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Genomic profiling of post-transplant lymphoproliferative disorders using cell-free DNA

Overview of attention for article published in Journal of Hematology & Oncology, September 2023
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  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Genomic profiling of post-transplant lymphoproliferative disorders using cell-free DNA
Published in
Journal of Hematology & Oncology, September 2023
DOI 10.1186/s13045-023-01500-x
Pubmed ID
Authors

Nick Veltmaat, Yujie Zhong, Filipe Montes de Jesus, Geok Wee Tan, Johanna A. A. Bult, Martijn M. Terpstra, Pim G. N. J. Mutsaers, Wendy B. C. Stevens, Rogier Mous, Joost S. P. Vermaat, Martine E. D. Chamuleau, Walter Noordzij, Erik A. M. Verschuuren, Klaas Kok, Joost L. Kluiver, Arjan Diepstra, Wouter J. Plattel, Anke van den Berg, Marcel Nijland

Abstract

Diagnosing post-transplant lymphoproliferative disorder (PTLD) is challenging and often requires invasive procedures. Analyses of cell-free DNA (cfDNA) isolated from plasma is minimally invasive and highly effective for genomic profiling of tumors. We studied the feasibility of using cfDNA to profile PTLD and explore its potential to serve as a screening tool. We included seventeen patients with monomorphic PTLD after solid organ transplantation in this multi-center observational cohort study. We used low-coverage whole genome sequencing (lcWGS) to detect copy number variations (CNVs) and targeted next-generation sequencing (NGS) to identify Epstein-Barr virus (EBV) DNA load and somatic single nucleotide variants (SNVs) in cfDNA from plasma. Seven out of seventeen (41%) patients had EBV-positive tumors, and 13/17 (76%) had stage IV disease. Nine out of seventeen (56%) patients showed CNVs in cfDNA, with more CNVs in EBV-negative cases. Recurrent gains were detected for 3q, 11q, and 18q. Recurrent losses were observed at 6q. The fraction of EBV reads in cfDNA from EBV-positive patients was 3-log higher compared to controls and EBV-negative patients. 289 SNVs were identified, with a median of 19 per sample. SNV burden correlated significantly with lactate dehydrogenase levels. Similar SNV burdens were observed in EBV-negative and EBV-positive PTLD. The most commonly mutated genes were TP53 and KMT2D (41%), followed by SPEN, TET2 (35%), and ARID1A, IGLL5, and PIM1 (29%), indicating DNA damage response, epigenetic regulation, and B-cell signaling/NFkB pathways as drivers of PTLD. Overall, CNVs were more prevalent in EBV-negative lymphoma, while no difference was observed in the number of SNVs. Our data indicated the potential of analyzing cfDNA as a tool for PTLD screening and response monitoring.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 25%
Researcher 2 17%
Student > Ph. D. Student 1 8%
Unknown 6 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 25%
Nursing and Health Professions 3 25%
Unknown 6 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 September 2023.
All research outputs
#8,361,778
of 24,988,588 outputs
Outputs from Journal of Hematology & Oncology
#596
of 1,274 outputs
Outputs of similar age
#118,078
of 337,211 outputs
Outputs of similar age from Journal of Hematology & Oncology
#7
of 10 outputs
Altmetric has tracked 24,988,588 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,274 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,211 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.