ANKRD22 Downregulation Reprograms Lipid Metabolism to Activate the Notch/Hes1 Pathway, Driving Immunosuppressive Macrophage Polarization in Colorectal Cancer

Abstract

Background

Macrophages in colorectal cancer (CRC) are predominantly derived from monocytes, yet the mechanisms by which the tumor microenvironment (TME) regulates their differentiation dynamics and phenotypic commitment remains poorly defined. Although we previously identified ANKRD22 as a macrophage immunomodulator, the regulation of ANKRD22 by the TME and its temporal impact on monocyte‒macrophage differentiation are still unclear.

Methods

We used untargeted metabolomics and cytokine microarrays to identify metabolites and cytokines from CRC cell supernatants that suppress ANKRD22 expression in macrophages. Immune infiltration in tumors was evaluated using cytometry by time-of-flight. The effects of ANKRD22 downregulation on monocyte-to-macrophage differentiation were investigated using scRNA-seq, scATAC-seq, and multiplex immunofluorescence staining.

Results

CRC cell-derived metabolites and cytokines downregulated ANKRD22 expression in macrophages via the p38 MAPK/MAX pathway. Ankrd22-deficient macrophages accelerated subcutaneous tumor growth in mice, promoting the expansion of immunosuppressive CD206⁺CD163⁺ macrophage subsets and decreasing the number of CD8⁺CD44⁺CD62L⁻ effector T cells. ANKRD22 downregulation delayed macrophage differentiation and maturation while increasing monocyte recruitment. Mechanistically, ANKRD22 suppression reduced the level of intracellular fatty acids, which in turn activated the Notch4/HES1 pathway, leading to differentiation arrest and immunosuppressive polarization. This process involved a newly identified early-differentiation immunosuppressive CD9⁺CD127⁺ macrophage subset within the TME. The combined pharmacological inhibition of Notch and long-acting IL-7 expression reversed these phenotypes, attenuated tumor growth, and diminished the CD9⁺CD127⁺ population.

Conclusion

ANKRD22 downregulation reprograms fatty acid metabolism to activate the Notch4/HES1 pathway, promoting immunosuppressive macrophage polarization. ANKRD22 is a key regulator of macrophage plasticity and a promising therapeutic target for reprogramming the immunosuppressive TME in CRC.

Introduction

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death globally.¹ Preventing its occurrence and development has become an urgent clinical problem. As the “soil” for CRC cell survival, the tumor microenvironment (TME) not only regulates the fate and phenotypic plasticity of CRC cells but also affects treatment selection and efficacy.² Therefore, CRC treatments should not only target tumor cells but also remodel the TME.³ A deeper understanding of the cellular and molecular mechanisms that underlie TME remodeling may facilitate the development of novel, multimodal therapies.

Like other TMEs, the CRC microenvironment is a dynamic entity shaped by interactions among immune cells, stromal cells, the extracellular matrix (ECM), and secreted factors centered on tumor cells. It supports immune evasion by spatiotemporally regulating immune checkpoints such as PD-1/PD-L1 and CTLA-4, synergistically inducing regulatory T-cell (Treg) infiltration, myeloid-derived suppressor cell expansion, and effector T-cell depletion.^3,4 Reversing this immunosuppression is therefore crucial for reshaping the CRC TME.

Macrophages, the dominant immune cells infiltrating the CRC TME, bridge innate and adaptive immunity and are key in establishing an immunosuppressive TME.⁵ Most tumor-associated macrophages (TAMs) in CRC originate from peripheral blood monocytes,⁶ which are recruited into the TME and differentiate into TAMs via transcription factors such as IRF8, STAT3, and RBPJ.^7,8 However, the mechanisms that govern monocyte infiltration and differentiation into highly heterogeneous macrophage subsets remain incompletely understood. Emerging evidence suggests that this process is dynamically regulated by both epigenetic mechanisms and tissue-specific microenvironmental cues.^9,10 For instance, Saeed et al demonstrated that epigenetic modifications driven by pattern recognition receptors shape the transcriptional landscape during monocyte-to-macrophage differentiation.¹¹ The heterogeneity of macrophages across tissues further underscores the importance of local microenvironmental signals in guiding differentiation.^12,13 Macrophages exhibit remarkable phenotypic plasticity through metabolic reprogramming, adapting to the varying physicochemical and biological conditions of the TME.¹⁴ Spatial transcriptomics has revealed that tissue-specific signals activate preexisting enhancers and remodel the chromatin architecture to promote macrophage differentiation.¹⁵ Nevertheless, how the TME temporally regulates macrophage differentiation and what key molecular players are involved remain unclear.

TAMs are broadly categorized into proinflammatory M1-like and immunosuppressive M2-like phenotypes, although these subsets often display functional overlap.¹⁶ The mechanisms driving TAM polarization toward an immunosuppressive phenotype have not been fully elucidated. Previous studies have indicated that c-Maf expression promotes M2-like polarization via metabolic reprogramming,¹⁷ whereas the loss of Mcpip1 enhances M1 polarization. Immunosuppressive SPP1⁺ TAMs are associated with angiogenesis and extracellular matrix remodeling, and hypoxic conditions can induce the IL-1β- and VEGF-mediated differentiation of CD14⁺ monocytes into SPP1⁺ TAMs.⁶ Recently, ZEB2 was identified as a master regulator of TAM immunosuppression, dampening type I interferon responses and antigen presentation.¹⁸ The mechanisms through which immature macrophages in the TME acquire immunosuppressive traits still require further exploration.

In our previous work, we identified ankyrin repeat domain-containing protein 22 (ANKRD22) as a TME-responsive protein. ANKRD22 belongs to the ankyrin repeat motif family, contains 191 amino acids with four ankyrin repeats, and is localized to mitochondrial membranes and lipid droplets in macrophages.¹⁹ Its expression is markedly upregulated in classically activated M1 macrophages but is low in M2 macrophages.²⁰ We observed that Ankrd22-knockout mice exhibited enhanced monocyte infiltration into liver and adipose tissue. Furthermore, the differentiation of monocytes from these tissues was delayed (unpublished data), suggesting that ANKRD22 regulates monocyte‒macrophage differentiation. Mitochondrial-mediated metabolic reprogramming can significantly affect the fate and function of macrophages.²¹ Research has indicated that OXR1, located in mitochondria, regulates osteoblast differentiation in mouse models of osteoporosis.²² Combined with our previous research, these findings revealed that the differentiation and function of mitochondria and macrophages are closely related. However, as ANKRD22 is a protein that is specifically located in lipid droplets and mitochondria, how the TME influences ANKRD22 expression and temporal macrophage differentiation in CRC remains unknown.

In this study, we have demonstrated that metabolites derived from CRC cells downregulating ANKRD22 expression in macrophages. This downregulation delays macrophage differentiation and maturation, thereby amplifying immunosuppression in the TME. Mechanistically, this effect is mediated through lipid metabolic reprogramming, which activates the Notch signaling pathway. Our findings reveal a new immunometabolic axis through which CRC cells impede macrophage differentiation and foster an immunosuppressive phenotype, offering potential targets and a theoretical foundation for TAM-directed therapies in CRC.

Materials and Methods

Cell Lines and Culture

The human monocytic leukemia cell line THP-1 (RRID:CVCL_0006), human CRC cell lines (HCT116 (RRID:CVCL_0291), DLD-1 (RRID:CVCL_0248), and RKO (CVCL_0504)), and mouse cell lines (MC38 (RRID:CVCL_B288), CT26 (RRID:CVCL_7254), and RAW264.7 (RRID:CVCL_0493)) were obtained from the Shanghai Cell Bank of the Chinese Academy of Sciences. All the cell lines were confirmed to be mycoplasma free. THP-1, HCT116, DLD-1, and CT26 cells were cultured in RPMI 1640 medium. MC38 and RAW264.7 cells were maintained in high-glucose DMEM, and RKO cells were maintained in MEM. All media contained 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin. The cells were incubated at 37 °C with 5% CO₂ and passaged every 2–3 days. THP-1 cells were treated with 100 ng/mL phorbol 12-myristate 13-acetate (PMA; Sigma, USA) for 24 hours to induce differentiation into macrophages. The direct coculture of macrophages with tumor cells involved direct contact culture, whereas indirect coculture involved the use of Transwell inserts (Corning, #3413, USA).

Mice

C57BL/6 (RRID: IMSR_JAX:000664) and BALB/c (RRID:MGI:2683685) mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). All animal procedures were approved by the Clinical Medical Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine (No. 2023–148) and the Medical Animal Ethics Committee of Zhejiang Chinese Medicine University (No. IACUC-20210628-07) in compliance with international guidelines. All the mice were housed under specific pathogen-free (SPF) conditions at the Animal Experimental Center of Zhejiang Chinese Medical University (25 ± 3 °C, 30–70% humidity, 12 h light/dark cycle) with free access to food and water. For tumor experiments, an endpoint of 2000 mm³ was established. The study complies with the Guide for the Care and Use of Laboratory Animals.

Ankrd22⁻/⁻ mice on a C57BL/6 background were generated by targeting exon 2 of the Ankrd22 gene (NCBI: NM_024204.6) via CRISPR/Cas9-mediated knockout. Cas9 mRNA and guide RNA were microinjected into fertilized eggs. Founders were genotyped by PCR and sequencing, and homozygous knockout mice were established in the F2 generation. The colony underwent annual biological purification. The mice in this study were divided into Ankrd22^−/− and Ankrd22^+/+ groups.

For euthanasia, mice (≤8 per chamber) were placed in a 10-L closed transparent acrylic chamber. The chamber was then filled with 99% CO₂ at a flow rate of 3 L/min for 5–10 minutes. After the exposure period, the CO₂ flow was discontinued. At 2 minutes post-exposure, the mice were assessed for signs of life, including heartbeat, respiration, and responsiveness to external stimuli, until apnea and loss of consciousness are confirmed. Once apnea and the absence of the pedal withdrawal reflex were verified, all the mice were immediately subjected to cervical dislocation as a secondary physical method.

Human Samples

Human CRC and matched distant normal fresh tissues were obtained from the Department of Surgical Oncology, and formalin-fixed, paraffin-embedded (FFPE) sections were obtained from the Department of Pathology. Peripheral blood monocytes were obtained from healthy donors. All of the human samples were provided by the Second Affiliated Hospital of Zhejiang University School of Medicine with patient informed consent and approval from the Clinical Medical Ethics Committee (No. 2024–0732). The study complies with the Declaration of Helsinki.

Isolation of Primary Cells

1. Bone Marrow-Derived Macrophages (BMDMs): Femurs and tibias from euthanized mice were flushed with cold RPMI 1640. The bone marrow suspension was filtered (70 µm) and centrifuged. The cells were resuspended in RPMI 1640 medium supplemented with 10% FBS, 1% penicillin-streptomycin, and 20 ng/mL mouse M-CSF (Novoprotein, China) and cultured for differentiation.

2. Colorectum-Derived Macrophages (CDMs): Mouse colorectal tissue pieces were incubated in HBSS supplemented with 5 mM EDTA and 1 mM DTT at 37 °C to remove epithelial cells. The remaining tissue was minced and digested in HBSS containing 1 mg/mL collagenase IV (Sigma) at 37 °C. The cell suspension was filtered (70 µm) and centrifuged. The lamina propria cell pellet was used for subsequent macrophage purification by fluorescence-activated cell sorting (FACS).

3. Human Tissue Dissociation and Macrophage Isolation: Fresh human CRC tissues were minced and digested in RPMI 1640 containing 1 mg/mL collagenase IV (Sigma) and 1 mg/mL hyaluronidase (Sigma) for 60 minutes at 37 °C. The digested suspension was filtered (70 µm) and centrifuged. CD14⁺ macrophages were isolated from the single-cell suspension using CD14 MicroBeads and an LS column on a magnetic activated cell sorting (MACS) separator (Miltenyi Biotec, Germany).

4. Human Peripheral Blood Monocytes: Monocytes were isolated using a Peripheral Blood Mononuclear Cell Isolation Kit (TBD Science, China), after which human M-CSF (Novoprotein, China) was used to induce the differentiation of monocytes into macrophages.

Exosome Isolation and Purification

CRC tumor cell-derived exosomes were isolated using the Exosome Isolation and Purification Kit (MedChemExpress, USA) according to the manufacturer’s instructions.

Transplanted Tumor Models

MC38 or CT26 cells and macrophages were mixed at a 1:1 ratio, combined with an equal volume of Matrigel (Corning, USA), and subcutaneously injected (100 µL total) into the right axilla of C57BL/6 (MC38 mix) or BALB/c (CT26 mix) mice. The tumor volume was measured every 3 days with calipers and calculated as V = L×W²/2. The sample group consisted of Ankrd22^−/− macrophages, whereas the control group consisted of Ankrd22^+/+ macrophages.

Flow Cytometry (FCM) and Cell Sorting

Single-cell suspensions were resuspended in PBS supplemented with 2% FBS, incubated with an Fc receptor blocker (BioLegend, USA), and stained with fluorochrome-conjugated antibodies for 30 minutes at 4 °C in the dark. The cells were subsequently washed, filtered (40 µm), and analyzed or sorted on a flow cytometer. The data were analyzed using FlowJo v10.8.1. (RRID:SCR_008520). The following flow cytometry antibodies were used: BODIPY 493/503 (MedChemExpress, USA), Zombie Aqua^TM Dye, PE/Cyanine7 anti-mouse CD45, FITC anti-mouse F4/80, APC/Fire^TM 750 anti-mouse F4/80, PerCP/Cyanine5.5 anti-mouse CD9, PE anti-mouse CD9, Brilliant Violet 421TM anti-mouse CD127, PE anti-mouse Arginase1, APC anti-mouse CD206, PE/Cyanine7 anti-human CD45, APC anti-human CD68, FITC anti-human CD9, PE anti-human CD127, and Brilliant Violet 421TM anti-human CD14 (BioLegend).

Cytometry by Time-Of-Flight (CyTOF)

Single-cell suspensions were stained with cisplatin viability stain, blocked, and stained with a surface antibody cocktail. Cells were fixed overnight in MaxPar^® Fix and Perm Buffer containing an Ir intercalator, followed by intracellular staining. The cells were subsequently washed and resuspended in EQ™ Four Element Calibration Beads solution before acquisition on a CyTOF instrument (R&D, USA). The data were debarcoded, normalized, and analyzed. Manual gating in FlowJo excluded debris and doublets. The X-shift algorithm was used for clustering, and t-SNE was used for dimensionality reduction.

Multiplex Immunohistochemical Staining (mIHC)

For this purpose, 4 µm thick FFPE sections were stained sequentially with primary antibodies paired with a TSA 6-color kit (Yuanxibio, China) and counterstained with SN470 (Yuanxibio). The antibody panel included anti-CD68 (Biolynx, China)/TSA 440, anti-CD9 (HUABIO, China)/TSA620, anti-CD127/TSA520 (HUABIO), anti-osteopontin (Abcam, UK), anti-CD68/TSA 480, and anti-arginase-1 (Cell Signaling Technology, USA) antibodies. Slides were scanned using a Pannoramic MIDI imaging system.

Western Blot

Cells were lysed in RIPA buffer supplemented with protease inhibitors (Sigma). The lysates were boiled in loading buffer, separated by SDS‒PAGE, and transferred to nitrocellulose membranes (Cytiva). The membranes were blocked with 5% nonfat milk and incubated with primary antibodies overnight, after which they were incubated with HRP-conjugated secondary antibodies (Jackson ImmunoResearch, USA). The signals were detected using chemiluminescence. The primary antibodies used were as follows: p38 MAPK, phospho-p38 MAPK, Mad-1, MAX, HES1, and Jagged1 (Cell Signaling Technology) and GAPDH and β-Tubulin (HUABIO).

RNA Extraction and Quantitative RT‒PCR (RT‒qPCR)

Total RNA was extracted using NucleoZOL (Macherey-Nagel, Germany) and reverse-transcribed into cDNA using a kit (Takara, Japan). RT‒qPCR was performed using Premix Ex Taq™ (Probe qPCR) (Takara) on a CFX96 Connect system (Bio-Rad, USA). The primer sequences are listed in Supplementary Table 1.

Chromatin Immunoprecipitation (ChIP)

ChIP assays were performed on PMA-differentiated THP-1 cells using the SimpleChIP Plus Enzymatic Chromatin IP Kit (Cell Signaling Technology). Cells were crosslinked with 1% formaldehyde. Chromatin was immunoprecipitated using an anti-MAX antibody (Abcam) or control IgG. Precipitated DNA was purified and analyzed by qPCR with primers specific to the ANKRD22 upstream region. Input, anti-Histone H3, and normal rabbit IgG samples served as controls.

Metabolomics Analysis

Metabolomic analysis was performed on the supernatant from CRC cells. Nontargeted metabolomics was performed by LC-Bio Technologies. The supernatant was analyzed by UPLC (UltiMate 3000 system with an ACQUITY UPLC T3 column) coupled to a Q Exactive mass spectrometer. The raw data were processed using XCMS (RRID:SCR_015538) and analyzed with R software (v4.0.0). The threshold for differential metabolites is: FC ≥1.2 with p value < 0.05.

Spatial Transcriptomics

FFPE human CRC tissue sections were processed by Shenzhen Yuce Biotechnology (Shenzhen, China). After target RNA exposure, in situ hybridization was performed using a Whole Transcriptome Atlas probe set. Slides were stained with morphological markers and scanned, and regions of interest were selected. Oligonucleotide tags from these regions were released by UV light, collected, and used to construct sequencing libraries for the Illumina platform. Differential gene expression analysis was performed using edgeR (v3.34.0), with the following thresholds applied: false discovery rate < 0.05 and absolute |Log₂FC| > 1.

Single-Cell RNA Sequencing (scRNA-Seq)

scRNA-seq was performed on CD45⁺CD11b⁺/F4/80⁺ cells sorted from tumors by FACS. scRNA-seq was conducted by LC-Bio Technologies (Hangzhou, China). Libraries were prepared using the 10× Genomics Chromium Single-Cell 3′ Kit (V3) and sequenced on an Illumina NovaSeq 6000 platform (10× Genomics, USA). The raw data were processed with Cell Ranger to align the reads to the reference genome and generate feature-barcode matrices. Downstream analysis, including quality control (genes/cell >500, mitochondrial ratio <25%), dimensionality reduction (UMAP/t-SNE), and clustering, was performed in Seurat (v4.1.0) in R. Marker genes were selected based on the following criteria: p value < 0.05, |Log₂FC| ≥ 0.26, and expression in more than 10% of cells in each cluster.

Single-Cell Assay for Transposase-Accessible Chromatin Sequencing (scATAC-Seq)

scATAC-seq was conducted by LC-Bio Technologies. Nuclei were isolated from single-cell suspensions and tagmented with transposase to fragment open chromatin. Barcoded libraries were prepared using the 10× Genomics platform and sequenced on an Illumina system. Sequencing reads were aligned to the reference genome using BWA-MEM2 (RRID:SCR_022192), and the data quality was assessed before downstream bioinformatic analysis. Peaks were annotated by genomic position (eg, promoter, intronic, distal), and motif enrichment analysis was conducted on marker peaks to identify cell type-specific and condition-specific motifs, using stringent criteria (|Log₂FC| > 0.5, p value < 0.05).

Statistical Analysis

The data are presented as the mean ± standard error of the mean (SEM). Statistical analyses were performed using GraphPad Prism 9.0 (RRID:SCR_002798). Each experiment was conducted 3 times in independent repetitions. Comparisons between two groups were made using Student’s t test. Comparisons among multiple groups were analyzed by one-way or two-way ANOVA. A P value < 0.05 was considered to indicate statistical significance.

Results

CRC Cells Downregulated the Expression of ANKRD22 in Macrophages Through the p38 MAPK/MAX Pathway via a Variety of Paracrine Substances

As the dominant tumor-infiltrating immune cells, macrophages play a key role in the development of CRC.²³ To assess the expression of ANKRD22 in macrophages in CRC tissues, we isolated CD14⁺ macrophages from paired human CRC and adjacent normal tissues with anti-CD14 magnetic beads. RT‒qPCR revealed that ANKRD22 expression was significantly downregulated in CRC-derived macrophages (Figure 1A).

Figure 1.

CRC cell-derived exosomes, metabolites and cytokines downregulate the expression of ANKRD22 in macrophages through the p38 MAPK/MAX pathway. (A) ANKRD22 mRNA expression determined by RT‒qPCR in CD14⁺ macrophages isolated from CRC tissues and paired adjacent normal tissues by MACS. (B) ANKRD22 mRNA levels in THP-1 cells treated for 24 h with conditioned medium (CM) from HCT116, DLD-1, or RKO cells. (C) Ankrd22 mRNA expression in BMDMs treated with MC38 cell CM for 24 h. (D and E) Ankrd22 mRNA levels in BMDMs after indirect (D) or direct (E) coculture with MC38 cells for 24 h. (F) Ankrd22 mRNA expression in BMDMs treated for 24 h with MC38 cell-derived exosomes or a metabolic mixture upregulated. (G) Heatmap of metabolites in the supernatants of HCT116 and MC38 cells. The red gradient indicates an upregulation of metabolites, while the blue gradient indicates a downregulation. (H) Heatmap of cytokines upregulated in the supernatants of HCT116 and MC38 cells. The red gradient indicates an upregulation of cytokines, while the blue gradient indicates a downregulation. (I) ANKRD22 mRNA levels in THP-1 cells treated with 100 μΜ NAS, 5 μΜ 25-HC, or 10 ng/mL 3-HBE for 24 h. (J) ANKRD22 mRNA levels in THP-1 cells treated for 24 h with 10 ng/mL CXCL1, CXCL5, CXCL10, CXCL16, or CCL11.(K) Western blot analysis of p38 MAPK/MAX pathway activation in THP-1 cells treated for 24 h with exosomes (from 1×10⁷ HCT116 cells), 100 μΜ NAS or 5 μΜ 25-HC. (L) Western blot analysis of p38 MAPK/MAX pathway activation in THP-1 cells treated for 24 h with 10 ng/mL CXCL5, CXCL10, or CCL11. (M) ANKRD22 mRNA levels in THP-1 cells treated for 24 h with HCT116 exosomes, 25-HC or NAS, with or without 10 μΜ p38 MAPK inhibitor SB 202190. (N) Luciferase reporter assay of ANKRD22 promoter activity in MAX-transfected THP-1 cells. (O) ChIP-qPCR analysis of MAX binding to the ANKRD22 promoter in THP-1 cells. All the experiments were performed with n=3 biological replicates. The data are presented as the mean ± SEM. ns: not significant; **P < 0.01; ***P < 0.001; ****P < 0.0001 by Student’s t test (A, C, D, E and O) or one-way ANOVA (B, F, I, J, M and N).

To further explore how ANKRD22 is downregulated in macrophages, we first treated macrophages with culture supernatants from human and mouse CRC cells, and the results revealed that the expression of ANKRD22 in macrophages was significantly downregulated (Figure 1B and C). Next, we cocultured BMDMs with MC38 cells directly or indirectly, and Ankrd22 expression in BMDMs was also significantly downregulated (Figure 1D and E). Finally, RT‒qPCR revealed that both exosomes and metabolites isolated from MC38 cell supernatant downregulated Ankrd22 expression in BMDMs (Figure 1F).

To identify key supernatant components, we identified metabolites and secreted cytokines in CRC cell-derived supernatants. First, untargeted metabolomics revealed 10 metabolites whose levels were consistently elevated in the HCT116 and MC38 cell supernatants (Figure 1G and Figure S1A, B). Next, cytokine microarray analysis revealed that the levels of 7 cytokines increased in both cell lines (Figure 1H and Figure S1C, D). Furthermore, we selected several representative cytokines and metabolites for further validation. Subsequent validation revealed that the metabolites N1-acetylspermidine (NAS) and 25-hydroxycholesterol (25-HC) derived from CRC cells significantly downregulated ANKRD22 expression in THP-1 cells, whereas ethyl 3-hydroxybutyrate (3-HBE) had no significant effect (Figure 1I). Similarly, cytokines, including CXCL1, CXCL5, CXCL10, and CCL11, derived from CRC cells significantly downregulated ANKRD22 expression in THP-1 cells, whereas CXCL16 did not significantly affect ANKRD22 expression (Figure 1J).

Given our prior finding that the p38 MAPK/MAX pathway regulates the expression of ANKRD22 in CRC cells,²⁴ we investigated whether it also participates in the downregulation of ANKRD22 expression induced by representative metabolites and cytokines. The results demonstrated that these exosomes, metabolites and cytokines activated the p38 MAPK pathway and significantly decreased the expression of the downstream transcription factor MAX (Figure 1K and L).

Furthermore, after the p38 MAPK pathway was inhibited, ANKRD22 expression in THP-1 cells treated with exosomes, NAS and 25-HC was restored to the original level (Figure 1M). Next, a luciferase reporter assay involving the promoter region of ANKRD22 revealed that cotransfection with MAX significantly increased luciferase activity (Figure 1N). Chromatin immunoprecipitation followed by quantitative PCR (ChIP‒qPCR) confirmed that MAX bound to the ANKRD22 promoter region in macrophages (Figure 1O).

Collectively, these results suggest that CRC-derived exosomes, metabolites and cytokines downregulate the expression of ANKRD22 in macrophages through the p38 MAPK/MAX pathway.

ANKRD22-Deficient Macrophages Drive the Formation of an Immunosuppressive TME in CRC

To explore the functional role of macrophages with downregulated ANKRD22 expression in tumors, we generated Ankrd22^−/− mice with CRISPR-Cas9 and gRNA gene knockout (Figure S2A, B). CDMs were isolated from Ankrd22^−/− and Ankrd22^+/+ mice. A subcutaneous tumor model was then established by coimplanting these macrophages with CRC cells. The results revealed that the size and weight of the tumors in the Ankrd22^−/− group significantly increased (Figure 2A–C). Similarly, similar results were obtained for BMDMs from Ankrd22^−/− mice (Figure S2C-H). Immunohistochemical staining for CD31 and Ki-67 revealed that the microvessel density and number of Ki-67⁺ cells significantly increased in the Ankrd22^−/− group of tumor tissues mixed with CDMs and CT26 cells (Figure 2D–F). Moreover, CyTOF analysis revealed that the proportion of CD8⁺CD44⁺CD62L⁻ T cells within tumors from the Ankrd22^−/− group decreased (Figure 2G–I and Figure S2I), whereas the proportion of CD206⁺CD163⁺ M2-like macrophages (C18) increased (Figure 2J and K). Finally, FCM confirmed that the proportion of CD206⁺ macrophages was significantly greater in tumors from Ankrd22^−/− mice (Figure 2L and Figure S2J), whereas the percentage of CD206+ cells was not significantly different between Ankrd22^+/+ and Ankrd22^−/− mice before inoculation (Figure S2K). These results suggest that ANKRD22 loss drives immunosuppressive macrophage polarization, thus promoting immunosuppressive TME formation.

Figure 2.

ANKRD22-deficient macrophages drive the formation of an immunosuppressive tumor microenvironment in CRC. (A) Subcutaneous tumors in BALB/c mice 14 days after coimplantation with CT26 murine colon cancer cells (5×10⁶) and CDMs (5×10⁶) from Ankrd22^−/− and Ankrd22^+/+ mice. n = 4. (B) Tumor growth curves. n = 4. (C) Tumor weight at the endpoint. n = 4. (D) Representative immunohistochemical staining for CD31 and Ki-67 in tumor sections. (E) Microvessel density quantified by CD31 staining. n = 3. (F) Percentage of Ki-67-positive cells. n = 3. (G–K) CyTOF analysis of single-cell suspensions from subcutaneous tumors. n = 3. G. t-SNE visualization of tumor-infiltrating immune cells. (H) t-SNE plot annotated by immune cell type. (I) Proportion of CD8⁺CD44⁺CD62L⁻ effector T cells. (J) t-SNE plots showing macrophage clusters in the Ankrd22^−/− and Ankrd22^+/+ groups. The red circle represents macrophages. (K) Expression of CD206 and CD163 in macrophages visualized by t-SNE. (L) Proportion of CD206⁺ macrophages among total macrophages measured by FCM. n = 3. The data are presented as the mean ± SEM. *P < 0.05, ****P < 0.0001 by Student’s t test (C, E, F, I and L) or two-way ANOVA (B).

ANKRD22-Deficient Macrophages Enhance Monocyte Recruitment and Differentiation via CCL-Receptor Interactions and ECM Remodeling

To further investigate how Ankrd22^−/− macrophages promote an immunosuppressive microenvironment, we performed scRNA-seq on CD45⁺CD11b⁺/F4/80⁺ cells sorted from tumors by FACS. Clustering identified 24 subsets. On the basis of marker genes, Clusters 0, 1, 3, 4, 6, 7, 10, and 11 were identified as macrophage subsets (Figure S3-1A, B). We reclustered macrophages and distinguished exogenously injected CDMs from peripheral blood monocyte-derived macrophages (MoMacs) recruited during tumor growth by sex-associated gene Xist expression (Figure 3A and B). Compared with control CDMs, significantly more MoMacs were recruited to tumors containing Ankrd22^−/− CDMs (Figure 3C and Figure S3-2A-E). This enhanced recruitment was further confirmed using PKH-26-labeled macrophages mixed with CT26 cells in a subcutaneous tumor mouse model. The proportion of PKH-26⁺ cells among macrophages in subcutaneous tumors was significantly greater in Ankrd22^+/+ control mice (Figure 3D), indicating greater dilution by recruited MoMacs in the Ankrd22^−/− group. Similarly, in vitro assays demonstrated that Ankrd22^−/− macrophages possessed superior monocyte recruitment capacity, which was significantly inhibited by blocking CCR1/2/5 (Figure 3E and Figure S3-1C), confirming the enhanced ability of these cells to recruit peripheral blood monocytes.

Figure 3.

ANKRD22-deficient macrophages enhance monocyte recruitment and differentiation via CCL-receptor interactions and ECM remodeling. (A) scRNA-seq analysis of CD45⁺CD11b⁺F4/80+ cells isolated by FACS from subcutaneous tumor single-cell suspensions in the Ankrd22^−/− and Ankrd22^+/+ groups. Cells were pooled from 4 mice per group. t-SNE visualization of macrophage subsets. (B) t-SNE plot indicating macrophage origin on the basis of Xist expression. (C) Relative abundance of CDMs and monocyte-derived macrophages (MoMacs) in subcutaneous tumors. (D) Proportion of PKH-26⁺ cells among macrophages in subcutaneous tumors formed by the coinjection of PKH-26-labeled CDMs and CT26 cells, as measured by FCM. n = 5. (E) In vitro macrophage recruitment was assessed by a Transwell assay. Mouse BMDMs were seeded in the upper chamber, with Ankrd22^−/− or Ankrd22^+/+ BMDMs in the lower well. After 24 h, the migrated cells were stained with crystal violet and counted across 5 random fields. n = 3. (F) Ro/e analysis of CDM subsets from scRNA-seq data, showing enrichment of cluster 0 in the Ankrd22^−/− group. [Ro/e > 1]: +++; [0.8 < Ro/e≤1]: ++; [0.2≤Ro/e≤0.8]: +. (G) Inflammation-promoting scores for CDM subsets. The gene sets are listed in Supplementary Box S1. (H) M1 and M2 gene set enrichment scores per CDM subset. The gene sets are listed in Supplementary Box S1. (I) GSEA of “Pathways in Cancer” in CDMs from the Ankrd22^−/− and Ankrd22^+/+ groups. (J) Ro/e analysis of major MoMac subsets. (K) Inflammation-promoting scores for MoMac subsets calculated using AddModuleScore. (L and M) GSEA of “Pathways in Cancer” (L) and “Colorectal Cancer” (M) in MoMacs from the Ankrd22^−/−vs Ankrd22^+/+ groups. (N) Heatmap of differentially expressed cytokines in CDMs between the Ankrd22^−/− and Ankrd22^+/+ groups. (O) Significantly altered receptor‒ligand pairs between the Ankrd22^−/− and Ankrd22^+/+ groups in Cluster 0 of the CDM and MoMac subsets. The dot size indicates the p value, and the color indicates the communication probability. (P) Heatmap of intercellular outgoing communication pattern recognition of CDMs and MoMacs. The data are presented as the mean±SEM. ***P< 0.001 by Student’s t test (D); **P < 0.01 vs the Ankrd22^+/+ control; ^&&P < 0.01, ^&&&P < 0.001 vs the Ankrd22^−/− control by two-way ANOVA (E).

Are both CDMs and MoMacs involved in the formation of the immunosuppressive microenvironment in CRC? To this end, we reclustered CDMs from CDM tumors and determined that the proportion of Cluster 0 CDMs was increased in the Ankrd22^−/− group (Figure 3F and Figure S3-1D). Gene set scoring revealed that Cluster 0 exhibited an inflammation-suppressive phenotype and a bias toward an M2-like state (Figure 3G and H). Gene set enrichment analysis (GSEA) revealed that tumor-related pathways were enriched in the Ankrd22^−/− group (Figure 3I). These findings suggest that Ankrd22^−/− macrophages have anti-inflammatory and protumor functions. Finally, the results of the clustering and gene set analyses of the recruited MoMacs also revealed that MoMac_Cluster 1 displayed phenotypic alterations similar to those of CDM_Cluster 0 (Figure 3J–M and Figure S3-1E), a pattern that was also observed in BMDM-derived tumors (Figure S3-2F-M). These findings suggest that Ankrd22^−/− macrophages promote the acquisition of an immunosuppressive phenotype by recruited MoMacs.

To elucidate the underlying mechanisms, we analyzed the levels of CDM-related cytokines in tumors from the Ankrd22^−/− and Ankrd22^+/+ groups, and the results revealed that the levels of Cxcl2, Ccl3, Cxcl1, and Cxcl3 were significantly increased in Ankrd22^−/− CDMs (Figure 3N). Intercellular communication analysis revealed increased activity of CCL-receptor pathways associated with recruitment and significant upregulation of the expression of ECM components (FN1, SPP1, and THBS) in Ankrd22^−/− CDMs, particularly within expanded Cluster 0 (Figure 3O and Figure S3-1F). Similar alterations occurred in the BMDM tumors (Figure S3-2N, O). The recognition patterns of extracellular communication revealed that MoMac_Cluster 1 and Ankrd22^−/− CDM_Cluster 0 shared similar communication profiles characterized by upregulated CCL, FN1, SPP1, and THBS expression (Figure 3P).

Collectively, these results demonstrate that ANKRD22 deficiency in macrophages enhances peripheral blood monocyte recruitment via CCL-receptor interactions and ECM remodeling. Furthermore, it promotes the differentiation of recruited MoMacs into immunosuppressive macrophages with similar phenotypes and communication patterns, creating an amplification loop that significantly increases immunosuppressive macrophage infiltration within tumors.

ANKRD22 Deficiency Delays Monocyte-to-Macrophage Differentiation Kinetics in Tumors

While our findings demonstrate that Ankrd22^−/− macrophages recruit peripheral blood monocytes, the effect of ANKRD22 expression on monocyte-to-macrophage differentiation kinetics within the TME remains unknown. Given that differentiation is intricately regulated by both the TME and epigenetic factors, we first investigated the differentiation trajectories of Ankrd22^−/− CDMs under physiological conditions. We isolated CD45⁺CD11b⁺/F4/80⁺ cells from the intestines of Ankrd22^−/− and Ankrd22^+/+ mice for scRNA-seq. Cluster analysis revealed 23 subsets, with Clusters 0, 2, 3, 4, 7, 8, 13, 19, and 21 classified as macrophages on the basis of marker genes (Figure S4A, B). Subsequent t-SNE visualization and reclustering of macrophages divided the mouse CDMs into 11 subsets (Figure 4A).

Figure 4.

ANKRD22 deficiency delays monocyte-to-macrophage differentiation in tumors. (A) scRNA-seq analysis of CD45⁺CD11b⁺F4/80⁺ cells isolated from colorectal lamina propria single-cell suspensions from Ankrd22^−/− and Ankrd22^+/+ mice by FACS. Cells were pooled from 5 mice per group. t-SNE visualization of macrophage subsets. (B) CytoTRACE analysis for predicting the differentiation states of CDMs. The color intensity corresponds to differentiation status (darker = less differentiated; left) and is overlaid on single-cell subsets (right). (C) CytoTRACE scores for all CDM clusters. Higher scores indicate less differentiated states. (D) Pseudotime trajectory plots for CDMs from Ankrd22^−/− and Ankrd22^+/+ mice in a two-dimensional state space defined by monocle 2. The pseudotime trajectory of individual cells (with darker colors indicating proximity to the starting point of the pseudotime axis) (left) and the differentiation tree structure of the subsets (right). (E) Ratio of expected (Ro/e) analysis of major CDM subsets. [Ro/e > 1]: +++; [0.8 < Ro/e≤1]: ++; [0.2≤Ro/e≤0.8]: +. (F) Proportion of MHCII⁺CX3CR1⁺ mature macrophages among CDMs from Ankrd22^−/− and Ankrd22^+/+ mice, as measured by FCM. The data are presented as the mean ± SEM. *P < 0.05 by Student’s t test. (G) Pseudotime trajectory plots via Monocle 2 showing the differentiation status of CDMs in subcutaneous tumors. The pseudotime trajectory of individual cells with darker colors indicating proximity to the starting point of the pseudotime axis (left) and the differentiation tree structure of each subset (right). (H) Pseudotime trajectory plots generated via monocle 2 showing the differentiation status of MoMacs in subcutaneous tumors. The pseudotime trajectory of individual cells with darker colors indicating proximity to the starting point of the pseudotime axis (left) and the differentiation tree structure of each subset (right).

Differentiation trajectory analysis using CytoTRACE indicated that Clusters 1, 4, and 10 represented progenitor states (Figure 4B and C). Pseudotime analysis in Monocle 2 confirmed that Clusters 1 and 4 resided at an early differentiation stage (Figure 4D). The ratio of expected (Ro/e) analysis revealed enrichment of early-stage Clusters 1 and 4 within Ankrd22^−/− CDMs (Figure 4E). FCM further validated the reduced proportion of MHCII⁺CX3CR1⁺ mature macrophages among Ankrd22^−/− CDMs (Figure 4F and Figure S4C). These findings suggest that the CDMs of Ankrd22^−/− mice delayed temporal differentiation.

We subsequently analyzed the differentiation trajectories of CDMs and MoMacs in tumors. Pseudotime analysis revealed that Ankrd22^−/− CDMs delayed temporal differentiation, as indicated by an increased proportion of the early-stage differentiation subset and a decreased proportion of the terminal-stage subset (Figure 4G); moreover, the differentiation of MoMacs in tumors presented similar differentiation delays (Figure 4H). These results demonstrate that ANKRD22 deficiency impedes monocyte-to-macrophage differentiation kinetics in tumor tissues.

The Notch4/HES1 Pathway Is Involved in the Delay in the Differentiation and Immunosuppressive Polarization of Macrophages Triggered by ANKRD22 Suppression

To elucidate the mechanism by which ANKRD22 suppression delays macrophage differentiation and promotes an immunosuppressive microenvironment in CRC, we performed scATAC-seq analysis on Ankrd22^−/− and Ankrd22^+/+ mouse CDMs. After clustering and identifying the cell types enriched in the colorectum, the cells were divided into 6 subsets (Figure 5A–C). Mapping scRNA-seq subset information to scATAC-seq data revealed that Subsets 2 and 4 corresponded to scRNA-seq Clusters 1 and 4, which were in the early stage of differentiation (Figure S5A). Differential peak analysis of CDM subsets revealed that the transcription factor Hes1 may be associated with the delayed differentiation of Ankrd22-knockout macrophages (Figure S5B).

Figure 5.

The Notch4/HES1 pathway mediates ANKRD22 suppression-induced delays in macrophage differentiation and immunosuppressive polarization. (A) scATAC-seq analysis of CD45⁺CD11b⁺/F4/80⁺ cells isolated from colorectal lamina propria single-cell suspensions from Ankrd22^−/− and Ankrd22^+/+ mice by FACS. Cells were pooled from 5 mice per group. Uniform manifold approximation and projection (UMAP) visualization. (B) UMAP plot annotated by cell type. (C) UMAP visualization of macrophage subsets. (D) Potential binding sites for the transcription factor HES1. (E) Transcription factor activity analysis of HES1 across CDM subsets. (F) Proportion of cells with an active Hes1 regulon analyzed by pySCENIC. (G) Chromatin accessibility profiles at the Hes1, Jag1, and Notch4 loci. The dashed red boxes present peaks of the corresponding genes. (H) t-SNE plots showing Jag1 and Notch4 expression in MoMacs from subcutaneous tumors. (I) Spatial transcriptomic analysis of paraffin-embedded sections from human CRC and paired nontumor tissues. CD68⁺ macrophages were identified via multiplex immunofluorescence staining for spatial transcriptome sequencing. (J) Notch signaling pathway scores in macrophages from spatial transcriptome data. (K) Spatial expression of HES1 and JAG1 mRNA in macrophages. (L) HES1 mRNA expression in human macrophages following treatment with 10 μM recombinant human Jagged1 (rhJagged1). (M) FOS mRNA expression during monocyte-to-macrophage differentiation in the presence or absence of 10 μM rhJagged1. (N) ARG1 mRNA expression in human macrophages after treatment with 10 μM rhJagged1. The data are presented as the mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 by Student’s t test (K, L and N) or two-way ANOVA (M).

Analysis of the activity of potential HES1 binding sites revealed that the transcriptional activity of Hes1 increased in the early differentiated subsets (Figure 5D and E). Transcription factor analysis (pySCENIC) revealed Zfp691, Hes1, Hic1, Runx3 and Ehf as regulators of Cluster 1 and Runx3, Hes1, Nr4a3, Crem and Maff as regulators of Cluster 4 (Figure S5C). Among these genes, Hes1 and Runx3 specifically regulated Clusters 1 and 4, with Hes1 activity significantly elevated in Ankrd22^−/− CDMs (Figure 5F and Figure S5D). As HES1 is a core target of the Notch pathway, we analyzed the chromatin accessibility of canonical Notch genes. The increased expression and chromatin accessibility of Hes1, Jag1, and Notch4 in early-differentiated subsets indicated that Hes1 activation likely occurs via the Jagged1-Notch4 axis (Figure 5G).

We next asked whether delayed macrophages in tumors acquire their immunosuppressive phenotype via the Jagged1-Notch4 pathway. GSEA revealed that the Notch pathway was enriched in Ankrd22^−/− tumor MoMacs (Figure S5E). The expression of Jag1 and Notch4 increased in immunosuppressive, early-differentiation Cluster 1 tumors from Ankrd22^−/− mice, whereas the expression of Notch1, Notch2 and Notch3 did not change (Figure 5H and Figure S5F). Correlation analysis revealed positive associations between Jag1/Notch4 and immunosuppressive genes and negative correlations with immune activation genes (Figure S5G). The spatial transcriptomics of paired human CRC samples further demonstrated the activation of the Notch pathway and significant upregulation of HES1 and JAG1 transcription in tumor-associated CD68⁺ macrophages (Figure 5I–K and Figure S5H). Finally, to investigate how the Notch pathway affects macrophage differentiation, we differentiated isolated human peripheral blood monocytes into macrophages in vitro. The activation of the Notch pathway with recombinant Jagged1 (rhJagged1) was confirmed by a corresponding increase in HES1 expression (Figure 5L). We then assessed differentiation status by monitoring FOS for a transcription factor whose expression is negatively correlated with macrophage differentiation.¹¹ Notably, rhJagged1-mediated Notch activation impeded monocyte-to-macrophage differentiation, as indicated by sustained FOS levels (Figure 5M). Concurrently, the activation of the Notch pathway increased the expression of immunosuppressive ARG1 (Figure 5N). Collectively, these results suggest that suppression of ANKRD22 delays differentiation and promotes an immunosuppressive macrophage phenotype through activation of the Notch4/HES1 pathway.

Intracellular Fatty Acid Reduction Mediates ANKRD22 Deficiency-Induced Notch Activation in Macrophages

To elucidate how ANKRD22 suppression activates the Notch pathway, and given its role in lipid metabolism, we first analyzed macrophage lipid dynamics. Compared with control treatment, FCM treatment resulted in significantly increased lipid droplet accumulation in Ankrd22^−/− macrophages (Figure 6A). Subsequent enzymatic assays demonstrated that Ankrd22 knockout significantly reduced intracellular fatty acid (FA) levels, whereas ANKRD22 overexpression increased intracellular FA levels (Figure 6B and C). The main component of lipid droplets is neutral lipids, which are usually broken down into fatty acids by lipase.²⁵ We further analyzed the expression of lipase and lipid droplet-associated proteins in macrophages and found Lpl expression to be downregulated in Ankrd22^−/− macrophages (Figure 6D). Furthermore, we detected LPL enzyme activity in BMDMs by a fully automated biochemical analyzer and found that the LPL content in Ankrd22^−/− BMDMs decreased (Figure 6E). ANKRD22 is localized to lipid droplets.²⁶ Therefore, we speculate that ANKRD22 recruits LPL to lipid droplets to degrade triglycerides to produce free fatty acids. The amount of LPL bound to lipid droplets decreased after Ankrd22 knockout, which affected the degradation of triglycerides and reduced the intracellular fatty acid content.

Figure 6.

Reduced levels of intracellular fatty acids mediate ANKRD22 deficiency-induced Notch activation in macrophages. (A) Lipid droplet content in CDMs from Ankrd22^−/− (KO) and Ankrd22^+/+ (WT) mice, as measured by BODIPY staining and FCM. (B) Free fatty acid content in BMDMs from Ankrd22^−/− and Ankrd22^+/+ mice. (C) Free fatty acid content in THP-1 cells overexpressing ANKRD22 (OE). (D) Heatmap of the expression of Lpl in macrophages derived from liver, colorectal, and subcutaneous tumors (including CDM and MoMac). (E) LPL enzyme activity in BMDMs from Ankrd22^−/− and Ankrd22^+/+ mice. (F) Jagged1 and HES1 expression in THP-1 cells treated with 200 μM oleic acid. (G) Western blot analysis of Jagged1 and HES1 expression in THP-1 and RAW264.7 cells treated with lipid metabolism modulators: Panel 1 (lipid droplet synthesis inhibitors: A922500 and PF-06424439); Panel 2 (fatty acid synthesis inhibitors: orlistat, fatostatin, and CMS-121); Panel 3 (fatty acid oxidation inhibitors: etomoxir and T0070907). (H) Jagged1 and HES1 expression in THP-1 cells treated with lipid metabolism modulators with or without a PPAR inhibitor (T0070907) or agonist (GW0742). (I) Jagged1 and HES1 expression in THP-1 cells treated with 200 μM oleic acid, with or without a PPAR inhibitor (T0070907) or agonist (GW0742). (J) Schematic diagram of how ANKRD22 deficiency regulates lipid metabolism reprogramming. The downward and upward arrows respectively represent the inhibition and activation of the pathways. The data are presented as the mean ± SEM. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; Student’s t test (A–C and E).

With respect to the notch pathway, exogenous oleic acid supplementation downregulated HES1 and Jagged1 expression, whereas specific inhibition of FA synthesis upregulated the expression of both proteins (Figure 6F and G). Given the critical role of PPAR in FA oxidation (FAO),²⁷ we treated THP-1 cells with a PPAR agonist or antagonist. The agonist suppressed Jagged1 and HES1 expression, whereas the antagonist increased them. Crucially, the agonist blocked FA synthesis inhibition-induced upregulation of Jagged1/HES1, and the antagonist reversed oleic acid-mediated downregulation (Figure 6H and I).

Collectively, these results indicate that ANKRD22 deficiency impairs the release of FA from lipid droplets through LPL, reducing the level of intracellular FAs and triggering the activation of the Notch pathway in macrophages (Figure 6J).

Delayed Differentiation and Notch Activation Drive an Immunosuppressive CD9⁺CD127⁺ Subset in Tumors

To explore the link between delayed macrophage differentiation and immunosuppressive polarization, we identified marker genes across normal CDMs and tumor CDMs/MoMacs and found that a delayed-differentiation subset of normal Ankrd22^−/− CDMs exhibited a gene expression profile similar to that of delayed subsets from tumor CDMs and MoMacs (Figure S6A). This population was defined as the F4/80⁺CD9⁺CD127⁺ macrophage subset. FCM confirmed the presence of this subset in both the normal mouse colorectum and subcutaneous tumors, with a significantly elevated proportion in Ankrd22^−/− mice (Figure 7A and Figure S6B, C). It was also detectable in human CRC and distant normal tissues, with a relatively high abundance in CRC samples (Figure 7B and C). Transcriptional profiling revealed upregulation of immunosuppressive genes (including Arg1, Spp1, and Mmps) within this subset in tumors (Figure S6D). Further validation by FCM and mIHC confirmed the elevated expression of ARG1 and SPP1 in the CD9⁺CD127⁺ macrophage subset derived from both human and mouse tumors, in contrast to minimal expression in the corresponding subset from the normal colorectum (Figure 7D–G). These findings suggest that this macrophage subset is highly plastic and is more prone to adopt an immunosuppressive phenotype within the TME. Additionally, we observed that this subset was predominantly localized at the margin between cancerous and noncancerous regions (Figure 7H). Together, these results suggest that the CD68⁺CD9⁺CD127⁺ subset may contribute to the establishment of an immunosuppressive microenvironment.

Figure 7.

Delayed differentiation and Notch activation drive an immunosuppressive CD9⁺CD127⁺ macrophage subset in tumors. (A) Proportion of F4/80⁺CD9⁺CD127⁺ cells among CDMs from Ankrd22^−/− and Ankrd22^+/+ mice determined by FCM. (B) Frequencies of CD68⁺CD9⁺CD127⁺ cells in human CRC tissues and matched distant normal tissues (≈10 cm apart) analyzed by FCM. (C) Comparison of CD68⁺CD9⁺CD127⁺ subset frequency between paired human CRC and distant normal tissues (≈10 cm apart) via mIHC. (D) Proportion of ARG1⁺ or SPP1⁺ cells within the F4/80⁺CD9⁺CD127⁺ CDM subset. (E) Proportion of ARG1⁺ or SPP1⁺ cells among total macrophages and the F4/80⁺CD9⁺CD127⁺ subset in subcutaneous tumors. (F) Representative mIHC images of the CD68⁺CD9⁺CD127⁺ subset in normal human colorectal tissues. Colors: CD9 (red), SPP1 (pink), CD127 (green), CD68 (cyan), ARG1 (yellow), DAPI (blue). (G) Representative multiplex immunohistochemistry (mIHC) images of human CRC samples showing CD68⁺CD9⁺CD127⁺ cells coexpressing ARG1 and/or SPP1. The marker colors are the same as those in (F). (H) Spatial localization of the CD68⁺CD9⁺CD127⁺ subset in human CRC tissues by mIHC. n = 13. (I) Proportion of the F4/80⁺CD9⁺CD127⁺ subset (the white arrows) among CDMs after treatment with 10 μM Limantrafin (CB-103), as measured by FCM. (J) Panels of lipid metabolism inhibitors/agonists were used to treat BMDMs, and the proportion of the F4/80⁺CD9⁺CD127⁺ macrophage subset among BMDMs was determined by FCM. (K) Subcutaneous tumors in BALB/c mice 14 days after coinjection of CT26 cells (5×10⁶) and BMDMs (5×10⁶) from Ankrd22^−/− or Ankrd22^+/+ mice. The mice received 25 mg/kg CB-103 (intragastric) and/or 10 mg/kg long-acting IL-7 Efineptakin Alfa (NT-17, intramuscular) starting 7 days post-inoculation. n = 4. (L) Tumor weights across treatment groups. (M) Proportion of the F4/80⁺CD9⁺CD127⁺ subset among tumor macrophages in each group, analyzed by FCM. The data are presented as the mean ± SEM. *P < 0.05, ***P < 0.001 by Student’s t test (A, C and I); *P < 0.05, **P < 0.01, ***P < 0.001 vs Ankrd22^+/+ control; ^#P < 0.05, ^##P < 0.01, ^####P < 0.0001 vs Ankrd22^−/− control by two-way ANOVA (L and M).

Given our findings linking ANKRD22 downregulation, Notch activation, and differentiation delay, we treated macrophages in vitro with a Notch inhibitor. FCM revealed that this treatment significantly reduced the proportion of the early-differentiated F4/80⁺CD9⁺CD127⁺ subset (Figure 7I and Figure S6E). We also found that inhibition of FA synthesis significantly increased the F4/80⁺CD9⁺CD127⁺ macrophage subset (Figure 7J). Given that CD127 is an IL-7 receptor, we assessed combinatorial targeting. In a mouse tumor model, the coadministration of a Notch inhibitor and long-acting IL-7 significantly inhibited tumor growth and reduced the proportion of the F4/80⁺CD9⁺CD127⁺ subset (Figure 7K–M).

These results demonstrate that the Notch pathway is involved in ANKRD22 suppression-mediated macrophage differentiation delay and immunosuppressive polarization. The combined inhibition of the Notch pathway and targeted CD127 administration represents a promising therapeutic strategy to restrict this immunosuppressive macrophage subset.

Discussion

This study demonstrated that CRC cells suppress ANKRD22 expression in macrophages through the release of metabolites and cytokines, thereby delaying macrophage differentiation and maturation. Furthermore, these temporally delayed macrophage subsets promote and amplify the immunosuppressive TME by recruiting monocytes and polarizing them into TAMs. We revealed that a reduction in the level of intracellular fatty acids, which mediates ANKRD22 deficiency-induced Notch activation, plays a critical role in this process of delayed macrophage differentiation and immunosuppressive polarization.

We found that CRC cell-derived metabolites and cytokines significantly downregulated ANKRD22 expression in macrophages, underscoring the impact of tumor cell‒macrophage crosstalk on the macrophage phenotype. The downregulation of ANKRD22 expression by CRC-derived metabolites and cytokines was dependent on p38 pathway activity. Intriguingly, while p38 activation in macrophages led to ANKRD22 downregulation, this effect differed from its role in CRC cells, suggesting the involvement of cell type-specific regulatory mechanisms. In macrophages, p38 activation stimulates downstream MAD family molecules that antagonize the transcriptional activity of the core factor MAX. In summary, CRC cells can downregulate ANKRD22 expression in macrophages through a variety of complex paracrine effects.

CyTOF analysis revealed that mixing Ankrd22^−/-   macrophages with tumor cells in tumorigenic tissues significantly increased the proportion of CD206⁺ macrophages and decreased the number of memory effector CD8⁺ T cells. These findings align with the established literature showing that TAMs inhibit immune cell function through various mechanisms, including direct suppression of CD8⁺ T-cell proliferation via Arg1, iNOS, and ROS; induction of T-cell inhibition through immune checkpoints such as PD-L1;²⁸ and release of TGFβ1 and CCL22 to inhibit dendritic cell maturation and recruit Tregs.²⁹ Additionally, we found that Ankrd22^−/-   macrophages recruited peripheral blood monocytes and promoted their acquisition of an immunosuppressive phenotype. scRNA-seq revealed that the CCL ligand–receptor pathway was markedly activated. Blocking CCR1/2/5 only partially inhibited the monocyte recruitment capacity, which remained higher than that in Ankrd22^+/+      macrophages, suggesting recruitment via other cytokines. The recruited monocytes acquired an intercellular communication pattern similar to that of Ankrd22^−/-  macrophages, indicating that differentiation-delayed TAMs promote and amplify the immunosuppressive microenvironment.

We found that the temporal differentiation of Ankrd22-knockout macrophages was delayed and that an F4/80⁺CD9⁺CD127⁺ immunosuppressive macrophage subset arrested at an early differentiation stage. An analogous CD68⁺CD9⁺CD127⁺ subset was also increased in human CRC tissues, suggesting that delayed differentiation underlies immunosuppressive phenotype switching in the TME. Dynamic changes in transcription factor expression control macrophage maturation.³⁰ scATAC-seq revealed increased chromatin accessibility and transcriptional activity of Hes1, a core transcription factor of the Notch pathway, in the delayed-differentiation subset of Ankrd22^−/-  CDMs. Given that Hes1 helps maintain cellular immaturity³¹ and that its expression decreases during normal monocyte-to-macrophage differentiation,¹¹ we speculate that sustained Hes1 expression maintains the early differentiation state of ANKRD22-deficient macrophages, enabling rapid responses to microenvironmental signals that promote CRC pathogenesis.

We further demonstrated that increased chromatin accessibility of Hes1, Jag1, and Notch4 in this macrophage subset correlated with upregulated immunosuppressive genes. JAG1-NOTCH4 expression, rather than that of NOTCH1/2/3, was upregulated in macrophages from mouse tumors and human CRC TAMs. rhJagged1-mediated Notch activation impeded monocyte-to-macrophage differentiation, and inhibition of the Notch pathway reduced the F4/80⁺CD9⁺CD127⁺ population; this effect was significantly enhanced by combining inhibition of Notch expression with the CD127-specific ligand IL-7. These findings indicate that Ankrd22 knockout activates the Notch pathway in macrophages, delaying their differentiation and maturation and leading to an immunosuppressive phenotype. The low expression of immunosuppressive molecules in this subset under normal conditions suggests that the TME enhances its polarization, suggesting a dual therapeutic benefit of Notch inhibition.³² The Notch inhibitor includes γ-secretase inhibitors, anti-Notch1/DLL4 antibodies, and dual-targeting DLL4/VEGF immunoglobulin.³³ The combined targeting of the Notch pathway and CD127 is expected to reshape the immune microenvironment in colorectal cancer.

Lipid metabolism reprogramming is closely linked to Notch pathway activation. ANKRD22 suppression increased lipid droplet levels but reduced intracellular fatty acid levels in macrophages, likely due to impaired lipid droplet hydrolysis. LPL can hydrolyze triglycerides, releasing free fatty acids.³⁴ Our study suggested that ANKRD22 deficiency-induced reprogramming of lipid metabolism may be enabled by LPL. The decrease in fatty acids was associated with Notch activation. As fatty acids are primary ligands for PPARs, which are essential for lipid homeostasis,³⁵ we found that modulating PPAR activity could reverse the effects of altered fatty acid levels on the Notch pathway. This finding implicates PPAR signaling in ANKRD22 deficiency-mediated metabolic rewiring that activates Notch. This is significant, as lipid metabolism is known to play a crucial role in TAM differentiation and function.³⁶ Our finding that Ankrd22 knockout activates the Notch pathway through lipid metabolism reprogramming, thereby delaying the differentiation of CDMs, provides a mechanistic link.

This study has several limitations that warrant further investigation. Although we established that lipid metabolism reprogramming mediates Notch pathway activation, the precise mechanism through which it activates specific Notch target molecules remains unclear. In addition, single-cell data were generated from pooled samples, which may obscure interindividual heterogeneity, dilute rare cell states, and introduce batch or composition effects. Furthermore, while the immunosuppressive nature of this macrophage subset was confirmed in human samples, its broader impact on the tumor microenvironment and its interactions with other immune cells require further exploration.

In conclusion, ANKRD22 downregulation reprograms fatty acid metabolism to activate the Notch4/HES1 pathway, thereby promoting immunosuppressive macrophage polarization. ANKRD22 is a key regulator of macrophage plasticity and a promising therapeutic target for reprogramming the immunosuppressive TME in CRC.

Data Sharing Statement

The data that support the findings of this study are available from the corresponding author (Yongliang Zhu) upon reasonable request.

Author Contributions

All the authors made a significant contribution to the work reported, whether it is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests.