ReviewCancers2020
Non-Small-Cell Lung Cancer Signaling Pathways, Metabolism, and PD-1/PD-L1 Antibodies.
Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 2 of them syntheses that pooled 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.
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
73 citing papers in PubMed, 2 syntheses or guidelines pooled it, 99 citations in OpenAlex.
- First-line immunotherapy efficacy in advanced squamous non-small cell lung cancer with PD-L1 expression ≥50%: a network meta-analysis of randomized controlled trials.Frontiers in oncology · 2024Pooled it
- Pooled it
- Ribonucleotide Reductase Inhibition Triggers Ferroptosis in Genetically Defined Subsets of Non-Small Cell Lung Cancer.Cancer research communications · 2026Article
- Tumor microenvironment and signaling pathways in melanoma brain metastasis.Annals of translational medicine · 2026Review
- The neuronal network of small cell lung cancer: a narrative review of the role of the nervous system in the pathogenesis and progression.Translational lung cancer research · 2026Review
- Review
- Metabolic Regulation of Immune Responses: Molecular Mechanisms, Diseases, and Therapeutic Targets.MedComm · 2026Review
- Exploration of network-based, machine learning, MD simulations, and MM/GBSA approaches revealed luteolin from Gynura procumbens as key inhibitor of MMP9 in NSCLC.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Integrated radiomics and immune infiltration analysis to decipher immunotherapy efficacy in lung adenocarcinoma.Quantitative imaging in medicine and surgery · 2025Article
- Expression patterns of MCM8 in lung adenocarcinoma and its correlation with key biological processes.European journal of medical research · 2025Article
- Icariin Inhibits Lung Adenocarcinoma Progression Through TP53-Mediated Ferroptosis.OncoTargets and therapy · 2025Article
- Significance of Ribonucleoside-diphosphate Reductase Subunit M2 in Lung Adenocarcinoma.Current gene therapy · 2025Article
- The multifaceted roles of mucins family in lung cancer: from prognostic biomarkers to promising targets.Frontiers in immunology · 2025Review
- Risk scoring model for lung adenocarcinoma based on PD-L1 related signature reveals prognostic predictability and correlation with tumor immune microenvironment genes was constructed.Frontiers in immunology · 2025Article
- Identification of the molecular subtype and prognostic characteristics of lung adenocarcinoma based on CD8Cancer biomarkers : section A of Disease markers · 2024Article
- Unraveling the immune landscape of lung adenocarcinoma: insights for tailoring therapeutic approaches.Discover oncology · 2024Article
- Anoikis-related subtype and prognosis analyses based on bioinformatics, and an expression verification of ANGPTL4 based on experiments of lung adenocarcinoma.Journal of thoracic disease · 2024Article
- Discovery of lung adenocarcinoma tumor antigens and ferroptosis subtypes for developing mRNA vaccines.Scientific reports · 2024Article
- SLC7A11 inhibits ferroptosis and downregulates PD-L1 levels in lung adenocarcinoma.Frontiers in immunology · 2024Article
- Prognostic gene HLA-DMA associated with cell cycle and immune infiltrates in LUAD.The clinical respiratory journal · 2023Article
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 7 institutions in 5 countries.
Funding
Abstract
Treatment of advanced (metastatic) non-small-cell lung cancer (NSCLC) is currently mainly based on immunotherapy with antibodies against PD-1 or PD-L1, alone, or in combination with chemotherapy. In locally advanced NSCLC and in early resected stages, immunotherapy is also employed. Tumor PD-L1 expression by immunohistochemistry is considered the standard practice. Response rate is low, with median progression free survival very short in the vast majority of studies reported. Herein, numerous biological facets of NSCLC are described involving driver genetic lesions, mutations ad fusions, PD-L1 glycosylation, ferroptosis and metabolic rewiring in NSCLC and lung adenocarcinoma (LUAD). Novel concepts, such as immune-transmitters and the effect of neurotransmitters in immune evasion and tumor growth, the nascent relevance of necroptosis and pyroptosis, possible new biomarkers, such as gasdermin D and gasdermin E, the conundrum of K-Ras mutations in LUADs, with the growing recognition of liver kinase B1 (LKB1) and metabolic pathways, including others, are also commented. The review serves to charter diverse treatment solutions, depending on the main altered signaling pathways, in order to have effectual immunotherapy. Tumor PDCD1 gene (encoding PD-1) has been recently described, in equilibrium with tumor PD-L1 (encoded by PDCD1LG1). Such description explains tumor hyper-progression, which has been reported in several studies, and poises the fundamental criterion that IHC PD-L1 expression as a biomarker should be revisited.
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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.