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Early detection and treatment of breast cancer by random peptide array in neuN transgenic mouse model

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Breast cancer is the most common cancer and currently the second leading cause of death among women in the United States. Patients’ five-year relative survival rate decreases from 99% to

Breast cancer is the most common cancer and currently the second leading cause of death among women in the United States. Patients’ five-year relative survival rate decreases from 99% to 25% when breast cancer is diagnosed late. Immune checkpoint blockage has shown to be a promising therapy to improve patients’ outcome in many other cancers. However, due to the lack of early diagnosis, the treatment is normally given in the later stages. An early diagnosis system for breast cancer could potentially revolutionize current treatment strategies, improve patients’ outcomes and even eradicate the disease. The current breast cancer diagnostic methods cannot meet this demand. A simple, effective, noninvasive and inexpensive early diagnostic technology is needed. Immunosignature technology leverages the power of the immune system to find cancer early. Antibodies targeting tumor antigens in the blood are probed on a high-throughput random peptide array and generate a specific binding pattern called the immunosignature.

In this dissertation, I propose a scenario for using immunosignature technology to detect breast cancer early and to implement an early treatment strategy by using the PD-L1 immune checkpoint inhibitor. I develop a methodology to describe the early diagnosis and treatment of breast cancer in a FVB/N neuN breast cancer mouse model. By comparing FVB/N neuN transgenic mice and age-matched wild type controls, I have found and validated specific immunosignatures at multiple time points before tumors are palpable. Immunosignatures change along with tumor development. Using a late-stage immunosignature to predict early samples, or vice versa, cannot achieve high prediction performance. By using the immunosignature of early breast cancer, I show that at the time of diagnosis, early treatment with the checkpoint blockade, anti-PD-L1, inhibits tumor growth in FVB/N neuN transgenic mouse model. The mRNA analysis of the PD-L1 level in mice mammary glands suggests that it is more effective to have treatment early.

Novel discoveries are changing understanding of breast cancer and improving strategies in clinical treatment. Researchers and healthcare professionals are actively working in the early diagnosis and early treatment fields. This dissertation provides a step along the road for better diagnosis and treatment of breast cancer.

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  • 2015

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Cancer autoantibody biomarker discovery and validation using nucleic acid programmable protein array

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Currently in the US, many patients with cancer do not benefit from the population-based screening, due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the

Currently in the US, many patients with cancer do not benefit from the population-based screening, due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the potential to detect diseases in a non-invasive way. Proteins released from small early tumors may only be present intermittently and get diluted to tiny concentrations in the blood, making them difficult to use as biomarkers. However, they can induce autoantibody (AAb) responses, which can amplify the signal and persist in the blood even if the antigen is gone. Circulating autoantibodies is a promising class of molecules that have potential to serve as early detection biomarkers for cancers. This Ph.D thesis aims to screen for autoantibody biomarkers for the early detection of two deadly cancer, basal-like breast cancer and lung adenocarcinoma. First, a method was developed to display proteins in both native and denatured conformation on protein array. This method adopted a novel protein tag technology, called HaloTag, to covalently immobilize proteins on glass slide surface. The covalent attachment allowed these proteins to endure harsh treatment without getting dissociated from slide surface, which enabled the profiling of antibody responses against both conformational and linear epitopes. Next, a plasma screening protocol was optimized to significantly increase signal to noise ratio of protein array based AAb detection. Following this, the AAb responses in basal-like breast cancer were explored using nucleic acid programmable protein arrays (NAPPA) containing 10,000 full-length human proteins in 45 cases and 45 controls. After verification in a large sample set (145 basal-like breast cancer cases / 145 controls / 70 non-basal breast cancer) by ELISA, a 13-AAb classifier was developed to differentiate patients from controls with a sensitivity of 33% at 98% specificity. Similar approach was also applied to the lung cancer study to identify AAbs that distinguished lung cancer patients from computed-tomography positive benign pulmonary nodules (137 lung cancer cases, 127 smoker controls, 170 benign controls). In this study, two panels of AAbs were discovered that showed promising sensitivity and specificity. Six out of eight AAb targets were also found to have elevated mRNA level in lung adenocarcinoma patients using TCGA data. These projects as a whole provide novel insights on the association between AAbs and cancer, as well as general B cell antigenicity against self-proteins.

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  • 2015

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From plasma peptide to phenotype: the emerging role of quiescin sulfhydryl oxidase 1 in tumor cell biology

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Cancer is a disease that affects millions of people worldwide each year. The metastatic progression of cancer is the number one reason for cancer related deaths. Cancer preventions rely on

Cancer is a disease that affects millions of people worldwide each year. The metastatic progression of cancer is the number one reason for cancer related deaths. Cancer preventions rely on the early identification of tumor cells as well as a detailed understanding of cancer as a whole. Identifying proteins specific to tumor cells provide an opportunity to develop noninvasive clinical tests and further our understanding of tumor biology. Using liquid chromatography-mass spectrometry (LC-MS/MS) a short peptide was identified in pancreatic cancer patient plasma that was not found in normal samples, and mapped back to QSOX1 protein. Immunohistochemistry was performed probing for QSOX1 in tumor tissue and discovered that QSOX1 is highly over-expressed in pancreatic and breast tumors. QSOX1 is a FAD-dependent sulfhydryl oxidase that is extremely efficient at forming disulfide bonds in nascent proteins. While the enzymology of QSOX1 has been well studied, the tumor biology of QSOX1 has not been studied. To begin to determine the advantage that QSOX1 over-expression provides to tumors, short hairpin RNA (shRNA) were used to reduce the expression of QSOX1 in human tumor cell lines. Following the loss of QSOX1 growth rate, apoptosis, cell cycle and invasive potential were compared between tumor cells transduced with shQSOX1 and control tumor cells. Knock-down of QSOX1 protein suppressed tumor cell growth but had no effect on apoptosis and cell cycle regulation. However, shQSOX1 dramatically inhibited the abilities of both pancreatic and breast tumor cells to invade through Matrigel in a modified Boyden chamber assay. Mechanistically, shQSOX1-transduced tumor cells secreted MMP-2 and -9 that were less active than MMP-2 and -9 from control cells. Taken together, these results suggest that the mechanism of QSOX1-mediated tumor cell invasion is through the post-translational activation of MMPs. This dissertation represents the first in depth study of the role that QSOX1 plays in tumor cell biology.

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  • 2012