Evidence map›Paper›PMID 38463768›Full record

ArticleHeliyon2024

A pan-cancer multi-omics analysis of lactylation genes associated with tumor microenvironment and cancer development.

Zhixuan Wu, Haodong Wu, Yinwei Dai, Ziqiong Wang, Hui Han, Yanyan Shen, Rongrong Zhang, Xiaowu Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Review
  20. Lactylation and antitumor immunity.Frontiers in immunology · 2025
    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

8 authors.

Zhixuan WuDepartment of Burns and Skin Repair Surgery, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Haodong WuDepartment of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Yinwei DaiDepartment of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Ziqiong WangDepartment of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Hui HanDepartment of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Yanyan ShenDepartment of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Rongrong ZhangDepartment of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.
Xiaowu WangDepartment of Burns and Skin Repair Surgery, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lactylation is a significant post-translational modification bridging the gap between cancer epigenetics and metabolic reprogramming. However, the association between lactylation and prognosis, tumor microenvironment (TME), and response to drug therapy in various cancers remains unclear. Methods: First, the expression, prognostic value, and genetic and epigenetic alterations of lactylation genes were systematically explored in a pan-cancer manner. Lactylation scores were derived for each tumor using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The correlation of lactylation scores with clinical features, prognosis, and TME was assessed by integrating multiple computational methods. In addition, GSE135222 data was used to assess the efficacy of lactylation scores in predicting immunotherapy outcomes. The expression of lactylation genes in breast cancers and gliomas were verified by RNA-sequencing. Results: Lactylation genes were significantly upregulated in most cancer types. CREBBP and EP300 exhibited high mutation rates in pan-cancer analysis. The prognostic impact of the lactylation score varied by tumor type, and lactylation score was a protective factor for KIRC, ACC, READ, LGG, and UVM, and a risk factor for CHOL, DLBC, LAML, and OV. In addition, a high lactylation score was associated with cold TME. The infiltration levels of CD8 Conclusion: Lactylation genes are involved in malignancy formation. Lactylation score serves as a promising biomarker for predicting patient prognosis and immunotherapy efficacy.

Indexed as

ImmunotherapyLactylationMulti-omicsPan-cancerTumor microenvironment

Identifiers

PMID38463768
PMCPMC10923869

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.