血清肿瘤标志物谱及趋化因子蛋白谱提高肺癌早期诊断及预后预测的临床研究
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摘要
前言
肺癌已经成为世界范围内死亡率最高的恶性肿瘤,同时研究证明吸烟是促进肺癌发生的主要危险因素。研究肺癌发病的分子病理机制并发现肺癌特异的生物标志物成为目前肺癌临床研究和转化医学研究的重点,进一步为肺癌个体化治疗提供更多的依据。生物标志物被定义为“一种具有可以被客观测量和评价正常生理过程、病理过程,或对治疗干预的药理/药效学反应的指标”,具体的检测方法包括免疫组化(组织中原位的表达)：基因变异(包括基因的扩增、突变和重排)；单核苷酸多态性检测(single nucleotide polymorphisms, SNP)以及广谱的或靶向的基因和蛋白的表达分析。
在肺癌早期诊断方面,低剂量螺旋计算机断层扫描(low dose spiral computerized tomography, LDCT)筛查虽然可以提示放射科医生和肺科医生发现大多数肺内的小结节,但是无法判断是否是早期肺癌,同时往往存在假阳性。即使结合了正电子发射型计算机断层扫描显像(positron emission computed tomography, PET)和非开胸手术活检等检查,其真阳性,即敏感性仍较低,并且增加了一定手术风险。但是通过联合分子生物学的检测技术,来辅助影像学的检查,可以显著提高肺癌早期诊断的特异性。这些生物标志物包括检测外周血清中特定的肿瘤标志物,或呼出气体挥发性有机化合物(volatile organic compounds, VOCs)及呼出气冷凝液(exhaled-breath condensate, EB C)的检测。在一项我们的临床研究中发现,联合目前已知的肿瘤标志物[癌胚抗原(carcino-embryonic antigen, CEA)、鳞状细胞癌抗原(squamous cell carcinoma, SCC)、细胞角蛋白19的片段(cytokeratin19Fragment, Cfyra21-1)],与一种新型的肿瘤标志物,胃泌素释放肽前体(pro-gastrin releasing peptide, ProGRP),可以提高肺癌诊断的敏感性和特异性,这种新的方法,可以帮助临床医生,诊断一些在CT影像中存在疑问的肺癌患者。类似的,通过针对呼出气体分子学检测的运用,也可以提高影像学检查的有效性。
在肺癌治疗效果方面,生物标志物变得尤为重要。在肺癌患者中,目前对单次化疗或抗肿瘤药物治疗的反应率普遍低于其它疾病的治疗效果。另外,化疗药物的有效浓度往往接近甚至与毒性浓度重合。因此,针对肺癌患者进行分层,同时筛选出对特定治疗方案最为敏感的人群,对患者和医生而言都具有非常重要的临床价值。目前分子靶向药物的临床运用,便是运用了生物标志物筛查的方法,来预测患者对特定药物的治疗效果[包括反应率、无进展存活时间(progression free survival, PFS)和总生存时间(overall survival, OS)].例如通过表皮生长因子受体(epidermal growth factor receptor, EGFR)基因突变的检测,可以从肺癌患者中筛选出一小部分具有该基因位点突变的人群,与其他肺癌患者相比,这类患者对于酪氨酸激酶抑制剂(tyrosine kinase inhibitor, TKI)的治疗具有更高的敏感性。目前,该项检查已被列入肺癌临床治疗的推荐指南中。与此同时,其它的一些生物标志物,例如K-RAS基因突变、EML4/ALK基因突变及针对抗血管内皮生长因子(vascular endothelial growth factor, VEGF)治疗的生物标志物等,仍在继续研究中,以获取更多的具有信服力的临床证据。在不久的将来,通过生物标志物的研究还将为我们提供开发新药的信息和依据,从而降低研发的经济和时间成本。
从系统生物学的角度来看,目前许多基于以往关于蛋白功能网络研究结果的数据库,已被免费公开,可以供我们使用。通过计算机数学模型的运用,在这些数据库中筛选出具有较高癌变相关值的网络蛋白谱。在之前的研究中发现了三种类型的生物标志物,包括与肿瘤细胞生长相关的生物标志物,例如丝裂原活化蛋白激酶家族中(mitogen-activated protein kinases, MAPK), MAPK1(ERK2)、 MAPK3(ERK1)及MAPK14(p38α); SMAD蛋白家族(SMAD1、SMAD2、 SMAD3和SMAD4);受体酪氨酸激酶(receptor tyrosine kinase, RTK)中的EGFR、成纤维细胞生长因子受体(fibroblast growth factor receptor1, FGFR1)和胰岛素受体(insulin receptor, INSR);转录调节因子中的CREBBP、CTNNB1(p-连环素)、E2F1和MYC。与肿瘤细胞存活相关的生物标志物,包括TP53(p53)、TRAF6、 BRCA1、SP1、丝氨酸／苏氨酸激酶(serine/threonine-specific protein kinase, AKT)及CSNK2A1(CK2)。以及与肿瘤细胞迁徙相关的生物标志物,包括PTK2(FAK)、TSC2、PLCG1和Ezrin。
本课题通过在两个肺癌患者队列的研究,分别利用血清肿瘤标志物谱或血清趋化因子蛋白谱测定的方法,来寻找在肺癌早期诊断及预后预测中具有重要作用的生物标志物。另外,本课题在分析了我国导致肺癌诊断周期(diagnostic lead time,DLT,定义为从症状出现到临床诊断的时间)延长的潜在因素,并首次建立了一套肺癌患者数字化临床评估系统(digital evaluation score system, DESS),用来将临床上描述性的信息转换为临床生物学信息。通过蛋白质组学和临床数据的相互整合,我们发现了一组肺癌生物标志物,具有较高的敏感性和特异性,并且可以显著减少肺癌的诊断周期。
第一部分血清肿瘤标志物谱在具有肺癌相关症状和高危因素的肺癌患者队列中早期诊断的作用
目的：本研究使用一组肺癌特异性指标谱为临床医生提供诊断信息,以便鉴别诊断小细胞肺癌(small cell lung cancer, SCLC)和非小细胞肺癌(non-small cell lung cancer, NSCLC)患者。
方法：测定89名具有肺癌高危因素的健康对象、12名小细胞肺癌和52名非小细胞肺癌患者血清中ProGRP、CEA、SCC和Cyfra21-1四种肿瘤标志物指标。诊断周期的资料,通过针对所有研究对象进行面谈获得。
结果：小细胞肺癌患者的ProGRP显著升高(p<0.0001),腺癌患者CEA显著升高(p<0.0001),而鳞癌患者SCC和Cyfra21-1均显著升高(p<0.0001)。分别对各指标进行界限值的设定,其中ProGRP为300pg/mL,CEA为7.3ng/mL,SCC为3ng/mL以及Cyfra21-1为6.5ng/mL。以ProGRP诊断小细胞肺癌的敏感性和特异性分别为75%和100%。通过加入ProGRP的运用,可以增加目前诊断NSCLC的肿瘤标志物谱的特异性(从88.1%上升至94.1%),并保持敏感性维持不变(75%)。在64名肺癌患者中,因患者因素导致的诊断周期的中位数为17天(四分位区间为2-33天),在医疗系统中的诊断周期为18天(四分位区间为14-33天)。仅有78.1%的肺癌患者可以通过CT检查得到阳性结果,而通过联合运用这四种生物标志物,发现了8例临床CT假阴性的NSCLC患者,这些病例可能在临床上会造成诊断周期的延长。
结论：研究所采用的这组血清肿瘤标志物谱提高了在高危健康人群中(除肾衰患者外)筛查肺癌的特异性,同时也提高了在具有恶性肿瘤患者中诊断肺癌的敏感性。通过在临床中使用该组生物标志物谱,将可能缩短我国基层医疗机构和专科医院针对肺癌的诊断周期。
第二部分血清趋化因子蛋白谱在非小细胞肺癌患者中对肺癌发生与预后的影响
目的：炎症在肺癌的发生和发展中起到重要的作用。本研究通过多重血清细胞因子的定量测定和分析,旨在发现可以预测接受化疗的非小细胞肺癌(NSCLC)患者预后的生物标志物。
方法：收集健康非吸烟志愿者的血清标本(14例),及NSCLC患者(50例,女性14例,男性36例,平均年龄58.0±11.4岁；36例腺癌,临床分期Ⅰ,Ⅲ和Ⅳ期；和14例鳞癌,临床分期Ⅰ至Ⅳ期)在入院当天诊断前采集血清标本。5例Ⅳ期腺癌患者在第2次和第3次入院时重复采样,以获得第1次和第2次化疗后的血清样本(即在首次诊断治疗后的第21天和第42天)。应用多重细胞因子免疫检测方法同时检测40种细胞因子的表达情况,通过肺癌临床生物信息量表采集临床信息并转换为数字的患者临床信息,所有的患者均完成长达2年的生存周期的随访。应用成组t检验及Mann-Whitney U检验比较40种细胞因子在不同类型肺癌患者血清中表达情况的差异,使用Mann-Whitney U检验比较各组肺癌患者间数字化信息量表数值,并用Stepwise多因素回归分析及Kaplan-Meier生存分析判定影响非小细胞肺癌生存预后的独立相关危险因素。
结果：在检测的40种炎症细胞因子,13种细胞因子在所有的肺癌患者中与健康对照组之间存在显著差异,18种细胞因子在腺癌患者中与健康对照组之间存在显著差异,11种细胞因子在鳞癌患者中与健康对照组之间存在显著差异。在Ⅳ期腺癌患者中发现,有9种细胞因子在接受化疗前和第一次化疗后之间存在显著差异,有13种细胞因子在接受化疗前和第二次化疗后之间存在显著差异。数字化临床评估系统(DESS)检测发现,在“原发肿瘤引起的症状”分值中,腺癌与鳞癌患者中具有显著差异(p=0.005)。在29例腺癌患者(临床分期ⅢB和Ⅳ期)中,血清中高表达单核细胞趋化因子4(monocyte chemoattractant protein4,MCP-4)、人生长调节致癌基因(growth-regulated oncogene, GRO)、胸腺表达趋化因子(thymus expressed chemokine, TECK)和巨噬细胞刺激蛋白a(macrophage stimulating protein a, MSPa)组的患者较正常表达组的患者具有较高的死亡风险,相反地,高表达可与糖蛋白D竞争疱疹病毒进入T细胞位点的TNF样诱导蛋白(lymphotoxin-like inducible protein that competes with glycoprotein D for herpesvirus entry on T cells,LIGHT)、皮肤T细胞虏获趋化因子(cutaneous T-cell attracting chemokines/CCL27, CTACK)、趋化因子配体28(C-C motif ligand28, CCL28)和白介素-29(interleukin-29, IL-29)组的患者较正常表达组的患者具有较低的死亡风险。
结论：在非小细胞肺癌的患者中存在与特定疾病相关的炎症细胞因子蛋白谱。通过该蛋白谱的运用,可以辅助肺癌的临床分型、预后预测、评估化疗疗效和生存周期。
Introduction
Lung cancer has become the worldwide No.1malignant tumor with highest mortality. Studies have shown smoking is the main risk factor of lung cancer. Understanding of the molecular pathogenesis of lung cancer and identifying specific biomarkers have become the most active areas of research, results of which are important for clinical and translational studies, as well as for personalized medicine. A biomarker is defined as'a readout that can be objectively measured and evaluated as an indicator of normal biologic or pathological processes, or of pharmacologic/pharmacodynamics responses to a therapeutic intervention'. Different measures have been used to identify biomarkers, including immunohistochemistry, genomic variations (such as gene amplification, mutation, or rearrangement), single nucleotide polymorphism (SNP) and global or targeted gene/protein expression.
Regarding to early diagnosis of lung cancer, low dose spiral computerized tomography (LDCT) scan could provide information on most small nodule in the lung, however it is difficult to determine whether the lesions are early stage of malignant tumor or not, and is burdened with high false positive rates. Even with combined positron emission computed tomography (PET) and non-open biopsy, the sensitivity of true-positive is still very low and it is associated with surgical risks of biopsy. However, by introducing bio-molecular detection to the current radiological examination, the specificity of early diagnosis could be significantly improved. Such biomarkers include detecting certain tumor biomarkers in peripheral serum samples or in exhaled breath volatile organic compounds (VOCs) or exhaled-breath condensate (EBC). In one of our clinical cohort studies, we found that by combining currently accepted tumor biomarkers (CEA, SCC, Cfyra21-1) with a new biomarker, ProGRP, it could significantly improve the sensitivity and specificity of diagnosis, which helped to rule in patients with questionable radiology findings from CT scan. Similarly, molecular analysis of exhaled breath improved the quality of radiological examination.
With respect to treatment effect, biomarker plays important roles in lung cancer therapy. In lung cancer, the response rate to single dose chemotherapy or other anti-tumor drugs was usually lower than in other diseases. And the therapeutic drug concentration is often close to or even overlaps with the toxic concentration. Therefore, it was very important to stratify the patients and segregate those who are most sensitive to treatment, benefiting both the patients and physicians. Currently, molecular targeting drug are being used in clinical application, following biomarker screening, which predicts the patients'response [including response rate, progression free survival (PFS) and overall survival (OS)]. For example, by detecting epidermal growth factor receptor (EGFR) mutation, we could screen out the small population of patients carrying this mutation and who will be more sensitive to the tyrosine kinase inhibitor (TKI) treatment than other lung cancer patients. And this protocol has now been included in the guidelines of lung cancer diagnosis and treatment. Meanwhile, other biomarkers, such as K-RAS mutation, EML4/ALK mutation and assay for anti-vascular endothelial growth factor (anti-VEGF) treatment are under studies to gather more convincing proofs. In the near future, biomarkers will also provide us with information and proofs in new drug discovery, lowering the economic cost and shortening the lead time.
In the field of system biology, many databases of previous studies on the network of protein functions are freely open to us. We can use mathematical computer model to screen these databases and define proteomics that are important to lung cancer carcinogenesis. In one of previous studies, three groups of such biomarkers were identified. These include cell growth related biomarkers, such as MAPK (MAPK1/ERK2, MAPK3/ERK1and MAPK14/p38α), SMAD (SMAD1, SMAD2, SMAD3and SMAD4), RTKS (EGFR, FGFR1and INSR); transcriptional regulators (CREBBP, CTNNB1/β-catenin, E2F1and MYC); cell survival related biomarkers include TP53/p53, TRAF6, BRCA1, SP1, AKT and CSNK2A1(CK2); and finally cell migration related biomarkers include PTK2/FAK, TSC2, PLCG1and EZR/ezrin.
In this study, we examined two cohorts of lung cancer patients, who were studied either with multiple serum tumor biomarkers or with protein profiling of chemokine to search for important early diagnosis and prognosis related biomarkers in lung cancer. In addition, in our project, we also analyzed the underlying causes of prolonged diagnostic lead time (DLT, defined as the time period from symptom to clinical diagnosis) in China and established a set of Digital Evaluation Score System (DESS) for transferring clinical data into clinical informatics. By comprehensively integrating proteomics and clinical data, we have identified a panel of lung cancer biomarkers with high sensitivity and specificity and significantly shorter DLT.
Part Ⅰ Role of a serum based biomarker panel in early diagnosis of lung cancer in a cohort of high-risk lung cancer patient presenting with cancer related symptoms
Objective:In this study, we applied a lung cancer specific panel to provide the clinical physicians with diagnostic information distinguishing small-cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC).
Methods:Serum levels of four factors (ProGRP, CEA, SCC and Cyfra21-1) were determined in89healthy subjects with high risk factor of lung cancer,12patients with SCLC, and52patients with NSCLC. The DLT information was collected by interviewing all the study participants.
Results:It is observed that significantly higher serum levels of ProGRP (p<0.0001) was found among SCLC patients; significantly higher CEA levels (p<0.0001) among adenocarcinoma and SCC patients (p<0.0001); and significantly higher Cyfra21-1levles (p<0.0001) in SCC. We have established the cut off values of ProGRP, CEA, SCC and Cyfra21-1at300pg/mL,7.3ng/mL,3ng/mL and6.5ng/mL, respectively. Sensitivity and specificity of ProGRP in diagnosing SCLC was75%and100%. With the inclusion of ProGRP, the specificity of these tumor markers for NSCLC was increased (from88.1%to94.1%) with the unchanged sensitivity (75%). Among64 patients, the median DLT was17days in patient delay (IQI=2-33days), compared with a median DLT of18days in system delay (IQI=14-33days). Only78.1%patient received positive CT scan result on; therefore, combining the diagnostic panel of the four factors discovered eight false-negative NSCLC cases, whom would be missed the diagnosis.
Conclusions:This panel of serum tumor marker increased the diagnostic specificity among high risk factor healthy subjects (excluding renal failure) and increased sensitivity in patients with malignant lung tumor. These results might be applied to shorten the diagnosis delay both in primary health care and in hospital specialty in China.
Part Ⅱ Protein profile of serum chemokine correlates with tumorgenesis and prognosis in non-small cell lung cancer patients
Rationale:Inflammation plays an important role in lung cancer development. In this study, multiple serum cytokines were quantified and analyzed in order to identify biomarkers for prognosis in non-small cell lung cancer (NSCLC) patients receiving chemotherapy.
Methods:Sera of healthy non-smokers (n=14) and of patients with NSCLC (n=50,14female and36male, with an average age of58.0±11.4years;36with adenocarcinoma, stage Ⅰ, Ⅲ and Ⅳ; and14with squamous cell carcinoma, stages Ⅰ to Ⅳ) were collected on first hospital admission for diagnosis. Sera of the five stages Ⅳ adenocarcinoma patients were collected again on second and third admissions following one to two course of chemotherapy (21and42days post-diagnosis). The cytokine protein concentrations were measured using multiplexed cytokine immunoassays. Clinical informatics was achieved by a Digital Evaluation Score System (DESS) for assessing severity of patients. All patients completed follow-up for up to two years. Student T-test and Mann-Whitney U test was applied to compare the different cytokine level in different groups of samples. Mann-Whitney U test was applied to compare the value of DESS, Stepwise regression and Kaplan-Meier survival analysis were used to determine independent risk factor of non-small cell cancer over survival.
Results:Among the40inflammatory mediators measured,13showed statistically significant differences between total lung cancer patients and healthy controls;18showed statistically significant differences between adenocarcinoma patients and healthy controls; and11showed a difference between squamous cell carcinoma patients and healthy controls. Among patients with adenocarcinoma (stage Ⅳ),9mediators showed a difference between untreated and post1st time chemotherapy and13mediators showed a difference between untreated and after2nd time chemotherapy. On DESS evaluation, the value of 'primary tumors caused symptoms' showed significant difference between adenocarcinoma and squamous carcinoma patients (p=0.005). Among29patients with adenocarcinomas (stage ⅢB and Ⅳ), higher levels of MCP-4, growth-regulated oncogene (GRO), thymus expressed chemokine (TECK) and macrophage stimulating protein a (MSPa) were associated with higher risk of death compared with those with normal serum levels. Conversely, higher levels of lymphotoxin-like inducible protein that competes with glycoprotein D for herpesvirus entry on T cells (LIGHT), cutaneous T-cell attracting chemokines/CCL27(CTACK), C-C motif ligand28(CCL28) and interleukin-29(IL-29) were associated with a lower risk of death compared with those with normal serum levels.
Conclusion:There is a disease-specific profile of inflammatory mediators in this group of NSCLC patients. This pattern might be useful for aiding cancer sub-classification, prognosis, evaluation of chemotherapy effects, and overall survival.
肺癌已经成为世界范围内死亡率最高的恶性肿瘤,同时研究证明吸烟是促进肺癌发生的主要危险因素。研究肺癌发病的分子病理机制并发现肺癌特异的生物标志物成为目前肺癌临床研究和转化医学研究的重点,进一步为肺癌个体化治疗提供更多的依据。生物标志物被定义为“一种具有可以被客观测量和评价正常生理过程、病理过程,或对治疗干预的药理/药效学反应的指标”,具体的检测方法包括免疫组化(组织中原位的表达)：基因变异(包括基因的扩增、突变和重排)；单核苷酸多态性检测(single nucleotide polymorphisms, SNP)以及广谱的或靶向的基因和蛋白的表达分析。
在肺癌早期诊断方面,低剂量螺旋计算机断层扫描(low dose spiral computerized tomography, LDCT)筛查虽然可以提示放射科医生和肺科医生发现大多数肺内的小结节,但是无法判断是否是早期肺癌,同时往往存在假阳性。即使结合了正电子发射型计算机断层扫描显像(positron emission computed tomography, PET)和非开胸手术活检等检查,其真阳性,即敏感性仍较低,并且增加了一定手术风险。但是通过联合分子生物学的检测技术,来辅助影像学的检查,可以显著提高肺癌早期诊断的特异性。这些生物标志物包括检测外周血清中特定的肿瘤标志物,或呼出气体挥发性有机化合物(volatile organic compounds, VOCs)及呼出气冷凝液(exhaled-breath condensate, EB C)的检测。在一项我们的临床研究中发现,联合目前已知的肿瘤标志物[癌胚抗原(carcino-embryonic antigen, CEA)、鳞状细胞癌抗原(squamous cell carcinoma, SCC)、细胞角蛋白19的片段(cytokeratin19Fragment, Cfyra21-1)],与一种新型的肿瘤标志物,胃泌素释放肽前体(pro-gastrin releasing peptide, ProGRP),可以提高肺癌诊断的敏感性和特异性,这种新的方法,可以帮助临床医生,诊断一些在CT影像中存在疑问的肺癌患者。类似的,通过针对呼出气体分子学检测的运用,也可以提高影像学检查的有效性。
在肺癌治疗效果方面,生物标志物变得尤为重要。在肺癌患者中,目前对单次化疗或抗肿瘤药物治疗的反应率普遍低于其它疾病的治疗效果。另外,化疗药物的有效浓度往往接近甚至与毒性浓度重合。因此,针对肺癌患者进行分层,同时筛选出对特定治疗方案最为敏感的人群,对患者和医生而言都具有非常重要的临床价值。目前分子靶向药物的临床运用,便是运用了生物标志物筛查的方法,来预测患者对特定药物的治疗效果[包括反应率、无进展存活时间(progression free survival, PFS)和总生存时间(overall survival, OS)].例如通过表皮生长因子受体(epidermal growth factor receptor, EGFR)基因突变的检测,可以从肺癌患者中筛选出一小部分具有该基因位点突变的人群,与其他肺癌患者相比,这类患者对于酪氨酸激酶抑制剂(tyrosine kinase inhibitor, TKI)的治疗具有更高的敏感性。目前,该项检查已被列入肺癌临床治疗的推荐指南中。与此同时,其它的一些生物标志物,例如K-RAS基因突变、EML4/ALK基因突变及针对抗血管内皮生长因子(vascular endothelial growth factor, VEGF)治疗的生物标志物等,仍在继续研究中,以获取更多的具有信服力的临床证据。在不久的将来,通过生物标志物的研究还将为我们提供开发新药的信息和依据,从而降低研发的经济和时间成本。
从系统生物学的角度来看,目前许多基于以往关于蛋白功能网络研究结果的数据库,已被免费公开,可以供我们使用。通过计算机数学模型的运用,在这些数据库中筛选出具有较高癌变相关值的网络蛋白谱。在之前的研究中发现了三种类型的生物标志物,包括与肿瘤细胞生长相关的生物标志物,例如丝裂原活化蛋白激酶家族中(mitogen-activated protein kinases, MAPK), MAPK1(ERK2)、 MAPK3(ERK1)及MAPK14(p38α); SMAD蛋白家族(SMAD1、SMAD2、 SMAD3和SMAD4);受体酪氨酸激酶(receptor tyrosine kinase, RTK)中的EGFR、成纤维细胞生长因子受体(fibroblast growth factor receptor1, FGFR1)和胰岛素受体(insulin receptor, INSR);转录调节因子中的CREBBP、CTNNB1(p-连环素)、E2F1和MYC。与肿瘤细胞存活相关的生物标志物,包括TP53(p53)、TRAF6、 BRCA1、SP1、丝氨酸／苏氨酸激酶(serine/threonine-specific protein kinase, AKT)及CSNK2A1(CK2)。以及与肿瘤细胞迁徙相关的生物标志物,包括PTK2(FAK)、TSC2、PLCG1和Ezrin。
本课题通过在两个肺癌患者队列的研究,分别利用血清肿瘤标志物谱或血清趋化因子蛋白谱测定的方法,来寻找在肺癌早期诊断及预后预测中具有重要作用的生物标志物。另外,本课题在分析了我国导致肺癌诊断周期(diagnostic lead time,DLT,定义为从症状出现到临床诊断的时间)延长的潜在因素,并首次建立了一套肺癌患者数字化临床评估系统(digital evaluation score system, DESS),用来将临床上描述性的信息转换为临床生物学信息。通过蛋白质组学和临床数据的相互整合,我们发现了一组肺癌生物标志物,具有较高的敏感性和特异性,并且可以显著减少肺癌的诊断周期。
第一部分血清肿瘤标志物谱在具有肺癌相关症状和高危因素的肺癌患者队列中早期诊断的作用
目的：本研究使用一组肺癌特异性指标谱为临床医生提供诊断信息,以便鉴别诊断小细胞肺癌(small cell lung cancer, SCLC)和非小细胞肺癌(non-small cell lung cancer, NSCLC)患者。
方法：测定89名具有肺癌高危因素的健康对象、12名小细胞肺癌和52名非小细胞肺癌患者血清中ProGRP、CEA、SCC和Cyfra21-1四种肿瘤标志物指标。诊断周期的资料,通过针对所有研究对象进行面谈获得。
结果：小细胞肺癌患者的ProGRP显著升高(p<0.0001),腺癌患者CEA显著升高(p<0.0001),而鳞癌患者SCC和Cyfra21-1均显著升高(p<0.0001)。分别对各指标进行界限值的设定,其中ProGRP为300pg/mL,CEA为7.3ng/mL,SCC为3ng/mL以及Cyfra21-1为6.5ng/mL。以ProGRP诊断小细胞肺癌的敏感性和特异性分别为75%和100%。通过加入ProGRP的运用,可以增加目前诊断NSCLC的肿瘤标志物谱的特异性(从88.1%上升至94.1%),并保持敏感性维持不变(75%)。在64名肺癌患者中,因患者因素导致的诊断周期的中位数为17天(四分位区间为2-33天),在医疗系统中的诊断周期为18天(四分位区间为14-33天)。仅有78.1%的肺癌患者可以通过CT检查得到阳性结果,而通过联合运用这四种生物标志物,发现了8例临床CT假阴性的NSCLC患者,这些病例可能在临床上会造成诊断周期的延长。
结论：研究所采用的这组血清肿瘤标志物谱提高了在高危健康人群中(除肾衰患者外)筛查肺癌的特异性,同时也提高了在具有恶性肿瘤患者中诊断肺癌的敏感性。通过在临床中使用该组生物标志物谱,将可能缩短我国基层医疗机构和专科医院针对肺癌的诊断周期。
第二部分血清趋化因子蛋白谱在非小细胞肺癌患者中对肺癌发生与预后的影响
目的：炎症在肺癌的发生和发展中起到重要的作用。本研究通过多重血清细胞因子的定量测定和分析,旨在发现可以预测接受化疗的非小细胞肺癌(NSCLC)患者预后的生物标志物。
方法：收集健康非吸烟志愿者的血清标本(14例),及NSCLC患者(50例,女性14例,男性36例,平均年龄58.0±11.4岁；36例腺癌,临床分期Ⅰ,Ⅲ和Ⅳ期；和14例鳞癌,临床分期Ⅰ至Ⅳ期)在入院当天诊断前采集血清标本。5例Ⅳ期腺癌患者在第2次和第3次入院时重复采样,以获得第1次和第2次化疗后的血清样本(即在首次诊断治疗后的第21天和第42天)。应用多重细胞因子免疫检测方法同时检测40种细胞因子的表达情况,通过肺癌临床生物信息量表采集临床信息并转换为数字的患者临床信息,所有的患者均完成长达2年的生存周期的随访。应用成组t检验及Mann-Whitney U检验比较40种细胞因子在不同类型肺癌患者血清中表达情况的差异,使用Mann-Whitney U检验比较各组肺癌患者间数字化信息量表数值,并用Stepwise多因素回归分析及Kaplan-Meier生存分析判定影响非小细胞肺癌生存预后的独立相关危险因素。
结果：在检测的40种炎症细胞因子,13种细胞因子在所有的肺癌患者中与健康对照组之间存在显著差异,18种细胞因子在腺癌患者中与健康对照组之间存在显著差异,11种细胞因子在鳞癌患者中与健康对照组之间存在显著差异。在Ⅳ期腺癌患者中发现,有9种细胞因子在接受化疗前和第一次化疗后之间存在显著差异,有13种细胞因子在接受化疗前和第二次化疗后之间存在显著差异。数字化临床评估系统(DESS)检测发现,在“原发肿瘤引起的症状”分值中,腺癌与鳞癌患者中具有显著差异(p=0.005)。在29例腺癌患者(临床分期ⅢB和Ⅳ期)中,血清中高表达单核细胞趋化因子4(monocyte chemoattractant protein4,MCP-4)、人生长调节致癌基因(growth-regulated oncogene, GRO)、胸腺表达趋化因子(thymus expressed chemokine, TECK)和巨噬细胞刺激蛋白a(macrophage stimulating protein a, MSPa)组的患者较正常表达组的患者具有较高的死亡风险,相反地,高表达可与糖蛋白D竞争疱疹病毒进入T细胞位点的TNF样诱导蛋白(lymphotoxin-like inducible protein that competes with glycoprotein D for herpesvirus entry on T cells,LIGHT)、皮肤T细胞虏获趋化因子(cutaneous T-cell attracting chemokines/CCL27, CTACK)、趋化因子配体28(C-C motif ligand28, CCL28)和白介素-29(interleukin-29, IL-29)组的患者较正常表达组的患者具有较低的死亡风险。
结论：在非小细胞肺癌的患者中存在与特定疾病相关的炎症细胞因子蛋白谱。通过该蛋白谱的运用,可以辅助肺癌的临床分型、预后预测、评估化疗疗效和生存周期。
Introduction
Lung cancer has become the worldwide No.1malignant tumor with highest mortality. Studies have shown smoking is the main risk factor of lung cancer. Understanding of the molecular pathogenesis of lung cancer and identifying specific biomarkers have become the most active areas of research, results of which are important for clinical and translational studies, as well as for personalized medicine. A biomarker is defined as'a readout that can be objectively measured and evaluated as an indicator of normal biologic or pathological processes, or of pharmacologic/pharmacodynamics responses to a therapeutic intervention'. Different measures have been used to identify biomarkers, including immunohistochemistry, genomic variations (such as gene amplification, mutation, or rearrangement), single nucleotide polymorphism (SNP) and global or targeted gene/protein expression.
Regarding to early diagnosis of lung cancer, low dose spiral computerized tomography (LDCT) scan could provide information on most small nodule in the lung, however it is difficult to determine whether the lesions are early stage of malignant tumor or not, and is burdened with high false positive rates. Even with combined positron emission computed tomography (PET) and non-open biopsy, the sensitivity of true-positive is still very low and it is associated with surgical risks of biopsy. However, by introducing bio-molecular detection to the current radiological examination, the specificity of early diagnosis could be significantly improved. Such biomarkers include detecting certain tumor biomarkers in peripheral serum samples or in exhaled breath volatile organic compounds (VOCs) or exhaled-breath condensate (EBC). In one of our clinical cohort studies, we found that by combining currently accepted tumor biomarkers (CEA, SCC, Cfyra21-1) with a new biomarker, ProGRP, it could significantly improve the sensitivity and specificity of diagnosis, which helped to rule in patients with questionable radiology findings from CT scan. Similarly, molecular analysis of exhaled breath improved the quality of radiological examination.
With respect to treatment effect, biomarker plays important roles in lung cancer therapy. In lung cancer, the response rate to single dose chemotherapy or other anti-tumor drugs was usually lower than in other diseases. And the therapeutic drug concentration is often close to or even overlaps with the toxic concentration. Therefore, it was very important to stratify the patients and segregate those who are most sensitive to treatment, benefiting both the patients and physicians. Currently, molecular targeting drug are being used in clinical application, following biomarker screening, which predicts the patients'response [including response rate, progression free survival (PFS) and overall survival (OS)]. For example, by detecting epidermal growth factor receptor (EGFR) mutation, we could screen out the small population of patients carrying this mutation and who will be more sensitive to the tyrosine kinase inhibitor (TKI) treatment than other lung cancer patients. And this protocol has now been included in the guidelines of lung cancer diagnosis and treatment. Meanwhile, other biomarkers, such as K-RAS mutation, EML4/ALK mutation and assay for anti-vascular endothelial growth factor (anti-VEGF) treatment are under studies to gather more convincing proofs. In the near future, biomarkers will also provide us with information and proofs in new drug discovery, lowering the economic cost and shortening the lead time.
In the field of system biology, many databases of previous studies on the network of protein functions are freely open to us. We can use mathematical computer model to screen these databases and define proteomics that are important to lung cancer carcinogenesis. In one of previous studies, three groups of such biomarkers were identified. These include cell growth related biomarkers, such as MAPK (MAPK1/ERK2, MAPK3/ERK1and MAPK14/p38α), SMAD (SMAD1, SMAD2, SMAD3and SMAD4), RTKS (EGFR, FGFR1and INSR); transcriptional regulators (CREBBP, CTNNB1/β-catenin, E2F1and MYC); cell survival related biomarkers include TP53/p53, TRAF6, BRCA1, SP1, AKT and CSNK2A1(CK2); and finally cell migration related biomarkers include PTK2/FAK, TSC2, PLCG1and EZR/ezrin.
In this study, we examined two cohorts of lung cancer patients, who were studied either with multiple serum tumor biomarkers or with protein profiling of chemokine to search for important early diagnosis and prognosis related biomarkers in lung cancer. In addition, in our project, we also analyzed the underlying causes of prolonged diagnostic lead time (DLT, defined as the time period from symptom to clinical diagnosis) in China and established a set of Digital Evaluation Score System (DESS) for transferring clinical data into clinical informatics. By comprehensively integrating proteomics and clinical data, we have identified a panel of lung cancer biomarkers with high sensitivity and specificity and significantly shorter DLT.
Part Ⅰ Role of a serum based biomarker panel in early diagnosis of lung cancer in a cohort of high-risk lung cancer patient presenting with cancer related symptoms
Objective:In this study, we applied a lung cancer specific panel to provide the clinical physicians with diagnostic information distinguishing small-cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC).
Methods:Serum levels of four factors (ProGRP, CEA, SCC and Cyfra21-1) were determined in89healthy subjects with high risk factor of lung cancer,12patients with SCLC, and52patients with NSCLC. The DLT information was collected by interviewing all the study participants.
Results:It is observed that significantly higher serum levels of ProGRP (p<0.0001) was found among SCLC patients; significantly higher CEA levels (p<0.0001) among adenocarcinoma and SCC patients (p<0.0001); and significantly higher Cyfra21-1levles (p<0.0001) in SCC. We have established the cut off values of ProGRP, CEA, SCC and Cyfra21-1at300pg/mL,7.3ng/mL,3ng/mL and6.5ng/mL, respectively. Sensitivity and specificity of ProGRP in diagnosing SCLC was75%and100%. With the inclusion of ProGRP, the specificity of these tumor markers for NSCLC was increased (from88.1%to94.1%) with the unchanged sensitivity (75%). Among64 patients, the median DLT was17days in patient delay (IQI=2-33days), compared with a median DLT of18days in system delay (IQI=14-33days). Only78.1%patient received positive CT scan result on; therefore, combining the diagnostic panel of the four factors discovered eight false-negative NSCLC cases, whom would be missed the diagnosis.
Conclusions:This panel of serum tumor marker increased the diagnostic specificity among high risk factor healthy subjects (excluding renal failure) and increased sensitivity in patients with malignant lung tumor. These results might be applied to shorten the diagnosis delay both in primary health care and in hospital specialty in China.
Part Ⅱ Protein profile of serum chemokine correlates with tumorgenesis and prognosis in non-small cell lung cancer patients
Rationale:Inflammation plays an important role in lung cancer development. In this study, multiple serum cytokines were quantified and analyzed in order to identify biomarkers for prognosis in non-small cell lung cancer (NSCLC) patients receiving chemotherapy.
Methods:Sera of healthy non-smokers (n=14) and of patients with NSCLC (n=50,14female and36male, with an average age of58.0±11.4years;36with adenocarcinoma, stage Ⅰ, Ⅲ and Ⅳ; and14with squamous cell carcinoma, stages Ⅰ to Ⅳ) were collected on first hospital admission for diagnosis. Sera of the five stages Ⅳ adenocarcinoma patients were collected again on second and third admissions following one to two course of chemotherapy (21and42days post-diagnosis). The cytokine protein concentrations were measured using multiplexed cytokine immunoassays. Clinical informatics was achieved by a Digital Evaluation Score System (DESS) for assessing severity of patients. All patients completed follow-up for up to two years. Student T-test and Mann-Whitney U test was applied to compare the different cytokine level in different groups of samples. Mann-Whitney U test was applied to compare the value of DESS, Stepwise regression and Kaplan-Meier survival analysis were used to determine independent risk factor of non-small cell cancer over survival.
Results:Among the40inflammatory mediators measured,13showed statistically significant differences between total lung cancer patients and healthy controls;18showed statistically significant differences between adenocarcinoma patients and healthy controls; and11showed a difference between squamous cell carcinoma patients and healthy controls. Among patients with adenocarcinoma (stage Ⅳ),9mediators showed a difference between untreated and post1st time chemotherapy and13mediators showed a difference between untreated and after2nd time chemotherapy. On DESS evaluation, the value of 'primary tumors caused symptoms' showed significant difference between adenocarcinoma and squamous carcinoma patients (p=0.005). Among29patients with adenocarcinomas (stage ⅢB and Ⅳ), higher levels of MCP-4, growth-regulated oncogene (GRO), thymus expressed chemokine (TECK) and macrophage stimulating protein a (MSPa) were associated with higher risk of death compared with those with normal serum levels. Conversely, higher levels of lymphotoxin-like inducible protein that competes with glycoprotein D for herpesvirus entry on T cells (LIGHT), cutaneous T-cell attracting chemokines/CCL27(CTACK), C-C motif ligand28(CCL28) and interleukin-29(IL-29) were associated with a lower risk of death compared with those with normal serum levels.
Conclusion:There is a disease-specific profile of inflammatory mediators in this group of NSCLC patients. This pattern might be useful for aiding cancer sub-classification, prognosis, evaluation of chemotherapy effects, and overall survival.
引文
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20. Metz CE. Basic principles of ROC analysis [J]. Seminars in nuclear medicine.1978;8:283-98.
21. Swensen SJ, Jett JR, Hartman TE, et al. Lung cancer screening with CT:Mayo Clinic experience [J]. Radiology 2003; 226:756-61.
22. Gohagan JK, Marcus PM, Fagerstrom RM, et al. Final results of the Lung Screening Study, a randomized feasibility study of spiral CT versus chest X-ray screening for lung cancer [J]. Lung cancer. 2005; 47:9-15.
23. Bastarrika G, Garcia-Velloso MJ, Lozano MD, et al. Early lung cancer detection using spiral computed tomography and positron emission tomography [J]. American journal of respiratory and critical care medicine.2005; 171:1378-83.
24. Vierikko T, Jarvenpaa R, Autti T, et al:Chest CT screening of asbestos-exposed workers:lung lesions and incidental findings [J]. The European respiratory journal:official journal of the European Society for Clinical Respiratory Physiology.2007; 29:78-84.
25. Jeong YJ, Lee KS, Jeong SY, et al. Solitary pulmonary nodule:characterization with combined wash-in and washout features at dynamic multi-detector row CT [J]. Radiology 2005; 237:675-83.
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31. Rafael M. ProGRP:A New Biomarker for Small Cell Lung Cancer [J]. European Journal of Clinical & Medical Oncology.2009;1:25-32.
32. Schneider J. Early detection of lung cancers-Comparison of computed tomography, cytology and fuzzy-based tumor markers panels [J]. Cancer biomarkers:section A of Disease markers. 2010;6:149-62.
33. Ou S-HI, Zell JA. Carcinoma NOS is a Common Histologic Diagnosis and is Increasing in Proportion Among Non-small Cell Lung Cancer Histologies [J]. Journal of Thoracic Oncology. 2009;4:1202-1211
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20. Metz CE. Basic principles of ROC analysis [J]. Seminars in nuclear medicine.1978;8:283-98.
21. Swensen SJ, Jett JR, Hartman TE, et al. Lung cancer screening with CT:Mayo Clinic experience [J]. Radiology 2003; 226:756-61.
22. Gohagan JK, Marcus PM, Fagerstrom RM, et al. Final results of the Lung Screening Study, a randomized feasibility study of spiral CT versus chest X-ray screening for lung cancer [J]. Lung cancer. 2005; 47:9-15.
23. Bastarrika G, Garcia-Velloso MJ, Lozano MD, et al. Early lung cancer detection using spiral computed tomography and positron emission tomography [J]. American journal of respiratory and critical care medicine.2005; 171:1378-83.
24. Vierikko T, Jarvenpaa R, Autti T, et al:Chest CT screening of asbestos-exposed workers:lung lesions and incidental findings [J]. The European respiratory journal:official journal of the European Society for Clinical Respiratory Physiology.2007; 29:78-84.
25. Jeong YJ, Lee KS, Jeong SY, et al. Solitary pulmonary nodule:characterization with combined wash-in and washout features at dynamic multi-detector row CT [J]. Radiology 2005; 237:675-83.
26. Kohno N, Hirasawa Y, Kondo K, et al. Comparative studies of CAM 123-6 and carcinoembryonic antigen for the serological detection of pulmonary adenocarcinoma [J]. Cancer detection and prevention.1997; 21:124-8.
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31. Rafael M. ProGRP:A New Biomarker for Small Cell Lung Cancer [J]. European Journal of Clinical & Medical Oncology.2009;1:25-32.
32. Schneider J. Early detection of lung cancers-Comparison of computed tomography, cytology and fuzzy-based tumor markers panels [J]. Cancer biomarkers:section A of Disease markers. 2010;6:149-62.
33. Ou S-HI, Zell JA. Carcinoma NOS is a Common Histologic Diagnosis and is Increasing in Proportion Among Non-small Cell Lung Cancer Histologies [J]. Journal of Thoracic Oncology. 2009;4:1202-1211
34. Zhang J, Chen S-F, Zhen Y, et al. Multicenter analysis of lung cancer patients younger than 45 years in Shanghai [J]. Cancer.2010;116:3656-3662.
35. Strand T-E, Malayeri C, Eskonsipo PKJ, et al. Adolescent smoking and trends in lung cancer incidence among young adults in Norway 1954-1998 [J]. Cancer Causes and Control.2004;15:27-33.
36. Marugame T, Yoshimi I, Kamo K-i, et al. Trends in Lung Cancer Mortality Among Young Adults in Japan [J]. Japanese Journal of Clinical Oncology.2005;35:177-180.
37. Balli D, Ren X, Chou FS, et al. Foxml transcription factor is required for macrophage migration during lung inflammation and tumor formation [J]. Oncogene.2011:1-14;
38. Eikawa S, Ohue Y, Kitaoka K, et al. Enrichment of Foxp3+ CD4 regulatory T cells in migrated T cells to IL-6- and IL-8-expressing tumors through predominant induction of CXCR1 by IL-6 [J]. J Immunol.2010; 185:6734-40.
39. Andersson A, Yang SC, Huang M, et al. IL-7 promotes CXCR3 ligand-dependent T cell antitumor reactivity in lung cancer [J]. J Immunol.2009;182:6951-8.
40. Ohri CM, Shikotra A, Green RH, et al. Chemokine receptor expression in tumour islets and stroma in non-small cell lung cancer [J]. BMC Cancer.2010;10:172.
41. Minamiya Y, Saito H, Takahashi N, et al. Expression of the chemokine receptor CXCR4 correlates with a favorable prognosis in patients with adenocarcinoma of the lung [J]. Lung Cancer. 2010;68:466-71.
42. Reckamp KL, Figlin RA, Burdick MD, et al. CXCR4 expression on circulating pan-cytokeratin positive cells is associated with survival in patients with advanced non-small cell lung cancer [J]. BMC Cancer.2009;9:213.
43. Raman D, Sobolik-Delmaire T, Richmond A. Chemokines in health and disease [J]. Exp Cell Res. 2011;317:575-89.
44. Schall TJ, Proudfoot AE. Overcoming hurdles in developing successful drugs targeting chemokine receptors [J]. Nat Rev Immunol.2011;11:355-63.
45. Balkwill FR. The chemokine system and cancer [J]. J Pathol.2012; 226:148-57.
46. Zlotnik A, Yoshie O. Chemokines:a new classification system and their role in immunity [J]. Immunity.2000;12:121-7.
47. Balkwill F. Cancer and the chemokine network [J]. Nat Rev Cancer.2004;4:540-50.
48. Allavena P, Germano G, Marchesi F, et al. Chemokines in cancer related inflammation [J]. Exp Cell Res.2011;317:664-73.
49. Mantovani A, Savino B, Locati M, et al. The chemokine system in cancer biology and therapy [J]. Cytokine Growth Factor Rev.2010;21:27-39.
50. Balkwill F.The significance of cancer cell expression of the chemokine receptor CXCR4 [J]. Semin Cancer Biol.2004;14:171-9.
51. Zlotnik A, Burkhardt AM, Homey B. Homeostatic chemokine receptors and organ-specific metastasis [J]. Nat Rev Immunol.2011;11:597-606.
52. Baggiolini M, Dewald B, Moser B. Interleukin-8 and related chemotactic cytokines--CXC and CC chemokines [J]. Adv Immunol.1994;55:97-179.
53. Taub DD, Oppenheim JJ. Chemokines, inflammation and the immune system [J]. Ther Immunol. 1994; 1:229-46.
54. Ma Q, Jones D, Springer TA. The chemokine receptor CXCR4 is required for the retention of B lineage and granulocytic precursors within the bone marrow microenvironment [J]. Immunity. 1999;10:463-71.
55. Aiuti A, Webb IJ, Bleul C, et al. The chemokine SDF-1 is a chemoattractant for human CD34+ hematopoietic progenitor cells and provides a new mechanism to explain the mobilization of CD34+ progenitors to peripheral blood [J]. J Exp Med.1997;185:111-20.
56. Bleul CC, Fuhlbrigge RC, Casasnovas JM, et al. A highly efficacious lymphocyte chemoattractant, stromal cell-derived factor 1 (SDF-1) [J]. J Exp Med.1996; 184:1101-9.
57. Ratajczak MZ, Kucia M, Reca R, et al. Stem cell plasticity revisited:CXCR4-positive cells expressing mRNA for early muscle, liver and neural cells 'hide out' in the bone marrow [J]. Leukemia. 2004; 18:29-40.
58. Zou YR, Kottmann AH, Kuroda M, et al. Function of the chemokine receptor CXCR4 in haematopoiesis and in cerebellar development [J]. Nature 1998;393:595-9.
59. Ratajczak MZ, Majka M, Kucia M, et al. Expression of functional CXCR4 by muscle satellite cells and secretion of SDF-1 by muscle-derived fibroblasts is associated with the presence of both muscle progenitors in bone marrow and hematopoietic stem/progenitor cells in muscles [J]. Stem Cells. 2003;21:363-71.
60. Phillips RJ, Mestas J, Gharaee-Kermani M, et al. Epidermal growth factor and hypoxia-induced expression of CXC chemokine receptor 4 on non-small cell lung cancer cells is regulated by the phosphatidylinositol 3-kinase/PTEN/AKT/mammalian target of rapamycin signaling pathway and activation of hypoxia inducible factor-1 alpha [J]. J Biol Chem.2005;280:22473-81.
61. Helbig G, Christopherson KW,2nd, Bhat-Nakshatri P, et al. NF-kappaB promotes breast cancer cell migration and metastasis by inducing the expression of the chemokine receptor CXCR4 [J]. J Biol Chem.2003;278:21631-8.
62. Vicente-Manzanares M, Rey M, Jones DR, et al. Involvement of phosphatidylinositol 3-kinase in stromal cell-derived factor-1 alpha-induced lymphocyte polarization and chemotaxis [J]. J Immunol. 1999; 163:4001-12.
63. Ganju RK, Brubaker SA, Meyer J, et al. The alpha-chemokine, stromal cell-derived factor-1 alpha, binds to the transmembrane G-protein-coupled CXCR-4 receptor and activates multiple signal transduction pathways [J]. J Biol Chem.1998;273:23169-75.
64. Libura J, Drukala J, Majka M, et al. CXCR4-SDF-1 signaling is active in rhabdomyosarcoma cells and regulates locomotion, chemotaxis, and adhesion [J]. Blood.2002;100:2597-606.
65. Tang CH, Tan TW, Fu WM, et al. Involvement of matrix metalloproteinase-9 in stromal cell-derived factor-1/CXCR4 pathway of lung cancer metastasis [J]. Carcinogenesis.2008;29:35-43.
66. Fernandis AZ, Prasad A, Band H, et al. Regulation of CXCR4-mediated chemotaxis and chemoinvasion of breast cancer cells [J]. Oncogene.2004;23:157-67.
67. Janowska-Wieczorek A, Marquez LA, Dobrowsky A, et al. Differential MMP and TIMP production by human marrow and peripheral blood CD34(+) cells in response to chemokines [J]. Exp Hematol.2000;28:1274-85.
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