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.
尽管头颈部鳞状细胞癌的发病率有所下降，其仍是全球范围内严峻的健康问题。缺乏精准的早期诊断生物标志物以及晚期诊断的延迟，是导致患者生存率低下的显著制约因素，也凸显了对创新诊断方法的迫切需求。本研究结合机器学习、加权基因共表达网络分析及网络生物学方法，系统探究了血小板的基因表达模式，以识别用于头颈部鳞状细胞癌诊断的转录组学标志物。通过对公开基因表达数据集的综合分析，我们发现了九个在头颈部鳞状细胞癌患者样本中表达显著上调的基因。利用TCGA和GTEx数据集对这些潜在诊断标志物进行进一步评估，结果显示其在区分头颈部鳞状细胞癌与非癌样本方面具有高度准确性。研究结果表明，这些基因特征可能为头颈部鳞状细胞癌的早期识别带来革命性突破。此外，本研究强调了肿瘤教化血小板的重要性——这类血小板携带反映肿瘤来源物质的RNA特征，为早期检测生物标志物提供了非侵入性来源。尽管使用的血小板与肿瘤样本来自不同个体，但我们的研究结果提示肿瘤教化血小板能够反映肿瘤的转录组学和表观遗传学特征。未来研究应致力于对同一患者的肿瘤与血小板样本进行直接关联分析，以进一步阐明两者之间的关系。本研究揭示了这些生物标志物在革新头颈部鳞状细胞癌早期诊断与个体化治疗策略方面的潜力，并倡导开展进一步研究以验证其预测价值与治疗潜力。
肿瘤(癌症)患者之家