Plasma-based microsatellite instability detection strategy to guide immune checkpoint blockade treatment

Zhenghang Wang, Xiaochen Zhao, Chan Gao, Jifang Gong, Xicheng Wang, Jing Gao, Zhongwu Li, Jie Wang, Bo Yang, Lei Wang, Bei Zhang, Yifan Zhou, Dalei Wang, Xiaofang Li, Yuezong Bai, Jian Li, Lin Shen, Zhenghang Wang, Xiaochen Zhao, Chan Gao, Jifang Gong, Xicheng Wang, Jing Gao, Zhongwu Li, Jie Wang, Bo Yang, Lei Wang, Bei Zhang, Yifan Zhou, Dalei Wang, Xiaofang Li, Yuezong Bai, Jian Li, Lin Shen

Abstract

Background: Microsatellite instability (MSI) represents the first pan-cancer biomarker approved to guide immune checkpoint blockade (ICB) treatment. However its widespread testing, especially outside of gastrointestinal cancer, is hampered by tissue availability.

Methods: An algorithm for detecting MSI from peripheral blood was established and validated using clinical plasma samples. Its value for predicting ICB efficacy was evaluated among 60 patients with advanced gastrointestinal cancer. The landscape of MSI in blood was also explored among 5138 advanced solid tumors.

Results: The algorithm included 100 microsatellite markers with high capture efficiency, sensitivity, and specificity. In comparison with orthogonal tissue PCR results, the method displayed a sensitivity of 82.5% (33/40) and a specificity of 96.2% (201/209), for an overall accuracy of 94.0% (234/249). When the clinical validation cohort was dichotomized by pretreatment blood MSI (bMSI), bMSI-high (bMSI-H) predicted both improved progression-free survival and overall survival than the blood microsatellite stable (bMSS) patients (HRs: 0.431 and 0.489, p=0.005 and 0.034, respectively). Four patients with bMSS were identified to have high blood tumor mutational burden (bTMB-H) and trended towards a better survival than the bMSS-bTMB-low (bTMB-L) subset (HR 0.026, 95% CI 0 to 2.635, p=0.011). These four patients with bMSS-bTMB-H plus the bMSI-H group collectively displayed significantly improved survival over the bMSS-bTMB-L patients (HR 0.317, 95% CI 0.157 to 0.640, p<0.001). Pan-cancer prevalence of bMSI-H was largely consistent with that shown for tissue except for much lower rates in endometrial and gastrointestinal cancers, and a remarkably higher prevalence in prostate cancer relative to other cancer types.

Conclusions: We have developed a reliable and robust next generation sequencing-based bMSI detection strategy which, in combination with a panel enabling concurrent profiling of bTMB from a single blood draw, may better inform ICB treatment.

Keywords: biomarkers; gastrointestinal neoplasms; genome instability; immunotherapy; tumor.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
A diagram illustrating the study design and samples used for each step. bMSI-H, blood-based MSI high; MS, microsatellite; MSI-H, microsatellite instability high; MSS, microsatellite stable; PD-1, programmed cell death protein-1; PD-L1, programmed death ligand 1.
Figure 2
Figure 2
Cut-off value determination to define the blood microsatellite instability-high (bMSI-H) status. For each sample, a bMSI score was calculated as the fraction of unstable loci in the 100 selected loci. To aim for a specificity of at least 95% according to pairwise comparison with tissue PCR results, the threshold for defining MSI-H was determined to be 0.2 as shown by the dashed line. Red dots represent tissue PCR-defined MSI-H tumors, and blue dots represent tissue PCR-defined (microsatellite stable) MSS tumors.
Figure 3
Figure 3
Best response of target lesions from the initiation of immune checkpoint blockade (ICB) treatment in the bMSI-H (A) and bMSS (B) subgroups. The upper and lower dashed lines mark progressive disease and partial response according to RECIST V.1.1, respectively. bMSI-H, blood-based microsatellite instability high; bMSS, blood microsatellite stable;RECIST, ResponseEvaluation Criteria in Solid Tumors.
Figure 4
Figure 4
Kaplan-Meier analyzes of progression-free survival (PFS) (A) and overall survival (OS) (B) in the patients with bMSI-H versus bMSS. A cohort of 60 patients with advanced gastrointestinal cancer were stratified based on their pretreatment bMSI statuses and the Kaplan-Meier curves for PFS and OS were compared between the bMSI-H and the bMSS subgroups. The tick marks indicate censored data. bMSI-H, blood-based microsatelliteinstability high; bMSS, blood microsatellite stable.
Figure 5
Figure 5
Blood tumor mutational burden (bTMB) as a complement to bMSI to inform ICB treatment. (A) The bTMB levels in the bMSI-H versus the bMSS groups; (B) Kaplan-Meier analysis of OS in the patients with bMSS-TMB-H versus bMSS-TMB-L; (C) Kaplan-Meier analysis of OS in the bMSI-H or bMSI-H versus the bMSS-bTMB-L patients. A cohort of 60 patients with advanced gastrointestinal cancer were stratified based on pretreatment bMSI and bTMB statuses, and those classified as bMSI-H-bTMB-L, bMSS-bTMB-H, or bMSI-H-bTMB-H were pooled as one group in (C). The tick marks indicate censored data. bMSI-H, blood-based microsatellite instability high; bMSS, blood microsatellite stable;H, high; ICB, immune checkpoint blockade; L, low; OS, overallsurvival.
Figure 6
Figure 6
Prevalence of bMSI across 18 cancer types comprizing 5138 solid tumors. bMSI, blood-based microsatellite instability; GIST, gastrointestinal stromal tumor; NSCLC, non-small cell lung cancer.

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