Capturing Tumor Heterogeneity and Clonal Evolution by Circulating Tumor DNA Profiling

Author(s):  
Florian Scherer
2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A18-A18
Author(s):  
Jaeyoun Choi ◽  
Myungwoo Nam ◽  
Stanislav Fridland ◽  
Jinyoung Hwang ◽  
Chan Mi Jung ◽  
...  

BackgroundTumor heterogeneity assessment may help predict response to immunotherapy. In melanoma mouse models, tumor heterogeneity impaired immune response.1 In addition, among lung cancer patients receiving immunotherapy, the high clonal neoantigen group had favorable survival and outcomes.2 Ideal methods of quantifying tumor heterogeneity are multiple biopsies or autopsy. However, these are not feasible in routine clinical practice. Circulating tumor DNA (ctDNA) is emerging as an alternative. Here, we reviewed the current state of tumor heterogeneity quantification from ctDNA. Furthermore, we propose a new tumor heterogeneity index(THI) based on our own scoring system, utilizing both ctDNA and tissue DNA.MethodsSystematic literature search on Pubmed was conducted up to August 18, 2020. A scoring system and THI were theoretically derived.ResultsTwo studies suggested their own methods of assessing tumor heterogeneity. One suggested clustering mutations with Pyclone,3 and the other suggested using the ratio of allele frequency (AF) to the maximum somatic allele frequency (MSAF).4 According to the former, the mutations in the highest cellular prevalence cluster can be defined as clonal mutations. According to the latter, the mutations with AF/MSAF<10% can be defined as subclonal mutations. To date, there have been no studies on utilizing both ctDNA and tissue DNA simultaneously to quantify tumor heterogeneity. We hypothesize that a mutation found in only one of either ctDNA or tissue DNA has a higher chance of being subclonal.We suggest a scoring system based on the previously mentioned methods to estimate the probability for a mutant allele to be subclonal. Adding up the points that correspond to the conditions results in a subclonality score (table 1). In a given ctDNA, the number of alleles with a subclonality score greater than or equal to 2 divided by the total number of alleles is defined as blood THI (bTHI) (figure 1). We can repeat the same calculation in a given tissue DNA for tissue THI (tTHI) (figure 2). Finally, we define composite THI (cTHI) as the mean of bTHI and tTHI.Abstract 18 Table 1Subclonality scoreAbstract 18 Figure 1Hypothetical distribution of all alleles found in ctDNA bTHI = the number of alleles with a subclonality score greater than or equal to 2/the total number of alleles found in ctDNA = 10/20 =50%Abstract 18 Figure 2Hypothetical distribution of all alleles found in tissue DNA tTHI= the number of alleles with a subclonality score greater than or equal to 2/the total number of alleles found in tissue DNA = 16/40 = 40% cTHI= (bTHI + tTHI)/2 = 45%ConclusionsTumor heterogeneity is becoming an important biomarker for predicting response to immunotherapy. Because autopsy and multiple biopsies are not feasible, utilizing both ctDNA and tissue DNA is the most comprehensive and practical approach. Therefore, we propose cTHI, for the first time, as a quantification measure of tumor heterogeneity.ReferencesWolf Y, Bartok O. UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma. Cell 2019;179:219–235.McGranahan N, Swanton C. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016;351:1463–1469.Ma F, Guan Y. Assessing tumor heterogeneity using ctDNA to predict and monitor therapeutic response in metastatic breast cancer. Int J Cancer 2020;146:1359–1368.Liu Z, Xie Z. Presence of allele frequency heterogeneity defined by ctDNA profiling predicts unfavorable overall survival of NSCLC. Transl Lung Cancer Res 2019;8:1045–1050.


Blood ◽  
2018 ◽  
Vol 131 (22) ◽  
pp. 2413-2425 ◽  
Author(s):  
Valeria Spina ◽  
Alessio Bruscaggin ◽  
Annarosa Cuccaro ◽  
Maurizio Martini ◽  
Martina Di Trani ◽  
...  

Key Points ctDNA is as an easily accessible source of tumor DNA for cHL genotyping. ctDNA is a radiation-free tool to track residual disease in cHL.


2019 ◽  
Author(s):  
Luke J. Martinson ◽  
Annabel J. Sharkey ◽  
Alan G. Dawson ◽  
Robert K. Hastings ◽  
Gareth Wilson ◽  
...  

2015 ◽  
Vol 61 (1) ◽  
pp. 112-123 ◽  
Author(s):  
Ellen Heitzer ◽  
Peter Ulz ◽  
Jochen B Geigl

Abstract BACKGROUND Targeted therapies have markedly changed the treatment of cancer over the past 10 years. However, almost all tumors acquire resistance to systemic treatment as a result of tumor heterogeneity, clonal evolution, and selection. Although genotyping is the most currently used method for categorizing tumors for clinical decisions, tumor tissues provide only a snapshot, or are often difficult to obtain. To overcome these issues, methods are needed for a rapid, cost-effective, and noninvasive identification of biomarkers at various time points during the course of disease. Because cell-free circulating tumor DNA (ctDNA) is a potential surrogate for the entire tumor genome, the use of ctDNA as a liquid biopsy may help to obtain the genetic follow-up data that are urgently needed. CONTENT This review includes recent studies exploring the diagnostic, prognostic, and predictive potential of ctDNA as a liquid biopsy in cancer. In addition, it covers biological and technical aspects, including recent advances in the analytical sensitivity and accuracy of DNA analysis as well as hurdles that have to be overcome before implementation into clinical routine. SUMMARY Although the analysis of ctDNA is a promising area, and despite all efforts to develop suitable tools for a comprehensive analysis of tumor genomes from plasma DNA, the liquid biopsy is not yet routinely used as a clinical application. Harmonization of preanalytical and analytical procedures is needed to provide clinical standards to validate the liquid biopsy as a clinical biomarker in well-designed and sufficiently powered multicenter studies.


2019 ◽  
Vol 25 (20) ◽  
pp. 6119-6126 ◽  
Author(s):  
Siddhartha Devarakonda ◽  
Sumithra Sankararaman ◽  
Brett H. Herzog ◽  
Kathryn A. Gold ◽  
Saiama N. Waqar ◽  
...  

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