medwireNews: Liquid biopsies could help to identify cancer patients who have an increased risk for venous thromboembolism (VTE), suggest preliminary results published in Nature Medicine.
The presence of circulating tumor (ct)DNA in plasma “was associated with VTE independent of clinical and radiographic features,” report the researchers, who also found that “[a] machine learning model trained on liquid biopsy data outperformed previous risk scores.”
They continue: “Because expert guidelines recommend [liquid biopsies] as therapy selection tools, many patients could, thus, receive effective VTE risk stratification with [a liquid biopsy] report with no additional overhead required of the patient or clinician.”
Outlining the background to the trial, Simon Mantha (Memorial Sloan Kettering Cancer Center, New York, USA) and colleagues explain that “[p]rophylactic anticoagulation lowers the risk of VTE, although defining the patients most likely to benefit is challenging.”
They therefore explored the use of liquid biopsy in three cohorts: a discovery and validation cohort comprising patients with any cancer type (n=4141 and 1426, respectively) who had undergone ctDNA sequencing with the MSK-ACCESS assay; and a generalizability cohort of patients with advanced non-small-cell lung cancer (n=463) who underwent sequencing with the ctDx Lung assay.
ctDNA positivity was significantly associated with an increased incidence of VTE in the discovery cohort, with a hazard ratio (HR) of 2.49, and this was also the case in the validation and generalizability cohorts, with respective HRs of 2.49 and 2.30.
Interestingly, analysis of the discovery cohort by tumor type showed that the association between ctDNA positivity and VTE risk held “for NSCLC and for melanoma, pancreatic and less represented cancers but not in bladder, hepatobiliary and colorectal cancers,” note Mantha et al.
They add: “Why ctDNA may portend VTE in some cancer types and not in others is complex and deserves further investigation into both tumor biology and host immune response to said biology in shedding versus non-shedding tumors.”
The team then showed that a machine learning model incorporating liquid biopsy variables – namely, ctDNA variant allele frequency, genomic content, and cell-free DNA concentration – predicted VTE risk with c-indices of 0.74, 0.73, and 0.67 in the discovery, validation, and generalizability cohorts, respectively. This was better than the corresponding c-indices of 0.57, 0.61, and 0.54 for the Khorana score, which is “a validated cancer VTE risk stratification measure based on hematologic and clinical parameters.”
Finally, an exploratory analysis in the discovery cohort revealed that among patients positive for ctDNA, anticoagulant use was associated with lower rates of VTE than nonuse, with a significant HR of 0.50 after adjusting for age, cancer type, and time since diagnosis. However, among ctDNA-negative patients, there was no difference in VTE rates between those who were versus were not prescribed anticoagulants.
Mantha and associates conclude: “DNA [liquid biopsy]-based models have the potential to predict VTE risk on a spectrum and to be deployed with minimal clinician burden. The use of [liquid biopsies] to guide anticoagulation in patients with cancer merits further validation.”
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