Combined DNA Analysis from Stool and Blood Samples Improves Tumor Tracking and Assessment of Clonal Heterogeneity in Localized Rectal Cancer Patients.

Objectives: In this study, stool samples were evaluated for tumor mutation analysis via a targeted next generation sequencing (NGS) approach in a small patient cohort suffering from localized rectal cancer. Introduction: Colorectal cancer (CRC) causes the second highest cancer-related death rate worldwide. Thus, improvements in disease assessment and monitoring that may facilitate treatment allocation and allow organ-sparing "watch-and-wait" treatment strategies are highly relevant for a significant number of CRC patients. Methods: Stool-based results were compared with mutation profiles derived from liquid biopsies and the gold standard procedure of tumor biopsy from the same patients. A workflow was established that enables the detection of de-novo tumor mutations in stool samples of CRC patients via ultra-sensitive cell-free tumor DNA target enrichment. Results: Notably, only a 19% overall concordance was found in mutational profiles across the compared sample specimens of stool, tumor, and liquid biopsies. Conclusion: Based on these results, the analysis of stool and liquid biopsy samples can provide important additional information on tumor heterogeneity and potentially on the assessment of minimal residual disease and clonal tumor evolution.

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking.

BACKGROUND: High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling. RESULTS: Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants. CONCLUSIONS: Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

DNA Quantity and Quality Comparisons between Cryopreserved and FFPE Tumors from Matched Pan-Cancer Samples.

Personalized cancer care requires molecular characterization of neoplasms. While the research community accepts frozen tissues as the gold standard analyte for molecular assays, the source of tissue for testing in clinical cancer care comes almost universally from formalin-fixed, paraffin-embedded tissue (FFPE). As newer technologies emerge for DNA characterization that requires higher molecular weight DNA, it was necessary to compare the quality of DNA in terms of DNA length between FFPE and cryopreserved samples. We hypothesized that cryopreserved samples would yield higher quantity and superior quality DNA compared to FFPE samples. We analyzed DNA metrics by performing a head-to-head comparison between FFPE and cryopreserved samples from 38 human tumors representing various cancer types. DNA quantity and purity were measured by UV spectrophotometry, and DNA from cryopreserved tissue demonstrated a 4.2-fold increase in DNA yield per mg of tissue (p-value < 0.001). DNA quality was measured on a fragment microelectrophoresis analyzer, and again, DNA from cryopreserved tissue demonstrated a 223% increase in the DNA quality number and a 9-fold increase in DNA fragments > 40,000 bp (p-value < 0.0001). DNA from the cryopreserved tissues was superior to the DNA from FFPE samples in terms of DNA yield and quality.

Tumor- and Fibroblast-Derived Cell-Free DNAs Differently Affect the Progression of B16 Melanoma In Vitro and In Vivo.

It is widely postulated that the majority of pathologically elevated extracellular or cell-free DNA (cfDNA) in cancer originates from tumor cells; however, evidence has emerged regarding the significant contributions of other cells from the tumor microenvironment. Here, the effect of cfDNA originating from murine B16 melanoma cells and L929 fibroblasts on B16 cells was investigated. It was found that cfDNAL929 increased the viability and migration properties of B16 cells in vitro and their invasiveness in vivo. In contrast, cfDNAB16 exhibited a negative effect on B16 cells, reducing their viability and migration in vitro, which in vivo led to decreased tumor size and metastasis number. It was shown that cell treatment with both cfDNAs resulted in an increase in the expression of genes encoding DNases and the oncogenes Braf, Kras, and Myc. cfDNAL929-treated cells were shown to experience oxidative stress. Gene expression changes in the case of cfDNAB16 treatment are well correlated with the observed decrease in proliferation and migration of B16 cells. The obtained data may indicate the possible involvement of fibroblast DNA in the tumor microenvironment in tumor progression and, potentially, in the formation of new tumor foci due to the transformation of normal cells.

Microsatellite Instability Detection in Cancer: A Multiplex qPCR Approach that Obviates the Need for Matching Normal Samples.

BACKGROUND: Microsatellite instability (MSI) indicates DNA mismatch repair deficiency in certain types of cancer, such as colorectal cancer. The current gold standard technique, PCR-capillary electrophoresis (CE), requires matching normal samples and specialized instrumentation. We developed VarTrace, a rapid and low-cost quantitative PCR (qPCR) assay, to evaluate MSI using solely the tumor sample DNA, obviating the requirement for matching normal samples. METHODS: One hundred and one formalin-fixed paraffin-embedded (FFPE) tumor samples were tested using VarTrace and compared with the Promega OncoMate assay utilizing PCR-CE. Tumor percentage limit of detection was evaluated on contrived samples derived from clinical high MSI (MSI-H) samples. Analytical sensitivity, specificity, limit of detection, and input requirements were assessed using synthetic commercial reference standards. RESULTS: VarTrace successfully analyzed all 101 clinical FFPE samples, demonstrating 100% sensitivity and 98% specificity compared to OncoMate. It detected MSI-H with 97% accuracy down to 10% tumor. Analytical studies using synthetic samples showed a limit of detection of 5% variant allele frequency and a limit of input of 0.5 ng. CONCLUSIONS: This study validates VarTrace as a swift, accurate, and economical assay for MSI detection in samples with low tumor percentages without the need for matching normal DNA. VarTrace's capacity for highly sensitive MSI analysis holds potential for enhancing the efficiency of clinical work flows and broadening the availability of this test.

Tumor extrachromosomal DNA: Biogenesis and recent advances in the field.

Extrachromosomal DNA (ecDNA) is a self-replicating circular DNA originating from the chromosomal genome and exists outside the chromosome. It contains specific gene sequences and non-coding regions that regulate transcription. Recent studies have demonstrated that ecDNA is present in various malignant tumors. Malignant tumor development and poor prognosis may depend on ecDNA's distinctive ring structure, which assists in amplifying oncogenes. During cell division, an uneven distribution of ecDNA significantly enhances tumor cells' heterogeneity, allowing tumor cells to adapt to changes in the tumor microenvironment and making them more resistant to treatments. The application of ecDNA as a cancer biomarker and therapeutic target holds great potential. This article examines the latest advancements in this area and discusses the potential clinical applications of ecDNA.

A Quest for Survival: A Review of the Early Biomarkers of Pancreatic Cancer and the Most Effective Approaches at Present.

Pancreatic cancer (PC) is the most lethal type of cancer; it has the lowest 5-year survival rate among all other types of cancers. More than half of PC cases are diagnosed at an advanced stage due to PC's insidious and non-specific symptoms. Surgery remains the most efficacious treatment option currently available, but only 10-20% of PC cases are resectable upon diagnosis. As of now, the sole biomarker approved by the United States Food and Drug Administration (US-FDA) for PC is carbohydrate antigen 19-9 (CA19-9); however, its use is limited for early diagnosis. An increasing number of studies have investigated a combination of biomarkers. Lately, there has been considerable interest in the application of a liquid biopsy, including the utilization of microRNAs (miRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Screening for PC is indicated for high-risk patients; studies on new diagnostic models combined with biomarkers for early detection have also shown promising results in terms of the ability of these models and biomarkers to aid clinicians in deciding on whether to start screening. This review seeks to provide a concise overview of the advancements in relation to existing biomarkers and explore novel strategies for the early detection of PC.

Precision cancer classification using liquid biopsy and advanced machine learning techniques.

Cancer presents a significant global health burden, resulting in millions of annual deaths. Timely detection is critical for improving survival rates, offering a crucial window for timely medical interventions. Liquid biopsy, analyzing genetic variations, and mutations in circulating cell-free, circulating tumor DNA (cfDNA/ctDNA) or molecular biomarkers, has emerged as a tool for early detection. This study focuses on cancer detection using mutations in plasma cfDNA/ctDNA and protein biomarker concentrations. The proposed system initially calculates the correlation coefficient to identify correlated features, while mutual information assesses each feature's relevance to the target variable, eliminating redundant features to improve efficiency. The eXtrem Gradient Boosting (XGBoost) feature importance method iteratively selects the top ten features, resulting in a 60% dataset dimensionality reduction. The Light Gradient Boosting Machine (LGBM) model is employed for classification, optimizing its performance through a random search for hyper-parameters. Final predictions are obtained by ensembling LGBM models from tenfold cross-validation, weighted by their respective balanced accuracy, and averaged to get final predictions. Applying this methodology, the proposed system achieves 99.45% accuracy and 99.95% AUC for detecting the presence of cancer while achieving 93.94% accuracy and 97.81% AUC for cancer-type classification. Our methodology leads to enhanced healthcare outcomes for cancer patients.

ctDNA transiting into urine is ultrashort and facilitates noninvasive liquid biopsy of HPV+ oropharyngeal cancer.

BACKGROUNDTransrenal cell-free tumor DNA (TR-ctDNA), which transits from the bloodstream into urine, has the potential to enable noninvasive cancer detection for a wide variety of nonurologic cancer types.MethodsUsing whole-genome sequencing, we discovered that urine TR-ctDNA fragments across multiple cancer types are predominantly ultrashort (<50 bp) and, therefore, likely to be missed by conventional ctDNA assays. We developed an ultrashort droplet digital PCR assay to detect TR-ctDNA originating from HPV-associated oropharyngeal squamous cell carcinoma (HPV+ OPSCC) and confirmed that assaying ultrashort DNA is critical for sensitive cancer detection from urine samples.ResultsTR-ctDNA was concordant with plasma ctDNA for cancer detection in patients with HPV+ OPSCC. As proof of concept for using urine TR-ctDNA for posttreatment surveillance, in a small longitudinal case series, TR-ctDNA showed promise for noninvasive detection of recurrence of HPV+ OPSCC.ConclusionOur data indicate that focusing on ultrashort fragments of TR-ctDNA will be important for realizing the full potential of urine-based cancer diagnostics. This has implications for urine-based detection of a wide variety of cancer types and for facilitating access to care through at-home specimen collections.FundingNIH grants R33 CA229023, R21 CA225493; NIH/National Cancer Institute grants U01 CA183848, R01 CA184153, and P30CA046592; American Cancer Society RSG-18-062-01-TBG; American Cancer Society Mission Boost grant MBGI-22-056-01-MBG; and the A. Alfred Taubman Medical Research Institute.

Lung cancer biomarkers: Raising the clinical value of the classical and the new ones.

Blood-based diagnostics for lung cancer support the diagnosis, estimation of prognosis, prediction, and monitoring of therapy response in lung cancer patients. The clinical utility of serum tumor markers has considerably increased due to developments in serum protein tumor markers analytics and clinical biomarker studies, the exploration of preanalytical and influencing conditions, the interpretation of biomarker combinations and individual biomarker kinetics, as well as the implementation of biostatistical models. In addition, circulating tumor DNA (ctDNA) and other liquid biopsy markers are playing an increasingly prominent role in the molecular tumor characterization and the monitoring of tumor evolution over time. Thus, modern lung cancer biomarkers may considerably contribute to an individualized companion diagnostics and provide a sensitive guidance for patients throughout the course of their disease. In this special edition on Tumor Markers in Lung Cancer, experts summarize recent developments in clinical laboratory diagnostics of lung cancer and give an outlook on future challenges and opportunities.

Using the DNA Integrity Number to Analyze DNA Quality in Specimens Collected from Liquid-Based Cytology after Fine-Needle Aspiration of Breast Tumors and Lesions.

INTRODUCTION: Cancer genome analysis using next-generation sequencing requires adequate and high-quality DNA samples. Genomic analyses were conventionally performed using formalin-fixed paraffin-embedded sections rather than cytology samples such as cell block or smear specimens. Specimens collected from liquid-based cytology (LBC) have the potential to be sources of high-quality DNA suitable for genetic analysis even after long-term storage. METHODS: We collected breast tumor/lesion fractions from 92 residual LBC specimens using fine-needle aspiration (FNA) biopsy, including breast carcinoma (1 invasive carcinoma and 4 ductal carcinomas in situ), papillomatous lesion (5 intraductal papillomas), and fibroepithelial lesion (19 phyllodes tumors and 53 fibroadenomas) samples, and others (1 ductal adenoma, 1 hamartoma, 1 fibrocystic disease, and 7 unknown). DNA was extracted from all samples and subjected to DNA integrity number (DIN) score analysis. RESULTS: Average DIN score collected from 92 LBC specimens was significantly higher score. In addition, high-quality DNA with high DIN values (7.39 ± 0.80) was successfully extracted more than 12 months after storage of residual LBC specimens. CONCLUSION: Residual LBC specimens collected from FNA of the breast were verified to carry high-quality DNA and could serve as an alternate source for genetic analysis.

Red blood cells function as reservoirs of tumor DNA.

Novel screening techniques for early detection of lung cancer are urgently needed. Profiling circulating tumor cell-free DNA (ctDNA) has emerged as a promising tool for biopsy-free tumor genotyping. However, both the scarcity and short half-life of ctDNA substantially limit the sensitivity and clinical utility of ctDNA detection methodologies. Our discovery that red blood cells (RBCs) sequester mitochondrial DNA opens a new avenue for detecting circulating nucleic acids, as RBCs represent an unrecognized reservoir of circulating nucleic acid. Here, we show that RBCs acquire tumor DNA following coculture with lung cancer cell lines harboring Kirsten rat sarcoma viral oncogene homolog (KRAS) and epidermal growth factor receptor (EGFR) mutations. RBC-bound tumor DNA is detectable in patients with early-stage non-small cell lung cancer (NSCLC) but not in healthy controls by qPCR. Our results collectively uncover a previously unrecognized yet easily accessible reservoir of tumor DNA, offering a promising foundation for future RBC-based tumor diagnostics.NEW & NOTEWORTHY We present a novel method for lung cancer detection by revealing RBCs as a reservoir for tumor DNA, overcoming the limitations of current circulating tumor ctDNA methodologies. By demonstrating that RBCs can capture tumor DNA, including critical mutations found in lung cancer, we provide a promising, biopsy-free avenue for early cancer diagnostics. This discovery opens up exciting possibilities for developing RBC-based diagnostic tools, significantly enhancing the sensitivity and clinical utility of noninvasive cancer detection.

Circulating Tumor DNA (ctDNA) and Its Role in Gynecologic Malignancies.

OPINION STATEMENT: Circulating tumor DNA (ctDNA) refers to small fragments of DNA released into the bloodstream by cancer cells. It is obtained through "liquid biopsy;" which most commonly refers to plasma or blood samples, but can be obtained from a number of bodily fluids including ascitic fluid, saliva, and even urine and stool. ctDNA is detected via polymerase chain reaction (PCR) or next-generation sequencing (NGS). The DNA from these samples is analyzed for the detection of point mutations, copy-number alterations, gene fusion, and DNA methylation. These results have the potential for use in cancer diagnosis, determining prognosis, targeting gene-specific therapies, and monitoring for/predicting disease recurrence and response to treatment. ctDNA offers an alternative to tissue biopsy; it is less invasive and can be monitored serially over time without multiple procedures. Moreover it may have the ability to detect disease recurrence or predict behavior in a way that solid tissue biopsies, tumor marker surveillance, and imaging cannot. Recent explosion in interest in ctDNA shows promising developments for widespread adoption of these techniques in cancer care. However, the use of ctDNA in diagnosis and treatment of gynecologic malignancies is currently limited, compared to adoption in other solid-organ tumors such as breast and colorectal cancers. Compared to other cancer types, there appear to be fewer comprehensive studies and clinical validations specifically focusing on the use of ctDNA in gynecologic cancers. More research is needed in this area to advance the potential for use of ctDNA in ovarian, endometrial, and cervical cancers before this can be routinely adopted to improve care for patients with gynecologic malignancies.

Analytical validation of NeXT Personal®, an ultra-sensitive personalized circulating tumor DNA assay.

We describe the analytical validation of NeXT Personal®, an ultra-sensitive, tumor-informed circulating tumor DNA (ctDNA) assay for detecting residual disease, monitoring therapy response, and detecting recurrence in patients diagnosed with solid tumor cancers. NeXT Personal uses whole genome sequencing of tumor and matched normal samples combined with advanced analytics to accurately identify up to ~1,800 somatic variants specific to the patient's tumor. A personalized panel is created, targeting these variants and then used to sequence cell-free DNA extracted from patient plasma samples for ultra-sensitive detection of ctDNA. The NeXT Personal analytical validation is based on panels designed from tumor and matched normal samples from two cell lines, and from 123 patients across nine cancer types. Analytical measurements demonstrated a detection threshold of 1.67 parts per million (PPM) with a limit of detection at 95% (LOD95) of 3.45 PPM. NeXT Personal showed linearity over a range of 0.8 to 300,000 PPM (Pearson correlation coefficient = 0.9998). Precision varied from a coefficient of variation of 12.8% to 3.6% over a range of 25 to 25,000 PPM. The assay targets 99.9% specificity, with this validation study measuring 100% specificity and in silico methods giving us a confidence interval of 99.92 to 100%. In summary, this study demonstrates NeXT Personal as an ultra-sensitive, highly quantitative and robust ctDNA assay that can be used to detect residual disease, monitor treatment response, and detect recurrence in patients.

Characterization and mitigation of artifacts derived from NGS library preparation due to structure-specific sequences in the human genome.

BACKGROUND: Hybridization capture-based targeted next generation sequencing (NGS) is gaining importance in routine cancer clinical practice. DNA library preparation is a fundamental step to produce high-quality sequencing data. Numerous unexpected, low variant allele frequency calls were observed in libraries using sonication fragmentation and enzymatic fragmentation. In this study, we investigated the characteristics of the artifact reads induced by sonication and enzymatic fragmentation. We also developed a bioinformatic algorithm to filter these sequencing errors. RESULTS: We used pairwise comparisons of somatic single nucleotide variants (SNVs) and insertions and deletions (indels) of the same tumor DNA samples prepared using both ultrasonic and enzymatic fragmentation protocols. Our analysis revealed that the number of artifact variants was significantly greater in the samples generated using enzymatic fragmentation than using sonication. Most of the artifacts derived from the sonication-treated libraries were chimeric artifact reads containing both cis- and trans-inverted repeat sequences of the genomic DNA. In contrast, chimeric artifact reads of endonuclease-treated libraries contained palindromic sequences with mismatched bases. Based on these distinctive features, we proposed a mechanistic hypothesis model, PDSM (pairing of partial single strands derived from a similar molecule), by which these sequencing errors derive from ultrasonication and enzymatic fragmentation library preparation. We developed a bioinformatic algorithm to generate a custom mutation "blacklist" in the BED region to reduce errors in downstream analyses. CONCLUSIONS: We first proposed a mechanistic hypothesis model (PDSM) of sequencing errors caused by specific structures of inverted repeat sequences and palindromic sequences in the natural genome. This new hypothesis predicts the existence of chimeric reads that could not be explained by previous models, and provides a new direction for further improving NGS analysis accuracy. A bioinformatic algorithm, ArtifactsFinder, was developed and used to reduce the sequencing errors in libraries produced using sonication and enzymatic fragmentation.

Clinical Application of Liquid Biopsy in Pancreatic Cancer: A Narrative Review.

Pancreatic ductal adenocarcinoma contributes significantly to global cancer-related deaths, featuring only a 10% survival rate over five years. The quest for novel tumor markers is critical to facilitate early diagnosis and tailor treatment strategies for this disease, which is key to improving patient outcomes. In pancreatic ductal adenocarcinoma, these markers have been demonstrated to play a crucial role in early identification, continuous monitoring, and prediction of its prognosis and have led to better patient outcomes. Nowadays, biopsy specimens serve to ascertain diagnosis and determine tumor type. However, liquid biopsies present distinct advantages over conventional biopsy techniques. They offer a noninvasive, easily administered procedure, delivering insights into the tumor's status and facilitating real-time monitoring. Liquid biopsies encompass a variety of elements, such as circulating tumor cells, circulating tumor DNA, extracellular vesicles, microRNAs, circulating RNA, tumor platelets, and tumor endothelial cells. This review aims to provide an overview of the clinical applications of liquid biopsy as a technique in the management of pancreatic cancer.

Application of plasma circulating KRAS mutations as a predictive biomarker for targeted treatment of pancreatic cancer.

Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in circulating tumor deoxyribonucleic acid (ctDNA) have been reported as representative noninvasive prognostic markers for pancreatic ductal adenocarcinoma (PDAC). Here, we aimed to evaluate single KRAS mutations as prognostic and predictive biomarkers, with an emphasis on potential therapeutic approaches to PDAC. A total of 128 patients were analyzed for multiple or single KRAS mutations (G12A, G12C, G12D, G12R, G12S, G12V, and G13D) in their tumors and plasma using droplet digital polymerase chain reaction (ddPCR). Overall, KRAS mutations were detected by multiplex ddPCR in 119 (93%) of tumor DNA and 68 (53.1%) of ctDNA, with a concordance rate of 80% between plasma ctDNA and tumor DNA in the metastatic stage, which was higher than the 44% in the resectable stage. Moreover, the prognostic prediction of both overall survival (OS) and progression-free survival (PFS) was more relevant using plasma ctDNA than tumor DNA. Further, we evaluated the selective tumor-suppressive efficacy of the KRAS G12C inhibitor sotorasib in a patient-derived organoid (PDO) from a KRAS G12C-mutated patient using a patient-derived xenograft (PDX) model. Sotorasib showed selective inhibition in vitro and in vivo with altered tumor microenvironment, including fibroblasts and macrophages. Collectively, screening for KRAS single mutations in plasma ctDNA and the use of preclinical models of PDO and PDX with genetic mutations would impact precision medicine in the context of PDAC.

Analytical evaluation of circulating tumor DNA sequencing assays.

In China, circulating tumor DNA analysis is widely used and numerous assays are available. Systematic evaluation to help users make informed selections is needed. Nine circulating tumor DNA assays, including one benchmark assay, were evaluated using 23 contrived reference samples. There were two sample types (cell-free DNA and plasma samples), three circulating tumor DNA inputs (low, < 20 ng; medium, 20-50 ng; high, > 50 ng), two variant allele frequency ranges (low, 0.1-0.5%; intermediate, 0.5-2.5%), and four variant types (single nucleotide, insertion/deletion, structural, and copy number). Sensitivity, specificity, reproducibility, and all processes from cell-free DNA extraction to bioinformatics analysis were assessed. The test assays were generally comparable or superior to the benchmark assay, demonstrating high analytical sensitivity. Variations in circulating tumor DNA extraction and quantification efficiency, sensitivity, and reproducibility were observed, particularly at lower inputs. These findings will guide circulating tumor DNA assay choice for research and clinical studies, allowing consideration of multiple technical parameters.

Plasma cell-free DNA in canine lymphoma patients as a novel material for genotyping.

Canine lymphoma is a disease with high morbidity and poor long-term prognosis, despite a high response rate to chemotherapy. In this study, we focused on liquid biopsy, in which small amounts of substances from body fluids were analysed, to determine whether cell-free DNA (cfDNA) in the plasma can be used as a biomarker for lymphoma in dogs. We found that 23 patients with lymphoma had significantly higher cfDNA concentrations than the 12 healthy dogs (median 2360 ng/mL versus 299 ng/mL, p < .0001). Polymerase chain reaction for antigen receptor rearrangement (PARR) was also employed using cfDNA from the lymphoma group to investigate whether cfDNA could be used for the detection of genetic clonality of lymphomas, as well as the genomic DNA (gDNA) extracted from an original lesion in each case. The correlation of the PARR results between cfDNA and gDNA was observed in 100% of B-cell lymphomas (10/10), 77.8% of T-cell lymphomas (7/9), and 100% of other types of lymphomas (4/4), respectively. These results indicate that plasma cfDNA levels are increasing in canine lymphoma patients, that cfDNA concentration can be a novel diagnostic tool, and that it can be used as a diagnostic tool for PARR.