Adjacent nontumor mucosa: The overlooked frontier in colorectal cancer prognostication

Abstract

Immune contexture increasingly shapes colorectal cancer (CRC) prognosis, yet most profiling is tumor-centric. The study interrogated adjacent nontumor mucosa (NM) and tumor center (TC) in 99 CRC patients with liver metastases (LM). Using immunohistochemistry for CD68 (M0), CD80 (M1), and CD206/CD163 (M2), they observed a consistent density gradient (CD163 > CD206 > CD68 > CD80) and markedly lower macrophage densities in TC vs NM, consistent with immune exclusion. Crucially, stage-specific prognostic signals resided in NM: Higher CD80⁺ density associated with longer overall survival (OS) in stage I-III, while higher CD163⁺ density associated with longer OS in stage IV; these persisted in multivariable models. NM likely captures “immunological field cancerization,” reflecting systemic immune tone, pre-metastatic niche cues, and therapy-induced reprogramming masked within the tumor core. Clinically, incorporating NM macrophage markers (CD80, CD163) into routine pathology, combined with T-cell based metrics, could refine risk stratification and guide stage-tailored immune modulation. Strengths include paired NM-TC analysis and whole-slide quantification; retrospective design and phenotypic readouts are limitations. Prospective validation and spatial/functional omics are warranted. Overall, this study positions NM as an overlooked but actionable immune compartment, with potential to improve decision-making and outcomes for CRC patients with LM.

Key Words: Colorectal cancer; Adjacent nontumor mucosa; Macrophage polarization; Liver metastases; Prognostic biomarkers

Core Tip: Most immune profiling in colorectal cancer focuses on the tumor core, overlooking adjacent nontumor mucosa (NM). The study show that NM macrophage subsets provide stage-specific prognostic signals after liver metastasectomy: Higher CD80-positive (M1-like) macrophages predict longer survival in stage I-III, while higher CD163-positive (M2-like) macrophages predict longer survival in stage IV. Tumor center metrics were not predictive. Incorporating NM immune profiling (CD80, CD163), alongside T-cell measures, could refine risk stratification and guide stage-tailored immune modulation.

INTRODUCTION

Colorectal cancer (CRC) remains a major contributor to global cancer morbidity and mortality, with worldwide incidence exceeding 19 million cancer cases in 2022 and CRC ranking among the leading causes of cancer-related death[1]. Yet CRC outcomes are shaped not only by the malignant epithelium but by the ecosystems in which tumors evolve[2]. While decades of work have refined our understanding of the tumor microenvironment (TME)[3], most immune profiling remains confined to the tumor core or invasive margin. The adjacent nontumor mucosa (NM), histologically normal tissue within a surgical resection, has been relatively ignored. Yet this compartment may register systemic immune tone, pre-metastatic niche signals, and therapy-induced reprogramming that the tumor core cannot reveal[4].

In addition, adjacent NM is unlikely to be biologically neutral. Common CRC driver mutations such as TP53, APC, and PIK3CA, present in a substantial proportion of patients and particularly enriched in metastatic disease, shape invasion, signaling pathways, and stromal immune interactions[5]. Tumor-intrinsic alterations and their downstream inflammatory or metabolic effects may extend beyond visible tumor boundaries, contributing to molecular or immune alterations in histologically normal mucosa, consistent with the concept of field cancerization[6]. In this context, Ye et al[7] deliver an important advance. In a retrospective cohort of 99 CRC patients who underwent curative resection of both primary tumors and liver metastases (LM), the authors paired formalin-fixed paraffin-embedded tissue from NM and tumor center (TC) and quantified macrophage subsets by immunohistochemistry (IHC): CD68 (M0), CD80 (M1), and CD206/CD163 (M2). They stratified patients into stage IV with synchronous LM (n = 55) and stage I-III who later developed metachronous LM (n = 44), and linked immune metrics to overall survival (OS) after liver metastasectomy, testing both absolute densities and TC/NM ratios[7]. This pattern is consistent with the broader principle that tissue-resident macrophages are imprinted by local cues and can maintain context-dependent programs that differ from inflamed cores[3].

STAGE-SPECIFIC MACROPHAGE PATTERNS IN ADJACENT NM

Several findings deserve emphasis[7]: First, across NM and TC, macrophage densities displayed a stable rank order: CD163 > CD206 > CD68 > CD80. Second, all subsets were notably less abundant in the TC than in NM, pointing to an immune-poor core rather than an inflammatory hotspot. Third and most relevant for prognosis, stage-specific associations appeared in the NM, not in the TC. In stage I-III disease, higher NM density of CD80⁺ (M1-like) macrophages was associated with longer OS; in stage IV, higher NM density of CD163⁺ (M2-like) macrophages predicted better outcomes (Figure 1). These associations persisted in multivariable models adjusted for clinically meaningful factors. In contrast, simple M1/M2 ratios or TC macrophage metrics were not associated with survival.

Figure 1 Paradigm shift in macrophage biology in colorectal cancer. From a tumor-centric view to an non-tumor mucosa (NM)-integrated, stage-specific model. Schematic illustration contrasting the traditional tumor-centric perspective with the proposed adjacent NM-integrated, stage-specific framework. Left panel (traditional tumor-centric view): Macrophage infiltration within the tumor center (TC) is relatively sparse and predominantly composed of M2-like macrophages (CD163⁺/CD206⁺), with limited M1-like macrophages (CD80⁺). Across stages, macrophage density within the TC is reduced compared with NM and is not associated with overall survival. Right panel (proposed NM-integrated model): In the adjacent NM, macrophages are more abundant and exhibit stage-specific prognostic associations. In stage I-III disease, higher densities of CD80⁺ M1-like macrophages in NM are associated with favorable prognosis and may reflect enhanced immune surveillance and cytotoxic support limiting metastatic dissemination. In contrast, in stage IV disease, increased CD163⁺/CD206⁺ M2-like macrophages in NM are associated with improved survival and may reflect tissue repair, vascular stabilization, and maintenance of epithelial integrity. Colored symbols represent macrophage subsets: M0 (CD68⁺, gray), M1-like (CD80⁺, orange), and M2-like (CD163⁺/CD206⁺, blue). The schematic reflects relative distribution patterns and conceptual associations rather than quantitative measurements.

IMMUNOLOGICAL FIELD EFFECTS AND MACROPHAGE FUNCTIONAL PLASTICITY

Why might NM outperform TC for prognostication? The NM may reflect “immunological field cancerization”, host tumor interactions that alter the immune state of tissue surrounding the tumor without overt histological change[8]. In CRC, such alterations may manifest as subtle epigenetic reprogramming, shifts in cytokine milieu, or selective recruitment and exclusion of immune cell subsets despite preserved histologic architecture[9]. As a surrogate of systemic immune competence, NM could capture the capacity for anti-tumor surveillance and response to therapy more faithfully than the immune-excluded core[8,10]. In vivo, macrophages rarely fall neatly into M1 or M2 categories; instead, they often display overlapping features along a spectrum. NM may therefore better reflect this mixed and context-dependent biology than the relatively immune-poor TC[11]. The stage-specific differences are biologically coherent: In earlier stages, CD80⁺ M1-like macrophages in NM can plausibly recruit and activate cytotoxic T and NK cells, aligning with improved outcomes where immune surveillance may suppress dissemination. Meanwhile, a subset of CD163⁺ macrophages in NM in stage IV may retain reparative, vascular-stabilizing, epithelial barrier-supporting, and antigen-presenting functions, potentially contributing to containment of further spread or supporting post-operative anti-tumor immunity, particularly in a context of perioperative systemic signals or chemotherapy that can reprogram macrophages toward anti-tumor phenotypes[12]. Perivascular and LYVE1⁺ macrophage subsets have been shown to stabilize vessels and contribute to vessel “normalization” under defined conditions[13], which can improve perfusion and limit hypoxia-driven spread.

The study also observed greater CD80⁺ density in NM among stage I-III patients compared with stage IV, supporting the hypothesis that immune surveillance is more preserved when metastases occur later. Notably, adjuvant FOLFOX containing oxaliplatin, which can skew macrophages toward M1-like phenotypes, was associated with improved OS after resection of metachronous LM, hinting at a potential synergy between therapy-induced macrophage conditioning and NM immune state. Such shifts are biologically plausible given macrophage polarization pathways (e.g., TLR/NF-κB and IFN-γ/JAK-STAT1 for inflammatory programs vs PI3K/Akt/mTOR and TGF-β/Smad for reparative programs)[14,15] that can be modulated by systemic therapies.

TRANSLATIONAL IMPLICATIONS AND METHODOLOGICAL CONSIDERATIONS

From a clinical standpoint, these results suggest several next steps. Pathology workflows could incorporate NM immune profiling alongside standard tumor evaluation. A related practical question is how NM sampling should be defined in routine practice: how far from the tumor edge tissue should be collected and how non-neoplastic mucosa should be verified histologically. CD80 and CD163 IHC in NM could be added to routine panels with minimal additional cost. Combined with T cell-based metrics (e.g., immunoscore), these markers may further refine risk stratification after LM surgery beyond TNM staging and traditional clinicopathologic features[16]. Importantly, adjacent NM represents an immune-rich interface in which macrophages interact with T cells, antigen-presenting pathways, and immune checkpoint axes. Emerging immunotherapeutic frameworks emphasize that immune checkpoints (e.g., PD-1/PD-L1, CTLA-4) and newer targets (TIM-3, LAG-3, TIGIT) function within complex signaling circuits involving JAK/STAT, PI3K-AKT, and MAPK pathways[17]. In this context, NM macrophage states should be interpreted as part of a broader immune signaling landscape rather than as isolated polarization markers. Given marker overlap and phenotype-function mismatch in vivo, NM CD80/CD163 should complement multiplex macrophage panels and spatially resolved metrics rather than serve as standalone surrogates. For patients with stage I-III disease and low NM CD80, tighter surveillance or macrophage-directed strategies that enhance M1 polarization might be warranted. Conversely, in stage IV patients with low NM CD163, strategies aimed at reprogramming M2 macrophages to anti-tumor phenotypes, or supporting their reparative and vascular integrity functions, deserve investigation.

Methodologically, the study’s strengths include side-by-side, whole-slide, digital quantification of four macrophage markers across NM and TC; the use of TC/NM ratios; and stage-specific analysis tied to a clinically relevant endpoint-OS after metastasectomy. Key limitations are its retrospective, single-center design, moderate sample size, and the inherent constraints of IHC markers that capture phenotype more than function. This is especially relevant as single markers rarely capture mixed states; multi-marker and spatial transcriptomic approaches are better suited to resolve macrophage heterogeneity. Treatment heterogeneity and limited molecular data preclude definitive mechanistic inferences. These caveats underscore the need for prospective, multi-center validation, and for functional and spatial omics approaches (multiplex imaging, spatial transcriptomics) to delineate macrophage programs and their crosstalk with adaptive immune cells. Beyond conventional IHC, advances in biosensor-driven biomarker detection and microfluidic platforms may facilitate scalable, multiplexed interrogation of tissue-level or molecular signals, supporting the clinical feasibility of NM-based biomarkers[18].

However, discordant macrophage prognostic associations in CRC may arise from several recurring sources: Differences in cohort composition (stage distribution, synchronous vs metachronous LM), marker panels (CD80 vs iNOS for M1)[19], quantification methods (whole-slide counts vs microarrays)[20], and the tissue compartments examined (TC vs NM)[8,21]. Considering these variables together helps explain why findings across studies do not always converge. Apparent contradictions are expected when macrophage phenotypes are plastic, tissue-imprinted, and measured with different single-marker panels across compartments[14,19]. By centering the NM, Ye et al[7] show that immune signatures outside the tumor core can outperform TC for predicting survival after LM surgery, a perspective shift that may reconcile prior inconsistencies when the analysis extends beyond the tumor core.

The implications are far-reaching. The immune story of CRC is not confined to the tumor. Adjacent NM harbors stage-specific macrophage signals that are clinically actionable[8,22]. Incorporating NM immune profiling into prognostic models could improve risk stratification, guide adjuvant therapy choices, and shape surveillance intensity. These observations also raise a broader question: Should treatment focus solely on tumor cells, or also on their surrounding ecosystems within the TME[23]? Rather than replacing tumor-directed therapy, profiling adjacent NM may complement it, offering additional prognostic information and potentially identifying windows for perioperative immune modulation. Macrophage-targeted strategies, including CSF1R/CCR2 axis modulation[24], metabolic/epigenetic reprogramming[25,26], and nanoparticle delivery[24], are already in clinical exploration, underscoring the feasibility of perioperative conditioning concepts while demanding careful safety gating. Integrating NM macrophage metrics with T-cell immunoscores and genomic features may yield composite immune risk models that surpass current clinicopathologic staging[27].

CONCLUSION

In sum, Ye et al[7] ask us to look just beyond the tumor edge. By doing so, they illuminate a neglected, yet informative, immune compartment whose macrophage composition predicts survival in a stage-specific manner. Validating and operationalizing these insights could help move CRC care toward microenvironment-aware decision-making, improving outcomes for patients confronting LM.