Defining Signatures of Breast Cancer Cells by HRMAS MRS

描述（由申请人提供）：乳腺癌是最常见的恶性肿瘤，也是美国女性癌症死亡的第二大原因。乳腺X线摄影有助于早期发现乳腺肿瘤，从而为乳腺肿瘤提供新的治疗方法，但也产生了争议。现在，许多患者在疾病的早期诊断，无症状阶段可能是保乳治疗（BCT）的候选人，但如果不及时进行根治性干预（乳房切除术，化疗和放疗），有些患者将经历病态的疾病过程并死亡。基于形态学的组织病理学迄今已有效地评估乳腺癌患者，特别是在以乳房切除术为主的年龄，但它是不敏感的指导治疗计划与BCT。除了形态学评估外，现在还需要一种直接评估个体肿瘤生物学行为并预测潜在侵袭性的方法来优化乳腺癌管理。为了实现这一点，我们将测试一个离体光谱方法识别细胞代谢签名的功效。通过为乳腺癌的生化诊断提供新的范例，该方法可以在BCT时代辅助乳腺肿瘤的诊断和鉴定。我们将用高分辨率魔角旋转（HRMAS）质子磁共振波谱（1HMRS）量化乳腺癌发生和进展中的细胞代谢变化。HRMAS 1HMRS可以测量完整人体组织标本中的细胞代谢物，同时保留组织病理学结构。我们将测试HRMAS 1HMRS定量乳腺癌代谢物的能力，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、分级和组织病理学阶段定义和评估乳腺癌的代谢特征，使用激光捕获显微切割（LCM）在细胞水平上对肿瘤特征进行分子生物学分析，逆转录聚合酶链反应（RT-PCR），并建立生化数据库，帮助预测肿瘤病理和患者的结果，独立于病理。首先，我们将用HRMAS 1HMRS定量新手术标本以及储存的冷冻组织的组织代谢物。然后将观察到的与组织病理学相关的代谢物用于创建乳腺癌代谢物特征的数据库。这些签名应该是有用的，在临床护理的妇女与乳腺癌，确定为候选人的乳房保留治疗侵袭性较低的肿瘤。

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.