基于生物信息学探讨分层蛋白在肺腺癌的表达特征及预后价值

doi:10.3877/cma.j.issn.1674-6902.2026.05.010

目的

基于生物信息学方法探讨分层蛋白在肺腺癌(adenocarcinoma of the lung)中的表达特征、诊断与预后价值，分析与免疫细胞浸润相关性。

方法

采用TCGA数据库获取肺腺癌538例及癌旁正常组织58例样本的RNA-seq数据，根据HPA数据库获取分层蛋白蛋白免疫组化数据。采用Kruskal Wallis检验、配对样本t检验比较分层蛋白mRNA在肿瘤与正常组织中的差异表达；通过受试者特征工作曲线(receiver operating characteristic, ROC)判断诊断效能；利用Kaplan-Meier生存分析和COX回归分析判断预后价值；采用ssGSEA算法及Spearman相关分析判断分层蛋白表达与24种免疫细胞浸润程度的相关性。

结果

分层蛋白mRNA在肺腺癌组织中显著高表达(非配对比较P<0.001，配对比较P<0.001)，HPA免疫组化结果一致。分层蛋白表达水平与T分期(P＝0.012)、N分期(P＝0.008)、病理分期(P＝0.015)及总生存期(overall survival, OS)(P＝0.021)显著相关，与年龄、性别、种族、吸烟状况及治疗结果无显著关联(P>0.05)。ROC曲线下面积(area under the curve, AUC)为0.755，诊断能力中等。Kaplan-Meier分析显示，分层蛋白高表达组无进展生存期(progression-free survival, PFS)(P＝0.004)和OS(P＝0.009)低于低表达组。多因素COX回归显示，残余肿瘤、T分期、N分期、M分期及主要治疗结果是影响预后的危险因素(P<0.05)。免疫浸润分析显示，分层蛋白表达与NK细胞(R＝0.157，P<0.001)、未成熟树突细胞(iDC，R＝0.155，P<0.001)及Th17细胞(R＝0.135，P<0.001)呈显著正相关，与中央记忆T细胞(Tcm，R＝0.306，P<0.001)和辅助性T细胞(Th，R＝0.250，P<0.001)呈显著负相关。

结论

分层蛋白在肺腺癌中显著高表达，诊断效能良好，高表达与预后差及特定免疫细胞浸润模式相关，分层蛋白可通过免疫调控参与肺腺癌进展，有望成为肺腺癌早期诊断和个体化治疗潜在靶点。

关键词: 肺腺癌, 分层蛋白, 生物信息学, 早期诊断, 免疫细胞浸润

Objective

To systematically evaluate the expression characteristics, diagnostic and prognostic value of stratifin in lung adenocarcinoma based on bioinformatics methods, and to analyze its correlation with immune cell infiltration.

Methods

RNAseq data from 538 lung adenocarcinoma tissues and 58 adjacent normal tissues were obtained from the TCGA database, and immunohistochemical data for SFN protein were retrieved from the HPA database. The Kruskal Wallis test and paired sample ttest were used to compare the differential expression of SFN mRNA between tumour and normal tissues. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves. Prognostic value was evaluated by Kaplan-Meier survival analysis and Cox regression analysis. The ssGSEA algorithm and Spearman correlation analysis were employed to assess the correlations between SFN expression and the infiltration levels of 24 immune cell types.

Results

SFN mRNA was significantly overexpressed in lung adenocarcinoma tissues (unpaired comparison P<0.001; paired comparison P<0.001), and the immunohistochemical results from HPA were consistent. SFN expression levels were significantly associated with T stage (P=0.012), N stage (P=0.008), pathological stage (P=0.015), and overall survival (OS)(P=0.021), but not with age, sex, race, smoking status, or treatment outcome (P>0.05). The area under the ROC curve (AUC) was 0.755, indicating moderate diagnostic capability. Kaplan-Meier analysis showed that the high SFN expression group had significantly shorter progressionfree survival (PFS)(P=0.004) and OS (P=0.009) than the low expression group. Multivariate Cox regression identified residual tumour, T stage, N stage, M stage, and primary therapy outcome as independent risk factors (all P<0.05). Immune infiltration analysis revealed that SFN expression was significantly positively correlated with NK cells (R=0.157, P<0.001), immature dendritic cells (iDC, R=0.155, P<0.001), and Th17 cells (R=0.135, P<0.001), while it was significantly negatively correlated with central memory T cells (Tcm, R=0.306, P<0.001) and helper T cells (Th, R=0.250, P<0.001).

Conclusion

SFN is significantly overexpressed in lung adenocarcinoma and shows good diagnostic efficacy. Its high expression is closely associated with poor prognosis and a specific pattern of immune cell infiltration. SFN may participate in lung adenocarcinoma progression through immune regulation and holds promise as a potential target for early diagnosis and personalised treatment.

Key words: Adenocarcinoma of the lung, Stratifin, Bioinformatics, Early diagnosis, Immune cell infiltration

图1 SFN mRNA在LUAD和正常肺组织中的差异表达。图A为SFN mRNA在TCGA数据库泛癌种肿瘤组织与癌旁正常组织差异表达；图B为SFN mRNA在配对肺癌组织与癌旁正常和肺组织样本中差异表达；图C为SFN mRNA在非配对肺癌组织与癌旁正常和肺组织样本中差异表达；图D为SFN蛋白在正常肺组织样本免疫组化染色；图E为SFN蛋白在肺腺癌组织样本免疫组化染色注：SFN为SFN基因表达量；Normal为正常组织；Tumor为肿瘤组织；TPM为每百万测序片段对应的转录本数量；ACC为肾上腺皮质癌；BLCA为膀胱尿路上皮癌；BRCA为乳腺浸润癌；CESC为宫颈鳞癌与宫颈腺癌；CHOL为胆管癌；COAD为结肠腺癌；DLBC为弥漫性大B细胞淋巴瘤；ESCA为食管癌；GBM为多形性胶质母细胞瘤；HNSC为头颈部鳞状细胞癌；KICH为肾嫌色细胞癌；KIRC为肾透明细胞癌；KIRP为肾乳头状细胞癌；LAML为急性髓系白血病；LGG为低级别胶质瘤；LIHC为肝细胞肝癌；LUAD为肺腺癌；LUSC为肺鳞状细胞癌；MESO为间皮瘤；OV为卵巢浆液性囊腺癌；PAAD为胰腺腺癌；PCPG为嗜铬细胞瘤/副神经节瘤；PRAD为前列腺腺癌；READ为直肠腺癌；SARC为肉瘤；SKCM为皮肤黑色素瘤；STAD为胃腺癌；TGCT为睾丸生殖细胞肿瘤；THCA为甲状腺癌；THYM为胸腺瘤；UCEC为子宫内膜癌

图2 SFN mRNA表达在LUAD诊断和预后价值。图A为SFN mRNA诊断LUAD的ROC曲线；图B、C为使用Kaplan-Meier分析不同SFN表达水平下OS和PFS；图D为预测1年、3年和5年总体生存的预后的列线图；图E为分析1年、3年和5年总体生存(OS)风险的Nomogram校准图注：SFN Low为SFN低表达组；SFN High为SFN高表达组；HR为风险比；CI为置信区间；AUC为曲线下面积；TPR为真阳性率；FPR为假阳性率；Sensitivity (TPR)为灵敏度(真阳性率)；1-Specificity (FPR)为1-特异度(假阳性率)；Overall Survival为总体生存期；Survival probability为生存概率；Time (days)为时间(天); Points为单项分值；Residual tumor为残留肿瘤；R0为无残留；R1&R2为镜下/肉眼残留肿瘤；Total Points为总分；Linear Predictor为线性预测值；1-year Survival Probability为1年生存概率；3-year Survival Probability为3年生存概率；5-year Survival Probability为5年生存概率；Observed fraction survival probability为实际观测的生存概；Nomogram predicted survival probability为列线图预测生存概率；Ideal line为理想拟合线

表1 肺腺癌生存预后COX单因素和多因素分析

临床特征	例数	单因素分析		多因素分析
临床特征	例数	HR(95%CI)	P值	HR(95%CI)	P值
年龄	520
≤65	257
>65	263	1.216(0.910~1.625)	0.186
性别	530
女	283
男	247	1.087(0.816~1.448)	0.569
吸烟状况	516
否	74
是	442	0.942(0.625~1.420)	0.775
组织类型	441
肺腺癌(混合亚类)	109
肺腺癌(NOS)	332	1.153(0.797~1.668)	0.449
残余肿瘤	365
R0	349
R1&R2	16	3.913(2.188~6.997)	0.001	3.062(1.198~7.824)	0.019
T分期	527
T1&T2	461
T3&T4	66	2.352(1.614~3.426)	0.001	2.161(1.136~4.111)	0.019
N分期	514
N0	345
N1&N2&N3	169	2.547(1.904~3.407)	0.001	1.601(1.030~2.486)	0.036
M分期	381
M0	356
M1	25	2.176(1.272~3.722)	0.005	1.966(0.835~4.629)	0.122
主要治疗结局	442
CR&PR	333
PD&SD	109	2.634(1.875~3.700)	0.001	3.056(1.849~5.051)	0.001
分层蛋白表达	530
低	264
高	266	1.617(1.209~2.164)	0.001	1.337(0.850~2.104)	0.209

表1 肺腺癌生存预后COX单因素和多因素分析

临床特征	例数	单因素分析		多因素分析
临床特征	例数	HR(95%CI)	P值	HR(95%CI)	P值
年龄	520
≤65	257
>65	263	1.216(0.910~1.625)	0.186
性别	530
女	283
男	247	1.087(0.816~1.448)	0.569
吸烟状况	516
否	74
是	442	0.942(0.625~1.420)	0.775
组织类型	441
肺腺癌(混合亚类)	109
肺腺癌(NOS)	332	1.153(0.797~1.668)	0.449
残余肿瘤	365
R0	349
R1&R2	16	3.913(2.188~6.997)	0.001	3.062(1.198~7.824)	0.019
T分期	527
T1&T2	461
T3&T4	66	2.352(1.614~3.426)	0.001	2.161(1.136~4.111)	0.019
N分期	514
N0	345
N1&N2&N3	169	2.547(1.904~3.407)	0.001	1.601(1.030~2.486)	0.036
M分期	381
M0	356
M1	25	2.176(1.272~3.722)	0.005	1.966(0.835~4.629)	0.122
主要治疗结局	442
CR&PR	333
PD&SD	109	2.634(1.875~3.700)	0.001	3.056(1.849~5.051)	0.001
分层蛋白表达	530
低	264
高	266	1.617(1.209~2.164)	0.001	1.337(0.850~2.104)	0.209

图3 SFN表达与免疫细胞浸润之间的关系。图A为24种免疫细胞与SFN表达之间的相关性分析；图B-D为SFN表达与三个显著正相关免疫细胞浸润的相关性分析，图B为NK细胞；图C为iDC；图D为TH17细胞；图E-F为SFN表达与两个显著负相关免疫细胞浸润的相关性分析，图E为Tcm，图F为辅助性T细胞注：NK cells为自然杀伤细胞；iDC为未成熟树突状细胞；Th17 cells为17型辅助性T细胞；Neutrophils为中性粒细胞；TReg为调节性T细胞；aDC为活化树突状细胞；DC为树突状细胞；NK CD56dim cells为CD56低表达自然杀伤细胞；Th1 cells为1型辅助性T细胞；Th2 cells为2型辅助性T细胞；Macrophages为巨噬细胞；Eosinophils为嗜酸性粒细胞；Mast cells为肥大细胞；pDC为浆细胞样树突状细胞；CD8 T cells为CD8阳性T淋巴细胞；NK CD56bright为CD56高表达自然杀伤细胞；Tgd为γσT细胞；Cytotoxic cells为细胞毒性细胞；TFH为滤泡辅助性T细胞；T cells为T淋巴细胞；B cells为B淋巴细胞；Tem为效应记忆T细胞；T helper cells为辅助性T细胞；Tcm为中央记忆T细胞。Enrichment为细胞富集丰度；Spearman为斯皮尔曼相关分析；Correlation为相关系数

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Exploring the expression characteristics and prognostic value of SFN in lung adenocarcinoma based on bioinformatics

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Exploring the expression characteristics and prognostic value of SFN in lung adenocarcinoma based on bioinformatics