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

 描述(申请人提供)：临床上常用的乳腺癌预后和预测分子标志物包括Ki67、ER、PR、Her2和有丝分裂指数(MI)。在这些标记物中，Ki67增殖指数(Ki)是一种通用的独立预后标记物，MI是目前肿瘤分级系统中不可或缺的元素。不幸的是，这些标记物还没有达到足够的重复性和可靠性来准确预测疾病的预后和侵袭性。目前可用的临床预测指标(KI和MI)的风险预测能力有限，这是阻碍准确的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本质上来自不重叠的微观场，并且处于不同的尺度上，因此它们是不可比拟的，并且丢失了有价值的信息。我们的目标是将肿瘤的Ki和MI放在同一个测量尺度上，以便更准确地利用它们真正的预后潜力，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来合理地整合Ki和MI，通过定义一个组合的“有丝分裂频率风险指数”(MFRI)，它可能比MI更好地预测和预测与低级别肿瘤相关的转移风险。创新之处在于通过使用抗Ki67和抗磷组蛋白H3抗体(对有丝分裂细胞染色)对KI和MI进行免疫荧光共染色，从同一个领域提取KI和MI，以收集额外的一层相关信息，可能增强分级的预后能力。我们的方法的意义和影响在于MFRI具有广泛的临床适用性，它将取代MI在肿瘤分级系统中的作用，并在各种肿瘤类型中重复性和可靠性地预测转移风险。我们的新范式认为，在低级别肿瘤中，周期细胞间有丝分裂频率(MFRI)是比MI更好的预后指标，这是一个开创性的概念，并在早期预测肿瘤行为方面具有翻译前景。目的1对5000例乳腺癌患者的临床资料进行回顾性分析，以(1)评价不同级别乳腺肿瘤KI和MI之间的变量相关性，以及(2)用平均MI/平均KI比值代替MI，以提高肿瘤分级的预后准确性。目的2将测定大量1级(n=200)和2级(n=200)乳腺癌样本的有丝分裂频率风险指数(MFRI)，并检查其与临床结果的相关性。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级肿瘤患者分层为个性化药物的低风险和高风险类别。新的风险指数MFRI很可能也可以为一些低级别、非侵袭性乳腺癌转化为侵袭性肿瘤提供有洞察力的线索，这些肿瘤有能力转移到远处。

 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.