EPI-X4, a CXCR4 antagonist inhibits tumor growth in pancreatic cancer and lymphoma models

Endogenous peptide inhibitor for CXCR4 (EPI-X4) is a CXCR4 antagonist with potential for cancer therapy. It is a processed fragment of serum albumin from the hemofiltrate of dialysis patients. This study reports the efficacy of fifteen EPI-X4 derivatives in pancreatic cancer and lymphoma models. In vitro, the peptides were investigated for antiproliferation (cytotoxicity) by MTT assay. The mRNA expression for CXCR4 and CXCL12 was determined by RT-PCR, chip array and RNA sequencing. Chip array analysis yielded 634 genes associated with CXCR4/CXCL12 signaling. About 21% of these genes correlated with metastasis in the context of cell motility, proliferation, and survival. Expression levels of these genes were altered in pancreatic cancer (36%), lymphoma models (53%) and in patients' data (58%). EPI-X4 derivatives failed to inhibit cell proliferation due to low expression of CXCR4 in vitro, but inhibited tumor growth in the bioassays with significant efficacy. In the pancreatic cancer model, EPI-X4a, f and k inhibited mean tumor growth by > 50% and even caused complete remissions. In the lymphoma model, EPI-X4b, n and p inhibited mean tumor growth by > 70% and caused stable disease. Given the non-toxic and non-immunogenic properties of EPI-X4, these findings underscore its status as a promising therapy of pancreatic cancer and lymphoma and warrant further studies. SIMPLE SUMMARY: This study examined the value of chemokine receptor CXCR4 as an antineoplastic target for the endogenous peptide inhibitor of CXCR4 (EPI-X4), a 12-meric peptide derived from serum albumin. EPI-X4 inhibits CXCR4 interaction with its natural ligand, CXCL12 (SDF1). Therefore, malignancies (including pancreatic cancer and lymphoma) that depend on the CXCR4/CXCL12 pathway for progression can be targeted with EPI-X4. Of 634 genes that were linked to the CXCR4/CXCL12 pathway, 21% were associated with metastasis. In cultured human Suit2-007 pancreatic cancer cells, CXCR4 showed low to undetectable expression, which was why EPI-X4 did not inhibit pancreatic cancer cell proliferation. These findings were different in vivo, where CXCR4 was highly expressed and EPI-X4 inhibited tumor growth in rodents harboring pancreatic cancer or lymphoma. In the pancreatic cancer model, EPI-X4 derivatives a, f and k caused complete remissions, while in lymphomas EPI-X4 derivatives b, n and p caused stable disease.

Advanced EPI-X4 Derivatives Covalently Bind Human Serum Albumin Resulting in Prolonged Plasma Stability

Advanced derivatives of the Endogenous Peptide Inhibitor of CXCR4 (EPI-X4) have shown therapeutic efficacy upon topical administration in animal models of asthma and dermatitis. Here, we studied the plasma stability of the EPI-X4 lead compounds WSC02 and JM#21, using mass spectrometry to monitor the chemical integrity of the peptides and a functional fluorescence-based assay to determine peptide function in a CXCR4-antibody competition assay. Although mass spectrometry revealed very rapid disappearance of both peptides in human plasma within seconds, the functional assay revealed a significantly higher half-life of 9 min for EPI-X4 WSC02 and 6 min for EPI-X4 JM#21. Further analyses demonstrated that EPI-X4 WSC02 and EPI-X4 JM#21 interact with low molecular weight plasma components and serum albumin. Albumin binding is mediated by the formation of a disulfide bridge between Cys10 in the EPI-X4 peptides and Cys34 in albumin. These covalently linked albumin-peptide complexes have a higher stability in plasma as compared with the non-bound peptides and retain the ability to bind and antagonize CXCR4. Remarkably, chemically synthesized albumin-EPI-X4 conjugates coupled by non-breakable bonds have a drastically increased plasma stability of over 2 h. Thus, covalent coupling of EPI-X4 to albumin in vitro before administration or in vivo post administration may significantly increase the pharmacokinetic properties of this new class of CXCR4 antagonists.

Biparatopic Protein Nanoparticles for the Precision Therapy of CXCR4+ Cancers

Simple Summary

Aimed at minimizing side toxicities cancer therapies require appropriate functional vehicles at the nanoscale, for receptor-mediated tumor-targeted drug delivery. The aim of the present study was to explore the human peptide EPI-X4 as a CXCR4-targeting agent in self-assembled, protein-only nanoparticles. While the systemic tumor biodistribution of EPI-X4-based materials is modest, this peptide shows potent proapoptotic effects on CXCR4⁺ cancer cells. Interestingly, the in vivo selectivity of EPI-X4 was dramatically improved, once combined into biparatopic nanoparticles, with a second CXCR4 ligand, the peptide T22. Biparatopic nanoparticles promote a highly selective tumor destruction in a mouse model of human colorectal cancer, probably associated to the CXCR4 antagonist role of EPI-X4. This study not only validates a new human ligand of the tumoral marker CXCR4, but it also offers a novel strategy for the combination, in protein nanoparticles, of dual acting ligands of tumoral markers for highly selective drug delivery.

Abstract

The accumulated molecular knowledge about human cancer enables the identification of multiple cell surface markers as highly specific therapeutic targets. A proper tumor targeting could significantly avoid drug exposure of healthy cells, minimizing side effects, but it is also expected to increase the therapeutic index. Specifically, colorectal cancer has a particularly poor prognosis in late stages, being drug targeting an appropriate strategy to substantially improve the therapeutic efficacy. In this study, we have explored the potential of the human albumin-derived peptide, EPI-X4, as a suitable ligand to target colorectal cancer via the cell surface protein CXCR4, a chemokine receptor overexpressed in cancer stem cells. To explore the potential use of this ligand, self-assembling protein nanoparticles have been generated displaying an engineered EPI-X4 version, which conferred a modest CXCR4 targeting and fast and high level of cell apoptosis in tumor CXCR4⁺ cells, in vitro and in vivo. In addition, when EPI-X4-based building blocks are combined with biologically inert polypeptides containing the CXCR4 ligand T22, the resulting biparatopic nanoparticles show a dramatically improved biodistribution in mouse models of CXCR4⁺ human cancer, faster cell internalization and enhanced target cell death when compared to the version based on a single ligand. The generation of biparatopic materials opens exciting possibilities in oncotherapies based on high precision drug delivery based on the receptor CXCR4.

Absence of the CXCR4 antagonist EPI-X4 from pharmaceutical human serum albumin preparations

BACKGROUND

Endogenous Peptide Inhibitor of CXCR4 (EPI-X4) is a natural antagonist of the CXC chemokine receptor 4 (CXCR4). EPI-X4 is a 16-mer peptide that is released from human serum albumin (HSA) by acidic aspartic proteases such as Cathepsin D and E. Since human serum albumin (HSA) is an important medicinal substance we asked whether different pharmaceutical HSA products contain EPI-X4 which could have been generated during manufacturing and whether HSA can serve as a substrate for cathepsins despite of the presence of stabilizers like caprylate.

METHODS

Eight pharmaceutical HSA preparations representing all currently used fractionation technologies were analyzed. The previously described specific EPI-X4 ELISA was used for quantification; in vitro EPI-X4 generation by acidification in the presence or absence of cathepsins was followed by quantification with ELISA.

RESULTS

None of the pharmaceutical HSA preparations tested contained EPI-X4. Acidification of HSA did not generate EPI-X4. Addition of cathepsins D and E to acidified HSA yielded high concentrations of EPI-X4 in all HSA preparations, indistinguishable between individual products.

CONCLUSION

Medicinal HSA preparations per se do not contain EPI-X4, but will replenish its precursor which can be cleaved to EPI-X4 in vivo, environmental conditions permitting.

Targeting of CXCR4 by the Naturally Occurring CXCR4 Antagonist EPI-X4 in Waldenström's Macroglobulinemia

CXCR4 expression and downstream signaling have been identified as key factors in malignant hematopoiesis. Thus, up to 40% of all patients with Waldenström's macroglobulinemia (WM) carry an activating mutation of CXCR4 that leads to a more aggressive clinical course and inferior outcome upon treatment with the Bruton's tyrosine kinase inhibitor ibrutinib. Nevertheless, little is known about physiological mechanisms counteracting CXCR4 signaling in hematopoietic neoplasms. Recently, the endogenous human peptide EPI-X4 was identified as a natural CXCR4 antagonist that effectively blocks CXCL12-mediated receptor internalization and suppresses the migration and invasion of cancer cells towards a CXCL12 gradient. Here, we demonstrate that EPI-X4 efficiently binds to CXCR4 of WM cells and decreases their migration towards CXCL12. The CXCR4 inhibitory activity of EPI-X4 is accompanied by reduced expression of genes involved in MAPK signaling and energy metabolism. Notably, the anti-WM activity of EPI-X4 could be further augmented by the rational design of EPI-X4 derivatives showing higher binding affinity to CXCR4. In summary, these data demonstrate that a naturally occurring anti-CXCR4 peptide is able to interfere with WM cell behaviour, and that optimized derivatives of EPI-X4 may represent a promising approach in suppressing growth promoting CXCR4 signaling in WM.

PPI-Detect: A support vector machine model for sequence-based prediction of protein-protein interactions

The prediction of peptide-protein or protein-protein interactions (PPI) is a challenging task, especially if amino acid sequences are the only information available. Machine learning methods allow us to exploit the information content in PPI datasets. However, the numerical codification of these datasets often influences the performance of data mining approaches. Here, we introduce a procedure for the general-purpose numerical codification of polypeptides. This procedure transforms pairs of amino acid sequences into a machine learning-friendly vector, whose elements represent numerical descriptors of residues in proteins. We used this numerical encoding procedure for the development of a support vector machine model (PPI-Detect), which allows predicting whether two proteins will interact or not. PPI-Detect (https://ppi-detect.zmb.uni-due.de/) outperforms state of the art sequence-based predictors of PPI. We employed PPI-Detect for the analysis of derivatives of EPI-X4, an endogenous peptide inhibitor of CXCR4, a G-protein-coupled receptor. There, we identified with high accuracy those peptides which bind better than EPI-X4 to the receptor. Also using PPI-Detect, we designed a novel peptide and then experimentally established its anti-CXCR4 activity. © 2019 Wiley Periodicals, Inc.