ArticleJournal of thoracic disease2022
Article in Journal of thoracic disease, 2022. 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, 9 citations in OpenAlex.
- Review
- MAGE-A4 induces non-small cell lung cancer and tumor-promoting plasma cell accumulation.Science advances · 2025Article
- FXR-regulated COX6A2 triggers mitochondrial apoptosis of pancreatic β-cell in type 2 diabetes.Cell death & disease · 2024Article
- Identification and validation of a novel robust glioblastoma prognosis model based on bioinformatics.Heliyon · 2024Article
- Uncovering therapeutic targets for macrophage-mediated T cell suppression and PD-L1 therapy sensitization.Cell reports. Medicine · 2024Article
- HLA Class I Expression Is Associated with DNA Damage and Immune Cell Infiltration into Dysplastic and Neoplastic Lesions in Ulcerative Colitis.International journal of molecular sciences · 2023Article
- The roles of STMN3 in various cancers.Science progressReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: At present, non-small cell lung cancer (NSCLC) remains a great threat to the health of people worldwide. Immune checkpoint inhibitors (ICIs) have shown positive results in the treatment of advanced NSCLC. However, the treatment response of ICIs is not stable and unpredictable. We used a bioinformatics analysis to determine a novel signature to diagnose the hot and cold tumor in NSCLC which may guide the programmed cell death protein 1/programmed cell death 1 ligand 1 ( Methods: The RNA-seq dataset and clinical data of 485 lung adenocarcinoma (LUAD) and 473 lung squamous cell carcinoma (LUSC) samples from The Cancer Genome Atlas (TCGA) database. Tumor infiltrating immune cells was calculated by CIBERSORT algorithm and ConsensusClusterPlus was used to classify the hot and cold tumor. Least absolute shrinkage and selection operator (LASSO) regression, Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) were performed to determine the diagnostic area under curve (AUC) of novel signature of ICIs treatment. Overall survival (OS) analysis was based on the Kaplan-Meier statistical method. Results: In this study, we found that the expression of Conclusions: This study aimed to identify the classification of hot and cold tumors, and develop a novel signature to predict the ICI treatments response for
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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.