Lee HM, Li SC. Rethinking p16, p53, and HPV in HNCSCC through lessons from glioblastoma subclonal evolution toward patient-centric N-of-1 single-cell RNA sequencing paradigm. World J Clin Cases 2025; 13(32): 104208 [DOI: 10.12998/wjcc.v13.i32.104208]
Corresponding Author of This Article
Shengwen Calvin Li, PhD, Department of Neurology, University of California-Irvine School of Medicine, 1001 Health Sciences Road, Orange, CA 92868, United States. sli@choc.org
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Oncology
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Nov 16, 2025 (publication date) through Nov 15, 2025
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World Journal of Clinical Cases
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2307-8960
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Lee HM, Li SC. Rethinking p16, p53, and HPV in HNCSCC through lessons from glioblastoma subclonal evolution toward patient-centric N-of-1 single-cell RNA sequencing paradigm. World J Clin Cases 2025; 13(32): 104208 [DOI: 10.12998/wjcc.v13.i32.104208]
World J Clin Cases. Nov 16, 2025; 13(32): 104208 Published online Nov 16, 2025. doi: 10.12998/wjcc.v13.i32.104208
Rethinking p16, p53, and HPV in HNCSCC through lessons from glioblastoma subclonal evolution toward patient-centric N-of-1 single-cell RNA sequencing paradigm
Henry Michael Lee, Shengwen Calvin Li
Henry Michael Lee, Shengwen Calvin Li, Department of Neurology, University of California-Irvine School of Medicine, Orange, CA 92868, United States
Co-first authors: Henry Michael Lee and Shengwen Calvin Li.
Author contributions: Lee HM and Li SC contribute conceptually and in writing, they contributed equally to this manuscript and are co-first authors.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Shengwen Calvin Li, PhD, Department of Neurology, University of California-Irvine School of Medicine, 1001 Health Sciences Road, Orange, CA 92868, United States. sli@choc.org
Received: December 16, 2024 Revised: August 29, 2025 Accepted: October 15, 2025 Published online: November 16, 2025 Processing time: 334 Days and 8.9 Hours
Abstract
Head and neck cutaneous squamous cell carcinoma (HNCSCC) remains underexplored compared to oropharyngeal squamous cell carcinoma, particularly in relation to human papillomavirus (HPV) and molecular markers such as p16 and p53. While p16 is a well-established surrogate for HPV in oropharyngeal cancer, our review highlights its unreliable role in HNCSCC, where positivity is instead associated with recurrence and metastasis. Similarly, p53 illustrates a dual role - wild-type as a genomic safeguard, mutated as an oncogenic driver - complicating prognostication. Methodological considerations, including the limitations of immunohistochemistry for HPV detection, underscore the need for multi-method and molecular validation in future studies. Ultraviolet radiation is posited as a key modifier of p16 function, decoupling expression from tumor suppression. To contextualize these findings, we draw parallels to glioblastoma (GBM), where subclonal evolution, p53 dysfunction, and intratumoral heterogeneity drive relapse despite aggressive multimodal therapies. GBM exemplifies how bulk-level biomarker generalizations often obscure dynamic cellular ecosystems, reinforcing the necessity of single-cell and spatial approaches. Multi-omics integration - encompassing genome, transcriptome, proteome, and tumor microenvironment mapping - coupled with single-cell RNA sequencing and spatial transcriptomics, offers a path forward for resolving subclonal dynamics in both HNCSCC and GBM. These technologies provide the resolution needed to track tumor-immune-stromal co-evolution, identify therapy-resistant clones, and anticipate recurrence. We argue for a N-of-1, patient- and cell-centric paradigm that reframes biomarkers not as static surrogates but as dynamic readouts of cancer evolution across time and tissue contexts. Conceptually, we propose kinetic and microenvironmental frameworks (e.g., “load-and-lock” barriers; dormancy and immune-synapse stabilization) as hypothesis-generating avenues to stall clonal handoffs and improve outcome prediction. Together, these perspectives argue for revised biomarker frameworks in HNCSCC and ethically inclusive, mechanism-anchored studies that bridge discovery with individualized care. By bridging insights from HNCSCC with the lessons of GBM, this review underscores the need for ethically inclusive, mechanistically informed frameworks that integrate subclonal evolution, biomarker re-interpretation, and precision-personalized hybrid models. Such an approach will be essential for advancing from one-size-fits-all strategies to individualized lifetime cancer care.
Core Tip: Nam et al’s article provides a compelling investigation into the mysterious interaction between human papillomavirus, p16, and p53 in Asian populations. This investigation is part of the investigation into the pathogenesis and prognosis of cancer. The results of this study not only contribute to our expansion of knowledge regarding head and neck cutaneous squamous cell carcinoma, but they also question our preconceived assumptions regarding biomarkers that have traditionally been associated with positive outcomes.