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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2025.1742654</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Mini Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Roles of immunosuppressive myeloid states in colorectal cancer checkpoint inhibitor non-response: single-cell and spatial proteomics, and reprogramming approaches</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Dai</surname><given-names>Yu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn003"><sup>&#x2020;</sup></xref>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
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</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Luo</surname><given-names>Xinyu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn003"><sup>&#x2020;</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Zhang</surname><given-names>Li</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Yan</surname><given-names>Jin</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3221831/overview"/>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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<aff id="aff1"><label>1</label><institution>Department of Oncology, The Affiliated Hospital of Southwest Medical University</institution>, <city>Luzhou</city>, <state>Sichuan</state>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>School of Medicine, University of Electronic Science and Technology of China, Sichuan Cancer Hospital</institution>, <city>Chengdu</city>, <state>Sichuan</state>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>Department of Abdominal Medical Oncology, Sichuan Cancer Hospital &amp; Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China</institution>, <city>Chengdu</city>, <state>Sichuan</state>,&#xa0;<country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Li Zhang, <email xlink:href="mailto:zhangli@scszlyy.org.cn">zhangli@scszlyy.org.cn</email>; Jin Yan, <email xlink:href="mailto:yanjin_1111@163.com">yanjin_1111@163.com</email></corresp>
<fn fn-type="equal" id="fn003">
<label>&#x2020;</label>
<p>These authors have contributed equally to this work</p></fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-06">
<day>06</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1742654</elocation-id>
<history>
<date date-type="received">
<day>09</day>
<month>11</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>11</day>
<month>12</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Dai, Luo, Zhang and Yan.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Dai, Luo, Zhang and Yan</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-06">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<p>Colorectal cancer (CRC) exhibits a striking dichotomy in response to immune checkpoint inhibitors (ICIs), with durable benefit largely restricted to dMMR/MSI-H disease while most pMMR/MSS tumors remain refractory. Central to this resistance is an immunosuppressive myeloid ecosystem&#x2014;dominated by SPP1high tumor-associated macrophages, neutrophils/PMN-MDSCs, and LAMP3<sup>+</sup> mregDCs&#x2014;that enforces chemokine-driven exclusion, attenuates antigen presentation, and sustains metabolite-mediated T-cell suppression. Despite advances in checkpoint blockade and biomarker stratification, these microenvironmental circuits constitute a major therapeutic hurdle. Moreover, single-cell and spatial proteomic platforms (e.g., CITE-seq, CODEX, imaging mass cytometry) now resolve the composition and topology of suppressive neighborhoods and highlight their utility for patient stratification and pharmacodynamic monitoring. This mini review summarizes cellular and spatial mechanisms by which myeloid states drive ICI non-response in CRC, emphasizing stromal TGF-&#x3b2;&#x2013;coupled SPP1+ TAM programs, granulocytic chemokine axes (CXCL1/2&#x2013;CXCR2; IL-8&#x2013;CXCR1/2), and mregDC-mediated co-inhibition. We outline current and emerging myeloid-reprogramming strategies&#x2014;including PI3K&#x3b3; and CSF1&#x2013;CSF1R targeting, TREM2 antagonism, COX-2&#x2013;PGE2 blockade, and adenosine-axis inhibition&#x2014;and their integration with PD-(L)1 therapy, alongside single-cell/spatial endpoints to quantify on-treatment remodeling. The purpose of this mini-review is to provide a mechanistic and technology-informed framework to reference rational trial design and clinical translation for overcoming checkpoint resistance in CRC.</p>
</abstract>
<kwd-group>
<kwd>cancer-associated fibroblasts</kwd>
<kwd>checkpoint resistance</kwd>
<kwd>colorectal cancer</kwd>
<kwd>immune checkpoint inhibitors</kwd>
<kwd>neutrophils</kwd>
<kwd>tumor-associated macrophages</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was not received for this work and/or its publication.</funding-statement>
</funding-group>
<counts>
<fig-count count="1"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="92"/>
<page-count count="8"/>
<word-count count="3372"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Cancer Immunity and Immunotherapy</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Colorectal cancer (CRC) illustrates a marked dichotomy in responsiveness to immune checkpoint inhibitors (ICIs): durable clinical benefit is largely confined to the mismatch repair&#x2013;deficient/microsatellite instability&#x2013;high (dMMR/MSI-H) subset, whereas the majority of mismatch repair&#x2013;proficient/microsatellite-stable (pMMR/MSS) tumors fail to respond (<xref ref-type="bibr" rid="B1">1</xref>&#x2013;<xref ref-type="bibr" rid="B3">3</xref>). This disparity reflects fundamental differences in tumor&#x2013;immune ecology and has motivated concerted efforts to define tractable barriers to T-cell&#x2013;directed immunotherapy in CRC (<xref ref-type="bibr" rid="B4">4</xref>&#x2013;<xref ref-type="bibr" rid="B6">6</xref>). In parallel, molecular taxonomies such as the consensus molecular subtypes (CMS) emphasize that mesenchymal, TGF-&#x3b2;&#x2013;rich stromal programs (e.g., CMS4) coexist with immune-inflamed (CMS1) states (<xref ref-type="bibr" rid="B7">7</xref>&#x2013;<xref ref-type="bibr" rid="B9">9</xref>), reinforcing the premise that context-specific microenvironmental circuits shape antitumor immunity and therapeutic outcome.</p>
<p>A convergent body of evidence implicates immunosuppressive myeloid populations&#x2014;tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), neutrophils, and mature dendritic cells enriched in immunoregulatory molecules (mregDCs)&#x2014;as dominant effectors of checkpoint inhibitor non-response (<xref ref-type="bibr" rid="B10">10</xref>&#x2013;<xref ref-type="bibr" rid="B12">12</xref>). These lineages constrain priming and execution of cytotoxic T-cell responses through impaired antigen presentation, nitric-oxide/reactive oxygen species programs, checkpoint ligand upregulation, and tolerogenic cytokine/eicosanoid/adenosine networks. Single-cell atlases in CRC further resolve functionally distinct myeloid states; for example, SPP1high macrophages that interact with fibroblast activation protein (FAP)+ cancer-associated fibroblasts and align with desmoplastic, T-cell&#x2013;excluded niches (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Spatially resolved proteomic imaging corroborates that these myeloid programs assemble into reproducible &#x201c;cellular neighborhoods&#x201d;&#x2014;recurrent, analytically defined arrangements of cell types within fixed spatial radii&#x2014;at the invasive front that stratify antitumor immunity and prognosis (<xref ref-type="bibr" rid="B15">15</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>).</p>
<p>Non-response phenotypes also track with granulocytic axes. Across tumor types, elevated systemic and intratumoral IL-8 (CXCL8) associates with reduced benefit from PD-(L)1 blockade, consistent with neutrophil/MDSC-mediated suppression (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B19">19</xref>). In CRC, clinicopathologic inflammation and neutrophil enrichment correlate with resistance even among dMMR/MSI-H cases, underscoring that myeloid circuits can override high neoantigen load. These observations place chemokine pathways such as CXCL1/2&#x2013;CXCR2, CCL2&#x2013;CCR2, and IL-8&#x2013;CXCR1/2&#x2014;and their downstream effector programs&#x2014;at the center of immune exclusion in CRC.</p>
<p>Methodological advances now enable rigorous deconvolution of myeloid heterogeneity and its spatial organization in human CRC. High-parameter single-cell RNA sequencing coupled to protein measurements has delineated TAM, dendritic, and neutrophil states linked to therapeutic sensitivity and resistance, and has provided mechanistic readouts for experimental perturbations (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>). Spatial proteomics platforms&#x2014;including co-detection by indexing (CODEX) and imaging mass cytometry (IMC)&#x2014;quantify dozens of proteins per cell <italic>in situ</italic>, allowing direct mapping of immune&#x2013;stromal interfaces (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B23">23</xref>), ligand&#x2013;receptor topologies, and suppressive niches at single-cell resolution.</p>
<p>These insights nominate myeloid reprogramming as a rational complement to ICIs in CRC. Targetable nodes include PI3K&#x3b3;, a&#xa0;macrophage-intrinsic signaling switch whose inhibition restores&#xa0;inflammatory antigen presentation and augments checkpoint&#xa0;blockade; the CSF1&#x2013;CSF1R axis that maintains immunosuppressive TAM pools; TREM2, a myeloid checkpoint whose blockade reshapes TAM states and synergizes with PD-1 therapy; and metabolic circuits such as COX-2&#x2013;PGE<sub>2</sub> and adenosine (CD39/CD73&#x2013;A<sub>2</sub>A/A<sub>2</sub>B) that tonically enforce T-cell suppression. This review synthesizes current understanding of immunosuppressive myeloid states in CRC non-response to ICIs, with two aims: first, to integrate single-cell and spatial proteomic evidence that defines the composition and architecture of suppressive niches in human tumors; and second, to evaluate reprogramming strategies that target these myeloid circuits to convert immune-excluded CRC into ICI-responsive disease. The intent is to provide a mechanistic and technology-informed framework to guide study design and clinical translation in CRC immunotherapy.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Landscape of immunosuppressive myeloid states in colorectal cancer</title>
<p>Across colorectal tumors, the immunosuppressive myeloid compartment comprises lineage-defined populations&#x2014;tumor-associated macrophages, neutrophils/PMN-MDSCs, monocytic-MDSCs, and dendritic cells&#x2014;and finer &#x201c;states&#x201d; defined by transcriptional and protein markers shared across these cells. As shown in <xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>, single-cell profiling in human CRC delineates macrophage states that diverge from the canonical M1/M2 schema; among these, SPP1high macrophages are consistently expanded and associate with extracellular matrix remodeling, VEGF/EGF signaling, and chemokine outputs that favor T-cell exclusion (<xref ref-type="bibr" rid="B24">24</xref>,&#xa0;<xref ref-type="bibr" rid="B25">25</xref>). While transcriptomic data indicate that these cells are typically enriched for immunoregulatory transcripts such as TREM2, ARG1, IL10 and PD-L1. Within this framework, SPP1high macrophages&#x2014;predominantly monocyte-derived and overlapping with but not identical to classical M2-like TAMs&#x2014;are consistently expanded, with evidence for angiogenic versus matrix-remodeling SPP1<sup>+</sup> subclusters that mirror analogous populations in other gastrointestinal malignancies. Spatial analyses demonstrate that SPP1high macrophages colocalize with fibroblast activation protein (FAP)+ cancer-associated fibroblasts at the invasive front, forming a mesenchymal&#x2013;myeloid circuit linked to desmoplasia, poor cytotoxic infiltration, and adverse outcome (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>). These observations situate SPP1high macrophages as a central suppressive node in CRC.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Immunosuppressive myeloid&#x2013;stromal crosstalk underlying PD-1/PD-L1 resistance in the CRC tumor microenvironment.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1742654-g001.tif">
<alt-text content-type="machine-generated">Diagram illustrating immune interactions in colorectal cancer (CRC). Neutrophil recruitment is mediated by IL-8/CXCL1/2 signaling. T cells interact with CRC cells through PD-1/PD-L1. Components include SPP1+ TAM, FAP+ CAF, and mregDC.</alt-text>
</graphic></fig>
<p>Granulocytic axes are prominent in CRC immune evasion. Neutrophils and PMN-MDSCs accumulate through CXCL1/2&#x2013;CXCR2 and IL-8/CXCR1/2 signaling, amplify reactive oxygen species and arginase programs, and enforce immune exclusion. Pharmacologic and genetic perturbations across gastrointestinal and colitis-associated models demonstrate that CXCR2 signaling governs granulocytic recruitment and tumor promotion, providing mechanistic support for therapeutic targeting of this pathway (<xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B29">29</xref>). Clinically, elevated circulating IL-8 tracks with inferior outcomes to PD-(L)1 blockade across malignancies, consistent with a neutrophil-dominated suppressive milieu that can supersede high tumor antigenicity (<xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B31">31</xref>). In CRC, emergent data nominate combined CCR1/CXCR2 blockade to curtail protumor myeloid trafficking, underscoring the therapeutic relevance of chemokine circuits (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>).</p>
<p>Dendritic cell lineages in CRC encompass conventional DC1/2 and a mature LAMP3<sup>+</sup> state enriched in immunoregulatory molecules (mregDC) that upregulates PD-L1, PD-L2 and other tolerogenic mediators while retaining antigen-presentation machinery (<xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>). This program, induced upon tumor-antigen uptake, supports T-cell priming in a context that simultaneously delivers checkpoint and cytokine-based inhibitory signals, thereby tuning effector differentiation and exhaustion. These DC states participate in structured cellular neighborhoods identified by multiplexed imaging; CRC tissues harbor myeloid-attracting hubs at the tumor&#x2013;luminal interface and MMRd-enriched immune hubs&#xa0;within tumor nests (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>), each with characteristic myeloid&#x2013;lymphoid assemblies that stratify prognosis and therapeutic sensitivity.</p>
<p>CRC harbors a reproducible landscape of suppressive myeloid states anchored by SPP1high tumor-associated macrophages, CXCR2-driven granulocytic programs, and mregDC modules. Single-cell and spatial studies converge on the concept that these populations assemble into mesenchymal-skewed, chemokine-rich niches that impede T-cell recruitment and function (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B39">39</xref>). These features provide mechanistic context for checkpoint inhibitor non-response in pMMR/MSS disease.</p>
</sec>
<sec id="s3">
<label>3</label>
<title>Single-cell and spatial proteomics for mapping suppressive niches</title>
<p>Single-cell multi-omic profiling and high-plex spatial proteomics provide complementary resolution on how immunosuppressive myeloid programs are organized in colorectal cancer (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B41">41</xref>). Antibody-tagged single-cell transcriptomics (CITE-seq, REAP-seq) jointly quantifies transcripts and surface proteins, enabling direct measurement of checkpoint ligands, antigen-presentation molecules, chemokine receptors, and myeloid differentiation markers within the same cells and thereby resolving SPP1<sup>high</sup> TAMs, mregDCs, and granulocytic states with reduced label ambiguity (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>). As shown in <xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>, these platforms define intracellular programs, whereas high-parameter imaging modalities capture the topologies that enforce T-cell exclusion. CITE-seq and REAP-seq are established for simultaneous RNA&#x2013;protein readouts and support robust annotation of myeloid states that are otherwise weakly separable by mRNA alone.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Single-cell and spatial proteomic platforms for delineating immunosuppressive niches in colorectal cancer.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Platform</th>
<th valign="middle" align="center">Modality/readout</th>
<th valign="middle" align="center">Specimen &amp; scale</th>
<th valign="middle" align="center">Typical utility for suppressive-niche mapping</th>
<th valign="middle" align="center">Notes</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">CITE-seq/REAP-seq</td>
<td valign="middle" align="center">Droplet scRNA-seq with antibody-derived tags (RNA+protein)</td>
<td valign="middle" align="center">Fresh/viable single-cell suspensions; &#x2265;10<sup>4</sup> cells</td>
<td valign="middle" align="center">Define TAM, mregDC, MDSC, neutrophil states; quantify PD-L1, HLA-DR, CSF1R, CXCR2, AXL at single-cell level</td>
<td valign="middle" align="center">Panel validation; isotype/background controls; batch correction and doublet removal</td>
</tr>
<tr>
<td valign="middle" align="center">CODEX</td>
<td valign="middle" align="center">DNA-barcoded antibody cyclic IF (&#x2265;40&#x2013;60 proteins)</td>
<td valign="middle" align="center">FFPE sections; whole fields or tissue microarrays</td>
<td valign="middle" align="center">Map cellular neighborhoods at the invasive front; measure myeloid&#x2013;CAF&#x2013;T-cell interfaces and checkpoint ligand densities</td>
<td valign="middle" align="center">Antibody conjugation/FFPE reactivity; spillover correction; segmentation QC</td>
</tr>
<tr>
<td valign="middle" align="center">Imaging Mass Cytometry (Hyperion IMC)</td>
<td valign="middle" align="center">Metal-tagged antibody TOF imaging (&#x2248;30&#x2013;40 proteins)</td>
<td valign="middle" align="center">FFPE/Frozen; tiles to whole regions</td>
<td valign="middle" align="center">Quantify cell&#x2013;cell proximities and gradients; identify neutrophil/MDSC corridors and macrophage rings</td>
<td valign="middle" align="center">Metal channel optimization; cross-slide normalization; proximity/ripley statistics</td>
</tr>
<tr>
<td valign="middle" align="center">MIBI-TOF</td>
<td valign="middle" align="center">Secondary-ion mass spectrometry of metal-conjugated antibodies</td>
<td valign="middle" align="center">FFPE; high-resolution fields</td>
<td valign="middle" align="center">Stable quantification across batches; fine mapping of ligand&#x2013;receptor borders</td>
<td valign="middle" align="center">Vacuum stability, depth profiling; rigorous panel calibration</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CITE, cellular indexing of transcriptomes and epitopes; REAP, RNA end-associated purification; TAM, tumor-associated macrophage; mregDC, mature dendritic cells enriched in immunoregulatory molecule; MDSC, myeloid-derived suppressor cell; CODEX, co-detection by indexing; IF, immunofluorescence; FFPE, formalin-fixed paraffin-embedding; CAF, cancer-associated fibroblast; QC, quality control; IMC, imaging mass cytometry; MIBI-TOF, multiplexed ion beam imaging by time of flight.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Multiplexed spatial imaging has established that CRC assembles reproducible &#x201c;cellular neighborhoods&#x201d; at the invasive front in which myeloid, stromal, and lymphoid elements co-cluster. Using 56-marker CODEX on CRC tissue microarrays, Some studies identified coordinated neighborhoods whose composition stratified immune pressure and outcome, directly implicating organized myeloid&#x2013;stromal hubs in immune control (<xref ref-type="bibr" rid="B44">44</xref>&#x2013;<xref ref-type="bibr" rid="B46">46</xref>). Spatial multi-omic analyses consistently show tight coupling of SPP1<sup>+</sup> macrophages with FAP<sup>+</sup> cancer-associated fibroblasts, a mesenchymal&#x2013;myeloid circuit linked to extracellular-matrix remodeling and T-cell exclusion in independent CRC cohorts and validated by spatial transcriptomics and immunofluorescence (<xref ref-type="bibr" rid="B47">47</xref>, <xref ref-type="bibr" rid="B48">48</xref>). Three-dimensional high-plex atlases further reveal gradients and barriers not apparent in two dimensions, quantify cell&#x2013;cell distances (<xref ref-type="bibr" rid="B49">49</xref>,&#xa0;<xref ref-type="bibr" rid="B50">50</xref>), and uncover nested suppressive structures that align with histologic fronts and glandular architecture in CRC.</p>
<p>These spatial readouts contextualize mechanistic nodes relevant to non-response. Lymphatic-adjacent Treg&#x2013;mregDC niches form immunoregulatory hubs that restrict antigen access and can be quantified by CODEX/IMC to nominate actionable checkpoints and cytokine axes. Spatially mapped TGF-&#x3b2; activity aligns with induction of immunosuppressive SPP1<sup>+</sup> macrophages and impaired T-cell recruitment, reinforcing a dual stromal&#x2013;myeloid barrier that is measurable with multiplexed imaging and suitable for pharmacodynamic monitoring in trials that combine myeloid-reprogramming agents with PD-(L)1 blockade.</p>
</sec>
<sec id="s4">
<label>4</label>
<title>Mechanistic circuits connecting myeloid programs to checkpoint inhibitor failure</title>
<p>CRC non-response to ICIs maps to stromal&#x2013;myeloid circuits that restrict T-cell access, blunt priming, and attenuate effector function. Single-cell and spatial analyses position SPP1high tumor-associated macrophages in tight contact with FAP+ cancer-associated fibroblasts at the invasive front, enriched for extracellular-matrix and TGF-&#x3b2; signaling; this configuration aligns with immune-excluded architecture and adverse outcome (<xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B52">52</xref>). Functional inference and experimental data support SPP1&#x2013;CD44 and TGF-&#x3b2;&#x2013;SMAD2/3/4 programs, coupled to PI3K&#x3b3;&#x2013;AKT signaling and integrated with CSF1, CXCL12, CCL2, VEGF, and complement components, which stabilize SPP1<sup>+</sup>/TREM2<sup>+</sup> macrophage identity, skew antigen presentation, and exclude cytotoxic lymphocytes (<xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B54">54</xref>). In immune-excluded tumors, stromal TGF-&#x3b2; blockade restores intratumoral T-cell penetration and sensitizes to PD-(L)1 therapy, nominating this mesenchymal&#x2013;myeloid axis as a proximal cause of checkpoint failure.</p>
<p>Chemokine pathways couple granulocytic recruitment to resistance. CXCL1/2&#x2013;CXCR2 and IL-8/CXCR1/2 signaling drive accumulation of neutrophils and PMN-MDSCs that generate reactive oxygen species and arginase programs, degrade chemokine gradients, and physically occlude T-cell entry (<xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B56">56</xref>). Clinically, elevated baseline or on-treatment IL-8 tracks with reduced benefit from PD-(L)1 blockade across solid tumors, supporting IL-8/CXCR2 as a resistance biomarker and therapeutic target; CXCR2 inhibition increases effector T-cell infiltration and potentiates immunotherapy in preclinical models (<xref ref-type="bibr" rid="B57">57</xref>, <xref ref-type="bibr" rid="B58">58</xref>).</p>
<p>Antigen handling and co-inhibitory signaling by dendritic cells constitute a second node linking myeloid states to non-response. Mature, migratory LAMP3<sup>+</sup> dendritic cells (mregDCs) upregulate PD-L1/PD-L2 and immunoregulatory cytokines while preserving antigen-presentation machinery (<xref ref-type="bibr" rid="B59">59</xref>, <xref ref-type="bibr" rid="B60">60</xref>); in tumors, these cells accumulate at lymphoid&#x2013;stromal interfaces where they support constrained priming and program T-cell exhaustion under high checkpoint ligand density.</p>
<p>Macrophage-intrinsic signaling and metabolic circuits sustain these barriers and directly antagonize PD-1&#x2013;directed reinvigoration. PI3K&#x3b3; signaling in macrophages enforces a C/EBP&#x3b2;-driven program that suppresses antigen presentation and promotes IL-10/ARG1 output; pharmacologic PI3K&#x3b3; inhibition reprograms TAMs and synergizes with PD-1 blockade. TREM2+ lipid-associated TAMs curtail T-cell function, and anti-TREM2 augments PD-1 therapy in resistant settings (<xref ref-type="bibr" rid="B61">61</xref>, <xref ref-type="bibr" rid="B62">62</xref>). COX-2&#x2013;PGE<sub>2</sub> signaling and PMN-MDSC-intrinsic FATP2-dependent arachidonic-acid metabolism amplify PGE<sub>2</sub> production, reinforce myeloid suppression, and reduce responsiveness to ICIs; early clinical experience indicates feasibility of combining COX inhibition with PD-1 in MSI-H CRC (<xref ref-type="bibr" rid="B63">63</xref>, <xref ref-type="bibr" rid="B64">64</xref>). Adenosine produced through CD39/CD73 engages A<sub>2</sub>A/A<sub>2</sub>B receptors on myeloid and lymphoid cells to blunt effector responses, implicating ectonucleotidases and adenosine-receptor antagonists as complementary approaches (<xref ref-type="bibr" rid="B65">65</xref>, <xref ref-type="bibr" rid="B66">66</xref>). In CRC models, CSF1R inhibition reprograms TAMs and potentiates anti-PD-1 efficacy, further highlighting the tractability of these circuits (<xref ref-type="bibr" rid="B67">67</xref>, <xref ref-type="bibr" rid="B68">68</xref>).</p>
<p>These pathways converge on T-cell signal deprivation and signaling interference: ARG1-mediated L-arginine depletion downregulates CD3&#x3b6; and arrests T-cell cycling, while iNOS-derived nitric oxide and peroxynitrite from MDSCs nitrates T-cell receptors and impairs antigen recognition, consolidating myeloid control over effector competence in CRC.</p>
</sec>
<sec id="s5">
<label>5</label>
<title>Reprogramming strategies targeting myeloid compartments</title>
<p>Therapeutic reprogramming of myeloid lineages in CRC aims to restore antigen presentation, diminish suppressive cytokine&#x2013;eicosanoid&#x2013;adenosine signaling, and reduce chemokine-driven exclusion of effector T cells. Macrophage-intrinsic phosphoinositide 3-kinase-&#x3b3; (PI3K&#x3b3;) functions as a signaling switch that biases tumor-associated macrophages (TAMs) toward immunosuppression; pharmacologic PI3K&#x3b3; inhibition rebalances NF-&#x3ba;B/C/EBP&#x3b2; programs, enhances antigen-presenting functions, and potentiates PD-(L)1 blockade in preclinical models, supporting clinical evaluation as a combinatorial partner (<xref ref-type="bibr" rid="B69">69</xref>, <xref ref-type="bibr" rid="B70">70</xref>). Complementarily, targeting the CSF1&#x2013;CSF1R axis reduces and re-educates suppressive TAM pools and increases intratumoral CD8+ T-cell infiltration. In CRC models, CSF1R inhibition augmented anti&#x2013;PD-1 efficacy, indicating on-target remodeling of macrophage phenotypes (<xref ref-type="bibr" rid="B71">71</xref>, <xref ref-type="bibr" rid="B72">72</xref>). However, CSF1R blockade can induce compensatory granulocytic recruitment through cancer-associated fibroblast chemokines, arguing for rational pairing with chemokine-axis inhibitors or T cell&#x2013;priming agents to prevent myeloid rebound.</p>
<p>TREM2 defines an immunosuppressive TAM state that accumulates across solid tumors, including colorectal contexts. Genetic ablation or antibody blockade of TREM2 reorganizes the myeloid compartment toward inflammatory phenotypes, increases intratumoral T-cell activity, and synergizes with PD-1 blockade <italic>in vivo</italic> (<xref ref-type="bibr" rid="B73">73</xref>, <xref ref-type="bibr" rid="B74">74</xref>). Mechanistic and translational studies further support TREM2 as a therapeutically tractable macrophage checkpoint; effector-enhanced anti-TREM2 antibodies and modalities delivering TREM2-directed binders into the tumor bed improve responses to PD-1 therapy, including in CRC models (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B76">76</xref>). These position TREM2 antagonism as a candidate backbone for myeloid reprogramming in checkpoint-refractory CRC.</p>
<p>Granulocytic programs that enforce immune exclusion can be attenuated by interrupting chemokine-driven trafficking. In CRC, preclinical and early translational evidence supports blockade of IL-8/CXCL1/2&#x2013;CXCR1/2 pathways to reduce neutrophil/PMN-MDSC accumulation and improve sensitivity to immune checkpoint blockade. Dual inhibition of CCR1 and CXCR2 curtailed myeloid recruitment and exhibited antitumor activity in colorectal settings, providing a strategy to counteract chemokine redundancy and stromal compensation observed with single-node targeting (<xref ref-type="bibr" rid="B77">77</xref>&#x2013;<xref ref-type="bibr" rid="B80">80</xref>). Broader analyses of CXCR1/2 therapeutics corroborate that neutrophil-directed inhibition can be integrated with ICIs where granulocytic exclusion dominates (<xref ref-type="bibr" rid="B81">81</xref>, <xref ref-type="bibr" rid="B82">82</xref>).</p>
<p>Metabolic and purinergic circuits that stabilize suppressive myeloid states are tractable points of intervention. COX-2&#x2013;PGE<sub>2</sub> signaling dampens dendritic-cell function, promotes regulatory myeloid outputs, and constrains T-cell priming; selective EP2/EP4 pathway inhibition or COX blockade reverses these effects in&#xa0;models, and early clinical experience combining COX inhibition&#xa0;with PD-1 in dMMR metastatic CRC indicates feasibility&#xa0;and&#xa0;activity, motivating expansion into pMMR disease (<xref ref-type="bibr" rid="B83">83</xref>,&#xa0;<xref ref-type="bibr" rid="B84">84</xref>).&#xa0;In&#xa0;PMN-MDSCs, fatty-acid transport protein-2 (FATP2/SLC27A2)&#xa0;drives arachidonic-acid uptake and PGE<sub>2</sub> synthesis; FATP2&#xa0;inhibition abrogates granulocytic suppression and enhances&#xa0;checkpoint responses <italic>in vivo</italic>, nominating a selective strategy&#xa0;to&#xa0;disable neutrophil-dominant resistance (<xref ref-type="bibr" rid="B85">85</xref>, <xref ref-type="bibr" rid="B86">86</xref>). The adenosinergic axis (CD39/CD73&#x2013;A<sub>2</sub>A/A<sub>2</sub>B) tonically suppresses myeloid and lymphoid effector functions; co-blockade of CD73 and A<sub>2</sub>A receptors increases antitumor immunity and synergizes with ICIs in preclinical systems, and multiple agents targeting this pathway are under clinical evaluation (<xref ref-type="bibr" rid="B87">87</xref>, <xref ref-type="bibr" rid="B88">88</xref>). Because macrophages, neutrophils, and MDSCs are also crucial for host defense and tissue repair, myeloid-targeted combinations may increase infection risk, delay wound healing, and trigger on-target inflammatory toxicities that must be carefully profiled in CRC trials.</p>
</sec>
<sec id="s6" sec-type="conclusions">
<label>6</label>
<title>Conclusion and outlook</title>
<p>Across colorectal cancer, convergent single-cell and spatial proteomic evidence identifies immunosuppressive myeloid programs as primary constraints on checkpoint inhibitor efficacy. SPP1high macrophages coupled to fibroblast-rich, TGF-&#x3b2;&#x2013;dominant stroma, CXCR2-driven granulocytic circuits, and LAMP3<sup>+</sup> mregDC modules form interconnected barriers that limit T-cell priming, trafficking, and effector function (<xref ref-type="bibr" rid="B89">89</xref>, <xref ref-type="bibr" rid="B90">90</xref>). These populations assemble into reproducible cellular neighborhoods&#x2014;particularly at the invasive front&#x2014;where ligand&#x2013;receptor density, matrix architecture, and chemokine gradients align to produce T-cell exclusion and checkpoint non-response. This integrated model explains why pMMR/MSS tumors rarely benefit from PD-(L)1 blockade and why even dMMR/MSI-H disease can be overridden by dominant myeloid axes.</p>
<p>Methodological advances now enable precise dissection of these states and their spatial context in clinical specimens. Joint RNA&#x2013;protein single-cell profiling distinguishes closely related myeloid phenotypes and quantifies actionable surface molecules, while high-plex imaging resolves cell&#x2013;cell proximities, gradients, and compartmentalized signaling. As shown in <xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>, these platforms provide complementary views of composition and topology and are sufficiently mature for biomarker development and pharmacodynamic assessment. Standardized panel design, segmentation quality control, and cross-batch normalization remain essential to ensure reproducibility across centers and trial cohorts.</p>
<p>Therapeutically, reprogramming&#x2014;not ablation&#x2014;of myeloid compartments emerges as the most generalizable path to synergy with PD-(L)1 blockade. Macrophage-intrinsic switches (PI3K&#x3b3;, TREM2), lineage-support pathways (CSF1&#x2013;CSF1R), neutrophil trafficking axes (IL-8/CXCL1/2&#x2013;CXCR1/2; CCR1/CCR2), and immunometabolic circuits (COX-2&#x2013;PGE<sub>2</sub>; FATP2-dependent lipid handling; CD39/CD73&#x2013;A<sub>2</sub>A/A<sub>2</sub>B adenosine signaling) constitute tractable nodes that can be combined to dismantle redundant suppressive loops. The preclinical and early translational signal across these targets supports a development strategy that prioritizes rational doublets with PD-(L)1 and favors mechanisms that simultaneously improve antigen presentation, restore chemokine balance, and reduce metabolite-mediated T-cell suppression (<xref ref-type="bibr" rid="B91">91</xref>, <xref ref-type="bibr" rid="B92">92</xref>). Because pathway compensation is common, combinations that pair macrophage re-education with neutrophil-axis interruption, or that couple stromal TGF-&#x3b2; modulation with myeloid-targeted agents, are likely to be required in immune-excluded CRC.</p>
<p>Translation will depend on trial designs that embed single-cell and spatial endpoints. Neoadjuvant &#x201c;window&#x201d; studies and trials in metastatic CRC should use on-treatment biopsies to quantify state shifts in SPP1high TAMs, neutrophil/MDSC densities, mregDC prevalence, checkpoint-ligand distribution, and T-cell access to tumor nests. Peripheral biomarkers&#x2014;such as circulating IL-8 and blood-derived myeloid signatures&#x2014;can provide complementary, low-burden monitoring but should be analytically bridged to tissue-resolved readouts. Prospective stratification by stromal&#x2013;myeloid architecture (e.g., mesenchymal/TGF-&#x3b2;&#x2013;high niches) and by chemokine-axis activity will reduce biological heterogeneity and increase the likelihood of detecting true drug&#x2013;drug interactions.</p>
<p>Looking forward, three priorities are clear. First, harmonized taxonomies of CRC myeloid states, grounded in cross-platform reference atlases, are needed to stabilize target selection and endpoint interpretation. Second, pharmacodynamic standards that tie quantitative remodeling of suppressive neighborhoods to clinical benefit should be codified and used to advance only those combinations that meet predefined tissue-based thresholds. Third, iterative co-development of drugs and diagnostics&#x2014;integrating single-cell, spatial, and circulating measures&#x2014;will be essential to match specific myeloid barriers with the most appropriate reprogramming strategies. By aligning mechanism, measurement, and patient selection, it should be possible to convert the immune-excluded colorectal tumor into a context receptive to checkpoint reinvigoration and to broaden durable benefit beyond the dMMR/MSI-H subset.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>YD: Methodology, Conceptualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. XL: Methodology, Conceptualization, Writing &#x2013; original draft. LZ: Writing &#x2013; review &amp; editing, Conceptualization. JY: Writing &#x2013; review &amp; editing, Methodology, Conceptualization.</p></sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
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<fn-group>
<fn id="n1" fn-type="custom" custom-type="edited-by">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1300788">Chunguang Guo</ext-link>, Chinese Academy of Medical Sciences and Peking Union Medical College, China</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2872917">Ke Xu</ext-link>, Chongqing General Hospital, China</p></fn>
</fn-group>
<fn-group>
<fn fn-type="abbr" id="abbrev1">
<label>Abbreviations:</label>
<p>CRC, colorectal cancer; ICIs, immune checkpoint inhibitors; dMMR, mismatch repair-deficient; MSI-H, microsatellite instability-high; pMMR, mismatch repair-proficient; MSS, microsatellite-stable; CMS, consensus molecular subtypes; TAMs, tumor-associated macrophages; MDSCs, myeloid-derived suppressor cells; mregDCs, mature dendritic cells enriched in immunoregulatory molecules; FAP, fibroblast activation protein; CODEX, co-detection by indexing; IMC, imaging mass cytometry; PI3K&#x3b3;, phosphoinositide 3-kinase-&#x3b3;; FATP2, fatty-acid transport protein-2.</p>
</fn>
</fn-group>
</back>
</article>