Cao Wei, Jin Dacheng, Min Weirun, Li Haochi, Wang Rong, Zhang Jinlong, Gou Yunjiu
First Clinical Medical School, Gansu University of Chinese Medicine, Lanzhou, China.
Chest Clinic Center, Gansu Provincial People's Hospital, Lanzhou, China.
BMC Cancer. 2025 Jan 20;25(1):105. doi: 10.1186/s12885-025-13483-8.
Esophageal cancer is a grave malignant condition. While radiotherapy, often in conjunction with chemotherapy, serves as a cornerstone in the management of locally advanced or metastatic cases, patient tolerance and treatment resistance frequently hinder its efficacy. Cell-in-cell structures, prevalent in various tumors, have been linked to prognosis. Hence, investigating the prognostic significance and regulatory mechanisms of genes related to these intracellular structures in esophageal cancer is imperative. The Cancer Genome Atlas (TCGA) Esophageal Cancer (ESCA) dataset served as the training set for the analysis. Differentially expressed genes (DEGs) in ESCA samples were identified, with those related to intercellular structures designated cell-in-cell-related differential expression genes (CIC-related DEGs). Cox regression analysis was employed to identify prognostic genes, categorizing samples into high- and low-risk groups based on median risk scores. Validation was conducted using the GSE53624 risk model. Established methodologies included morphological mapping, enrichment analysis, immune infiltration analysis, prognostic gene expression validation, molecular docking, and Reverse Transcription Polymerase Chain Reaction (RT-PCR) validation. Thirty-eight intersecting genes were identified between the disease and normal groups in ESCA samples. Stepwise multivariate Cox analysis pinpointed three prognostic genes: androgen receptor (AR), C-X-C motif chemokine ligand 8 (CXCL8), and epidermal growth factor receptor (EGFR). The risk model's applicability was confirmed in the GSE53624 dataset, revealing eight significantly different immune-related gene sets. Prognostic gene expression validation demonstrated significant differences between the disease and normal groups in both datasets. The proteins corresponding to the three prognostic genes interacted with gefitinib and osimertinib. RT-PCR results corroborated the differential expression of prognostic genes in esophageal cancer tissues. This study identified AR, CXCL8, and EGFR as prognostic genes and demonstrated their molecular interactions with gefitinib and osimertinib, providing a foundation for ESCA diagnosis and treatment.
食管癌是一种严重的恶性疾病。放疗通常与化疗联合使用，是局部晚期或转移性病例治疗的基石，但患者耐受性和治疗抵抗性常常阻碍其疗效。细胞内细胞结构在各种肿瘤中普遍存在，与预后相关。因此，研究食管癌中与这些细胞内结构相关基因的预后意义和调控机制至关重要。癌症基因组图谱（TCGA）食管癌（ESCA）数据集用作分析的训练集。鉴定了ESCA样本中的差异表达基因（DEG），将与细胞间结构相关的基因指定为细胞内细胞相关差异表达基因（CIC相关DEG）。采用Cox回归分析确定预后基因，根据中位风险评分将样本分为高风险组和低风险组。使用GSE53624风险模型进行验证。既定方法包括形态学映射、富集分析、免疫浸润分析、预后基因表达验证、分子对接和逆转录聚合酶链反应（RT-PCR）验证。在ESCA样本的疾病组和正常组之间鉴定出38个交叉基因。逐步多变量Cox分析确定了三个预后基因：雄激素受体（AR）、C-X-C基序趋化因子配体8（CXCL8）和表皮生长因子受体（EGFR）。风险模型在GSE53624数据集中的适用性得到证实，揭示了八个显著不同的免疫相关基因集。预后基因表达验证表明，两个数据集中疾病组和正常组之间存在显著差异。与三个预后基因相对应的蛋白质与吉非替尼和奥希替尼相互作用。RT-PCR结果证实了食管癌组织中预后基因的差异表达。本研究确定AR、CXCL8和EGFR为预后基因，并证明了它们与吉非替尼和奥希替尼的分子相互作用，为ESCA的诊断和治疗提供了基础。
