Background
Lung cancer is the most deadliest cancer in the world in recent years, seriously threatening human health and life (1). At present, the clinical treatment methods for lung cancer include surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, but these treatment methods have great limitations (2). Surgery is only suitable for early and some intermediate stage lung cancer patients, and may cause complications after surgery. Chemotherapy and radiotherapy are usually used for advanced lung cancer patients, but due to drug tolerance, these two methods can not cure the tumor, and will cause damage to normal tissues. Targeted therapy is only suitable for some specific lung cancer patients, and has limited treatment effect, easy to produce drug resistance. Immunotherapy has been proven to significantly improve the survival rate of lung cancer patients, but also has many side effects, such as immune-related toxicity reactions (2).
According to the traditional concept, the lungs of healthy people are sterile, but recent research shows that human lungs have a complex microbiota. Introducing genetically engineered microorganisms that can specifically express anti-tumor factors into the lungs of tumor patients can achieve efficient delivery of anti-tumor drugs. Moreover, using bacteria as drug delivery carriers is a promising new treatment strategy. Especially the Salmonella delivery system, which has been verified for its specificity, safety and efficacy (3).
In order to overcome the current clinical dilemma of lung cancer treatment, establish a more efficient and low side effect lung cancer treatment method, and develop a new microbial-based tumor treatment system, we plan to develop a precise lung cancer treatment method based on AI-selected genetically engineered bacteria. For the purpose of facilitating genetic modification, we chose Escherichia coli as the chassis organism
Research Aims
In order to overcome the current dilemma in the clinical treatment of lung cancer, establish a more efficient lung cancer treatment with low side effects, and develop a new microbial-based tumor treatment system, we plan to develop an accurate treatment of lung cancer based on genetically engineered bacteria selected by machine learning.
Design
Machine Learning Classification
To do this, we construct a machine learning model to analyze the differences between bacteria collected from the lung microbiome of individuals and those same bacteria cultured in vitro. Additionally, we aim to investigate the disparities between bacteria collected from cancerous environments and the same bacteria when cultured in vitro. Our objective is to identify distinctive features, functions, and relevant genes of bacteria in both cancerous and normal lung tissues.
Logic Gate Circuit Construction
In order to accurately target the tumor and ensure that the drug is only released in the tumor microenvironment, we constructed a logic gate circuit that induces the expression of downstream anti-tumor protein (IRGD-CDD) under high lactic acid, low oxygen, and low pH conditions. Referring to the method of constructing biological gate circuits by Green et al., we constructed a three-input AND gate circuit (4). We used LldR (lactic acid-induced promoter), pPepT (hypoxia-induced promoter), and pCadC (low pH-induced promoter) to control the expression of three input RNAs, and introduced a Switch sequence upstream of the mRNA of CDD-iRGD (5)(6). Only when the three promoters are expressed simultaneously, producing three inputs, can the hairpin structure of the Switch sequence be opened, allowing the expression of the downstream CDD-Irgd.
Anti-tumor protein construction
IRGD-CDD protein is a fusion protein, in which CDD is the cell death domain of mitochondrial protein Bit1, which has stronger ability to kill cells than full-length Bit1 protein. iRGD is a tumor-specific peptide, which has the ability to specifically bind to tumor cells and has strong tumor penetration1. IRGD-CDD fusion protein can target tumor cells and internalize into tumor cells through neuropilin-1 activated pathway, triggering cell death (7).
Using type II secretion system to secrete anti-tumor proteins
To ensure that the exogenous IRGD-CDD can be secreted by E. coli, we inserted the Heat-Stable Enterotoxin II (ssSTII) sequence at the N-terminus of the IRGD-CDD protein. The signal peptide of STII can transport proteins from the cytoplasm to the periplasm of E. coli, thus it can be used as a carrier to express heterologous proteins in E. coli (8).
Resveratrol-induced lysis of engineered bacteria
To prevent side effects such as excessive bacterial proliferation in the lungs and gene leakage, we designed a bacterial suicide program. We introduced a resveratrol-inducible promoter and a downstream phage gene (phiX174E) that lyses bacteria into E. coli. Our idea is that when the treatment is over, the patient inhales volatile resveratrol, which induces the expression of the lysis gene, causing these drug-delivering engineered bacteria to lyse, preventing potential side effects (9).
References
[1] Thai, A.A. et al. (2021) ‘Lung cancer’, Lancet (London, England), 398(10299), pp. 535–554.
[2] Hirsch, F.R. et al. (2017) ‘Lung cancer: current therapies and new targeted treatments’, The Lancet, 389(10066), pp. 299–311.
[3] Raman, V. et al. (2021) Intracellular delivery of protein drugs with an autonomously lysing bacterial system reduces tumor growth and metastases. Nat Commun 12, 6116.
[4] Green, A. A. et al. (2017) Complex cellular logic computation using ribocomputing devices. Nature 548, 117–121.
[5] Xiao, D. et al. (2022) ‘A d,l-lactate biosensor based on allosteric transcription factor LldR and amplified luminescent proximity homogeneous assay’, Biosensors and Bioelectronics, 211, p. 114378.
[6] Lombardo, M.J. et al. (1997) ‘Regulation of the Salmonella typhimurium pepT gene by cyclic AMP receptor protein (CRP) and FNR acting at a hybrid CRP-FNR site’, Journal of Bacteriology, 179(6), pp. 1909–1917.
[7] Chen, R. et al. (2013) ‘Application of a Proapoptotic Peptide to Intratumorally Spreading Cancer Therapy’, Cancer Research, 73(4), pp. 1352–1361.
[8] Zhou, Y., Liu, P., Gan, Y. et al. (2016) Enhancing full-length antibody production by signal peptide engineering. Microb Cell Fact 15, 47 (2016).
[9] Engineering genetic devices for in vivo control of therapeutic T cell activity triggered by the dietary molecule resveratrol | PNAS (no date).