NDRquant

NDRquant is a method for quantification the content of circulating tumor DNA (ctDNA) in plasma cell-free DNA (cfDNA) based on tissue-specific cfDNA degradation of nucleosome depleted regions (NDR).

References:

Zhu, G. et al. Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden. Nat Commun 12, 2229 (2021). https://doi.org/10.1038/s41467-021-22463-y

 

Description

NDRquant is a quantitative method for estimation of ctDNA levels in plasma samples using local tissue-specific cell-free DNA degradation patterns. NDRquant-CRC is quantitative model, based on 6 regulatory regions, that can estimate ctDNA levels in blood plasma from colorectal cancer patients. NDRquant-PAN is a model pased on 10 regulatory regions that is able to estimate ctDNA levels in blood plasma from both breast cancer and colorectal cancer patients. Since the model requires data from 10 or less NDRs, these regions can be profiled at low cost by capturing <25 kb of genomic sequence, potentially enabling quantitative low-cost tracking of ctDNA dynamics and disease progression.

 

Usage Example

The NDRquant workflow comprise the following 2 steps:

1. Generating relative coverages of the predictive NDRs.

For a given promoter NDR (-150 to 50bp relative to TSS), the raw coverage is divided by the mean raw coverage of the upstream (-2000 to -1000bp relative to TSS) and downstream (1000 to 2000bp relative to TSS) flanks. A similar approach was used for the first exon-intron junction (NDR, -300 to -100 bp relative to first exon end). The genomic locations of predictive NDRs for the NDRquant-CRC and NDRquant-Pan models are provided in the data folder. The full code for calculating the relative coverage of promoter/junction NDRs is available in the code folder (scripts: "generate-feature-promoter.sh", "generate-feature-junction.sh").

example:

For a given plasma sample, we first compute depth at NDR and flanking regions:

  > samtools depth -aa -r NDR.site in.bam > NDR.depth
  > samtools depth -aa -r Flanks.site in.bam > Flanks.depth
  > cat NDR.depth
  19 41082591 89
  19 41082592 86
  19 41082593 87
  ...........
  19 41082791 95
  > mean_flanks=$(awk '{ total += $3 } END { print total/NR }' Flanks.depth)
  > Relative_coverage_NDR=$(awk -v flanks=$mean_flanks '{if($3>2) print 2/flanks; else print $3/flanks}' NDR.depth | awk '{ total += $1 } END { print total/NR }')
  > echo "Relative coverage is" $Relative_coverage_NDR
  Relative coverage is 0.40

Gene	Transcript	Chr	Site	Orientation	Region	NDR.site	Flanks.site	Relative_coverage
SHKBP1	ENST00000599716	19	41082891	+	junction	19:41082591-41082791	19:41080891-41081891 19:41083891-41084891	0.40
ACSL1	ENST00000454703	4	185747070	-	junction	4:185747170-185747370	4:185745070-185746070 4:185748070-185749070	0.49
BCAR1	ENST00000162330	16	75285369	-	junction	16:75285469-75285669	16:75283369-75284369 16:75286369-75287369	0.78
RAB25	ENST00000361084	1	156030951	+	promoter	1:156030801-156031001	1:156028951-156029951 1:156031951-156032951	0.85
PRTN3	ENST00000234347	19	840960	+	promoter	19:840810-841010	19:838960-839960 19:841960-842960	1.01
LSR	ENST00000605618	19	35739922	+	promoter	19:35739772-35739972	19:35737922-35738922 19:35740922-35741922	0.84

2. Estimating the ctDNA fractions.

The ctDNA fraction can be estimated from the relative coverages of the predictive NDRs with linear regression using the trained parameters (data/ folder, "model coefficients.xlsx").

example:

The ctDNA fraction can be estimated from the calculated relative coverages above using the trained parameters:

fraction=sum(Coefficient*Relative_coverage)+Intercept

Feature	Gene	Transcript	Coefficient	Relative_coverage
1	SHKBP1	ENST00000599716	0.607	0.40
2	ACSL1	ENST00000454703	0.431	0.49
3	BCAR1	ENST00000162330	-0.321	0.78
4	RAB25	ENST00000361084	-0.213	0.85
5	PRTN3	ENST00000234347	0.062	1.01
6	LSR	ENST00000605618	-0.174	0.84
Intercept = 0.4368

 

Method Development

At this stage, NDRquant-CRC and NDRquant-PAN has been developed and benchmarked with whole genome sequencing (WGS) data of plasma samples from healthy donors, colorectal cancer (CRC) and breast cancer (BRCA) patients. The NDRquant-CRC model has been further validated using capture-based sequencing data targeting the 6 NDRs across >50 independent plasma samples from CRC patients. The data used for development and benchmarking of the models is summarized below.

Model	No. of NDRs	WGS data (model development)	Capture data (validation)
CRC	6	CRC (n=12), Healthy (n=29)	CRC (n=53)
PAN (multiple cancers)	10	CRC (n=12), BRCA (n=10), Healthy (n=29)	N/A - in progress

 

Data Availability

cfDNA sequencing data have been deposited at the European Genome-phenome Archive (EGA) under the accession code EGAS00001004657. https://ega-archive.org/studies/EGAS00001004657