ReviewNature reviews. Cancer2022
Rethinking cancer targeting strategies in the era of smart cell therapeutics.
Review in Nature reviews. Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed, 55 citations in OpenAlex.
- Microenvironmental regulation of solid tumour resistance to CAR T cell therapy.Nature reviews. Immunology · 2026Review
- CAR T cell therapy in type 1 diabetes: what we know and what remains to be explored.Biological procedures online · 2025Review
- Advancements in DNA-Driven Precision Modulation of Cell Surface Receptor for Programmable Cellular Functions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- EccDNA-Driven VPS41 Amplification Alleviates Genotoxic Stress via Lysosomal KAI1 Degradation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Programming tumor evolution with selection gene drives to proactively combat drug resistance.Nature biotechnology · 2025Article
- Emerging artificial intelligence-driven precision therapies in tumor drug resistance: recent advances, opportunities, and challenges.Molecular cancer · 2025Review
- Engineering synthetic suppressor T cells that execute locally targeted immunoprotective programs.Science (New York, N.Y.) · 2024Article
- Advances in CAR-T therapy for central nervous system tumors.Biomarker research · 2024Review
- Quantitative design of cell type-specific mRNA stability from microRNA expression data.bioRxiv : the preprint server for biology · 2024Article
- Therapeutic targets of armored chimeric antigen receptor T cells navigating the tumor microenvironment.Experimental hematology & oncology · 2024Review
- Cancer therapy resistance mediated by cancer-associated fibroblast-derived extracellular vesicles: biological mechanisms to clinical significance and implications.Molecular cancer · 2024Review
- Exploring the clinical and biological significance of the cell cycle-related gene CHMP4C in prostate cancer.BMC medical genomics · 2024Article
- DNA-functionalized artificial mechanoreceptor for de novo force-responsive signaling.Nature chemical biology · 2024Article
- Programmable synthetic receptors: the next-generation of cell and gene therapies.Signal transduction and targeted therapy · 2024Review
- Beyond BCMA: the next wave of CAR T cell therapy in multiple myeloma.Frontiers in oncology · 2024Review
- MultiplexedNucleic acid therapeutics · 2024Article
- Revolutionizing Cancer Treatment: Unveiling New Frontiers by Targeting the (Un)Usual Suspects.Cancers · 2023Article
- Cell surface sculpting using logic-gated protein actuators.bioRxiv : the preprint server for biology · 2023Article
- Design and mathematical analysis of activating transcriptional amplifiers that enable modular temporal control in synthetic juxtacrine circuits.Synthetic and systems biotechnology · 2023Article
- Arming CAR-T cells with cytokines and more: Innovations in the fourth-generation CAR-T development.Molecular therapy : the journal of the American Society of Gene Therapy · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
In the past several decades, the development of cancer therapeutics has largely focused on precision targeting of single cancer-associated molecules. Despite great advances, such targeted therapies still show incomplete precision and the eventual development of resistance due to target heterogeneity or mutation. However, the recent development of cell-based therapies such as chimeric antigen receptor (CAR) T cells presents a revolutionary opportunity to reframe strategies for targeting cancers. Immune cells equipped with synthetic circuits are essentially living computers that can be programmed to recognize tumours based on multiple signals, including both tumour cell-intrinsic and microenvironmental. Moreover, cells can be programmed to launch broad but highly localized therapeutic responses that can limit the potential for escape while still maintaining high precision. Although these emerging smart cell engineering capabilities have yet to be fully implemented in the clinic, we argue here that they will become much more powerful when combined with machine learning analysis of genomic data, which can guide the design of therapeutic recognition programs that are the most discriminatory and actionable. The merging of cancer analytics and synthetic biology could lead to nuanced paradigms of tumour recognition, more akin to facial recognition, that have the ability to more effectively address the complex challenges of treating cancer.
Indexed as
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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.