Evidence map›Paper›PMID 36303017›Full record

ArticleNature methods2022

Netie: inferring the evolution of neoantigen-T cell interactions in tumors.

Tianshi Lu, Seongoh Park, Yi Han, Yunguan Wang, Shawna Marie Hubert, P Andy Futreal, Ignacio Wistuba, John V Heymach, Alexandre Reuben, Jianjun Zhang and 1 more

Open access · greenAbstract read
In one paragraph

Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

8 citing papers in PubMed, 6 citations in OpenAlex.

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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

11 authors at 3 institutions in 2 countries.

Tianshi LuQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Seongoh ParkSchool of Mathematics, Statistics and Data Science, Sungshin Women's University, Seoul, Republic of Korea.
Yi HanQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Yunguan WangQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Shawna Marie HubertDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
P Andy FutrealDepartment of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0001-8663-2671
Ignacio WistubaDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
John V HeymachDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0001-9068-8942
Alexandre ReubenDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0003-4510-0382
Jianjun ZhangDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0001-7872-3477
Tao WangQuantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA. Tao.Wang@UTSouthwestern.edu.ORCID 0000-0002-4355-149X
The University of Texas MD Anderson Cancer Center · USSouthwestern Medical Center · USSungshin Women's University · KR

Funding

UT Southwestern Medical Center Simmons Comprehensive Cancer CenterP30CA142543 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI MELANIE H. COBB · 2010 to 2026
$53.7M
Finding the optimal balance of immunotherapy efficacy and toxicity.U01AI156189 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI GERBER, DAVID ERIC, WAKELAND, EDWARD K. · 2020 to 2024
$3.1M
The molecular and immune evolution in the progression of lung neoplasia to invasive adenocarcinomaR01CA234629 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ZHANG, JIANJUN · 2019 to 2023
$1.8M
Applying deep learning to predict T cell receptor binding specificity of neoantigens and response to checkpoint inhibitorsR01CA258584 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI WANG, TAO, WANG, XINLEI · 2021 to 2025
$1.4M
NCI NIH HHS P30 CA142543NCI NIH HHS R01 CA234629NCI NIH HHS R01 CA258584NIAID NIH HHS U01 AI156189
6 · The paper itself

Abstract

Neoantigens are the key targets of antitumor immune responses from cytotoxic T cells and play a critical role in affecting tumor progressions and immunotherapy treatment responses. However, little is known about how the interaction between neoantigens and T cells ultimately affects the evolution of cancerous masses. Here, we develop a hierarchical Bayesian model, named neoantigen-T cell interaction estimation (netie) to infer the history of neoantigen-CD8

Indexed as

Antigens, NeoplasmNeoplasmsBayes TheoremCell CommunicationHumansImmunotherapyAntigens, Neoplasm

Identifiers

PMID36303017
PMCPMC10083098
OpenAlexW4307407961

What OpenQuestion holds

Textmetadata
LicenceTDM
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.