Microbial and host biomarker development for detection and prognosis of early stage non-small cell lung cancer

用于早期非小细胞肺癌检测和预后的微生物和宿主生物标志物开发

• 批准号: 10701254
• 负责人: HARVEY Ira PASS
• 金额: $ 70.34万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-04 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10701254
• 关键词: Applications Grants; Bioinformatics; Biological Assay; Biological Markers; Blinded; Blood; Blood specimen; Cancer Etiology; Cancer Patient; Cancer Prognosis; Cessation of life; Chest; Circulation; Clinical; Collaborations; Culture-independent methods; Custom; DNA; Data; Detection; Development; Diagnosis; Disease; Early Detection Research Network; Early Diagnosis; Evaluation Studies; Excision; Health; Histologic; Imaging Techniques; Industrialization; Investigation; Laboratories; Lung; Lung nodule; Malignant Neoplasms; Malignant neoplasm of lung; Measurement; Metagenomics; Modeling; Nature; Nodule; Non-Malignant; Non-Small-Cell Lung Carcinoma; Operative Surgical Procedures; Outcome; Patients; Phase; Procedures; Prognosis; Publishing; RNA; Recurrence; Recurrent Malignant Neoplasm; Recurrent disease; Research Design; Resectable; Resources; Risk; Sampling; Specimen; TNM; Testing; Thoracotomy; Tissue Sample; Treatment Failure; Work; accurate diagnosis; biobank; biological specimen archives; biomarker development; cancer diagnosis; cancer recurrence; clinical biomarkers; cohort; diagnostic signature; diagnostic strategy; effective therapy; experience; feature selection; genomic signature; high risk; improved; metabolome; metabolomics; metagenome; microbial; microbial genomics; microbial products; microbial signature; microbiome; mortality; multiple omics; nano-string; next generation sequencing; novel; predictive marker; predictive signature; prevent; prognostic signature; prospective; respiratory microbiota; sample collection; targeted biomarker; transcriptome; transcriptomics

Project summary (OVERALL) Lung cancer remains the leading cause of all cancer mortality. Improved imaging techniques enable the detection of lung cancer at earlier stages, yet a large number of patients with non-malignant lung nodules are frequently subjected to invasive diagnostic approaches. Even though surgical removal of early stage non-small cell lung cancer (NSCLC) is the most effective therapy, post-surgical recurrence of NSCLC remains a significant problem as survival. Currently there are no clinically useful biomarkers that can accurately diagnose the indeterminate nodule or identify those patients destined to have recurrence of cancer after successful surgical removal. Recently, the use of culture-independent techniques to characterize the microbiome by us and others has led to identification of microbial signatures associated with lung cancer diagnosis and prognosis among a cohort with a wide range of disease stages. Preliminary metagenomic data obtained in collaboration with Micronoma using blood samples of our NYU cohort have identified microbial signatures in systemic circulation associated with early-stage NSCLC diagnosis. Further, using a NanoString platform we have identified circulating RNA signatures predictive of early-stage NSCLC diagnosis. In addition, our preliminary data shows that lower airway signatures can be used to predict prognosis post-surgical removal of early stage cancer. These data suggest that microbial and host genomic signatures could be leveraged to develop useful biomarkers in early-stage NSCLC. The addition of metabolite measurements could further contribute to this predictive power since those are end products of microbial and host functions. Under this BCC application we will first identify top microbial/host biomarkers that predict early-stage NSCLC diagnosis and prognosis using blood and lower airway samples from a cohort of patients with lung nodules and a presumed surgical clinical Stage I (<3cm) but with a final histological diagnosis of early-stage NSCLC (TNM  IIIA) or non-NSCLC nodules. We will implement cutting edge bioinformatic approaches to identify the most promising targets from these unbiased omic approach (metagenome, metabolome and transcriptome) which will guide the development of targeted approaches that to be validated under the Biomarker Reference Laboratory. These targeted approaches will include the development of targeted microbial DNA next generation sequencing, targeted metabolite measurement and custom-made NanoString panels as CLIA level assays, internally and externally validated, that will identify patients at highest risk for NSCLC diagnosis and recurrence after complete surgical resection.

项目总结(总体) 肺癌仍然是所有癌症死亡的首要原因。改进的成像技术使检测成为可能 肺癌的早期，然而大量的非恶性肺结节患者经常 受到侵入性诊断方法的影响。即使手术切除早期非小细胞肺 肿瘤(NSCLC)是目前最有效的治疗方法，但NSCLC术后复发仍是一个重要问题 作为生存。目前还没有临床上有用的生物标志物可以准确地诊断不确定的 或确定那些在手术切除成功后注定会复发的癌症患者。 最近，我们和其他人使用与培养无关的技术来表征微生物组，这导致了 与肺癌诊断和预后相关的微生物特征在一群肺癌患者中的鉴定 疾病的各个阶段。与Microronoma合作获得的初步元基因组数据 我们纽约大学队列的血液样本已经在体循环中发现了与 早期非小细胞肺癌诊断。此外，使用纳米串平台，我们已经鉴定了循环RNA 预示早期非小细胞肺癌诊断的征象。此外，我们的初步数据显示，下呼吸道 信号可以用来预测早期癌症手术切除后的预后。这些数据表明 微生物和宿主基因组特征可以在早期阶段被利用来开发有用的生物标志物 非小细胞肺癌。添加代谢物测量可能进一步有助于这种预测能力，因为 是微生物和宿主功能的最终产物。在此密件抄送申请下，我们将首先确定 利用血液和下呼吸道预测早期非小细胞肺癌诊断和预后的微生物/宿主生物标志物 样本来自一组肺结节患者，推测为外科临床I期(&lt；3 cm)，但有 早期非小细胞肺癌(IIIA)或非小细胞肺癌结节的最终组织学诊断。我们将实施采伐 边缘生物信息学方法从这些无偏的基因组方法中识别最有希望的目标 (元基因组、代谢组和转录组)，它将指导开发有针对性的方法，以 在Biomarker参考实验室下进行验证。这些有针对性的方法将包括 开发靶向微生物DNA下一代测序、靶向代谢物测量和 定制的纳米串面板，作为CLIA级别的分析，内部和外部验证，将确定 NSCLC确诊和完全手术切除后复发风险最高的患者。