Evidence map›Paper›PMID 34597589›Full record

ArticleCancer cell2021

The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma.

Chloé B Steen, Bogdan A Luca, Mohammad S Esfahani, Armon Azizi, Brian J Sworder, Barzin Y Nabet, David M Kurtz, Chih Long Liu, Farnaz Khameneh, Ranjana H Advani and 6 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 231 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
231citing papers in PubMed, 1 pooled it
–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

231 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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171 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Chloé B SteenDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
Bogdan A LucaDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Mohammad S EsfahaniDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA.
Armon AziziDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
Brian J SworderDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA.
Barzin Y NabetDepartment of Radiation Oncology, Stanford University Medical Center, Stanford, CA 94305, USA.
David M KurtzDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA.
Chih Long LiuDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA.
Farnaz KhamenehDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
Ranjana H AdvaniDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA.
Yasodha NatkunamDepartment of Pathology, Stanford University Medical Center, Stanford, CA 94305, USA.
June H MyklebustDepartment of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for B-cell malignancies, Institute for Clinical Medicine, University of Oslo, Oslo, Norway.
Maximilian DiehnDepartment of Radiation Oncology, Stanford University Medical Center, Stanford, CA 94305, USA.
Andrew J GentlesDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA.
Aaron M NewmanDepartment of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology & Regenerative Medicine, Stanford University, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: amnewman@stanford.edu.
Ash A AlizadehDepartment of Medicine, Division of Oncology, Stanford University, Stanford, CA 94305, USA; Institute for Stem Cell Biology & Regenerative Medicine, Stanford University, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: arasha@stanford.edu.

Funding

Stanford Cancer Immune Monitoring and Analysis Center (CIMAC)U24CA224309 · NCI · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Holden T. Maecker · 2017 to 2026
$19.9M
Spatial-Genomic Integrative Multi-Species Analysis of Lymph Node MetastasisU54CA209971 · NCI · STANFORD UNIVERSITY · PI NOLAN, GARRY P, PLEVRITIS, SYLVIA KATINA · 2016 to 2021
$11.0M
Circulating Genomic Determinants of Treatment Failure in Hodgkin LymphomaR01CA257655 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2021 to 2025
$3.2M
Molecularly-based outcome and toxicity prediction after radiotherapy for lung cancerR01CA254179 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2020 to 2024
$3.1M
Analysis of urine tumor nucleic acids for detection and personalized surveillance of bladder cancerR01CA244526 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2020 to 2024
$3.0M
A Genomic Framework for Molecular Risk Prediction & Individualized Lymphoma TherapyR01CA233975 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2019 to 2023
$2.8M
Delineating developmental programs driving tumorigenesis in triple-negative breast cancerR01CA255450 · NCI · STANFORD UNIVERSITY · PI NEWMAN, AARON M · 2021 to 2025
$2.5M
Noninvasive monitoring of lung cancer patients treated with radiotherapyR01CA188298 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2015 to 2019
$1.8M
Molecular Characterization and Personalized Approaches to Non-Hodgkin Lymphoma from Circulating Tumor DNAK08CA241076 · NCI · STANFORD UNIVERSITY · PI KURTZ, DAVID MATTHEW · 2019 to 2023
$957k
Ultrasensitive Quantitation of Circulating Tumor DNAR00CA187192 · NCI · STANFORD UNIVERSITY · PI NEWMAN, AARON M · 2017 to 2019
$747k
NCI NIH HHS K08 CA241076NCI NIH HHS R00 CA187192NCI NIH HHS R01 CA188298NCI NIH HHS R01 CA233975NCI NIH HHS R01 CA244526NCI NIH HHS R01 CA254179NCI NIH HHS R01 CA255450NCI NIH HHS R01 CA257655NCI NIH HHS U24 CA224309NCI NIH HHS U54 CA209971
6 · The paper itself

Abstract

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-origin subtypes and associated genomic lesions, but also by diverse cell types and cell states in the tumor microenvironment (TME). However, dissecting these cell states and their clinical relevance at scale remains challenging. Here, we implemented EcoTyper, a machine-learning framework integrating transcriptome deconvolution and single-cell RNA sequencing, to characterize clinically relevant DLBCL cell states and ecosystems. Using this approach, we identified five cell states of malignant B cells that vary in prognostic associations and differentiation status. We also identified striking variation in cell states for 12 other lineages comprising the TME and forming cell state interactions in stereotyped ecosystems. While cell-of-origin subtypes have distinct TME composition, DLBCL ecosystems capture clinical heterogeneity within existing subtypes and extend beyond cell-of-origin and genotypic classes. These results resolve the DLBCL microenvironment at systems-level resolution and identify opportunities for therapeutic targeting (https://ecotyper.stanford.edu/lymphoma).

Indexed as

EcosystemHumansLymphoma, Large B-Cell, DiffusePrognosisTumor MicroenvironmentCIBERSORTxdiffuse large B cell lymphomadigital cytometryDLBCLEcoTyperexpression deconvolutionlymphomatumor ecosystemstumor immunologytumor microenvironment

Identifiers

PMID34597589
PMCPMC9205168

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.