Project description:Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA (ctDNA) alterations through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative treatment in patients with operable gastric cancer. After filtering alterations from matched white blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.
Project description:Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA alterations (ctDNA) through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative chemotherapy in patients with operable gastric cancer. After filtering alterations derived from matched white-blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.
Project description:Currently, approximately 30%-55% of the patients with non-small cell lung cancer (NSCLC) develop recurrence due to minimal residual disease (MRD) after receiving surgical resection of the tumor. This study aims to develop an ultrasensitive and affordable fragmentomic assay for MRD detection in patients with NSCLC. A total of 87 patients with NSCLC, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for both whole-genome sequencing (WGS) and targeted sequencing. WGS-based cell-free DNA (cfDNA) fragment profile was used to fit regularized Cox regression models, and leave-one-out cross-validation was further used to evaluate models' performance. The models showed excellent performances in detecting patients with a high risk of recurrence. At 7 days postsurgical, the high-risk patients detected by our model showed an increased risk of 4.6 times, while the risk increased to 8.3 times at 6 months postsurgical. These fragmentomics determined higher risk compared with the targeted sequencing-based circulating mutations both at 7 days and 6 months postsurgical. The overall sensitivity for detecting patients with recurrence reached 78.3% while using both fragmentomics and mutation results from 7 days and 6 months postsurgical, which increased from the 43.5% sensitivity by using only the circulating mutations. The fragmentomics showed great sensitivity in predicting patient recurrence compared with the traditional circulating mutation, especially after the surgery for early-stage NSCLC, therefore exhibiting great potential to guide adjuvant therapeutics.SignificanceThe circulating tumor DNA mutation-based approach shows limited performance in MRD detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, we describe a cfDNA fragmentomics-based method in MRD detection of resectable NSCLC using WGS, and the cfDNA fragmentomics showed a great sensitivity in predicting prognosis.
Project description:Key Points • Nearly 95% of cfDNA is derived from hematopoietic tissue.• cfDNA MRD at D90 is an important predictor of post-alloHCT relapse. Visual Abstract Abstract The measurable residual disease (MRD) assessment provides an attractive predictor of allogeneic hematopoietic cell transplnat (alloHCT) outcomes. Cell-free DNA (cfDNA) has been applied to diagnosis, early detection, and disease burden monitoring in various tumors, but its utility as an MRD test in myeloid malignancies has not been systematically evaluated. We sought to determine the differential sensitivity between bone marrow (BM) and cfDNA MRD and to assess the effect of cfDNA MRD on alloHCT outcomes. The technical and clinical validation cohorts, including 82 patients participating in clinical trials (Bone Marrow Transplant Clinical Trials Network-0201 and 0402), were used. Ultradeep error-corrected targeted sequencing was performed on plasma and BM-derived DNA. We demonstrated that 94.6% (range, 93.9-95.3) of cfDNA was derived from hematopoietic tissue. The mutant allele fraction was congruent between BM and cfDNA (rho = 0.8; P < .0001); however, cfDNA seemed to be more sensitive in detecting clones with a variant allele frequency (VAF) of <0.26%. cfDNA-MRD clearance by day 90 after alloHCT (D90) was associated with improved relapse-free survival (RFS, median survival not reached vs 5.5 months; P < .0001) and overall survival (OS, median survival not reached vs 7.3 months; P < .0001) when compared with patients with persistent MRD. Irrespective of pre-alloHCT MRD, D90 cfDNA MRD was associated with inferior 2-year OS (16.7% vs 84.8%; P < .0001) and RFS (16.7% vs 80.7%; P < .0001). cfDNA seems to be an accurate, minimally invasive alternative to BM aspirates in MRD assessment and confers important prognostic implications in patients with myeloid malignancies undergoing alloHCT.
Project description:Early detection plays a critical role in mitigating mortality rates linked to gastric cancer. However, current clinical screening methods exhibit suboptimal efficacy. Methylation alterations identified from cell-free DNA (cfDNA) present a promising biomarker for early cancer detection. Our study focused on identifying gastric cancer-specific markers from cfDNA methylation to facilitate early detection. We enrolled 150 gastric cancer patients and 100 healthy controls in this study, and undertook genome-wide methylation profiling of cfDNA using cell-free methylated DNA immunoprecipitation and high-throughput sequencing. We identified 21 differentially methylated regions (DMRs) between the gastric tumor and nontumor groups using multiple algorithms. Subsequently, using the 21 DMRs, we developed a gastric cancer detection model by random forest algorithm in the discovery set, and validated the model in an independent set. The model was able to accurately discriminate gastric cancer with a sensitivity and specificity of 93.90% and 95.15% in the discovery set, respectively, and 88.38% and 94.23% in the validation set, respectively. These results underscore the efficacy and accuracy of cfDNA-derived methylation markers in distinguishing early stage gastric cancer. This study highlighted the significance of cfDNA methylation alterations in early gastric cancer detection.
Project description:Synovial sarcoma (SS) is genetically characterized by chromosomal translocation, which generates SYT-SSX fusion transcripts. Although SS can occur in any body part, primary gastric SS is substantially rare. Here we describe a detection of the fusion gene sequence of gastric SS in plasma cell-free DNA (cfDNA). A gastric submucosal tumor was detected in the stomach of a 27-year-old woman and diagnosed as SS. Candidate intronic primers were designed to detect the intronic fusion breakpoint and this fusion sequence was confirmed in intron 10 of SYT and intron 5 of SSX2 by genomic polymerase chain reaction (PCR) and direct sequencing. A locked nucleic acid (LNA) probe specific to the fusion sequence was designed for detecting the fusion sequence in plasma and the fusion sequence was detected in preoperative plasma cfDNA, while not detected in postoperative plasma cfDNA. This technique will be useful for monitoring translocation-derived diseases such as SS.
Project description:PurposeWe recently reported the development of a cell-free DNA (cfDNA) targeted methylation (TM)-based sequencing approach for a multi-cancer early detection (MCED) test that includes cancer signal origin prediction. Here, we evaluated the prognostic significance of cancer detection by the MCED test using longitudinal follow-up data.Experimental designAs part of a Circulating Cell-free Genome Atlas (CCGA) substudy, plasma cfDNA samples were sequenced using a TM approach, and machine learning classifiers predicted cancer status and cancer signal origin. Overall survival (OS) of cancer participants in the first 3 years of follow-up was evaluated in relation to cancer detection by the MCED test and clinical characteristics.ResultsCancers not detected by the MCED test had significantly better OS (P < 0.0001) than cancers detected, even after accounting for other covariates, including clinical stage and method of clinical diagnosis (i.e., standard-of-care screening or clinical presentation with signs/symptoms). Additionally, cancers not detected by the MCED test had better OS than was expected when data were adjusted for age, stage, and cancer type from the Surveillance, Epidemiology, and End Results (SEER) program. In cancers with current screening options, the MCED test also differentiated more aggressive cancers from less aggressive cancers (P < 0.0001).ConclusionsCancer detection by the MCED test was prognostic beyond clinical stage and method of diagnosis. Cancers not detected by the MCED test had better prognosis than cancers detected and SEER-based expected survival. Cancer detection and prognosis may be linked by the underlying biological factor of tumor fraction in cfDNA.
Project description:ImportanceLeptomeningeal disease (LMD) is a devastating complication of cancer that is frequently underdiagnosed owing to the low sensitivity of cerebrospinal fluid (CSF) cytologic assessment, the current benchmark diagnostic method. Improving diagnostic sensitivity may lead to improved treatment decisions.ObjectiveTo assess whether cell-free DNA (cfDNA) analysis of CSF may be used to diagnose LMD more accurately than cytologic analysis.Design, setting, and participantsThis diagnostic study conducted in a neuro-oncology clinic at 2 large, tertiary medical centers assessed the use of genomic sequencing of CSF samples obtained from 30 patients with suspected or confirmed LMD from 2015 through 2018 to identify tumor-derived cfDNA. From the same CSF samples, cytologic analyses were conducted, and the results of the 2 tests were compared. This study consisted of 2 patient populations: 22 patients with cytologically confirmed LMD without parenchymal tumors abutting their CSF and 8 patients with parenchymal brain metastases with no evidence of LMD. Patients were considered positive for the presence of LMD if previous CSF cytologic analysis was positive for malignant cells. The analysis was conducted from 2015 to 2018.Main outcomes and measuresThe primary outcome was the diagnostic accuracy of cfDNA analysis, defined as the number of tests that resulted in correct diagnoses out of the total number of tests assayed. Hypotheses were formed before data collection.ResultsIn total, 30 patients (23 women [77%]; median age, 51 years [range, 28-81 years]), primarily presenting with metastatic solid malignant neoplasms, participated in this study. For 48 follow-up samples from patients previously diagnosed via cytologic analysis as having LMD with no parenchymal tumor abutting CSF, cfDNA findings were accurate in the assessment of LMD in 45 samples (94%; 95% CI, 83%-99%), whereas cytologic analysis was accurate in 36 samples (75%; 95% CI, 60%-86%), a significant difference (P = .02). Of 43 LMD-positive samples, CSF cfDNA analysis was sensitive to LMD in 40 samples (93%; 95% CI, 81%-99%), and cytologic analysis was sensitive to LMD in 31 samples (72%; 95% CI, 56%-85%), a significant difference (P = .02). For 3 patients with parenchymal brain metastases abutting the CSF and no suspicion of LMD, cytologic findings were negative for LMD in all 3 patients, whereas cfDNA findings were positive in all 3 patients.Conclusions and relevanceThis diagnostic study found improved sensitivity and accuracy of cfDNA CSF testing vs cytologic assessment for diagnosing LMD with the exception of parenchymal tumors abutting CSF, suggesting improved ability to diagnosis LMD. Consideration of incorporating CSF cfDNA analysis into clinical care is warranted.
Project description:BackgroundRecent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection.MethodsIn this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups.ResultsIndividual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1).ConclusionThese novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases.