ArticleWorld journal of clinical cases2025
Rethinking p16, p53, and HPV in HNCSCC through lessons from glioblastoma subclonal evolution toward patient-centric N-of-1 single-cell RNA sequencing paradigm.
Article in World journal of clinical cases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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 (
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