Back

Organoid modeling of tumor-associated macrophages reveals phagocytosis checkpoint blockade-induced conversion to an immunosuppressive SPP1+ phenotype

Nakano, M.; Heo, L.; Yang, Y.-P.; Munoz, L. P.; Liu, Y.; Zhao, L.; Park, J.; Tsekitsidou, E.; Francois, A.; Liu, J.; Trotman-Grant, A. C.; Henao Echeverri, M. F.; Rada, C. C.; Tran, E.; Khokhar, A.; Yuki, K.; Bhattacharya, A.; Horn, H. T.; Polak, R.; Yenwongfai, L. N.; Li, Y.; Peach, M.; Nasajpour, E.; Pavlovitch-Bedzyk, A. J.; Chang, A. L.; Lim, M.; Petritsch, C. K.; Hayden Gephart, M.; Leppert, J. T.; Nair, R. V.; Davis, M. M.; Bassik, M. C.; Zhang, M.; Odegard, J.; Bates, J. G.; Leung, L. L.; Majeti, R.; Kuo, C. J.

2026-05-09 cancer biology
10.64898/2026.05.06.722767 bioRxiv
Show abstract

Tumor-associated macrophages (TAM) exert essential functions during the immune response to cancer. However, investigations of TAM within a native human tumor microenvironment (TME) have been impeded by a lack of appropriate model systems. Here, patient-derived organoids (PDO) from air-liquid interface (ALI)-grown tumor fragments, containing a human TME that encompassed stroma and immune subsets, robustly preserved TAM that were maintained by endogenous CSF-1 and appropriately responded to polarization signals. Antibody blockade of the CD47 regulatory checkpoint in organoids stimulated phagocytosis and remodeled TAM cytokine secretion profiles that were confirmed in anti-CD47 phase I trial patients. Amongst PDO histologies screened, anti-CD47 tumor killing was notable in clear cell renal cell carcinoma (ccRCC) which was associated with increased TAM infiltration. PDO contained diverse previously described TAM subsets; however, anti-CD47 reprogrammed organoid TAM toward an immunosuppressive SPP1+ phenotype, highlighting a negative feedback mechanism. Our findings uncover a resistance circuit engaged by macrophage checkpoint blockade and position ALI PDO as a robust translational platform for dissecting human macrophage biology and informing precision immunotherapy.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Nature Communications
4913 papers in training set
Top 15%
12.0%
2
Cancer Cell
38 papers in training set
Top 0.1%
9.8%
3
Cell Stem Cell
57 papers in training set
Top 0.1%
9.8%
4
Nature Cancer
35 papers in training set
Top 0.1%
6.6%
5
Cell Reports
1338 papers in training set
Top 8%
6.1%
6
Cancer Discovery
61 papers in training set
Top 0.4%
4.7%
7
Cell Reports Medicine
140 papers in training set
Top 1%
3.9%
50% of probability mass above
8
Developmental Cell
168 papers in training set
Top 5%
3.6%
9
Cancer Research
116 papers in training set
Top 1%
2.5%
10
Nature Cell Biology
99 papers in training set
Top 2%
2.5%
11
Advanced Science
249 papers in training set
Top 8%
2.5%
12
Journal of Clinical Investigation
164 papers in training set
Top 2%
2.0%
13
Science Advances
1098 papers in training set
Top 15%
1.8%
14
Cell
370 papers in training set
Top 12%
1.6%
15
EMBO Molecular Medicine
85 papers in training set
Top 2%
1.6%
16
Nature
575 papers in training set
Top 12%
1.4%
17
Cell Genomics
162 papers in training set
Top 5%
1.2%
18
Cell Systems
167 papers in training set
Top 10%
1.2%
19
Immunity
58 papers in training set
Top 4%
0.9%
20
Science Translational Medicine
111 papers in training set
Top 5%
0.9%
21
JCI Insight
241 papers in training set
Top 6%
0.9%
22
The EMBO Journal
267 papers in training set
Top 4%
0.9%
23
Journal of Experimental Medicine
106 papers in training set
Top 4%
0.8%
24
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 46%
0.7%
25
Genome Medicine
154 papers in training set
Top 9%
0.7%
26
Clinical Cancer Research
58 papers in training set
Top 2%
0.7%
27
eLife
5422 papers in training set
Top 62%
0.6%