ReviewCancers2022
Deciphering Tumour Heterogeneity: From Tissue to Liquid Biopsy.
Review in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 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
72 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Preclinical Anticipation of On- and Off-Target Resistance Mechanisms to Anti-Cancer Drugs: A Systematic Review.International journal of molecular sciences · 2024Pooled it
- Clinical utility and diagnostic value of tumor-educated platelets in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2023Pooled it
- Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.European radiology · 2026Article
- Circulating tumour cells for guiding antibody‒drug conjugate therapy: Role of artificial intelligence.Clinical and translational medicine · 2026Review
- Lung tumour secretome and extracellular vesicles: mechanisms, biomarkers, and therapeutic opportunities.Cancer metastasis reviews · 2026Review
- Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.Cancer medicine · 2026Review
- ITHindex: An integrated web-based platform for intratumor heterogeneity evaluation.PLOS digital health · 2026Article
- Bioorthogonal Fluorogenic Reporters for Noninvasive Imaging and Urinalysis of Immunotherapeutic Response in Renal Cell Carcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- Electrochemical liquid biopsy across cancer care pathway.The journal of liquid biopsy · 2026Review
- A Laminar Microfluidic Platform for Probing the Effects of Spatially Heterogeneous Drug Distributions.Micromachines · 2026Article
- Radiogenomics in Lymphoma and Multiple Myeloma: A Systematic Review of Current Evidence and Future Directions.Journal of clinical medicine · 2026Review
- The role of liquid biopsy in the molecular characterization of HPV-related cancers.Folia microbiologica · 2026Review
- Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.Histochemistry and cell biology · 2026Review
- Artificial Intelligence in Oncology: A Comprehensive Cross-Cancer Translational Readiness Analysis Across 18 Malignancies.Cancers · 2026Review
- Harnessing Cancer Stem Cells and 3D Organoids in Unravelling Spatial and Cellular Heterogeneity in Cancer.International journal of molecular sciences · 2026Review
- Tumor-immune trajectory context connects static tissue architecture to clinical outcomes.bioRxiv : the preprint server for biology · 2026Article
- Artificial intelligence-powered liquid biopsy in cancer: a paradigm shift in cancer detection and personalized care.Cancer cell international · 2026Review
- Intratumoral heterogeneity in microsatellite instability status at single-cell resolution.iScience · 2026Article
- Liquid biopsy in Oncology: Results of a Delphi consensus study endorsed by the AIOM-SIAPEC/IAP-SIBioC-SIF Italian scientific societies.The journal of liquid biopsy · 2026Article
12 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human solid malignancies harbour a heterogeneous set of cells with distinct genotypes and phenotypes. This heterogeneity is installed at multiple levels. A biological diversity is commonly observed between tumours from different patients (inter-tumour heterogeneity) and cannot be fully captured by the current consensus molecular classifications for specific cancers. To extend the complexity in cancer, there are substantial differences from cell to cell within an individual tumour (intra-tumour heterogeneity, ITH) and the features of cancer cells evolve in space and time. Currently, treatment-decision making usually relies on the molecular characteristics of a limited tumour tissue sample at the time of diagnosis or disease progression but does not take into account the complexity of the bulk tumours and their constant evolution over time. In this review, we explore the extent of tumour heterogeneity with an emphasis on ITH and report the mechanisms that promote and sustain this diversity in cancers. We summarise the clinical strikes of ITH in the management of patients with cancer. Finally, we discuss the current material and technological approaches that are relevant to adequately appreciate ITH.
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.