Back

Tumor-tropic E. coli engineered as living T and NK cell engagers

Yang, S.; Bader, A. C.; Sendker, S.; Hu, A.; Chen, D. C.; Nath, H.; Chen, A.; Bobilev, E.; Sheffer, M.; Hui, V. W.; Kochs, T. E.; Maia, A.; Tang, J.; Liu, F.; Deng, X.; Nguyen, M.; Stanojevic, M.; Tarannum, M.; Albert, C. L.; Ali, A. K.; Shapiro, R.; Wei, Y.; Zhang, K.; Wang, Z.; Chung, Y. R.; Parry, E.; Campisi, M.; Barbie, D.; Lane, A. A.; Li, H.; Ligon, K. L.; Huang, K.; Wucherpfennig, K. W.; Chugh, S.; Ullrich, E.; Einsele, H.; Chen, J.; Koreth, J.; Silveira, V. S.; Soiffer, R.; Little, J. S.; Wu, C. J.; Ritz, J.; Li, J.; Aguirre, A. J.; Romee, R.

2026-08-20 bioengineering
10.64898/2026.08.18.745642 bioRxiv
Show abstract

Despite advances in immunotherapy, most solid tumors remain resistant to treatment. Immune cell engagers redirect cytotoxic lymphocytes against cancer, but limited tumor access, immunosuppressive microenvironments and systemic immune activation limit efficacy. Here we develop live immune modulating engagers (LIME), a modular platform where non-pathogenic, tumor-tropic Escherichia coli display tandem single-chain variable fragments targeting a tumor-associated antigen and an activating receptor on T or natural killer cells. LIME bridged effector and tumor cells, induced transcriptional programs of T cell activation, metabolism and proliferation, and enhanced cytotoxicity across cancer cell lines and patient-derived organoids. In mouse models, LIME safely accumulated in tumors, outperformed tarlatamab in small cell lung cancer, and induced durable immunity in lymphoma. RAS inhibition and PD-L1 blockade enhanced LIME activity in pancreatic cancer and induced humoral responses. Multi-lineage immune modulation remained tumor-confined, without organ toxicity. These findings establish LIME as a versatile living therapeutic platform for programmable, tumor-restricted immune orchestration.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 14%
12.7%
Similar papers in this journal
2
Nature Biomedical Engineering
○ 47 papers in training set
Top 0.1%
9.5%
Similar papers in this journal
3
Nature Biotechnology
○ 172 papers in training set
Top 0.5%
6.6%
Similar papers in this journal
4
Advanced Science
○ 286 papers in training set
Top 0.8%
6.6%
Similar papers in this journal
5
Nature Nanotechnology
○ 32 papers in training set
Top 0.1%
4.8%
Similar papers in this journal
6
Science Advances
● 1243 papers in training set
Top 11%
3.2%
7
Cell
○ 431 papers in training set
Top 3%
3.2%
8
Nature Chemical Biology
○ 119 papers in training set
Top 0.9%
2.7%
9
Advanced Materials
○ 56 papers in training set
Top 0.5%
2.4%
50% of probability mass above
10
ACS Nano
● 113 papers in training set
Top 0.9%
2.4%
11
Nature Chemistry
○ 42 papers in training set
Top 0.4%
2.4%
12
Science Translational Medicine
● 127 papers in training set
Top 1%
2.1%
13
Angewandte Chemie International Edition
○ 93 papers in training set
Top 0.8%
2.1%
14
Nature Methods
○ 385 papers in training set
Top 4%
2.1%
15
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 24%
2.1%
16
Science
● 477 papers in training set
Top 4%
2.1%
17
Neuron
○ 337 papers in training set
Top 3%
1.9%
18
Signal Transduction and Targeted Therapy
○ 30 papers in training set
Top 0.3%
1.7%
19
Molecular Therapy
○ 81 papers in training set
Top 1.0%
1.7%
20
ACS Chemical Biology
● 167 papers in training set
Top 2%
1.5%
21
Nature Metabolism
○ 69 papers in training set
Top 1%
1.5%
22
ACS Central Science
● 71 papers in training set
Top 0.9%
1.4%
23
Nature Medicine
○ 125 papers in training set
Top 3%
1.1%
24
Journal of the American Chemical Society
● 217 papers in training set
Top 2%
1.1%
25
Cell Chemical Biology
○ 94 papers in training set
Top 1%
1.0%
26
Nature
○ 645 papers in training set
Top 9%
1.0%
27
Biomaterials
○ 84 papers in training set
Top 1%
1.0%
28
Nature Cell Biology
○ 118 papers in training set
Top 3%
1.0%
29
Nature Materials
○ 28 papers in training set
Top 0.5%
0.9%
30
Cell Reports
○ 1498 papers in training set
Top 27%
0.8%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.