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  • Author or Editor: Kristina M. Kruglyak x
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Abstract

OBJECTIVE

The purpose of this study was to evaluate the performance of a next-generation sequencing-based liquid biopsy test for cancer monitoring in dogs.

SAMPLES

Pre- and postoperative blood samples were collected from dogs with confirmed cancer diagnoses originally enrolled in the CANcer Detection in Dogs (CANDiD) study. A subset of dogs also had longitudinal blood samples collected for recurrence monitoring.

METHODS

All cancer-diagnosed patients had a preoperative blood sample in which a cancer signal was detected and had at least 1 postoperative sample collected. Clinical data were used to assign a clinical disease status for each follow-up visit.

RESULTS

Following excisional surgery, in the absence of clinical residual disease at the postoperative visit, patients with Cancer Signal Detected results at that visit were 1.94 times as likely (95% CI, 1.21 to 3.12; P = .013) to have clinical recurrence within 6 months compared to patients with Cancer Signal Not Detected results. In the subset of patients with longitudinal liquid biopsy samples that had clinical recurrence documented during the study period, 82% (9/11; 95% CI, 48% to 97%) had Cancer Signal Detected in blood prior to or concomitant with clinical recurrence; in the 6 patients where molecular recurrence was detected prior to clinical recurrence, the median lead time was 168 days (range, 47 to 238).

CLINICAL RELEVANCE

Next-generation sequencing-based liquid biopsy is a noninvasive tool that may offer utility as an adjunct to current standard-of-care clinical assessment for cancer monitoring; further studies are needed to confirm diagnostic accuracy in a larger population.

Open access
in American Journal of Veterinary Research

Abstract

OBJECTIVE

To review ordering patterns, positivity rates, and outcome data for a subset of consecutive samples submitted for a commercially available, blood-based multicancer early-detection liquid biopsy test for dogs using next-generation sequencing at 1 laboratory.

SAMPLE

1,500 consecutively submitted blood samples from client-owned dogs with and without clinical suspicion and/or history of cancer for prospective liquid biopsy testing between December 28, 2021, and June 28, 2022.

PROCEDURES

We performed a retrospective observational study, reviewing data from 1,500 consecutive clinical samples submitted for liquid biopsy testing. Outcome data were obtained via medical record review, direct communication with the referring clinic, and/or a patient outcome survey through October 16, 2022.

RESULTS

Sixty-four percent (910/1,419) of reportable samples were submitted for cancer screening, 26% (366/1,419) for aid in diagnosis, and 10% (143/1,419) for other indications. The positivity rate was 25.4% (93/366) in aid-in-diagnosis patients and 4.5% (41/910) in screening patients. Outcome data were available for 33% (465/1,401) of patients, and outcomes were classifiable for 428 patients. The relative observed sensitivity was 61.5% (67/109) and specificity was 97.5% (311/319). The positive predictive value was 75.0% (21/28) for screening patients and 97.7% (43/44) for aid-in-diagnosis patients, and the time to diagnostic resolution following a positive result was < 2 weeks in most cases.

CLINICAL RELEVANCE

Liquid biopsy using next-generation sequencing represents a novel tool for noninvasive detection of cancer in dogs. Real-world clinical performance meets or exceeds expectations established in the test’s clinical validation study.

Open access
in Journal of the American Veterinary Medical Association

Abstract

OBJECTIVE

To validate the performance of a novel, integrated test for canine cancer screening that combines cell-free DNA quantification with next-generation sequencing (NGS) analysis.

SAMPLE

Retrospective data from a total of 1,947 cancer-diagnosed and presumably cancer-free dogs were used to validate test performance for the detection of 7 predefined cancer types (lymphoma, hemangiosarcoma, osteosarcoma, leukemia, histiocytic sarcoma, primary lung tumors, and urothelial carcinoma), using independent training and testing sets.

METHODS

Cell-free DNA quantification data from all samples were analyzed using a proprietary machine learning algorithm to determine a Cancer Probability Index (High, Moderate, or Low). High and Low Probability of Cancer were final result classifications. Moderate cases were additionally analyzed by NGS to arrive at a final classification of High Probability of Cancer (Cancer Signal Detected) or Low Probability of Cancer (Cancer Signal Not Detected).

RESULTS

Of the 595 dogs in the testing set, 89% (n = 530) received a High or Low Probability result based on the machine learning algorithm; 11% (65) were Moderate Probability, and NGS results were used to assign a final classification. Overall, 87 of 122 dogs with the 7 predefined cancer types were classified as High Probability and 467 of 473 presumably cancer-free dogs were classified as Low Probability, corresponding to a sensitivity of 71.3% for the predefined cancer types at a specificity of 98.7%.

CLINICAL RELEVANCE

This integrated test offers a novel option to screen for cancer types that may be difficult to detect by physical examination at a dog’s wellness visit.

Open access
in Journal of the American Veterinary Medical Association