Pathologic Scoring Shows Promise for Assessing Lung Tumor Therapy Response

11/06/2023

cancer cells
Immune cells attacking cancer. Credit: Adobe iStock

一种新的病理评分系统可以准确地评估患者接受手术前癌症治疗后剩下多少肺肿瘤,可以用来预测患者的生存, according to new research led by investigators at the Bloomberg~Kimmel Institute for Cancer Immunotherapy at the Johns Hopkins Kimmel Cancer Center and the Mark Foundation Center for Advanced Genomics and Imaging at the Johns Hopkins University.

本研究表明,在肺癌手术前对接受免疫治疗和化疗的患者进行残留活瘤(RVT)的病理评估,可以对患者的治疗反应进行稳健有效的评估,可能有助于指导患者的治疗和预测患者的生存. 后一项发现支持肿瘤病理评估作为早期临床试验终点和潜在加速监管批准的生存替代指标.

The results were published on Nov. 4 in the journal Nature Medicine and simultaneously presented by senior study author Janis Taube, M.D., M.Sc., 约翰霍普金斯大学医学院皮肤病理学部主任,也是坎摩尔癌症中心的成员, at the Society for Immunotherapy of Cancer annual meeting in San Diego.

Immunotherapies harness a patient’s immune system to target their tumors. 这些强效药物通常与常规化疗配合使用,以帮助患者在手术前缩小肿瘤, increasing the likelihood of successfully eliminating the cancer. To gauge treatment success, oncologists typically rely on radiologic imaging of the remaining tumor, 但在早期肿瘤中,结果并不总是像在晚期癌症中那样准确. More recently, circulating tumor DNA (ctDNA) clearance, 使用基因测序来检测患者血液样本中肺癌相关的突变, has also shown promise, but is not yet widely available.

For the new study, investigators performed a new analysis on data from the randomized, phase 3 CheckMate 816 study. 该研究发现,手术前用免疫疗法(nivolumab)加化疗治疗非小细胞肺癌患者可提高无事件生存率. 这个重要的替代终点可以帮助预测长期生存和病理完全缓解, which measures whether any tumor is left.

“大多数研究都集中在你是否没有肿瘤残留或肿瘤残留小于或等于10%, which is called a major pathologic response,” says lead study author Julie Stein Deutsch, M.D., an assistant professor of dermatology at Johns Hopkins.

During the study, the investigators used a new approach, which measures residual tumor in patients who received neoadjuvant therapy, to predict outcomes in patients with a greater range of treatment responses. 他们使用免疫相关病理反应标准(irPRC)来寻找病理变化,这些变化表明肿瘤在免疫治疗前已经存在于组织中,但被治疗破坏了, allowing them to measure what percentage of the tumor was left, or the RVT, ranging from 0% to 100%.

因此,他们能够根据剩余肿瘤的大小将患者分为三组. In the future, 诸如此类的数据可能有助于指导下一轮临床试验,并最终帮助肿瘤学家决定如何治疗这些亚组中的个体, Deutsch says. For example, 没有肿瘤残留的患者可以跳过术后免疫治疗或有相对有限的数量, 而中间组的个体可能需要持续更长时间的免疫治疗. 那些表现出非常有限反应的人可能需要转换到一种新的治疗方法或在他们的治疗方案中添加一种新的治疗方法. 该团队的下一步工作将包括确定最有临床意义的RVT截止点.

他们还将目光投向原发肿瘤之外,并使用RVT来评估免疫治疗对淋巴结肿瘤的效果, which showed additive value with the primary tumor for predicting survival. Long term, it may also be possible to strategically combine pathology, 放射学和ctDNA结果用于治疗效果的纵向监测.

Already, 研究人员证明,病理评分系统可以评估10种类型的肿瘤, including lung, skin and colorectal cancers, which could be another advantage over other tumor scoring systems.

“这些多种肿瘤类型的共同特征意味着病理学家不必切换到不同的评分系统来评估病理反应. This is similar to what already exists in radiology, RECIST系统在所有肿瘤类型中用于确定对治疗的客观反应,” Taube says, 注意到病理学家已经完成了必要的工作流程,作为评估手术切除肿瘤的标准程序的一部分. 评估RVT成本低廉,使用病理学家常用的工具和用品, Deutsch says, which may also make it accessible for those working in low-resource settings.

“随着这些免疫疗法进入临床试验并成为标准治疗,这一点很重要, 全世界的病理学家都有一个标准的评分系统来评估治疗反应,” Taube says. 

Study co-authors were Ashley Cimino-Mathews, Elizabeth Thompson, Patrick M. Forde, Daphne Wang, Robert A. Anders, Edward Gabrielson, Peter Illei, Jaroslaw Jedrych, Ludmila Danilova and Joel Sunshine of Johns Hopkins. Other authors were from the Hospital Universitario Puerta de Hierro in Madrid, Spain; McGill University Health Center in Montreal, Canada; Institut du Thorax Curie-Montsouris in Paris, France; Aberdeen Royal Infirmary in the United Kingdom; Bristol Myers Squibb in Princeton, New Jersey; and Queen’s University in Kingston, Canada.

该研究得到了Bristol Myers Squibb, Ono Pharmaceutical Company Ltd .的支持., the Bloomberg~Kimmel Institute for Cancer Immunotherapy, 马克癌症研究基金会和美国国立卫生研究院(资助R01 CA142779).

Deutsch以一项用于注释病理图像以预测患者预后的系统和方法的专利命名.S. Provisional Patent Application 63/313,548, filed in Feb. 2022). Taube receives support for this study from Bristol Myers Squibb; receives consulting fees from AstraZeneca, Bristol Myers Squibb, Merck and Roche; participates on advisory boards from AstraZeneca; and is named on a patent for a machine learning algorithm for irPRC. 这些关系由约翰霍普金斯大学根据其利益冲突政策进行管理.