# High resolution spatial transcriptomics and machine learning to identify mechanisms responsible for the immunosuppressive tumor microenvironment in HIV+ lung cancer patients (Immuno/Microenvironment)

> **NIH NIH P30** · VIRGINIA COMMONWEALTH UNIVERSITY · 2024 · $249,999

## Abstract

Project Summary
After accounting for potential confounders such as age, sex, and smoking, HIV has been identified as an independent risk
factor for lung cancer. Lung cancer (adenocarcinoma) emerging as the primary cause of cancer-related deaths in
individuals with HIV. HIV+ individuals diagnosed with lung cancer typically exhibit limited survival and disease-free survival,
and poor quality of life with additional clinical complications associated with chem/radio therapies. Therefore, research
endeavors to discover mechanisms responsible for worse prognosis of lung cancer in HIV+ individuals, will significantly
impact patient lives. A common belief is that HIV patients have damage specifically to immune cells in the
microenvironments. Within the TME from HIV+ tumors, there is a comparable level of infiltration of lymphocytes and
tumor-associated macrophages (TAMs) compared to non-HIV tumors. A comprehensive examination of data reveals
distinctive features of a modified tumor microenvironment (TME) in HIV-positive lung cancer patients, exhibiting
compromised anti-tumor responses. We aim to identify the cellular, transcriptomic, and mechanistic changes in tumor
microenvironment (TME) cells of the HIV+ lung cancer (LC) affected individuals. We have collected unique set of non-HIV
and HIV+ LC samples from patients and their normal lung tissue samples. These samples are distributed for males and
females, less than 60 and more than 60 years of age, and matched for comorbidities, which helps us understand
mechanistic differences in the transcriptome of TME cells in relation with HIV+ and non-HIV status. Our lab published a
seminal article with Nature, which demonstrated that competitive and non-cell autonomous interactions between the
cancer cells and the various cell types in the TME is a key process which defines oncogenic fate during early and late stages
of cancer, including the metastatic probabilities. Our high impact demonstrates the role of competitive and non-cell
autonomous interactions on cellular fate of tumor microenvironment cells in lung cancer. And there is evidence of
competitive interactions and Flower Win and Lose system is found in the TME of LC samples. We propose key role of non-
cell autonomous and competitive interactions in the formation of non-responsive and immunosuppressive TME in HIV+
LC patients. Our aims are to perform ultra-high resolution spatial transcriptomics on non-HIV and HIV+ lung cancer samples
with age <60 and >60 years. And to use ultra-high resolution spatial transcriptomics to decipher competitive and non-cell
autonomous mechanisms which regulate the fate of the tumor microenvironment and cancer cells in HIV+ lung cancer
samples.

## Key facts

- **NIH application ID:** 11048045
- **Project number:** 3P30CA016059-42S4
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** Robert A. Winn
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $249,999
- **Award type:** 3
- **Project period:** 1995-12-01 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11048045

## Citation

> US National Institutes of Health, RePORTER application 11048045, High resolution spatial transcriptomics and machine learning to identify mechanisms responsible for the immunosuppressive tumor microenvironment in HIV+ lung cancer patients (Immuno/Microenvironment) (3P30CA016059-42S4). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11048045. Licensed CC0.

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