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Open Access | Just Accepted

A Novel Approach for Detection of Genes Related to Oral Squamous Cell Carcinoma

Yu Guan1,Haoran Peng1,Caiyun Yang1Jianqiang Li1Xi Xu1Jinli Zhang1Linna Zhao1( )Weiliang Qiu2

1 College of Computer Science, Beijing University of Technology, Beijing 100124, China

2 Non-clinical Efficacy and Safety, Sanofi, Cambridge, MA, USA

These authors contributed equally to this paper

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Abstract

Oral squamous cell carcinoma (OSCC) has the highest incidence among all the oral neoplasms, thus widely affects people’s life. Genetics has an important effect on the OSCC’s etiopathogenesis. However, OSCC’s molecular mechanism has not been completed investigated yet. We proposed a novel method to detect genes that are associated to OSCC, where mean difference and variance difference were compared between cases and controls. This method can discover knowledge from gene data by processing multi-format information and has managed to identify disease-associated genes for many complex human diseases, like melanoma, head and neck squamous cell carcinoma (HNSCC), lung adenocarcinoma, and serous ovarian cancer. Based on Gene Expression Omnibus, two OSCC datasets were derived and gene probes were then identified, typed as differentially variable (DV) and differentially expressed (DE), with number 456 and 2,375, respectively. Those probes can be further discriminated as DE-only, DV-only and then DE-and-DV probes, with number 2,193, 274 and 182, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were adopted to distinctly enrich genes that relevant to these three kinds of specific probes, as per the DAVID functional analysis, implying they have diverse works in OSCC. In the future, our novel method also could be applied to investigate other complex human diseases’ genetic risk factors.

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Tsinghua Science and Technology

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Cite this article:
Guan Y, Peng H, Yang C, et al. A Novel Approach for Detection of Genes Related to Oral Squamous Cell Carcinoma. Tsinghua Science and Technology, 2026, https://doi.org/10.26599/TST.2026.9010021

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Received: 10 March 2023
Revised: 17 October 2024
Accepted: 04 February 2026
Available online: 08 April 2026

© The author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).