Mapping and reprogramming human tissue microenvironments with MintFlow Article Swipe
Amir Akbarnejad
,
Lloyd Steele
,
Daniyal J. Jafree
,
Sebastian Birk
,
Marta Rosa Sallese
,
Koen Rademaker
,
Adam R. Boxall
,
Benjamin Rumney
,
Catherine Tudor
,
Minal Patel
,
Martin Prete
,
Stanislaw Makarchuk
,
Tong Li
,
Jonas Maaskola
,
Tong Li
,
Kenny Roberts
,
April Foster
,
Kenny Roberts
,
Giuseppe Testa
,
Satveer K. Mahil
,
Giuseppe Testa
,
Satveer K. Mahil
,
Sattar Vakili
,
Menna R. Clatworthy
,
Thomas J. Mitchell
,
Omer Ali Bayraktar
,
Omer Ali Bayraktar
,
Thomas J. Mitchell
,
Muzlifah Haniffa
,
Mohammad Lotfollahi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.06.24.661094
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.06.24.661094
Tissue microenvironments reprogram local cellular states in disease, yet current computational spatial methods remain descriptive and do not simulate tissue perturbation. We present MintFlow, a generative AI algorithm that learns how the tissue microenvironment influences cell states and predicts how tissue perturbations can reprogram them. Applied to three human diseases, MintFlow uncovered distinct pathogenic spatial reprogramming in inflammatory and tumor microenvironments. In atopic dermatitis, MintFlow identified a novel, spatially-imprinted, type 2 ( IL13 + ITGAE + ) epidermal T resident memory cell population (type 2 T RM ), and decoded signaling pathways within the perivascular lymphoid niche. In melanoma, MintFlow identified fibrotic stroma resembling keloid scar tissue. In kidney cancer, MintFlow resolved immunosuppressed CD8 + T cell states within tertiary lymphoid structures. Furthermore, MintFlow enabled in silico perturbations of disease-relevant cell states and tissue environments. Regulatory T cell modulation in atopic dermatitis was predicted to suppress the pro-inflammatory tissue environment, supporting manipulation of these cells as a therapeutic target. In kidney cancer, in silico T cell replacement recapitulated immune checkpoint blockade, while spatially targeted macrophage depletion reverted immunosuppressed T cell states. The corresponding gene programs correlated with survival in large kidney cancer patient cohorts. Together, these findings position MintFlow as a tool for unbiased disease mechanism prediction and in silico perturbation, accelerating translational hypothesis generation and guiding therapeutic strategies.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.06.24.661094
- https://www.biorxiv.org/content/biorxiv/early/2025/06/26/2025.06.24.661094.full.pdf
- OA Status
- green
- References
- 69
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411673872
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411673872Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2025.06.24.661094Digital Object Identifier
- Title
-
Mapping and reprogramming human tissue microenvironments with MintFlowWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-26Full publication date if available
- Authors
-
Amir Akbarnejad, Lloyd Steele, Daniyal J. Jafree, Sebastian Birk, Marta Rosa Sallese, Koen Rademaker, Adam R. Boxall, Benjamin Rumney, Catherine Tudor, Minal Patel, Martin Prete, Stanislaw Makarchuk, Tong Li, Jonas Maaskola, Tong Li, Kenny Roberts, April Foster, Kenny Roberts, Giuseppe Testa, Satveer K. Mahil, Giuseppe Testa, Satveer K. Mahil, Sattar Vakili, Menna R. Clatworthy, Thomas J. Mitchell, Omer Ali Bayraktar, Omer Ali Bayraktar, Thomas J. Mitchell, Muzlifah Haniffa, Mohammad LotfollahiList of authors in order
- Landing page
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https://doi.org/10.1101/2025.06.24.661094Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2025/06/26/2025.06.24.661094.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2025/06/26/2025.06.24.661094.full.pdfDirect OA link when available
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Reprogramming, Generative grammar, Disease, Computational biology, Cell, Biology, Computer science, Cell biology, Neuroscience, Artificial intelligence, Medicine, Genetics, Internal medicineTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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69Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.spatial | 12, 55 |
| abstract_inverted_index.states. | 181 |
| abstract_inverted_index.target. | 159 |
| abstract_inverted_index.tissue. | 107 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.MintFlow | 51, 65, 100, 111, 124, 199 |
| abstract_inverted_index.cellular | 5 |
| abstract_inverted_index.cohorts. | 194 |
| abstract_inverted_index.disease, | 8 |
| abstract_inverted_index.distinct | 53 |
| abstract_inverted_index.fibrotic | 102 |
| abstract_inverted_index.findings | 197 |
| abstract_inverted_index.lymphoid | 96, 121 |
| abstract_inverted_index.pathways | 92 |
| abstract_inverted_index.position | 198 |
| abstract_inverted_index.predicts | 39 |
| abstract_inverted_index.programs | 185 |
| abstract_inverted_index.resident | 80 |
| abstract_inverted_index.resolved | 112 |
| abstract_inverted_index.reverted | 177 |
| abstract_inverted_index.simulate | 19 |
| abstract_inverted_index.suppress | 146 |
| abstract_inverted_index.survival | 188 |
| abstract_inverted_index.targeted | 174 |
| abstract_inverted_index.tertiary | 120 |
| abstract_inverted_index.unbiased | 204 |
| abstract_inverted_index.MintFlow, | 24 |
| abstract_inverted_index.Together, | 195 |
| abstract_inverted_index.algorithm | 28 |
| abstract_inverted_index.blockade, | 171 |
| abstract_inverted_index.depletion | 176 |
| abstract_inverted_index.diseases, | 50 |
| abstract_inverted_index.epidermal | 78 |
| abstract_inverted_index.mechanism | 206 |
| abstract_inverted_index.melanoma, | 99 |
| abstract_inverted_index.predicted | 144 |
| abstract_inverted_index.reprogram | 3, 44 |
| abstract_inverted_index.signaling | 91 |
| abstract_inverted_index.spatially | 173 |
| abstract_inverted_index.uncovered | 52 |
| abstract_inverted_index.Regulatory | 136 |
| abstract_inverted_index.checkpoint | 170 |
| abstract_inverted_index.correlated | 186 |
| abstract_inverted_index.dermatitis | 142 |
| abstract_inverted_index.generation | 215 |
| abstract_inverted_index.generative | 26 |
| abstract_inverted_index.hypothesis | 214 |
| abstract_inverted_index.identified | 66, 101 |
| abstract_inverted_index.influences | 35 |
| abstract_inverted_index.macrophage | 175 |
| abstract_inverted_index.modulation | 139 |
| abstract_inverted_index.pathogenic | 54 |
| abstract_inverted_index.population | 83 |
| abstract_inverted_index.prediction | 207 |
| abstract_inverted_index.resembling | 104 |
| abstract_inverted_index.supporting | 151 |
| abstract_inverted_index.dermatitis, | 64 |
| abstract_inverted_index.descriptive | 15 |
| abstract_inverted_index.replacement | 167 |
| abstract_inverted_index.strategies. | 219 |
| abstract_inverted_index.structures. | 122 |
| abstract_inverted_index.therapeutic | 158, 218 |
| abstract_inverted_index.Furthermore, | 123 |
| abstract_inverted_index.accelerating | 212 |
| abstract_inverted_index.environment, | 150 |
| abstract_inverted_index.inflammatory | 58 |
| abstract_inverted_index.manipulation | 152 |
| abstract_inverted_index.perivascular | 95 |
| abstract_inverted_index.computational | 11 |
| abstract_inverted_index.corresponding | 183 |
| abstract_inverted_index.environments. | 135 |
| abstract_inverted_index.perturbation, | 211 |
| abstract_inverted_index.perturbation. | 21 |
| abstract_inverted_index.perturbations | 42, 128 |
| abstract_inverted_index.recapitulated | 168 |
| abstract_inverted_index.reprogramming | 56 |
| abstract_inverted_index.translational | 213 |
| abstract_inverted_index.disease-relevant | 130 |
| abstract_inverted_index.immunosuppressed | 113, 178 |
| abstract_inverted_index.microenvironment | 34 |
| abstract_inverted_index.pro-inflammatory | 148 |
| abstract_inverted_index.microenvironments | 2 |
| abstract_inverted_index.microenvironments. | 61 |
| abstract_inverted_index.spatially-imprinted, | 69 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5077814625, https://openalex.org/A5066316755 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 30 |
| corresponding_institution_ids | https://openalex.org/I109736498, https://openalex.org/I21196054, https://openalex.org/I241749, https://openalex.org/I2802476451, https://openalex.org/I4210133722 |
| citation_normalized_percentile.value | 0.17122089 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |