{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/130792"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/130792","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"Novel Immunometabolic Therapies and Prognostic Markers for Lymphedema","abstract":"Lymphedema is a chronic, disabling health condition affecting over 40 million people globally. There are limited treatments for lymphedema and none are effective for the late stages of the disease. Fibrosis is a key pathology contributing to the chronic irreversibility of this clinical entity. New therapeutics are needed to target lymphedema fibrosis, and improved prognostic models are required to reliably predict who will develop chronic, severe lymphedema to appropriately triage and monitor patients for timely diagnosis and treatment. It is unknown if: (1) gene expression changes in tissue are associated with the development of fibrosis in lymphedema, (2) stimulating a non-fibrotic gene expression profile using drug therapy can reduce fibrosis in lymphedema tissues, and (3) biomarkers can reliably predict the occurrence and severity of lymphedema. Temporal RNA-sequencing of murine lymphedema tissues identified that increased interleukin 17 (IL-17) signaling and decreased peroxisome proliferator-activated receptor (PPAR) signaling occurred early in lymphedema and were sustained chronically. These gene expression changes co-occurred with fibrosis, which began to develop as early as two weeks after lymphedema development and continued until at least 35 weeks after the initiation of lymphedema. Using both mechanism of action- and pharmacogenomics-based approaches, drugs candidates were identified to target IL-17 and/or PPAR gene expression, and reduced lymphedema fibrosis in cellular and animal models. Additionally, in a prognostic biomarker study of 373 breast cancer patients with and without lymphedema, a novel prognostic model based on metabolic and inflammatory risk factors (e.g. breast fat density, BMI, age) was able to predict the occurrence and severity of lymphedema. Together, this research offers important novel insights into risk model development and therapeutic approaches for lymphedema.","abstract_html":"Lymphedema is a chronic, disabling health condition affecting over 40 million people globally. There are limited treatments for lymphedema and none are effective for the late stages of the disease. Fibrosis is a key pathology contributing to the chronic irreversibility of this clinical entity. New therapeutics are needed to target lymphedema fibrosis, and improved prognostic models are required to reliably predict who will develop chronic, severe lymphedema to appropriately triage and monitor patients for timely diagnosis and treatment. It is unknown if: (1) gene expression changes in tissue are associated with the development of fibrosis in lymphedema, (2) stimulating a non-fibrotic gene expression profile using drug therapy can reduce fibrosis in lymphedema tissues, and (3) biomarkers can reliably predict the occurrence and severity of lymphedema. Temporal RNA-sequencing of murine lymphedema tissues identified that increased interleukin 17 (IL-17) signaling and decreased peroxisome proliferator-activated receptor (PPAR) signaling occurred early in lymphedema and were sustained chronically. These gene expression changes co-occurred with fibrosis, which began to develop as early as two weeks after lymphedema development and continued until at least 35 weeks after the initiation of lymphedema. Using both mechanism of action- and pharmacogenomics-based approaches, drugs candidates were identified to target IL-17 and/or PPAR gene expression, and reduced lymphedema fibrosis in cellular and animal models. Additionally, in a prognostic biomarker study of 373 breast cancer patients with and without lymphedema, a novel prognostic model based on metabolic and inflammatory risk factors (e.g. breast fat density, BMI, age) was able to predict the occurrence and severity of lymphedema. Together, this research offers important novel insights into risk model development and therapeutic approaches for lymphedema.","abstract_has_math":false,"creators":["Kwan, Jennifer Yin Yee"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Medical Science","school":null,"contributors":[],"advisors":["Liu, Fei-Fei"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-11","date_published":"2021-11","updated_at":"2026-07-27T21:28:13Z","subjects":["Fibrosis","Inflammation","Lymphedema","Metabolism"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/130792","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Liu, Fei-Fei"]},{"key":"dc:contributor.department","label":"Department","values":["Medical Science"]},{"key":"dc:creator","label":"Author","values":["Kwan, Jennifer Yin Yee"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-11"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-11-29T05:13:19Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-11-29T05:13:19Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-11"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Fibrosis","Inflammation","Lymphedema","Metabolism"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/130792"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Lymphedema is a chronic, disabling health condition affecting over 40 million people globally. There are limited treatments for lymphedema and none are effective for the late stages of the disease. Fibrosis is a key pathology contributing to the chronic irreversibility of this clinical entity. New therapeutics are needed to target lymphedema fibrosis, and improved prognostic models are required to reliably predict who will develop chronic, severe lymphedema to appropriately triage and monitor patients for timely diagnosis and treatment. It is unknown if: (1) gene expression changes in tissue are associated with the development of fibrosis in lymphedema, (2) stimulating a non-fibrotic gene expression profile using drug therapy can reduce fibrosis in lymphedema tissues, and (3) biomarkers can reliably predict the occurrence and severity of lymphedema. Temporal RNA-sequencing of murine lymphedema tissues identified that increased interleukin 17 (IL-17) signaling and decreased peroxisome proliferator-activated receptor (PPAR) signaling occurred early in lymphedema and were sustained chronically. These gene expression changes co-occurred with fibrosis, which began to develop as early as two weeks after lymphedema development and continued until at least 35 weeks after the initiation of lymphedema. Using both mechanism of action- and pharmacogenomics-based approaches, drugs candidates were identified to target IL-17 and/or PPAR gene expression, and reduced lymphedema fibrosis in cellular and animal models. Additionally, in a prognostic biomarker study of 373 breast cancer patients with and without lymphedema, a novel prognostic model based on metabolic and inflammatory risk factors (e.g. breast fat density, BMI, age) was able to predict the occurrence and severity of lymphedema. Together, this research offers important novel insights into risk model development and therapeutic approaches for lymphedema."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Novel Immunometabolic Therapies and Prognostic Markers for Lymphedema"]}]}],"canonical_facts":{"dc:contributor.advisor":["Liu, Fei-Fei"],"dc:contributor.department":["Medical Science"],"dc:creator":["Kwan, Jennifer Yin Yee"],"dc:date":["2021-11"],"dc:date.accessioned":["2023-11-29T05:13:19Z"],"dc:date.available":["2023-11-29T05:13:19Z"],"dc:date.issued":["2021-11"],"dc:description.abstract":["Lymphedema is a chronic, disabling health condition affecting over 40 million people globally. There are limited treatments for lymphedema and none are effective for the late stages of the disease. Fibrosis is a key pathology contributing to the chronic irreversibility of this clinical entity. New therapeutics are needed to target lymphedema fibrosis, and improved prognostic models are required to reliably predict who will develop chronic, severe lymphedema to appropriately triage and monitor patients for timely diagnosis and treatment. It is unknown if: (1) gene expression changes in tissue are associated with the development of fibrosis in lymphedema, (2) stimulating a non-fibrotic gene expression profile using drug therapy can reduce fibrosis in lymphedema tissues, and (3) biomarkers can reliably predict the occurrence and severity of lymphedema. Temporal RNA-sequencing of murine lymphedema tissues identified that increased interleukin 17 (IL-17) signaling and decreased peroxisome proliferator-activated receptor (PPAR) signaling occurred early in lymphedema and were sustained chronically. These gene expression changes co-occurred with fibrosis, which began to develop as early as two weeks after lymphedema development and continued until at least 35 weeks after the initiation of lymphedema. Using both mechanism of action- and pharmacogenomics-based approaches, drugs candidates were identified to target IL-17 and/or PPAR gene expression, and reduced lymphedema fibrosis in cellular and animal models. Additionally, in a prognostic biomarker study of 373 breast cancer patients with and without lymphedema, a novel prognostic model based on metabolic and inflammatory risk factors (e.g. breast fat density, BMI, age) was able to predict the occurrence and severity of lymphedema. Together, this research offers important novel insights into risk model development and therapeutic approaches for lymphedema."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1807/130792"],"dc:subject":["Fibrosis","Inflammation","Lymphedema","Metabolism"],"dc:title":["Novel Immunometabolic Therapies and Prognostic Markers for Lymphedema"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:13Z"}