As a multifunctional cytokine, LIF has a complex role in tumorigenesis. While LIF inhibits leukemia, recent studies including ours show that LIF promotes the development and progression of many types of solid tumors, including breast cancer. LIF is frequently overexpressed in breast cancers (~50-60%) across different subtypes, and is enriched in breast cancers in women younger than 45, which tend to be more aggressive with less treatment options. LIF overexpression is associated with poor prognosis. However, the precise role of LIF in breast cancer is not well-established and its underlying mechanism is poorly understood. Metabolic reprogramming is a hallmark of cancer cells and a key contributor to cancer progression, including breast cancer. Enhanced glycolysis and enhanced lipid synthesis are two key metabolic changes in cancer, including breast cancer, which are critical for cancer progression. Our preliminary studies using an unbiased approach (liquid chromatography/mass spectrometry-based metabolite analysis) identified LIF as a novel and unique driver for metabolic reprogramming in breast cancer. We found that: 1) LIF activates glycolysis and lipid synthesis in breast cancer cells in vitro and in vivo; 2) blocking glycolysis and lipid synthesis by RNAi and specific pharmacological inhibitors largely abolished the promoting effect of LIF on breast tumorigenesis. Based on our preliminary results, we hypothesize that LIF plays a critical role in breast tumorigenesis, and enhanced glycolysis and lipid synthesis is a critical underlying mechanism, which can be targeted for therapy. To test this hypothesis, we proposed a rigorous research plan with robust and unbiased methods. We will 1) establish LIF's role in breast tumorigenesis by using 3 mouse models, including LIF transgenic and knockout mouse models; 2) determine whether metabolic reprograming driven by LIF, is a critical mechanism whereby LIF promotes breast tumorigenesis; 3) assess the therapeutic potential of targeting these metabolic changes in breast cancer with LIF overexpression. The goal of this study is to determine the role and mechanism of LIF in breast cancer and metabolic reprogramming to provide effective therapeutic targets/strategies for breast cancer. If successful, this study will: 1) provide evidence that LIF promotes breast tumorigenesis; 2) uncover LIF as an important and unique driver for metabolic reprogramming in breast cancer; 3) reveal mechanisms for LIF in breast tumorigenesis and metabolic reprogramming; 4) provide the rationale and strategies to target specific metabolic changes in breast cancers with LIF overexpression.

Public Health Relevance

Projective Narrative This proposal aims to understand the role and mechanism of LIF in breast cancer and cancer metabolism. We will test the hypothesis that LIF plays a critical role in promoting breast tumorigenesis through metabolic reprogramming, which can be targeted for therapy. We expect that results from this study will reveal the role of LIF in breast tumorigenesis and its underlying mechanism, and importantly, provide the rationale and strategies to target specific metabolic changes, especially enhanced glycolysis and lipid synthesis, in breast cancers with LIF overexpression.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA227912-02
Application #
9654722
Study Section
Tumor Cell Biology Study Section (TCB)
Program Officer
Willis, Kristine Amalee
Project Start
2018-03-01
Project End
2023-02-28
Budget Start
2019-03-01
Budget End
2020-02-29
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Rbhs -Cancer Institute of New Jersey
Department
Type
Overall Medical
DUNS #
078728091
City
New Brunswick
State
NJ
Country
United States
Zip Code
08901
Liu, Juan; Zhang, Cen; Hu, Wenwei et al. (2018) Parkinson's disease-associated protein Parkin: an unusual player in cancer. Cancer Commun (Lond) 38:40
Zhao, Yuhan; Wu, Lihua; Yue, Xuetian et al. (2018) A polymorphism in the tumor suppressor p53 affects aging and longevity in mouse models. Elife 7: