Back

Enhanced specificity of high sensitivity somatic variant profiling in cell-free DNA via paired normal sequencing: design, validation, and clinical experience of the MSK-ACCESS liquid biopsy assay

Brannon, A. R.; Jayakumaran, G.; Diosdado, M.; Patel, J.; Razumova, A.; Hu, Y.; Meng, F.; Haque, M.; Sadowska, J.; Sadowska, J.; Murphy, B.; Baldi, T.; Johnson, I.; Ptashkin, R.; Hasan, M.; Srinivasan, P.; Rema, A. B.; Rijo, I.; Agarunov, A.; Won, H.; Perera, D.; Brown, D. N.; Samolia, A.; Jing, X.; Gedvilaite, E.; Yang, J. L.; Stephens, D. P.; Dix, J.-M.; DeGroat, N.; Nafa, K.; Syed, A.; Li, A.; Lebow, E. S.; Bowman, A. S.; Ferguson, D. C.; Liu, Y.; Mata, D. A.; Sharma, R.; Yang, S.-R.; Bale, T.; Benhamida, J. K.; Chang, J. C.; Dogan, S.; Hameed, M. R.; Hechtman, J. F.; Moung, C.; Ross, D. S.

2020-06-29 genomics
10.1101/2020.06.27.175471 bioRxiv
Show abstract

Circulating cell-free DNA (cfDNA) from blood plasma of cancer patients can be used to interrogate somatic tumor alterations non-invasively or when adequate tissue is unavailable. We have developed and clinically implemented MSK-ACCESS (Analysis of Circulating cfDNA to Evaluate Somatic Status), an NGS assay for detection of very low frequency somatic alterations in select exons and introns of 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 98% for a priori mutation profiling. To evaluate the performance and utility of MSK-ACCESS, we report results from the first 681 prospective blood samples (617 patients) that underwent clinical analysis to guide patient management. Somatic mutations, copy number, and/or structural variants were detected in 73% of the samples, and 56% of these circulating-tumor DNA (ctDNA) positive samples had clinically actionable alterations. The utilization of matched white blood cell sequencing allowed retention of somatic alterations while filtering out over 10,000 germline and clonal hematopoiesis variants, thereby greatly enhancing the specificity of the assay. Taken together, our experience illustrates the importance of analyzing a matched normal sample when interpreting cfDNA results and highlights the potential of cfDNA profiling to guide treatment selection, monitor treatment response, and identify mechanisms of treatment resistance.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Clinical Chemistry
22 papers in training set
Top 0.1%
19.1%
2
Genome Medicine
154 papers in training set
Top 0.3%
12.6%
3
The Journal of Molecular Diagnostics
36 papers in training set
Top 0.1%
6.9%
4
PLOS ONE
4510 papers in training set
Top 26%
6.5%
5
Journal of Clinical Microbiology
120 papers in training set
Top 0.5%
4.0%
6
Scientific Reports
3102 papers in training set
Top 30%
4.0%
50% of probability mass above
7
Nature Communications
4913 papers in training set
Top 39%
3.7%
8
Clinical Cancer Research
58 papers in training set
Top 0.7%
2.4%
9
Clinical Infectious Diseases
231 papers in training set
Top 2%
2.4%
10
Cancer Research Communications
46 papers in training set
Top 0.3%
2.1%
11
Med
38 papers in training set
Top 0.3%
1.7%
12
Annals of Oncology
13 papers in training set
Top 0.5%
1.5%
13
BMC Genomics
328 papers in training set
Top 3%
1.4%
14
Genetics in Medicine
69 papers in training set
Top 0.8%
1.2%
15
Cancer Medicine
24 papers in training set
Top 1.0%
1.2%
16
Cell Reports Medicine
140 papers in training set
Top 6%
1.1%
17
JCI Insight
241 papers in training set
Top 5%
1.0%
18
EBioMedicine
39 papers in training set
Top 0.7%
1.0%
19
The American Journal of Human Genetics
206 papers in training set
Top 3%
0.9%
20
Nucleic Acids Research
1128 papers in training set
Top 15%
0.9%
21
Nature Biotechnology
147 papers in training set
Top 7%
0.8%
22
EMBO Molecular Medicine
85 papers in training set
Top 4%
0.8%
23
Science Translational Medicine
111 papers in training set
Top 6%
0.8%
24
Cell
370 papers in training set
Top 17%
0.8%
25
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 44%
0.8%
26
Diagnostic Microbiology and Infectious Disease
21 papers in training set
Top 0.2%
0.8%
27
Oncotarget
15 papers in training set
Top 0.4%
0.8%
28
eLife
5422 papers in training set
Top 59%
0.7%
29
Nature Medicine
117 papers in training set
Top 5%
0.7%
30
NAR Genomics and Bioinformatics
214 papers in training set
Top 4%
0.7%