Evidence map›Paper›PMID 37671017›Full record

ArticleCell reports methods2023

A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy.

Xiyu Peng, Jasme Lee, Matthew Adamow, Colleen Maher, Michael A Postow, Margaret K Callahan, Katherine S Panageas, Ronglai Shen

Open access · goldAbstract read
In one paragraph

Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Article
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  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Xiyu PengDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Jasme LeeDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Matthew AdamowImmune Monitoring Facility, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Colleen MaherParker Institute for Cancer Immunotherapy, San Francisco, CA 94129, USA.
Michael A PostowDepartment of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Margaret K CallahanParker Institute for Cancer Immunotherapy, San Francisco, CA 94129, USA.
Katherine S PanageasDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Ronglai ShenDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Understanding Immunotype, a Novel Biomarker for Checkpoint Blockade ResistanceR01CA276286 · NCI · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI Margaret Kathleen Callahan · 2023 to 2026
$1.7M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA276286
6 · The paper itself

Abstract

We present TopicFlow, a computational framework for flow cytometry data analysis of patient blood samples for the identification of functional and dynamic topics in circulating T cell population. This framework applies a Latent Dirichlet Allocation (LDA) model, adapting the concept of topic modeling in text mining to flow cytometry. To demonstrate the utility of our method, we conducted an analysis of ∼17 million T cells collected from 138 peripheral blood samples in 51 patients with melanoma undergoing treatment with immune checkpoint inhibitors (ICIs). Our study highlights three latent dynamic topics identified by LDA: a T cell exhaustion topic that independently recapitulates the previously identified LAG-3

Indexed as

NeoplasmsT-LymphocytesData AnalysisData MiningFlow CytometryHumansImmunotherapy

Identifiers

PMID37671017
PMCPMC10475788
OpenAlexW4385484142

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.