Development of Biologically Based Therapies for Basal-like Breast Tumors

There have been many experiments on breast cancer cell lines and tumors with respect to identifying genes/pathways that are involved in cancer initiation, progression and response to therapy; however, only a few actually make suggestions that might affect treatment. The knowledge that breast cancer actually represents several diseases that arise from at least two different epithelial cells has been a major stepping-stone for stratifying patients and identifying more selective and biology-based therapies. Drugs aimed at the estrogen receptor, estrogen production, and HER2 have been very successful in the many patients whose tumors are dependent upon these signaling pathways for growth. Unfortunately for tumors that lack these markers, such as basal-like subtype, there are few treatment options. Until recently, few studies had actually considered if there were subtype-specific differences in response to chemotherapy. This dissertation focuses on the basal-like subtype of cancer and examines responses to chemotherapeutics relative to the luminal subtypes and evaluates the EGFR pathway as a place for potential therapeutic intervention. In response to two chemotherapeutics - doxorubicin and 5-fluorouracil - a general stress response was the dominant profile and this profile varied both in vitro and in vivo between the subtypes. The drug-specific response was more similar in the subtypes. A predictive gene list was identified that could predict both subtype and drug treatment with fairly high accuracy suggesting some degree of subtype-specific mechanism of action. The different responses to doxorubicin and 5-fluorouracil led us to evaluate sensitivity to a larger panel of drugs and cell lines and we determined that the basal-like subtype was more sensitive to carboplatin. While identification of chemotherapy regimens that are beneficial to the basal-like subtype is needed, drugs targeted to specific deregulated pathways in this subtype will be more effective in the long run. My work evaluated the EGFR pathway and determined it is high in 90% of all basal-like tumors, but I also identified high expression of genes downstream of EGFR that can induce EGFR-independent activation of this pathway. My data suggest that inhibition of MEK or PI3K, along with chemotherapeutics, may be an effective regimen for basal-like patients

Lessons from Controversy: Interpreting the Sand Creek Massacre in Colorado

This thesis is a case study of the 2012 History Colorado Center exhibit, Collision: The Sand Creek Massacre, 1860s – Today. Collision was an exhibit that attempted to showcase the history of the Sand Creek Massacre – an 1864 event where well over one hundred peaceful Cheyenne and Arapaho people were murdered by the 3rd Regiment of the Colorado Military District. Collision remained open for a little more than a year – this thesis interrogates the reasons behind its closure and its status as a controversial museum exhibit. The findings of this thesis show that a lack of collaboration with the Descendant Communities of the Cheyenne and Arapaho was only one of many problems at work. At the time of the exhibit, History Colorado prioritized the generation of revenue and “sustainability” over providing staff and stakeholders with a timeline conducive to the collaborative process. Additionally, Collision was developed utilizing an “audience first” methodology in order to attract visitors to the museum; History Colorado did not consider their stakeholders as an influential audience. The closure of the exhibit was ultimately facilitated by Tribal Representatives via Denver weekly paper, Westword. Journalist Patricia Calhoun’s articles exposed History Colorado’s lack of collaboration with the Tribes and in turn, public pressure demanded the closure of the exhibit. This thesis examines what can be learned from controversy, the importance of multi-vocality in exhibit development, and the decolonizing work that must be done from within museums

Joint and individual variation explained (JIVE) for integrated analysis of multiple data types

Research in several fields now requires the analysis of data sets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such data sets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data and provides new directions for the visual exploration of joint and individual structures. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types. Data and software are available at https://genome.unc.edu/jive/Comment: Published in at http://dx.doi.org/10.1214/12-AOAS597 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Identification of mRNA isoform switching in breast cancer

Abstract Background Alternative splicing provides a major mechanism to generate protein diversity. Increasing evidence suggests a link of dysregulation of splicing associated with cancer. While previous genomic-based studies demonstrated the expression of a handful of tumor-specific isoforms, genome-wide alterations in the balance between isoforms and cancer subtypes is understudied. Result We systematically analyzed the isoform-level expression patterns and isoform switching events of 819 breast tumor and normal samples assayed by mRNA-seq from TCGA project. On average, 2.2 isoforms per gene were detected and 67.5 % of detected genes (i.e. expressed) showed 1–2 isoforms only. While the majority of isoforms for a given gene were positively correlated with each other and the overall gene level, 470 pairs of isoforms displayed an inverse correlation suggesting a switching event. Most of the isoform switching events were associated with molecular subtypes, including a Basal-like-associated switching in CTNND1. 88 genes showed switching independent of subtypes, among which the isoform pattern of PRICKLE1 was associated with a large genomic signature of biological significance. Conclusion Our results reveal that the majority of genes do not undergo complex mRNA splicing within breast cancers, and that there is a general concordance in isoform and gene expression levels in breast tumors. We identified hundreds of isoform switching events across breast tumors, most of which were associated with differences in tumor subtypes. As exemplified by the detailed analysis of CTNND1 and PRICKLE1, these isoform switching events potentially provide new insights into the post-transcriptional regulatory mechanisms of tumor subtypes and cancer biology

Potential Tumor Suppressor Role for the c-Myb Oncogene in Luminal Breast Cancer

The transcription factor c-Myb has been well characterized as an oncogene in several human tumor types, and its expression in the hematopoietic stem/progenitor cell population is essential for proper hematopoiesis. However, the role of c-Myb in mammopoeisis and breast tumorigenesis is poorly understood, despite its high expression in the majority of breast cancer cases (60-80%).We find that c-Myb high expression in human breast tumors correlates with the luminal/ER+ phenotype and a good prognosis. Stable RNAi knock-down of endogenous c-Myb in the MCF7 luminal breast tumor cell line increased tumorigenesis both in vitro and in vivo, suggesting a possible tumor suppressor role in luminal breast cancer. We created a mammary-derived c-Myb expression signature, comprised of both direct and indirect c-Myb target genes, and found it to be highly correlated with a published mature luminal mammary cell signature and least correlated with a mammary stem/progenitor lineage gene signature.These data describe, for the first time, a possible tumor suppressor role for the c-Myb proto-oncogene in breast cancer that has implications for the understanding of luminal tumorigenesis and for guiding treatment

Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

Genomic Analysis of Immune Cell Infiltrates Across 11 Tumor Types

Background: Immune infiltration of the tumor microenvironment has been associated with improved survival for some patients with solid tumors. The precise makeup and prognostic relevance of immune infiltrates across a broad spectrum of tumors remain unclear