Evidence map›Paper›PMID 33188016›Full record

ArticleScience advances2020

Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome.

Alvin Shi, Gyulnara G Kasumova, William A Michaud, Jessica Cintolo-Gonzalez, Marta Díaz-Martínez, Jacqueline Ohmura, Arnav Mehta, Isabel Chien, Dennie T Frederick, Sonia Cohen and 6 more

Abstract read
In one paragraph

Article in Science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

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  19. Biomarkers for immunotherapy of hepatocellular carcinoma.Nature reviews. Clinical oncology · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Alvin ShiComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.ORCID 0000-0002-6625-6792
Gyulnara G KasumovaDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.
William A MichaudDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.
Jessica Cintolo-GonzalezDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.
Marta Díaz-MartínezDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.
Jacqueline OhmuraDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-5894-2493
Arnav MehtaCancer Center, Massachusetts General Hospital, Boston, MA, USA.
Isabel ChienComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
Dennie T FrederickDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.
Sonia CohenDepartment of Surgery, Massachusetts General Hospital, Boston, MA, USA.
Deborah PlanaCancer Center, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-4218-1693
Douglas JohnsonDepartment of Medicine, Vanderbilt University, Nashville, TN, USA.
Keith T FlahertyCancer Center, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-3402-0478
Ryan J SullivanCancer Center, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0001-5344-6645
Manolis KellisComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. gmboland@partners.org manoli@mit.edu.ORCID 0000-0001-7113-9630
Genevieve M BolandBroad Institute of Harvard and MIT, Cambridge, MA, USA. gmboland@partners.org manoli@mit.edu.ORCID 0000-0002-7522-6173

Funding

Harvard Clinical and Translational Science CenterUL1TR001102 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$106.2M
Medical Scientist Training ProgramT32GM007753 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI WALENSKY, LOREN DAVID · 1985 to 2021
$50.0M
Training Program in Cancer Biology and TherapeuticsT32CA071345 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Daniel A. Haber, Lecia V. Sequist · 1997 to 2026
$10.6M
Graduate Training in Computational and Systems BiologyT32GM087237 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BURGE, CHRISTOPHER B · 2009 to 2023
$4.6M
NCATS NIH HHS UL1 TR001102NCI NIH HHS T32 CA071345NIGMS NIH HHS T32 GM007753NIGMS NIH HHS T32 GM087237
6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) show promise, but most patients do not respond. We identify and validate biomarkers from extracellular vesicles (EVs), allowing non-invasive monitoring of tumor- intrinsic and host immune status, as well as a prediction of ICI response. We undertook transcriptomic profiling of plasma-derived EVs and tumors from 50 patients with metastatic melanoma receiving ICI, and validated with an independent EV-only cohort of 30 patients. Plasma-derived EV and tumor transcriptomes correlate. EV profiles reveal drivers of ICI resistance and melanoma progression, exhibit differentially expressed genes/pathways, and correlate with clinical response to ICI. We created a Bayesian probabilistic deconvolution model to estimate contributions from tumor and non-tumor sources, enabling interpretation of differentially expressed genes/pathways. EV RNA-seq mutations also segregated ICI response. EVs serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, function as predictive markers of ICI responsiveness, and monitor tumor persistence and immune activation.

Identifiers

PMID33188016
PMCPMC7673759

What OpenQuestion holds

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Registered trials

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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.