# Molecular determinants of lung cancer in HIV infected and uninfected individuals in Uganda and Tanzania

> **NIH NIH U54** · CASE WESTERN RESERVE UNIVERSITY · 2021 · $312,432

## Abstract

ABSTRACT – Project 2
We will assess molecular risks and co-incidence of lung cancer, HIV and accelerated aging as a factor in lung
cancer incidence and progression in HIV infected patients. We will define the somatic mutations of lung cancer,
link them to HIV subtype and explore the hypothesized role of DNA methylome aging in HIV- infected versus
uninfected individuals as an associative factor that could potentially be utilized as a future biomarker to predict
likelihood of lung cancer development or disease progression. These data will provide the first comprehensive
assessment of somatic mutation burden in East African lung cancer, which will guide access to therapeutically
effective agents to target actionable lung cancer mutations. These will be linked to risk factors associated with
HIV including immunosuppression, immune protection, and accelerated aging that may increase the risk of
cancer in HIV+ individuals. These will help to discern whether epidemiological factors from Project 1 can project
risk for lung cancer at the molecular level and whether, together, we can identify prominent factors linking
epidemiologic risk, HIV-1 infection, and lung cancer in East Africa.

## Key facts

- **NIH application ID:** 10267199
- **Project number:** 5U54CA254566-02
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** STANTON L. GERSON
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $312,432
- **Award type:** 5
- **Project period:** 2020-09-21 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10267199

## Citation

> US National Institutes of Health, RePORTER application 10267199, Molecular determinants of lung cancer in HIV infected and uninfected individuals in Uganda and Tanzania (5U54CA254566-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10267199. Licensed CC0.

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