What question did this study set out to answer?

This study aims to identify early epigenomic alterations that predict the risk of cSCC in patients with HS.

April 5, 2026Cancer Research0 citations

Abstract 4211: AI-driven epigenomic profiling reveals early predictors of cutaneous squamous cell carcinoma risk in hidradenitis suppurativa

MKMurali R. KurachaNational Academy of Sciences SKSree Naga V. KurachaBoys Town AVAaren VedangiNaval Science & Technological Laboratory

Key Points

This study aims to identify early epigenomic alterations that predict the risk of cSCC in patients with HS.
Profiled genome-wide DNA methylation in blood samples from HS patients and matched controls.
Identified differentially methylated CpGs using a bioinformatics pipeline.
Employed AI techniques including deep learning and survival modeling to assess cSCC risk.
Established a continuous cSCC Epigenetic Prognostic Score (cSCC-EPS) to categorize risk levels.
Identified significant methylation alterations at 32 CpG sites linked to cSCC risk.
Developed a Cox model with a C-index of 0.78-0.84, indicating strong prognostic capability.
Detected key CpGs associated with high-risk cSCC in the HS population.
Demonstrated that methylation profiling can stratify HS patients into varying risk categories.

Abstract

Abstract Background: Hidradenitis Suppurativa (HS) is a chronic inflammatory skin disease with a markedly increased risk of cutaneous squamous cell carcinoma (cSCC), including aggressive and often fatal variants. Although cSCC arises through ultraviolet injury, chronic inflammation, impaired wound repair, and smoking, its molecular drivers remain incompletely defined. Emerging evidence implicates epigenetic dysregulation, particularly DNA methylation, as an early indicator of carcinogenic potential. Our HS cohort contained no cSCC cases at recruitment, providing a unique opportunity to identify early epigenomic alterations preceding malignant transformation. Methods: Genome-wide DNA methylation was profiled in blood from 24 HS cases and matched controls using the Illumina MethylationEPIC array. Differentially methylated CpGs were identified through a rigorous bioinformatic pipeline and cross-referenced with cSCC datasets to define overlap with oncogenic pathways. Artificial intelligence approaches, including deep learning, Cox elastic-net survival modeling, random forest, and integrated AI/ML pipelines, were used to prioritize CpGs associated with cSCC risk. Results: We identified significant methylation alterations (FDR ≤ 0.05) at 32 CpG sites across 32 genes in HS, comprising 24 hypomethylated and 8 hypermethylated loci. All are previously implicated in cSCC and converge on canonical oncogenic pathways, including EGFR/MAPK, p53, TERT, NOTCH signaling, and DNA repair/chromatin remodeling. The cSCC tumor-trained Cox proportional hazards model (Cox model) demonstrated strong prognostic performance (C-index 0.78-0.84 across cross-validation). Applying this model to HS samples generated a continuous cSCC Epigenetic Prognostic Score (cSCC-EPS) that stratified HS patients into low-, intermediate-, and high-risk methylation phenotypes. SHapley Additive exPlanations (SHAP) analyses highlighted CpGs within EGFR, DNMT1, TP53, NOTCH3, BRAF, and TERT as the strongest contributors to cSCC predicted risk. This integrative AI-ML epigenetic pipeline identified HS patients with methylation profiles converging on high-risk cSCC tumor biology, suggesting a blood-based molecular window into early carcinogenic processes. Conclusions: HS patients harbor blood-based methylation signatures that mirror early epigenomic alterations seen in cSCC. This AI-integrated framework provides the first evidence that these biomarkers can predict malignant transformation in HS, positioning methylation profiling as a promising tool for early cSCC risk assessment. Citation Format: Murali R. Kuracha, Sree Naga V. Kuracha, Aaren Vedangi, Radhakrishna Uppala, Lavanya Uppala, Venkata Duvvuri. AI-driven epigenomic profiling reveals early predictors of cutaneous squamous cell carcinoma risk in hidradenitis suppurativa abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4211.

Ask AI

Helpful

Bookmark

View Full Paper