Evidence map›Paper›PMID 34970479›Full record

ArticleFrontiers in oncology2021

GDPLichi: a DNA Damage Repair-Related Gene Classifier for Predicting Lung Adenocarcinoma Immune Checkpoint Inhibitors Response.

Yang Leng, Shiying Dang, Fei Yin, Tianshun Gao, Xing Xiao, Yi Zhang, Lin Chen, Changfei Qin, Nannan Lai, Xiao-Yong Zhan and 7 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2021. 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
–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

8 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
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

17 authors.

Yang LengScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Shiying DangScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Fei YinDepartment of Thoracic Surgery, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Tianshun GaoScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Xing XiaoScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Yi ZhangScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Lin ChenScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Changfei QinScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Nannan LaiScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Xiao-Yong ZhanScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Ke HuangScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Chuanming LuoCenter for Clinical Neuroscience, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Yang KangScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Nan WangScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Yun LiDepartment of Thoracic Surgery, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Yuhong LiangSchool of Medicine, Southern University Of Science And Technology, Shenzhen, China.
Bihui HuangScientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is one of the most common and mortal malignancies, usually with a poor prognosis in its advanced or recurrent stages. Recently, immune checkpoint inhibitors (ICIs) immunotherapy has revolutionized the treatment of human cancers including lung adenocarcinoma (LUAD), and significantly improved patients' prognoses. However, the prognostic and predictive outcomes differ because of tumor heterogeneity. Here, we present an effective method, GDPLichi (Genes of DNA damage repair to predict LUAD immune checkpoint inhibitors response), as the signature to predict the LUAD patient's response to the ICIs. GDPLichi utilized only 7 maker genes from 8 DDR pathways to construct the predictive model and classified LUAD patients into two subgroups: low- and high-risk groups. The high-risk group was featured by worse prognosis and decreased B cells, CD8

Indexed as

DNA damage repair (DDR)GDPLichigene classifierimmune check inhibitor (ICI)lung adenocarcinoma

Identifiers

PMID34970479
PMCPMC8713481

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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.