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Review
. 2023 Jan;11(1):e005924.
doi: 10.1136/jitc-2022-005924.

Liquid biopsy approaches to capture tumor evolution and clinical outcomes during cancer immunotherapy

Affiliations
Review

Liquid biopsy approaches to capture tumor evolution and clinical outcomes during cancer immunotherapy

Lavanya Sivapalan et al. J Immunother Cancer. 2023 Jan.

Abstract

Circulating cell-free tumor DNA (ctDNA) can serve as a real-time biomarker of tumor burden and provide unique insights into the evolving molecular landscape of cancers under the selective pressure of immunotherapy. Tracking the landscape of genomic alterations detected in ctDNA may reveal the clonal architecture of the metastatic cascade and thus improve our understanding of the molecular wiring of therapeutic responses. While liquid biopsies may provide a rapid and accurate evaluation of tumor burden dynamics during immunotherapy, the complexity of antitumor immune responses is not fully captured through single-feature ctDNA analyses. This underscores a need for integrative studies modeling the tumor and the immune compartment to understand the kinetics of tumor clearance in association with the quality of antitumor immune responses. Clinical applications of ctDNA testing in patients treated with immune checkpoint inhibitors have shown both predictive and prognostic value through the detection of genomic biomarkers, such as tumor mutational burden and microsatellite instability, as well as allowing for real-time monitoring of circulating tumor burden and the assessment of early on-therapy responses. These efforts highlight the emerging role of liquid biopsies in selecting patients for cancer immunotherapy, monitoring therapeutic efficacy, determining the optimal duration of treatment and ultimately guiding treatment selection and sequencing. The clinical translation of liquid biopsies is propelled by the increasing number of ctDNA-directed interventional clinical trials in the immuno-oncology space, signifying a critical step towards implementation of liquid biopsies in precision immuno-oncology.

Keywords: Genetic Markers; Immunotherapy; Tumor Biomarkers.

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Conflict of interest statement

Competing interests: VA receives research funding to Johns Hopkins University from Astra Zeneca, Personal Genome Diagnostics and Delfi Diagnostics and has received research funding to Johns Hopkins University from Bristol-Myers Squibb in the past 5 years. VA is an inventor on patent applications (63/276,525, 17/779,936, 16/312,152, 16/341,862, 17/047,006 and 17/598,690) submitted by Johns Hopkins University related to cancer genomic analyses, ctDNA therapeutic response monitoring and immunogenomic features of response to immunotherapy that have been licensed to one or more entities. Under the terms of these license agreements, the University and inventors are entitled to fees and royalty distributions. JVC has served on an advisory board for Illumina. JCM has served in a consulting role to MJH Life Sciences, Johnson & Johnson, and Doximity and has received research funding to his institution from Merck via the Conquer Cancer Young Investigators Award. BPL has served in a consultant/advisory role for Janssen, Daiichi Sankyo, AstraZeneca, Eli Lilly, Genentech, Mirati, Amgen, Pfizer, BMS, Guardant 360, and Foundation Medicine. SS has served in a consultant/advisory role for Genentech and MJH Life Sciences. VL has served in a consultant/advisory role for Takeda, Seattle Genetics, Bristol-Myers Squibb, AstraZeneca and Guardant Health and has received research funding from GlaxoSmithKline, BMS, Merck and Seattle Genetics. MS and JJ are employees of Personal Genome Diagnostics (Labcorp).

Figures

Figure 1
Figure 1
Approaches for the detection and analysis of ctDNA in the context of immuno-oncology. cfDNA isolated from plasma contains a complex mixture of fragments of varying cellular origin, most of which are derived from normal or hematopoietic cells undergoing apoptosis. A proportion of cfDNA can also originate from clonally expanded hematopoietic cells and contains somatic mutations associated with clonal haematopoiesis (CH). In patients with cancer, a variable proportion of cfDNA fragments are tumor-derived, known as ctDNA, which can be detected through tumor-agnostic or tumor-informed approaches, using optimized PCR-based methods, such as droplet digital PCR, or next-generation sequencing, including targeted and whole genome sequencing. ctDNA can be analyzed using a variety of approaches to determine the landscape of sequence alterations, structural changes and methylation patterns, alongside fragment size profiles, end-motifs and other cfDNA fragment physical properties. In the context of immunotherapy, serial sampling and longitudinal ctDNA analyses can pinpoint the evolving tumor burden. As a real-time biomarker of tumor burden, longitudinal ctDNA assessments can also provide insights into emergence of potential therapeutic resistance mechanisms, which can be detected prior to radiographic responses derived from conventional imaging. Integration of ctDNA analyses into clinical use for immuno-oncology may provide added utility for the study of difficult to evaluate tumor-types (eg, mesothelioma), patient selection for immunotherapy and subsequent response monitoring, particularly in radiographically stable disease. Accurate response monitoring can inform decisions on the optimal duration of immunotherapy and appropriate strategies for treatment escalation/de-escalation based on ctDNA molecular responses. cfDNA, cell-free DNA; ctDNA, cell-free tumor DNA; ddPCR, droplet digital PCR, WGS; whole genome sequencing.
Figure 2
Figure 2
Potential applications of ctDNA to guide clinical decision-making in patients receiving immunotherapy. In patients with early localized disease, ctDNA analyses at the time of clinical diagnosis can enable the stratification of high-risk individuals towards neoadjuvant treatment with ICI. Furthermore, the detection of ctDNA after treatment with curative intent, which is indicative of MRD, could aid in the identification of high-risk patients that could benefit from adjuvant immunotherapy. Longitudinal ctDNA assessment can also inform optimization of therapy duration and guide maintenance therapy. In patients with metastatic disease, blood-based assessments of predictive genomic biomarkers of ICI response, including bTMB and MSI, can improve the selection of patients for immunotherapy regimens. Longitudinal monitoring of ctDNA levels during immunotherapy can expedite clinical response assessments and allow for pseudoprogression to be accurately identified and distinguished from true disease progression. Finally, in refractory disease, ctDNA tracking can be used to detect the emergence of resistance mutations leading to molecular progression prior to radiologic progression. bTMB, blood TMB; ctDNA, cell-free tumor DNA; ICI, immune checkpoint inhibitors; MRD, minimal residual disease; MSI, microsatellite instability.
Figure 3
Figure 3
Leveraging the hallmarks of cfDNA to expand current and future uses in immuno-oncology. Multiple hallmark features of cfDNA can be harnessed through either baseline measurements or longitudinal analyses. Blood-based tumor mutational burden and MSI, the latter detected through changes in microsatellite length or MMR-induced frameshift alterations giving rise to a MSI-high (MSI-H) tumor genotype, have shown significant promise for non-invasive assessment in cases where the availability of tissue biopsies is limited. In tandem, longitudinal ctDNA tracking using sequence alterations, structural changes and tumor-specific phylogenetic profiling can enable quantitative assessment of changes in circulating tumor load and provide a key insight into tumor immunoediting during immunotherapy. Several emerging approaches have gained traction and may enhance the future potential of ctDNA testing in immuno-oncology. In this context, analyses of cfDNA epigenetic features, genome-wide chromatin accessibility and fragmentation profiles may be implemented in integrative multi-feature ctDNA methodologies to detect and track circulating tumor burden during immunotherapy. bTMB, microsatellite instability; cfDNA, cell-free DNA; ctDNA, cell-free tumor DNA; MMR, mismatch repair; MSI, microsatellite instability.

Comment in

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