ArticleCancer medicine2019
Risk stratification for lung adenocarcinoma on EGFR and TP53 mutation status, chemotherapy, and PD-L1 immunotherapy.
Article in Cancer medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Single-cell profiling reveals FAM117A as a key regulator linking macrophage-epithelial crosstalk with the progression of lung adenocarcinoma.Experimental hematology & oncology · 2026Article
- Exploring the Synergistic Mechanism of AP2A2 Transcription Factor Inhibition via Molecular Modeling and Simulations as a Novel Computational Approach for Combating Breast Cancer: In Silico Interpretations.Molecular biotechnology · 2024Article
- Construction and validation of an efferocytosis-related prognostic signature in lung adenocarcinoma.Journal of cancer research and clinical oncology · 2023Article
- Clinical predictors of treatment efficacy and a prognostic nomogram in patients with lung adenocarcinoma receiving immune checkpoint inhibitors: a retrospective study.Journal of thoracic disease · 2022Article
- Characterization of the Immune Cell Infiltration Landscape Uncovers Prognostic and Immunogenic Characteristics in Lung Adenocarcinoma.Frontiers in genetics · 2022Article
- Cutaneous adverse reactions in a lung cancer patient treated with pembrolizumab: A case report.Experimental and therapeutic medicine · 2022Article
- Proteome profiling of formalin-fixed, paraffin-embedded lung adenocarcinoma tissues using a tandem mass tag-based quantitative proteomics approach.Oncology letters · 2021Article
- Article
- Risk stratification for lung adenocarcinoma on EGFR and TP53 mutation status, chemotherapy, and PD-L1 immunotherapy.Cancer medicine · 2019Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The overall survival rates for lung cancer remain unsatisfactorily low, even for patients with biomarkers for which target therapies or immunotherapies are recommended. Better identification of at-risk patients is needed to achieve more effective personalized treatment. Here, we derived a risk-stratifying gene signature consisting of five genes that had the greatest differential expression by stage from lung adenocarcinoma (LUAD) transcriptomes. The new gene signature enabled survival prognosis for multiple LUAD datasets from different platforms of transcriptomics and risk stratification for patients with and without a mutation in TP53 or EGFR, with high and low levels of PD-L1, and with and without adjuvant chemotherapy treatment. Using these evaluations, it was also shown to be more robust compared to several other gene signatures. Functional analysis of the five genes and their protein-protein interaction partners indicated that they are functionally enriched in cell cycle, endocytosis, and EGFR regulation, which are biological processes associated with lung cancer and drug resistance. Extensive discussions on related experimental studies suggest that the five genes are novel and sensible targets for developing new drugs and/or tackling drug resistance problems for LUAD.
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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.