Colorectal cancer is the third most common cancer in the United States with a 5-year late-stage survival rate of only 14%. Due to the lack of translation between animal models and clinical trials as well as the inefficacy of many chemotherapeutics in initial clinical trials, researchers are turning to in vitro drug screening models in an effort to mimic the conditions in vivo. This research project aimed to validate an in vitro tumor culture model within a microfluidic device using a clinically relevant chemotherapy drug. The first experiment consisted of a cell density and drug concentration study to determine the correct cell density and oxaliplatin concentration combinations that would result in a spectrum of quantifiable effects on the tumor cells. This experiment was then converted from a monolayer cell culture on glass into a 2D culture on top of a fibrin extracellular matrix (ECM) to ensure that the cells would respond in a similar way to the drug in the presence of an ECM as they did in the first experiment. The third experiment involved SW620 cells cultured within the fibrin hydrogel to create a 3D tumor model that better mimics the growing conditions in vivo. The goal of this experiment was again to ensure that the cells would respond in the same way to the oxaliplatin treatments as the previous experiments when adding complexity to the model. The final experiment was then to convert this 3D experiment performed in chamber slides into a 3D culture within a microfluidic device with media and oxaliplatin treatments perfused through the chamber using a syringe pump. The purpose of this experiment was to assess whether tumor cells could grow and survive within a microfluidic device with interstitial flow as well as determining if they responded as expected to the oxaliplatin treatment. The first three experiments performed within chamber slides showed that tumor count and average tumor size decreased with increasing oxaliplatin concentrations as expected, which is comparable to the in vivo tumor response to the drug. The fourth experiment demonstrated that, although cells are able to grow within the microfluidic device, this model did not accurately replicate the in vivo condition and future work needs to be aimed at improving the design of the device as well as optimizing parameters within the experiment.

<p>Colorectal cancer (CRC) is the third most prevalent cancer in the United States and estimated to affect 151,030 people and kill 52,580 people in 2022. Although some populations are more susceptible for CRC due to inherited cancer-causing mutations or having family history of CRC, most CRC cases occur sporadically with accumulation of a series of somatic mutation in tumor suppressor genes, oncogenes, and DNA repair system in the colon. Mutations in the adenomatous polyposis coli <em>(APC)</em> and the Kirsten rat sarcoma viral oncogene homologue <em>(KRAS)</em> are known as cancer driving mutations which are most frequently identified genetic lesions at early stages of sporadic CRC development. To evaluate effective drugs for prevention and treatment, preclinical models of CRC that resemble key features of human CRCs are crucial. Genetically modified mouse models (GEMM) of CRC bearing loss of <em>Apc</em> with or without other mutations, such as oncogenic <em>Kras</em> have been valuable tools to study pathobiology, treatment, and prevention of CRC. However, a major limitation of most <em>Apc</em>-mutant GEMMs is the predominant distribution of tumors in the small intestine rather than in the colon. Previously, a murine model bearing colon-specific mutations in <em>Apc</em> and <em>Kras</em> has been reported to develop colon-specific tumorigenesis in the colon, utilizing the <em>carbonic anhydrase 1 promoter/enhancer-Cre recombinase (CAC)</em> in Cre-LoxP system to restrict <em>Apc</em> knockout and a latent expression of oncogenic <em>Kras</em> in the colon tissue. However, only limited features of this model, so called AKC mouse, have been characterized so far. The lack of in depth understanding of this model could potentially hamper its utility for cancer research. Therefore, in Chapter 2 of this dissertation, I first characterized key aspects of disease-related phenotypes including clinical and histopathological features, tumor-elicited inflammation, the transcriptomic profiles, the gut microbial profiles in the AKC mice. Further, comparative analysis has been made on the transcriptomic profiles between AKC mice and human colon cancers with mutations in <em>APC</em> and <em>KRAS</em> at cancer stage II or below to evaluate the utility of the mouse model for studying human CRCs.</p> <p>Chemoprevention is the use of drugs or natural substances to inhibit initiation and delay of the progression of tumorigenesis, which could be a promising approach to reduce the incidence, mortality, and morbidity of CRC. Delta-tocotrienol (𝛿TE) is a natural analogue of vitamin E which has been shown to have antioxidant, anti-inflammatory and anticancer activities. Although its anticancer effects have been studied in different models of CRCs, including carcinogen-induced models, carcinogen-induced colitis-associated models, and colon cancer xenograft models, it has not been tested in a genetic model of sporadic CRC harboring <em>Apc</em> and <em>Kras</em> mutations. Therefore, in Chapter 3, the antitumor effects of 𝛿TE-rich tocotrienols (𝛿TE/gTE) and the potential mechanisms were investigated in AKC mice. 𝛿TE/𝛾TE-supplementation significantly improved the survival of AKC mice and suppressed tumorigenesis in association with inhibition of cell proliferation in the tumors. Further, the anti-tumor effects were correlated with reduction of pro-inflammatory and pro-tumorigenic cytokines, such as interleukin-1b and granulocyte-macrophage colony stimulating factor (GM-CSF), transcriptional enrichment of pathways involved in fatty acid metabolism, and reduction of diacylglycerol (DG) level in the colon tissue.</p> <p>Finally, AKC mice were used for screening the efficacies of other potential chemoprevention candidates, including aspirin, sulindac, and resveratrol in Chapter 4. Aspirin and sulindac are nonsteroidal anti-inflammatory drugs (NSAIDs) and they are among the most studied chemoprevention agents for CRC. However, the long-term regular use of NSAIDs may cause bleedings in the gastrointestinal organ system or hemorrhagic stroke. For aspirin, although extensive studies have shown its beneficial role in the prevention of primary CRC, there are mixed results for its benefit and harms, which may require further identification of populations who will benefit from the regular use of aspirin for prevention of CRC. Resveratrol is a naturally derived polyphenol, which is known for its antioxidant, anti-inflammatory, and antimicrobial activities with generally good safety profile. In our study, when the dietary supplementation of three compounds alone or in combination with 𝛿TE/gTE were examined for its antineoplastic effects in the AKC mice, only aspirin significantly suppressed tumorigenesis with decreased pro-inflammatory and pro-tumorigenic cytokines in the colon without overt toxicity. We found that sulindac induced serious gastric lesions and potential liver toxicity with some animals died earlier than the rest over the study period. Additionally, in this model, resveratrol was not effective in reducing tumorigenesis, in contrast to a previous study where the workgroup used similar genetic model of CRC but different modality to induce the mutations. Our findings add lines of evidence that depending on the use of different models the test compounds, aspirin, sulindac, and resveratrol may exhibit varying cancer prevention effects. Further research is warranted to identify underlying mechanisms that could explain the heterogenous responses to the test compounds and to optimize the interventions. </p>

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide, accounting for over 600,000 deaths annually. The mortality rate of CRC can be significantly reduced if it is detected early, suggesting the importance of cancer screening in CRC management. Currently, colonoscopy is the gold standard for CRC diagnosis as it is accurate and reliable. However, it is an invasive procedure that is associated with risks of complications, which contributes to the lack of patient compliance in colonoscopy screening. Other noninvasive detection methods suffer from poor sensitivity and specificity. Thus, there remains a great demand for the development of a noninvasive and accurate test for CRC diagnosis. Recently, studies using next-generation sequencing techniques have revealed compositional changes in the intestinal microbiome associated with CRC, implicating the possibility of using fecal microbiome as potential diagnostic markers. Specifically, the level of the gram-negative bacterium, Fusobacterium nucleatum, has been shown to be elevated in CRC patients compared to healthy controls. The work described in this thesis aims to develop unique RNA-cleaving DNAzymes that can distinguish between healthy and CRC stool microbiomes. RNA-cleaving DNAzymes are single stranded DNA molecules that are extensively used as analytical tools for metal ion sensing and bacterial detection. We conducted an in vitro selection experiment and isolated a F. nucleatum-responsive RNA-cleaving DNAzyme sensor, named RFD-FN1, that is activated by a heat stable protein marker by this bacterium. RFD-FN1 is highly specific for F. nucleatum and it has a limit of detection of 107 CFU/mL without culture and a single cell when cultured for 36 hours. The discovery of this novel molecular probe for F. nucleatum presents an important step forward towards the development of a novel DNAzyme-based detection method for colorectal cancer. / Thesis / Master of Science (MSc)

Background and Purpose: Colorectal cancer (CRC) is the third most common cancer, the second leading cause of cancer death, with lower survival rates at later stages. Adherence to CRC screening can prevent the development of cancerous polyps and reduce incidence. Area-level characteristics, such as access to healthcare and deprivation, can create barriers to timely screening, increasing the risk of developing CRC. The degree to which area-level characteristics versus individual-level characteristics are responsible for CRC outcomes, including incidence and stage at diagnosis, are not well-understood. Specifically, deficits in the use of spatial statistical techniques has led to a lack of clarity in the current literature. This study aimed to overcome these deficiencies by identifying and utilizing the optimal measurement for area-level access to healthcare and deprivation, employing robust spatiotemporal and multilevel analytic methods to assess their effects on CRC incidence and late-stage diagnosis in Pennsylvania (PA) at the block group-level from 2008 to 2017. The results of this research will more accurately map areas of high predicted CRC relative risk for targeted public health interventions to reduce the burden of CRC over time. The following three study aims were used to address the research problem: Aim 1: Identify the best predictive measure of access to healthcare for estimating CRC incidence risk at the block group-level in PA from 2008 to 2017. Q1: What is the best measure of access to care for estimating risk of CRC incidence? H1.1: The most comprehensive measurement, Multi-Modal 2SFCA, is optimal for predicting CRC incidence compared to unidimensional distance, availability, and other 2SFCA measures. H1.2: Weighting access to healthcare measures for individual insurance coverage improves predictive performance of CRC incidence. Aim 2: Ascertain the relative risk from area-level deprivation on CRC incidence at the block group-level in PA from 2008 to 2017.Q2: How does area-level deprivation affect CRC incidence? H2.1: WQS will demonstrate the relative importance of an extensive array of SES variables for CRC incidence. H2.2: Higher deprivation will be positively associated with risk of CRC incidence. Aim 3: Determine the individual-level likelihood of being diagnosed with late-stage CRC based on place of residence across PA from 2008 to 2017.Q3: How does place of residence affect the likelihood of developing late-stage CRC incidence after adjusting for individual-level characteristics and covariates? H3.1: PA residents living in areas of worse deprivation and low access to care have a higher likelihood of being diagnosed with late-stage CRC. H3.2: The likelihood of late-stage CRC varies significantly by individual characteristics. Methods: This research used ecologic and cross-sectional study designs to perform secondary data analysis of the cancer registry and publicly available data. The geographic units were block groups in PA (N = 9,740), accessed from the US Census Bureau. The sample included screening age-eligible PA residents, 45-75 years, diagnosed with a primary incident case of CRC from 2008 to 2017 (N=34,250), identified via the PA Cancer Registry. Out-of-state residents at diagnosis and high-risk individuals were excluded. Nine block groups were uninhabitable with no population and thus excluded. Primary exposure variables (i.e., area-level access to healthcare and deprivation) were calculated using the PA Cancer Registry, a provider database, the US Census Bureau’s polygon and network shapefiles, and American Community Survey. Ecologic covariates (see below) were derived from the American Community Survey, the Behavioral Risk Factor Surveillance System, and the USDA’s Rural-Urban Commuting Areas. The PA Cancer Registry provided individual data for patient demographics, tumor characteristics, and insurance coverage. Exploratory spatial, temporal, and spatiotemporal analyses of the CRC data were performed before Aims 1 to 3. Aim 1: CRC cases were aggregated by block group to represent a count of CRC incidence. Area-level access to healthcare measures was calculated using providers’ addresses, population-weighted block group centroids, and road/rail networks (i.e., driving, walking, and public transit). Measures included great-circle distance, driving distance to the nearest provider by miles/time, physician-to-population ratio, enhanced two-step floating catchment area (2SFCA), variable 2SFCA, and multi-modal 2SFCA. Four 15-minute catchment sizes were tested (range = 15-60-minutes). A weighted version of each 2SFCA measure for insurance coverage was calculated. Predictive performance was assessed with model fit statistics from 29 hierarchical Bayesian spatiotemporal Poisson regression models. All models included CRC screening adherence, rurality, age, race, education level, unemployment, and poverty level. Aim 2: CRC cases were aggregated by block group to represent a count of CRC incidence. Area-level deprivation indicators (n=39) were calculated from the American Community Survey’s five-year pooled estimates for demographic, social, economic, and housing characteristics and represented at the census tract or block group-level. Weighted Quantile Sum regression generated an area-level deprivation index, weighting each indicator by its relative relationship with CRC incidence. A hierarchical Bayesian spatiotemporal Poisson regression with conditional autoregressive priors and a first-order autoregressive time series process was used to estimate the relative risk of CRC. The ecologic covariates included in the model were area-level access to healthcare from Aim 1, CRC screening adherence, rurality, age, and sex. Aim 3: Three binary outcome variables represented localized vs. regional, distant, and regional and distant CRC at diagnosis. Aim 1 and 2’s area-level access to healthcare and deprivation measurements were used for this study’s primary exposure variables. The data was split into three time periods (2008-2009, 2010-2013, and 2014-2017) to analyze CRCS coverage mandates from the Affordable Care Act for private insurers in 2010 and Medicare in 2014. Using binomial distributed outcomes, three two-level generalized linear mixed models using hierarchical Bayesian methods with conditional autoregressive priors were run for each time period. Results: There were 34,250 eligible incident cases with 0-6 cases per block group (N=9,731) each year and an average of 3.5 cases per block group for the pooled study period. From 2008 to 2017, the pooled CRC incidence rate was 7.45 cases per 1,000 for 45 to 75 year olds in PA. Scan statistics found the highest CRC burden was in Philadelphia (northeast, west, and south), Pittsburgh, and rural areas in southwest PA (e.g., Westmoreland County and Fayette County) and northcentral PA (e.g., Lycoming County, Clinton County, and Centre County). In PA, yearly crude CRC rates decreased slightly over the ten years (0.80 to 0.72, Δ =-.08), though not empirically tested. Aim 1: The best fitting model used the Multi-Modal 2SFCA, which included aggregated physician-to-population ratios within 45-minutes from the provider facility for population-weighted block group centroids via driving, walking, and public transit of the same distance. Access was generally worst in rural areas and best in urban/suburban areas. Block groups with access one standard deviation above the state median had 27% decreased CRC risk. Weighting for insurance coverage improved a measure’s predictive ability for shorter travel times (i.e., 15-minutes and 30-minutes). Aim 2: Of a 39 indicator deprivation index, nine were statistically significant and three were related to SES (i.e., median household income, the percent of the block group without a high school degree, or living in a house without heating). However, the most important significant indicators belonged to geography and income domains, collectively representing 71% of the relative influence of the index. The area-level deprivation index was significant and positively associated with CRC incidence at the block group-level in PA from 2008 to 2017 (RR: 1.33, 95% CI: 1.32–1.34). Aim 3: After accounting for individual age, race, and insurance coverage, the relationship between area-level access to healthcare and deprivation and late-stage CRC became non-significant. While no area-level effects were significant, several individual-level features had consistent significant findings across outcomes and time periods. At the individual-level, having government insurance and being uninsured had significant positive relationships for all outomes and time periods. Age, and race had significant inverse relationships with late-stage CRC diagnosis. Conclusions: In summary, this study addressed the limitations of previous research by employing innovative measurement techniques, such as the Multi-Modal 2SFCA and Weighted Quantile Sum regression, and rigorous spatiotemporal methods to assess the impact of area-level access to healthcare and deprivation on CRC incidence and late-stage diagnosis. The findings highlight the importance of considering walking and public transit access to healthcare in relation to CRC incidence. Additionally, the study demonstrated the effectiveness of the WQS method in calculating an accurate area-level deprivation index, which enhanced the prediction of CRC incidence and identified high-risk areas for targeted interventions. However, individual-level characteristics, particularly insurance coverage, were found to be more influential in predicting the stage at which CRC was diagnosed than area-level effects. Regardless, using inferences and similar methods from this dissertation improves disease mapping and resource allocation for CRCS outreach, supports evidence for policy, and helps guide the development of tailored public health interventions to ultimately reduce the burden of CRC. / Epidemiology

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24804号 / 医博第4996号 / 新制||医||1067(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 武藤 学, 教授 藤田 恭之, 教授 川口 義弥 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Indiana University-Purdue University Indianapolis (IUPUI) / The occurrence of colorectal cancer among those over the age of 50 is decreasing; conversely, the rate of diagnosis for those under 50 years old is increasing. While medical researchers scramble to identify the cause for this increase, young onset colorectal cancer (YOCC) patients and survivors are left to navigate a new normal. This new normal often includes awkward and troublesome concerns such as scarring, colostomy bags, and bowel problems. Contrary to those diagnosed with colorectal cancer later in life, those that are diagnosed at a younger age are forced to deal with these issues for many years. The purpose of this exploratory study was to identify privacy issues surrounding YOCC. Because of the significant increase in diagnoses, YOCC is now being researched independently from colorectal cancer in general. The topic of privacy has been researched in academic disciplines, including medicine. Privacy issues surrounding cancer have been researched, as well. Yet, the topic of privacy concerns facing YOCC patients/survivors has been overlooked. It is important to identify privacy concerns specific to YOCC patients/survivors as the information could help health care providers, communication scholars, and caregivers. Patient narratives were analyzed employing thematic analysis to identify privacy concerns of YOCC patients/survivors through the lens of Communication Privacy Management theory (CPM theory). Results indicated that participants discussed disclosure of their YOCC journey as a process. Within this disclosure process, YOCC patients/survivors identified specific privacy issues that influenced the way they disclosed or concealed information specific to their illness. There is a growing need for more research into the YOCC community due to the increase in diagnosis rates and their unique privacy concerns. Potential topics for future research include the impact of COVID-19, patient desire to help others, social media influence on disclosure, how patient disclosure could impact provider training, dating with YOCC, and specific demographic research.

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京都大学 / 新制・課程博士 / 博士(医学) / 甲第23758号 / 医博第4804号 / 新制||医||1056(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 今中 雄一, 教授 川上 浩司, 教授 小濱 和貴 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(医学) / 甲第23799号 / 医博第4845号 / 新制||医||1058(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 妹尾 浩, 教授 中川 一路, 教授 伊藤 貴浩 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM