ArticleCancer medicine2021
Tumor stemness and immune infiltration synergistically predict response of radiotherapy or immunotherapy and relapse in lung adenocarcinoma.
Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 15 citations in OpenAlex.
- Effectiveness of Artificial Intelligence Models in Predicting Lung Cancer Recurrence: A Gene Biomarker-Driven Review.Cancers · 2025Review
- The role of ANLN in malignant tumors: pathogenesis, treatment resistance and targeted strategies.Frontiers in cell and developmental biology · 2025Review
- Application of artificial intelligence-based stemness index in cancer.Frontiers in oncology · 2025Review
- Histological transformation in lung adenocarcinoma: Insights of mechanisms and therapeutic windows.Journal of translational internal medicine · 2024Article
- Construction of a pathomics model for predicting mRNAsi in lung adenocarcinoma and exploration of biological mechanism.Heliyon · 2024Article
- Cancer stem cells: advances in knowledge and implications for cancer therapy.Signal transduction and targeted therapy · 2024Review
- Article
- Old Dog, New Trick: A Tumor-Intrinsic Role for PD-1 in Chemoresistant Tumor Subclones.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- A novel stemness classification in acute myeloid leukemia by the stemness index and the identification of cancer stem cell-related biomarkers.Frontiers in immunology · 2023Article
- Glycolytic Genes Predict Immune Status and Prognosis Non-Small-Cell Lung Cancer Patients with Radiotherapy and Chemotherapy.BioMed research international · 2023Article
- YAP1 as a Novel Negative Biomarker of Immune Checkpoint Inhibitors for EGFR-Mutant Non-Small-Cell Lung Cancer.Canadian respiratory journal · 2023Article
- A Novel Risk Score Model of Lactate Metabolism for Predicting over Survival and Immune Signature in Lung Adenocarcinoma.Cancers · 2022Article
- Tumor stemness and immune infiltration synergistically predict response of radiotherapy or immunotherapy and relapse in lung adenocarcinoma.Cancer medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer stem cells (CSCs) have been shown to accelerate tumor recurrence, radiotherapy, and chemotherapy resistance. Immunotherapy is a powerful anticancer treatment that can significantly prolong the overall survival of patients with lung adenocarcinoma (LUAD). However, little is known about the function of genes related to tumor stemness and immune infiltration in LUAD. After integrating the tumor stemness index based on mRNA expression (mRNAsi), immune score, mRNA expression, and clinical information from the TCGA database, we screened 380 tumor stemness and immune (TSI)-related genes and constructed a five TSI-specific-gene (CPS1, CCR2, NT5E, ANLN, and ABCC2) signature (TSISig) using a machine learning method. Survival analysis indicated that TSISig could stably predict the prognosis of patients with LUAD. Comparison of mRNAsi and immune score between high- and low-TSISig groups suggested that TSISig characterized tumor stemness and immune infiltration. In addition, enrichment of immune subpopulations showed that the low-TSISig group held more immune subpopulations. GSEA revealed that TSISig had a strong association with the cell cycle and human immune response. Further analysis revealed that TSISig not only had a good predictive ability for prognosis but could also serve as an excellent predictor of tumor recurrence and response to radiotherapy and immunotherapy in LUAD patients. TSISig might regulate the development of LUAD by coordinating tumor stemness and immune infiltration. Finally, a connectivity map (CMap) analysis demonstrated that the HDAC inhibitor could target TSISig.
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.