ReviewCancers2021
Intratumoral Cellular Heterogeneity: Implications for Drug Resistance in Patients with Non-Small Cell Lung Cancer.
Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Advancements in Immunotherapy for Lung Cancer: A Meta-Analysis of Clinical Trial Outcomes.The clinical respiratory journal · 2026Pooled it
- Should We Perform Repeated Re-biopsy for the Detection of T790M Mutation?Cancer research and treatment · 2023Pooled it
- Article
- Spatial immunoprofiling of retroperitoneal leiomyosarcomas reveals intratumoral heterogeneity in immune cell infiltration, checkpoint molecule expression, and tertiary lymphoid structures.Annals of medicine · 2025Article
- Exploring targeted therapies against RFPL3 for non-small cell lung cancer with lymph node metastasis.Discover oncology · 2025Article
- Liposomes, immune cells, and lung cancer subtypes: A bidirectional Mendelian randomization study.Medicine · 2025Article
- Intratumoral heterogeneity and drug resistance in cancer.Cancer cell international · 2025Review
- Survival prediction and molecular subtyping of squamous cell lung cancer based on network embedding.Scientific reports · 2024Article
- Review
- Targeting HER3 to overcome EGFR TKI resistance in NSCLC.Frontiers in immunology · 2023Review
- Single-cell RNA sequencing revealed subclonal heterogeneity and gene signatures of gemcitabine sensitivity in pancreatic cancer.Frontiers in pharmacology · 2023Article
- Enhanced recovery of postoperative nursing for single-port thoracoscopic surgery in lung cancer patients.Frontiers in oncology · 2023Review
- Article
- Functional Roles of Bromodomain Proteins in Cancer.Cancers · 2021Review
- Review
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tailored therapies based on the identification of molecular targets currently represent a well-established therapeutic scenario in the treatment of non-small cell lung cancer (NSCLC) patients. However, while aiming to improve patients' response to therapy, development of resistance is frequently observed in daily clinical practice. Intratumoral heterogeneity is a frequent event in NSCLC, responsible for several critical issues in patients' diagnosis and treatment. Advances in single-cell sequencing technologies have allowed in-depth profiling of tumors and attributed intratumoral heterogeneity to genetic, epigenetic, and protein modification driven diversities within cancer cell populations. This review highlights current research on the biological role of tumor heterogeneity and its impact on the development of acquired resistance in NSCLC patients.
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.