Novel insights into paclitaxel’s role on tumor-associated macrophages in enhancing PD-1 blockade in breast cancer treatment

Abstract

Background

Triple-negative breast cancer (TNBC) poses unique challenges due to its complex nature and the need for more effective treatments. Recent studies showed encouraging outcomes from combining paclitaxel (PTX) with programmed cell death protein-1 (PD-1) blockade in treating TNBC, although the exact mechanisms behind the improved results are unclear.

Methods

We employed an integrated approach, analyzing spatial transcriptomics and single-cell RNA sequencing data from TNBC patients to understand why the combination of PTX and PD-1 blockade showed better response in TNBC patients. We focused on toll-like receptor 4 (TLR4), a receptor of PTX, and its role in modulating the cross-presentation signaling pathways in tumor-associated macrophages (TAMs) within the tumor microenvironment. Leveraging insights obtained from patient-derived data, we conducted in vitro experiments using immunosuppressive bone marrow-derived macrophages (iBMDMs) to validate if PTX could augment the cross-presentation and phagocytosis activities. Subsequently, we extended our study to an in vivo murine model of TNBC to ascertain the effects of PTX on the cross-presentation capabilities of TAMs and its downstream impact on CD8+ T cell-mediated immune responses.

Results

Data analysis from TNBC patients revealed that the activation of TLR4 and cross-presentation signaling pathways are crucial for the antitumor efficacy of PTX. In vitro studies showed that PTX treatment enhances the cross-presentation ability of iBMDMs. In vivo experiments demonstrated that PTX activates TLR4-dependent cross-presentation in TAMs, improving CD8+ T cell-mediated antitumor responses. The efficacy of PTX in promoting antitumor immunity was elicited when combined with PD-1 blockade, suggesting a complementary interaction.

Conclusions

This study reveals how PTX boosts the effectiveness of PD-1 inhibitors in treating TNBC. We found that PTX activates TLR4 signaling in TAMs. This activation enhances their ability to present antigens, thereby boosting CD8+ T cell antitumor responses. These findings not only shed light on PTX’s immunomodulatory role in TNBC but also underscore the potential of targeting TAMs’ antigen presentation capabilities in immunotherapy approaches.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• Combining paclitaxel (PTX) with immune checkpoint inhibitors (ICI) in the clinic demonstrates significant clinical efficacy against triple-negative breast cancer (TNBC). However, the detailed mechanisms underlying this synergy remain not fully understood.

WHAT THIS STUDY ADDS

• The study revealed that PTX enhances tumor-associated macrophage antigen cross-presentation via a TLR4-dependent mechanism. Based on PTX-induced modulation of the immune landscape, the study delineates that the complementary outcome of PTX and ICI combination is CD8+ T cell-dependent.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• By offering novel insights into the therapeutic efficacy of PTX, a conventional anticancer drug for TNBC, this study significantly contributes to the development of promising anticancer immunotherapy combinations. These findings hold substantial promise for addressing the high unmet medical needs associated with TNBC as well as other tumors, thereby providing valuable support for advancements in cancer treatment strategies.

Background

Triple-negative breast cancer (TNBC) is identified by the lack of estrogen, progesterone, and HER2 receptors, making up around 15%–20% of total breast cancer occurrences.¹ This absence of key receptors, typically targeted in other breast cancer subtypes, renders TNBC particularly challenging to treat. Notoriously aggressive, TNBC predominantly affects younger women and is associated with a high mortality rate, surpassed only by lung cancer in terms of cancer-related deaths among women.¹ The complexity of TNBC lies not only in its unique cellular characteristics but also in its tumor microenvironment (TME), which plays a pivotal role in the progression of the disease and the response to treatment.² Notably, the high infiltration of tumor-associated macrophages (TAMs) in TNBC promotes tumor aggressiveness and is related to distant metastasis and poor prognosis.3,5 This complexity and the difficulty in treating TNBC highlight the urgent need for developing innovative therapeutic strategies.⁶

Recent clinical evaluations have shown that monotherapy with immune checkpoint inhibitors (ICIs) targeting programmed cell death protein-1/programmed cell death-ligand 1 (PD-1/PD-L1) has demonstrated relatively low efficacy in TNBC, with objective response rates ranging from only 5.3 % to 21.4 %.^{7 8} In contrast, the combination of paclitaxel (PTX) with PD-1 blockade has exhibited encouraging clinical efficacy in TNBC patients.^{9 10} Specifically, this combined therapy has improved overall survival by 27% compared with chemotherapy alone and has shown a 13.6% higher pathological complete response rate without a significant increase in the incidence of adverse events.^{9 10} Recent findings suggest that, beyond the well-known mechanism of PTX in stabilizing microtubules to inhibit cancer cell division and induce apoptosis, its role as a toll-like receptor 4 (TLR4) agonist in reprogramming TAMs from an M2 to an M1 profile may be the primary anticancer mechanism in vivo.¹¹ However, the exact reasons why TAM-dependent immunotherapeutic efficacy of PTX enhances the effectiveness of CD8+ T cell-targeting PD-1 blockade are not fully explained, indicating the need for further mechanistic studies.

Our study aims to unravel the intricate interactions between PTX, TAMs, and TLR4 signaling in TNBC. By integrating clinical trial data with experimental models, we intend to elucidate how PTX affects the TME, particularly in modulating the function of TAMs in activating tumor-specific CD8+ T cell immunity via TLR4 signaling pathways. We aim to investigate the influence of this modulation on the therapeutic efficacy of combined PTX and anti-PD-1 antibody therapy. This investigation may shed light on the role of TAMs in TNBC immunotherapy and provide deeper insights into the synergistic effectiveness of PTX and ICI combination therapy in TNBC and other TAM-rich tumors.

Methods

scRNA-seq and Visium data processing

The scRNA-seq data in this study were acquired from the NCBI Gene Expression Omnibus database using the accession numbers GSE176078 and GSE169246. Following count matrix construction, we conducted an integrative analysis of the four scRNA-seq datasets using the R package Seurat (V.4.3.0) in R (V.4.3.1). For GSE176078, we only used 10 TNBC samples from the preprocessed data. Cells with an expression of fewer than 200 genes and a mitochondrial gene percentage exceeding 20 were excluded. The gene expression values were subjected to log-normalization. UMAP (uniform manifold approximation and projection) was computed using 15 principal components. For GSE169246, cells from progressed tumors and blood were excluded. We filtered cells with a unique molecular identifier count of <2000 or >25 000 and <750 expressed genes or >4000. UMAP was performed for the first 10 PCs. The myeloid cell population was extracted from the datasets based on the existing clustering detailed in the original publications. For the Visium spatial transcriptomics data, four datasets from TNBC patients were obtained from the Zenodo repository (DOI: 10.5281/zenodo.4739739), sourced from the same study. To identify cell types constituting the spatial spots used for the single-cell transcriptomic data analysis, the CellDART algorithm¹² was employed, using default parameters. All other procedures were conducted using the Seurat and Scanpy packages.

Gene set enrichment analysis

Gene set enrichment analysis (GSEA) analysis and statistical analysis on GSEA were performed using the fgsea package (V.1.27) in R. Gene sets from the TLR4 signaling pathway were acquired from GSEA (https://www.gseamsigdb.org/gsea/msigdb/cards/REACTOME_ACTIVATED_TLR4_SIGNALLING). Gene sets from the presentation signaling pathway were organized based on references (online supplemental table 1). Marker genes that upregulated in responders compared with non-responders were determined by FindMarker function in Seurat. Average log₂(fold change) values were used. GSEA for differentially expressed genes of baseline from responders who received PTX-PD-L1 therapy compared with non-responders were acquired from hallmark pathways using h.all.v6.2.symbols in the GSEA database.

Animals

Female C57BL/6 and BALB/c mice, 6–8 weeks old, were purchased from Orient Bio (South Korea). TLR4 knockout (KO) mice with a C57BL/6 background were created using cryopreserved resources provided by Dr. Sung Joong Lee from Seoul National University. The in vitro fertilization procedure was carried out by the Korea Research Institute of Bioscience and Biotechnology. TLR4 KO^+/− mice were then transferred to the KIST animal facility for breeding to generate TLR4 KO^−/− mice. Female TLR4 KO^−/− mice, aged 6−8 weeks, were chosen for the experiments. OT-I CD8+ T cell receptor (TCR)-transgenic male mice (Tg(TcraTcrb)1100Mjb) in the C57BL/6 background and FVB/N female mice (Tg(MMTVPyVT) 634Mul/J) were purchased from the Jackson Laboratory.

Cells and in vitro treatment of PTX

EO771, 4T1, and HEK293T cell lines were purchased from the American Type Culture Collection. EO771 and HEK293T were cultured and maintained in high glucose Dulbecco’s Modified Eagle Medium (Cytiva), and 4T1 was cultured in RPMI-1640. The media were supplemented with 1% antibiotic-antimycotics (ThermoFisher) and 10% fetal bovine serum (Gibco).

Bone marrow cells were obtained from the femurs and tibiae of 6–8 week C57BL/6 mice and TLR4 KO mice or BALB/c mice to induce wild-type (WT) bone marrow-derived macrophage (BMDM), WT immunosuppressive BMDM (iBMDM), or TLR4 KO iBMDM.¹³ The cells collected from the mice were filtered with 40 µM cell strainers, and red blood cells (RBC) were removed with the RBC lysis buffer (BioLegend). The cells were plated in a 90 mm petri dish in RPMI (day 0) and incubated overnight. The cells collected after 24 hours were seeded in RPMI supplemented with 20 ng/mL macrophage colony-stimulating factor (M-CSF, Peprotech). 20 ng/mL M-CSF was added on days 2 and 3. The medium was replaced with fresh M-CSF-containing RPMI on day 4. On day 6, the medium was refreshed with RPMI containing additional cytokines and incubated for an additional 48 hours accordingly: 20 ng/mL M-CSF for BMDMs, IL-4 (Peprotech) 20 ng/mL, IL-13 (Peprotech) 20 ng/mL for iBMDMs. All cells were maintained at 37°C in a humidified atmosphere of 5% CO₂. All cell lines were tested for mycoplasma contamination with Mycostrip (InvivoGen) and maintained free of mycoplasma.

In vitro analysis of macrophage phenotypes

To analyze the macrophage phenotypes, cells were stained with the following antibodies for flow cytometric analysis; FITC anti-mouse F4/80 (BM8), BV605 anti-mouse CD11b (M1/70), PE anti-mouse CD206 (C068C2), PE anti-Nos2 (iNOS) (W16030C), PE anti-mouse H-2Kb (AF6-88.5), PE anti-mouse CD40 (FGK45), PE anti-mouse CD80 (16–10 A1), or PE anti-mouse CD86 (A17199A), PE anti-phospho-TBK1/NAK antibody (D52C2, Cell Signaling).

In vivo tumor models

To establish a TNBC tumor-bearing mouse model, 10⁶ EO771 cells or 5×10⁵ 4T1 cells were implanted on a female C57BL/6 or BALB/c mouse mammary fat pad, respectively. After the tumor establishment, mice were randomized before treatment yet blinded for tumor size measurement and data analysis. For in vivo injection, PTX was reconstituted with a 50:50 v/v mixture of Cremophor EL(Millipore) and ethanol. 10 mg/kg PTX or the same volume of control vehicle was intravenously injected every other day 5 times when tumor size reached 50–80 mm³ (day 0). 200 µg αPD-1 (anti-mouse PD-1 antibody, RMP1-14, InVivoMAb) was intraperitoneally injected on days 2, 4, 6, and 8. The size of tumors and the body weight of mice were assessed every other day. Tumor volumes were determined using a modified ellipsoidal formula: volume=length×width²/2. The tumor-bearing mice were sacrificed on day 14 to assess the TME and monitored for another 2 days to track the survival rate. The mice were considered non-viable when the tumor volume reached 2000 mm³ post-treatment.

For CD4+ or CD8+ T cell depletion, 200μg neutralizing anti-mouse CD4 (GK1.5, InVivoMAb) or anti-mouse CD8 antibody (2.43, InVivoMAb) was intraperitoneally injected into tumor-bearing mice every 3 days, starting from a day before initial PTX treatment (days −1, 2, 5, 8). The same amount of Rat IgG2bκ (InVivoMAb) was used for control reagents, following the identical injection schedule.

For TAM depletion, clodronate liposomes and control liposomes were purchased from LIPOSOMA (Netherlands). When EO771 tumor volume reached 50–80 mm², 4.55 mL/kg control liposome or clodronate liposome was intraperitoneally injected into mice on days 0, 3, 6, and 9, and 10 mg/kg PTX was injected intravenously on days 0, 2, 4, 6, and 8.

Cell cytotoxicity analysis

HEK293T, EO771, or iBMDMs were refreshed with 0.01–10 µM PTX containing growth media. After 48 hours PTX treatment, the cells and media were collected and resuspended in an annexin binding buffer (ThermoFisher). The fluorochrome-conjugated Annexin V (AdipoGen) was added to the samples to stain the dying cells for 10 min at room temperature (RT) in the dark. The samples were washed with the annexin binding buffer and further analyzed by flow cytometry.

In vitro phagocytosis assay

PTX treated-treated or non-treated iBMDMs were labeled with 1 µM CellTracker Deep Red (ThermoFisher) for 25 min at RT in the dark. The remaining dye was removed by centrifugation after staining. Stained iBMDMs were then seeded and incubated for 24 hours. EO771 cancer cells were stained with 1 µM CellTracker Green CMFDA (ThermoFisher) and cocultured with iBMDMs in a ratio of 4:1 in a growth medium at 37°C for 2 hours. All cells were collected and washed for flow cytometry analysis. The degree of phagocytosis was calculated as the percentage of green+ cells within deep red+macrophages.

In vitro cross-presentation assay

iBMDMs were treated with 0–10 µM PTX for 24 hours. After 24 hours, 10 µg/mL ovalbumin (OVA) peptide SIINFEKL (Sigma-Aldrich) was added and incubated for an additional 24 hours. To examine the TLR4 pathway dependency of PTX, cells were pretreated with 10 µg/mL TAK-242 (Sigma-Aldrich) or anti-TLR4 antibody (Abcam) for 24 hours before PTX treatment. 100 µg/mL LPS was added simultaneously as PTX. After 48 hours of initial treatment of PTX or LPS, cells and supernatants were collected and stained with APC anti-F4/80 antibody (BM8) and PE anti-H-2Kb-OVA antibody (25-D1.16) from BioLegend and further analyzed with flow cytometry.

Western blot

iBMDMs were collected and resuspended with RIPA buffer (Cell Signaling Technology) supplemented with a protease inhibitor cocktail (Roche). The mixture was incubated in ice for 20 min with intermittent vortexing every 5 min. Subsequently, protein concentration from lysed cells was quantified with a bicinchoninic acid protein assay kit (BioRad). Western blot was performed with the antibodies as follows: anti-NF-κB p65 (L8F8, Cell Signaling), anti-ERp57 (Abcam), anti-calreticulin (Abcam), anti-TPN (EPR25083-20, Abcam), anti-beta 2 microglobulin (β2M) (EP2978Y, Abcam), anti-GAPDH (686613, R&D system), anti-Rabbit IgG-Peroxidase antibody (A0545, MERCK), and anti-mouse IgG-peroxidase antibody (A4416, MERCK).

Real time-quantitative PCR (RT-qPCR)

iBMDMs treated with PTX for 48 hours were harvested and processed to extract DNA and form mRNA using a DNA-spin Plasmid DNA Purification kit (Intron bio) and RNeasy Mini Kit (Qiagen) according to the manufacturer’s protocol. Following RNA extraction, RNA was quantified with a Nanodrop One spectrophotometer (ThermoFisher). RNA was subjected to cDNA synthesis using the TOPscript RT DryMIX (dT18) kit (Enzynomics). SimpliAmp Thermal Cycler (ThermoFisher) was used for reverse transcription. Subsequently, cDNA was amplified using specific primers with PowerUP SYBR Green Master Mix (ThermoFisher) and analyzed using Applied Biosystems Real-Time PCR Instruments. The PCR cycling conditions were as follows: (1) 50℃ for 2 min, (2) 95℃ for 2 min, (3) 95℃ for 1 s, (4) 60℃ for 30 s, (5) repeat steps 3 and 4 for 39 more times, and (6) melt curve stage: 95℃ for 1 s, 60℃ for 20 s, and 95 ℃ for 1 s. The expression of the target gene was normalized to the levels of GAPDH. Primers were synthesized by Cosmogenetech (South Korea) (table 1).

Table 1. List of primers used for real time-quantitative PCR.

RAB11A	F	5’-	TTGCAACAAGAAGCATCCAG	−3’
	R	5’-	CTTATTGCCCACAAGCATGA	−3’
ERGIC53	F	5’-	GAG AAC TGG GAA GTG GAA GTG	−3’
	R	5’-	CTT TAG CGA GTT GTC AGA GGG	−3’
VAMP8	F	5’-	CGGAAATGACCGAGTTAGGA	−3’
	R	5’-	CACCTTCTGGGACGTTGTCT	−3’
GAPDH	F	5’-	CATCACTGCCACCCAGAAGACTG	−3’
	R	5’-	ATGCCAGTGAGCTTCCCGTTCAG	−3’

Immune transcriptome profiling of in vitro cultured iBMDM

iBMDMs treated with PTX for 48 hours or non-treated samples were harvested and resuspended with the Buffer RLT (Qiagen). The RNA extraction was performed by Philekorea (South Korea), and the extracted samples went through quality analysis to ensure a high throughput. The RNA gene expression was analyzed employing the NanoString nCounter mouse Myeloid Innate Immunity gene expression panel (NanoString Technologies). The gene expression data were normalized against a set of positive and negative controls to account for background noise and platform-associated variation. The graphs were plotted using normalized expression data. The gene sets employed for heatmap construction were acquired from the GO Biological Process Annotations 2023 (GO_0002474, GO_0045807, GO_0034142). The data were initially analyzed with nSolver (NanoString), and the heatmap was plotted with GraphPad Prism.

Single-cell preparation and flow cytometry analysis

Tumor tissues acquired from mice were dissociated using a tumor dissociation kit and Gentle MACS dissociator (MiltenyiBiotec). The resulting tissue suspension was filtered through a 40 µm strainer to ensure a homogeneous cell population. The RBCs were removed with RBC lysis buffer, and dead cells were removed using a dead cell removal kit (MiltenyiBiotec). The viable cells were collected and counted by flow cytometry. 10⁶ viable cells were preblocked with anti-CD16/CD32 (2.4G2) at RT for 10 min. Zombie Aqua Fixable Viability Kit (BioLegend) or LIVE/DEAD Fixable Near-IR Dead Cell Stain Kit (Invitrogen) was used to stain the dead cells. Following antibodies purchased from BioLegend were added for analysis; PE/Cyanine7 anti-mouse CD45.2 (104), FITC anti-mouse F4/80 (BM8), FITC anti-mouse CD8a (53–6.7), PE anti-mouse H-2Kb (AF6-88.5), PE anti-mouse CD11c (N418), APC anti-mouse CD11c (N418), APC anti-mouse TLR4 (SA15-2), APC anti-mouse CD3 (17A2), BV605 anti-mouse CD11b (M1/70). Depletion of TAM was verified by staining CD45.2, CD11b, and F4/80 antibodies. Depletion of CD4+ or CD8+ cells was verified by staining CD45.2, CD3, FITC anti-mouse CD4 (RM4-5), or CD8a antibodies, respectively.

To isolate TAM from the tumor tissue, viable cells underwent magnetic bead sorting with anti-F4/80 MicroBeads (MiltenyiBiotec) following the manufacturer’s protocol. To acquire CD8+ T cells from mice, spleens and tumor-draining lymph nodes (TDLNs) were collected. The spleens were dissociated with GentleMACS, and the TDLNs were gently mashed and filtered through a 40 µm strainer in RPMI. The cells collected from TDLN and spleens were combined and underwent RBC lysis and CD8+ T cell sorting with a CD8+ T cell isolation kit (MiltenyiBiotec) according to the manufacturer-provided protocols.

In vitro T cell cross-priming assay

5×10⁴ iBMDMs or TAMs and 2.5×10⁵ CD8+ T cells acquired from mice were resuspended in RPMI and seeded in 96-well U-bottom plates. 10 µg/mL OVA-peptide for antigenic stimulation was added to the samples with T cells for stimulating iBMDMs. After 72 hours, the culture media was analyzed with mouse IFN-γ Quantikine ELISA (R&D systems) following manufacturer-provided protocol. The optical density was measured with VICTOR Nivo (Perkin Elmer).

Immunohistochemistry

The obtained tumor tissues were fixed with 4% formalin and prepared into paraffin blocks for analysis. The samples were sliced and TUNEL stained. The stained samples were analyzed to quantify TUNEL-positive cell number relative to the whole area of samples.

Multiplex immunohistochemistry

Prism CDX (South Korea) performed the antibody staining and image scan. The acquired tumor tissues were fixed with 4% formalin and embedded into paraffin blocks, and 4 μm thick sliced tissues were prepared. The slides were heated for 1 hour in a dry oven at 60℃ and multiplex immunofluorescence stained with Leica Bond Rx Automated Stainer (Leica Biosystems). Briefly, the slides were dewaxed with Leica Bond Dewax solution (Leica Biosystems), followed by antigen retrieval using Bond Epitope Retrieval 2 (Leica Biosystems) for 30 min. The staining process was sequential rounds of blocking buffer (TheraNovis), followed by primary antibody incubation for 30 min and goat anti-Rabbit IgG H&L secondary antibody (Abcam) incubation for 10 min. The primary antibodies are as follows: anti-F4/80 (Cell Signaling Technology), anti-CD11b (Abcam), anti-MHC1 (Novus), anti-PD-L1 (Cell Signaling Technology), and anti-CD8 (Cell Signaling Technology). The visualization of antigen was accomplished using Astra-dye (TheraNovis) for 10 min, after which the slide was treated with Bond Epitope Retrieval 1 (Leica Biosystems) for 20 min to remove bound antibodies. The Astra-dyes are as follows: Astra-570 for anti-F4/80, Astra-520 for anti-CD11b, Astra-690 for anti-MHC1, Astra-620 for anti-PD-L1, and Astra-DIG with Anti-Dig-780 for anti-CD8. The process from the blocking to the antigen retrieval step was repeated for each antibody staining. The nuclei were stained with DAPI (ThermoFisher) for counterstaining after the last round of antigen retrieval. The slides were coverslipped using ProLong Gold antifade reagent (Invitrogen). The multiplex stained slides were scanned using the PhenoImager HT (Akoya Biosciences) at ×20 magnification. The representative image for training was selected in Phenochart Whole Slide Viewer V.1.0.12 (Akoya Biosciences), and an algorithm was created in the InForm Tissue Analysis software V.2.6 (Akoya Biosciences). Based on DAPI staining, each single cell was segmented and phenotyped according to each marker’s expression compartment and intensity. After designating the region of interest to be analyzed on the tissue slide, the same algorithm created in this way was applied. The exported data were consolidated and analyzed using R; phenoptr (Akoya Biosciences) and phenoptrReport (Akoya Biosciences) packages.

Transcriptome sequencing of TAM

The overall sampling and analysis of TAM acquired from mice was conducted by Macrogen (South Korea). Using the TruSeq Nano DNA kit, a paired-end 350 bp insert size library was created for the two species (Illumina, San Diego, California, USA). Using the standard Illumina operating protocol, the libraries were then sequenced using 2×151 bp paired-end sequencing on the Illumina NovaSeq6000 platform. The primary data processing was completed with the manufacturer’s program Real-Time Analysis (RTA 1.18.66.3). FASTQ sequence files were constructed with the Illumina tool bcl2fastq. FastQC was used to examine the raw read quality visually. Trimmomatic (V.0.38) was used to delete the remaining adapter sequences, leading and trailing nucleotides with a Phred score of less than 25 and reads less than 50 bp. The TruSeq stranded mRNA library kit (Illumina) was used with the Illumina platform for analysis. Sample quality assessment was performed with FastQC, and data were trimmed using Trimmomatic 0.38. Genome assembly GRCm38 (MM10) was used for gene identification and analyzed with HISAT2 V.2.1.0, followed by assembly of the potential transcript with StringTie V.2.1.3b.

Statistical analysis

All experiments were conducted at least two times with sufficient number of replicates to ensure robust statistical analysis. Detailed information regarding the number of samples and the meaning of data values are provided in the figure legends. Error bars represent the SEM. Statistical significance was determined using Student’s unpaired two-tailed t-test for comparisons between two groups, one-way analysis of variance with Tukey’s post hoc test for multiple comparisons, or a log-rank (Mantel-Cox) test for mice survival rates. Significance levels are indicated by *, **, and *** for p values of <0.05, <0.01, and<0.001, respectively. Only statistically significant comparisons are shown.

Results

Clinical antitumor efficacy of PTX correlates with TLR4 signaling and cross-presentation in TAMs with high TLR4 expression in TNBC

To investigate whether PTX induces an antitumor immune response through the TLR4 signaling pathway and acts as a TLR4 agonist, we analyzed publicly available spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) datasets of patient-derived TNBC. These datasets include both treatment-naïve and drug-treated TNBC samples. By analyzing scRNA-seq data from 10 TNBC patients (GSE170678), we observed significant TLR4 expression within the myeloid cell population, particularly in macrophages (online supplemental figure 1A,B). Further analysis of Visium spatial transcriptomic data from the same study revealed that the TLR4 expression level showed the highest correlation with the distribution of myeloid cells in the TME (figure 1A). Another independent scRNA-seq dataset from twenty-two TNBC patients (GSE169246) also supported these findings, identifying monocytes and, notably, macrophages as the primary cells expressing TLR4 (figure 1B,C). To validate these observations in TNBC mouse models, we conducted further experiments. We found that TAMs (CD45.2+CD11b+F4/80+ cells) were the predominant cell population expressing TLR4 in the TME of syngeneic 4T1 and EO771 tumor models, as well as in transgenic MMTV-PyMT tumor models (figure 1D). These results suggest that PTX, potentially acting as a TLR4 agonist, might be most sensitive in TAMs due to the comparably high TLR4 expression.

Figure 1. Clinical antitumor efficacy of paclitaxel (PTX) correlates with toll-like receptor 4 (TLR4) signaling and cross-presentation in tumor-associated macrophages (TAMs) with high TLR4 expression in triple-negative breast cancer (TNBC). (A) Spearman correlation of TLR4 expression in cell clusters in the publicly available spatial transcriptomic dataset (Zenodo.4739749). (B) Intercellular heterogeneity of TLR4 expression in TNBC patients was quantified by single-cell RNA sequencing. The uniform manifold approximation and projection for dimension reduction (UMAP) plot of immune cells in TME is distinguished into four clusters (upper left) and TLR4 expression of the cells (upper right). The clusters are as follows: T cell, myeloid cell, B cell, and innate lymphoid cell. The UMAP plot of myeloid cells is distinguished into seven clusters (lower left) and TLR4 expression of the cells (lower right). Macrophage, monocyte, conventional dendritic cell 1(cDC1), conventional dendritic cell 2 (cDC2), myeloid DC (mDC), plasmacytoid DCs (pDC), and mast cell. (C) TLR4 expression in myeloid cell populations from immune cells in tumors of TNBC patients (GSE169246). Samples include baseline (specimen collected before treatment of PTX) and post-treatment of PTX or its combination with the anti-PD-L1 atezolizumab. (D) Intercellular heterogeneity of TLR4 expression in TME of TNBC syngeneic mouse models (EO771, n=4; 4T1, n=6) and syngeneic mouse model (MMTV-PyMT, n=4) were analyzed with flow cytometry. Each column displays group means with individual data points and error bars with SEM. Statistical significance was determined using one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test. P values indicate significant differences (**p<0.01; ***p<0.001; only statistically significant comparisons shown). (E) Gene set enrichment analysis (GSEA) on TAM in tumors of TNBC patients (GSE169246) who received PTX treatment (post-treatment specimens), including both responder and non-responders. (F) Upregulated signaling pathways from baseline sample data from responders who received PTX+anti-PD-L1 therapy compared with non-responders (pretreatment specimens). The statistical analysis of transcriptome data is detailed in the Methods section.

Next, to understand the relationship between TLR4 expression in TAMs and clinical response to PTX regimens in patients, we investigated whether TLR4-related signaling pathways were upregulated in TAMs following PTX administration in PTX responders. GSEA on a scRNAseq dataset (GSE169246) revealed that the TLR4 signaling pathway was significantly enhanced in TAMs from TNBC patients who responded to PTX, compared with non-responders (figure 1E). Considering the crucial role of myeloid cell cross-presentation in the infiltration of tumor-specific CD8+ T cells, which are targets of PD-1 blockade and pivotal in antitumor immunity,14,16 we analyzed whether an increase in cross-presentation genes in TAMs post-PTX treatment correlated with the antitumor efficacy of PTX. The GSEA analysis showed that the cross-presentation signaling pathway was also enriched in TAMs from TNBC patients who responded to PTX compared with non-responders (figure 1E). Furthermore, signaling pathway related to interferon (IFN)-α and IFN-γ responses were significantly upregulated in baseline TAMs from TNBC patients both who responded to PTX or PTX+PD-L1 therapy when compared with those of non-responders17,19 (figure 1F and online supplemental figure 1C). Collectively, our data emphasize that overexpression of TLR4 and upregulation of TLR4 signaling with cross-presentation capabilities within TAMs enhance the immunotherapeutic efficacy of PTX regimens in TNBC.

PTX augments cross-presentation of immunosuppressive bone marrow-derived macrophages in a TLR4-dependent manner

To mimic TAM in vitro for understanding the effect of PTX, we differentiated BMDMs) to iBMDMs by conditioning with IL-4 (online supplemental figure 2A). Recognizing that cancer cells are more sensitive to PTX than normal cells,^{20 21} we established an appropriate PTX concentration to assess its impact on iBMDM without causing significant cytotoxicity (online supplemental figure 3).

Our initial step involved transcriptome analysis of PTX-treated iBMDMs. This analysis revealed a notable increase in the expression of genes critical for phagocytosis and antigen presentation compared with untreated controls (figure 2A). Additionally, we observed an upregulation of RAB11a, ERGIC53, and VAMP8, key genes in antigen fragment-major histocompatibility complex (MHC) formation and transport^{19 22} (figure 2B). We also detected elevated levels of NOX2-related genes, CYBB and NCF2, which are known to inhibit rapid phagolysosomal acidification,²³ enhancing antigen survival and promoting cross-presentation in PTX-treated iBMDMs (figure 2B). Along with the functional modification, we observed changes in phenotypical markers indicating that PTX treatment can more effectively reprogram iBMDMs compared with BMDMs, resulting in a less immunosuppressive phenotype (online supplemental figure 2B). These findings underscore the role of PTX in amplifying TAM-driven cross-presentation.

Figure 2. Paclitaxel (PTX) augments cross-presentation of iBMDMs in a toll-like receptor 4 (TLR4)-dependent manner. (A) Heatmap depicting the genetic signatures of PTX-treated and non-treated immunosuppressive bone marrow-derived macrophages (iBMDMs) (n=3). The analyzed gene sets are acquired from GO Biological Process Annotations 2023 (Phagocytosis: GO0002474, antigen presentation: GO0045807). (B) The mRNA expression of PTX-treated and non-treated iBMDMs was analyzed through immune transcriptome profiling and RT-qPCR. CYBB and NCF2 were plotted based on analysis by NanoString. RAB11a, ERGIC53, and VAMP8 are plotted based on RT-qPCR results. The selected genes encode representative markers of the cross-presentation process. (C) The protein expression was assessed with western blotting of peptide-loading complex components (ERp57, CRT, TPN, β2M) and GAPDH for loading control on TLR4 WT (left) and TLR4 KO (right) iBMDMs. (D) The phagocytosis on EO771 and 4T1 cells by TLR4 WT iBMDM and TLR4 KO iBMDM were assessed with flow cytometry. (E–H) PTX was treated for 48 hours on TLR4 WT or KO iBMDMs, and OVA-peptide was added 24 hours after initial PTX treatment. (E) The PTX concentration-dependent cross-presentation enhancement was analyzed. 0.01–10 µM PTX was treated for 48 hours on TLR4 WT iBMDMs, and OVA-peptide was added 24 hours after initial PTX treatment (n=3). On TLR4 KO iBMDMs, 10 µM PTX was treated, and the antigenic peptide was added accordingly (n=3). (F) TLR4 dependency of PTX treatment on antigen cross-presentation (n=6). The positive control for elevation of cross-presentation was tested utilizing LPS treatment, which was diminished on TAK-242 (TLR4 blockade) pre-treatment. (G) TLR4 dependency of PTX treatment on antigen cross-presentation. iBMDMs were pretreated with either TAK-242 or anti-TLR4 antibody for 24 hours prior to exposure to PTX and an ovalbumin (OVA)-peptide challenge. Representative histogram illustrating the distribution of OVA-bound H2Kb expression on treated iBMDMs. (H) The quantitation of secreted IFN-γ from OVA-peptide-challenged splenic CD8+ T cells from OT-1 mice (n=4). Post 24 hours or 48 hours of PTX treatment, TLR4 WT or KO iBMDMs were coincubated with CD8+ T cells and OVA-peptide. The supernatants were collected and analyzed after 72 hours of the OVA-peptide challenge. Each column displays group means with individual data points and error bars with SEM. Statistical significance was determined using Student’s unpaired two-tailed t-test (B, D, right of E) or one-way ANOVA followed by Tukey’s multiple comparison test (left of E, F, H). P values indicate significant differences (*p<0.05; **p<0.01; ***p<0.001). ANOVA, analysis of variance; WT, wild type.

To explore if enhanced cross-presentation by PTX is mediated through TLR4, we observed upregulation of TLR4 signaling pathway related genes (online supplemental figures 4 and 5A,B) and used TLR4 KO iBMDM for further investigation. In TLR4 WT iBMDMs, PTX induced an increase in proteins associated with MHC1 antigen loading, an effect deficient in TLR4 KO iBMDMs (figure 2C and online supplemental figure 5B). Phagocytosis and antigen cross-presentation assays showed that the enhanced cancer cell phagocytosis and antigen cross-presentation observed in PTX-treated TLR4 WT iBMDMs were prevented in TLR4 KO iBMDMs (figure 2D,E and online supplemental figure 6A). PTX exhibited cross-presentation enhancing capabilities similar to that of the TLR4 agonist lipopolysaccharide (LPS) treatment. This effect was abolished on treatment with the TLR4 inhibitor or TLR4 antibody (figure 2F,G and online supplemental figure 6B). Consistent with previous studies showing PTX induces maturation of dendritic cells (DCs) with increased CD86 expression,²⁴ we noted a significant rise in CD86 expression in PTX-treated iBMDMs (online supplemental figure 6C). Furthermore, PTX-treated iBMDMs significantly enhanced IFN-γ production in CD8+ T cells during coincubation, indicating an improved cross-priming ability of iBMDMs due to PTX treatment (figure 2H). These results suggest that PTX stimulates cross-presentation in TAMs through a TLR4-dependent pathway, leading to the activation of CD8+ T cells.

PTX enhances antitumor CD8+ T cell immunity by amplifying cross-presentation in TAM via TLR4 signaling

Based on the enhanced cross-presentation and CD8+ T cell activation by PTX treatment to iBMDM, we evaluated the antitumor effect of intravenously administered PTX and its relation to TLR4 using TLR4 KO EO771 TNBC mouse model (figure 3A). Systemic PTX administration manifested significant antitumor effects in TLR4 WT mice without notable toxicity (figure 3B and online supplemental figure 7A,B). In contrast, the antitumor efficacy of PTX was reduced in TLR4 KO mice (figure 3B and online supplemental figure 7B). Subsequent analysis using flow cytometry analysis revealed an increase in MHC1 expression in TAMs and a CD8+ T cell population within the TME of PTX-treated TLR4 WT mice (figure 3C and online supplemental figures 8 and 9A–C). These effects of PTX were not observed in the PTX-treated TLR4 KO mice (figure 3C). Consistent with these observations, it was verified that the cross-priming ability of TAMs extracted from the TME from the PTX-treated group was enhanced in a TLR4-dependent manner (figure 3D). Coherent with findings from iBMDM in vitro (figure 2A), transcriptomic analysis on TAMs in TME from TLR4 WT mice indicated that systemic PTX treatment significantly upregulated phagocytosis and antigen presentation-associated genes (figure 3E). Furthermore, multiplex immunohistochemistry (IHC) demonstrated an increased frequency of MHC1+ TAMs and CD8+ T cells in PTX-treated TNBC TME compared with the control group (figure 3F,G). Since DCs serve as professional antigen-presenting cells, we compared the response of DCs and TAMs in the EO771 WT tumor model to PTX. Flow cytometric analysis revealed that TLR4, a receptor for PTX, is expressed at a lower level in DCs compared with TAMs, suggesting that TAMs respond more effectively to PTX (online supplemental figure 9D). In addition, the administration of PTX did not increase the expression of MHC1 and CD86 in in DCs (online supplemental figure 9E,F). Overall, these results suggest that PTX enhances the cross-presentation capabilities of TAMs in TNBC in vivo, leading to an augmented CD8+ T cell-mediated antitumor response.

Figure 3. Paclitaxel (PTX) enhances antitumor CD8+ T cell immunity by amplifying cross-presentation in tumor-associated macrophag (TAM) via toll-like receptor 4 (TLR4) signaling. (A) EO771 tumor-bearing orthotopic C57BL/6 or TLR4 KO mice were intravenously treated with PTX or control vehicle (CTRL) five times after tumor size reached 50–80 mm³. (B) The tumor size of TLR4 WT mice (left) (n=16 or 17) and TLR4 KO mice (right) (n=5) were measured every other day from the initial injection day (D 0). (C) The tumor tissues of TLR4 WT mice (n=5) (left) and TLR4 KO mice (n=3) (right) were acquired on day 10, and tumor microenvironment (TME) was assessed at the cellular level via flow cytometry. (D) TAMs from TLR4 WT mice (left) or TLR4 KO mice (right) were isolated from the acquired tumor tissue and coincubated 72 hours with naive CD8+ T cells from non-tumor bearing mice. IFN-γ secretion was measured from the supernatant (n=3). TAMs from three mice were pooled and analyzed. (E) mRNA expression profile of TAMs from PTX treated or non-treated tumors of TLR4 WT mice were assessed through transcriptome sequencing. TAMs from four to six mice were pooled for analysis, and each sample are represented by each row. The identical gene sets in figure 2A were used as representative data. (F–G) Multiplex immunohistochemistry (IHC) staining of TME from the acquired tumor tissue. (F) Immune cell frequency per area (mm²) were quantified using Inform software and R statistical analysis (n=3). (G) Representative images of multiplex IHC. Each data point indicates means with error bars for SEM (B) or each column displays group means with individual data points and error bars with SEM (C, D, F). Statistical significance was determined using Student’s unpaired two-tailed t-test (C, D, F), or evaluated with tumor volumes at day 10 postinitial injection (B). P values indicate significant differences (*p<0.05; **p<0.01; ***p<0.001).

PTX amplifies the antitumor effects of PD-1 blockade in TNBC through TLR4-dependent mechanisms

To ascertain whether the antitumor efficacy of PTX depends on CD8+ T cell immunity induced by enhanced cross-presentation in TAMs, we evaluated the antitumor effects of PTX in TNBC using mice depleted of TAMs, CD4+ T cells, or CD8+ T cells (figure 4A and online supplemental figure 10). While the antitumor effects of PTX persisted in mice depleted of CD4+ T cells, these effects were abrogated with TAMs or CD8+ T cell depletion, emphasizing the TAM-CD8+ T cell immunity-dependent antitumor effect of PTX (figure 4B and online supplemental figure 11). Despite PTX-induced CD8+ T cell-dependent antitumor effects in TNBC, the efficacy of PTX monotherapy was limited. As CD8+ T cell infiltrates, tumor cells upregulate programmed death-ligand 1 (PD-L1) expression in response to IFN-γ secreted by CD8+ T cells, subsequently inhibiting CD8+ T cells. It is also known that immune and endothelial cells upregulate PD-L1 in response to CD8+ T cell infiltration.²⁵ Furthermore, PD-L1 expression on myeloid cells within the tumor has been reported to be crucial for PD-1 response.²⁶ Multiplex IHC analyses revealed a substantial increase in PD-L1 expression on myeloid cells within PTX-treated TNBC tumors, with an increased frequency of PD-L1+myeloid cells (figure 4C,D). We then assessed whether combining PTX with PD-1 blockade could yield superior antitumor effects compared with either treatment alone using the same TNBC model (figure 4E). While PD-1 monotherapy failed to elicit significant antitumor effects, an administration of PTX combined with PD-1 blockade induced remarkable antitumor responses (figure 4F and online supplemental figure 7C). This efficacy was significantly diminished in TLR4 KO mice (figure 4F and online supplemental figure 7C). Further, the combination treatment of PTX and PD-1 significantly improved survival rates in the TNBC tumor model compared with monotherapy (figure 4G). To verify the reproducibility of our findings, we replicated the experiment using the 4T1 orthotopic TNBC model. Administration of PTX elicited significant antitumor responses in the 4T1 model (online supplemental figure 12A,B). Consistent with results from the EO771 tumor model, TLR4 expression was higher in TAMs compared with DCs in the TME of the 4T1 model (online supplemental figure 12C). Additionally, the upregulation of MHC1, CD86, CD80, and CD40—markers indicative of the maturation and activation of DCs and TAMs—was observed to be greater in TAMs than in DCs (online supplemental figure 12D). Advancing our exploration, the combination therapy of PTX and PD-1 antibodies demonstrated statistically better efficacy compared with monotherapy in the murine 4T1 implanted model (online supplemental figure 12E–G). These findings underscore the potential applicability of PTX and PD-1 blockade as a combinatorial therapeutic strategy across diverse TNBC settings. Our findings also highlight the potential of combining PTX with PD-1 blockade to amplify potent antitumor immune responses and underscore the central role of TLR4-dependent cross-presentation within TAMs in mediating these effects.

Figure 4. Paclitaxel (PTX) amplifies the antitumor effects of PD-1 blockade in triple-negative breast cancer (TNBC) through toll-like receptor 4 (TLR4)-dependent mechanisms. (A) EO771 tumor-bearing mice were intraperitoneally injected with clodronate liposome (CLO) for TAM depletion. The control liposome (Con) was injected for comparison. For CD8+ or CD4+ T cell depletion, an anti-mouse CD8 or CD4 antibody was injected as the described schedule. (B) The tumor growth suppression of PTX was abrogated when tumor-associated macrophage (TAM) was depleted at EO771 tumor-bearing mice (n=6) (left). CD8+ T cell depletion abolished PTX-induced antitumor efficacy, which was retained on CD4+ T cell depletion (n=6 or 8) (right). (C–D) Multiplex immunohistochemistry (IHC) staining of TME from the acquired tumor tissue. (C) Representative multiplex IHC images of TME from control and PTX-treated mice. (D) PD-L1 expression profile of TME on PTX treatment was quantified through Inform & R, assessed by the cell count per area (mm²) of PD-L1+ myeloid cells in TME (left) (n=3) and the mean fluorescence intensity (MFI) of PD-L1 from total myeloid cells (right) (n=3). (E) The PTX and αPD-1 treatment combination was analyzed on EO771 tumor-bearing mice. PTX was injected accordingly, and αPD-1 was intraperitoneally injected on day 2, day 4, day 6, and day D 8. (F) The tumor volume of EO771 tumor-bearing mice on PTX and αPD-1 treatment was measured every other day from the day of initial injection on TLR4 WT (n=6) (left) and TLR4 KO (n=5) (right) mice. (G) The survival rate of EO771 tumor-bearing mice on PTX and αPD-1 treatment was monitored for 16 days (n=10). Representative images of multiplex IHC. Each data point indicates means with error bars for SEM (B, F) or each column displays group means with individual data points and error bars with SEM (D). Statistical significance was determined using Student’s unpaired two-tailed t-test (D), evaluated with tumor volumes at day 10 postinitial injection (B, F), or determined using Mantel-Cox test. P values indicate significant differences (*p<0.05; **p<0.01; ***p<0.001). (H) Schematic illustration of immunotherapeutic effect by enhancing antigen cross-presentation of TAM with PTX treatment combined with αPD-1. The schematic was created with BioRender.com.

Discussion

Our study in TNBC has revealed a critical mechanism where PTX, acting through TLR4 signaling, significantly enhances the cross-presentation capabilities of TAMs. These findings highlight that the immunotherapeutic efficacy of PTX is primarily derived from its modulation of TAM functions, particularly via TLR4-dependent enhancement of TAM cross-presentation, thereby bolstering CD8+ T cell-mediated immunity. Notably, our systemic administration of PTX in TNBC models demonstrates that its antitumor effects rely on the interplay between TAMs and CD8+T cells. Moreover, despite an increase in tumor-infiltrating CD8+ T cells following PTX monotherapy, the effectiveness is limited by PD-L1 expression in myeloid cells. Consistent with clinical outcomes, combination therapy of PD-1 blockades and PTX in TNBC animal models showed significant antitumor efficacy and a meaningful increase in survival rates, with these effects being diminished in TLR4 KO mice. These results emphasize the primary role of TAM function modulation in inducing tumor-specific CD8+ T cell immunity as the main mechanism of antitumor immunity of PTX and elucidate the superior efficacy mechanism of combined PTX and PD-1 blockade therapy observed in clinical settings.

It is well known that PD-L1 expression in various tumors, including TNBC, is an insufficient biomarker for predicting the therapeutic efficacy of PD-1 blockade.²⁷ Our findings illuminate that the enhancement of cross-presentation via TLR4 signaling in TAMs is a key factor in increasing the response rate to PD-1 blockade. While our study could not verify this due to limitations in the available clinical dataset, it is anticipated that future clinical trials will explore whether biomolecules related to TLR4 and cross-presentation signaling in TAMs post-PTX treatment can serve as crucial biomarkers to predict the response to PD-1 blockade.

Previous studies have reported that TLR4 activation in DCs significantly enhances antigen cross-presentation. For instance, TLR signaling, through the MyD88-IKK2 pathway, modulates the endosomal recycling compartment in DCs. This modulation facilitates the efficient cross-presentation of peptides contained within phagosomes.²⁸ Additionally, TLR4 engagement in DCs is known to mediate a Rab34-dependent reorganization of lysosomal distribution. This reorganization effectively inhibits the fusion of phagosomes and lysosomes, thereby augmenting the cross-presentation of antigens.²⁹ While our study demonstrates that PTX-induced TLR4 signaling activation in iBMDMs and TNBC TAMs escalates tumor antigen cross-presentation, a further detailed exploration into the correlation between TLR4 signaling and cross-presentation within TNBC TAMs remains a critical area for future research.

Several studies have suggested that PTX can affect other participants of the immune response through TLR4 expression, although research specifically addressing cancer is limited. In B cells, activation of TLR4 has been shown to enhance survival, proliferation, and cytokine secretion, thereby promoting B cell-mediated immunity and antibody production.³⁰ Although TLR4 expression in T cells has been documented, its functional role remains largely undefined³¹ Furthermore, intracellular TLR4 has been observed in NK cells, where its activation ex vivo leads to increased cytotoxicity through IFN-γ secretion.³² Although we have validated the differential cross-presentation abilities of TAMs on PTX treatment in the presence and absence of TLR4 ex vivo, the broader impact of PTX-induced TLR4 signaling activation on other cellular components within the tumor milieu warrants further investigation.

Former studies have elucidated that PTX induces apoptosis by targeting microtubules, leading to cell cycle arrest.³³ In ovarian cancer, PTX has been reported to induce immunogenic cell death through the TLR4 signaling pathway.³⁴ Other studies have elucidated that activation of TLR4 signaling in human breast cancer cells can induce chemoresistance, and that overexpression of TLR4 in cancer cells can diminish the antitumor efficacy of PTX.³⁵ This dichotomy indicates that the effects of PTX-TLR4 signaling on cancer cell fate are complex and context-dependent. Furthermore, previous research has reported that metronomic PTX treatment, which involves administering low doses multiple times, can effectively enhance the efficacy of PD-1 blockade.³⁶ Collectively, these findings suggest that accurately delivering PTX at optimal concentrations to specific locations is crucial. Therefore, developing drug delivery systems that effectively target PTX to TAMs in TNBC could not only maximize the immunotherapeutic effects of PTX but also open new horizons in TNBC treatment strategies.

Numerous strategies have been employed to target TAMs due to their significant role in oncogenesis. Predominantly, these strategies have focused on depleting TAM populations or modulating their phenotype from an M2-like protumoral state to an M1-like antitumoral state.37,44 Our research delineates that PTX potentiates the antigen-presenting capacity of TAMs via engagement of the TLR4 receptor. This facilitation results in an amplified response to immune checkpoint blockade therapy. Our findings reveal a novel therapeutic approach that capitalizes on the modulation of TAM functionality, heralding a prospective paradigm in the realm of combinatory cancer immunotherapy.

Data availability statement

All data relevant to the study are included in the article or uploaded as online supplemental information.