Introduction:

Cancer nanomedicines are designed to enhance the delivery of chemotherapeutics in solid tumors through the enhanced permeation and retention (EPR) effect. However, the extent of EPR has been shown to be highly variable between patients which eventually reduces the overall efficacy of nanomedicines against the current standards of care, hinders their clinical translation, and underlines the need for measures enabling personalized (nano)therapies. Tissue biomarkers are commonly used for patient stratification in oncology for targeted therapies, such as therapeutic antibodies (1). Nevertheless, there are still no established biomarkers and thus no patient stratification for nanomedicines. Recently, it has been shown that a high number of blood vessels and macrophages could serve as a biomarker for predicting nanomedicine accumulation in tumor (2). The extravasation and accumulation of endogenous nanoparticles such as the immunoglobulins G and M (IgG and IgM), could serve as a companion diagnostic indicating the tumor accumulation of nanomedicines. In this study, we aimed to investigate if the accumulation of immunoglobulins correlates with the accumulation of a fluorophore-labeled nanocarrier, using three tumor models with different degrees of nanomedicine accumulation (2).

Methods:

We used a 67 kDa-sized poly(N-(2-hydroxypropyl) methacrylamide) (PHPMA) polymer, which has been extensively investigated as a potential nanocarrier for tumor-targeted drug delivery (3). The biodistribution and tumor accumulation of DY750-labelled PHPMA was assessed in CD1 nude mice that were inoculated with either of the tested tumor models (squamous cell carcinoma (A431), ovarian carcinoma (MLS) and colon carcinoma (CT26)). Polymers were injected and then imaged via hybrid CT-FMT after 0.25, 4, 24 and 72 h post i.v. injection. To stain for perfused blood vessels, rhodamine lectin was injected after the last scan. Ex-vivo analysis of total (CD31+ve) blood vessels and immunoglobulins (IgG and IgM) was done using immunofluorescence stainings. Statistical testing was done using GraphPad prism 9.0 software (Figure 1A).

Results:

The biodistribution study of PHPMA polymers showed different degrees of tumor accumulation between the three models, ranging from 5 (A431) up to 10.2% (CT26)  of the injected dose (ID) normalized to 250 mm³ of tumor volume (Figure 1B-C). Overall, all three tumor models had variable accumulation of immunoglobulins, with IgG extravasating more and deeper from blood vessels than IgM, which was found to be more confined around blood vessels (Figure PD_A). Quantification of both IgG and IgM in terms of area fraction varied between the tumor models, showcasing the different degrees of the EPR effect (Figure PD_B). As shown in Figure PD_C, correlation analysis between the nanocarrier accumulation and immunoglobulin area fraction shows IgG moderately correlates with accumulation (r = 0.474, p = 0.086), which also poorly correlates with number of CD31+ve blood vessels, which may be due to IgG’s ability to penetrate tissues really well. On the other hand, IgM had a high correlation with the accumulation of PHPMA polymers (r = 0.734, p = 0.002) that correlated also well with number of CD31+ve blood vessels, which is a crucial tumor feature for nanomedicine delivery into solid tumors.

Conclusions:

Our study demonstrates that the accumulation of immunoglobulins (IgG and IgM) differs between tumor types. Notably, IgM shows significant potential to serve as an endogenous biomarker for nanomedicine accumulation. Using a practical and clinically feasible method, this research aims to address a key challenge in nanomedicine clinical translation which is patient stratification. Current efforts are focused on translating and validating this biomarker product in a clinical setting.

Acknowledgments:

The authors are grateful for financial support by the German Research Foundation (DFG: GRK / RTG 2735 (project number 331065168))

Novelty:

For the first time, we assessed the use of endogenous nanoparticles (immunoglobulins) as potential tissue biomarkers for cancer nanomedicine patient stratification.

Image/Figure:

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Image/Figure Caption:

Figure 1: Tumor accumulation of poly(N-(2-hydroxypropyl) methacrylamide) (PHPMA) polymers varies in tumors with different features. A) Study design B-C) FRI-based longitudinal optical imaging (B) and % of the injected dose (ID) normalized to 250 mm³ of tumor volume (C) of DY750-labelled PHPMA accumulation in the three tumors  (squamous cell carcinoma (A431), ovarian carcinoma (MLS) and colon carcinoma (CT26)). The white dashed circles indicate tumor location and images represent one mouse from each model. Each data point represents a CT–FMT scan of one animal. (2)   

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