A single nucleotide mutation drastically increases the expression of tumor-homing NGR-TNFα in the E. coli M15-pQE30 system by improving gene transcription

PDGFRβ-Antagonistic Affibody-Mediated Tumor-Targeted Tumor Necrosis Factor-Alpha for Enhanced Radiotherapy in Lung Cancer

The morbidity and mortality of lung cancer are still the highest among all malignant tumors. Radiotherapy plays an important role in clinical treatment of lung cancer. However, the effect of radiotherapy is not ideal due to the radiation resistance of tumor tissues. Abnormalities in tumor vascular structure and function affect blood perfusion, and oxygen transport is impeded, making tumor microenvironment hypoxic. Tumor hypoxia is the major cause of radiotherapy resistance. By promoting tumor vessel normalization and enhancing vascular transport function, tumor hypoxia can be relieved to reduce radiotherapy resistance and increase tumor radiotherapy sensitivity. In our previous study, a pericytes-targeted tumor necrosis factor alpha (named Z-TNFα) was first constructed and produced by genetically fusing the platelet-derived growth factor receptor β (PDGFRβ)-antagonistic affibody (ZPDGFRβ) to the TNFα, and the Z-TNFα induced normalization of tumor vessels and improved the delivery of doxorubicin, enhancing tumor chemotherapy. In this study, the tumor vessel normalization effect of Z-TNFα in lung cancer was further clarified. Moreover, the tumor hypoxia improvement and radiosensitizing effect of Z-TNFα were emphatically explored in vivo. Inspiringly, Z-TNFα specifically accumulated in Lewis lung carcinoma (LLC) tumor graft and relieved tumor hypoxia as well as inhibited HIF-1α expression. As expected, Z-TNFα significantly increased the effect of radiotherapy in mice bearing LLC tumor graft. In conclusion, these results demonstrated that Z-TNFα is also a promising radiosensitizer for lung cancer radiotherapy.

RGD-p21Ras-scFv expressed prokaryotically on a pilot scale inhibits ras-driven colorectal cancer growth by blocking p21Ras-GTP

BACKGROUND

Ras gene mutation and/or overexpression are drivers in the progression of cancers, including colorectal cancer. Blocking the Ras signaling has become a significant strategy for cancer therapy. Previously, we constructed a recombinant scFv, RGD-p21Ras-scFv by linking RGD membrane-penetrating peptide gene with the anti-p21Ras scFv gene. Here, we expressed prokaryotically RGD-p21Ras-scFv on a pilot scale, then investigated the anti-tumor effect and the mechanism of blocking Ras signaling.

METHODS

The E. coli bacteria which could highly express RGD-p21Ras-scFv was screened and grown in 100 L fermentation tank to produce RGD-p21Ras-scFv on optimized induced expression conditions. The scFv was purified from E. coli bacteria using His Ni-NTA column. ELISA was adopted to test the immunoreactivity of RGD-p21Ras-scFv against p21Ras proteins, and the IC50 of RGD-p21Ras-scFv was analyzed by CCK-8. Immunofluorescence colocalization and pull-down assays were used to determine the localization and binding between RGD-p21Ras-scFv and p21Ras. The interaction forces between RGD-p21Ras-scFv and p21Ras after binding were analyzed by molecular docking, and the stability after binding was determined by molecular dynamics simulations. p21Ras-GTP interaction was detected by Ras pull-down. Changes in the MEK-ERK /PI3K-AKT signaling paths downstream of Ras were detected by WB assays. The anti-tumor activity of RGD-p21Ras-scFv was investigated by nude mouse xenograft models.

RESULTS

The technique of RGD-p21Ras-scFv expression on a pilot scale was established. The wet weight of the harvested bacteria was 31.064 g/L, and 31.6 mg RGD-p21Ras-scFv was obtained from 1 L of bacterial medium. The purity of the recombinant antibody was above 85%, we found that the prepared on a pilot scale RGD-p21Ras-scFv could penetrate the cell membrane of colon cancer cells and bind to p21Ras, then led to reduce of p21Ras-GTP (active p21Ras). The phosphorylation of downstream effectors MEK-ERK /PI3K-AKT was downregulated. In vivo antitumor activity assays showed that the RGD-p21Ras-scFv inhibited the proliferation of colorectal cancer cell lines.

CONCLUSION

RGD-p21Ras-scFv prokaryotic expressed on pilot-scale could inhibited Ras-driven colorectal cancer growth by partially blocking p21Ras-GTP and might be able to be a hidden therapeutic antibody for treating RAS-driven tumors.

NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides

Tumor homing peptides (THPs) play a crucial role in recognizing and specifically binding to cancer cells. Although experimental approaches can facilitate the precise identification of THPs, they are usually time-consuming, labor-intensive, and not cost-effective. However, computational approaches can identify THPs by utilizing sequence information alone, thus highlighting their great potential for large-scale identification of THPs. Herein, we propose NEPTUNE, a novel computational approach for the accurate and large-scale identification of THPs from sequence information. Specifically, we constructed variant baseline models from multiple feature encoding schemes coupled with six popular machine learning algorithms. Subsequently, we comprehensively assessed and investigated the effects of these baseline models on THP prediction. Finally, the probabilistic information generated by the optimal baseline models is fed into a support vector machine-based classifier to construct the final meta-predictor (NEPTUNE). Cross-validation and independent tests demonstrated that NEPTUNE achieved superior performance for THP prediction compared with its constituent baseline models and the existing methods. Moreover, we employed the powerful SHapley additive exPlanations method to improve the interpretation of NEPTUNE and elucidate the most important features for identifying THPs. Finally, we implemented an online web server using NEPTUNE, which is available at http://pmlabstack.pythonanywhere.com/NEPTUNE. NEPTUNE could be beneficial for the large-scale identification of unknown THP candidates for follow-up experimental validation.

SCMTHP: A New Approach for Identifying and Characterizing of Tumor-Homing Peptides Using Estimated Propensity Scores of Amino Acids

Tumor-homing peptides (THPs) are small peptides that can recognize and bind cancer cells specifically. To gain a better understanding of THPs’ functional mechanisms, the accurate identification and characterization of THPs is required. Although some computational methods for in silico THP identification have been proposed, a major drawback is their lack of model interpretability. In this study, we propose a new, simple and easily interpretable computational approach (called SCMTHP) for identifying and analyzing tumor-homing activities of peptides via the use of a scoring card method (SCM). To improve the predictability and interpretability of our predictor, we generated propensity scores of 20 amino acids as THPs. Finally, informative physicochemical properties were used for providing insights on characteristics giving rise to the bioactivity of THPs via the use of SCMTHP-derived propensity scores. Benchmarking experiments from independent test indicated that SCMTHP could achieve comparable performance to state-of-the-art method with accuracies of 0.827 and 0.798, respectively, when evaluated on two benchmark datasets consisting of Main and Small datasets. Furthermore, SCMTHP was found to outperform several well-known machine learning-based classifiers (e.g., decision tree, k-nearest neighbor, multi-layer perceptron, naive Bayes and partial least squares regression) as indicated by both 10-fold cross-validation and independent tests. Finally, the SCMTHP web server was established and made freely available online. SCMTHP is expected to be a useful tool for rapid and accurate identification of THPs and for providing better understanding on THP biophysical and biochemical properties.