ReviewACS omega2023
Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis.
Review in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 26 citations in OpenAlex.
- Article
- Advances in Nuclear Medicine Diagnostics: The Promise of Radiolabeled Dendrimers.Molecules (Basel, Switzerland) · 2026Review
- Bacterial-based cancer therapy: mechanisms and therapeutic advances.Molecular biomedicine · 2026Review
- A stromal-derived five-gene signature predicts gastric cancer recurrence through integrated bioinformatics and single-cell analysis.Translational cancer research · 2026Article
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- Pseudotime-Based derivation of a PET-Based metabolic progression index for prognostic stratification in Extensive-Stage SCLC.Annals of nuclear medicine · 2026Article
- Prediction of mRECIST tumor response at firstfollow-up after DEB-TACE using a combined radiomics-clinical model and explainability methods.Clinical and experimental medicine · 2026Article
- Article
- Modeling VEGF and GLUT1 Expression as Coadapted Foraging Strategies in Cancer.bioRxiv : the preprint server for biology · 2026Article
- Integrated spatial metabolomics and transcriptomics reveal the molecular landscape of papillary thyroid cancer and its lymph node metastasis.Journal of translational medicine · 2025Article
- Advances in biomarkers of resistance to KRAS mutation-targeted inhibitors.Discover oncology · 2025Review
- Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer.Virchows Archiv : an international journal of pathology · 2025Article
- Pathway-guided architectures for interpretable AI in biological research.Computational and structural biotechnology journal · 2025Review
- Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine.Military Medical Research · 2024Review
- Advances in high throughput cell culture technologies for therapeutic screening and biological discovery applications.Bioengineering & translational medicine · 2024Review
- Article
- Radiomics-based machine learning models for differentiating pathological subtypes in cervical cancer: a multicenter study.Frontiers in oncology · 2024Article
- Phenotypic maps for precision medicine: a promising systems biology tool for assessing therapy response and resistance at a personalized level.Frontiers in network physiology · 2023Article
- Challenges of Deep Learning in Cancers.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics, and spatial transcriptomics allow recording of patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multiscale dynamics of its evolution. Here, we review the latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed burgeoning growth in the recent past in terms of mapping heterogeneity within tumor cell types as well as the stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor and a more systematic investigation of the implications of heterogeneity for patient outcomes.
Identifiers
What Socratic 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 Socratic graph.