# Metabolic Influences on Complex Tumor Neighborhoods

> **NIH NIH R35** · UNIVERSITY OF PENNSYLVANIA · 2024 · $921,582

## Abstract

Project Summary
Renal cell carcinoma is among the ten most prevalent malignances in the United States, exhibiting an
increased incidence in both men and women since 2001. The most common kidney cancer subtype is “clear
cell” renal cell carcinoma (ccRCC), which accounts for ~75% of all cases. For early-stage disease, surgical
resection of ccRCCs can be curative, although survival drops significantly for advanced, metastatic cancers.
Multiple therapies are now available to ccRCC patients, including anti-angiogenic VEGF/receptor tyrosine
kinase inhibitors, immune checkpoint blockade, mTORC1-based drugs, and a novel HIF-2a inhibitor.
However, not all patients respond to these treatments and five-year relapse rates now approach 40%, and the
majority of these cases develop metastases. Importantly, ccRCCs lack common oncogenic mutations
observed in other human cancers, including PI3K, PTEN, TP53, and KRAS, which hinders successful
treatment using corresponding targeted therapies. Instead, we have generated copy number variation,
transcriptomic, and metabolomic data to identify multiple metabolic pathways that are universally altered in
ccRCC tumors. These include loss of the gluconeogenic enzyme fructose-1,6-bisphosphate 1 (FBP1) and
urea cycle enzymes, including argininosuccinate synthetase 1 (ASS1), argininosuccinate lyase (ASL), and
arginase 2 (ARG2). Finally, ccRCCs exhibit unusually high numbers of lipid droplets, organelles which store
triglycerides and cholesterol esters and a hallmark of this disease. By delineating the molecular consequences
of these universal metabolic changes, we have developed new therapeutic strategies to target most patients
diagnosed with this kidney cancer subtype. Moreover, our findings have been extended to other cancers such
as hepatocellular carcinoma (HCC) and soft tissue sarcoma (STS) which appear to engage in highly similar
metabolic reprogramming. Our data demonstrate that “senolytics” like ABT-263 could be deployed for the
treatment of HCC, whereas ITX-5061, an inhibitor of the HDL cholesterol transporter SCARB1, may be
effective for treating ccRCC. The results are paradigm-shifting in that understandable skepticism remains
regarding the utility of “drugging” cancer metabolism, considering the metabolic heterogeneity, plasticity, and
redundancy observed in various cancers. However, our results using autochthonous in vivo tumor models
provide a rationale for deeper exploration. Ongoing and future work will investigate how consistent metabolic
adaptations within the tumor parenchyma impact stromal components, such as fibroblasts and immune cells,
based on an arsenal of complementary in vitro and in vivo models, that include novel autochthonous HCC and
STS mouse models and ccRCC and HCC patient derived xenografts and organoids. A principal conceptual
innovation of our recent work is the demonstration that multiple metabolic networks are consistently altered
(~100%) in genetically diverse cancers like ccRCC, HCC, an...

## Key facts

- **NIH application ID:** 10931721
- **Project number:** 5R35CA220483-09
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** M. CELESTE SIMON
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $921,582
- **Award type:** 5
- **Project period:** 2017-08-01 → 2030-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10931721

## Citation

> US National Institutes of Health, RePORTER application 10931721, Metabolic Influences on Complex Tumor Neighborhoods (5R35CA220483-09). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10931721. Licensed CC0.

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