# Early detection and risk of head and neck cancer through immune based spatial omics

> **NIH NIH U01** · YALE UNIVERSITY · 2023 · $705,328

## Abstract

ABSTRACT
Head and neck squamous cell carcinoma (HNSCC) is the seventh most common cancer worldwide. In the oral
cavity, most cases of squamous cell carcinoma begin as a precursor lesion classified by the World Health
Organization (WHO) as an “oral potentially malignant disorder (OPMD).” Oral leukoplakia is the most common
OPMD, with a global prevalence of 4.1% and a malignant transformation rate between 0.1%-34.0%, and the
malignant transformation rate increases to 40% in oral dysplasia. These wide ranges of malignant
transformation rates suggest an unmet need to develop prognostic biomarkers that can better differentiate
benign from premalignant lesions and predict the risk of transformation of premalignant lesions to invasive
cancer. During the development of cancer, immunoediting occurs within the tumor microenvironment.
Immunoediting consists of three phases: elimination, equilibrium, and escape. We posit that there are defined
immune signatures within a lesional microenvironment that correlate with the transformation of precancerous
cells to invasive cancer based on the known phases of immunoediting. The current standard of care tools to
establish benign from premalignant oral lesions include conventional hematoxylin/eosin (HE) and single
staining immunohistochemistry (IHC), which limits the number of immune cells which can be evaluated at any
one time. Thus, we developed an innovative spatial omics technology (SAFE) that facilitates the
comprehensive and deep multiplexing of whole tissue sections and incorporates artificial intelligence and
machine learning approaches to accelerate the analysis of ~45 molecular and immune signatures within oral
lesions in a clinically appropriate timeframe. We propose to perform single-cell RNA sequencing to identify the
unique cellular and immunological transcriptional programs that distinguish benign and premalignant oral
lesions (N=60) and will assess relevant protein expression and spatial localization via SAFE (Aim 1).
Subsequently, in Aim 2, we will evaluate the defining molecular and/or immunological signature(s) in a unique
set of patients (N=55) with serial biopsies documenting transformation from premalignancy to cancer over 20
years against a separate cohort of benign and premalignant lesions (N=155). From our dataset, we will
develop an oral cancer progression model that incorporates the host immune response for the first time to
improve risk assessment for malignant progression to a degree superior to what is currently possible.

## Key facts

- **NIH application ID:** 11032405
- **Project number:** 7U01DE033324-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Sara Isabel Pai
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $705,328
- **Award type:** 7
- **Project period:** 2024-03-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11032405

## Citation

> US National Institutes of Health, RePORTER application 11032405, Early detection and risk of head and neck cancer through immune based spatial omics (7U01DE033324-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11032405. Licensed CC0.

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