尽管头颈鳞状细胞癌的发病率有所下降，但它仍然是一个严重的全球健康问题。缺乏精确的早期诊断生物标志物和后期诊断的推迟是导致生存率低下的显着限制，并强调需要创新的诊断方法。在这项研究中，我们采用机器学习、加权基因共表达网络分析 (WGCNA) 和网络生物学来研究血小板的基因表达模式，识别用于 HNSCC 诊断的转录组标记。我们对公开的基因表达数据集进行全面检查，发现在诊断为 HNSCC 的个体样本中，有 9 个基因的表达显着升高。使用 TCGA 和 GTEx 数据集进一步评估这些潜在的诊断标记物，证明区分 HNSCC 和非癌样本的准确性很高。研究结果表明，这些基因特征可能会彻底改变早期 HNSCC 的识别。此外，该研究还强调了肿瘤诱导血小板（TEP）的重要性，TEP 携带指示肿瘤来源物质的 RNA 特征，为早期检测生物标志物提供了非侵入性来源。尽管使用来自不同个体的血小板和肿瘤样本，我们的结果表明 TEP 反映了肿瘤的转录组和表观遗传景观。未来的研究应该旨在直接关联来自同一患者的肿瘤和血小板样本，以进一步阐明这种关系。这项研究强调了这些生物标志物在改变 HNSCC 早期诊断和个性化治疗策略方面的潜力，提倡进一步研究以验证其预测和治疗潜力。

Although there has been a reduction in head and neck squamous cell carcinoma occurrence, it continues to be a serious global health concern. The lack of precise early diagnostic biomarkers and postponed diagnosis in the later stages are notable constraints that contribute to poor survival rates and emphasize the need for innovative diagnostic methods. In this study, we employed machine learning alongside weighted gene co-expression network analysis (WGCNA) and network biology to investigate the gene expression patterns of blood platelets, identifying transcriptomic markers for HNSCC diagnosis. Our comprehensive examination of publicly available gene expression datasets revealed nine genes with significantly elevated expression in samples from individuals diagnosed with HNSCC. These potential diagnostic markers were further assessed using TCGA and GTEx datasets, demonstrating high accuracy in distinguishing between HNSCC and non-cancerous samples. The findings indicate that these gene signatures could revolutionize early HNSCC identification. Additionally, the study highlights the significance of tumor-educated platelets (TEPs), which carry RNA signatures indicative of tumor-derived material, offering a non-invasive source for early-detection biomarkers. Despite using platelet and tumor samples from different individuals, our results suggest that TEPs reflect the transcriptomic and epigenetic landscape of tumors. Future research should aim to directly correlate tumor and platelet samples from the same patients to further elucidate this relationship. This study underscores the potential of these biomarkers in transforming early diagnosis and personalized treatment strategies for HNSCC, advocating for further research to validate their predictive and therapeutic potential.