ArticleNature communications2022
The landscape of receptor-mediated precision cancer combination therapy via a single-cell perspective.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Proteomic Profiling Identifies CLDN3 as a Tumor-Selective Therapeutic Target in Small Cell Lung Cancer.bioRxiv : the preprint server for biology · 2026Article
- Tumor-targeted bispecific antibodies effectively inhibit oncogenic pathways while minimizing toxicity.Science advances · 2026Article
- Multispecific nanobody degraders co-deplete membrane receptors and enable targeted delivery of diverse payloads.bioRxiv : the preprint server for biology · 2026Article
- Engineering Immunity: Current Progress and Future Directions of CAR-T Cell Therapy.International journal of molecular sciences · 2026Review
- Discovering anticancer drug target combinations via network-informed signaling-based approach.Communications medicine · 2025Article
- A first-in-class EGFR-directed KRAS G12V selective inhibitor.Cancer cell · 2025Article
- Biomimetic cancer cell membrane engineered lipid nanoparticles for enhanced chemotherapy of homologous malignant tumor.BMC cancer · 2025Article
- Advancing therapeutics in small-cell lung cancer.Nature cancer · 2025Review
- Single-cell-guided identification of logic-gated antigen combinations for designing effective and safe CAR therapy.bioRxiv : the preprint server for biology · 2025Article
- Finding Multiple Optimal Solutions to an Integer Linear Program by Random Perturbations of Its Objective Function.Algorithms · 2025Article
- Review
- Pan-Cancer Insights: A Study of Microbial Metabolite Receptors in Malignancy Dynamics.Cancers · 2024Article
- Egfl6 promotes ovarian cancer progression by enhancing the immunosuppressive functions of tumor-associated myeloid cells.The Journal of clinical investigation · 2024Article
- Anticancer Target Combinations: Network-Informed Signaling-Based Approach to Discovery.bioRxiv : the preprint server for biology · 2024Article
- Review
- Personalized tumor combination therapy optimization using the single-cell transcriptome.Genome medicine · 2023Article
- Article
- Protein Tyrosine Phosphatase Receptor Zeta 1 as a Potential Target in Cancer Therapy and Diagnosis.International journal of molecular sciences · 2023Review
- Transcriptomic Approaches in Studies on and Applications of Chimeric Antigen Receptor T Cells.Biomedicines · 2023Review
- Functional biomaterials for biomimetic 3D in vitro tumor microenvironment modeling.In vitro models · 2023Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Mining a large cohort of single-cell transcriptomics data, here we employ combinatorial optimization techniques to chart the landscape of optimal combination therapies in cancer. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient for killing at least 80% of tumor cells while sparing at least 90% of nontumor cells in the tumor microenvironment. However, as more stringent and selective killing is required, the number of targets needed rises rapidly. Emerging individual targets include PTPRZ1 for brain and head and neck cancers and EGFR in multiple tumor types. In sum, this study provides a computational estimate of the identity and number of targets needed in combination to target cancers selectively and precisely.
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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.