Tumor-killing nanoreactors fueled by tumor debris can enhance radiofrequency ablation therapy and boost antitumor immune responses

Radiofrequency ablation (RFA) is clinically adopted to destruct solid tumors, but is often incapable of completely ablating large tumors and those with multiple metastatic sites. Here we develop a CaCO3-assisted double emulsion method to encapsulate lipoxidase and hemin with poly(lactic-co-glycolic acid) (PLGA) to enhance RFA. We show the HLCaP nanoreactors (NRs) with pH-dependent catalytic capacity can continuously produce cytotoxic lipid radicals via the lipid peroxidation chain reaction using cancer cell debris as the fuel. Upon being fixed inside the residual tumors post RFA, HLCaP NRs exhibit a suppression effect on residual tumors in mice and rabbits by triggering ferroptosis. Moreover, treatment with HLCaP NRs post RFA can prime antitumor immunity to effectively suppress the growth of both residual and metastatic tumors, also in combination with immune checkpoint blockade. This work highlights that tumor-debris-fueled nanoreactors can benefit RFA by inhibiting tumor recurrence and preventing tumor metastasis.

Supplementary Fig. 4. UV-vis spectra of native LA (0.9 g mL -1 ) and corresponding LAOOH prepared by incubating commercial LA (0.9 g mL -1 ) with LOX at 37 o C for 3 min.

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Supplementary Fig. 5 Lipid peroxidation generation capacities of LP, HP and HLP NPs quantified by incubating them with LA (a) or cell lysates (b) at pH 6.8 and 7.4 for 4 h, respectively. Data were represented as mean ± SD, n = 3 biologically independent samples.
Supplementary Fig. 6. The capacities of hemin in promoting the propagation of lipid peroxidation from linoleic acids (LA) in the presence of oxygen and nitrogen. It was shown the hemin in the presence of oxygen could effectively promote the propagation of LA from these auto-oxidized LA, which is generated via the dissolved oxygen mediated oxidation of LA. Data was represented as mean ± SD, n = 3 biologically independent samples. Supplementary Fig. 10 Relative viabilities of HepG2 cells incubated with HCaP NPs, LCaP NPs and HLCaP NRs in the absence (a) or presence (b) of cancer cell lysates for 24 h before being determined by MTT assay. (c) Relative cell viabilities of HepG2 cells post various treatments as indicated. Data were represented as mean ± SD, n = 6 biologically independent samples, P values calculated by two-tailed student's t-test were shown on figure.
Supplementary Fig. 11 In vitro therapeutic efficacay of HLCaP NRs against MCF-7 cells (a&b), B16 cells (c&d), and CT26 cells (e&f) treated in the presence or absence of cancer cell lysates, respectively. Data were represented as mean ± SD, n = 6 biologically independent samples. Supplementary Fig. 15 Semi-quantitative analysis of DCFH fluorescence intensities of the tumor slices as shown in Figure 3e, data were represented as mean ± SD, n = 3 biologically independent samples,. S11 Supplementary Fig. 16 Confocal images of tumor slices collected from 4T1 tumor-bearing mice at 24 h and 72 h post different treatments as indicated, and subsequently stained with DCFH-DA (a) and BODIPY TM 581/591 C11 (b), respectively. A representative image of three biologically independent replicates from each group is shown in Figure a- Supplementary Fig. 17 Semi-quantitative analysis of HMGB1 signals of the tumor slices as shown in figure 3f, data was represented as mean ± SD, n = 3 biologically independent samples. S12 Supplementary Fig. 18 Confocal images of tumor slices collected from 4T1 tumor-bearing mice after different treatments as indicated for 24 h and stained with CRT primary antibodies and corresponding Alexa 488 conjugated secondary antibodies. A representative image of three biologically independent samples from each group is shown. Supplementary Fig. 19 Semi-quantitative analysis of bioluminescence intensity of Luc-4T1 tumors before and after RFA treatment (50 W, 2 min) based on the in vivo bioluminescence imaging shown in Figure 4b.

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Supplementary Fig. 20 The micrographs of H&E-stained tumor slices collected at 24 h from 4T1 tumor-bearing mice after different treatments. A representative image of three biologically independent samples from each group is shown. Supplementary Fig. 21 Mobility free survival rates of animals bearing H22 tumors (a, n = 5), PDX tumors (b, n = 5) and VX2 tumors (c, n = 4) post different treatments as indicated. The mice and rabbits were euthanized when their tumor volumes were larger than 1000 and 5000 mm 3 , respectively. S14 Supplementary Fig. 22 (a) Individual tumor growth curves of both primary treated 4T1 tumors (up panel) and distant untreated tumors (down panel) of each group of mice with different treatments as indicated (n = 10 or 15). (b) Representative photographs of 3 mice randomly picked out from each group recorded at varying time intervals as indicated.
Supplementary Fig. 23 (a) Gating strategy to determine the percentage of CD11c + CD80 + CD86 + DC cells. (b) Representative flow cytometric analysis of the DC maturation in the drain lymph nodes adjacent to the primary tumors based on 5 biologically independent samples. S16 Supplementary Fig. 24 (a) Gating strategy to determine the percentages of CD3 + CD8 + T cells and CD3 + CD4 + T cells, respectively (up panel). Representative flow cytometric analysis of the frequency of CD3 + CD8 + T cells in the distant tumors based on 5 biologically independent samples. (b) The frequencies of CD3 + CD4 + T cells inside the distant tumors post various treatments as indicated, data was represented as mean ± SD, n = 5 biologically independent animals.