Biomarkers in Cancer Diagnosis, Prognosis and Therapeutic Outcome

项目1A：为了研究癌变过程中肺微生物组的粘膜相关改变，我们利用NCI-MD病例对照研究并测序了V3-V5 16S rRNA基因。候选细菌身份在癌症基因组图谱中的肺癌样本中得到验证。我们检测了正常健康组织与NCI-MD非肿瘤邻近组织和肿瘤组织样本内（α多样性）和样本间（β多样性）的生态多样性。我们发现肺癌患者的多样性和丰富性增加，这可能与肺微环境的变化有关，表明获得了体细胞突变或免疫系统的改变。我们确定了两个能够从立即尸检对照中分类肺癌病例的属，Variovorax和Streptococcus，并且可能是肺癌风险的生物标志物或与癌症的发生和进展相关。与来自同一个体的非肿瘤组织相比，肿瘤中的Variovorax丰度更高，这一发现在更大的TCGA数据集中得到了验证。使用Resphera Insight来确定我们的16S rRNA基因读数，我们能够推定该物种为酸虫。对切除的肺肿瘤进行荧光原位杂交（FISH）分析，进一步证实了肿瘤组织中酸卵黄的存在。Acidovorax定位于肿瘤细胞内。在I期肺癌中，Variovorax的丰度较高，链球菌的丰度较低，这表明这些可能是癌症风险的生物标志物或与癌症发生有关。酸ovorax可以区分肺癌、腺癌（AD）和鳞状细胞癌（SCC）的组织学亚型。我们假设scc相关的微生物类群在TP53突变的肿瘤中更丰富。我们研究了TP53突变、微生物分类群和肿瘤组织学之间的关系。特定的微生物类群在TP53突变的SCC中更为丰富，而AD与TP53突变之间没有发现关联模式。这些数据支持这样的假设，即在TP53突变的肿瘤中，scc相关的分类群更容易进入肿瘤微环境。液滴数字PCR （ddPCR）方法将实现物种水平的验证和定量。我们正在开发从肺肿瘤中鉴定细菌分离物的方法，并正在研究粘膜相关肺微生物组的作用，其与炎症和肺癌代谢组的关系，以及这种关系的潜在机制。我们正在NCI无菌小鼠设施和抗生素治疗的SPF小鼠中使用K-ras/p53R172H小鼠模型研究特定细菌物种之间的机制关系。项目1B：我们开发了甲基化特异性ddPCR来检测和量化罕见的甲基化事件，以研究液体活检中的生物标志物。ddPCR检测可以检测到30个甲基化启动子DNA的单倍体基因组等量物，并计数单个甲基化等位基因的存在率为0.2%。还观察到肿瘤和邻近组织之间甲基化水平的差异。因此，我们已经建立了一个强大的和超灵敏的方法来标准化测定DNA启动子甲基化状态。我们已经开发了一种使用FFPE肿瘤样本进行肺癌患者预后分类的ddPCR检测。我们获得的证据表明，在晚期肺癌患者的ctDNA中可以检测到甲基化DNA，并且正在继续优化I期肺癌患者的检测条件。项目1C：另一个项目是评估尿液和血液肿瘤代谢物液体活检方法在早期发现肺癌和肝癌以及评估患者预后方面的作用。在国防部（DoD）临床探索奖的支持下，我们正在研究尿代谢物在军事人员早期肺癌检测（DECAMP）联盟中的预测能力。在这个正在进行的收集中，我们收到了病例和对照，包括在入组前一年内在胸部CT上发现大小为7- 30mm的不确定肺结节的既往或当前吸烟者。然后对他们进行长达2年的标准护理，直到最终诊断为肺癌或良性肺部疾病。同事们已经证明，在吸烟者的支气管上皮细胞和更远的鼻上皮中测量的基因表达特征反映了肺癌的存在，这与香烟烟雾引起的分子“损伤场”的存在一致。我们的代谢组学分析将与这些患者的支气管和鼻上皮细胞分析进行比较和整合。我们已经收到了NLST LDCT组的肺癌病例和对照组，正在测量这些受试者尿液中的4种代谢物，以回答上述问题。我们正在评估肺癌生物标本资源网络（LCBRN）样本中术后尿肿瘤代谢物CR和NANA是否降低。我们分析了46例患者手术前、6个月、12个月和24个月的尿液样本，以及随访的复发和生存数据。我们还收集了11例患者术后20个月和21例患者术后24个月的尿液标本。我们已经证明，这些代谢产物的尿液水平升高与肺癌复发有关。尿代谢物与肝癌诊断相关，并在NCI-UMD和TIGER LC队列中得到验证。我们正在研究肺癌研究中发现的4种尿液代谢物是否也能诊断肝癌。我们最初与王欣、LHC和楚拉蓬研究所合作，在95例肝细胞癌（HCC）病例中进行了一项试点研究。对照和高风险受试者的年龄、性别和种族与病例的频率相匹配。本研究表明，与人群对照相比，先前确定在肺癌中增加的尿肿瘤代谢物在HCC患者中也升高，更重要的是，与高危人群相比。接下来，我们评估了在独立的泰国肝癌基因组学和表达研究计划（TIGER-LC）队列中是否观察到相同的结果。我们假设除了HCC外，这4种代谢物也在胆管癌（CCA）中升高。本分析结果表明，与CCA和HCC各自的高风险受试者和未受影响的对照组相比，CCA和HCC的尿肿瘤代谢物显著升高。经年龄、性别、HBV和HCV状态调整后的多变量分析显示，与高危人群相比，4种代谢物诊断HCC的预测能力较高。在CCA中观察到类似的结果。此外，与HCC相比，CCA中3种代谢物（肌酸核糖体、n -乙酰神经氨酸和代谢物561+）的水平显著高于HCC。与临床使用的肿瘤标志物CA19-9相比，尿4代谢物谱显示出诊断CCA的高预测能力，而它们的组合导致分类器的显著改进，指出了这种类型的液体活检的临床应用。

Project 1A: To investigate mucosa-associated alterations of the lung microbiome during carcinogenesis, we utilized the NCI-MD case-control study and sequenced the V3-V5 16S rRNA gene. Candidate bacterial identities were validated in lung cancer samples from The Cancer Genome Atlas. We examined the ecological diversity within samples (alpha diversity) and between samples (beta diversity) of normal healthy tissues and NCI-MD non-tumor adjacent and tumor tissues. We found increasing diversity and richness in subjects with lung cancer, which could be related to changes in the lung microenvironment, indicating acquisition of somatic mutations or alterations in the immune system. We identified two genera that were able to classify lung cancer cases from immediate autopsy controls, Variovorax and Streptococcus, and may be biomarkers of lung cancer risk or associated with cancer initiation and progression. Variovorax abundance was higher in tumor compared to non-tumor tissues from the same individual, a finding that was validated in the larger TCGA dataset. Using the Resphera Insight to speciate our 16S rRNA gene reads, we were able to putatively identify the species as acidovorax. Fluorescent in situ hybridization (FISH) analysis of resected lung tumors further confirmed the presence of acidovorax in tumor tissue. Acidovorax was localized intracellularly in tumor cells. A higher abundance of Variovorax and lower abundance of Streptococcus was seen in Stage I lung cancer, suggesting these maybe biomarkers of cancer risk or associated with cancer initiation. Acidovorax species could differentiate between histological subtypes of lung cancer, adenocarcinoma (AD) and squamous cell carcinoma (SCC). We hypothesized that SCC-associated microbial taxa would be more abundant in tumors with TP53 mutations.. We investigated the association between TP53 mutations, microbial taxa, and tumor histology. Specific microbial taxa were more abundant in SCC with TP53 mutations, whereas no pattern of association was found among AD with TP53 mutations. These data support the hypothesis that in tumors with TP53 mutations, SCC-associated taxa gain greater access to the tumor microenvironment.. Species-level validation and quantification will be achieved by droplet digital PCR (ddPCR) methods. We are developing methods to identify bacterial isolates from lung tumors and are examining the role of the mucosa-associated lung microbiome, its relationship to inflammation and the metabolome in lung cancer, and the mechanisms underlying this relationship. We are investigating these mechanistic relationship between specific bacterial species using a K-ras/p53R172H mouse model in the NCI gnotobiotic mouse facility and in the antibiotic-treated SPF mice. Project 1B: We developed methylation-specific ddPCR to detect and quantify rare methylation events to investigate biomarkers in liquid biopsies. The ddPCR assay could detect as few as 30 haploid genome-equivalents of methylated promoter DNA, and count a single methylated allele present at 0.2%. Differences in methylation levels between tumors and adjacent tissues were also observed. Therefore, we have established a robust and ultrasensitive method for standardized determination of DNA promoter methylation status. We have developed a ddPCR assay for prognostic classification of lung cancer patients using FFPE tumor samples. We obtained evidence that methylated DNA is detectable in ctDNA from lung cancer patients at advanced stage, and are continuing to optimize conditions for detection in patients with Stage I lung cancer. Project 1C: Another project was to evaluate urinary and blood tumor metabolite liquid biopsy approaches for early detection of lung and liver cancer and for assessing patient outcome. In a collaboration supported by the Department of Defense (DoD) Clinical Exploration Award, we are in the process of investigating the predictive capability of urinary metabolites in the Detection of Early lung Cancer among Military Personnel (DECAMP) consortium. In this ongoing collection, we have received cases and controls consisting of former or current smokers with an indeterminate pulmonary nodule 7-30 mm in size on chest CT within the year prior to enrollment. They were then followed with standard of care for up to 2 years until a final diagnosis of lung cancer or benign lung disease was made. Colleagues have shown that gene expression features measured in bronchial epithelial cells and the more distant nasal epithelium of smokers reflect the presence of cancer in the lung, consistent with the presence of a molecular "field of injury" caused by cigarette smoke. Our metabolomic analysis will be compared to, and integrated with, the analysis of bronchial and nasal epithelial cells from these patients. We have received lung cancer cases and controls from the LDCT arm of the NLST and are in the process of measuring 4 metabolites in the urine of these subjects to answer the aforementioned questions. We are in the process of evaluating whether urinary tumor metabolites CR and NANA decrease after surgery in the Lung Cancer Biospecimen Resource Network (LCBRN) samples. We are analyzing pre-, 6-, 12- and 24-months post-surgery urine specimens from 46 patients, with follow-up recurrence and survival data. We also obtained 20-month post-surgery urine specimens from 11 patients, and 24-month from 21 patients. We have demonstrated elevated urinary levels of these metabolites are associated with lung cancer recurrence. Urinary metabolites are associated with liver cancer diagnosis and validated in the NCI-UMD and TIGER LC cohorts. We are investigating if the 4 urinary metabolites discovered in our lung cancer studies are also diagnositic of liver cancer. We initially conducted a pilot study in 95 hepatocellular carcinoma (HCC) cases, in collaboration with Xin Wang, LHC and Chulabhorn Research Institute. Controls and high-risk subjects were frequency matched to cases on age, gender and race. This study showed that urinary tumor metabolites previously identified as increased in lung cancer are also elevated in HCC cases compared to population controls and, more importantly, high risk subjects. Next, we evaluated whether the same results were observed in the independent Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC) cohort. We hypothesized that the 4 metabolites are also elevated in cholangiocarcinoma (CCA) in addition to HCC. The results of this analysis indicated that urinary tumor metabolites are significantly elevated in CCA and HCC when compared to their respective high risk subjects and unaffected controls.Multivariable analysis adjusted for age, gender, HBV and HCV status indicates that the predictive ability of 4 metabolites to diagnose HCC was high when compared to high-risk subjects. Similar results were observed in CCA. Additionally, levels of 3 metabolites (creatine riboside, N-acetyulneuraminic acid and metabolite 561+), were significantly higher in CCA when compared to HCC. Urinary 4-metabolite profile shows a high predictive ability to diagnose CCA when compared to a clinically utilize tumor marker CA19-9, while their combination leads to a significantly improved classifier pointing to a clinical utility of this type of liquid biopsy.