Evidence map›Paper›PMID 39131379›Full record

ArticlebioRxiv : the preprint server for biology2024

Impact of preanalytical factors on liquid biopsy in the canine cancer model.

Kate Megquier, Christopher Husted, Justin Rhoades, Michelle E White, Diane P Genereux, Frances L Chen, Kan Xiong, Euijin Kwon, Ross Swofford, Corrie Painter and 4 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Kate MegquierBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-1458-0865
Christopher HustedBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Justin RhoadesBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Michelle E WhiteBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Diane P GenereuxBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Frances L ChenBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Kan XiongBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Euijin KwonGenomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA.
Ross SwoffordGenomics and Computational Biology, UMass Chan Medical School, Worcester, MA, USA.
Corrie PainterBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Viktor AdalsteinssonBroad Institute of MIT and Harvard, Cambridge, MA, USA.
Cheryl A LondonTufts Cummings School of Veterinary Medicine, North Grafton, MA, USA.
Heather L GardnerTufts Cummings School of Veterinary Medicine, North Grafton, MA, USA.
Elinor K KarlssonBroad Institute of MIT and Harvard, Cambridge, MA, USA.

Funding

Transforming family dogs into a powerful and accessible model for human cancerR37CA218570 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI KARLSSON, ELINOR · 2018 to 2022
$3.2M
Enhancing the efficacy of immunotherapy in DLBCL using rational combination approachesU01CA224153 · NCI · TUFTS UNIVERSITY BOSTON · PI LONDON, CHERYL A · 2017 to 2021
$3.1M
Leveraging canine spontaneous cancer to optimize the power of blood biopsyR01CA255319 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI KARLSSON, ELINOR, LONDON, CHERYL A · 2021 to 2025
$3.1M
Optimizing Novel Immunotherapy Combinations Targeting the Tumor Microenvironment in Canine Spontaneous OsteosarcomaU01CA224182 · NCI · COLORADO STATE UNIVERSITY · PI DOW, STEVEN W., LONDON, CHERYL A · 2017 to 2022
$2.8M
Elucidating the therapeutic utility of targeting metabolic dependencies in osteosarcomaK01OD028268 · OD · TUFTS UNIVERSITY BOSTON · PI GARDNER, HEATHER LYNN · 2020 to 2024
$631k
Advancing precision medicine through development of the canine comparative cancer modelF32CA247088 · NCI · BROAD INSTITUTE, INC. · PI MEGQUIER, KATHERINE JANE · 2020 to 2022
$205k
NCI NIH HHS F32 CA247088NCI NIH HHS R01 CA255319NCI NIH HHS R37 CA218570NCI NIH HHS U01 CA224153NCI NIH HHS U01 CA224182NIH HHS K01 OD028268
6 · The paper itself

Abstract

While liquid biopsy has potential to transform cancer diagnostics through minimally-invasive detection and monitoring of tumors, the impact of preanalytical factors such as the timing and anatomical location of blood draw is not well understood. To address this gap, we leveraged pet dogs with spontaneous cancer as a model system, as their compressed disease timeline facilitates rapid diagnostic benchmarking. Key liquid biopsy metrics from dogs were consistent with existing reports from human patients. The tumor content of samples was higher from venipuncture sites closer to the tumor and from a central vein. Metrics also differed between lymphoma and non-hematopoietic cancers, urging cancer-type-specific interpretation. Liquid biopsy was highly sensitive to disease status, with changes identified soon after post chemotherapy administration, and trends of increased tumor fraction and other metrics observed prior to clinical relapse in dogs with lymphoma or osteosarcoma. These data support the utility of pet dogs with cancer as a relevant system for advancing liquid biopsy platforms.

Indexed as

cancercaninecell-free DNAcomparativeliquid biopsyoptimization

Identifiers

PMID39131379
PMCPMC11312437

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.