Defining Signatures of Breast Cancer Cells by HRMAS MRS

描述(申请人提供)：乳腺癌是美国女性最常见的恶性肿瘤，也是导致癌症死亡的第二大原因。乳房X光检查有助于早期发现乳腺肿瘤，从而有助于新的治疗方法，但也产生了争议。现在许多患者在疾病的非常早期、无症状阶段被诊断出来，可能是保乳治疗(BCT)的候选对象，但如果不及时进行根治性干预(乳房切除、化疗和放射治疗)，一些患者将经历病态病程并死亡。到目前为止，基于形态的组织病理学在评估乳腺癌患者方面提供了有效的服务，特别是在以乳房切除术为主的年龄，但它对指导BCT的治疗计划不敏感。除了形态评估外，现在需要一种直接评估单个肿瘤的生物学行为并预测潜在侵袭性的方法来优化乳腺癌治疗。为了实现这一点，我们将测试一种识别细胞代谢特征的体外光谱方法的有效性。通过为乳腺癌的生化诊断提供一种新的范式，该方法可以辅助BCT时代的乳腺肿瘤的诊断和预后。我们将使用高分辨率魔角旋转(HRMAS)质子磁共振波谱(1HMRS)来量化乳腺癌发生和发展过程中细胞代谢的变化。HRMAS 1HMRS可以测量完整的人体组织标本中的细胞代谢物，同时保留组织病理结构。我们将测试HRMAS 1HMRS对乳腺癌代谢物进行量化的能力，将获得的代谢浓度与在相同完整组织样本中测量的组织病理学特征相关联，根据类型、分级和组织病理分期定义和评估乳腺癌的代谢特征，使用激光捕获显微切割(LCM)、逆转录聚合酶链式反应(RT-PCR)在细胞水平上对肿瘤特征进行分子生物学分析，并建立有助于预测肿瘤病理和患者预后的生化数据库，而不依赖于病理。最初，我们将使用HRMAS 1HMRS对新的手术标本以及储存的冰冻组织的组织代谢物进行量化。观察到的与组织病理学相关的代谢物将被用于创建乳腺癌代谢物特征的数据库。通过识别侵袭性较小的肿瘤作为保乳治疗的候选对象，这些特征应该在乳腺癌女性的临床护理中有用。

DESCRIPTION (provided by applicant):Breast cancer is the most commonly diagnosed malignancy and second leading cause of cancer death among American women. Mammography has contributed to early detection, and thus new treatments, of breast tumors, but has also generated controversies. Many patients now diagnosed at very early, symptom free stages of the disease may be likely candidates for breast-conserving treatment (BCT), but some will experience a morbid disease course and die if not promptly treated with radical intervention (mastectomy, chemo- and radiation therapies). Morphology-based histopathology has to date served effectively in assessing breast cancer patients, particularly in the age dominated by mastectomy, but it is insensitive in guiding treatment plans with BCT. In addition to morphological evaluation, a method that directly evaluates the biological behavior of individual tumors and predicts potential aggressiveness is now needed for optimal breast cancer management. To achieve this, we will test the efficacy of an ex vivo spectroscopic method of identifying cellular metabolic signatures. By providing a new paradigm for the biochemical diagnosis of breast cancer, this method can assist in the diagnosis and prognostication of breast tumors in the era of BCT. We will quantify cellular metabolic changes in the development and progression of breast cancer with high-resolution magic angle spinning (HRMAS) proton magnetic resonance spectroscopy (1HMRS). HRMAS 1HMRS can measure cellular metabolites in intact human tissue specimens, while preserving histopathological structures. We will test the ability of HRMAS 1HMRS to quantify breast cancer metabolites, correlate metabolic concentrations obtained with histopathological features measured in the same intact tissue samples, define and evaluate metabolic signatures for breast cancer according to type, grade and histopathologic stage, perform molecular biology analyses of tumor signatures at the cellular level with laser capture microdissection (LCM), reverse transcription polymerase chain reaction (RT-PCR), and establish biochemical databases that help predict tumor pathologies and patient outcome, independently of pathology. Initially, we will quantify tissue metabolites of new surgical specimens, as well as stored frozen tissues, with HRMAS 1HMRS. Observed metabolites that correlate with histopathology will then be used to create a database of breast cancer metabolite signatures. These signatures should be useful in clinical care of women with breast cancer by identifying less aggressive tumors as candidates for breast-conserving treatment.