ArticleNPJ precision oncology2024
Prognostic patterns in invasion lymph nodes of lung adenocarcinoma reveal distinct tumor microenvironments.
Article in NPJ precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Prognostic impact of the lymph node yield on survival in patients with stage I lung adenocarcinoma receiving sublobar resection.Frontiers in molecular biosciences · 2026Article
- The evolving role of the immune microenvironment of tumor draining lymph nodes in the development of biomarkers of non-small cell lung cancer.Frontiers in oncology · 2026Review
- Development and validation of an interpretable machine learning model for prediction of occult lymph node metastasis in clinical stage T1 lung adenocarcinoma.Translational lung cancer research · 2025Article
- Customized transformer for lymph node metastasis prediction from lung adenocarcinoma histology in a multicentric study.NPJ precision oncology · 2025Article
- Integrative Single-Cell and Machine Learning Analysis Reveals Immune Microenvironment Remodelling in Lymph Node Metastasis of Lung Adenocarcinoma.Journal of cellular and molecular medicine · 2025Article
- Stage-dependent spatial distribution and prognostic value of CD8NPJ precision oncology · 2025Article
- From trash to treasure: tumor draining lymph nodes as a multi-omics goldmine in cancer therapy.Frontiers in oncology · 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
15 authors.
Funding
Abstract
Tumor-draining lymph nodes (TDLNs) are usually the first station of tumor metastasis in lung cancer. TDLNs+ have distinct pathomorphologic and tumor microenvironment (TME)-compositional patterns, which still need to be thoroughly investigated in lung adenocarcinoma (LUAD). Here, we enrolled 312 LUAD patients with TDLNs+ from our institution between 2015 and 2019. 3DHISTECH was used to scan all of the TDLNs+. Based on morphologic features, TDLNs+ patterns were classified as polarized-type or scattered-type, and TME-compositional patterns were classified as colloid-type, necrosis-type, specific-type, and common-type. Multivariate analysis revealed an increased risk of early recurrence associated with scattered-type (HR 2.37, 95% CI: 1.06-5.28), colloid-type (HR 1.95, 95% CI: 1.03-3.67), and necrosis-type (HR 2.21, 95% CI: 1.13-4.89). NanoString transcriptional analysis revealed an immunosuppression and vascular invasion hallmark in scattered and necrosis patterns and an immunoactivated hallmark in polarized and common patterns. According to imaging mass cytometry (IMC), the scattered and necrosis patterns revealed that germinal centers (GC) were compromised, GCB cell and T cell proliferation were deficient, tumor cells had the potential for proliferation, and the immune attack may be weaker. In this study, we present evidence that LUAD patients have distinct patterns and immune hallmarks of TDLNs+ related to their prognosis.
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.