Enhancing prognostic power of tumor grade by revisiting Ki67-mitosis relationship

 描述（由申请人提供）：临床实践中常用的乳腺癌预后和预测分子标志物包括Ki 67、ER、PR、Her 2和有丝分裂指数（MI）。在这些标志物中，Ki 67增殖指数（KI）是一种通用的独立预后标志物，MI是当前肿瘤分级系统的组成部分。不幸的是，这些标志物还没有达到足够的可重复性和可靠性，以准确地预测疾病的预后和侵略性。目前可用的临床预测指标（KI和MI）的风险预测能力有限，这是阻碍准确患者分层以做出最佳治疗决策的关键障碍。在诊断病理学中，KI和MI基本上来自非重叠的显微镜视野，并且在不同的尺度上，因此它们是不可比较的，并且丢失了有价值的信息。我们的目标是将肿瘤的KI和MI置于同一测量尺度上，以便更准确地利用其真实的预后潜力，并增强肿瘤分级的风险预测能力。我们的中心假设预测，低级别肿瘤内的有丝分裂频率驱动其获得高度侵袭性和恶性表型的能力。我们提出了一种新的方法，合理地整合KI和MI定义一个组合的“有丝分裂频率风险指数”（MFRI），这可能是一个更好的临床指标和预测转移风险与低级别肿瘤，比MI。创新在于通过使用抗Ki 67和抗磷酸组蛋白H3抗体（染色有丝分裂细胞）对KI和MI进行免疫荧光共染色来从同一视野提取KI和MI，以收集额外的相关信息层，这可以增强等级的预后能力。我们方法的意义和影响在于MFRI的广泛临床适用性，它将取代肿瘤分级系统中的MI，并在各种肿瘤类型中可重复且可靠地预测转移风险。我们的新范式，即循环细胞间有丝分裂频率（MFRI）在低级别肿瘤中是比MI更好的预测因子，这是一个突破性的概念，并在肿瘤行为的早期预测中具有转化前景。AIM 1将涉及对5000例乳腺癌患者的病历进行回顾性审查，以（i）评价不同级别乳腺肿瘤中KI和MI之间的变量相关性，以及（ii）确定用平均MI/平均KI比值替代MI可提高肿瘤级别的预后准确性。AIM 2将确定1级（n=200）和2级（n=200）乳腺癌样本的大型队列的有丝分裂频率风险指数（MFRI），并检查其与临床结局的相关性。该项目的成功完成可能会改变目前与风险预测相关的临床实践范式，帮助将1级和2级肿瘤患者分层为低风险和高风险类别，以进行个性化治疗。新的风险指数MFRI也可能提供有见地的线索，解释为什么一些低级别的非侵袭性乳腺癌会转化为具有转移到远处的能力的侵袭性肿瘤。

 DESCRIPTION (provided by applicant): Prognostic and predictive molecular markers for breast cancer commonly used in clinical practice include Ki67, ER, PR, Her2, and mitotic index (MI). Of these markers, Ki67 proliferation index (KI), is a universal independent prognostic marker, and MI is an integral element of the current tumor grading system. Unfortunately, these markers have not achieved sufficient reproducibility and reliability to accurately predict disease prognosis and aggressiveness. The limited risk-predictive power of currently-available clinical prognosticators (KI and MI) is the critical barrier preventing accurate patient stratification for optimal therapeutic decision-making. In diagnostic pathology, KI and MI are essentially derived from non-overlapping microscopic fields and are on disparate scales, owing to which they are incomparable and valuable information is lost. Our objective is to bring a tumor's KI and MI on the same measurement scale so as to more accurately harness their true prognostic potential and augment the risk-predictive power of tumor grade. Our central hypothesis predicts that the mitotic frequency within a low-grade tumor drives its ability to acquire highly aggressive and malignant phenotypes. We propose a novel method to rationally integrate KI and MI by defining a combined "Mitotic Frequency Risk Index" (MFRI) which may serve as a better clinical prognosticator and predictor of metastatic risk associated with a low-grade tumor, than MI. Innovation lies in extracting both KI and MI from the same field by co-staining them immune-fluorescently using anti-Ki67 and anti-phosphohistoneH3 antibody (that stains mitotic cells) to glean an extra layer of relevant information that may enhance the prognostic power of grade. The significance and impact of our approach lies in the broad clinical applicability of MFRI, which would replace MI in the tumor grading system and predict metastatic risk reproducibly and reliably in a variety of tumor types. Our novel paradigm that mitotic frequency among cycling cells (MFRI) is a better prognosticator than MI in low-grade tumors is a groundbreaking concept and holds translational promise in early prediction of tumor behavior. AIM 1 will involve a retrospective review of 5000 medical records of breast cancer patients to (i) evaluate the variable correlation between KI and MI across different grades of breast tumors, and (ii) establish that replacement of MI by the mean MI/mean KI ratio improves prognostic accuracy of tumor grade. AIM 2 will determine the Mitotic Frequency Risk Index (MFRI) for a large cohort of Grade 1 (n=200) and Grade 2 (n=200) breast cancer samples and examine its correlation with clinical outcomes. The successful completion of this project may shift current clinical practice paradigms related to risk prognostication by aiding stratification of patients with Grade 1 and 2 tumors into low- and high-risk categories for personalized medicine. It is likely that MFRI, the novel risk index, may also offer insightful cues into why some low-grade, non-invasive breast cancers transform into aggressive tumors that have the ability to metastasize to distant sites.