ASHG 2019: Comparison between Mutation Profiles of Paired Whole Blood and cfDNA Samples

Introduction

Liquid biopsies are increasingly becoming a tool of choice for researching cancer detection and monitoring. Cell-free DNA or cfDNA is simply small fragments of DNA circulating in bodily fluids. It is also known as circulating cell-free DNA (ccfDNA), circulating tumor DNA (ctDNA) and cell free-fetal DNA (cffDNA). Next-Gen Sequencing of cfDNA is coming into maturity as a non-invasive method to identify mutational profiles in many cancer types. 

Figure 1Figure 2

  • Apoptotic or necrotic cell death results in near-complete digestion of native chromatin from normal cell, tumor or fetus.
  • Each 160-175 bp DNA is wrapped ~1.67 times around one nucleosome. These protein-bound DNA fragments preferentially survive digestion and are released into the circulation, and can be recovered from peripheral blood plasma as cfDNA.
  • Typical cfDNA peaks characterized by Agilent 2100 Bioanalyzer, with a main peak at 175 bp, second and third peaks at 350 and 525 bp.
A big question is how do you separate a germ line variant from a tumor variant. Understanding the difference in a patient sample can give a more thorough understanding of a variant that can be used to study a cancer type. An easy solution is to compare germ line variants from whole blood genomic DNA (gDNA). This would couple easily with plasma sample collection as plasma can be directly separated from a single sample point.
 
Here we describe a simple method to isolate both gDNA and cfDNA from a donor blood sample and discuss the automation of both extractions. We show the efficacy of cfDNA as reliable biomarker analysis tool by comparing mutations in cfDNA vs whole blood. The study determines if the difference between tumor and germ line mutations can be established and the limitations.
 
Biomek i-SeriesDue to larger volumes necessary to extract sufficient concentrations of cfDNA, automation can assist in the extraction. The Apostle MiniMax™ High Efficiency Cell-Free DNA (cfDNA) extraction kit was automated on the Biomek i-Series. It provides equal recovery of cfDNA as a manual extraction with much less hands on-time. The kit used in the study to extract whole blood, GenFind V3, has also been automated on the Biomek i-Series; allowing for reduced hands with the same quality results as a manual extraction

Methods

Sample Preparation

Blood was collected from 3 donors in EDTA tubes. After the blood was delivered to the site 10ng of Horizon Multiplex I cfDNA Reference Standard Set was added to ½ of the blood collected from each donor. The whole blood was then centrifuged twice, for 2,000xg for 10 minutes and supernatant was moved to a fresh tube and for centrifuged a second time at 6,000xg for 30 minutes. The second supernatant was used for cfDNA extractions; and the lower phase was used for genomic DNA extractions. Both phases were then stored at -80°C. The plasma was thawed at 37°C. Half of plasma from each donor that did not have 10ng of Horizon Multiplex I cfDNA Reference Standard Set had 200ng of Horizon Multiplex I cfDNA Reference Standard Set added to it as a positive control. The plasma samples were then processed using Apostle MiniMax™. Due to the lag in separating the whole blood from the plasma the cfDNA was size-selected using SPRIselect for 200bp size. The blood was thawed at room temperature. The genomic DNA was extracted from blood using GenFind V3.
 

Sample Name

Sample Type

Treatment

cfDNA_508plus

Plasma

10 ng of Horizon Multiplex I cfDNA Reference Standard Set added prior to plasma isolation

cfDNA_509plus

cfDNA_510plus

Blood_508plus

Lower Phase of Blood

Blood_509plus

Blood_510plus

cfDNA_508C

Plasma

200 ng of Horizon Multiplex I cfDNA Reference Standard Set added after plasma isolation

cfDNA_509C

cfDNA_510C

Blood_508C

Lower Phase of Blood

Nothing added

Blood_509C

Blood_510C

Library Preparation

Following extraction of gDNA and cfDNA, the DNA was quantified using Quant-it Picogreen Assay for the gDNA and using Kappa hgQuant kit for the cfDNA. Library construction was done using 100 ng of DNA with the Swift Biosciences Accel-NGS 2S Hyb DNA Library Kit, following the library construction genes were enriched prior to sequencing using the Swift Biosciences Pan-Cancer Hyb Panel. The libraries were sequenced on a NextSeq 550. 

Sequencing Analysis

The sequencing was analyzed using Illumina Basespace; the reads were aligned to the genes enriched in the Swift Biosciences Pan-Cancer Hyb Panel by using the BWA enrichment application. 

Similar coverage of reads for cfDNA and gDNA

Sample Name+

Total Aligned Reads

Percent Aligned Reads

Targeted Aligned Reads

Read Enrichment

Padded Target Aligned Reads

Padded Read Enrichment

Blood_508C

58,813,981

100%

33333485

57%

35026658

60%

Blood_508plus

22,512,598

100%

13011447

58%

13655481

61%

Blood_509C

17,747,434

100%

11593225

65%

12237570

69%

Blood_509plus

18,678,850

100%

12752101

68%

13427976

72%

Blood_510C

20,504,009

100%

12370374

60%

12973986

63%

Blood_510plus

16,742,634

100%

11320236

68%

11894055

71%

cfDNA_508C

26,162,565

100%

17505630

67%

17734578

68%

cfDNA_508plus

30,039,905

100%

18265618

61%

18567893

62%

cfDNA_509C

33,127,967

100%

18915218

57%

19157799

58%

cfDNA_509plus

8,382,099

100%

5973231

71%

6154497

73%

cfDNA_510C

32,309,659

100%

19874851

62%

20109025

62%

cfDNA_510plus

12,908,033

100%

8773743

68%

8907368

69%

The table above shows the number of reads that were aligned and the number of reads that were aligned to the targeted genes. The samples containing gDNA had on average 25 million reads and the cfDNA had on average 24 million reads.  

Sample Name

Mean Region Coverage Depth

Uniformity of Coverage (Pct > 0.2*mean)

Target Coverage at 1X

Target Coverage at 10X

Target Coverage at 20X

Target Coverage at 50X

Blood_508C

4489.2

99.70%

100.00%

100.00%

100.00%

100.00%

Blood_508plus

1739.2

90.40%

100.00%

100.00%

100.00%

99.90%

Blood_509C

1550.5

88.80%

100.00%

100.00%

100.00%

99.80%

Blood_509plus

1703.6

86.50%

100.00%

100.00%

100.00%

99.80%

Blood_510C

1651.4

91.10%

100.00%

100.00%

100.00%

99.80%

Blood_510plus

1513

87.40%

100.00%

100.00%

100.00%

99.80%

cfDNA_508C

2315.1

92.40%

100.00%

100.00%

100.00%

99.90%

cfDNA_508plus

2432.1

90.50%

100.00%

100.00%

100.00%

99.90%

cfDNA_509C

2523.4

99.70%

100.00%

100.00%

100.00%

100.00%

cfDNA_509plus

801.6

85.10%

100.00%

100.00%

99.90%

99.20%

cfDNA_510C

2634.5

93.70%

100.00%

100.00%

100.00%

100.00%

cfDNA_510plus

1166.7

88.90%

100.00%

100.00%

99.90%

99.70%

The table above shows the mean coverage depth for each sample. The average coverage for both gDNA and cfDNA was ~91%. At least 99% of the genes had coverage at 50x. This indicates that the variants can be called with high confidence. 

Variant differences are observed between cfDNA and gDNA

Three of 8 the variants were found in the spiked Horizon Multiplex I cfDNA Reference Standard Set. This most likely is due to the low amounts of horizon cfDNA sample compared to the overall DNA extracted.  None of the Horizon cfDNA was detected in the gDNA sequences. The sequences could have not been detected due either to low amounts and insufficient sequencing coverage or the sequences were not present in the lower phase of blood after centrifugation. 

Figure 1 - Number of Variants Found

Figure 2 - Number of Variants Found

Reference Standard Gene

Reference Standard Variant

Reference Standard Coordinate

Reference Standard mutation Type

Samples  where Reference Standard was found

KRAS

G12D

25398284

C>T

cfDNA_ 508C

cfDNA_ 510C

NRAS

Q61K

1.15E+08

G>T

cfDNA_ 509C

 

NRAS

A59T

1.15E+08

C>T

cfDNA_ 509plus

 

 

Sample Name

SNVs

SNV Het/Hom Ratio

SNV Ts/Tv Ratio

Indels

Indel Het/Hom Ratio

Blood_508C

500

1.4

2.2

117

3

Blood_508plus

500

1.4

2.2

181

6

Blood_509C

588

2.4

2.5

201

9.6

Blood_509plus

590

2.4

2.5

196

8.8

Blood_510C

501

1.7

2.3

197

8

Blood_510plus

502

1.8

2.2

183

7.3

cfDNA_508C

955

8.3

2.6

426

25.6

cfDNA_508plus

636

6.8

2.3

275

18.6

cfDNA_509C

963

8.2

2.6

434

26.1

cfDNA_509plus

717

8.3

2.5

304

32.8

cfDNA_510C

944

8.3

2.6

455

31.5

cfDNA_510plus

669

7.4

2.4

303

29.3

Because we were unable to detect all of the spiked cfDNA, we extended our analysis to all variants. The total number of SNVs and insertion and deletions can be seen in the table above. For all three of the donors the average total number of variants found in gDNA was 29 and for cfDNA was 55 (Figure 1). To further this analysis we examined the number of variants that were only found in cfDNA or only found in gDNA. The number of variants only found in gDNA was 10 fold less than the number of variants only found in cfDNA for all three donors (figure 2). Because the majority of the mutations were found in both, this could indicate that any variant found only in the cfDNA could be candidates for ctDNA analysis. 

Conclusions

  • Variants found only in cfDNA could be used as an initial screen for ctDNA analysis
  • Apostle MiniMax™ and GenFind V3 can be used together to get a picture of germ line variants and cfDNA, potential ctDNA, variants
  • These results show that a holistic view of a cancer subject can be gained by using one sample source, whole blood
     
In partnership with

Swift Biosciences™

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