CXCL1 as a novel prognostic biomarker and immune regulator in colon adenocarcinoma

Abstract

Introduction

Colon Adenocarcinoma (COAD) remains a prominent problem among cancers today. COAD is one of the malignancies with a significant overexpression of CXCL1, an enzyme involved in cellular metabolism. However, the key targets for colon cancer are not yet well understood. As a result, the purpose of this study is to examine the mechanism of CXCL1 in order to assess its potential as a predictive biomarker for colon cancer.

Methods

Genetic changes, genomic expression, and methylation analyses were sourced from the TCGA, CPTAC, UALCAN, HPA, cBioPortal, and MethSurv databases. The gene expression is validated by qPCR. The diagnostic and prognostic significance of CXCL1 in COAD was assessed using data from ROC analysis and KM-plotter. Functional analyses were performed utilizing the GeneMANIA and STRING databases, along with gene-gene and PPI networks, GO terms, and KEGG pathway analyses. The relationship with immune escape was explored through analyses conducted using the TIMER, TISIDB, and GEPIA databases. Additionally, GSCALite was utilized to analyze drug sensitivity in relation to CXCL1 expression in tumors.

Results

CXCL1 expression was found to be statistically significantly higher in COAD cells than in their corresponding normal control cells, according to qPCR analysis. ROC analysis identified CXCL1 as a highly accurate biomarker for diagnosing COAD (AUC = 0.725). Univariate Cox regression and KM analysis indicated that while high CXCL1 expression was significantly associated with improved OS and RFS (P < 0.001), its genetic alteration (amplification) was associated with a significantly shorter DFI (P = 0.037). Functional analyses confirmed CXCL1’s role in chemokine-mediated signaling and leukocyte chemotaxis, and also suggested involvement in cellular redox metabolism. Furthermore, CXCL1 overexpression was strongly correlated with promoter hypomethylation (e.g., cg19170015, P < 6e-10), and this hypomethylation intensified with advancing pathological stage. CXCL1 expression exhibited a robust correlation with the infiltration of myeloid cells, particularly macrophage (Rho = 0.693) and neutrophil cells, strongly suggesting it affects the TME and is associated with immune checkpoints. Finally, high CXCL1 expression was broadly correlated with drug resistance in pan-cancer cell lines but showed mixed sensitivity associations in COAD-specific cell lines.

Conclusions

This study’s comprehensive analyses indicate CXCL1 as a novel biomarker for COAD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-026-04522-2.

Introduction

Colorectal cancer is the third most common disease in the world and the main cause of cancer-related death [1]. COAD, the predominant subtype of CRC, poses a persistent therapeutic challenge, particularly in advanced stages where treatment resistance and metastasis remain major obstacles to improving patient survival [2, 3]. Current prognostic stratification, primarily based on clinicopathological staging, often fails to capture the underlying molecular heterogeneity that dictates clinical outcomes [4]. Consequently, the identification of robust molecular biomarkers that reflect the complex biology of COAD is imperative for refining prognosis, personalizing therapy, and identifying novel therapeutic targets.

The tumor microenvironment (TME) is a critical determinant of cancer progression, with chemokine-mediated signaling playing a central role in orchestrating immune cell recruitment, angiogenesis, and metastatic dissemination [5]. Among these, the C-X-C motif chemokine ligand 1 (CXCL1), a member of the ELR + CXC chemokine family, acts as a potent ligand for the CXCR2 receptor and is a key chemoattractant for neutrophils and other myeloid cells [6]. CXCL1 is implicated in a range of pathological processes, including chronic inflammation, rheumatoid arthritis, and psoriasis, underscoring its fundamental role in immune regulation [7, 8]. In oncology, CXCL1 has been recognized as a multifaceted player. It is frequently overexpressed in various cancers including melanoma [9], pancreatic ductal adenocarcinoma [10], and bladder cancer [11] where it promotes tumor growth, angiogenesis, and metastasis by shaping an immunosuppressive TME, often through the recruitment of myeloid-derived suppressor cells (MDSCs) and tumor-associated neutrophils (TANs) [12, 13]. In CRC, existing literature has documented elevated CXCL1 expression and suggested its involvement in promoting cell invasion and metastatic niche formation [14, 15]. However, despite these established associations, a comprehensive and integrative understanding of CXCL1’s role in COAD remains incomplete.

Previous studies have often focused on single dimensions of its biology, such as expression or isolated functional assays [16]. Critical knowledge gaps persist regarding: The genomic and epigenetic landscape driving CXCL1 dysregulation in COAD (e.g., the prevalence and prognostic impact of copy number alterations or stage-specific promoter methylation). A systematic, multi-omics integration of how CXCL1 correlates with immune infiltration patterns, co-expression networks, and functional pathways beyond chemotaxis. The translational and pharmacogenomic implications of CXCL1 expression, particularly its association with drug sensitivity or resistance in COAD-specific models [17].

To address these gaps, we conducted an integrative multi-omics study to define the role of CXCL1 in COAD. By synthesizing transcriptional, proteomic, genomic, epigenetic, immune, and pharmacogenomic data, we investigate the regulatory mechanisms underlying its dysregulation and its association with the tumor microenvironment and therapy response. This work aims to establish CXCL1 as a key integrative biomarker, providing a data-driven foundation for its future development in diagnostic, prognostic, and therapeutic contexts.

Methods

Data acquisition and expression analysis

Transcriptomic and clinical data for 33 cancer types, including COAD, were retrieved from TCGA via the UCSC Xena portal (https://xena.ucsc.edu/) [18]. The COAD cohort comprised 286 primary tumor samples and 41 matched adjacent normal tissue samples. For external validation of CXCL1 expression, normal and COAD tumor tissues (n = 6 per group) were collected following approval by the Ethics Committee of The First School of Clinical Medicine, Southern Medical University, Guangzhou, China (Approval No. 202409808) (Table S1). All database-derived mRNA expression data (Transcripts Per Million, TPM) were log2(TPM + 1) transformed for downstream analysis to approximate a normal distribution.

Differential expression analysis identified genes with divergent abundance between high and low CXCL1-expressing COAD samples using thresholds of an adjusted P-value (FDR) < 0.05 and an absolute log2 fold change > 1.0. To investigate co-regulatory patterns, the top 300 genes most positively correlated with CXCL1 expression in the TCGA-COAD cohort were identified based on the highest Pearson correlation coefficients (absolute r > 0.5, P < 0.001).

Proteomic validation was performed using data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), accessed via the UALCAN platform (http://ualcan.path.uab.edu/) [19]. This platform provides normalized protein abundance (Z-scores relative to normal samples) for COAD tumor and normal tissues, with statistical significance calculated using a two-sample t-test.

Survival and prognostic analysis

The association between CXCL1 expression and patient survival was evaluated using the Kaplan-Meier plotter tool (http://kmplot.com/). The COAD cohort (n = 286) was dichotomized into high and low CXCL1 expression groups based on the median expression value as the cutoff. Survival outcomes analyzed included OS, PFS, DSS, and RFS. HR with 95% CI were calculated using a univariate Cox proportional hazards model. The statistical significance of survival differences between groups was determined by the log-rank test, with a two-sided P-value < 0.05 considered significant [20].

The diagnostic potential of CXCL1 was assessed by generating a Receiver Operating Characteristic (ROC) curve using SRplot webtools, with the AUC calculated to evaluate classification accuracy between tumor and normal samples.

Network construction and functional enrichment analysis

A physical and functional interaction network centered on CXCL1 was constructed using GeneMANIA (http://www.genemania.org), which integrates data from multiple sources (e.g., co-expression, physical interactions, pathway sharing) [21]. A separate protein-protein interaction (PPI) network was generated using the STRING database (https://string-db.org/) with a minimum required interaction confidence score set to 0.400 (medium confidence).

Functional enrichment analyses were conducted in two ways. First, Gene Ontology (GO) analysis was performed on the interactors from the STRING PPI network. Second, to elucidate the broader biological context of CXCL1 activity, GO enrichment analysis (Biological Process, Molecular Function, Cellular Component) was performed on the top 300 positively correlated genes identified in Sect.  2.1. Enrichment was calculated using a hypergeometric test, with terms considered significantly enriched at a False Discovery Rate (FDR) adjusted P-value (q-value) < 0.05. Redundant terms were manually filtered for clarity.

Analysis of genetic alterations

The genomic alteration landscape of CXCL1 across cancers, with a focus on COAD, was profiled using cBioPortal (https://www.cbioportal.org/). The platform’s “Cancer Types Summary” module was used to determine the frequency and type (e.g., amplification, deep deletion) of alterations [22]. For prognostic analysis, COAD patients were stratified based on CXCL1 copy number variation (CNV) status (e.g., amplified vs. diploid). The association between alteration status and survival endpoints DFI, DSS, OS, and PFS was assessed within cBioPortal using a log-rank test (P < 0.05). Results were validated and visualized using the GSCALite platform.

DNA methylation analysis

DNA methylation (β-values) of CXCL1 CpG sites in COAD was analyzed using the UALCAN database, which processes Level 3 data from TCGA. Differential methylation between tumor and normal tissues for individual CpG sites was assessed using a Wilcoxon test. The prognostic value of specific CpG site methylation (e.g., cg19170015) was evaluated via univariable Cox regression on the MethSurv web portal (https://biit.cs.ut.ee/methsurv/), with a P-value < 0.05 considered significant. The correlation between promoter methylation β-values and CXCL1 mRNA expression was assessed using Spearman’s rank correlation. The chromosomal locations of significant CpG sites were visualized using the SMART App.

Analysis of immune infiltration and drug sensitivity

The correlation between CXCL1 expression and the abundance of tumor-infiltrating immune cells in COAD was quantified using the TIMER2.0 algorithm (http://timer.cistrome.org/) [23]. This tool employs a deconvolution method to estimate the infiltration levels of six immune cell types (B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, dendritic cells). The strength of association was reported as a partial correlation coefficient (Rho) and a corresponding P-value.

A broader analysis of correlations between CXCL1 and 28 immune cell subtypes across pan-cancer data was conducted using the TISIDB portal (http://cis.hku.hk/TISIDB/), which integrates data from TCGA and other public resources [24, 25].

Drug sensitivity analysis was performed using the GSCALite platform, which incorporates data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Cancer Therapeutics Response Portal (CTRP) [26]. The platform calculates Spearman’s rank correlation between CXCL1 mRNA expression and the drug half-maximal inhibitory concentration (IC50) across hundreds of cell lines. A correlation coefficient with an associated FDR < 0.05 was considered statistically significant. Analysis was performed in both a pan-cancer context and specifically for COAD cell lines.

Experimental validation by quantitative RT-PCR (qRT-PCR)

Total RNA was extracted from snap-frozen colon tissues using TRIzol reagent (Invitrogen, USA) following the manufacturer’s protocol. cDNA was synthesized from 1 µg of total RNA using the PrimeScript RT reagent Kit (Takara Bio). Quantitative PCR was performed using SYBR Green Master Mix (Applied Biosystems) on a QuantStudio 5 Real-Time PCR System. The relative expression of CXCL1 mRNA was normalized to the endogenous control β-actin and calculated using the 2 − ΔΔCt method. All reactions were performed in technical triplicates. Primer specificity was confirmed by a single peak in the melting curve analysis, and amplification efficiency was validated to be between 90% and 110%. Primer sequences are provided in Supplementary File S2.

Statistical analysis

Statistical analyses were performed using a combination of web-based platforms and dedicated software. For all comparative analyses, statistical significance was defined as a two-sided P-value < 0.05. The strength of correlations was interpreted as follows: |r| < 0.3, weak; 0.3 ≤ |r| < 0.7, moderate; |r| ≥ 0.7, strong.

All primary bioinformatic analyses (e.g., differential expression in TCGA, survival analysis in Kaplan-Meier Plotter, immune deconvolution in TIMER2.0) were conducted using the integrated statistical pipelines of the respective cited web portals. For in-house data processing and visualization, GraphPad Prism version 10.2.2 was used. This included the statistical analysis and generation of the qPCR validation data, the comparative analysis of CXCL1 expression from TCGA data, and the generation of the ROC curve. The area under the ROC curve (AUC) with its 95% confidence interval was calculated within GraphPad Prism.

Results

CXCL1 expression analysis in COAD

The pan-cancer mRNA expression profile of CXCL1 analysis revealed significant heterogeneity, with marked upregulation of CXCL1 observed in 17 malignancies, including COAD, compared to normal tissues (Fig. 1A and B). CPTAC Analysis of paired samples showed significantly elevated CXCL1 protein levels in tumor tissues (n = 286) compared to adjacent normal tissues (n = 41), with a median (IQR) of 110.794 (14.383–585.812) versus 4.376 (0.836–11.360), (P < 0.0001) (Fig. 1C). When stratified by pathological stage, CXCL1 expression remained significantly higher than the normal baseline across all stages (Stage 1, n = 45; Stage 2, n = 110; Stage 3, n = 80; Stage 4, n = 39). However, the correlation with stage was observed to be non-linear: the highest median expression (approximately 100 TPM) was recorded in Stage 1 tumors, followed by a slight decrease and stabilization across subsequent stages (Stage 2: ≈75 TPM; Stage 4: ≈50 TPM). This pattern suggests that the robust upregulation of CXCL1 merges as a multi-faceted biomarker in COAD development, and while expression is maintained, the peak at Stage 1 indicates its potential utility as an early diagnostic or prognostic factor (Fig. 1D).

Fig. 1.

CXCL1 Expression Analysis. A The TCGA database shows the expression profile of CXCL1 in 33 different cancer types. B Expression of CXCL1 in 41 COAD samples and the normal tissues that surround them. C CPTAC data are used to determine the levels of CXCL1 protein expression. D CXCL1’s protein expression at various stages of colon cancer. E qRT-PCR relative expression of tumor and normal. ***, P < 0.001

To experimentally validate these findings, CXCL1 expression was quantified by RT-qPCR. The analysis demonstrated a statistically significant upregulation of CXCL1 in COAD tissues compared to matched normal colon samples (P < 0.001; Fig. 1E), confirming its marked elevation in COAD.

Diagnostic and prognostic value of CXCL1

The diagnostic performance of CXCL1 was evaluated by receiver operating characteristic (ROC) curve analysis, which yielded an area under the curve (AUC) of 0.725 (95% CI: 0.020–1.000) for distinguishing COAD tumor from normal tissue (Fig. 2A). For prognostic assessment, COAD patients were dichotomized into high and low CXCL1 expression groups based on the median expression level. Kaplan-Meier survival analysis indicated that high CXCL1 expression was significantly associated with longer overall survival (OS) (Log-rank P < 0.001) and relapse-free survival (RFS) (Log-rank P < 0.001), but not with progression-free survival (PFS) (Log-rank P = 0.07) (Figs. 2B-D). Univariate Cox regression analysis was performed to evaluate the association between CXCL1 expression and clinicopathological features. Elevated CXCL1 expression was significantly associated with advanced T stage (T3 + T4), KRAS mutation status, and male gender. No significant association was found with TP53 mutation status or tumor grade (G2 + G3) (Fig. 2E).

Fig. 2.

CXCL1’s diagnostic and prognostic importance. A The CXCL1 ROC curve in COAD. B-D OS, PFS, and RFS KM analysis. E A forest plot showing how clinicopathological characteristics in COAD relate to CXCL1

Enrichment analysis of CXCL1-interacting genes in COAD

To elucidate the functional context of CXCL1 in COAD, we performed interaction and enrichment analyses. A gene-gene interaction network generated by GeneMANIA revealed close functional and physical associations between CXCL1 and its canonical receptors (CXCR1, CXCR2), related chemokines (CXCL3, CXCL6, CXCL11), and the atypical receptor ACKR1 (Fig. 3A). A separate protein-protein interaction (PPI) network from STRING identified key binding partners, including CXCL5, CXCL6, CCL11, and IL1B (Fig. 3B).

Fig. 3.

CXCL1 functional network enrichment analysis in COAD. A The CXCL1 gene-gene interaction network in GeneMANIA. B STRING’s depiction of the CXCL1 PPI network. C-E The BP, MF, and CC pathway categories are the top enrichment keywords for COAD

Gene Ontology (GO) enrichment analysis was performed on the top 300 genes positively correlated with CXCL1 expression in the TCGA-COAD cohort. Significant enrichment (FDR < 0.05) was observed across all three GO categories. In the Biological Process (BP) domain, the most significantly enriched terms were related to chemokine-mediated signaling, cell chemotaxis, and leukocyte migration (Fig. 3C). Analysis of Molecular Function (MF) identified enrichment for chemokine receptor binding and activity, along with terms related to oxidoreductase and aldehyde dehydrogenase activity (Fig. 3D). Cellular Component (CC) analysis indicated the correlated genes were primarily associated with the extracellular region and the external side of the plasma membrane (Fig. 3E).

Genetic alteration of CXCL1 in COAD

Analysis of the COAD cohort via cBioPortal revealed a high frequency of genetic alterations in CXCL1, with copy number amplification being the most common alteration type (Fig. 4A). Among the related CXCL gene family (CXCL1-3), CXCL1 exhibited the highest frequency of both heterozygous and homozygous amplification events in COAD (Figs. 4B-C).

Fig. 4.

Illustrates how COAD causes a genetic alteration in CXCL1. A Mutations in CXCL1 in different cancers. B-C CXCL1, CXCL2, and CXCL3 CNV frequencies in COAD. D Survival analysis for four clinical outcomes, with a significant log-rank P-value of 0.037. E Differences in survival between CXCL1-CXCL3 CNV groups for a number of COAD clinical outcomes. Data are presented as −log10(FDR) and −log10(P)-values, with significance highlighted

Kaplan-Meier analysis demonstrated that patients with CXCL1 amplification (n = 49) had a significantly shorter Disease-Free Interval (DFI) compared to those with wild-type (WT) status (Log-rank P = 0.037; Fig. 4D). This association was specific to DFI, as CXCL1 amplification was not significantly associated with DSS, OS, or PFS (Fig. 4E). Furthermore, the association of CXCL1 amplification with reduced DFI was more pronounced than for CXCL2 or CXCL3 amplification (Fig. 4E). These data identify CXCL1 amplification as a prevalent genomic event in COAD that is specifically linked to an increased risk of disease recurrence.

DNA methylation of CXCL1 and its gene correlation in COAD

The regulation of CXCL1 in COAD is strongly linked to epigenetic modification. As shown in Fig. 5A, CXCL1 expression is highly and significantly elevated in COAD tumor tissue compared to normal tissue. This overexpression is likely driven by the observed hypomethylation of the gene’s promoter region, specifically at the cg19170015 locus, where tumor samples exhibit significantly lower Beta-values than normal controls (Wilcoxon P < 6e-10, Fig. 5B). Furthermore, this epigenetic dysregulation appears to correlate with disease progression, as the degree of CXCL1 hypomethylation (indicated by lower M-values) significantly increases with advancing pathological stage in COAD (Anova P = 0.029, Fig. 5C). The overall methylation landscape in COAD is associated with distinct changes in gene expression; specifically, there is co-activation of genes with hypo-methylated promoters (e.g., IDO1) and silencing of genes with hyper-methylated promoters (e.g., YWHACS), suggesting that CXCL1 hypomethylation is part of a broader, stage-dependent epigenetic reprogramming signature in COAD (Figs. 5D-E). This analysis offers significant insights into the potential functional interactions and regulatory pathways associated with CXCL1 in COAD.

Fig. 5.

Shows the methylation analysis of CXCL1 in COAD. A CXCL1 CpG Methylation in COAD B CXCL1 promoter methylation status in COAD. C CXCL1 methylation correlation with pathological stage in COAD. D Top 25 genes with hypo-methylated promoters and corresponding expression in COAD. E Top 25 genes with hyper-methylated promoters and corresponding expression in COAD

Correlation of CXCL1 expression and immune cell infiltration in COAD

TIMER analysis demonstrated a positive association between CXCL1 levels and the abundance of six specific tumor-infiltrating lymphocyte subsets in COAD. CXCL1 expression exhibits the strongest positive correlations with the infiltration levels of Macrophage (Rho = 0.693, P = 1.10e-30) and Neutrophil cells (Rho = 0.547, P = 3.55e-09). While weaker, significant positive correlations were also observed for CD4 + T and CD8 + T cells (Fig. 6A). This strong affinity for myeloid cell recruitment is confirmed and extended by the pan-cancer analysis in Fig. 6B, where CXCL1 expression demonstrates a broad pattern of positive correlation across numerous cancer types with the infiltration of multiple immune cell subsets, most notably myeloid-derived cells, including neutrophils and MDSCs (Myeloid-Derived Suppressor Cells). Collectively, these analyses reveal a strong correlative link between CXCL1 expression and immune cell infiltration, most notably of myeloid cells, positioning it as a potential marker of an inflammatory, pro-tumorigenic TME across cancers.

Fig. 6.

Immune cell and CXCL1 correlation. A The correlation between CXCL1 expression and tumor-infiltrating immune cells from the TIMER database. B Analysis of the connection between immune cell subsets and CXCL1 expression across cancers

Drug sensitivity

Pan-cancer analysis, incorporating data from the GDSC and CTRP databases, revealed a consistent pattern. As shown in Figs. 7A-B, high CXCL1 expression was significantly correlated (FDR < 0.05) with resistance to a broad array of compounds across diverse cancer cell lines. In the GDSC dataset, a majority of drugs showed a positive correlation coefficient with CXCL1 (indicating resistance), with agents such as AR-42 exhibiting particularly high significance (-log10(FDR) > 10). A similar trend was observed in the CTRP dataset, where compounds like Avramilamide showed a strong positive correlation. These pan-cancer results suggest that elevated CXCL1 expression may serve as a correlative marker for a generalized therapy-resistant phenotype.

Fig. 7.

The relationship between CXCL1 expression and drug sensitivity was investigated using the GSCALite database. A Correlation between CXCL mRNA expression and GDSC drug sensitivity. B Correlation between CXCL1 mRNA expression and CTRP drug sensitivity. (7 C) Correlation between CXCL1 mRNA expression and small molecule sensitivity in COAD cell lines

In contrast, the COAD-specific analysis presented a more complex and context-dependent profile (Fig. 7C). Within colon adenocarcinoma cell lines, CXCL1 expression was associated with resistance to certain agents, as indicated by negative Z-scores (e.g., for endo-WRK-1). Notably, it was also correlated with increased sensitivity to other compounds, demonstrated by positive Z-scores for drugs such as Simularian and nicardamide (FDR < 0.05). This divergent association underscores that the relationship between CXCL1 expression and drug response is not uniform but is highly dependent on both the cellular context (tumor type) and the specific therapeutic agent.

Discussion

COAD presents a persistent therapeutic challenge, underscoring the need for biomarkers that reflect its complex molecular pathogenesis. Through an integrated multi-omics framework, this study delineates the clinical and biological significance of the chemokine CXCL1 in COAD. We confirm its significant upregulation at the mRNA and protein levels in tumor tissues. More importantly, we elucidate a multi-layered regulatory landscape: CXCL1 dysregulation is associated with concurrent genetic amplification and focal epigenetic hypomethylation at a key promoter locus, exhibits robust correlations with specific immune cell infiltration patterns, and demonstrates a context-dependent association with therapeutic response. While this analysis identifies CXCL1 as a candidate biomarker, we emphasize that our findings are primarily correlative and serve to generate focused hypotheses for future mechanistic investigation. This integrative approach aligns with contemporary biomarker discovery pipelines in CRC, such as the multi-omics methodology employed for DLX4 [27], and contributes a novel, data-rich profile of CXCL1 to this field.

Our analysis reveals that CXCL1 overexpression in COAD is underpinned by complementary genetic and epigenetic mechanisms, a dual-regulation model that enhances its potential as a stable biomarker. We identified CXCL1 amplification as a prevalent genomic alteration, and patients harboring this copy number gain experienced a significantly shorter Disease-Free Interval. This establishes amplification as a potential genetic driver of early recurrence. Concurrently, our epigenetic analysis across multiple CpG sites identified promoter hypomethylation, particularly at the cg19170015 locus, as strongly and negatively correlated with CXCL1 expression. The degree of hypomethylation at this site intensified with advancing pathological stage, suggesting a dynamic, stage-dependent epigenetic contribution to CXCL1 activation. This integrative genomic-epigenetic perspective is a key novel finding of our study. The focused identification of a specific, prognostically significant CpG site (cg19170015) aligns with the strategy of defining precise epigenetic biomarkers in CRC, as demonstrated in recent work integrating methylation signatures with immune profiles [28]. This convergence of genetic and epigenetic dysregulation provides a compelling molecular basis for the sustained oncogenic signal associated with CXCL1 in COAD.

The tumor-promoting effects of chemokines are largely mediated through their role in shaping the immune landscape [29]. Our data provide strong correlative evidence that CXCL1 is associated with an immunosuppressive TME in COAD. Functional enrichment analysis confirmed that CXCL1 and its co-expressed genes are central to chemokine signaling and leukocyte chemotaxis. At a cellular level, we observed robust positive correlations between CXCL1 expression and the infiltration of macrophages and neutrophils [30]. Importantly, more granular analysis revealed a significant positive correlation with an MDSC abundance signature and a concurrent negative correlation with a metric of cytolytic activity. This pattern is consistent with established mechanisms in other malignancies [31], such as pancreatic cancer, where CXCL1/CXCR2 signaling facilitates metastasis by recruiting immunosuppressive myeloid cells [32]. Therefore, our data suggest that elevated CXCL1 may be a marker of a TME characterized by myeloid-driven immunosuppression and impaired cytotoxic function, rather than indicating a direct role.

Beyond its canonical immune functions, our GO analysis of molecular functions revealed an intriguing correlation between the CXCL1-associated gene set and terms related to oxidoreductase activity. This novel, hypothesis-generating observation suggests a potential, less-explored intersection between chemokine signaling and cellular redox or metabolic states within the TME, an area that merits dedicated investigation in future studies.

The translation of biomarker discovery into therapeutic strategy is paramount. Our pharmacogenomic analysis yielded nuanced insights. In a pan-cancer context, high CXCL1 expression was broadly correlated with resistance to a wide array of compounds, suggesting it may be a marker of a generalized therapy-resistant phenotype, potentially linked to the immunosuppressive TME with which it correlates [33]. However, in COAD-specific cell lines, the association was more complex, with CXCL1 expression correlating with sensitivity to certain agents like nicardamide [34]. This indicates that the therapeutic vulnerability linked to CXCL1 is likely highly context- and agent-specific.

These correlations have direct implications for therapeutic development. The CXCL1/CXCR2 axis is a clinically investigated target, and our data provide a rationale for exploring CXCR2 inhibitors in COAD subsets defined by high CXCL1 or its amplification, with the aim of disrupting myeloid cell recruitment [33]. Furthermore, the observed epigenetic regulation suggests that the activity of demethylating agents on CXCL1 expression and its downstream effects warrants examination. Finally, the identification of compounds showing correlated sensitivity in high CXCL1-expressing COAD models opens avenues for exploring rational combination therapies.

Limitations and future perspectives

This study provides a robust, multi-dimensional nomination of CXCL1 as a COAD biomarker, several limitations must be acknowledged. First, the core findings are associative, derived from retrospective bioinformatic analysis. Although statistically robust, these correlations do not establish causality. The proposed roles of CXCL1 in immune modulation and therapy resistance remain hypothesis-generating and require direct functional validation using in vitro and in vivo models. Second, while our expanded qPCR cohort (n = 6 pairs) strengthens mRNA-level validation, future work should prioritize protein-level confirmation (e.g., IHC on tissue microarrays) and functional studies in relevant COAD models to establish mechanistic causality. Third, the drug sensitivity data are derived from monolayer cell cultures, which do not fully recapitulate the complex in vivo TME. Finally, this study lacks in vivo functional validation; employing CXCL1 modulation in patient-derived xenograft or murine models of COAD is an essential next step.

Conclusion

In conclusion, this multi-omics investigation establishes CXCL1 as a multi-faceted biomarker in COAD pathogenesis. We elucidate a novel regulatory framework involving concurrent genetic amplification and stage-associated epigenetic hypomethylation at a specific promoter locus. We demonstrate its strong correlation with an immunosuppressive myeloid-rich TME and define its complex association with therapeutic response. By synthesizing these data layers, CXCL1 emerges as a compelling candidate for further development as a prognostic indicator and a component of therapeutic strategies aimed at modulating the tumor immune microenvironment in colon adenocarcinoma.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

JL: writing – original draft. HT: review & editing. WT: Writing – review & editing, Funding acquisition, Supervision.

Funding

The author(s) declare financial support was received for the research by Department of Anesthesiology, People’s Hospital of Guangxi Zhuang Autonomous Region-Nanning, Nanning 530016, Guangxi Autonomous Region CN China.

Data availability

The gene expression data for the TCGA Colon and Rectal Cancer (COADREAD) cohort analyzed in this study are publicly available from the UCSC Xena platform (https://xena.ucsc.edu/) under the dataset identifier TCGA.COADREAD.sampleMap/AgilentG4502A_07_3. Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/) under the accession number GSE136889. Clinical Proteomic Tumor Analysis Consortium (CPTAC) (https://proteomics.cancer.gov/programs/cptac), and cBioPortal (https://www.cbioportal.org/). All supporting online tools are cited in the manuscript. The original RT-qPCR data are available from the corresponding author upon request, and primer sequences are provided in the supplementary file.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of The First School of Clinical Medicine, Southern Medical University, Guangzhou, China (Approval No. 202409808). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Competing interests

The authors declare no competing interests.