The Cancer Metabolism and Growth (CMG) Program has the overall goal to determine how oncogenic alterations regulate tumor cell metabolism, growth, proliferation, survival, and tumor-host interaction to facilitate disease progression. The ultimate aim is to identify new approaches to improve cancer treatment through innovative biochemical, molecular and biological research. In vivo approaches to address metabolic, physical and immunologic functions in cancer and state-of-the-art measurement of cancer metabolism are signature Program features that span the Rutgers/Princeton consortium. CMG provides the platform for productive, collaborative, and impactful science, and interfaces with the Cancer Center for the translation of that science, both bench to bedside and bedside to bench. CMG has 59 members from 26 Departments, 10 Schools, and 3 Universities. CMG research is well funded with $14.3M annual direct peer-reviewed grant support, $9.2M of which is cancer-focused (9 multi-PI), with $3M from the NCI (21 R01-equivalent/14 PIs). In the last funding period CMG members published more than 835 papers, 31% of which are collaborative (15% intra- and 22% inter-collaborative) with 21% top-tier journals and 50% collaborative with other institutions. In comparison to the last funding period, this represents an increase in both total and collaborative publications, and seven additional multi-PI grants. Impactful CMG cancer science includes the discovery that circulating lactate is a major supplier of carbon to the tricarboxylic acid (TCA) cycle in tumors, and that the folate pathway significantly contributes to NADPH production. How glutamine metabolism is critical for MYC-driven cancers, how mTOR signaling is controlled by nutrient availability, and how protein and lipid scavenging contribute to cancer growth, proliferation and survival were also discovered by CMG research. Examination of metabolic interactions between tumor and host revealed new mechanisms of metastasis, and how tumors physically interact with their local environment and the immune system. Program members discovered that metastasis represents corruption of normal developmental processes, that cell polarity and tissue/cytoskeletal tension in the tumor microenvironment alter oncogenic signaling via the Hippo and other pathways, and that nutrient scavenging, interferons and the removal of dead cells by efferocytosis alter the immune response to tumors. Translation of CMG research has led to clinical trials targeting metabolism, promoting apoptosis and activating anti-tumor immune responses. In turn, clinical observations have informed CMG research to model treatment, resistance and exceptional responders to identify underlying mechanisms and to improve therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
2P30CA072720-20
Application #
9632903
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2019-03-07
Budget End
2020-02-29
Support Year
20
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Rbhs -Cancer Institute of New Jersey
Department
Type
DUNS #
078728091
City
New Brunswick
State
NJ
Country
United States
Zip Code
08901
DeRenzo, Evan G; Moss, Joel; Singer, Eric A (2018) Implications of the Revised Common Rule for Human Participant Research. Chest :
Feng, Simin; Dai, Zhuqing; Liu, Anna B et al. (2018) Intake of stigmasterol and ?-sitosterol alters lipid metabolism and alleviates NAFLD in mice fed a high-fat western-style diet. Biochim Biophys Acta Mol Cell Biol Lipids 1863:1274-1284
Song, Mihae; Kumaran, Muthu N; Gounder, Murugesan et al. (2018) Phase I trial of selenium plus chemotherapy in gynecologic cancers. Gynecol Oncol 150:478-486
Khiabanian, Hossein; Hirshfield, Kim M; Goldfinger, Mendel et al. (2018) Inference of Germline Mutational Status and Evaluation of Loss of Heterozygosity in High-Depth, Tumor-Only Sequencing Data. JCO Precis Oncol 2018:
Rabadan, Raul; Bhanot, Gyan; Marsilio, Sonia et al. (2018) On statistical modeling of sequencing noise in high depth data to assess tumor evolution. J Stat Phys 172:143-155
Gupta, Apar; Ohri, Nisha; Haffty, Bruce G (2018) Hypofractionated whole breast irradiation is cost-effective-but is that enough to change practice? Transl Cancer Res 7:S469-S472
Ding, Qiang; Nimgaonkar, Ila; Archer, Nicholas F et al. (2018) Identification of the Intragenomic Promoter Controlling Hepatitis E Virus Subgenomic RNA Transcription. MBio 9:
Liu, Ling; Su, Xiaoyang; Quinn 3rd, William J et al. (2018) Quantitative Analysis of NAD Synthesis-Breakdown Fluxes. Cell Metab 27:1067-1080.e5
Liu, Anna B; Tao, Siyao; Lee, Mao-Jung et al. (2018) Effects of gut microbiota and time of treatment on tissue levels of green tea polyphenols in mice. Biofactors :
Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun et al. (2018) Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence. Am J Epidemiol 187:366-377

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