scholarly journals Griffin: Framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA

Author(s):  
Anna-Lisa Doebley ◽  
Minjeong Ko ◽  
Hanna Liao ◽  
A Eden Cruikshank ◽  
Caroline Kikawa ◽  
...  

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we developed Griffin, a new method for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing (WGS) data. Griffin employs a novel GC correction procedure tailored to variable cfDNA fragment sizes, which improves the prediction of chromatin accessibility. Griffin achieved excellent performance for detecting tumor cfDNA in early-stage cancer patients (AUC=0.96). Next, we applied Griffin for the first demonstration of estrogen receptor (ER) subtyping in metastatic breast cancer from cfDNA. We analyzed 254 samples from 139 patients and predicted ER subtype with high performance (AUC=0.89), leading to insights about tumor heterogeneity. In summary, Griffin is a framework for accurate clinical subtyping and can be generalizable to other cancer types for precision oncology applications.

Dose-Response ◽  
2019 ◽  
Vol 17 (4) ◽  
pp. 155932581989101
Author(s):  
Fan Jiang ◽  
Xiaoxiao Yang ◽  
Xiping He ◽  
Mingming Yang

Liquid biopsy has the great potential of detecting early diseases before deterioration and is valued for screening abnormalities at early stage. In oncology, circulating DNA derived from shed cancer cells reflects the tissue of origin, so it could be used to locate tissue sites during early screening. However, the heterogenous parameters of different types limit the clinical application, making it inaccessible to encompass all the cancer types. Instead, for reproducible scenario as pregnancy, fetal cell-free DNA has been well utilized for screening aneuploidies. Noninvasive and convenient as is, it would be of great value in the next decades far more than early diagnosis. This review recapitulates the discovery and development of tumor and fetal cell-free DNA. The common factors are also present that could be taken into consideration when collecting, transporting, and preserving samples. Meanwhile, several protocols used for purifying cell-free DNA, either classic ones or through commercial kits, are compared carefully. In addition, the development of technologies for analyzing cell-free DNA have been summarized and discussed in detail, especially some up-to-date approaches. At the end, the potential prospect of circulating DNA is bravely depicted. In summary, although there would be a lot of efforts before it’s prevalent, cell-free DNA remains a promising tool in point-of-care diagnostic medicine.


2020 ◽  
Author(s):  
Xionghui Zhou ◽  
Yaping Liu

AbstractThe global variation of cell-free DNA fragmentation patterns is a promising biomarker for cancer diagnosis. However, the characterization of its hotspots and aberrations in early-stage cancer at the fine-scale is still poorly understood. Here, we developed an approach to de novo characterize genome-wide cell-free DNA fragmentation hotspots by integrating both fragment coverage and size from whole-genome sequencing. These hotspots are highly enriched in regulatory elements, such as promoters, and hematopoietic-specific enhancers. Surprisingly, half of the high-confident hotspots are still largely protected by the nucleosome and located near repeats, named inaccessible hotspots, which suggests the unknown origin of cell-free DNA fragmentation. In early-stage cancer, we observed the increases of fragmentation level at these inaccessible hotspots from microsatellite repeats and the decreases of fragmentation level at accessible hotspots near promoter regions, mostly with the silenced biological processes from peripheral immune cells and enriched in CTCF insulators. We identified the fragmentation hotspots from 298 cancer samples across 8 different cancer types (92% in stage I to III), 103 benign samples, and 247 healthy samples. The fine-scale fragmentation level at most variable hotspots showed cancer-specific fragmentation patterns across multiple cancer types and non-cancer controls. Therefore, with the fine-scale fragmentation signals alone in a machine learning model, we achieved 42% to 93% sensitivity at 100% specificity in different early-stage cancer. In cancer positive cases, we further localized cancer to a small number of anatomic sites with a median of 85% accuracy. The results here highlight the significance to characterize the fine-scale cell-free DNA fragmentation hotspot as a novel molecular marker for the screening of early-stage cancer that requires both high sensitivity and ultra-high specificity.


2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 3058-3058
Author(s):  
Anna Bergamaschi ◽  
Francois Collins ◽  
Chris Ellison ◽  
Yuhong Ning ◽  
Gulfem Guler ◽  
...  

3058 Background: Methylation and hydroxymethylation of cytosines enable the epigenomic regulation of gene suppression and activation. 5-hydroxymethyl-cytosine (5hmC) is globally decreased in tumor tissue. However, genome-wide analysis using precise 5hmC labelling techniques reveals more nuanced changes upon tumorigenesis and raises the possibility that this loss could be exploited for developing a cancer biomarker. This suggests that 5hmC profiles might enable discrete classification of not only tumor tissue but also of tumor cell-free DNA (cfDNA). We sought to identify genome-wide 5hmC changes in plasma based cfDNA from cancer patients representing multiple disease types, stages and clinical characteristics in comparison with non-cancer patients. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to the genome to determine 5hmC counts per genomic feature. Regularized regression models were constructed to classify cancer samples (age matched or corrected for smoking status) on non-overlapping training (80% of all samples) and test sample sets (20% of all samples). Results: 226 non-cancer patients and 278 cancers across four cancer types (breast, colorectal, lung-squamous and pancreas) were included in this study, where more than 60% of cancer samples were early stage disease (I or II). Upon comparison with non-cancer samples, 5hmC peaks have reduced enrichment in exons in breast, colorectal and lung cancer but not in pancreatic cancer. Further, 5hmC peaks in pancreas show different patterns of enrichment in 3’UTR, translational termination sites, promoters and LTR. Overall 5hmC signal density was reduced in late stage cancers across all four diseases. The ability to classify non-cancer versus cancer patients was evaluated via cross-validation of out of fold prediction in the training set with AUC > 0.84 for all four cancer types. Further, test set sensitivity across all four cancer types was found to be > 66% with 98% specificity. Conclusions: These findings suggest that 5hmC changes in plasma cfDNA enable classification of early stages of breast, colorectal, lung-squamous and pancreas cancer and are promising biomarkers for disease detection.


Lung Cancer ◽  
2015 ◽  
Vol 90 (1) ◽  
pp. 78-84 ◽  
Author(s):  
Shu Xia ◽  
Chiang-Ching Huang ◽  
Min Le ◽  
Rachel Dittmar ◽  
Meijun Du ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1448
Author(s):  
Raquel Herranz ◽  
Julia Oto ◽  
Emma Plana ◽  
Álvaro Fernández-Pardo ◽  
Fernando Cana ◽  
...  

Bladder cancer (BC) is among the most frequent cancer types in the world and is the most lethal urological malignancy. Presently, diagnostic and follow-up methods for BC are expensive and invasive. Thus, the identification of novel predictive biomarkers for diagnosis, progression, and prognosis of BC is of paramount importance. To date, several studies have evidenced that cell-free DNA (cfDNA) found in liquid biopsies such as blood and urine may play a role in the particular scenario of urologic tumors, and its analysis may improve BC diagnosis report about cancer progression or even evaluate the effectiveness of a specific treatment or anticipate whether a treatment would be useful for a specific patient depending on the tumor characteristics. In the present review, we have summarized the up-to-date studies evaluating the value of cfDNA as potential diagnostic, prognostic, or monitoring biomarker for BC in several biofluids.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3043-3043
Author(s):  
Grace Q. Zhao ◽  
Yun Bao ◽  
Heng Wang ◽  
Wanping Hu ◽  
John Coller ◽  
...  

3043 Background: Assessing the genomic and epigenomic changes on plasma cell-free DNA (cfDNA) using next-generation sequencing (NGS) has become increasingly important for cancer detection and treatment selection guidance. However, two major hurdles of existing targeted NGS methods make them impractical for the clinical setting. First, there is no comprehensive, end to end, kit solution available for targeted methylation sequencing (TMS), let alone one that analyzes both mutation and methylation information in one assay. Second, the low yield of cfDNA from clinical blood samples presents a major challenge for conducting multi-omic analysis. Thus, an assay that is capable of both genomic and epigenomic analysis would be advantageous for clinical research and future diagnostic assays. Methods: Here, we report the performance of Point-n-SeqTM dual analysis, a kit solution that can provide in-depth DNA analysis with highly flexible and customizable focused panels to enable both genomic and epigenomic analysis without sample splitting. With custom panels of tens to thousands of markers designed with > 99% first-pass success rate, we conducted both performance validation and multi-center, multi-operator, reproducibility studies. Using spike-in titration of cancer cell-line gDNA with known mutation and methylation profiles, Point-n-Seq assay achieved a reliable detection level down to 0.003% of tumor DNA with a linear relationship between the measured and expected fractions. Benchmarked with conventional targeted sequencing and methylation sequencing, Point-n-Seq solution also demonstrated improved performance, speed and shortened hands-on time. Results: In a pilot clinical study, a colorectal cancer (CRC) TMS panel covering 560 methylation markers and a mutation panel with > 350 hotspot mutations in 22 genes were used in the dual assay. Using 1ml of plasma from late-stage CRC patients, cancer-specific methylation signals were detected in all samples tested, and oncogenic mutations. In an early-stage cohort (33 stage I/II CRC patient ), comparison of the analysis between tumor-informed, personalized-mutation panels (̃100 private SNVs) for each patient and the tumor-independent CRC methylation panels were conducted. The initial results showed that tumor-independent TMS assay achieved a comparable detection compared to the personalized tumor-informed approach. Moreover, cfDNA size information (fragmentome) is also integrated into the analysis of the same Point-n-Seq workflow to improve the assay sensitivity. Conclusions: Point-n-Seq dual analysis is poised to advance both research and clinical applications of early cancer detection, minimal residual disease (MRD), and monitoring.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10544-10544
Author(s):  
Tiancheng Han ◽  
Yuanyuan Hong ◽  
Pei Zhihua ◽  
Song Xiaofeng ◽  
Jianing Yu ◽  
...  

10544 Background: Screening the biomarkers from the cell-free DNA (cfDNA) of peripheral blood is a non-invasive and promising method for cancer diagnosis. Among diverse types of biomarkers, epigenetic biomarkers have been reported to be one of the most promising ones. Epigenetic modifications are widespread on the human genome and generally have strong signals due to the similar methylation patterns shared by adjacent CpG sites. Although some epigenetic diagnostic methods have been developed based on cfDNAs, few of them could be applied to pan-cancer and their sensitivities are barely satisfactory for early cancer detection. Methods: Targeted methylation sequencing was performed using our in-house-designed panel targeting regions with abundant cancer-specific methylation CpGs. The cfDNA samples from 80 healthy individuals and 549 cancer patients of 14 cancer types were separately sequenced. The dataset was randomly split into one discovery dataset and one validation dataset. Moreover, cfDNA samples from four cancer patients were diluted with the healthy cfDNAs to generate 12 in vitro simulated samples with low circulating tumor DNA (ctDNA) fraction. Additionally, DNAs extracted from 130 unmatched tumor formalin fixation and paraffin embedding (FFPE) samples of 10 cancer types were sequenced to screen the diagnostic biomarkers. Adjacent CpG sites were first merged into methylation-correlated blocks (MCB) according to their correlations of methylation levels in tumor DNAs. The MCBs with higher methylation levels in tumor DNAs than that of healthy cfDNAs (from the discovery dataset) were defined as our hypermethylation biomarkers. For each cfDNA sample, a hypermethylation score (HM-score) was computed to measure the overall methylation level difference of selected biomarkers. The performance of our method was evaluated with the real-world dataset, while the limit of detection was estimated using the simulated low-ctDNA samples. Results: Our model based on 37 hypermethylation MCB biomarkers achieved an area under the curve (AUC) of 0.89 and 0.86 in the real-world pan-cancer discovery and validation cfDNA datasets, respectively. Furthermore, the overall specificity and sensitivity are 100% and 76.19% in the discovery dataset, and 96.67% and 72.86% in the validation dataset. In the validation dataset, 28/40 (70%) of early-stage colorectal cancer patients and 10/20 (50%) of non-small-cell lung cancer patients were successfully diagnosed. Additionally, all the simulated samples with theoretical ctDNA factions over 0.5% were predicted as diseased, demonstrating the ability of our method to detect tumor signals at early stages. Conclusions: Our cfDNA-based epigenetic method outperforms currently available methods in various cancer types, and is promising to be applied to early-stage cancer detection and samples with low ctDNA fractions.


2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Zhigang Zuo ◽  
Jiying Tang ◽  
Xiaojun Cai ◽  
Feng Ke ◽  
Zhenzong Shi

Abstract Monitoring of early-stage breast cancer is critical in promptly addressing disease relapse. Circulating cell-free DNA provides a minimally invasive and sensitive means to probing the disease. In a longitudinal analysis of 250 patients with early breast cancer, we compared the circulating cell-free DNA recovered from both plasma and urine specimens. For comparison, 50 healthy controls were also recruited. Specific mutations associated with the disease were profiled to determine the clinical sensitivity and specificity. Correlations of recovered concentrations of cell-free DNA with outcomes were examined to address early prognostication. PIK3CA mutation profiling in both plasma and urinary cell-free DNA showed an agreement of 97.2% compared with the results obtained for tumor tissues. The analysis of healthy controls revealed that cell-free DNA measurements were stable and consistent over time. Over the short 6-month period of monitoring, our analyses showed declines in recovered cell-free DNA; these findings may aid physicians in stratifying patients at higher risk for relapse. Similar results were observed in both plasma and urine specimens (hazard ratios: 2.16 and 2.48, respectively). Cell-free DNA presents a novel and sensitive method for the monitoring of early-stage breast cancer. In the present study, serial measurements of both plasma and urine specimens were useful in probing the disease.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Gulfem D. Guler ◽  
Yuhong Ning ◽  
Chin-Jen Ku ◽  
Tierney Phillips ◽  
Erin McCarthy ◽  
...  

Abstract Pancreatic cancer is often detected late, when curative therapies are no longer possible. Here, we present non-invasive detection of pancreatic ductal adenocarcinoma (PDAC) by 5-hydroxymethylcytosine (5hmC) changes in circulating cell free DNA from a PDAC cohort (n = 64) in comparison with a non-cancer cohort (n = 243). Differential hydroxymethylation is found in thousands of genes, most significantly in genes related to pancreas development or function (GATA4, GATA6, PROX1, ONECUT1, MEIS2), and cancer pathogenesis (YAP1, TEAD1, PROX1, IGF1). cfDNA hydroxymethylome in PDAC cohort is differentially enriched for genes that are commonly de-regulated in PDAC tumors upon activation of KRAS and inactivation of TP53. Regularized regression models built using 5hmC densities in genes perform with AUC of 0.92 (discovery dataset, n = 79) and 0.92–0.94 (two independent test sets, n = 228). Furthermore, tissue-derived 5hmC features can be used to classify PDAC cfDNA (AUC = 0.88). These findings suggest that 5hmC changes enable classification of PDAC even during early stage disease.


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