Background:Breast cancer (BC) comprises multiple subtypes with distinct molecular features, which differ in their interplay with host immunity, prognosis, and treatment. Non-invasive blood analyses can provide valuable insights into systemic immunity during cancer. The aim of this study was to analyze the expression of transcriptional isoforms in peripheral blood mononuclear cells (PBMCs) from BC patients and healthy women to identify potential BC immune biomarkers.Methods:RNA sequencing and isoform-level bioinformatics were performed on PBMCs from 12 triple-negative and 13 luminal A patients. Isoform expression validation by qRT-PCR and clinicopathological correlations were performed in a larger cohort (156 BC patients and 32 healthy women).Results:Transcriptional analyses showed a significant (p< 0.001) decrease in theENST00000374459 RASGEF1Aisoform in PBMCs of BC compared to healthy subjects, indicating disease-related expression changes. The decrease was associated with higher ctDNA and Ki-67 values.Conclusions:The levels of theRASGEF1Atranscriptional isoformENST00000374459may have the potential to distinguish between BC and healthy subjects. The downregulation ofENST00000374459in breast cancer is associated with higher proliferation and ctDNA shedding. Specialized bioinformatics analyses such as isoform analyses hold significant promise in the detection of biomarkers, since standard RNA sequencing analyses may overlook specific transcriptional changes that may be disease-associated and biologically important.
背景：乳腺癌包含多种具有不同分子特征的亚型，这些亚型在与宿主免疫系统的相互作用、预后及治疗方面存在差异。非侵入性血液分析可为癌症期间的系统性免疫状态提供重要信息。本研究旨在分析乳腺癌患者与健康女性外周血单个核细胞中转录亚型的表达情况，以识别潜在的乳腺癌免疫生物标志物。 方法：对12例三阴性乳腺癌和13例Luminal A型乳腺癌患者的外周血单个核细胞进行RNA测序及亚型水平生物信息学分析。通过qRT-PCR在更大规模队列（156例乳腺癌患者和32例健康女性）中验证亚型表达，并进行临床病理学相关性分析。 结果：转录分析显示，与健康受试者相比，乳腺癌患者外周血单个核细胞中ENST00000374459 RASGEF1A亚型的表达显著降低（p<0.001），表明该变化与疾病相关。该表达下调与较高的循环肿瘤DNA和Ki-67值相关。 结论：RASGEF1A转录亚型ENST00000374459的表达水平可能具备区分乳腺癌患者与健康受试者的潜力。该亚型在乳腺癌中的下调与更高的增殖活性和循环肿瘤DNA释放相关。由于标准RNA测序分析可能忽略与疾病相关且具有重要生物学意义的特定转录变化，因此如亚型分析这类专业生物信息学分析在生物标志物检测领域具有显著应用前景。
肿瘤(癌症)患者之家