Redox imaging for breast cancer prognosis

描述(申请人提供)：目前的病理指标不能准确预测个别癌症患者的治疗结果和复发/转移风险。肿瘤线粒体代谢的程度及其在肿瘤内的异质性是癌症进展的关键因素，而现有技术无法充分确定这些因素。能否将肿瘤线粒体代谢及其异质性的影像指标结合到乳腺癌预后模型中，以促进个体化治疗，这是人们非常感兴趣的，也是尚未得到满足的需求。本项目的目的是证明线粒体氧化还原成像，即内源性NADH和氧化黄素蛋白(FP，包括FAD)的荧光成像，在乳腺癌(BC)的治疗中具有预后价值。我们的中心假设是异质性相关线粒体氧化还原成像(HAMRI)指数(FP、NADH和氧化还原比率，例如FP/NADH)可以预测或增加预测BC预后的价值。在第一个目标中，我们将确定线粒体氧化还原成像指标对BC患者预后的预测。我们将开发一种光学成像针头设备，并在活体活检过程中获得实时的氧化还原成像测量。我们将检验假设1a，即HMARI指数可以区分癌(浸润性和原位)、癌前病变和良性/正常乳腺组织。我们还将对自2008年以来收集的临床BC冰冻标本进行回顾性氧化还原成像。我们将检验假设1b，即Hamri指数可以预测结直肠癌局部复发和转移的风险，并有可能为当前的临床预后模型增加价值。此外，我们将测试假设1c，即Hamri可以预测节点状态。在第二个目标中，我们将在小鼠和细胞模型中确定预测氧化还原成像指标的代谢基础。我们将检验假设2a：1)Hamri指数与通过对转移灶中红色荧光蛋白的荧光成像测量的BC小鼠异种移植瘤体内转移潜能相关；2)Hamri指数与BC细胞系体外侵袭潜能相关。我们将用不同的生化试剂处理癌细胞，以改变线粒体的氧化还原状态。我们将检验假设2b，即线粒体氧化还原状态的变化与BC侵袭/转移潜能的变化相关。我们还将确定这些变化是否与自由基水平和氧化损伤的变化有关。该项目的预期结果包括：1)建立快速(实时可实现)、低成本和独立的预测结直肠癌预后的Hamri指数；2)建立线粒体氧化还原状态作为结直肠癌进展到转移的关键因素。这些新的结果将对乳腺癌的治疗产生重大的临床影响，并可推广到其他不同形式的癌症。我们相信，随着进一步的发展，这项研究有可能重塑目前的BC预后模型，从而为乳腺癌的治疗和监测开辟新的、新的范式。

DESCRIPTION (provided by applicant): Current pathological indices cannot accurately predict the treatment outcome and the risk of recurrence/metastasis for individual cancer patients. The extent of tumor mitochondrial metabolism and its heterogeneity within the tumor are crucial factors in cancer progression that cannot be adequately determined with existing techniques. There are great interests and unmet needs in testing whether the combination of imaging indices of the tumor mitochondrial metabolism and its heterogeneity can be incorporated into the breast cancer prognostic models to facilitate individualized treatment. The objective of this project is to demonstrate that the mitochondrial redox imaging, i.e., fluorescence imaging of endogenous NADH and oxidized flavoproteins (Fp including FAD), has prognostic value in managing breast cancer (BC). Our central hypothesis is that the heterogeneity-associated mitochondrial redox imaging (HAMRI) indices (Fp, NADH and the redox ratios, e.g., Fp/NADH) can predict or add value for predicting BC prognosis. In the first aim, we will identify the mitochondrial redox imaging indices for BC prognosis in patients. We will develop an optical-imaging needle device and obtain real-time redox imaging measurements in vivo during the biopsy procedures. We will test hypothesis 1a that the HMARI indices can differentiate among cancerous (invasive vs in situ), premalignant and benign/normal breast tissues. We will also conduct redox imaging retrospectively on clinical BC frozen specimens collected since 2008. We will test hypothesis 1b that the HAMRI indices can predict the risk of local recurrence and metastasis of BC and have the potential to add value to current clinical prognostic model. Furthermore, we will test hypothesis 1c that HAMRI can predict nodal status. In the second aim, we will identify the metabolic basis for prognostic redox imaging indices in mouse and cell models. We will test hypothesis 2a that 1) the HAMRI indices correlate with the metastatic potential of BC mouse xenografts in vivo measured by fluorescence imaging of red fluorescence proteins in the metastases, and 2) the HAMRI indices correlate with the invasive potentials of BC cell lines in vitro. We will treat cancer cells with different biochemical reagents to modify th mitochondrial redox state. We will test hypothesis 2b that changes of the mitochondrial redox state correlate with the changes of invasive/metastatic potential of BC. We will also determine if these changes are associated with changes in the levels of free radicals and oxidative damages. Anticipated outcomes from this project include: 1) Establish the HAMRI indices as rapid (real time achievable), low-cost, and independent predictors of BC prognosis; 2) Establish the mitochondrial redox state as a key factor in BC progression to metastasis. These novel results will have significant clinical impact on breast cancer management and can be extended to other diverse forms of cancers. We believe that this research, with further developments, has the potential to reshape the current BC prognostic models and therefore, open new, novel paradigms in the treatment and monitoring of breast cancer.