应用MALDI-TOF-MS检测肺鳞癌患者血清多肽并分析其与化疗疗效相关性

发布时间：2018-09-07 12:10

【摘要】：背景与目的晚期肺鳞癌(squamous cell carcinoma of lung,SCC)一线治疗以化疗为主,其标准铂二联方案化疗只能给患者带来有限的获益。并且不同的患者对于化疗药物的获益不同。所以实现化疗药物最优选择达到个体化预见性治疗尤为重要。本研究应用基质辅助激光解析电离飞行时间质谱(matrix-assisted laser desorption/ionization-time of flight-mass spectrometry,MALDI-TOF-MS)检测初治晚期SCC患者接受紫杉醇类联合铂类化疗前血清多肽,并分析其与化疗疗效的相关性。方法初治晚期SCC患者接受紫杉醇类联合铂类方案化疗,每两周期进行疗效评价。评效为完全缓解(complete response,CR)或部分缓解(partial response,PR)患者定义为化疗敏感组,疾病进展(progressive disease,PD)患者定义为耐药组。留取SCC患者化疗前血清样本,81例患者按照3:1的比例随机分为训练组(敏感组I与耐药组I)和验证组(敏感组II与耐药组II),预处理训练组血清样本并进行MALDI-TOFMS检测,得到血清多肽指纹图谱。经Clin Pro Tools软件系统分析处理,得到敏感组I与耐药组I的差异多肽。应用软件内置的3种不同的生物学算法分别建立疗效预测模型,选取最优算法建立疗效预测模型。运用验证组进行盲样验证。结果训练组共纳入30例敏感组患者,31例耐药组患者;验证组共纳入敏感与耐药组患者各10例。训练组在敏感与耐药组有96个差异多肽,其中具有统计学意义的多肽有16个(P0.001)。由5个多肽(1,897.75 Da,2,023.93 Da,3,683.36 Da,4,269.56 Da,5,341.29 Da)建立疗效预测模型。该模型对化疗敏感组患者的识别率为95.11%,交叉验证率为89.18%。经验证组进行盲样验证,其模型的准确率为85%,灵敏度为90.0%,特异性为80.0%。敏感组I中位无进展生存期(progress free survival,PFS)为7.2个月(95%CI:4.4-14.5);耐药组I中位PFS为1.8个月(95%CI:0.7-3.5)。结果发现:4,232.04 Da、4,269.56 Da的差异多肽与SCC患者PFS存在相关性(P0.001)。结论应用MALDI-TOF-MS技术可检测到化疗敏感组及耐药组患者的血清多肽存在差异,初步建立的疗效预测模型可用于预测紫杉醇类联合铂类方案化疗疗效。但需进一步扩大样本量完善及验证模型。
[Abstract]:Background & objective chemotherapy is the primary treatment for advanced lung squamous cell carcinoma (squamous cell carcinoma of lung,SCC). And different patients have different benefits for chemotherapeutic drugs. Therefore, it is very important to realize the optimal choice of chemotherapeutic drugs to achieve individualized predictive therapy. In this study, matrix-assisted laser desorption ionization time of flight mass spectrometry (matrix-assisted laser desorption/ionization-time of flight-mass spectrometry,MALDI-TOF-MS) was used to detect serum polypeptides in patients with primary and advanced SCC receiving paclitaxel combined with platinum chemotherapy, and the correlation between them and the effect of chemotherapy was analyzed. Methods SCC patients were treated with paclitaxel combined with platinum regimen every two cycles. Patients with complete remission (complete response,CR) or partial remission (partial response,PR) were defined as chemosensitive group and patients with progression of disease (progressive disease,PD) were defined as drug resistance group. The serum samples of 81 patients with SCC before chemotherapy were randomly divided into training group (sensitive group I and drug resistance group I) and validation group (sensitive group II and drug resistant group II), pretreatment training group) according to 3:1 ratio. The fingerprint of serum polypeptide was obtained. The differential polypeptides of sensitive group I and drug resistant group I were obtained by Clin Pro Tools system analysis. Three different biological algorithms built into the software were used to establish the model of curative effect prediction, and the optimal algorithm was selected to establish the model of curative effect prediction. The validation group was used for blind sample validation. Results there were 30 cases of sensitive group and 31 cases of drug resistance group in training group, and 10 cases in sensitive group and 10 cases in drug resistance group in validation group. In the training group, there were 96 different polypeptides in sensitive and resistant groups, 16 of which were statistically significant (P0.001). Five polypeptides (1897.75 Da,2023.93 Da,3683.36 Da,4269.56 Da,5341.29 Da) were used to establish a therapeutic effect prediction model. The recognition rate and cross validation rate of the model for chemosensitive group were 95.11 and 89.18 respectively. The accuracy of the model was 85, the sensitivity was 90.0, and the specificity was 80.0. The median progressive survival time (progress free survival,PFS) was 7.2 months (95%CI:4.4-14.5) in the sensitive group and 1.8 months (95%CI:0.7-3.5) in the resistant group. The results showed that there was a correlation between the differential polypeptide of 1: 4232.04 Da,4269.56 Da and PFS in SCC patients (P0. 001). Conclusion the difference of serum polypeptides between chemosensitive group and resistant group can be detected by MALDI-TOF-MS technique, and the preliminary therapeutic effect prediction model can be used to predict the efficacy of paclitaxel combined with platinum regimen chemotherapy. However, it is necessary to further expand the sample size and verify the model.
【作者单位】：军事医学科学院附属医院肺部肿瘤科;国家生物医学分析中心;
【基金】：国家重大科学仪器设备开发专项(No.2011YQ170067)资助~~
【分类号】：R734.2

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