ReviewOncogene2020
The microcosmos of intratumor heterogeneity: the space-time of cancer evolution.
Review in Oncogene, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
What it found
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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.
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.
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Who cites it
58 citing papers in PubMed, 86 citations in OpenAlex.
- Estimation of cell lineages in tumors from spatial transcriptomics data.Nature communications · 2023Trial
- DWI-derived intratumoral, peritumoral, and habitat features for preoperative prediction of lymph node metastasis in early-stage cervical cancer using machine learning method.Abdominal radiology (New York) · 2026Article
- Identifying phenotype-genotype-function coupling in 3D organoid imaging using Shape, Appearance and Motion Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Ultrasound-targeted cavitation induced tumor vascular normalization and radiotherapy sensitization in breast cancer.Science China. Life sciences · 2026Article
- Role of chromatin remodeling and immunopharmacology in cancer therapy.Molecular medicine (Cambridge, Mass.) · 2026Review
- ViMST: vision transformer-based dual modality multi-task graph contrastive network for spatial transcriptomics microenvironments investigation.BMC biology · 2026Article
- Tumor heterogeneity: development, mechanisms, and therapeutic implications.Signal transduction and targeted therapy · 2026Review
- Cross-modality representation and multi-sample integration of spatially resolved omics data.Briefings in bioinformatics · 2026Article
- Selection for Function in Early Life: Implications for Early-Onset Pathologies.Evolutionary applications · 2026Article
- Preoperatively Predicting PIT1 Expression in Pituitary Adenomas Using Habitat, Intra-tumoral and Peri-tumoral Radiomics Based on MRI.Journal of imaging informatics in medicine · 2025Article
- CT-based intratumoral heterogeneity quantification fusing deep learning radiomics for predicting lymph node metastasis in early-stage lung adenocarcinoma: a multicenter study.Scientific reports · 2025Article
- SPACE: Spatially variable gene clustering adjusting for cell type effect for improved spatial domain detection.Nucleic acids research · 2025Article
- Article
- Spatial-temporal radiogenomics in predicting neoadjuvant chemotherapy efficacy for breast cancer: a comprehensive review.Journal of translational medicine · 2025Review
- Gene spatial integration: enhancing spatial transcriptomics analysis via deep learning and batch effect mitigation.Bioinformatics (Oxford, England) · 2025Article
- Chromosomal Instability and Clonal Heterogeneity in Breast Cancer: From Mechanisms to Clinical Applications.Cancers · 2025Review
- Heterogeneity and distribution characteristics of tertiary lymphoid structures predict prognostic outcome in esophageal squamous cell carcinoma.Frontiers in immunology · 2025Article
- RNA sequencing enables neoantigen discovery and vaccine validation in breast and lung cancer.Frontiers in immunology · 2025Article
- Radiomics reveals the biological basis for non-small cell lung cancer prognostic stratification by reflecting tumor immune microenvironment heterogeneity.Frontiers in immunology · 2025Article
- RBMS1-mediates the biogenesis of circNFIB promotes perineural invasion of pancreatic ductal adenocarcinoma via the L1CAM/MAPK pathway.Theranostics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
The Cancer Genome Atlas consortium brought us terabytes of information about genetic alterations in different types of human tumors. While many cancer-driver genes have been identified through these efforts, interrogating cancer genomes has also shed new light on tumor complexity. Mutations were found to vary tremendously in their allelic frequencies within the same tumor. Based on those variant allelic frequencies grouping, an estimate of genetically distinct "clones" of cancer cells can be determined for each tumor. It was estimated that 4-8 clones are present in every human tumor. Presence of distinct clones, cells that differ in their genotype and/or phenotype, is one of the roots for the major challenge of effectively curing cancer patients. Any given treatment applied to a heterogeneous mixture of cancer cells will yield distinct responses in different cells and may be ineffective in killing particular clones. Moreover, in highly heterogeneous tumors, stochastically, there is a higher chance of presence of traits, such as point mutations in key receptor tyrosine kinases, that drive drug resistance. Thus, intratumor heterogeneity is like an arsenal, providing a variety of weapons for self-defense against cancer-targeted therapy. However, in this arsenal the supplies are constantly changing, as cancer cells are accumulating new mutations. What is also changing is the battlefield-the tumor microenvironment including all noncancerous cells within the tumor and surrounding tissue, which also contribute to the diversification of cancer's forces. In order to design more effective therapies that would target this ever-changing landscape, we need to learn more about the two elusive variables that shape the tumor ecosystem: the space-how could we exploit the organization of tumor microenvironment? and the time-how could we predict the changes in heterogeneous tumors?
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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.