# Systems biology modeling of radiation resistance and chemotherapy-radiation combination therapies in head and neck squamous cell carcinoma

> **NIH NIH F30** · EMORY UNIVERSITY · 2020 · $45,585

## Abstract

Tumor resistance to radiation therapy remains a significant obstacle to long-term cancer patient survival,
especially for head and neck squamous cell carcinoma (HNSCC), a cancer type with poor long-term outcomes
(less than 50% advanced stage five-year survival). To overcome the problem of radiation resistance, radiation
therapy is being combined with radiation-sensitizing chemotherapies. Prediction of an individual’s sensitivity to
radiation and specific chemotherapy-radiation combination therapies prior to treatment would improve the
development of personalized treatment plans for cancer patients. Efforts are being made to create systems
biology models of cancer cells for biomarker discovery and prediction of treatment response; however, due to
methodological shortcomings, failure to integrate multi-omic data on a genome-scale, and lack of specificity to
individual patient tumors, these predictive models have yet to be implemented clinically. To address these needs,
the objective of this project is to develop a personalized systems biology modeling platform for individualized
prediction of HNSCC patient tumor response to radiation and chemotherapy-radiation combination therapies.
These models will be created by first integrating comprehensive biological data on individual patients from The
Cancer Genome Atlas (TCGA). This approach will allow for the comparison of metabolic, signaling, and
phenotypic signatures between radiation-sensitive and radiation-resistant patient tumors. By then integrating the
mechanisms of action of radiation therapy and radiation-sensitizing chemotherapies into the modeling
framework, the response to particular chemotherapy-radiation combination therapies in individual radiation-
resistant patient tumors can be predicted. Machine learning classifiers will be developed from TCGA patient data
and model predictions to determine which biological and clinical factors are most predictive of radiation sensitivity
and chemotherapy-radiation combination therapy success. It is hypothesized that differential response to
chemotherapy-radiation combination therapies in radiation-resistant HNSCC tumors is accomplished
through redox metabolism and signaling, and components of redox biology within the modeling
framework will significantly enrich the list of predictive biomarkers for combination therapy success.
Although the focus of this project will be on HNSCC, this systems biology modeling approach will be applicable
to any cancer type. The outcomes of this project will be a reduced set of clinically-measurable biomarkers for
accurate prediction of HNSCC patient response to radiation therapy and specific chemotherapy-radiation
combination therapies, as well as a precision medicine platform to test clinically relevant therapeutic strategies.
This project is innovative because it combines multi-omic cancer patient data with state-of-the-art systems
biology modeling techniques to investigate the biological mechanisms of radiation resis...

## Key facts

- **NIH application ID:** 10380480
- **Project number:** 7F30CA224968-04
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Joshua Elliott Lewis
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $45,585
- **Award type:** 7
- **Project period:** 2018-05-14 → 2021-05-13

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10380480

## Citation

> US National Institutes of Health, RePORTER application 10380480, Systems biology modeling of radiation resistance and chemotherapy-radiation combination therapies in head and neck squamous cell carcinoma (7F30CA224968-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10380480. Licensed CC0.

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