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Description
Cancer is a problem of multicellularity, making it a problem across all species. This pervasiveness has led to much research into the defense and the pathology of the disease. Previously, studies have been limited in sample size, taxonomic breadth, and comparative methods to explain and understand the data available. Here,

Cancer is a problem of multicellularity, making it a problem across all species. This pervasiveness has led to much research into the defense and the pathology of the disease. Previously, studies have been limited in sample size, taxonomic breadth, and comparative methods to explain and understand the data available. Here, we have access to life history and cancer risk data of 17,563 individuals for 327 species, spanning across three monophyletic clades: Amphibians, Sauropsids, and Mammals. Comparative biology’s approach to cross-species cancer prevalence is crucial to the identification of species that are uniquely resistant to cancer as well as stratifying risk across a phylogeny based on the life history framework. Using the life history framework, alongside a multitude of life history data, was able to find that neoplasia prevalence increases with adult weight and longevity, but decreases with gestation time. It was also discovered that malignancy prevalence decreases with gestation time. Gestation and adult weight are also both significant predictors of neoplasia and malignancy prevalence when controlling for the other. On an evolutionary scale, cancer risk appears to be best described by sudden shifts in cancer prevalence followed by stabilizing selection of that trait. The understanding of increases and decreases of cancer risk across species could create better insight on human’s own cancer risk, as well as disease prevention in humans.
ContributorsMellon, Walker (Author) / Maley, Carlo (Thesis director) / Compton, Zachary (Committee member) / Mallo, Diego (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Economics (Contributor)
Created2022-12
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Description
Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an

Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an adaptive error model

into statistical decomposition of mixed populations, which corrects the mean-variance

dependency of sequencing data at the subclonal level and enables accurate subclonal

discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer

simulations and real-world data, this new method, named model-based adaptive grouping

of subclones (MAGOS), consistently outperforms existing methods on minimum

sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports

subclone analysis using single nucleotide variants and copy number variants from one or

more samples of an individual tumor. GUST algorithm, on the other hand is a novel method

in detecting the cancer type specific driver genes. Combination of MAGOS and GUST

results can provide insights into cancer progression. Applications of MAGOS and GUST

to whole-exome sequencing data of 33 different cancer types’ samples discovered a

significant association between subclonal diversity and their drivers and patient overall

survival.
ContributorsAhmadinejad, Navid (Author) / Liu, Li (Thesis advisor) / Maley, Carlo (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide and exhibits a male-bias in occurrence and mortality. Previous studies have provided insight into the role of inherited genetic regulation of transcription in modulating sex-differences in HCC etiology and mortality. This study uses pathway analysis to add insight

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide and exhibits a male-bias in occurrence and mortality. Previous studies have provided insight into the role of inherited genetic regulation of transcription in modulating sex-differences in HCC etiology and mortality. This study uses pathway analysis to add insight into the biological processes that drive sex-differences in HCC etiology as well as a provide additional framework for future studies on sex-biased cancers. Gene expression data from normal, tumor adjacent, and HCC liver tissue were used to calculate pathway scores using a tool called PathOlogist that not only takes into consideration the molecules in a biological pathway, but also the interaction type and directionality of the signaling pathways. Analysis of the pathway scores uncovered etiologically relevant pathways differentiating male and female HCC. In normal and tumor adjacent liver tissue, males showed higher activity of pathways related to translation factors and signaling. Females did not show higher activity of any pathways compared to males in normal and tumor adjacent liver tissue. Work suggest biologic processes that underlie sex-biases in HCC occurrence and mortality. Both males and females differed in the activation of pathways related apoptosis, cell cycle, signaling, and metabolism in HCC. These results identify clinically relevant pathways for future research and therapeutic targeting.
ContributorsRehling, Thomas E (Author) / Buetow, Kenneth (Thesis advisor) / Wilson, Melissa (Committee member) / Maley, Carlo (Committee member) / Arizona State University (Publisher)
Created2021
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Description

Evolution has driven organisms to develop a wide range of biological mechanisms to protect against cancer. Some organisms, including the sponge Tethya wilhelma and the Placozoa Trichoplax adhaerens have developed particularly effective mechanisms to suppress cancer and repair DNA damage. While these mechanisms are rooted in DNA damage repair and

Evolution has driven organisms to develop a wide range of biological mechanisms to protect against cancer. Some organisms, including the sponge Tethya wilhelma and the Placozoa Trichoplax adhaerens have developed particularly effective mechanisms to suppress cancer and repair DNA damage. While these mechanisms are rooted in DNA damage repair and prevention, evidence of bacteria may suggest that endosymbionts living within the organisms may plays a role as well. Likewise, other organisms, such as the flatworm Macrostomum lignano, are proven model organisms whose extensive documentation enables more in-depth analysis of biological mechanisms associated with cancer. Sponges, flatworms, and Placozoa were exposed to X-ray radiation totaling 600 Gy, 25 Gy, and up to 240 Gy, respectively. RNA sequencing and bioinformatics analyses were undergone to determine the differential gene expression of the animals at different time points. No common response to the X-ray radiation was discovered amongst all organisms. Instead, sponges showed evidence of tumor suppression and DNA repair gene upregulation including CUBN, bacterial endosymbionts showed evidence of lateral gene transfer and different DNA repair genes including FH, and flatworms showed evidence of allelic and mutational shifts in which tumorous populations became more reliant on alternate alleles and a single variant signature. This study highlights the varying mechanisms that have evolved in different organisms and the importance of studying these novel model organisms further.

ContributorsScirone, Jonathan (Author) / Fortunato, Angelo (Thesis director) / Maley, Carlo (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05