Evidence map›Paper›PMID 36911742›Full record

ArticleFrontiers in immunology2023

Identification of tumor mutation burden-associated molecular and clinical features in cancer by analyzing multi-omics data.

Mengyuan Li, Xuejiao Gao, Xiaosheng Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
8.5field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Comprehensive Genomic Profiles of Melanoma in Veterans Compared to Reference Databases.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2025
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. AnInternational journal of molecular sciences · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

3 authors at 2 institutions in 1 country.

Mengyuan LiSchool of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China.
Xuejiao GaoSchool of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China.
Xiaosheng WangSchool of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
Nanjing University of Chinese Medicine · CNChina Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tumor mutation burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in cancer. Systematic identification of molecular features correlated with TMB is significant, although such investigation remains insufficient. Methods: We analyzed associations of somatic mutations, pathways, protein expression, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), competing endogenous RNA (ceRNA) antitumor immune signatures, and clinical features with TMB in various cancers using multi-omics datasets from The Cancer Genome Atlas (TCGA) program and datasets for cancer cohorts receiving the immune checkpoint blockade therapy. Results: Among the 32 TCGA cancer types, melanoma harbored the highest percentage of high-TMB (≥ 10/Mb) cancers (49.4%), followed by lung adenocarcinoma (36.9%) and lung squamous cell carcinoma (28.1%). Three hundred seventy-six genes had significant correlations of their mutations with increased TMB in various cancers, including 11 genes ( Conclusions: The molecular and clinical features significantly associated with TMB could be valuable predictors for TMB and immunotherapy response and therefore have potential clinical values for cancer management.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsBiomarkers, TumorFemaleHumansMultiomicsMutationPhosphatidylinositol 3-KinasesProtein-Tyrosine KinasesProto-Oncogene ProteinsBiomarkers, TumorPhosphatidylinositol 3-KinasesProtein-Tyrosine KinasesProto-Oncogene Proteinsantitumor immunitycancer immunotherapyceRNAmulti-omicsTMB prognostic scoretumor mutation burden

Identifiers

PMID36911742
PMCPMC9998480
OpenAlexW4321789115

What OpenQuestion holds

Textmetadata
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.