Immune Profile Analysis of Tumor-Draining Lymph Nodes in Breast Cancer

乳腺癌肿瘤引流淋巴结的免疫特征分析

• 批准号: 8061630
• 负责人: Peter Poon-Hang Lee
• 金额: $ 11.61万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2012-07-10
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8061630
• 关键词: Axillary lymph node group; CD4 Positive T Lymphocytes; Cancer Patient; Cells; Characteristics; Clinical; Dendritic Cells; Diagnostic Neoplasm Staging; Disease-Free Survival; Goals; Helper-Inducer T-Lymphocyte; Hematoxylin and Eosin Staining Method; Histology; Immune; Investigation; Lead; Malignant Neoplasms; Methods; Modeling; Nature; Neoplasm Metastasis; Nodal; Outcome; Pathologic; Patients; Population; Prognostic Factor; Recurrence; Relapse; Research Personnel; Sentinel; Sentinel Lymph Node; Staging; Staining method; Stains; Stratification; Survival Rate; T-Lymphocyte; Testing; Tumor Cell Invasion; Tumor stage; Work; base; clinical practice; follow-up; high risk; insight; lymph nodes; malignant breast neoplasm; novel strategies; novel therapeutics; prognostic; prognostic indicator; tool; tumor

DESCRIPTION (provided by applicant): Lymph node metastasis is well established as one of the strongest prognostic indicators of clinical outcome for patients with breast cancer. Current clinical practice involves only histological examination of nodes for the presence or absence of tumor, ignoring the immunological nature of lymph nodes in cancer. We hypothesize that immune profile analysis of tumor-draining lymph nodes (TDLN) may be a more sensitive and earlier method of detecting metastasis, and may provide additional information on clinical outcome. In preliminary studies, we analyzed the lymph node immune profiles in 77 breast cancer patients with tumor-involved sentinel lymph nodes (SLN) and 5-year clinical follow-up. We found significant perturbations in the immune profiles of all tumor-involved sentinel (SLN) and non-sentinel axillary lymph nodes (NSALN), with decreases in CD4 helper T cell and CD1a dendritic cell populations identifying nodal metastasis with an average accuracy of 95% and sensitivity of 96% from a single nodal section - a 20% greater accuracy compared to multilevel hematoxylin and eosin staining. Intriguingly, we observed immune profile changes even in some tumor-free NSALNs, suggesting that such changes may precede metastasis. Immune profile changes within NSALNs were highly predictive of disease-free survival and independent of tumor invasion status of such nodes. Stratification of patients with T2 tumors by NSALN CD4 showed a 5-year DPS rate of 88% for patients with a high CD4 population, versus 0% for patients with a low CD4 population (p=0.007) - this is superior to other clinical or pathologic factors. The goal of this proposal is to expand on these findings to develop a new clinical prognostic tool for breast cancer management based on immune analysis of TDLNs. The central hypothesis that we will test is that immune profile analysis of SLN and NSALN adds substantial prognostic power to tumor invasion status of such nodes in predicting clinical outcome in early-stage breast cancer patients. We propose to confirm the prognostic clinical value (5-yr DPS) of NSALN immune analysis (T and dendritic cells) in SLN+ patients with a larger, multi-center population, and to investigate clinical correlation with other immune cell populations (Aim 1), to assess the prognostic clinical value of immune analysis of tumor-free SLN (Aim 2), and to combine tumor invasion status and immune profile of SLN and NSALN together as a comprehensive predictor of clinical outcome (Aim 3). If successful, this work will establish immune profile analysis of SLN and NSALN as a useful adjunct to tumor invasion status as a prognostic factor to predict breast cancer patients likely to relapse. In addition, we will identify a more complete picture of immune cell populations impacted by breast cancer within SLN and NSALN that could lead to mechanistic insights and novel therapeutic strategies. Lastly, this work may support a novel approach to TDLN analysis in breast cancer - to remove an optimal, minimum number of SLN and NSALN for tumor and immune profile analysis as a comprehensive predictor of clinical outcome.

描述（由申请人提供）：淋巴结转移已被确定为乳腺癌患者临床预后最强的预后指标之一。当前的临床实践仅涉及对肿瘤存在或不存在的节点的组织学检查，忽略了癌症中淋巴结的免疫学性质。我们假设对肿瘤淋巴结（TDLN）的免疫概况分析可能是一种更敏感的检测转移方法，并且可能提供有关临床结果的其他信息。在初步研究中，我们分析了77名乳腺肿瘤卫星淋巴结淋巴结（SLN）和5年临床随访的乳腺癌患者的淋巴结免疫谱。我们发现，所有涉及肿瘤的前哨（SLN）和非塞替尼腋窝淋巴结（NSALN）的免疫特征的显着扰动，CD4辅助T细胞和CD1A树突状细胞种群的降低降低，与95％的平均准确度相结合的95％nod criptive-nodal转移量的平均精度与95％的平均准确性 - 与95％的平均精度相结合 - 苏木精和曙红染色。有趣的是，我们观察到即使在某些无肿瘤的NSALN中，免疫谱也发生了变化，这表明这种变化可能在转移之前。 NSALNS内的免疫谱变化高度预测了无疾病的生存，并且独立于此类淋巴结的肿瘤侵袭状态。 NSALN CD4对T2肿瘤患者的分层显示，CD4人群较高的患者的5年DPS率为88％，而CD4人群较低的患者为0％（P = 0.007） - 这比其他临床或病理因素优于其他临床或病理因素。该提案的目的是扩大这些发现，以开发基于TDLN的免疫分析的乳腺癌管理的新临床预后工具。我们将测试的中心假设是，SLN和NSALN的免疫概况分析为此类淋巴结的肿瘤侵袭状态增加了预后能力，以预测早期乳腺癌患者的临床结果。 We propose to confirm the prognostic clinical value (5-yr DPS) of NSALN immune analysis (T and dendritic cells) in SLN+ patients with a larger, multi-center population, and to investigate clinical correlation with other immune cell populations (Aim 1), to assess the prognostic clinical value of immune analysis of tumor-free SLN (Aim 2), and to combine tumor invasion status and immune profile of SLN and NSALN一起作为临床结果的全面预测指标（AIM 3）。如果成功，这项工作将建立对SLN和NSALN的免疫概况分析，是肿瘤入侵状态的有用辅助，是预测可能复发的乳腺癌患者的预后因素。此外，我们将确定SLN和NSALN内受到乳腺癌影响的免疫细胞群体的更完整的情况，这可能会导致机械洞察力和新颖的治疗策略。最后，这项工作可能支持一种新型的乳腺癌TDLN分析方法 - 以去除最佳的，最少的SLN和NSALN，用于肿瘤，并作为临床结果的全面预测指标。