Supplementary Figure S4 from Development of a Clinical Assay to Guide Patient Therapy in HPV-Associated Head and Neck Cancer
Year: 2026
Type: supplementary-materials
Abstract: Supplemental Figure 4. Comprehensive comparison of all gene sets and potential summary metrics for the NF-κB signature using RNAseq from the UNC cohort. UNC Cohort originally presented in Schrank and colleagues PNAS 2023 (1). Correlation plot with scatter and Pearson correlation values. Nano str – the gene signature utilized in the nanostring assay including 232 NF-κB related genes, which are compared to 27 control genes, these genes were identified in our prior publications as outlined below and represent the combination of the PNAS and Onco large gene sets as defined below. Onco small – Top 50 NF-κB related genes identified in prior work using machine learning improved differential expression, prioritized by p-value in Schrank et at, Oncotarget 2022 (2), 49 of which are included (one excluded by probe design) in the NanoString panel. 29 of these genes are also identified as NF-κB related genes with an orthogonal approach in our prior work using WGCNA (1). Onco large – Top 75 NF-κB related genes identified in prior work using machine learning improved differential expression, prioritized by p-value in Schrank et at, Oncotarget 2022 (2), 74 of which are included (one excluded by probe design) in the NanoString panel 45 of these genes are also identified as NF-κB related genes with an orthogonal approach in our prior work using WGCNA (1). Pnas – 203 NF-κB related genes identified in our prior work using WGCNA, a network-based approach in Schrank and colleagues PNAS 2023 (3). Onco only – NF-κB genes identified by differential expression but not by WGCNA. Pnas only – NF-κB genes identified by WGCNA but not by differential expression. Mean – mean expression of signature genes. Median – median expression of signature genes. PCA – sample value of PC1, for PCA performed on signature genes only after expression normalization. ssGSEA – Signature sized normalized enrichment score (NES) calculated by the single sample gene set enrichment method.
Authors: Sri Vemulamanda, Aditi Kothari, Loris De Cecco, Sulgi Kim, Aditi Kulkarni, Pragati Upadhyay, Stefano Cavalieri, Christophe Courtine, Yasine Mirmozaffari, Jane Brown, Andrew Sewell, Yael Flamand, Yue Xie, Lili Zheng, Shanthi Marur, Trevor Hackman, Bart Singer, John Ayman Hakim, Lori Ramkissoon, Yan Li, Hina Rehmani, Xue Li, Siddharth Sheth, Xuguang Chen, Jennifer Dorth, Quintin Pan, Evan Graboyes, Bhishamjit Chera, Barbara Burtness, Robert L. Ferris, Rene Leemans, Ruud H. Brakenhoff, Frank Hoebers, Kathrin Scheckenbach, Tito Poli, Lisa Licitra, Wendell G. Yarbrough, Natalia Issaeva, Travis P. Schrank
Language: English
Topic: Head and Neck Cancer Studies
Subfield: Otorhinolaryngology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W7167062581