Evidence map›Paper›PMID 32571915›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Circulating immune cell phenotype dynamics reflect the strength of tumor-immune cell interactions in patients during immunotherapy.

Jason I Griffiths, Pierre Wallet, Lance T Pflieger, David Stenehjem, Xuan Liu, Patrick A Cosgrove, Neena A Leggett, Jasmine A McQuerry, Gajendra Shrestha, Maura Rossetti and 6 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed
5.6field-weighted citation impact, top 3% of its field
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

75 citing papers in PubMed, 97 citations in OpenAlex.

  1. Towards liquid biopsy-based analysis of antitumour immunity.Nature reviews. Clinical oncology · 2026
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15 more citing papers are in PubMed but not listed here.

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 at 6 institutions in 1 country.

Jason I GriffithsDepartment of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010.ORCID 0000-0002-1667-8233
Pierre WalletDepartment of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010.ORCID 0000-0001-6639-9526
Lance T PfliegerDepartment of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010.
David StenehjemCollege of Pharmacy, University of Minnesota, Duluth, MN 55812.ORCID 0000-0002-1831-285X
Xuan LiuDepartment of Integrative Biology and Pharmacology, School of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030.
Patrick A CosgroveDepartment of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010.ORCID 0000-0001-7784-7785
Neena A LeggettDepartment of Integrative Biology and Pharmacology, School of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030.
Jasmine A McQuerryDepartment of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010.
Gajendra ShresthaDepartment of Pharmacology and Toxicology, College of Pharmacy, University of Utah, Salt Lake City, UT 84112.ORCID 0000-0001-6525-7913
Maura RossettiDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, Los Angeles, CA 90095.
Gemalene SungaDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, Los Angeles, CA 90095.ORCID 0000-0002-8695-1813
Philip J MoosDepartment of Pharmacology and Toxicology, College of Pharmacy, University of Utah, Salt Lake City, UT 84112.
Frederick R AdlerDepartment of Mathematics, University of Utah, Salt Lake City, UT 84112.
Jeffrey T ChangDepartment of Integrative Biology and Pharmacology, School of Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030.
Sunil SharmaTranslational Oncology Research & Drug Discovery, Translational Genomics Research Institute, Phoenix, AZ 85004 ssharma@tgen.org abild@coh.org.
Andrea H BildDepartment of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010; ssharma@tgen.org abild@coh.org.
City Of Hope National Medical Center · USThe University of Texas Health Science Center at Houston · USUniversity of Utah · USUniversity of California, Los Angeles · USTranslational Genomics Research Institute · USUniversity of Minnesota, Duluth · US

Funding

UTAH REGIONAL CANCER CENTERP30CA042014 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI KATHARINE S ULLMAN · 1986 to 2026
$72.6M
Project 2: Targeting Cooperative Phenotypes Common in Spatial HeterogeneityU54CA209978 · NCI · UNIVERSITY OF UTAH · PI BILD, ANDREA HOPE · 2017 to 2021
$10.5M
NCI NIH HHS P30 CA042014NCI NIH HHS U54 CA209978
6 · The paper itself

Abstract

The extent to which immune cell phenotypes in the peripheral blood reflect within-tumor immune activity prior to and early in cancer therapy is unclear. To address this question, we studied the population dynamics of tumor and immune cells, and immune phenotypic changes, using clinical tumor and immune cell measurements and single-cell genomic analyses. These samples were serially obtained from a cohort of advanced gastrointestinal cancer patients enrolled in a trial with chemotherapy and immunotherapy. Using an ecological population model, fitted to clinical tumor burden and immune cell abundance data from each patient, we find evidence of a strong tumor-circulating immune cell interaction in responder patients but not in those patients that progress on treatment. Upon initiation of therapy, immune cell abundance increased rapidly in responsive patients, and once the peak level is reached tumor burden decreases, similar to models of predator-prey interactions; these dynamic patterns were absent in nonresponder patients. To interrogate phenotype dynamics of circulating immune cells, we performed single-cell RNA sequencing at serial time points during treatment. These data show that peripheral immune cell phenotypes were linked to the increased strength of patients' tumor-immune cell interaction, including increased cytotoxic differentiation and strong activation of interferon signaling in peripheral T cells in responder patients. Joint modeling of clinical and genomic data highlights the interactions between tumor and immune cell populations and reveals how variation in patient responsiveness can be explained by differences in peripheral immune cell signaling and differentiation soon after the initiation of immunotherapy.

Indexed as

PhenotypeCell CommunicationGene Expression RegulationHumansImmunologic FactorsImmunotherapyMonocytesNeoplasmsSequence Analysis, RNASingle-Cell AnalysisT-LymphocytesTumor MicroenvironmentImmunologic Factorscancerecological modelsimmunotherapyphenotypessingle-cell RNA sequencing

Identifiers

PMID32571915
PMCPMC7355015
OpenAlexW3036731669

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.