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. 2024 Jul 11;18(29):19332–19344. doi: 10.1021/acsnano.4c05893

Transforming Albumin into a Trojan Horse of Immunotherapy-Resistant Colorectal Cancer with a High Microsatellite Instability

Wenguang Yang †, Zhanfeng Li †, Yong Li ‡, Wangxiao He †,*, Jin Yan †,‡,§,*
PMCID: PMC11271175  PMID: 38990329

Abstract

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The therapeutic response of microsatellite instability-high (MSI-H) colorectal cancer (CRC) to immune checkpoint inhibitors (ICI) is indeed surprising; however, the emergence of acquired resistance poses an even greater threat to the survival of these patients. Herein, bioinformatics analysis of MSI-H CRC samples revealed that Wnt signaling pathway represents a promising target for acquired immune reactivation, while subsequent analysis and biochemical testing substantiated the inclination of Wnt-hyperactive CRC cells to engage in macropinocytosis with human serum albumin (HSA). These findings have inspired us to develop an engineered HSA that not only possesses the ability to specifically target cancer cells but also effectively suppresses the Wnt/β-catenin cascade within these malignant cells. In pursuit of this objective, a comprehensive screening of reported Wnt small-molecule inhibitors was conducted to evaluate their affinity with HSA, and it was discovered that Carnosic acid (CA) exhibited the highest affinity while simultaneously revealing multiple binding sites. Further investigation revealed that CA HSA the capability to engineer HSA into spherical and size-tunable nanostructures known as eHSA (Engineering HSA particle), which demonstrated optimized macropinocytosis-dependent cellular internalization. As anticipated, eHSA effectively suppressed the Wnt signaling pathway and reactivated the acquired immune response in vivo. Furthermore, eHSA successfully restored sensitivity to Anti-PD1’s anticancer effects in both subcutaneous and orthotopic mouse homograft models of MSI-H CRC, as well as a humanized hu-PBMC patient-derived orthotopic xenograft (PDOX) mouse model of MSI-H CRC, all while maintaining a favorable safety profile. The collective implementation of this clinically viable immune reactivation strategy not only enables the delivery of Wnt inhibitors for CRC therapy, but also serves as an exemplary demonstration of precision-medicine-guided nanopharmaceutical development that effectively harnesses specific cellular indications in pathological states.

Keywords: albumin, immunotherapy resistance, colorectal cancer, microsatellite instability-high, Wnt pathway

Introduction

Colorectal cancer (CRC) with a high microsatellite instability (MSI-H) phenotype demonstrates characteristics such as an elevated tumor mutational burden and enhanced infiltration of lymphocytic cells, which are conducive to sustained clinical responses and improved therapeutic outcomes when treated with immune checkpoint inhibitors (ICIs), particularly PD-1 neutralizing antibodies.1−3 However, this treatment proved beneficial to less than half of MSI-H-CRC patients; nonetheless, the emergence of acquired resistance posed an even greater threat to the survival of these individuals.4 Nowadays, an increasing body of research unveiled that the fundamental mechanism underlying both intrinsic and acquired resistance against ICIs is the evasion of antitumor immune responses.5 This phenomenon can arise from genetic mutations associated with immune regulation,6 alterations in tumor cell energy metabolism,7 as well as shifts in the T-cell repertoire characterized by an upregulation of regulatory T cells relative to effector T cells.8 The urgent clinical and medical need for reliable strategies to decipher these immune evasion mechanisms, overcome immune resistance, and thus expand the scope of immunotherapy for CRC necessitates the development of elegant approaches.

In recent years, the Wnt/β-catenin signaling pathway has garnered increasing attention in relation to its role in evading antitumor immune responses, particularly in CRC, which can be attributed to both its epidemiological significance and biological functionality.9 As for the former, more than 80% of colorectal cancer (CRC) cases exhibit hyperactivation of the Wnt pathway,10 while an overwhelming majority of resistance to immune checkpoint inhibitors (ICIs) in MSI-H-CRC is closely associated with this hyperactivation.11,12 Regarding the latter, the Wnt/β-catenin signaling pathway exerts its influence on tumor immune evasion through various mechanisms, encompassing but not limited to (1) activating downstream pathways (such as C-myc, Cyclin-D1, MMP-7, and TCF1) to facilitate cancer cell proliferation, migration, and invasion;13 (2) exerting inhibitory effects on the viability and cytotoxicity of cytotoxic T lymphocytes (CTLs), while simultaneously promoting the activation of regulatory T cells (Tregs);14 and (3) inducing macropinocytosis in cancer cells to enhance nutrient acquisition thereby establishing a nutritional advantage for cancer cells over immune cells.15 Although necessary and urgent, the development of potent and safe inhibitors targeting the Wnt/β-catenin signaling pathway remains an arduous challenge, with no known candidates currently eligible for clinical application.16−18 The first category of Wnt inhibitors aims to impede the accumulation of β-catenin by blocking upstream signaling molecules in this pathway, including DVL, Frizzled, and Porcupine.16,17 However, these inhibitors often exhibit limited efficacy when mutations occur downstream in the Wnt pathway (APC, Axin, or β-catenin).16 The second category of Wnt inhibitors operates by facilitating the degradation of β-catenin or impeding the interaction between β-catenin and its coactivators.17 Despite showcasing formidable antitumor capabilities, these medications often entail severe side effects linked to elevated exposure dosages.16,17,19 Thus, the design of prospective Wnt inhibitors necessitates an exceptional level of tumor targeting specificity, given the pivotal role played by the Wnt pathway in tissue repair and maintenance of normal physiological functions.20

Toward this objective, we hypothesize that the upregulated macropinocytosis observed in CRC cells as a result of Wnt activation could serve as a targeted approach for delivering Wnt inhibitors. The activation of the Wnt/β-catenin cascade has been found to enhance the expression of macropinocytosis-associated proteins Pak1 and RAC1, thereby bestowing cancer cells with a nutritional advantage over immune cells in the nutrient-deprived tumor microenvironment, particularly in intestinal tumors.15,21,22 Herein, we validated the biological processes of Wnt-driven immune evasion and macropinocytosis in MSI-H-CRC using advanced bioinformatics methods. Furthermore, we have unveiled the propensity of Wnt-hyperactive CRC cells to engage in macropinocytosis with human serum albumin (HSA), which inspired us to develop an engineered HSA that can not only be specifically taken up by cancer cells but also effectively suppress the Wnt/β-catenin cascade within these malignant cells. Toward this objective, a comprehensive screening of reported Wnt small-molecule inhibitors was conducted using an Artificial Intelligence strategy to assess their affinity with HSA. Carnosic acid (CA) exhibited the highest affinity toward HSA while simultaneously revealing multiple binding sites. Consequently, CA possesses the capability to engineer HSA into spherical and size-tunable nanostructures termed eHSA (Engineering HSA particle). Notably, these nanostructures demonstrated optimized macropinocytosis-dependent cellular internalization compared to the conventional HSA monomer. As anticipated, eHSA effectively suppressed the Wnt signaling pathway and reactivated the acquired immune response in vivo. Furthermore, eHSA successfully restored sensitivity to Anti-PD1’s anticancer effects in both subcutaneous and orthotopic mouse homograft models of MSI-H CRC, as well as a humanized hu-PBMC patient-derived orthotopic xenograft (PDOX) mouse model of MSI-H CRC, all while maintaining a favorable safety profile. The collective implementation of this clinically viable immune reactivation strategy not only enables the delivery of Wnt inhibitors for CRC therapy, but also serves as an exemplary demonstration of precision-medicine-guided nanopharmaceutical development that effectively harnesses specific cellular indications in pathological states.

Results/Discussion

Activation of Wnt Signaling Drives Immune Evasion and Upregulates Macropinocytosis in CRC

Supporting our drug delivery strategy, we validated the role of Wnt activation in driving immune evasion and macropinocytosis in CRC patients using bioinformatics approaches (Figure 1A). The gene expression data sets were obtained from CRC patients with microsatellite instability (MSI) information from the GEO database (GSE39582).23 Within these data sets, MSI expression showed significant correlations with a series of immune therapy indicators (Figure 1B) including immune therapy score (Tide score), T-cell exclusion of tumor, cancer-associated fibroblast levels (CAF signature) and tumor-associated M2-type macrophages (TAM (M2 subtype) signature), indicating MSI-H patients are more likely to benefit from immune therapy. Focusing on the dMMR subtype (representing MSI-H patients, 76 cases) within the data set, we performed ssGSEA scoring based on the Wnt gene set and categorized them into WNTH (top 25 scoring) and WNTL (bottom 25 scoring) groups. Compared to WNTL group, WNTH group showed significantly reduced immune therapy benefits (Tide score) and upregulation of T exclusion of tumor (Figure 1C), along with GSEA results demonstrating negative regulation in biological processes related to the immune system (Figure 1D), immune effector (Figure 1E), cytokines (Figure 1F), and immune responses (Figure 1G).

Figure 1.

Figure 1

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Wnt signaling activation drives immune evasion and upregulates macrophage phagocytosis in colon cancer. (A) Activation of the Wnt signaling pathway drives immune evasion and upregulates micropinocytosis in CRC, ultimately leading to adverse prognosis. (B) Bioinformatics analysis of GSE39582 data set (N = 585) reveals the correlation between MSI expression and tumor immunotherapy-related indicators in CRC. (C) Immunotherapy scores (Tide score) and tumor immune suppression (T-cell exclusion of tumor) between the WntH and WntL groups. The WntH (top 25)/WntL (bottom 25) grouping is based on the ssGSEA scores of Wnt gene set in dMMR-type patients (N = 76) from the GSE39582 data set. (D–G) Gene set enrichment analysis (GSEA) of immune system regulation in the WntH and WntL (control).groups. (H) Volcano plot of differential gene expression between the WntH and WntL (control) group. The data is derived from the gene expression data set of CRCpatients from TCGA (N = 471). The data set was subjected to ssGSEA scoring based on the Wnt gene set, and then sorted by score to create WntH group (top 50) and the WntL group (bottom 50). (I–K) GSEA of pinocytosis (I, J) and micropinocytosis (K) processes in the WntH and WntL (control) groups. (L) Expression levels of RAC1 and PAK1 in the WntH and WntL groups. (M) Spearman correlation analysis of RAC1 and PAK1 with Wnt pathway-related proteins, including Wnt3, Ctnnb1, MYC, and TCF1. All gene expression levels were standardized to the GAPDH expression levels. Data are represented as mean ± standard deviation. (*, p < 0.05; **, p < 0.01; ***, p < 0.001; and ****, p < 0.00001.)

In exploring Wnt activation and upregulation of macrophage phagocytosis, we obtained gene expression data sets of all CRC patients from TCGA database (471 cases) and similarly categorized them into WNTL (top 50 scoring) and WNTH groups (bottom 50 scoring). Analysis of differential genes (Figure 1H) revealed upregulated enrichment of pinocytosis (Figure 1I) and macropinocytosis (Figure 1J,K) pathways in the WNTH group. Further, we evaluated the abundance of macropinocytosis-driving proteins PAK1 and RAC1. Compared to WNTL group, WNTH group exhibited significant upregulation of PAK1 and RAC1 (Figure 1L). Additionally, PAK1 and RAC1 showed significant positive correlations with Wnt pathway proteins (Wnt3, CTNNB1, MYC, and TCF7) (Figure 1M), revealing the driving effect of Wnt activation on macropinocytosis in CRC.

Cellular Internalization of HSA Is Dependent on Micropinocytosis, and CA Exhibits High Affinity to HSA with Multiple Binding Sites

Plasma proteins often serve the role of transporting nutrients within organisms and exhibit a relatively long half-life. Consequently, they are frequently utilized as carriers for drug delivery24 to enhance the pharmacokinetic properties.25,26 Considering this, we assessed the uptake efficiency of a series of plasma proteins, including HSA, IGG, FBL, and HGB, in the MC38 (murine CRC cell line) for subsequent supramolecular construction. Following a 6-h incubation of MC38 cells with FITC-labeled HSA, IGG, FBL, and HGB, FCM results revealed that HSA-FITC exhibited the highest uptake, while other proteins were scarcely internalized. (Figure 2A).

Figure 2.

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HSA exhibits macropinocytosis-dependent cellular internalization and screening for appropriate Wnt inhibitor. (A) Flow cytometric (FCM) analysis of the uptake of various plasma proteins, including HSA, FBL, IGG, and HGB (labeled with FITC), by MC38 cells. (B, C) FCM analysis of HSAFITC uptake in MC38 (B) and HCT116 (C) cell lines after pretreatment with macropinocytosis inhibitors EIPA and cytochalasin D and Wnt inhibitor CA for 2 h, along with laser confocal microscopy (CLSM) images showing colocalization of HSAFITC and TRITC-Dextran. (scale bar: 40 μm). (D) Molecular docking screening of Wnt inhibitors library to match the hydrophobic pocket of HSA (PDB coordinates: 1AO6). (E) Trajectory images and cluster numbers from coarse-grained molecular dynamics simulations with a mass ratio of 1:1 for HSA:CA at different time points.

Given the enhanced macropinocytosis of CRC, we further explored the internalization mechanism of HSA. HCT116 and MCT116 cell lines were pretreated with macropinocytosis inhibitors EIPA and Cyto D, followed by incubation with FITC-labeled HSA (HSAFITC) for 6 h. Compared to Control group, FCM and CLMS images showed that, EIPA and Cyto D decreased uptake of HSAFITC(Figure 2B,C). Of note, Cyto D exhibited a weaker inhibitory effect compared to EIPA, which may be attributed to the complex role of Cyto D in regulating other uptake pathways such as clathrin-dependent endocytosis and caveolae-dependent endocytosis.27 Consistent changes in fluorescence intensity and colocalization of TRITC-Dextran28 and HSAFITC further confirmed that HSA was taken up via macropinocytosis pathway (Figure 2B,C). Furthermore, cells pretreated with Wnt inhibitor Carnosic acid (CA) also showed reduced uptake of HSAFITC and TRITC-Dextran, confirming the dynamic relationship between Wnt signal inhibition and downregulation of macropinocytosis, consistent with previous bioinformatics analysis (Figure 1I–M). Surprisingly, TCGA database analysis revealed higher expression (Figure S1A) of HSA-binding protein SPARC29 in CRC, and molecular docking (Figure S1B) and fluorescence polarization results (Figure S1C) consistently indicated high affinity between HSA and SPARC. These pieces of evidence suggest that HSA may possess active targeting characteristics toward CRC. As expected, blocking cells with SPARC antibodies significantly reduced the efficiency of HSA uptake (Figure S1D,E).

To match the physicochemical properties of HSA, we utilized the typical hydrophobic cavity of HSA as a binding site for molecular docking screening of Wnt inhibitors library16 and demonstrated corresponding binding conformations (Figure 2D). The compound CA exhibited the utmost affinity toward HSA, boasting a binding energy of −3.3 kcal/mol and multiple discernible binding sites, thereby implying the profound capability of CA to intricately assemble with HAS into a sophisticated hierarchical structure. To verify it, a coarsened system comprising randomly dispersed HSA and CA (mass ratio 1:1) was constructed to investigate the molecular motion patterns of HSA and CA in a many-to-many mode. The trajectory analysis revealed rapid system aggregation within 200 μs, gradually transitioning into a nearly spherical structure (Figure 2E), which indicates the inherent self-assembly tendency between CA and HSA.

Construction of Supramolecular eHSA with Cellular Internalization Properties Dependent on Macropinocytosis

The self-assembly tendency between CA and HSA was further investigated by varying the mass ratios of HSA to CA. When the ratio of HSA:CA was 2:1, a loosely packed near-spheroid nanostructure could be observed by TEM (Figure 3A), while maintaining a small hydrodynamic diameter (Figure 3A). Increasing the ratio of CA resulted in more pronounced aggregation and a larger hydrodynamic diameter (Figure 3B,C). Considering that the hydrodynamic diameter at a ratio of 1:1 is closer to that of commercial albumin-bound paclitaxel,30,31 this supramolecular HSA was named eHSA and subsequently evaluated in later experiments. Moreover, the loading efficiency of CA by eHSA was as high as 82.4% (Figure S2), and it exhibited excellent colloidal stability due to its zeta potential of −25.3 mV (Figure S3A), which was further confirmed by the absence of significant disintegration or changes in particle size observed within 24 h in PBS containing 20% FBS (Figure S3B).

Figure 3.

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Construction of supramolecular eHSA with cellular internalization properties dependent on macropinocytosis. (A–C) TEM images and hydrodynamic size distribution measured by DLS of HSA:CA at mass ratios of 2:1 (A), 1:1 (B), and 1:2.5 (C). (D, E) Flow cytometric analysis of HSAFITC uptake in MC38 (D) and HCT116 (E) cell lines after pretreatment with macropinocytosis inhibitors EIPA and CytoD, and SPRAC antibody for 2 h, along with laser confocal microscopy images showing colocalization of HSAFITC and TRITC-Dextran. (scale bar: 40 μm) (F–I) GSEA analysis results of differentially expressed genes between eHSA and control groups in endocytosis (F, G), macropinocytosis (H), and pinocytosis (I) processes. (J, K) Hierarchical clustering heatmaps of gene sets of endocytosis (J) and macropinocytosis (K) processes. (*, p < 0.05; **, p < 0.01; ***, p < 0.001; and ****, p < 0.00001.).

Further testing of the internalization characteristics of eHSA was conducted in MC38 and HCT116. FCM and CLSM images indicated significant inhibition of eHSA cellular uptake by Cyto D and EIPA. Additionally, CLSM images of Control group showed high colocalization correlation between HSA-FITC and TRITC-Dextran (0.77 correlation for MC38 and 0.83 for HCT116), suggesting eHSA were uptaken via macropinocytosis pathways (Figure 3D,E). Moreover, cells treated with SPARC antibodies exhibited reduced uptake of eHSA (decreased by 14.2% in MC38 and 8.9% in HCT116), revealing the positive role of SPARC in eHSA internalization. Importantly, under the same concentration conditions, the uptake of eHSA is significantly higher than that of HSA in MC38 and HCT116 cells (Figure S4), which could be attributed to two factors:32 (1) the suitable nanoscale size of eHSA enhances adhesion to the cell membrane, thereby providing the necessary membrane curvature energy for internalization; (2) the bridging effect of Au increases the rigidity of eHSA, thus enhancing cellular internalization. In summary, compared to monomeric HSA, eHSA demonstrated macropinocytosis-dependent cellular uptake and enhanced internalization, aligning with the expectations of eHSA molecular design.

Of note, despite the presence of CA in our drugs, eHSA demonstrated efficient cellular uptake, which implies that eHSA effectively blocked the toxicity of CA in vivo circulation, thus exhibiting biocompatibility with normal tissues. To further elucidate this, transcriptome sequencing was performed on HCT116 cells after 24 h of incubation with eHSA. GSEA revealed significant downregulation of gene sets related to endocytosis (Figure 3F,G,J), macropinocytosis (Figure 3H,K), pinocytosis (Figure 3I), phagocytosis (Figure S5A,B) and cytoskeleton (Figure S5C) in eHSA group. The aforementioned findings once again underscored the exclusive manifestation of CA toxicity postinternalization, while concurrently exhibiting extracellular safety. Moreover, the eHSA-treated group exhibited an upregulation in autophagy (Figure S5D), which can be attributed to the inhibition of macropinocytosis and subsequent cellular nutrient deficiency.33,34 This process is likely to augment the anticancer cytotoxicity of eHSA.

eHSA Effectively Inhibited Wnt Pathway Activation In Vitro and Consequently Suppressed Cell Viability

To further elucidate the mechanism of action and tumor inhibitory effect of eHSA, we conducted transcriptome sequencing on HCT116 cells incubated with either PBS (control group) or eHSA for a duration of 24 h. The volcano plot (Figure 4A) unveiled a total of 674 differentially expressed proteins, comprising 587 upregulated proteins and 87 downregulated proteins. Gene Set Enrichment Analysis (GSEA) performed on these differential proteins demonstrated a significant downregulation in Wnt-related gene sets within the eHSA-treated cells (Figure 4B–D). Additionally, Figure 4E exhibits cluster analysis pertaining to the gene set associated with the Regulation of Wnt signaling pathway. These comprehensive analyses collectively suggest that eHSA effectively impedes the Wnt signaling pathway in an in vitro setting.

Figure 4.

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eHSA effectively inhibited Wnt pathway activation in vitro and consequently suppressed cell viability. (A) Volcano plot depicting the differential gene expression between HCT116 cells treated with 10 μM eHSA or PBS (control group) for 24 h (n = 3); Genes with an absolute log2FoldChange greater than 1.3 and adjust p-value less than 0.05 are considered differentially expressed genes. (B–E) GSEA analysis results of differentially expressed genes in the gene sets related to the Wnt signaling pathway (B–D) along with the hierarchical clustering heatmap (E). (F, G) MTT cell viability assay of MC38 (F) and HCT116 (G) cell lines after treatment with a series of concentration gradients of eHSA or CA for 48 h. (H–M) GSEA results of differentially expressed genes in the gene sets related to cellular apoptosis (H–I) or the cell cycle (J–M) processes.

Additionally, we compared the cell cytotoxic effects of CA and eHSA via MTT cell viability assay. As shown in Figure 4F,G, eHSA exhibited lower IC50 values and more effective cell killing than CA in both HCT116 and MC38 cell lines, whereas HSA did not demonstrate cytotoxic effects on the cells (Figure S6). Furthermore, GSEA results for eHSA also demonstrated upregulation of apoptosis-retaled gene sets (Figure 4H,I) and downregulation of cell cycle-related gene sets (Figure 4J–M). These pieces of evidence collectively suggest that eHSA effectively inhibits cancer cell proliferation by suppressing the Wnt signaling cascade.

Wnt Pathway Was Inhibited by eHSA, Leading to the Reactivation of T-Cell Acquired Immunity In Vivo

In pursuit of enhancing the efficacy of immunotherapy, we investigated the Wnt pathway inhibitory effect of eHSA and its immunomodulatory effects in CRC Syngeneic subcutaneous transplantation model. As shown in Figure 5A, C57/B6 mice were randomly divided into four groups when subcutaneous tumor volume reached 50 to 100 mm3: Control (200 μL PBS), Anti-PD1 (5 mg/kg), eHSA (2 mg/kg), and Combo (Anti-PD1+eHSA combination). During a 10-day treatment cycle with alternate-day dosing, the tumor growth curve indicated a tumor inhibition rate of 47.5% after eHSA treatment. Moreover, in combination with PD-1 immunotherapy, the Combo group exhibited a 17.6% increase in tumor inhibition compared to Anti-PD1 group (Figure 5B). Tumor images at the end of treatment (Figure 5C) also confirm that eHSA, whether administered alone or in combination with PD1 therapy, significantly inhibits tumor proliferation. TUNEL apoptosis staining (Figures 5D and S7A) and immunohistochemical images of Ki67 (Figures 5E and S7B), and Cyclin-D1 (Figures 5F and S7C) in tumor tissues further corroborated tumor suppression effect at the molecular level. To validate the underlying mechanism of eHSA sensitizing immunotherapy, we analyzed Wnt activity and immune microenvironment of tumor tissues. Immunohistochemical results showed a significant reduction in β-catenin protein expression in the eHSA and Combo groups (Figures 5G and S7D). Analysis of T-cell infiltration in tumor tissues by immunofluorescence FCM35 revealed significant alterations in the T-cell repertoire in eHSA group. Additionally, in combination therapy, compared to Anti-PD1 group, Combo group exhibited a 54.6% reduction in Treg cell proportion (Figure 5H), while Granzyme B and INF-γ were upregulated by 5.61-fold and 3.12-fold, respectively (Figure 5I). Overall, these abundant findings suggest that eHSA suppresses tumor proliferation by downregulating Wnt activity, thereby enhancing PD-1 therapy’s effectiveness by upregulating cytotoxic T-cell infiltration in tumor tissues.

Figure 5.

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Wnt pathway was inhibited by eHSA, leading to the reactivation of T-cell acquired immunity in vivo. (A) Construction and dosing regimen of the MC38 CRCsubcutaneous transplant model. (B, C) For CRC subcutaneous transplantation mouse model, tumor growth curves (B) and tumor images (C) of the Control, Anti-PD1, and Combo groups during the 10-day alternate-day treatment period. (D) Quantitative scores of Tunel staining in tumor tissues of each group. (E–G) Quantitative scores of Ki67 (E), Cyclin D1 (F), and β-catenin (G) immunohistochemical staining in tumor tissues of each group. (H) Multichannel FCM analysis for Treg cell markers after different treatments. (I) Multichannel FCM analysis for cytotoxic T-cell indicators, including GzmB and INF-γ, after different treatments. (J) Survival curves for the Anti-PD1, eHSA, Combo, and 5-FU groups in the orthotopic colon cancer mouse model. (K, L) Abdominal fluid volume (K), and tumor weight (L) after random sampling on days 10 and 11 of treatment. (*, p < 0.05; **, p < 0.01; ***, p < 0.001; and ****, p < 0.00001.).

Administration of eHSA and Anti-PD1 Combo-Therapy Significantly Extends the Survival of Mice with Orthotopic MC38 CRC

The antitumor efficacy of eHSA has prompted us to further explore its therapeutic effects for orthotopic CRC. Initially, MC38 cells were inoculated into the submesentery colon of female C57BL/6 mice to establish an in situ CRC mouse model. Subsequently, these mice were randomly divided into five groups: CON, Anti-PD1, eHSA, Combo, and 5-FU. They were then intervened according to the dosing scheme outlined in Figure 6A via intravenous tail vein injection. The frontline chemotherapy drug for CRC treatment, 5-FU, served as a positive control to evaluate the efficacy of other groups. During the 10-day administration, a reduction in body weight was not observed across all five groups (Figure 6B), thereby affirming the treatment’s impeccable biosafety. The colon images, obtained through random sampling of two mice from each group, unequivocally demonstrated that the combination treatment exhibited the most potent tumor suppression effect (Figure 6C). These findings were further corroborated by a statistically significant reduction in abdominal fluid volumes (Figure 6D) and tumor weights (Figure 6E) within the Combo group. Specifically, monotherapy with Anti-PD1 or eHSA only resulted in a modest decrease of ascites volume by 40 and 43% respectively (Figure 6D), along with a mere shrinkage of tumors by 19 and 25%, respectively (Figure 6E), both proving less effective than treatment with 5-FU. However, to our delight, the combined administration of Anti-PD1 and eHSA showcased an impressive reduction in ascites volume exceeding over 70% (Figure 6D), coupled with a tumor shrinkage surpassing over 40% (Figure 6E). Consequently, this combo-therapy significantly extended the median survival time for orthotopic MC38 CRC mice from 20 to 30 days - clearly superior to those treated solely with Anti-PD1 (23 days), eHSA (25 days), or 5-FU (23 days) (Figure 6F). The combined administration of eHSA and Anti-PD1 therapy demonstrates an enhancement in the survival rate of mice with orthotopic MC38 CRC.

Figure 6.

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Administration of eHSA and Anti-PD1 combo-therapy significantly extends the survival of mice with orthotopic MC38 CRC. (A) Dosing regimens for the mouse model of in situ MC38 CRC included Anti-PD1, eHSA, Combo, and 5-FU groups. (B) Weight change curves of mice in each group during the treatment period. (C–E) After randomly selecting mice from each group on day 10 of treatment, we analyzed images of colon tumors (C), ascites volume (D), and tumor weight (E) from the collected samples. (F) Survival curves of each group after treatment completion. (*, p < 0.05; **, p < 0.01; ***, p < 0.001; and ****, p < 0.00001).

eHSA Treatment Effectively Inhibited Wnt Activation and Enhanced the Efficacy of PD-1 Therapy in Humanized PDOX Models of CRC

Considering the heterogeneity in biological features and tissue structures between human and murine sources, we established patient-derived orthotopic xenograft (PDOX) models36,37 of MSH-CRC to investigate the clinical translational potential of eHSA. Specifically, surgically obtained MSI-H colorectal cancer tumors were dissected into 2–3 mm3 fragments and implanted subcutaneously into NSG mice (P1). Successful engraftment was indicated when tumors reached 1–2 cm3 in size. Subsequently, P1 transplantable tumor were resected and reimplanted into NOD/SCID mice for up to the third generation (P3) to ensure model stability and representativeness. Additionally, to humanize the immunodeficient mice, peripheral blood mononuclear cells (PBMCs) were isolated from healthy donors (HLA-A1+) to obtain peripheral blood mononuclear cells, comprising lymphocytes, monocytes, and natural killer cells, which play crucial roles in the immune system. 7.5 × 105 PBMCs were intravenously injected into NSG mice for immune reconstitution. P3 transplantable tumor were then sectioned and implanted into the colons of 20 female NSG mice to establish humanized colorectal cancer PDOX models for eHSA efficacy studies. Subsequently, peripheral blood from humanized NSG mice was harvested and intravenously injected into PDOX models for human immune reconstitution (Figure 7A).

Figure 7.

Figure 7

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eHSA treatment effectively inhibited Wnt activation and enhanced the efficacy of PD-1 therapy in humanized PDOX models of CRC. (A) Schematic representation of the construction of the humanized CRC-PDOX model and the process of humanized immune reconstitution. (B) Volcano plot illustrating the differential gene expression between eHSA and Control groups after treatment (n = 3). (C) Cluster heatmap depicting the expression of these differential genes in key proteins of Wnt/β-catenin signaling pathway. (D–F) GSEA results of the differential genes in Wnt-related gene sets (D, E) and cytotoxic T-cell (CD8+)-related gene sets (F). (G) Dosing regimens for Anti-PD1, eHSA, and Combo groups in the CRC-PDOX model. (H, I) Tumor tissue volume (H) and weight (I) of mice in each group at the end of treatment. (J–M) Immunohistochemical staining images and quantitative scoring (N) of Ki67 (J), Cyclin D1 (K), C-myc (L), and β-catenin (M) of tumor tissues for each group (scale bar: 100 μm). (*, p < 0.05; **, p < 0.01; ***, p < 0.001; and ****, p < 0.00001.).

To investigate the biofunction of eHSA in this preclinical model, tumor tissues from Control and eHSA groups (n = 3) were randomly selected after a single dose for transcriptome sequencing. The volcano plot in Figure 7B illustrates the differentially expressed genes between the Control and eHSA groups. Further clustering and GSEA of these differentially expressed genes revealed that, compared to the Control, eHSA significantly decreased the transcriptional levels of the Wnt/β-catenin signaling pathway in tumor tissues (Figure 7C) and exhibited negative enrichment in Wnt-related gene sets (Figure 7D,E). Notably, eHSA group also showed enrichment in gene set: PID_CD8_TCR_PATHWAY (Figure 7F), indicating the involvement of eHSA in processes such as activation and functional activation of CD8+ T cells.

For the potency test, a 5-week drug intervention was administered according to the dosing regimen outlined in Figure 7G. Upon completion of the treatment period, all mice were sacrificed, and tumor tissues were harvested. The tumor size (Figure 7H) and weight (Figure 7I) of each group demonstrated that eHSA significantly inhibited tumor proliferation, either as monotherapy or in combination therapy, indicating antitumor effects of eHSA in the humanized CRC-PDOX model. Immunohistochemical staining of these tumor tissue sections further supported these findings. Staining images and quantitative scoring results revealed that all treatment groups downregulated Ki67 (Figure 7J,N), Cyclin-D1 (Figure 7K,N), and C-myc (Figure 7L,N) to inhibit tumor proliferation and metastasis. The β-catenin expression in the eHSA and Combo groups was significantly downregulated (Figure 7M,N), consistent with the transcriptome sequencing results, indicating the downregulation of the Wnt signaling pathway. Overall, eHSA significantly inhibited Wnt signaling pathway activation and sensitizes Anti-PD1 therapy in the humanized CRC-PDOX model.

Conclusions

In this study, we employed bioinformatics methodologies to unveil the intricate biological processes underlying Wnt activation-induced immune resistance and augmented macropinocytosis in patients with MSI-H-CRC. Drawing upon this profound understanding, we have devised a nanopharmaceutical strategy to harness the full potential of the augmented macropinocytosis in CRC cells triggered by Wnt activation, thereby enabling targeted delivery of Wnt inhibitors. Subsequent analysis and biochemical testing substantiated the inclination of Wnt-hyperactive CRC cells to engage in macropinocytosis with human serum albumin (HSA). These findings have inspired us to develop an engineered HSA that not only possesses the ability to specifically target cancer cells but also effectively suppresses the Wnt/β-catenin cascade within these malignant cells. In the pursuit of this objective, an AI strategy was employed to conduct a comprehensive screening of reported Wnt small-molecule inhibitors, unveiling their affinity with HSA. CA exhibited the utmost affinity toward HSA while simultaneously revealing multiple binding sites. Subsequently, HSA and CA were ingeniously utilized as self-assembly modules to fabricate a nanoscale engineered HAS termed eHSA. The inherent macropinocytosis of HSA and its nanoparticulate nature were leveraged, resulting in eHSA demonstrating significantly enhanced internalization by CRC cells. The results demonstrated the potent inhibitory effect of eHSA on Wnt signaling activity, both in vitro and in vivo. In comparison to conventional Wnt inhibitors, the HSA encapsulation strategy proposed in this study enhances the targeting ability and cytotoxicity of small molecule drugs, while also offering advantages such as simplicity in synthesis and solution stability.

Importantly, eHSA exerted a positive regulatory effect on the tumor immune microenvironment by downregulating Treg cells and upregulating cytotoxic T cells, thereby creating favorable conditions for the efficacy of Anti-PD1 immunotherapy. Whether used alone or in combination with PD1 immunotherapy, eHSA restrained tumor proliferation and prolonged survival time in both subcutaneous/orthotopic models of MC38 CRC. Moreover, eHSA exhibited similar therapeutic efficacy in PDOX models, highlighting its substantial clinical translational potential. In summary, this immunoreactivation strategy targeting the Wnt signaling pathway via macropinocytosis inhibition provides an approach to improving the effectiveness of immunotherapy in MSI-H-CRC patients. The collective implementation of this clinically viable immune reactivation strategy not only enables the delivery of Wnt inhibitors for CRC therapy, but also serves as an exemplary demonstration of precision-medicine-guided nanopharmaceutical development that effectively harnesses specific cellular indications in pathological states.

Methods/Experimental

Synthesis of eHSA

Initially, dissolve 5 mg of HSA and 0.5 mg of TECP in 1 mL of PBS solution, followed by sonication for a duration of 10 min to completely reduce the disulfide bonds within HSA. Subsequently, adjust the solution volume to 4.5 mL and incorporate an appropriate quantity of CA DMSO solution to achieve a mass ratio between HSA and CA at either 2:1, 1:1, or 1:2.5. Vigorously agitate the system for a period of 5 min to ensure thorough homogenization.

Characterization of eHSA

The morphology and structure of eHSA are observed using high-resolution transmission electron microscopy (HRTEM) on the Talos F200X, revealing its intricate form and arrangement. The fluid dynamic particle size distribution and zeta potential of the eHSA solution are measured with precision using dynamic light scattering (DLS) employing the advanced Malvern Zetasizer Nano ZS system. To assess the stability of eHSA, it is dissolved in a PBS solution, and its particle size distribution is meticulously analyzed at various time intervals ranging from 1 to 24 h to discern any fluctuations in size. In order to evaluate the loading efficiency of CA by eHSA, centrifugation at a speed of 10,000 rpm for 5 min is employed followed by analysis of the supernatant for CA content utilizing HPLC; this quantitative analysis relies on an established standard curve.

Acknowledgments

This work was supported by the National Key Research and Development Program of China (No. 2022YFE0133500), the National Natural Science Foundation of China (No. 22007076, No. 82272782, and No. 32171256), the Thousand Talents Plan of Shaanxi Province (For W.H.), and “The Young Talent Support Plan” of Xi'an Jiaotong University (W.H.). We thank the Instrument Analysis Center of Xi'an Jiaotong University for their assistance with TEM, DLS, and FT-IR analysis. We also appreciate the help of RNA-seq analysis from Tgene Biotech (Shanghai) Co., Ltd.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsnano.4c05893.

  • Supplementary methods (including general information for reagents, necessary details for animal experiments, necessary protocols for cell experiments, and statistical approach) and 7 supplementary figures (PDF)

Author Contributions

∥ W.Y. and Z.L. contributed equally to this work.

The authors declare no competing financial interest.

Supplementary Material

nn4c05893_si_001.pdf (867.6KB, pdf)

References

  1. Asaoka Y.; Ijichi H.; Koike K. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N. Engl. J. Med. 2015, 373, 1979. 10.1056/NEJMc1510353. [DOI] [PubMed] [Google Scholar]
  2. Marcus L.; Lemery S. J.; Keegan P.; Pazdur R. FDA Approval Summary: Pembrolizumab for the Treatment of Microsatellite Instability-High Solid Tumors. Clin. Cancer. Res. 2019, 25, 3753–3758. 10.1158/1078-0432.CCR-18-4070. [DOI] [PubMed] [Google Scholar]
  3. Overman M. J.; McDermott R.; Leach J. L.; Lonardi S.; Lenz H.-J.; Morse M. A.; Desai J.; Hill A.; Axelson M.; Moss R. A.; et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study. Lancet Oncol. 2017, 18, 1182–1191. 10.1016/S1470-2045(17)30422-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Sahin I. H.; Akce M.; Alese O.; Shaib W.; Lesinski G. B.; El-Rayes B.; Wu C. Immune checkpoint inhibitors for the treatment of MSI-H/MMR-D colorectal cancer and a perspective on resistance mechanisms. Br. J. Cancer 2019, 121, 809–818. 10.1038/s41416-019-0599-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Scheper W.; Kelderman S.; Fanchi L. F.; Linnemann C.; Bendle G.; de Rooij M. A. J.; Hirt C.; Mezzadra R.; Slagter M.; Dijkstra K.; et al. Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers. Nat. Med. 2019, 25, 89–94. 10.1038/s41591-018-0266-5. [DOI] [PubMed] [Google Scholar]
  6. Grasso C. S.; Giannakis M.; Wells D. K.; Hamada T.; Mu X. J.; Quist M.; Nowak J. A.; Nishihara R.; Qian Z. R.; Inamura K.; et al. Genetic Mechanisms of Immune Evasion in Colorectal Cancer. Cancer Discovery 2018, 8, 730–749. 10.1158/2159-8290.CD-17-1327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Walenta S.; Wetterling M.; Lehrke M.; Schwickert G.; Sundfo̷r K.; Rofstad E. K.; Mueller-Klieser W. High lactate levels predict likelihood of metastases, tumor recurrence, and restricted patient survival in human cervical cancers. Cancer Res. 2000, 60, 916–921. [PubMed] [Google Scholar]
  8. Michel S.; Benner A.; Tariverdian M.; Wentzensen N.; Hoefler P.; Pommerencke T.; Grabe N.; von Knebel Doeberitz M.; Kloor M. High density of FOXP3-positive T cells infiltrating colorectal cancers with microsatellite instability. Br. J. Cancer 2008, 99, 1867–1873. 10.1038/sj.bjc.6604756. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Michels B. E.; Mosa M. H.; Grebbin B. M.; Yepes D.; Darvishi T.; Hausmann J.; Urlaub H.; Zeuzem S.; Kvasnicka H. M.; Oellerich T.; et al. Human colon organoids reveal distinct physiologic and oncogenic Wnt responses. J. Exp. Med. 2019, 216, 704–720. 10.1084/jem.20180823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Wan T.; Pan Q.; Liu C.; Guo J.; Li B.; Yan X.; Cheng Y.; Ping Y. A Duplex CRISPR-Cas9 Ribonucleoprotein Nanomedicine for Colorectal Cancer Gene Therapy. Nano Lett. 2021, 21, 9761–9771. 10.1021/acs.nanolett.1c03708. [DOI] [PubMed] [Google Scholar]
  11. Chen B.; Scurrah C. R.; McKinley E. T.; Simmons A. J.; Ramirez-Solano M. A.; Zhu X.; Markham N. O.; Heiser C. N.; Vega P. N.; Rolong A.; et al. Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps. Cell 2021, 184, 6262–6280.e26. 10.1016/j.cell.2021.11.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Pai S. G.; Carneiro B. A.; Mota J. M.; Costa R.; Leite C. A.; Barroso-Sousa R.; Kaplan J. B.; Chae Y. K.; Giles F. J. Wnt/beta-catenin pathway: modulating anticancer immune response. J. Hematol. Oncol. 2017, 10, 101. 10.1186/s13045-017-0471-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Zhang K.; Yang P.-P.; He P.-P.; Wen S.-F.; Zou X.-R.; Fan Y.; Chen Z.-M.; Cao H.; Yang Z.; Yue K.; et al. Peptide-Based Nanoparticles Mimic Fibrillogenesis of Laminin in Tumor Vessels for Precise Embolization. ACS Nano 2020, 14, 7170–7180. 10.1021/acsnano.0c02110. [DOI] [PubMed] [Google Scholar]
  14. Keerthivasan S.; Aghajani K.; Dose M.; Molinero L.; Khan M. W.; Venkateswaran V.; Weber C.; Emmanuel A. O.; Sun T.; Bentrem D. J.; et al. β-Catenin promotes colitis and colon cancer through imprinting of proinflammatory properties in T cells. Sci. Transl. Med. 2014, 6, 225ra228. 10.1126/scitranslmed.3007607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Tejeda-Muñoz N.; Albrecht L. V.; Bui M. H.; De Robertis E. M. Wnt canonical pathway activates macropinocytosis and lysosomal degradation of extracellular proteins. Proc. Natl. Acad. Sci. U. S. A. 2019, 116, 10402–10411. 10.1073/pnas.1903506116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Polakis P. Drugging Wnt signalling in cancer. EMBO J. 2012, 31, 2737–2746. 10.1038/emboj.2012.126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kahn M. Can we safely target the WNT pathway?. Nat. Rev. Drug Discovery 2014, 13, 513. 10.1038/nrd4233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Feng M.; Jin J. Q.; Xia L.; Xiao T.; Mei S.; Wang X.; Huang X.; Chen J.; Liu M.; Chen C.; Rafi S.; Zhu A. X.; Feng Y. X.; Zhu D.; et al. Pharmacological inhibition of β-catenin/BCL9 interaction overcomes resistance to immune checkpoint blockades by modulating Treg cells. Sci. Adv. 2019, 5, eaau5240 10.1126/sciadv.aau5240. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Zhao H.; Ming T.; Tang S.; Ren S.; Yang H.; Liu M.; Tao Q.; Xu H. Wnt signaling in colorectal cancer: pathogenic role and therapeutic target. Mol. Cancer 2022, 21, 144. 10.1186/s12943-022-01616-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Sukhdeo K.; Mani M.; Zhang Y.; Dutta J.; Yasui H.; Rooney M. D.; Carrasco D. E.; Zheng M.; He H.; Tai Y.-T.; et al. Targeting the beta-catenin/TCF transcriptional complex in the treatment of multiple myeloma. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 7516–7521. 10.1073/pnas.0610299104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Tejeda-Muñoz N.; De Robertis E. M. Wnt, GSK3, and Macropinocytosis. Subcell. Biochem. 2022, 98, 169–187. 10.1007/978-3-030-94004-1_9. [DOI] [PubMed] [Google Scholar]
  22. Redelman-Sidi G.; Binyamin A.; Gaeta I.; Palm W.; Thompson C. B.; Romesser P. B.; Lowe S. W.; Bagul M.; Doench J. G.; Root D. E.; et al. The Canonical Wnt Pathway Drives Macropinocytosis in Cancer. Cancer Res. 2018, 78, 4658–4670. 10.1158/0008-5472.CAN-17-3199. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Marisa L.; de Reyniès A.; Duval A.; Selves J.; Gaub M. P.; Vescovo L.; Etienne-Grimaldi M.-C.; Schiappa R.; Guenot D.; Ayadi M.; et al. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med. 2013, 10, e1001453 10.1371/journal.pmed.1001453. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Zhang Y.; Sun T.; Jiang C. Biomacromolecules as carriers in drug delivery and tissue engineering. Acta Pharm. Sin. B 2018, 8, 34–50. 10.1016/j.apsb.2017.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. di Masi A.; Trezza V.; Leboffe L.; Ascenzi P. Human plasma lipocalins and serum albumin: Plasma alternative carriers?. J. Controlled Release 2016, 228, 191–205. 10.1016/j.jconrel.2016.02.049. [DOI] [PubMed] [Google Scholar]
  26. Spada A.; Emami J.; Tuszynski J. A.; Lavasanifar A. The Uniqueness of Albumin as a Carrier in Nanodrug Delivery. Mol. Pharmaceutics 2021, 18, 1862–1894. 10.1021/acs.molpharmaceut.1c00046. [DOI] [PubMed] [Google Scholar]
  27. Liu B. R.; Li J.-F.; Lu S.-W.; Leel H.-J.; Huang Y.-W.; Shannon K. B.; Aronstam R. S. Cellular internalization of quantum dots noncovalently conjugated with arginine-rich cell-penetrating peptides. J. Nanosci. Nanotechnol. 2010, 10, 6534–6543. 10.1166/jnn.2010.2637. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Byun J.-K.; Lee S.; Kang G. W.; Lee Y. R.; Park S. Y.; Song I.-S.; Yun J. W.; Lee J.; Choi Y.-K.; Park K.-G. Macropinocytosis is an alternative pathway of cysteine acquisition and mitigates sorafenib-induced ferroptosis in hepatocellular carcinoma. J. Exp. Clin. Cancer Res. 2022, 41, 98. 10.1186/s13046-022-02296-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Ji Q.; Zhu H.; Qin Y.; Zhang R.; Wang L.; Zhang E.; Zhou X.; Meng R. GP60 and SPARC as albumin receptors: key targeted sites for the delivery of antitumor drugs. Front. Pharmacol. 2024, 15, 1329636 10.3389/fphar.2024.1329636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Ibrahim N. K.; Desai N.; Legha S.; Soon-Shiong P.; Theriault R. L.; Rivera E.; Esmaeli B.; Ring S. E.; Bedikian A.; Hortobagyi G. N.; et al. Phase I and pharmacokinetic study of ABI-007, a Cremophor-free, protein-stabilized, nanoparticle formulation of paclitaxel. Clin. Cancer. Res. 2002, 8, 1038–1044. [PubMed] [Google Scholar]
  31. Hennenfent K. L.; Govindan R. Novel formulations of taxanes: a review. Old wine in a new bottle? Ann. Oncol. 2006, 17, 735–749. 10.1093/annonc/mdj100. [DOI] [PubMed] [Google Scholar]
  32. Zhang S.; Gao H.; Bao G. Physical Principles of Nanoparticle Cellular Endocytosis. ACS Nano 2015, 9, 8655–8671. 10.1021/acsnano.5b03184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Florey O.; Overholtzer M. Macropinocytosis and autophagy crosstalk in nutrient scavenging. Philos. Trans. R. Soc. London B Biol. Sci. 2019, 374, 20180154 10.1098/rstb.2018.0154. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Su H.; Yang F.; Fu R.; Li X.; French R.; Mose E.; Pu X.; Trinh B.; Kumar A.; Liu J.; et al. Cancer cells escape autophagy inhibition via NRF2-induced macropinocytosis. Cancer Cell 2021, 39, 678–693.e11. 10.1016/j.ccell.2021.02.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Yan J.; Liu D.; Wang J.; You W.; Yang W.; Yan S.; He W. Rewiring chaperone-mediated autophagy in cancer by a prion-like chemical inducer of proximity to counteract adaptive immune resistance. Drug Resist. Update. 2024, 73, 101037 10.1016/j.drup.2023.101037. [DOI] [PubMed] [Google Scholar]
  36. Mao Y.; Wang W.; Yang J.; Zhou X.; Lu Y.; Gao J.; Wang X.; Wen L.; Fu W.; Tang F. Drug repurposing screening and mechanism analysis based on human colorectal cancer organoids. Protein Cell 2024, 15, 285–304. 10.1093/procel/pwad038. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Tang H.; Xue Y.; Li B.; Xu X.; Zhang F.; Guo J.; Li Q.; Yuan T.; Chen Y.; Pan Y.; et al. Membrane-camouflaged supramolecular nanoparticles for co-delivery of chemotherapeutic and molecular-targeted drugs with siRNA against patient-derived pancreatic carcinoma. Acta Pharm. Sin. B 2022, 12, 3410–3426. 10.1016/j.apsb.2022.02.007. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

nn4c05893_si_001.pdf (867.6KB, pdf)

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