2025 Sequencing Strategies for Population and Cancer Epidemiology Studies (SeqSPACE) : Submission #5
Submission information
Submission Number: 5
Submission ID: 150827
Submission UUID: 36d82ad8-9925-4f12-a96d-309ad32b96e0
Submission URI: /egrp/seqspaceabstracts
Submission Update: /egrp/seqspaceabstracts?token=zXnYSXlyg8mVhFPdOwZZkQeY6n5a_FFvRzOe7516sFM
Created: Wed, 09/03/2025 - 15:21
Completed: Wed, 09/03/2025 - 15:21
Changed: Wed, 09/03/2025 - 15:21
Remote IP address: 10.208.24.230
Submitted by: Anonymous
Language: English
Is draft: No
Webform: seqspace (Abstracts)
Presenter Information
Monica
A.
Wagner
Ph.D
Assistant Professor (Tenure Track)
Case Western Reserve University
Abstract Information
Transcriptomic Profiling of Socioeconomic Stratification in Oropharyngeal Squamous Cell Carcinoma
Socioeconomic disadvantage is increasingly recognized as a contributor to differences in cancer outcomes, yet its biological mechanisms remain poorly understood. To explore the molecular impact of social context, we performed bulk RNA sequencing on whole blood samples from individuals diagnosed with oropharyngeal squamous cell carcinoma, collected either prior to radiation or more than one-year post-treatment. Participants were stratified by Area Deprivation Index (ADI), a validated measure of neighborhood-level socioeconomic disadvantage ranging from 1 to 100, with higher scores indicating greater disadvantage.
Using the DESeq2 pipeline, we modeled differential gene expression between individuals with high ADI (80-100; n=12) and low ADI (1-40; n=11). Genes were considered significant using a raw p-value threshold of < 0.05, chosen to enhance sensitivity in this exploratory, hypothesis-generating analysis. While adjusted p-values are standard for controlling false discovery rates, our use of unadjusted p-values reflects the preliminary nature of the dataset and supports future validation efforts.
This approach revealed distinct gene expression profiles between ADI-high and ADI-low individuals, with notable differences in genes involved in oxidative stress (GPX1), immune regulation (PF4, TGFB1I1), and cellular signaling (FSTL1, TREML1). These findings suggest that individuals from socioeconomically disadvantaged neighborhoods may exhibit systemic biological alterations that influence disease progression, immune response, and treatment outcomes,
Peripheral blood offers a practical biospecimen for capturing circulating immune and inflammatory signals, providing insight into the systemic effects of social determinants of health. This study demonstrates the feasibility of integrating ADI into RNA-seq workflows to uncover biologically meaningful differences in cancer populations and highlights a scalable approach for investigating the intersection of social context and molecular biology in head and neck cancer.
Using the DESeq2 pipeline, we modeled differential gene expression between individuals with high ADI (80-100; n=12) and low ADI (1-40; n=11). Genes were considered significant using a raw p-value threshold of < 0.05, chosen to enhance sensitivity in this exploratory, hypothesis-generating analysis. While adjusted p-values are standard for controlling false discovery rates, our use of unadjusted p-values reflects the preliminary nature of the dataset and supports future validation efforts.
This approach revealed distinct gene expression profiles between ADI-high and ADI-low individuals, with notable differences in genes involved in oxidative stress (GPX1), immune regulation (PF4, TGFB1I1), and cellular signaling (FSTL1, TREML1). These findings suggest that individuals from socioeconomically disadvantaged neighborhoods may exhibit systemic biological alterations that influence disease progression, immune response, and treatment outcomes,
Peripheral blood offers a practical biospecimen for capturing circulating immune and inflammatory signals, providing insight into the systemic effects of social determinants of health. This study demonstrates the feasibility of integrating ADI into RNA-seq workflows to uncover biologically meaningful differences in cancer populations and highlights a scalable approach for investigating the intersection of social context and molecular biology in head and neck cancer.