Evidence map›Paper›PMID 33072070›Full record

ArticleFrontiers in immunology2020

Clinical Implications of Aberrant PD-1 and CTLA4 Expression for Cancer Immunity and Prognosis: A Pan-Cancer Study.

Jian-Nan Liu, Xiang-Shuo Kong, Tao Huang, Rui Wang, Wang Li, Qi-Feng Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 2 pooled it
5.3field-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

69 citing papers in PubMed, 2 syntheses or guidelines pooled it, 93 citations in OpenAlex.

  1. Pooled it
  2. CTLA-4 Expression and Its Clinical Significance in Breast Cancer.Archivum immunologiae et therapiae experimentalis · 2021
    Pooled it
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. CD8Current oncology (Toronto, Ont.) · 2025
    Article
  9. Article
  10. Article
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  14. ERH Impacts Patient Prognosis and Tumor Immune Microenvironment: A Pan-Cancer Analysis.Combinatorial chemistry & high throughput screening · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

9 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

6 authors at 4 institutions in 1 country.

Jian-Nan LiuDepartment of Oncology, Yantai Yuhuangding Hospital, Yantai, China.
Xiang-Shuo KongDepartment of Oncology, Yantai Yuhuangding Hospital, Yantai, China.
Tao HuangDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Rui WangDepartment of Respiratory Oncology, Fushan District People's Hospital, Yantai, China.
Wang LiDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Qi-Feng ChenDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Sun Yat-sen University · CNYuhuangding Hospital · CNState Key Laboratory of Oncology in South ChinaYantaishan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combination therapy with inhibitors of cytotoxic T lymphocyte-associated protein (CTLA)4 and programmed death (PD)-1 has demonstrated efficacy in cancer patients. However, there is little information on CTLA4 and PD-1 expression levels and their clinical significance across diverse cancers. In this study, we addressed this question by analyzing PD-1 and CTLA4 levels in 33 different types of cancer along with their prognostic significance using The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia datasets. Liver hepatocellular carcinoma (LIHC) patients receiving cytokine-induced killer cell (CIK) immunotherapy at Sun Yat-sen University cancer center were enrolled for survival analysis. The correlation between PD-1/CTLA4 expression and cancer immunity was also analyzed. The results showed that PD-1 and CTLA4 transcript levels varied across cancer cell lines, with aberrant expression detected in certain cancer types; Kaplan-Meier analysis with the Cox proportional hazards model showed that this was closely related to overall survival in breast invasive carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, acute myeloid leukemialymphoma, uterine corpus endometrial carcinoma, and uveal melanoma in TCGA. High serum PD-1 and CTLA4 levels predicted better survival in LIHC patients receiving CIK therapy. PD-1 and CTLA4 levels were found to be significantly correlated with the degree of tumor cell infiltration using Tumor Immune Estimation Resource, Estimating Relative Subsets of RNA Transcripts, and Estimation of Stromal and immune Cells in Malignant Tumor Tissues Using Expression Data as well as with tumor-infiltrating lymphocyte marker expression; they were also related to tumor mutation burden, microsatellite instability, mismatch repair, and the expression of DNA methyltransferases in some cancer types. Gene set enrichment analysis of 33 cancer types provided further evidence for associations between PD-1/CTLA4 levels and cancer development and immunocyte infiltration. Thus, PD-1 and CTLA4 play important roles in tumorigenesis and tumor immunity and can serve as prognostic biomarkers in different cancer types.

Indexed as

Biomarkers, TumorGene ExpressionAdultAgedCTLA-4 AntigenDatabases, FactualDisease SusceptibilityFemaleGene Expression ProfilingHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasmsPrognosisProgrammed Cell Death 1 ReceptorBiomarkers, TumorCTLA-4 AntigenCTLA4 protein, humanProgrammed Cell Death 1 Receptorcancer immunityCTLA4pan-cancerPD-1prognostic biomarker

Identifiers

PMID33072070
PMCPMC7539667
OpenAlexW3085007071

What OpenQuestion holds

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LicenceCC BY
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.