal cancer (70%). HPV type 16 is the most common subtype. Three antigens that are critical for integration or tumor progression are E2, E6 and E7. In this study, we developed a systematic approach to identify naturally-processed HPV16-derived HLA class I epitopes for immunotherapy development. Methods: K562 cells, which lack HLA expression, were transduced with each HPV16 antigen using lentivirus and supertransfected with HLA-A2 by nucleofection. Stable cell lines expressing each antigen were selected for and maintained throughout the investigation. In order to establish a Gateway-compatible vector for robust transient gene expression, a Gateway recombination expression cloning cassette was inserted into the commercial Lonza pMAX GFP backbone, which has been experimentally shown to display high transfection expression efficiency. GFP was cloned into the vector and plain K562 cells were transfected with the plasmid by nucleofection. Results: Expression of K562-A2 was tested at various time points by flow cytometry and A2 expression was confirmed. Protein expression was shown for the transduced K562 E7 by Western blot analysis. High transfection efficiency of the pMAX_GFP_Dest vector (up to 97% GFP+ cells) was obtained 48 hours post transfection, comparable to the commercial GFP-plasmid. Conclusion: We have established a rapid system for target viral antigen co-expression with single HLA molecules for analysis of antigen presentation. Using HPV as a model system, our goal is to identify specific antigenic peptide sequences to develop immunotherapeutic treatments for HPV-associated cancers.
ContributorsVarda, Bianca Marie (Author) / Anderson, Karen (Thesis director) / Borges, Chad (Committee member) / Krishna, Sri (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Mr. Green has stage 4 prostate cancer which has spread to the bones and liver and has become resistant to radiation and standard chemotherapy treatment. After 3 rounds of chemotherapy, his primary oncologist recommends that he participate in a clinical trial. He went to Dr. Red at the Saguaro Clinic after reading on the internet about a new Phase 1 clinical trial that the clinic is hosting, which is designed to target a specific receptor called AB-111 that may be present in malignant prostate, cervical, ovarian, and breast cells. After signing consent and completing the blood screens in the morning at the clinic, Mr. Green is told his liver enzymes are too high and the ranges specified in the protocol prohibit him from enrolling. Mr. Green is noticeably affected and distressed at this news, and Dr. Red recommends end-of-life care. Behind the scenes, this event is noted on official medical documents and trial study rosters as a "screen fail." This narrative, while fictional, is realistic because similar events occur in cancer clinical trial sites on a regular basis. I look at the inner "world" and mental journey of possible clinical trial candidates as they seek out information about clinical trials and gain understanding of their function \u2014 specifically in the context of Phase 1 cancer clinical trials. To whom is the language of the term "screen failure" useful? How does excluding individuals from clinical trials protect their health and does the integrity of the trial data supersede the person's curative goals? What is the message that cancer patients (potential research subjects) receive regarding clinical trials from sources outside their oncologists?
ContributorsMcKane, Alexandra (Author) / Maienschein, Jane (Thesis director) / Ellison, Karin (Committee member) / Foy, Joseph (Committee member) / Barrett, The Honors College (Contributor)
Created2013-12
Description
A major challenge with tissue samples used for biopsies is the inability to monitor their molecular quality before diagnostic testing. When tissue is resected from a patient, the cells are removed from their blood supply and normal temperature-controlled environment, which causes significant biological stress. As a result, the molecular composition and integrity undergo significant change. Currently, there is no method to track the effects of these artefactual stresses on the sample tissue to determine any deviations from the actual patient physiology. Without a way to track these changes, pathologists have to blindly trust that the tissue samples they are given are of high quality and fit for molecular analysis; physicians use the analysis to make diagnoses and treatment plans based on the assumption that the samples are valid. A possible way to track the quality of the tissue is by measuring volatile organic compounds (VOCs) released from the samples. VOCs are carbon-based chemicals with high vapor pressure at room temperature. There are over 1,800 known VOCs within humans and a number of these exist in every tissue sample. They are individualized and often indicative of a person’s metabolic condition. For this reason, VOCs are often used for diagnostic purposes. Their usefulness in diagnostics, reflectiveness of a person’s metabolic state, and accessibility lends them to being beneficial for tracking degradation. We hypothesize that there is a relationship between the change in concentration of the volatile organic compounds of a sample, and the molecular quality of a sample. This relationship is what would indicate the accuracy of the tissue quality used for a biopsy in relation to the tissue within the body.
ContributorsSharma, Nandini (Co-author) / Fragoso, Claudia (Co-author) / Grenier, Tyler (Co-author) / Hanson, Abigail (Co-author) / Compton, Carolyn (Thesis director) / Tao, Nongjian (Committee member) / Moakley, George (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
With cancer rates increasing and affecting more people every year, I felt it was important to educate the younger generation about the potential factors that could put them at risk of receiving a cancer diagnosis later in life. I thought that this was important to do because most students, especially in rural communities, are not taught the factors that increase your risk of getting cancer in the future. This leads to students not having the tools to think about the repercussions that their actions can have in their distant future in regard to their risk of getting cancer. I went to six schools throughout the valley and the White Mountains of Arizona with differing education levels and demographics to provide them with prevention strategies that they could implement into their daily lives to reduce their risk of getting cancer in the future. Some of the schools had curriculums that included cancer and some of the factors that increase your risk, while others never mention what is happening biologically when a person has cancer. I introduced factors such as no smoking or tobacco use, diet, exercise, sunscreen use, avoiding alcohol, and getting screened regularly. While at each school, I discussed the importance of creating these healthy habits while they are young because cancer is a disease that comes from the accumulation of mutations that can begin occurring in their bodies even now. After my presentation, 98.6% of the 305 students who viewed my presentation felt like they had learned something from the presentation and were almost all willing to implement at least one of the changes into their daily lives.
ContributorsGoforth, Michelle Nicole (Author) / Compton, Carolyn (Thesis director) / Lake, Douglas (Committee member) / Popova, Laura (Committee member) / Dean, W.P. Carey School of Business (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated various impacts of bioactive food molecules on the promotion or prevention of these oncogenic mutations. This work explores several of these molecules and their relation to cancer prevention and provides a sample meal plan, which highlights many additional molecules that are currently being studied.
ContributorsCurtin, Elise (Author) / Don, Rachael (Thesis director) / Compton, Carolyn (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
Description
Evolutionary theory provides a rich framework for understanding cancer dynamics across scales of biological organization. The field of cancer evolution has largely been divided into two domains, comparative oncology - the study of cancer across the tree of life, and tumor evolution. This work provides a theoretical framework to unify these subfields with the intent that an understanding of the evolutionary dynamics driving cancer risk at one scale can inform the understanding of the dynamics on another scale. The evolution of multicellular life and the unique vulnerabilities in the cellular mechanisms that underpin it explain the ubiquity of cancer prevalence across the tree of life. The breakdown in cellular cooperation and communication that were required for multicellular life define the hallmarks of cancer. As divergent life histories drove speciation events, it similarly drove divergences in fundamental cancer risk across species. An understanding of the impact that species’ life history theory has on the underlying network of multicellular cooperation and somatic evolution allows for robust predictions on cross-species cancer risk. A large-scale veterinary cancer database is utilized to validate many of the predictions on cancer risk made from life history evolution. Changing scales to the cellular level, it lays predictions on the fate of somatic mutations and the fitness benefits they confer to neoplastic cells compared to their healthy counterparts. The cancer hallmarks, far more than just a way to unify the many seemingly unique pathologies defined as cancer, is a powerful toolset to understand how specific mutations may change the fitness of somatic cells throughout carcinogenesis and tumor progression. Alongside highlighting the significant advances in evolutionary approaches to cancer across scales, this work provides a lucid confirmation that an understanding of both scales provides the most complete portrait of evolutionary cancer dynamics.
ContributorsCompton, Zachary Taylor (Author) / Maley, Carlo C. (Thesis advisor) / Aktipis, Athena (Committee member) / Buetow, Kenneth (Committee member) / Nedelcu, Aurora (Committee member) / Compton, Carolyn (Committee member) / Arizona State University (Publisher)
Created2023
Description
Quiescin sulfhydryl oxidase 1 (QSOX1) is a highly conserved disulfide bond-generating enzyme that represents the ancient fusion of two major thiol-disulfide oxidoreductase gene families: thioredoxin and ERV. QSOX1 was first linked with cancer after being identified as overexpressed in pancreatic ductal adenocarcinoma (but not in adjacent normal ductal epithelia, infiltrating lymphocytes, or chronic pancreatitis). QSOX1 overexpression has been confirmed in a number of other histological tumor types, such as breast, lung, kidney, prostate, and others. Expression of QSOX1 supports a proliferative and invasive phenotype in tumor cells, and its enzymatic activity is critical for promoting an invasive phenotype. An in vivo tumor growth study utilizing the pancreatic tumor cell line MIAPaCa-2 containing a QSOX1-silencing shRNA construct revealed that QSOX1 expression supports a proliferative phenotype. These preliminary studies suggest that suppressing the enzymatic activity of QSOX1 could represent a novel therapeutic strategy to inhibit proliferation and invasion of malignant neoplasms.
The goal of this research was to identify and characterize biologically active small molecule inhibitors for QSOX1. Chemical inhibition of QSOX1 enzymatic activity was hypothesized to reduce growth and invasion of tumor cells. Recombinant QSOX1 was screened against libraries of small molecules using an enzymatic activity assay to identify potential QSOX1 inhibitors. Two lead QSOX1 inhibitors were confirmed, 2-phenyl-1, 2-benzisoselenazol-3-one (ebselen), and 3-methoxy-n-[4-(1 pyrrolidinyl)phenyl]benzamide. The biological activity of these compounds is consistent with QSOX1 knockdown in tumor cell lines, reducing growth and invasion in vitro. Treatment of tumor cells with these compounds also resulted in specific ECM defects, a phenotype associated with QSOX1 knockdown. Additionally, these compounds were shown to be active in pancreatic and renal cancer xenografts, reducing tumor growth with daily treatment. For ebselen, the molecular mechanism of inhibition was determined using a combination of biochemical and mass spectrometric techniques. The results obtained in these studies provide proof-of-principle that targeting QSOX1 enzymatic activity with chemical compounds represents a novel potential therapeutic avenue worthy of further investigation in cancer. Additionally, the utility of these small molecules as chemical probes will yield future insight into the general biology of QSOX1, including the identification of novel substrates of QSOX1.
The goal of this research was to identify and characterize biologically active small molecule inhibitors for QSOX1. Chemical inhibition of QSOX1 enzymatic activity was hypothesized to reduce growth and invasion of tumor cells. Recombinant QSOX1 was screened against libraries of small molecules using an enzymatic activity assay to identify potential QSOX1 inhibitors. Two lead QSOX1 inhibitors were confirmed, 2-phenyl-1, 2-benzisoselenazol-3-one (ebselen), and 3-methoxy-n-[4-(1 pyrrolidinyl)phenyl]benzamide. The biological activity of these compounds is consistent with QSOX1 knockdown in tumor cell lines, reducing growth and invasion in vitro. Treatment of tumor cells with these compounds also resulted in specific ECM defects, a phenotype associated with QSOX1 knockdown. Additionally, these compounds were shown to be active in pancreatic and renal cancer xenografts, reducing tumor growth with daily treatment. For ebselen, the molecular mechanism of inhibition was determined using a combination of biochemical and mass spectrometric techniques. The results obtained in these studies provide proof-of-principle that targeting QSOX1 enzymatic activity with chemical compounds represents a novel potential therapeutic avenue worthy of further investigation in cancer. Additionally, the utility of these small molecules as chemical probes will yield future insight into the general biology of QSOX1, including the identification of novel substrates of QSOX1.
ContributorsHanavan, Paul D (Author) / Lake, Douglas (Thesis advisor) / LaBaer, Joshua (Committee member) / Mangone, Marco (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cancer is a heterogeneous disease with discrete oncogenic mechanisms. P53 mutation is the most common oncogenic mutation in many cancers including breast cancer. This dissertation focuses on fundamental genetic alterations enforced by p53 mutation as an indirect target. p53 mutation upregulates the mevalonate pathway genes altering cholesterol biosynthesis and prenylation. Prenylation, a lipid modification, is required for small GTPases signaling cascades. Project 1 demonstrates that prenylation inhibition can specifically target cells harboring p53 mutation resulting in reduced tumor proliferation and migration. Mutating p53 is associated with Ras and RhoA activation and statin prevents this activity by inhibiting prenylation. Ras-related pathway genes were selected from the transcriptomic analysis for evaluating correlation to statin sensitivity. A gene signature of seventeen genes and TP53 genotype (referred to as MPR signature) is generated to predict response to statins. MPR signature is validated through two datasets of drug screening in cell lines. As advancements in targeted gene modification are rising, the CRISPR-Cas9 technology has emerged as a new cancer therapeutic strategy. One of the important risk factors in gene therapy is the immune recognition of the exogenous therapeutic tool, resulting in obstruction of treatment and possibly serious health consequences. Project 2 describes a method development that can potentially improve the safety and efficacy of gene-targeting proteins. A cohort of 155 healthy individuals was screened for pre-existing B cell and T cell immune response to the S. pyogenes Cas9 protein. We detected antibodies against Cas9 in more than 10% of the healthy population and identified two immunodominant T cell epitopes of this protein. A de-immunized Cas9 that maintains the wild-type functionality was engineered by mutating the identified T cell epitopes. The gene signature and method described here have the potential to improve strategies for genome-driven tumor targeting.
ContributorsRoshdi Ferdosi, Shayesteh (Author) / Anderson, Karen S (Thesis advisor) / LaBaer, Joshua (Thesis advisor) / Woodbury, Neel (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2017
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