ArticleJournal of thoracic disease2025
Identification of esophageal cancer tumor antigens and immune subtypes for guiding vaccine development.
Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- SH3BGRL2 as a vital tumor suppressor and prognostic factor in human esophageal squamous cell carcinoma.Journal of thoracic disease · 2025Article
- Therapeutic cancer vaccines in pancreatic cancer.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Esophageal cancer (ESCA) is a highly aggressive malignancy characterized by poor prognosis, primarily due to late diagnosis and limited treatment efficacy. Immunotherapies, such as vaccines, necessitate a more comprehensive understanding of the tumor immune microenvironment and tumor-specific antigens. The immune heterogeneity of ESCA, which is shaped by immune cell infiltration and antigen presentation, remains largely unexplored, particularly in terms of its interactions with autoimmune mechanisms. This study employs multi-omics analysis to profile the immunophenotype of ESCA, aiming to identify immune evasion mechanisms, tumor antigens, and autoimmune-related pathways. By elucidating these features, we seek to uncover potential targets for vaccine development and personalized immunotherapies, thereby improving therapeutic outcomes. Methods: To screen for potential antigen genes, we examined the overexpressed and mutated genes specific to ESCA. Additionally, we employed Kaplan-Meier survival and Cox analysis to evaluate the prognostic relevance of these potential tumor antigens. To achieve data aggregation and construct a consistency matrix, we used consistency clustering. Subsequently, a graph learning-based dimensionality reduction method was implemented to clarify the immune subtypes. Furthermore, weighted gene coexpression network analysis (WGCNA) was used to cluster potential antigen genes and identify hub genes. Results: Our analysis identified six overexpressed and mutated tumor antigens that were strongly associated with poor prognosis and antigen-presenting cell (APC) infiltration in ESCA. Analysis of The Cancer Genome Atlas (TCGA) data consistently identified three immune subtypes. These findings allowed for the construction of the immune landscape of TCGA samples based on the respective immune subtypes. The integration of immunogenomics analysis further allowed for the characterization of the immune microenvironment for each immune subtype. WGCNA successfully screened for three prognostic factors. Conclusions: In our analysis,
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.