Article
Published: 11 November 2020

Inhibition of PCSK9 potentiates immune checkpoint therapy for cancer

Xinjian Liu^1,2^na1,
Xuhui Bao¹^na1,
Mengjie Hu¹,
Hanman Chang¹,
Meng Jiao¹,
Jin Cheng³,
Liyi Xie⁴,
Qian Huang³,
Fang Li¹ &
…
Chuan-Yuan Li ORCID: orcid.org/0000-0002-0418-6231^1,5,6

Nature volume 588, pages 693–698 (2020)Cite this article

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Abstract

Despite its success in achieving the long-term survival of 10–30% of treated individuals, immune therapy is still ineffective for most patients with cancer^1,2. Many efforts are therefore underway to identify new approaches that enhance such immune ‘checkpoint’ therapy^3,4,5 (so called because its aim is to block proteins that inhibit checkpoint signalling pathways in T cells, thereby freeing those immune cells to target cancer cells). Here we show that inhibiting PCSK9—a key protein in the regulation of cholesterol metabolism^6,7,8—can boost the response of tumours to immune checkpoint therapy, through a mechanism that is independent of PCSK9’s cholesterol-regulating functions. Deleting the PCSK9 gene in mouse cancer cells substantially attenuates or prevents their growth in mice in a manner that depends on cytotoxic T cells. It also enhances the efficacy of immune therapy that is targeted at the checkpoint protein PD1. Furthermore, clinically approved PCSK9-neutralizing antibodies synergize with anti-PD1 therapy in suppressing tumour growth in mouse models of cancer. Inhibiting PCSK9—either through genetic deletion or using PCSK9 antibodies—increases the expression of major histocompatibility protein class I (MHC I) proteins on the tumour cell surface, promoting robust intratumoral infiltration of cytotoxic T cells. Mechanistically, we find that PCSK9 can disrupt the recycling of MHC I to the cell surface by associating with it physically and promoting its relocation and degradation in the lysosome. Together, these results suggest that inhibiting PCSK9 is a promising way to enhance immune checkpoint therapy for cancer.

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Main

The importance of cholesterol metabolism in cancer immunotherapy was highlighted recently by the finding that inhibiting ACAT1—an enzyme that esterifies cholesterol—can potentiate the anti-tumour activities of CD8⁺ T cells by enhancing the clustering of T-cell antigen receptors⁹. It was also reported that lowering blood cholesterol levels could boost cancer immunotherapy based on adoptive T cells¹⁰. Cholesterol in the cellular membrane has also been shown to play key roles in the recycling of MHC I molecules¹¹. Given these findings, we hypothesized that PCSK9 might play a part in regulating anti-tumour immunity. PCSK9’s capacity to regulate cholesterol levels in the body lies in its ability to downregulate the cell-surface levels of low-density-lipoprotein (LDL) receptor (LDLR) by redirecting it to the lysosome for degradation, instead of recycling it back to the surface, through both extracellular and intracellular routes^{12,13,14,15,16}, thereby reducing cholesterol metabolism. In addition to LDLR, PCSK9 also regulates the cell-surface levels of other receptors such as the very low density lipoprotein receptor (VLDLR), apolipoprotein E receptor 2 (ApoeER2)¹⁷, LDL-related protein-1 (LRP-1)¹⁸, CD36¹⁹ and β-secretase 1 (BACE1)²⁰. The ability of PCSK9 to regulate a diverse group of cell-surface proteins hinted that it might also be able to influence additional membrane proteins that are important in anti-tumour immune responses. Targeting PCSK9 to treat cancer is also attractive because two neutralizing antibodies against it, evolocumab and alirocumab, have already been approved for human clinical use to lower cholesterol levels^21,22.

PCSK9 deficiency and tumour growth rate

To assess the effects of PCSK9 on tumour growth, we knocked out the Pcsk9 gene in four malignant mouse cancer cell lines (B16F10, 4T1, MC38 and CT26) using CRISPR–Cas9 technology (Extended Data Fig. 1a)^23,24. Knocking out PCSK9 did not alter the morphology or the in vitro growth rates of tumour cells (Extended Data Fig. 1b–d). When PCSK9-deficient cells were inoculated into syngeneic mouse hosts, however, their abilities to form tumours were significantly attenuated by comparison with vector controls (Fig. 1a–h). Preferential growth suppression of PCSK9-deficient cells was further confirmed through in vivo competition experiments with fluorescently labelled tumour cells (Extended Data Fig. 1e–g). Furthermore, reintroducing PCSK9 into PCSK9-knockout B16F10 cells rescued their tumorigenic abilities (Extended Data Fig. 2a–c), thereby ruling out the possibility that off-target CRISPR–Cas9 knockouts might be responsible for the observed delay in tumour growth.

**Fig. 1: PCSK9 depletion attenuates tumour growth in syngeneic mice.**

To determine the involvement of the immune system, we inoculated PCSK9-deficient and vector control 4T1 and B16F10 tumour cells into NCG mice deficient in T cells, B cells and natural killer cells. Our results showed that PCSK9 deficiency had no effect on tumour growth in NCG mice (Extended Data Fig. 2d–i). Furthermore, PCSK9 deficiency did not influence the ability of B16F10 cells to form tumours in Rag1-deficient mice, which do not have mature T or B cells (Extended Data Fig. 2j, k).

PCSK9 inhibition and immunotherapy

Because PCSK9 is known to regulate cholesterol levels by promoting the degradation of LDLR in the lysosome^13,14, we also examined the involvement of both of these proteins in regulating the tumorigenicity of mouse tumours. We generated LDLR-deficient B16F10 cells (Extended Data Fig. 3a) and evaluated the tumour-forming abilities of these cells in C57BL/6 mice; LDLR deficiency had no significant effect on tumour growth (Extended Data Fig. 3b, c). We further evaluated tumour growth from control and PCSK9-knockout B16F10 melanoma cells in syngeneic wild-type and LDLR^−/− mice that were fed a high-fat diet; cholesterol levels should be ten- to twenty-fold higher in the latter than in the former²⁵. Our results indicate that the attenuation in tumour growth resulting from PCSK9 deficiency was not affected by host LDLR status or cholesterol levels (Extended Data Fig. 3d, e).

To evaluate whether PCSK9 deficiency could synergize with immune checkpoint blockade therapy^1,26, we carried out tumour-growth-delay experiments using a mouse anti-PD1 immune checkpoint inhibitor in syngeneic mice inoculated with PCSK9-deficient B16F10, MC38, 4T1 or CT26 tumour cells. Anti-PD1 antibody synergized with PCSK9 deficiency in all four models (Fig. 2a–f and Extended Data Fig. 4a–f) in suppressing tumour growth.

**Fig. 2: Inhibition of PCSK9 overcomes tumour resistance to anti-PD1 therapy.**

We next examined whether the observed synergy between PCSK9 deficiency and anti-PD1 antibody treatment could be recapitulated by using evolocumab or alirocumab—two PCSK9-neutralizing antibodies that have been approved to treat hyperlipidaemia in humans^21,22. Both have been shown to be effective in lowering cholesterol in mice^27,28. Although administration of the anti-PCSK9 antibodies alone delayed the growth of MC38 tumours, their efficacies were enhanced significantly when combined with an anti-PD1 antibody, with long-term survival of some host mice (Fig. 2g–i). Thus, antibody-mediated PCSK9 neutralization enhances anti-PD1 therapy in mouse tumour models.

We next assessed whether anti-PCSK9 antibodies could work in tumours that had developed resistance to immune checkpoint therapy. We first developed an anti-PD1-resistant MC38R colon cancer model through three rounds of in vivo/in vitro selection (Extended Data Fig. 4g). Tumours established in syngeneic mice from the MC38R tumour cells were then treated with an anti-PD1 antibody and/or evolocumab. Treatment with evolocumab was effective either alone or in combination with anti-PD1 treatment for MC38R tumours (Extended Data Fig. 4h–j). Furthermore, evolocumab had no effect on tumour growth in PCSK9-deficient MC38 tumours (Extended Data Fig. 4k–m), indicating that tumour-cell-intrinsic PCSK9, rather than host PCSK9, is important for the anti-tumour efficacy of evolocumab.

In further experiments, we examined whether those mice that remain tumour-free after initial inoculation with tumour cells and treatment could resist a rechallenge with parental tumour cells. Lethal doses of wild-type tumour cells with an intact Pcsk9 gene were injected into those mice that remained tumour free after the initial challenge. A significant fraction of long-term survivors of 4T1 PCSK9-knockout tumours (Extended Data Fig. 5a–c), B16F10 PCSK9-knockout tumours (Extended Data Fig. 5d–f) and MC38 PCSK9-knockout tumours (Extended Data Fig. 5g–i) rejected the rechallenge with wild-type tumour cells, indicating an anti-tumour immune memory.

PCSK9 and lymphocyte infiltration

We next attempted to quantify immune effector cells in control and PCSK9-deficient B16F10 tumours by immunofluorescence staining and flow cytometry (see Extended Data Fig. 5j for the flow-cytometry gating strategy). Immunofluorescence staining indicated that PCSK9 depletion caused an overall increase in intratumoral infiltration of CD45⁺ leukocytes (Extended Data Fig. 6a) and CD8⁺ cells (Extended Data Fig. 6b). Of particular interest was that CD8⁺ cells remained mostly in the periphery in control tumours (Extended Data Fig. 6b, top panels), but moved into tumour-cell-rich areas in PCSK9-deficient B16F10 tumours (Extended Data Fig. 6b, bottom panels).

Flow-cytometry analyses confirmed significant increases in numbers of intratumoral CD8⁺ cytotoxic T cells (CTLs) (Fig. 3a), CD4⁺ T helper (T_H) cells (Fig. 3b), γδ T cells (Fig. 3c), and natural killer cells (Fig. 3d) in PCSK9-deficient tumours. By contrast, no significant increases in numbers of CD4⁺ Foxp3⁺ regulatory T (T_reg) cells were observed (Fig. 3e). Moreover, there were no increases in the numbers of CD4⁺ or CD8⁺ T cells in the spleens of host mice (Extended Data Fig. 6c). The ratios of CTLs to T_reg cells in the PCSK9-deficient tumours were significantly increased (Fig. 3f). Consistent with this, both the numbers and the percentages of interferon-γ⁺ (IFN-γ⁺) and granzyme B⁺ (GZMB⁺) CTLs also increased significantly in PCSK9-deficient tumours (Fig. 3g, h and Extended Data Fig. 6d), as did the intratumoral expression of IFNG and GZMB (assessed by quantitative reverse transcription with polymerase chain reaction, qRT–PCR; Extended Data Fig. 6e, f). On the other hand, measurement of T-cell exhaustion markers showed no significant changes (Extended Data Fig. 6g–i).

**Fig. 3: Depletion of PCSK9 enhances intratumoral T-cell infiltration.**

We next examined the effect of evolocumab on the tumour immune microenvironment in the 4T1 mouse breast cancer model. Evolocumab also showed clear anti-tumour efficacy in this model (Extended Data Fig. 6j–l). However, anti-PD1 therapy was ineffective, as reported before²⁹. When we analysed intratumoral CTLs, we found that both anti-PD1 and anti-PCSK9 antibodies boosted the numbers of CTLs inside tumours (Extended Data Fig. 6m). However, only the presence of evolocumab could boost the number of active IFN-γ⁺ CTLs (Extended Data Fig. 6n).

In order to determine the relative importance of different immune effector cells, we used a well established antibody-based approach³⁰ to deplete CD4⁺ T cells, CD8⁺ T cells or natural killer cells, in order to assess their relative importance in regulating the growth of PCSK9-deficient tumours. Our data indicate that depleting CD8⁺ T cells completely abolished the growth delay of PCSK9-deficient tumours (Fig. 3i, j). By contrast, depleting CD4⁺ T cells or natural killer cells had only marginal effects (Extended Data Fig. 7a–e).

To further characterize the effects of PCSK9 deficiency on intratumoral T cells, we carried out molecular analysis of the T-cell antigen receptor (TCR) repertoire. Our analysis suggests that total TCR counts (Fig. 3k) and the number of unique TCRs (Fig. 3l) were significantly increased in PCSK9-deficient tumours. These results suggest that both the number and the diversity of mature T cells were significantly elevated in PCSK9-deficient tumours. Further analysis showed that productive clonality—a measurement of the dominance of individual T-cell clones—was elevated in PCSK9-deficient tumours (Fig. 3m), indicating significant expansion and dominance of a subset of T-cell clones, in addition to an overall increase in the diversity of mature T cells. Closer examination revealed that the maximum dominance of individual T-cell clones in both control and PCSK9-deficient tumours was close to 20–30%, which suggests that a few T-cell clones accounted for 30% of the whole intratumoral T-cell population (Fig. 3n). Of interest is that the dominant clones in PCSK9-deficient tumours were different from those in control tumours (Fig. 3o).

We then determined the influence of PCSK9 deficiency on CTL-mediated killing of tumour cells by using the OT-1 transgenic mouse model³¹, with which we isolated T cells engineered to express TCRs specific for the chicken ovalbumin (OVA) antigen (SIINFEKL). We then evaluated the cytotoxic effects of these T cells against OVA-transduced, tdTomato-labelled vector control and PCSK9-deficient B16F10 melanoma cells in vitro. Our results indicate that PCSK9-deficient B16F10 cells were significantly more susceptible than control cells to killing by CTLs (Fig. 3p and Extended Data Fig. 7f). Consistent with our preclinical data, expression of PCSK9 messenger RNA correlated negatively with expression of the CTL marker CD8A in four human malignancies (Fig. 3q).

PCSK9 and MHC I regulation

We next focused on the molecular mechanism(s) involved in the enhanced CTL-mediated killing of PCSK9-deficient tumour cells. Because of the known roles of PCSK9 in regulating the levels of cell-surface proteins such as LDLR^17,32,33, we hypothesized that PCSK9 deficiency may influence antigen presentation on the surface of tumour cells. Indeed, we found that staining of H2-K^b MHC I molecules bound to SIINFEKL was significantly enhanced on the surface of IFN-γ-stimulated, PCSK9-deficient, B16F10 OVA cells compared with control B16F10 OVA cells (Fig. 4a and Extended Data Fig. 7g). Thus, PCSK9 has a strong influence on the presentation of peptide antigens by MHC I. We further examined the effect of PCSK9 knockout on H2^b MHC I alloantigen levels on the surface of B16F10 tumour cells grown in vivo. Our analysis indicated that the expression of MHC I on the tumour cell surface was significantly increased in PCSK9-deficient tumours when compared with controls (Fig. 4b, c). Similarly, PCSK9 deficiency also caused a significant increase in H2^d MHC I alloantigen levels in IFN-γ-treated 4T1 cells in vitro (Fig. 4d). By contrast, PCSK9 deficiency failed to show any effect on MHC II expression and had only a marginal effect on PD-L1 expression in B16F10 cells (Extended Data Fig. 7h, i). We further observed increased levels of human leukocyte antigen (HLA)-A2 in the human breast cancer line MDA-MB-231 following PCSK9 knockout (Fig. 4e and Extended Data Fig. 7j) or incubation with anti-PCSK9 antibodies (Extended Data Fig. 7k). Similarly, treatment of mouse 4T1 tumours with evolocumab also boosted MHC I levels on the surface of 4T1 cells (Extended Data Fig. 7l). On the other hand, incubating exogenous PCSK9 protein with PCSK9-deficient MDA-MB-231 cells caused a decrease in surface HLA-A2 levels (Fig. 4f).

**Fig. 4: PCSK9 promotes lysosome-mediated degradation of MHC I in tumour cells.**

We next overexpressed the MHC I protein H2-K1 in B16F10 cells (Extended Data Fig. 8a) and evaluated their tumour-forming abilities and response to anti-PD1 therapy. We found that H2-K1 expression significantly attenuated tumour growth alone or in combination with anti-PD1 antibody (Extended Data Fig. 8b, c). By contrast, genetic depletion of H2-K1 abrogated the tumour growth delay induced by PCSK9 inhibition (Extended Data Fig. 8d, e). Our results therefore establish H2-K1 as an essential downstream factor of PCSK9 in regulating tumour growth.

How does PCSK9 regulate cell-surface MHC I expression? Previously it was reported that cholesterol levels may influence MHC I recycling¹¹. Therefore, it is possible that PCSK9 could regulate MHC I indirectly through LDLR, the key cholesterol regulator that is also an established downstream target of PCSK9. In order to determine whether LDLR levels could regulate MHC I levels downstream of PCSK9, we generated B16F10 cells with LDLR knockdown alone or in combination with PCSK9 knockout (Extended Data Fig. 8f). We then showed that LDLR knockdown did not diminish the growth suppression caused by PCSK9 deficiency in B16F10 tumours (Extended Data Fig. 8g, h), nor did it have any influence on MHC I expression on the surface of B16F10 cells (Extended Data Fig. 8i). Furthermore, LDLR knockout did not affect the upregulation of surface MHC I expression induced by PCSK9 deficiency (Extended Data Fig. 8j).

Because PCSK9 can downregulate the LDLR protein by interacting with it physically and redirecting it to lysosomes for degradation^{12,13,14,15,16}, we next examined whether PCSK9 can similarly regulate surface levels of MHC I through a direct interaction. We first created recombinant mouse PCSK9 mutants with various internal deletions or truncations on the basis of the protein’s domain structure (Extended Data Fig. 9a). Each of those deleted PCSK9 genes was then co-transduced into 293T cells together with a full-length H2-K1 gene. Deletion of the M2 domain within the carboxy-terminal region of PCSK9 showed almost complete loss of binding to H2-K1, while deletions of the other two C-terminal domains (M1 and M3) and of the domain comprising amino acids 367–386, which is involved in LDLR binding³⁴, in the catalytic region also showed reduced H2-K1 binding (Fig. 4g, Extended Data Fig. 9b). On the other hand, deletion mapping of H2-K1 showed that absence of the α1 region (amino acids 66–100) and, in particular, of amino acids 68–70, which sits in the loop right before the helix structure of the α1 domain³⁵, completely abolished binding to PCSK9 (Extended Data Fig. 9c, d). To demonstrate the functional importance of the interacting domains in PCSK9 and H2-K1, we reintroduced wild-type or PCSK9 ΔM2 (PCSK9 with a deletion of the M2 region, amino acids 535–608) into PCSK9-knockout B16F10 cells. In tumour growth experiments, reintroduction of the wild-type PCSK9 abolished the tumour growth delay, while that of PCSK9 ΔM2 had no effect (Extended Data Fig. 9e, f). By comparison, reintroduction of wild-type H2-K1 attenuated the tumour-forming abilities of both H2-K1-deficient and PCSK9/H2-K1 double-knockout cells. On the other hand, reintroduction of the H2-K1 variant lacking amino acids 68–70 did not slow tumour growth (Extended Data Fig. 9g, h).

To understand how PCSK9 regulates the surface expression of MHC I, we carried out immunofluorescence co-staining of exogenously expressed H2-K1 and/or PCSK9 in B16F10 cells with PCSK9 knockout or PCSK9 overexpression. In PCSK9-overexpressing cells, more H2-K1 was localized in the lysosome and less in the plasma membrane (Fig. 4h, top panels). On the other hand, in PCSK9-knockout cells, H2-K1 staining indicated greater localization to the plasma membrane (Fig. 4h, lower panels). Western blot analysis of fractionated cellular lysates confirmed the immunofluorescence staining results. In the lysosome fraction, PCSK9 overexpression caused an increase in H2-K1 protein while PCSK9 knockout induced a decrease (Fig. 4i). By contrast, in the membrane fraction, PCSK9 overexpression reduced the relative abundance of the H2-K1 protein while PCSK9 knockout increased it (Fig. 4j).

We next used western blotting to analyse the functional significance of the physical association between PCSK9 and H2-K1 and the localization of H2-K1 to the lysosome. In the absence of de novo protein synthesis (following treatment with cycloheximide), HLA-ABC levels in PCSK9-knockout MDA-MB-231 cells declined more slowly by comparison with control cells (Fig. 4k). However, when the cells were exposed to bafilomycin to inhibit lysosome function, the levels of HLA-ABC increased substantially in control cells but did not change much in PCSK9-knockout cells (Fig. 4l), suggesting a key role for PCSK9 in regulating HLA-ABC levels through lysosome-mediated degradation. Our results thus suggest that PCSK9 downregulates MHC I surface levels in a manner similar to its negative regulation of LDLR by lysosome-mediated degradation. Consistent with these preclinical findings, individuals with high tumour PCSK9 mRNA expression had worse overall survival than those with low expression in nine different patient cohorts from The Cancer Genome Atlas (TCGA; Extended Data Fig. 9i).

Discussion

Our finding that PCSK9 has an important role in regulating cell-surface MHC I levels (summarized in Extended Data Fig. 10) and thereby influences intratumoral immune infiltration is mechanistically new and has great translational potential. It suggests that neutralizing PCSK9 might promote intratumoral infiltration by T cells and thus render tumours more responsive to immune checkpoint therapy. Previous studies have shown that the amount of active T cells correlates positively with the success of immune checkpoint blockade therapy^36,37. Our results, demonstrating the potent tumour-suppressing effect of combining anti-PD1 antibodies with either evolocumab or alirocumab, provide a compelling rationale for conducting future clinical trials in patients with cancer. Given the well known safety profiles of the anti-PCSK9 antibodies, these drugs might enhance immune checkpoint therapy without additional side effects.

Methods

No statistical methods were used to predetermine sample size. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment.

Cell lines

B16F10 mouse melanoma cells, CT26 mouse colon carcinoma cells, 4T1 mouse breast carcinoma cells and MDA-MB-231 human breast cancer cells were purchased from the Cell Culture Facility of Duke University School of Medicine. The identities of human cell lines were verified by the short tandem repeat (STR) method. 293T cells were purchased from the American Type Culture Collection (ATCC; Manassas, VA). MC38 mouse colon adenocarcinoma cells were purchased from Kerafast (Boston, MA). B16F10, CT26, 4T1, MC38 and MDA-MB-231 cells were all grown in Dulbecco’s modified Eagle medium (DMEM) (Sigma) with 10% fetal bovine serum (FBS), 100 units per millilitre of penicillin and 100 μg ml⁻¹ streptomycin. All cell lines were periodically tested for mycoplasma contamination using a universal mycoplasma detection kit (ATCC).

CRISPR–Cas9-mediated gene knockout

Knockout cells were generated with lentivirus-mediated CRISPR–Cas9 technology. Single guided RNA (sgRNA) sequences were designed using a public-domain online CRISPR design tool (chopchop.cbu.uib.no)³⁸. SgRNA sequences targeting mouse PCSK9 were as follows: 1, AGAACCACGAGTGGCCCCGA; 2, CGGCTATACCCACCGGCCAG; 3, CATGCTTCATGTCACAGAGT; 4, TCATTTGACGCTGTCTGGGG. SgRNA sequences targeting human PCSK9 were: 1, CAGATGGGGGTCTTACCGGG; 2,TCTTGGTGAGGTATCCCCGG. Sequences targeting mouse LDLR were: 1, ACAGTCGACATCCCCGTCGC; 2, CCGCGGATCTGATGCGTCGC. Sequences targeting mouse H2-K1 were: 1, CGAATCGCCGACAGGTGCGA; 2, CGAGATATGAGCCGCGGGCG. Double-stranded oligonucleotides encoding the sgRNA sequences were cloned into BsmB1 (Thermal Fisher Scientific)-digested plasmid LentiCRISPRv2 (deposited by F. Zhang of MIT to Addgene, Cambridge, MA)^24,39, which co-expresses Cas9 and sgRNA in the same vector. The sgRNA-encoding CRISPR lentivirus vectors were then produced using an established protocol from the Trono laboratory (https://www.epfl.ch/labs/tronolab/laboratory-of-virology-and-genetics/lentivectors-toolbox/). To generate the knockout cell lines, target cells were infected with sgRNA-encoding CRISPR lentivirus and cultured in DMEM with 10% FBS and selected in puromycin (1 μg ml⁻¹ for B16F10 and MDA-MB-231 cells, 5 μg ml⁻¹ for 4T1 cells, 6 μg ml⁻¹ for MC38 cells, and 8 μg ml⁻¹ for CT26 cells) for 7–10 days. They were then seeded into 96-well plates. Clones emerging from the plates were then expanded, and expression of target protein in infected cells was detected by western blot (for PCSK9) or flow cytometry (for H2-K1) to verify the knockdown. To generate PCSK9-knockout/LDLR-knockdown or PCSK9-knockout/H2-K1-knockdown B16F10 cell lines, we cloned mouse LDLR or H2-K1 sgRNAs into LentiCRISPRv2 vector incorporating the neomycin-resistance gene. PCSK9-knockout cells were infected with sgRNA-encoding CRISPR lentivirus and selected in G418 for ten days. Expression of H2-K1 and LDLR protein in mixed infected cells was then detected by western blot to verify the knockdown.

Colony formation in soft agar

To measure the ability of PCSK9-deficient tumour cells to grow in three dimensions, we carried out soft-agar assays according to an established protocol⁴⁰. Cells were seeded at a density of 10,000 cells per well in 6-well plates with soft agar. The colonies were fixed and stained with 0.005% crystal violet after three weeks in culture. The numbers of colonies per well were then counted. Two independent experiments were carried out.

Antibodies and related reagents

Antibodies and reagents were used for western blotting, immunofluorescence and immunoprecipitation. The antibodies, their source and dilution information are as follows. Fluorescein isothiocyanate (FITC)-bound anti-mouse CD45: clone 30-F11, catalogue number 103108, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. Pacific blue anti-mouse CD3ε: clone 145-2c11, catalogue number 100334, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. AF647-bound anti-mouse CD4: clone GK1.5, catalogue number 100424, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. Allophycocyanin (APC)/Fire750-bound anti-mouse CD8a: clone 53-6.7, catalogue number 100766, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. Phycoerythrin (PE)-bound anti-mouse NK1.1: clone PK136, catalogue number 108707, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. Phycoerythrin (PE)-bound anti-mouse Foxp3: clone MF-14, catalogue number 126403, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. APC-bound anti-mouse TCR γ/δ: clone GL3, catalogue number 118115, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE-bound anti-mouse GZMB: clone QA16A02, catalogue number 372207, 5 μl per 10⁶ cells in 100 μl dilution buffer, Biolegend. AF647-bound anti-mouse IFN-γ: clone XMG1.2, catalogue number 505816, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. FITC-bound anti-human HLA-A2: clone BB7.2, catalogue number 343322, 0.5 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. FITC-bound anti-mouse H-2K^b/D^b: clone 28-8-6, catalogue number 114605, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE-bound anti-mouse H-2K^b/D^b: clone 28-8-6, catalogue number 114608, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. FITC-bound anti-mouse H-2K^d/D^d: clone 34-1-2S, catalogue number 114706, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE/Cy7-bound anti-mouse H-2K^b bound to SIINFEKL: clone 25-D1.16, catalogue number 141607, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. AF647-bound anti-mouse PD1: clone 29F.1A12, catalogue number 135229, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE-bound anti-mouse TIGIT: clone 1G9, catalogue number 142103, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE-bound anti-mouse CTLA4: clone UC10-4B9, catalogue number 106305, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE-bound anti-mouse TNF-α: clone MP6-XT22, catalogue number 506305, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. APC-bound anti-mouse I-A/I-E: clone M5/114.15.2, catalogue number 107613, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE/Cy7-bound anti-mouse PD-L1: clone 10F.9G2, catalogue number 124313, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. TruStain FcX (anti-mouse CD16/32): clone 93, catalogue number 101319, 1 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. APC-bound anti-mouse TCRVβ5.1/5.2: clone MR9-4, catalogue number 139505, 0.25 μg per 10⁶ cells in 100 μl dilution buffer, Biolegend. PE/Cy7-bound anti-Cas9 monoclonal antibody: clone 6H4, catalogue number 25-6499-82, 0.06 μg per 10⁶ cells in 100 μl dilution buffer, ThermoFisher. Purified anti-mouse CD45: clone 30-F11, catalogue number 103101, immunofluorescence, 1:50 dilution, Biolegend. Purified rat anti-mouse CD8a: clone 53-6.7, catalogue number 550281, immunofluorescence, 1:50 dilution, BD. Mouse/rat anti-PCSK9 antibody: catalogue number AF3985, western blotting, 1 μg ml⁻¹ dilution, R&D Systems. Mouse/human/rat anti-PCSK9 antibody: catalogue number 55206-1-AP, western blotting, 1:1,000 dilution, Proteintech. Mouse anti-LDLR antibody: catalogue number AF2255, western blotting, 0.1 μg ml⁻¹ dilution, R&D. Anti-HLA class 1 ABC antibody: catalogue number 15240-1-AP, western blotting, 1:10,000 dilution, Proteintech. Anti-FLAG antibody: catalogue number F1804, immunoprecipitation, 2.5 μg ml⁻¹ dilution; western blotting, 0.5 μg ml⁻¹ dilution; Sigma. Anti-HA antibody: clone C29F4, catalogue number 3724T, immunoprecipitation, 1:50; western blotting, 1:1,000, Cell signaling Technology. Anti-LAMP2 antibody: clone 2D3B9, catalogue number 66301-1-lg, western blotting, 1:1,000, Proteintech. Pan-cadherin: catalogue number NB200-592, western blotting, 1:200, Novus Biologicals. Anti-GAPDH antibody: catalogue number 60004-1-Ig, western blotting, 1:20,000 dilution, Proteintech. Anti-actin monoclonal antibody (ACTN05 (C4): clone ACTN05 (C4), catalogue number MA5-11869, western blotting, 0.5 μg ml⁻¹ dilution, ThermoFisher.

Western blot analysis

Cells were washed with cold phosphate-buffered saline (PBS), then lysed in radioimmunoprecipitation assay (RIPA) buffer supplemented with protease inhibitors (Sigma). Equal amounts of lysates were separated by SDS–PAGE and transferred to polyvinyldifluoride (PVDF) membrane. Proteins were then probed with specific antibodies followed by secondary antibodies conjugated with horseradish peroxidase (HRP). The HRP signal was developed by electrochemiluminescence (ECL). Quantification of interested proteins was analysed using Image J (National Institutes of Health, NIH). Original uncropped images highlighting the cropped areas for Fig. 4g, i–l and Extended Data Figs. 1a, 2a, 3a, 7j, 8a, f, 9b–d are in Supplementary Fig. 1.

Molecular cloning

A series of mouse PCSK9 full-length and deletion mutants were generated by polymerase chain reaction (PCR) from complementary DNA derived from the B16F10 cells. These mutants were then cloned into the pLEX-MCS recombinant lentiviral vector (Thermo-Fisher) to be used for gene expression. An HA tag was attached to the 3′-end of different PCSK9 mutants. The same was done for mouse H2-K1, using a FLAG tag. The PCR primers used to clone mouse Pcsk9 are as follows: SpeI–mPCSK9 forward, 5′-CCGACTCTACTAGAGGATCCACTAGTGCCACCatgggcacccactgctctgc-3′; mPCSK9–NotI-reverse, 5′-caaaggcctcctgggttcagGCGGCCGCTTATCCGTATGATGTTCCTG-3′; mPCSK9-184–NotI reverse (Δ184–693), 5′-atggaagcagccaggtggagGCGGCCGCTTATCCGTATGATGTTCCTG-3′; mPCSK9-184–NotI reverse (Δ453–693), 5′-cactgccccccagcacccatGCGGCCGCTTATCCGTATGATGTTCCTG-3′; mPCSK9–(ΔM1 456–534) forward, 5′-gttgtggatgctgcagttggcgcctgtctcatgggtgctggggggC-3′; mPCSK9–(ΔM2 535–608) forward, 5′-ctccttgattttgcattccagacggggaaccaggcagcatctcgcg-3′; mPCSK9– (ΔM3 609–694) reverse NotI, 5′-CctgctgccatgccccagggGCGGCCGCTTATCCGTATGATGTTCCTG-3′.

The PCR primers used to clone H2-K1 were: H2-K1–FLAG forward, 5′-CCGACTCTACTAGAGGATCCACTAGTGCCACCatggtaccgtgcacgctgctcct-3′; H2-K1–FLAG reverse, 5′-AGAGGGGCGACCGGTGGCCAGACGCGTtcaCTTGTCGTCATCGTCTTTGTAGTCCTCGAGcgctagagaatgagggtcat-3′; H2K1-67 reverse, 5′-cggctcatatctcggattctccgc-3′; H2K1–(Δ66–100) forward 5′-gcggagaatccgagatatgagccgaccctgctcggctactacaa-3′; H2K1–(Δ68–70) forward 5′- gcggagaatccgagatatgagccgtggatggagcaggaggggcccgagtat-3′.

Ectopic gene expression

PCR primers with the sequences listed in the previous section were used to obtain full-length and various deleted mouse PCSK9 DNA fragments with HA tags, and full-length and deleted H2-K1 fragments with FLAG tags. DNA fragments encoding PCSK9–HA were then cloned into the pLEX-MCS vector, and H2-K1–FLAG was cloned into the pLEX-MCS vector, using a Gibson assembly kit according to the manufacturer’s instructions (New England Biolabs). Vectors encoding the genes were co-transfected into 293T cells for 24 h, and the cells were harvested for immunoprecipitation and western analyses.

Tumour growth in mice

All animal experiments were approved by the Duke University Institutional Animal Use and Care Committee (IACUC). C57BL/6J, Balb/c, Rag1-knockout, LDLR-knockout and OT-1 transgenic mice (in the C57BL/6J background) were purchased from The Jackson Laboratory (Bar Harbour, ME). Non-obese diabetic (NOD) CRISPR PrkdcIl2rGamma (NCG) triple-immunodeficient mice were purchased from Charles River Laboratory (Wilmington, MA). Female LDLR-knockout mice were fed a 60% high-fat diet (Research Diets; New Brunswick, NJ). Mice were housed at an ambient temperature of 72 °F, with a humidity of 30–70%, and a light cycle of 12 h on/12 h off set from 7am to 7pm. Before tumour cells were injected, age-matched 6–8-week-old mice were shaved at the flank. Tumour cells were then injected into the shaved flank subcutaneously, using 1.0 × 10⁵ CRISPR–Cas9-modified control or target-gene-knockout tumour cells. In experiments involving PCSK9-neutralizing antibodies, 6–8-week-old syngeneic female C57BL/6J or Balb/c mice were inoculated subcutaneously with MC38 cells (2.5 × 10⁵ per mouse) or 4T1 cells (1 × 10⁵ per mouse), respectively. About 200 μg of anti-PCSK9 monoclonal antibodies (evolocumab from Amgen, or alirocumab from Sanofi/Regeneron) or 200 μg human IgG2 isotype control (BioXcell) were injected (intraperitoneally) on days 3, 5, 8 and 11. In addition, 100 μg of anti-PD1 (clone RMP1-14, BioXcell) antibody were injected on days 5 (and 8 in some mice) in combination with the anti-PCSK9 antibodies. At least five mice per treatment group were included. No randomization or blinding was used in our tumour growth delay experiments. Mice were monitored for tumour growth every two days afterwards. Tumour size was measured using a caliper and calculated using the formula volume = (length)(width)²/2. The endpoint was defined as the time at which a progressively growing tumour reached 1.5 cm in its longest dimension or 2,000 mm³ in diameter. Mice were also euthanized when they experienced open skin lesions, lost more than 15% of their total body weight, or failed to thrive.

Lymphocyte depletion

To evaluate the role of specific subsets of immune effector cells in mice, we depleted CD4⁺ T cells, CD8⁺ T cells or natural killer cells using 150 μg of intraperitoneally injected anti-CD4 antibody (BioXcell, clone GK1.5), 100 μg of anti-CD8β antibody (BioXcell, clone 53-5.8) or 200 μg of anti-NK1.1 antibody (BioXcell, clone PK136), respectively, on days −3, 0, 3 and 8. Equal amounts of IgG isotype antibodies (BioXcell) were injected as a control.

In vivo competition assay

B16F10 cells stably expressing enhanced green fluorescent protein (EGFP) or tdTomato were infected with PCSK9-targeting sgRNA or control lentiviral vectors, respectively, and selected with 1 μg ml⁻¹ puromycin for 10 days. Subsequently, about 5 × 10⁴ PCSK9-knockout cells (EGFP-expressing) and 5 × 10⁴ control cells (tdTomato-expressing) were mixed and inoculated subcutaneously to C57BL/6J female mice. Tumours were excised 12–14 days after inoculation. They were then minced and incubated in DNase I (50 μg ml⁻¹, Sigma) and collagenase P (2 mg ml⁻¹, Sigma) for 20 min at 37 °C. The dissociated tumour cells were passed through a 70-μm cell strainer (BD). Tumour cells were washed and resuspended in ice-cold PBS with 2% FBS. The ratios of GFP and tdTomato tumour cells were analysed using the BD Canto II flow-cytometry system (Flow Cytometry Shared Facility, Duke University School of Medicine).

Analysis of cell-surface MHC I expression

For in vitro experiments, mouse B16F10 and 4T1 cells were treated with IFN-γ (B16F10 cells, 1 ng ml⁻¹; 4T1 cells, 4 ng ml⁻¹) for 12 h to stimulate MHC I expression and stained with FITC-labelled anti-H-2K^b/D^b antibodies or FITC-labelled anti-H-2K^d/D^d antibodies, respectively, for 20 min on ice. Human MDA-MB-231 cells were treated with 1 mg ml⁻¹ evolocumab or alirocumab or human IgG2 isotype control (BioXcell) for 72 h, or 1 μg ml⁻¹ recombinant PCSK9 protein (Prospec-Tany TechoGene Ltd) or BSA (Sigma) for 6 h, and stained with an FITC-labelled HLA-ABC antibody for 30 min on ice. After washing with PBS plus 2% FBS, the surface expression of MHC I was analysed using a BD Canto II flow cytometer (Flow Cytometry Shared Facility, Duke University School of Medicine). For in vivo experiments, vector control or PCSK9-deficient tumour cells transduced with exogenous markers (EGFP/tdTomato/Cas9) were inoculated separately into mice, and tumours were harvested 10–12 days later. Tumour tissues were then disaggregated and processed as described above and subjected to flow-cytometry analysis using an anti-H-2K^b/D^b antibody.

Analysis of tumour-infiltrating lymphocytes

About 1 × 10⁵ control and PCSK9-knockout or control cells were inoculated subcutaneously into C57BL/6 mice. Tumours were collected on day 12 after inoculation, weighed, and mechanically minced and incubated in DNase I (50 μg ml⁻¹, Sigma) and collagenase P (2 mg ml⁻¹, Sigma) for 20 min at 37 °C. The dissociated cells were passed through a 70-μm cell strainer (BD). The filtered cells were then blocked with an anti-CD16/32 antibody and stained with indicated surface antibodies for 20 min on ice. Dead cells were marked using live/dead fixable Aqua dye (Thermo Fisher Scientific). Intracellular antibodies were added after fixation and permeabilization as per the manufacturer’s instructions. The anti-mouse fluorochrome-conjugated antibodies are listed above in the ‘Antibodies and related reagents’ section. A BD Canto II flow cytometer (Flow Cytometry Shared Facility, Duke University School of Medicine) was used for analysis. Cell profiles were first recorded using FACS DIVA software (version 8.01), and data were then analysed using FlowJo (version 10).

qRT–PCR of CTL-related gene expression

Total RNA was extracted from CRISPR–Cas9 control or PCSK9-knockout B16F10 tumours (around 200–300 mm³ in volume) from tumour-bearing mice using the RNeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. RNA was subjected to cDNA synthesis with random hexamer primers using Superscript II reverse transcriptase (Invitrogen). Real-time quantitative RT–PCR (qRT–PCR) was performed using a QuantiTest SYBR Green PCR master mix kit (Qiagen). Primers used were: mouse GZMB, forward 5′-CCACTCTCGACCCTACATGG-3′, reverse 5′-GGCCCCCAAAGTGACATTTATT-3′; mouse IFNG, forward, 5′-ATGAACGCTACACACTGCATC-3′, reverse, 5′-CCATCCTTTTGCCAGTTCCTC-3′.

TCRs from tumour-infiltrating lymphocytes

Control and PCSK9-knockout B16F10 cells were inoculated as described above; on day 10 after inoculation, they were collected for genomic DNA extraction. Genomic DNA was extracted using a DNeasy blood and tissue kit (Qiagen) and submitted to Adaptive Biotechnologies for mouse TCR-β CDR3 survey sequencing. About 2.6 μg of initial DNA were used as inputs for PCR reactions. Data were analysed using ImmunoSEQ Analyzer 3.0, an Adaptive Biotechnologies online analysis platform.

OT-1 T cell culture

OT-1 CD8⁺ T cells expressing a transgene encoding a TCR that specifically recognizes SIINFEKL peptide bound to mouse H-2K^b were harvested from spleens of OT-1 C57BL/6 mice³¹. Activated OT-1 T cells were generated by incubating 5 × 10⁶ OT-1 SIINFEKL-pulsed mouse splenocytes per millilitre in vitro for 5–7 days in the presence of mouse recombinant interleukin-2^41,42. Briefly, an OT-1 mouse spleen was harvested and homogenized using aseptic techniques. The released cells were pelleted and resuspended in 3 ml of ACK buffer (0.15 M NH₄Cl, 1 mM KHCO₃ and 0.1 mM EDTA) for 2 min to lyse red blood cells at room temperature. The splenocytes were then pelleted, washed, and resuspended at 5 × 10⁶ cells per millilitre in complete growth medium (RPMI1640 Sigma-Aldrich) with 10% FBS (Corning), 1× penicillin–streptomycin (ThermoFisher Scientific), 1× sodium pyruvate (ThermoFisher Scientific), and 1× 2-mercaptoethanol (ThermoFisher Scientific) containing 0.75 μg ml⁻¹ SIINFEKL peptide (GenScript), and incubated at 37 °C in a 95% air/5% CO₂ humidified environment. Mouse recombinant interleukin-2 (ThermoFisher Scientific) was added on days 3 and 5 at 30 U ml⁻¹ with fresh complete growth medium. On day 7, the cells were harvested for assays. The specificity was determined by flow-cytometry analysis using APC/Fire750-labelled anti-mouse CD8 and APC-labelled anti-mouse TCRVβ5.1/5.2 antibodies (BioLegend).

Tumour-cell/T-cell co-culture analysis

B16F10 control–Td (expressing tdTomato fluorescent protein), B16F10 PCSK9-knockout–Td, B16F10 control–OVA–Td (expressing ovalbumin) and B16F10 PCSK9-knockout–OVA–Td cells were first stimulated by incubation with mouse recombinant IFN-γ at 1 ng ml⁻¹ for 12 h. The stimulated tumour cells were then cultured with OVA-specific T cells at a 1:1 ratio or without OVA-specific T cells in T-cell complete growth medium with mouse recombinant interleukin-2 (30 U ml⁻¹) for 24 h. Subsequently, tdTomato fluorescence was captured with a Zeiss Axio Observer.Z1 fluorescence microscope imaging station using ZEN imaging software (2012, blue edition, Carl Zeiss Microscopy GmbH). NIH ImageJ (version 1.52h) was used to count tdTomato-expressing tumour cells.

Cell fractionation and MHC I quantification

To investigate the distribution of MHC I in the lysosome or the plasma membrane, we used 5 × 10⁷ H2-K1–FLAG-transduced PCSK9-overexpress-ing or PCSK9-knockout B16F10 cells to isolate lysosome and membrane fractions. For lysosome isolation, we used a density gradient ultracentrifugation method according to the manufacturer’s instructions (lysosome enrichment kit, ThermoFisher Scientific). The membrane fraction was separated using membrane-separation buffer A (50 mM Tris-HCl, pH 7.5, 450 mM NaCl, 1.5 mM MgCl₂, 0.2 mM EDTA, 0.1 mM EGTA, 1 mM dithiothreitol (DTT, ThermoFisher Scientific) and buffer B (buffer A plus 1% NP40 and 0.1% SDS). MHC I expression in lysosome and membrane fractions was detected by western blotting using a mouse anti-FLAG antibody. Mouse anti-LAMP2 and rabbit anti-pan-cadherin were used as markers of lysosomes and membrane, respectively.

Immunofluorescence and immunohistochemistry

For immunofluorescence analysis, tumours from mice were fixed in 10% neutral-buffered formalin, embedded into paraffin, sectioned and then mounted onto slices. They were then stained by standard procedures using antibodies against mouse CD45 or CD8a (see the ‘Antibodies and related reagents’ section above). For lysosome co-localization experiments, PCSK9-overexpressing or PCSK9-knockout B16F10 cells were incubated with Lyso-Tracker (deep red, Thermo Fisher Scientific) at 37 °C for 20 min and then washed twice with Hanks’ balanced salt solution (HBSS). Cells were stained with 5 μg ml⁻¹ fluorescent conjugated wheat germ agglutinin (CF488 WGA) at 37 °C for 10 min, which selectively binds to N-acetyglucosamine and sialic acid residues to indicate the plasma membrane. Cells were then washed twice with PBS, fixed with 4% paraformaldehyde at room temperature for 15 min, and permeabilized with blocking buffer (1% BSA, 5% donkey serum and 0.1% digitonin) at room temperature for 30 min. The cells were incubated first with anti-FLAG primary antibody overnight at 4 °C, and then with fluorescent-labelled secondary antibodies for 1 h at room temperature. After washing with PBS, the stained slices were mounted with mounting medium (Vector Laboratories) containing DAPI. Images were captured by use of confocal microscopy.

Analysis of PCSK9 and H2-K1 interaction

293T cells were transduced with HA-tagged PCSK9 and FLAG-tagged H2-K1 constructs, cultured for about 24 h and then processed for co-immunoprecipitation analysis. Cultured cells in 10-cm Petri dishes were washed twice with ice-cold PBS and lysed with 500 μl immunoprecipitation lysis buffer (150 mM NaCl, 50 mM Tris and 0.1% NP-40) supplemented with protease inhibitors (Sigma) on ice. Cell lysates were transferred to 1.7 ml Eppendorf tubes and end-to-end rotated for 15 min at 4 °C. Protein concentration in lysates was measured using the Bio-Rad protein assay. For immunoprecipitation of HA-tagged PCSK9 protein, 500 μl of cell lysates were incubated with 3 μl anti-HA antibody (Cell Signaling technology) on a rotator at 4 °C overnight. Lysates with anti-HA antibodies were then incubated with 20 μl protein A/G agarose beads (Santa Cruz Biotechnology) for 2 h at 4 °C. After washing with immunoprecipitation lysis buffer three times, the pull-down complex was boiled in 2× SDS loading buffer for SDS–PAGE and western blot analysis.

Cycloheximide chase assay

To determine PCSK9’s effects on lysosomal degradation of the MHC I protein, vector control or PCSK9-knockout MDA-MB-231 cells were treated with 20 μg ml⁻¹ cycloheximide (CHX, Sigma) to inhibit protein biosynthesis for 1 h, 4 h, 8 h, 18 h or 24 h. For lysosome inhibition, MDA-MB-231 cells were treated with 20 nM bafilomycin A1 (Baf A1, Sigma) for 1 h, 4 h, 8 h, 18 h or 24 h. The cells were then harvested and MHC I proteins were detected by western blotting using anti-HLA-ABC antibodies.

Statistical analysis

Statistical analysis was performed using GraphPad Prism 6 software; P-values of less than 0.05 were considered statistically significant. Two-way ANOVA was used for multiple comparisons in tumour growth delay experiments. Log-rank tests were used for mouse survival analyses. In other experiments, comparisons between two groups were made with unpaired two-sided Student’s t-tests. The Gene Expression across Normal and Tumour tissue database (GENT)⁴³ was used to analyse the relationship between PCSK9 and CD8A in indicated patient cohorts. Data on PCSK9 gene expression and patient survival were obtained from cBioportal^44,45. In particular, we used The Cancer Genome Atlas (TCGA) data sets. Overall survivals of PCSK9 high and low groups were evaluated using log-rank tests; P-values of less than 0.05 were considered statistically significant.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this paper.

Data availability

PCSK9 and CD8A mRNA expression data from various human cancers were downloaded from the GENT (http://gent2.appex.kr/gent2/) database⁴³. PCSK9 mRNA expression and overall survival data were from TCGA data sets included in cBioportal^44,45 (https://www.cbioportal.org/) in November 2018. Western blot source data are provided in Supplementary Fig. 1. Source data for the quantitative graphs are provided for Figs. 1–4 and Extended Data Figs. 1–9. Other data in support of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

We thank J. M. Cook and colleagues at the Flow Cytometry Facility of Duke University School of Medicine for their assistance. We also thank the Duke University Light Microscopy Core Facility for professional help with confocal microscopy. We thank I. Li for proofreading our manuscript. We also thank S. Coffman of MedMedia Solutions for help with illustrations. C.-Y.L. is supported by US National Institutes of Health (NIH) grants ES024015, CA208852 and CA216876, and by a Cancer Center Support Grant (CCSG, CA014236) to Duke University. X.L. is supported by Guangdong Basic and Applied Basic Research Foundation grant 2020B1515020054 and Shenzhen Science and Technology Program grant JCYJ20190807154813511.

Author information

These authors contributed equally: Xinjian Liu, Xuhui Bao

Authors and Affiliations

Department of Dermatology, Duke University Medical Center, Durham, NC, USA
Xinjian Liu, Xuhui Bao, Mengjie Hu, Hanman Chang, Meng Jiao, Fang Li & Chuan-Yuan Li
Department of Biochemistry, Molecular Cancer Research Center, School of Medicine, Sun Yat-sen University, Shenzhen, Guangdong, China
Xinjian Liu
Molecular Diagnostic Laboratory of Cancer Center, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
Jin Cheng & Qian Huang
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
Liyi Xie
Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC, USA
Chuan-Yuan Li
Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA
Chuan-Yuan Li

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Xinjian Liu
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Xuhui Bao
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Hanman Chang
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Meng Jiao
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Jin Cheng
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Contributions

X.L., X.B. and C.-Y.L. designed the study. X.L., X.B. and H.C. carried out CRISPR–Cas9-mediated gene knockouts in tumour cells. X.L., X.B. and H.C. performed western blot analyses. X.L. generated PCSK9 and H2-K1 mutants and carried out immunoprecipitation/western blot experiments. X.L., X.B. and M.H. carried out mouse tumour-growth experiments. X.L. and X.B. characterized tumour cells in vitro and in vivo and intratumoral lymphocytes in vivo using flow cytometry. X.B. maintained OVA-specific T-cell culture, performed CTL assays and analysed the results, X.B., L.X. and X.L. analysed TCGA data for PCSK9 expression and its relationship to the expression of CD8A and prognosis of patients with cancer. M.H., M.J., J.C. and Q. H. carried out immunofluorescence and immunohistochemistry analyses. F.L. advised on CRISPR knockouts and provided material support. X.L., X.B. and C.L. wrote the manuscript with help from all co-authors. C.-Y.L. provided funding and study supervision.

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Correspondence to Chuan-Yuan Li.

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X.L. and C.-Y.L. are inventors on a patent application filed by Duke University that covers the use of anti-PCSK9 antibodies in cancer immunotherapy. The other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 CRISPR–Cas9-mediated knockout of PCSK9 and its effect on tumour-cell growth in vitro and in vivo.

a, Western blot analysis of the expression of PCSK9 in murine tumour lines (B16F10, 4T1, MC38 and CT26) with and without PCSK9 knockout (PCSK9KO). GAPDH was used as a protein loading control. The analysis was done twice with biologically independent samples. αGAPDH, anti-GAPDH antibody; αPCSK9, anti-PCSK9 antibody. b, Cell growth of vector control or PCSK9KO B16F10 tumour cells. Results (means ± s.e.m.) are from five biologically independent samples; P-values were calculated by unpaired two-sided t-test. c, Soft agar analysis of the colony-formation ability of B16F10 tumour cells transduced with vector control or PCSK9 sgRNA. d, Quantitative representation of soft agar formation in c. n = 4 biologically independent samples, showing means ± s.e.m; P-values calculated by unpaired two-sided t-test. e, Details of the in vivo competition assay. f, Change in ratios of mixed control–tdTomato and PCSK9KO–EGFP B16F10 cells after 12 days of growth in vivo (subcutaneously) in C57BL/6 mice, as determined by flow cytometry. g, Quantitative representation of the flow analysis in f, showing means ± s.e.m. n = 2 and 4 biologically independent tumour samples for in vitro and in vivo groups, respectively. P-values determined by unpaired two-sided t-test.

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Extended Data Fig. 2 Effect of PCSK9 re-expression and the host immune system on tumour formation by PCSK9-knockout cells.

a, Western blot analysis of the expression of exogenously transduced, HA-tagged PCSK9 in PCSK9KO B16F10 cells. The analysis was done once. b, c. Tumour formation from B16F10 PCSK9KO cells transduced with either vector control or PCSK9 (b), and Kaplan–Meier survival curves of host mice (c). About 2 × 10⁵ tumour cells were injected subcutaneously into C57BL/6 mice and observed for tumour formation. n = 5 tumours per group. Error bars show means ± s.e.m.; P-values were determined by two-way ANOVA in b and log-rank test in c. d–i, Growth rate (d, g), host survival (e, h) and endpoint tumour weight (f, i) of vector control and PCSK9KO 4T1 (d–f) and B16F10 (g–i) tumours. In each case, about 1 × 10⁵ tumour cells were injected subcutaneously and observed for tumour formation in NCG mice. n = 6 mice for d, e, g, h; and n = 5 tumours for f, i. Error bars in d, f, g, i represent means ± s.e.m.; ns, not significant, as determined by two-way ANOVA (d, g), log-rank test (e, h), or unpaired two- sided t-test (f, i). j, k, Tumour growth from vector control and PCSK9KO B16F10 cells in Rag1^−/− C57BL/6 mice (j) and Kaplan–Meier survival curve of tumour-bearing host mice (k). About 1 × 10⁵ vector control or PCSK9KO B16F10 tumour cells were injected into Rag1^−/− C57BL/6 mice and observed for tumour formation. n = 5 tumours per group. Error bars in j show means ± s.e.m. P-values were calculated by two-way ANOVA in j and by log-rank test in k.

Source data

Extended Data Fig. 3 The influence of tumour or host cell LDLR and host cholesterol levels on tumour growth from control or PCSK9KO tumour cells in immunocompetent hosts.

a, Western blot analysis of CRISPR–Cas9-mediated knockdown (KD) of LDLR in B16F10 cells. The analysis was done once. b, Tumour growth from vector control and LDLR KD B16F10 cells in C57BL/6 mice. n = 5 tumours per group. Error bars show means ± s.e.m. P-values were calculated by two-way ANOVA. c, Kaplan–Meier survival curve of mice (from b) bearing control and LDLR KD B16F10 tumours. n = 5 mice per group. P-values calculated by log-rank test. d, Tumour growth from vector control and PCSK9-knockout B16F10 cells in wild-type (C57) and LDLR^−/− mice fed on a high-fat diet. n = 12, 12, 5 and 5 tumours in, respectively, wild-type mice inoculated with control or PCSK9KO tumour cells, and in LDLR^−/− mice inoculated with control and PCSK9KO tumour cells. Error bars show means ± s.e.m. P-values were calculated by two-way ANOVA with multiple comparisons. e, Kaplan–Meier survival curve for wild-type and LDLR^−/− mice (from d) bearing vector control and PCSK9-knockout tumours. P-values were calculated by log-rank test.

Source data

Extended Data Fig. 4 Additional data on anti-PD1 treatment in murine tumours.

a, Treatment schedule for PCSK9KO 4T1 cells. Balb/c mice were implanted subcutaneously with PCSK9KO 4T1 tumour cells, treated with an anti-PD1 antibody at the indicated times, and observed for tumour formation. Animals that were implanted with PCSK9KO 4T1 tumour cells but did not form visible tumours by day 9 after inoculation were excluded from treatment with anti-PD1 antibodies. b, Tumour-growth delay in mice bearing PCSK9KO 4T1 tumours with or without anti-PD1 treatment. n = 5 tumours per group. Error bars show means ± s.e.m. P-values were calculated by two-way ANOVA. c, Kaplan–Meier survival curves for tumour-bearing mice from b. P-values were calculated by log-rank test. d, Treatment schedule for PCSK9KO CT26 tumours. Balb/c mice were implanted subcutaneously with PCSK9KO CT26 tumour cells, treated with an anti-PD1 antibody at the indicated times, and observed for tumour formation. e, Tumour-growth delay in mice bearing PCSK9KO CT26 tumours with or without anti-PD1 treatment. n = 5 tumours per group. Error bars show means ± s.e.m. P-values were determined by two-way ANOVA. f, Kaplan–Meier survival curves for tumour-bearing mice from e. Error bars show means ± s.e.m. P-values were determined by log-rank test. g, A scheme to develop anti-PD1-resistant MC38R tumour cells. h, Scheme for treating anti-PD1-resistant MC38R tumours with evolocumab and an anti-PD1 antibody. i, Tumour growth kinetics from anti-PD1-resistant MC38R tumours treated with anti-PD1 antibody and/or evolocumab. n = 5 tumours per group. Error bars show means ± s.e.m. P-values were determined by two-way ANOVA. j, Kaplan–Meier survival curve for mice bearing MC38R tumours from i. P-values were determined by log-rank test. k, Treatment schedule for PCSK9KO MC38 tumours. l, m, Tumour growth delay (l) and host mouse survival (m) among isotype (iso)- or evolocumab-treated mice bearing MC38-PCSK9KO tumours. n = 5 tumours per group. P-values were calculated by two-way ANOVA test in l and log-rank test in m.

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Extended Data Fig. 5 Rechallenge of mice that were tumour free after initial tumour inoculation, and gating strategy for intratumoral immune effector cells.

a–c, Treatment scheme (a), tumour growth (b) and survival of host mice (c) after rechallenge with wild-type 4T1 tumour cells in Balb/c mice that remained tumour-free 43 days after initial challenge with PCSK9-knockout 4T1 cells. The control group consisted of tumour-naive Balb/c mice challenged with wild-type 4T1 cells. n = 5 and 12 mice for naive and rechallenged groups, respectively. Error bars in b show means ± s.e.m. P-values in b, c were calculated by two-way ANOVA test and log-rank test, respectively. d–f, Treatment scheme (d), tumour growth (e) and survival of host mice (f) after rechallenge with wild-type B16F10 tumour cells in C57BL/6 mice that remained tumour-free 26 days after initial challenge with PCSK9-knockout B16F10 cells and treatment with anti-PD1 antibody. The control group consisted of tumour-naive C57BL/6 mice challenged with wild-type B16F10 cells. n = 5 and 13 mice for tumour-naive and rechallenge groups, respectively. Error bars in e show means ± s.e.m. P-values in e, f were calculated by two-way ANOVA and log-rank test, respectively. g–i, Treatment scheme (g), tumour growth (h) and survival of host mice (i) after rechallenge with parental MC38 tumour cells in C57BL/6 mice that remained tumour-free 34 days after initial challenge with PCSK9-knockout MC38 cells and treatment with anti-PD1 antibody. The control group consisted of tumour-naive C57BL/6 mice challenged with wild-type MC38 cells. n = 5 mice per group. Error bars in h show means ± s.e.m. P-values were calculated by two-way ANOVA (h) and log-rank test (i). j, Representative flow-cytometry gating strategy for quantifying the numbers of various immune effector cell subsets in murine tumours.

Extended Data Fig. 6 Additional data on the characterization of lymphocyte infiltration into murine tumours.

a, Immunofluorescence staining (left) and quantitative estimates (right) of CD45⁺ leukocytes in control and PCSK9KO tumours grown in syngeneic C57BL/6 mice. Scale bar, 50 μm; n = 3 biologically independent samples; four fluorescent fields for each of the three samples were counted. Error bars show means ± s.e.m.; P-values were calculated using unpaired two-sided t-tests. b, Immunofluorescence staining (left) and quantitative estimates (right) of CD8a⁺ cells in control and PCSK9KO B16F10 tumours. Scale bar, 20 μm. n = 3 biologically independent samples; four fluorescent fields for each of the three samples were counted; error bars show means ± s.e.m.; P-values were calculated using unpaired two-sided t-tests. c, Quantitative estimates of CD4⁺ and CD8⁺ T cells in the spleens of mice bearing control and PCSK9KO B16F10 tumours, as determined by flow cytometry. n = 3 mice per group; error bars show means ± s.e.m.; P-values were calculated using unpaired two-sided t-tests. d, Flow-cytometric determination of the percentage of intratumoral CD8⁺ T cells that expressed IFN-γ. n = 6, 5 tumours in the two groups. Error bars show means ± s.e.m.; P-values were calculated by unpaired two-sided t-test. e, f, qRT–PCR analysis of intratumoural IFNG (e) and GZMB (f) mRNA levels in control and PCSK9KO tumours. n = 3 and 4 tumours for INFG and GZMB groups, respectively. Error bars show means ± s.e.m.; P-values were determined by unpaired two-sided t-test. g–i, Flow-cytometric characterization of the cell-surface expression levels of exhaustion markers for intratumoral CD8⁺ T cells in vector control and PCSK9KO tumours. n = 6 and 5 tumours for control and PCSK9-knockout conditions. Error bars show means ± s.e.m.; P-values were determined by unpaired two-sided t-test. j, Schedule for treating Balb/c mice, injected with 4T1 tumour cells, with evolocumab (αPCSK9 Ab) and anti-PD1 antibodies. k, Growth of 4T1 tumours treated with anti-PD1 antibodies and/or evolocumab. n = 5 mice per group. P-values were determined by two-way ANOVA. l, Kaplan–Meier survival curves for mice in k. P-values were determined by log-rank tests. m, Frequency of CD8⁺ T cells in 4T1 tumours treated with anti-PD1 antibodies and/or evolocumab. n = 5 tumours per group. Error bars show means ± s.e.m.; P values were determined by unpaired two-sided t-test. n, Frequency of IFNγ⁺ CD8⁺ T cells in 4T1 tumours treated with anti-PD1 antibodies and/or evolocumab. n = 5 tumours per group. Error bars show means ± s.e.m.; P-values were determined by unpaired two-sided t-test.

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Extended Data Fig. 7 Additional data on the effect of PCSK9 inhibition on immune effector function and antigen presentation.

a, Injection schedule for antibody-mediated depletion of CD4⁺, CD8⁺ and natural killer (NK) immune cells. b, c, Growth rates (b) and host mouse survival (c) for PCSK9KO tumours in mice administered with control or anti-CD4 antibodies. n = 5 tumours per group. Error bars show means ± s.e.m.; P-values were determined by two-way ANOVA (b) and log-rank test (c). d, e, Growth rates (d) and host mouse survival (e) for PCSK9KO tumours in mice administered with control or anti-NK1.1 antibody. n = 5 tumours per group. Error bars show means ± s.e.m.; P-values were determined by two-way ANOVA (d) and log-rank test (e). f, Fluorescence images of tdTomato-labelled tumour cells with or without the OVA antigen in the presence or absence of OVA-specific T cells. The experiments were repeated twice with similar results. Scale bar, 200 μm. g, Enhanced presentation of OVA antigen (SIINFEKL) by MHC I in cultured B16F10 cells following PCSK9 deficiency. Control and PCSK9KO B16F10 cells transduced with the OVA gene were treated with IFN-γ and assayed for the amount of cell-surface H-2K^b–SIINFEKL complex using flow cytometry. Shown are representative results from analyses of four sets of biologically independent samples. h, i, Flow-cytometric analysis of MHC II (h) and PD-L1(i) expression in control and PCSK9KO B16F10 cells. n = 5 and 4 biologically independent samples, respectively. P-values were determined by unpaired two-sided t-test. j, Western blot analysis of PCSK9 expression in control or PCSK9KO MDA-MB-231 cells. The analyses were carried out twice. k, Effects of evolocumab and alirocumab on HLA-ABC expression on the surface of MDA-MB-231 human breast cancer cells. n = 6, 6 and 5 biologically independent samples from left to right. Data represent means ± s.e.m.; P-values were determined by unpaired two-sided t-test. l, H2-K^d/D^d expression levels for 4T1 tumour cells that were exposed to anti-PD1 antibodies and/or evolocumab in vivo. n = 5 mice per group. Error bars show means ± s.e.m.; P-values were determined by unpaired two-sided t-test.

Source data

Extended Data Fig. 8 Additional data on the analysis of PCSK9, H2-K1 and LDLR in murine tumour cells.

a, Lentivirus-mediated overexpression of HA-tagged H2-K1 in B16F10 cells as determined by western blot analysis. The analysis was done once. b, c, Tumour-growth delay (b) and Kaplan–Meier survival curve (c) of tumour-bearing C57BL/6 mice implanted with vector control or H2-K1-overexpressing B16F10 cells. Error bars show means ± s.e.m.; n = 5 tumours in each group; P-values were determined by two-way ANOVA (b) and log-rank test (c). d, e, Tumour-growth delay (d) and Kaplan–Meier survival curves (e) in mice injected with vector control, H2-K1-knockdown, PCSK9-knockout, or PCSK9-knockout plus H2-K1-knockdown B16F10 cells. n = 5 mice per group. Error bars show means ± s.e.m.; P-values were determined by two-way ANOVA (d) and log-rank test (e). f, Western blot analysis of LDLR knockdown in control and PCSK9KO B16F10 tumour cells. The analysis was done once. g, h, Tumour-growth delay (g) and Kaplan–Meier survival curves (h) from LDLR KD and LDLR KD/PCSK9KO B16F10 tumours. n = 5 mice per group. Error bars show means ± s.e.m.; P values were determined by two-way ANOVA (h) and log-rank test (i). i, Flow-cytometric analysis of MHC I expression in tumours formed from tdTomato-labelled control and LDLRKD B16F10 cells. n = 6 biologically independent tumours. Error bars show means ± s.e.m.; P-values were calculated by unpaired two-sided t-test. j, Flow-cytometric analysis of MHC I expression in tumours formed from tdTomato-labelled LDLR KD (n = 6) and LDLR KD/PCSK9KO cells (n = 4). Error bars show means ± s.e.m.; P-values were calculated by unpaired two-sided t-test.

Source data

Extended Data Fig. 9 Additional data on the mapping and functional characterization of interacting domains in PCSK9 and MHC I, and on the association of PCSK9 expression with the prognosis of TCGA cohorts.

a, Domain structure of mouse PCSK9. Catalytic, catalytic domain; CRD; C-terminal domain; Pro, propeptide; SP, signal peptide. b, Immunoprecipitation/western blot analysis of the interaction between full-length FLAG-labelled H2-K1 and full-length or partially deleted mouse HA-labelled PCSK9. Plasmids encoding the two genes were transfected into 293T cells in pairs, and lysates from transduced cells were immunoprecipitated with an anti-HA antibody and probed with an anti-FLAG antibody by western blot analysis. The analyses were repeated twice with biologically independent samples with similar results. c, Immunoprecipitation/western blot analysis of the interaction between full-length HA-labelled mouse PCSK9 and full-length or partially deleted FLAG-labelled H2-K1 (amino acids 66–202) (α1–α2 domains). The analyses were repeated twice with biologically independent samples, with similar results. d, Immunoprecipitation/western blot analysis of the interaction of HA-labelled mouse PCSK9 with full-length H2-K1 or H2-K1 with more limited deletions (amino acids 66–100, α1 domain; or amino acids 68–70). The analyses were repeated twice with biologically independent samples, with similar results. e, f, Tumour growth rates (e) and Kaplan–Meier survival curves (f) for mice inoculated with PCSK9KO B16F10 tumour cells, with re-expressed wild-type or partially (ΔM2) deleted PCSK9. n = 5 tumours per group. Error bars show means ± s.e.m.; P-values were determined by two-way ANOVA (e) and log-rank test (f). g, h, Tumour growth rates (g) and Kaplan–Meier survival curve (h) for mice inoculated with H2-K1KO or H2-K1/PCSK9 double-knockout (DKO) B16F10 tumour cells re-expressed with wild-type or partially deleted (Δ68–70) H2-K1. n = 5 tumours per group. Error bars show means ± s.e.m.; P-values were determined by two-way ANOVA (g) and log-rank test (h). i, Higher levels of PCSK9 expression correlate with worse survival in nine cohorts of patients with cancer, including liver hepatocellular carcinoma (LIHC), pancreatic adenocarcinoma (PAAD), skin cutaneous melanoma (SKCM), uveal melanoma (UVM), bladder urothelial carcinoma (BLCA), lung adenocarcinoma (LUAD), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP) and ovarian carcinoma (OV). P-values were calculated by log-rank test. Data are from TCGA data sets.

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Extended Data Fig. 10 Diagram illustrating PCSK9-mediated degradation of MHC I in the lysosome.

Left, in the presence of PCSK9, MHC I is transported into lysosomes and degraded. Right, in the absence of PCSK9 (through genetic deletion or antibody-mediated neutralization), MHC I levels on the surface remain high and can thus present tumour-specific peptide antigens more efficiently to T cells. Illustration by S. Coffman.

Supplementary information

Supplementary Information

This file contains Supplementary Figure 1. Raw images of immunoblots. Uncropped images of scanned immunoblots shown in Fig. 4g, Fig 4i, Fig. 4j, Fig 4k, and 4l, Extended Data Fig. 1a, Extended Data Fig. 2a, Extended Data Fig. 3a, Extended Data 7j, Extended Data Fig. 8a, Extended Data Fig. 8f, Extended Data Fig. 9b, Extended Data Fig. 9c, and Extended Data Fig. 9d.

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Liu, X., Bao, X., Hu, M. et al. Inhibition of PCSK9 potentiates immune checkpoint therapy for cancer. Nature 588, 693–698 (2020). https://doi.org/10.1038/s41586-020-2911-7

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Received: 24 December 2018
Accepted: 24 August 2020
Published: 11 November 2020
Issue Date: 24 December 2020
DOI: https://doi.org/10.1038/s41586-020-2911-7

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Abstract

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Main

PCSK9 deficiency and tumour growth rate

PCSK9 inhibition and immunotherapy

PCSK9 and lymphocyte infiltration

PCSK9 and MHC I regulation

Discussion

Methods

Cell lines

CRISPR–Cas9-mediated gene knockout

Colony formation in soft agar

Antibodies and related reagents

Western blot analysis

Molecular cloning

Ectopic gene expression

Tumour growth in mice

Lymphocyte depletion

In vivo competition assay

Analysis of cell-surface MHC I expression

Analysis of tumour-infiltrating lymphocytes

qRT–PCR of CTL-related gene expression

TCRs from tumour-infiltrating lymphocytes

OT-1 T cell culture

Tumour-cell/T-cell co-culture analysis

Cell fractionation and MHC I quantification

Immunofluorescence and immunohistochemistry

Analysis of PCSK9 and H2-K1 interaction

Cycloheximide chase assay

Statistical analysis

Reporting summary

Data availability

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