Inflammation and detection: Rethinking the biomarker landscape in gastric cancer

Abstract

Gastric carcinoma is a leading cause of cancer-related mortality worldwide, yet reliable noninvasive biomarkers for its early detection remain limited. As research continues to elucidate the inflammatory underpinnings of tumor initiation and progression, it has become increasingly clear that pro-inflammatory cytokines may hold promise as diagnostic adjuncts. Serum cytokines such as interleukin (IL)-1β, IL-6, IL-8, and interferon-gamma have been frequently reported as elevated in gastric cancer patients compared to healthy individuals. These molecules, known for their roles in modulating tumor-promoting inflammation, angiogenesis, and immune evasion, may serve as accessible indicators of disease presence or progression. Several studies have shown that individual cytokines, particularly IL-6 and IL-8, can achieve receiver operating characteristic curves and area under the curve values exceeding 0.70, suggesting reasonable diagnostic utility. We assess the comparative utility of individual cytokines versus multiplex panels, evaluate their roles in tumor biology and treatment resistance, and situate these findings within the broader inflammatory biomarker landscape. Limitations of the current literature, including small sample sizes, heterogeneity in study design, and lack of specificity, are critically discussed. We advocate for prospective, multicenter validation studies and highlight the promise of integrating inflammatory cytokine profiling into diagnostic algorithms. Composite cytokine panels may better reflect the complex immunobiology of tumor progression and offer a scalable, accessible adjunct to current gastric cancer screening strategies.

Key Words: Biomarker; Cytokine; Diagnosis; Gastric carcinoma; Inflammation; Pro-inflammatory

Core Tip: This letter evaluates the diagnostic and therapeutic utility of key inflammatory cytokines, such as interleukin (IL)-1β, IL-6, IL-8, and interferon-gamma, in gastric carcinoma (GC). These molecules are discussed as both biomarkers and drivers of tumor progression and chemoresistance. The discussion situates these markers within a broader inflammatory biomarker landscape that includes IL-10, IL-11, IL-18, C-X-C motif ligand 9, and host genetic factors. The analysis supports the use of multiplex cytokine panels over single markers for GC detection and treatment stratification, and outlines future directions for clinical integration and biomarker-guided therapy.

TO THE EDITOR

Gastric carcinoma (GC) remains one of the most lethal malignancies worldwide, in part due to the persistent lack of reliable noninvasive biomarkers for early detection. Ren et al[1] reported significantly elevated serum levels of interleukin (IL)-1β, IL-6, IL-8, and interferon-gamma (IFN-γ) in GC patients compared to healthy controls. Among these, IL-1β, IL-6, and IL-8 demonstrated potential diagnostic utility, with each yielding receiver operating characteristic (ROC) curves and area under the curve (AUC) values greater than 0.70 for distinguishing GC patients from controls.

Chronic inflammation is a well-established driver of gastric carcinogenesis[2,3]. Inflammatory mediators, such as IL-1β, IL-6, IL-8, and IFN-γ, modulate cell proliferation, angiogenesis, and immune evasion in GC. Recent reviews emphasize the “inflammation–cancer” axis and note that cytokines are being exploited as therapeutic targets in oncology[2,4]. Helicobacter pylori (H. pylori) infection triggers gastric mucosal release of cytokines and chemokines, fostering a microenvironment that promotes malignant transformation[4]. However, clinically useful blood biomarkers for GC are lacking, hampering early detection and risk stratification[5-7].

Among a diverse array of biomarker candidates, inflammatory cytokines have gained attention for their potential as both diagnostic indicators and biological mediators of tumorigenesis. Elevated levels of IL-1β, IL-6, IL-8, and IFN-γ have been consistently reported in GC patients compared to healthy controls, with diagnostic accuracy demonstrated by ROC AUC values in multiple studies[5,8].

Pro-inflammatory cytokines play a pivotal role in shaping the tumor microenvironment (TME) in GC, influencing tumor growth, angiogenesis, metastasis, and resistance to therapy. IL-1β acts as a potent driver of inflammation and tumor progression. It promotes epithelial–mesenchymal transition and activates nuclear factor-kappa B (NF-κB) signaling, contributing to GC cell invasion and metastasis. It also enhances angiogenesis by upregulating vascular endothelial growth factor (VEGF) and disrupts mucosal integrity, fueling chronic inflammation[9].

IL-6 functions via the Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) pathway, which is frequently hyperactivated in GC. IL-6 stimulates tumor cell proliferation, immune evasion, and chemoresistance. Elevated IL-6 Levels correlate with deeper invasion and lymph node metastasis[9,10].

IL-8 is a chemokine secreted by tumor and stromal cells, and promotes angiogenesis, enhances GC stem cell survival, and contributes to drug resistance through the CXC chemokine receptor 1 and 2 (CXCR1/2) signaling axis. Its levels are elevated in both early and advanced stages of GC and have been implicated in peritoneal dissemination[10].

IFN-γ, while traditionally viewed as anti-tumorigenic due to its immune-activating effects, can paradoxically induce immune exhaustion and upregulate programmed death ligand-1 (PD-L1) expression on tumor cells, thereby facilitating immune escape. It reflects a context-dependent dual role in tumor biology[11].

While multiple studies have reported elevated cytokine levels in GC, many vary in sample size, assay methodology, and control selection, factors that may impact reproducibility. Moreover, relatively few have undergone external validation in independent cohorts, and even fewer have linked biomarker performance to clinical outcomes such as survival or treatment response. Thus, while promising, the clinical utility of cytokine biomarkers remains limited by methodological heterogeneity and lack of standardization. This letter aims not only to summarize existing findings but also to critically appraise their translational readiness and highlight areas requiring further validation.

As described above, Ren et al[1] conducted a case-control study (n = 50 GC, n = 50 controls) measuring serum IL-1β, IL-2, IL-6, IL-8, IL-12, tumour necrosis factor-alpha (TNF-α), and IFN-γ levels by multiplex Luminex assay. They found IL-1β, IL-6, IL-8, and IFN-γ were significantly elevated in GC (P < 0.01 each), whereas IL-2, IL-12, and TNF-α were not. Their findings that IL-1β, IL-6, IL-8, and IFN-γ were significantly elevated in GC patients are in line with several prior studies linking these cytokines to tumor inflammation and immune dysregulation. This manuscript analyzes the diagnostic and prognostic value of these findings in the context of existing evidence and those reported in the literature.

IL-1β, IL-6, and IL-8 each achieved AUC > 0.70 for GC diagnosis. Notably, IL-1β and IL-6 Levels correlated with higher T and N stages. Their ROC results (AUCs = 0.71–0.78) indicate moderate accuracy. For example, IL-6 had an AUC of 0.72. Notably, combining markers improved performance. A three-cytokine panel (IL-1β+IL-6+IFN-γ) yielded AUC = 0.888, far higher than any single marker. This mirrors other studies where multi-marker panels outperform single analytes. For instance, an antibody array study identified an 11-protein panel (including cytokine receptors) that distinguished GC from controls[8].

DIAGNOSTIC UTILITY OF SINGLE CYTOKINE TESTS VS A PANEL OF CYTOKINES

Table 1 summarizes the key findings of the diagnostic value of cytokines[1,5,9,10,12-16]. Single-cytokine tests often lack both sensitivity and specificity. Different elevated levels of circulating IL-6 have been reported in GC as a biomarker, correlating with reduced overall survival[17]. In Sánchez-Zauco et al’s work[5], IL-6 showed high specificity (97%) but low sensitivity (39%), and IL-1β/IFN-γ had low specificity. In contrast, Kim et al[18] showed high IL-6 sensitivity (85.7%) but low specificity (50.1%) in GC. Importantly, another meta-analysis of four studies (n = 390) found serum IL-6 alone had pooled sensitivity 80%, specificity 86%, and AUC 0.90 for GC, suggesting strong diagnostic potential[12]. Wang et al[12] reported IL-6 alone with an AUC of 0.90 in a meta-analysis, likely due to larger pooled sample sizes and heterogeneous populations. Ren et al’s work[1], IL-6 (AUC = 0.72) is lower, possibly due to limited sample size or assay differences. The discrepancies between studies may reflect assay variation [enzyme-linked immunosorbent assay (ELISA) vs multiplex], population genetics, or inclusion criteria (e.g., H. pylori status). Indeed, Ren et al[1] did not report H. pylori infection rates, which is a known confounder in cytokine-based studies due to its strong effect on IL-1β and IL-6 expression. These data suggest that combinatorial panels of cytokines (and possibly other markers) will likely be needed to achieve clinically useful accuracy[8].

Table 1 Diagnostic and prognostic value of cytokines in gastric cancer.

Cytokine	Change in GC vs control	Diagnostic performance	Therapeutic/prognostic notes		Ref.
IL-1β	Increased in GC	AUC = 0.7; sensitivity approximately 0.76, specificity approximately 0.43	Central in Helicobacter pylori-driven inflammation; blocking IL-1β (e.g., canakinumab) is feasible; associated with tumor invasiveness and poor prognosis		Ren et al[1], Sánchez-Zauco et al[5]
IL-6	Increased in GC	AUC = 0.72; meta analysis: Sensitivity 0.80, specificity 0.86, AUC = 0.90	Potent growth and survival factor via Janus kinase/signal transducer and activator of transcription 3; high IL-6 predicts worse survival and chemoresistance		Ren et al[1], Kai et al[9], Janiczek-Polewska et al[10], Wang et al[12], Laurino et al[14]
IL-8	Increased in GC	AUC = 0.78; evidence mixed (some studies report no difference)	Promotes angiogenesis/metastasis; IL-8/CXC chemokine receptor 1 and 2 inhibitors reverse platinum resistance in preclinical GC models; rising IL-8 after treatment predicts chemoresistance		Ren et al[1], Liu et al[13], Jiang et al[15], Limpakan Yamada et al[16]
IFN-γ	Increased in GC	AUC = 0.65 (below 0.7)	Key T-cell cytokine; might reflect immune activation rather than tumor presence; Sánchez-Zauco et al[5] found it up in early GC; role in immunotherapy contexts		Ren et al[1], Sánchez-Zauco et al[5]
Multi-cytokine panel (IL-1β + IL-6 + IFN-γ)	Increased in GC	AUC = 0.888	Best diagnostic performance; synergistic detection		Ren et al[1]

AUC: Area under the curve; GC: Gastric carcinoma; IFN-γ: Interferon-gamma; IL: Interleukin.

These comparisons indicate that no single cytokine is sufficiently accurate on its own. Instead, multiplexed panels combining several ILs (and possibly additional tumor or stromal markers) are likely needed for reliable GC screening[1,8]. Given these issues, combining cytokines with each other or with conventional tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 19-9] and novel markers (miRNAs, methylation) could improve performance[8]. Wu et al[8] identified several non-cytokine proteins (Notch-3, Galectin-8, EphA1, etc.) that were elevated in GC. Their approach suggests that adding diverse biomarkers can capture heterogeneous tumor biology. Multi-analyte blood tests (e.g., CancerSEEK) have shown promise in other cancers, hinting that a “cytokine signature” could be one component of a broader GC panel. Large-scale proteomic studies and machine-learning classifiers may optimize such panels.

Furthermore, a broader panel of inflammatory mediators and immune markers beyond IL-1β/IL-6/IL-8 may improve GC screening and stratification. Integrating multiple markers can enhance detection. Herein, we expanded the discussion to include additional validated biomarkers [IL-10, IL-11, IL-18, IL-24, monokine induced by IFN-γ (MIG)/C-X-C motif ligand 9 (CXCL9), macrophage inflammatory protein-1β (MIP-1β)/C-C motif ligands 4 (CCL4), IL-2Rα] and host genetic factors (IL-6 rs1800796, IL-8 rs4073). We compared their diagnostic performance, linked them to tumor stage/progression, and considered their roles in chemoresistance and immunotherapy response. Some of these biomarkers have limited diagnostic sensitivity alone.

IL-10 is an immunosuppressive cytokine produced by regulatory T cells that dampens anti-tumor immunity. Serum IL-10 is often elevated in advanced GC and associates with poorer prognosis[19]. Szaflarska et al[19] found IL-10 > 10 pg/mL preoperatively predicted significantly worse survival. Thus, high IL-10 may flag aggressive, late-stage disease and suggest immune evasion. IL-10 alone is not a strong diagnostic (it is lower-sensitivity), but in combination with IL-6/IFN-γ it may improve discrimination.

IL-11 is a member of the IL-6 family. IL-11 signals via gp130/STAT3 to promote epithelial proliferation. Necula et al[20] reported increased IL-11 (and IL-6) in gastric tumor tissue and mucosa, correlating with TNM stage. In that study, IL-11 was elevated in tumors (though IL-6, not IL-11, was linked to survival). Preclinically, IL-11 drives GC progression: Inhibition of IL-11 signaling (e.g., IL-11 muteins or anti-IL-11Rα antibodies) markedly reduces tumor burden in gp130-mutant mouse models. Clinically, IL-11 remains underused as a serum biomarker, but its overexpression in tumors makes it a candidate marker for tumor burden and a therapeutic target (IL-11 blockade in trials).

IL-18 is a pro-Th1 cytokine that induces IFN-γ. IL-18 is elevated in GC patient serum[12]. In Thong-Ngam et al[21], GC patients’ mean IL-18 (58.5 pg/mL) exceeded controls (30.8 pg/mL). An IL-18 cutoff of 40 pg/mL yielded 52.2% sensitivity and 83.3% specificity, indicating moderate diagnostic value. IL-18 Levels also correlate with systemic inflammation and may complement IL-6/IL-1β in a multi-marker panel.

IL-24 [melanoma differentiation-associated gene-7 (MDA-7)] is a tumor-suppressive cytokine. IL-24 induces apoptosis and inhibits angiogenesis in diverse cancers[10,22]. Although not yet established as a serum biomarker in GC, IL-24’s expression is often lost in tumors, and its overexpression inhibits GC cell growth. IL-24 gene therapy (MDA-7) is an area of active research. Clinically, IL-24 may serve as a marker of anti-tumor immunity or a therapeutic biologic. More studies are needed to validate its diagnostic utility in GC.

MIG (CXCL9) is a monokine induced by IFN-γ (CXCL9) that is a T-cell chemoattractant. Plasma CXCL9 is consistently elevated in GC patients[23]. CXCL9 Levels rose markedly in advanced (stage III–IV) disease. Thus, MIG serves both as a marker of tumor-associated inflammation and of immune response. High MIG suggests an IFN-driven milieu. Thus, it might predict responsiveness to immunotherapies that rely on T-cell infiltration.

MIP-1β (CCL4) is a macrophage chemoattractant. CCL4 is also elevated in GC patient plasma[23]. Its levels increase in nearly all GC cases vs healthy controls, but without a clear stage gradient. As CCL4 attracts monocytes and T-cells, elevated MIP-1β may indicate an active immune microenvironment. It has been linked to metastasis in other tumors, suggesting it could mark aggressive phenotypes.

IL2 receptor α-chain (CD25) is the soluble α-chain of the IL-2 receptor reflects T-cell activation (often secreted by regulatory T cells and activated lymphocytes)[24]. Elevated sIL-2Rα occurs in several cancers, including GC, and often parallels tumor burden[25-27]. Although specific GC studies are limited, soluble CD25 (sCD25) can indicate an immunosuppressive microenvironment. It may rise in advanced disease and could help gauge response to immunotherapy (high sCD25 could blunt IL-2 signaling to effector T cells)[25,28].

Gene Polymorphisms can impact the cytokine levels. Host genetics can modulate cytokine expression. Notably, IL-6 promoter single nucleotide polymorphism (SNP) rs1800796 (-572 G/C) and IL-8 promoter rs4073 (-251 T/A) have been linked to GC susceptibility in Asian populations[29]. A meta-analysis found these polymorphisms associated with increased GC risk[13]. Such variants may identify high-risk individuals or influence baseline cytokine levels. For example, rs1800796 (C allele) correlates with higher IL-6 production and may predispose carriers to more aggressive inflammation-driven GC.

Cytokine gene polymorphisms can significantly influence individual variability in inflammation-mediated tumor progression. For instance, specific variants such as IL-1RN 2 allele, IL-6-634 G/G, and IL-10-1082 A/G have been linked to differences in survival outcomes among gastrointestinal cancer patients in palliative care, suggesting potential prognostic relevance[30]. Similarly, the IL-8 -251T>A polymorphism has been associated with shorter overall survival in GC patients with diffuse-type tumors and larger tumor sizes[31].

Incorporating cytokine genetic profiling into clinical workflows may enable stratified surveillance strategies and personalized treatment planning, especially in patients predisposed to aggressive disease phenotypes. For example, genetic polymorphisms in cytokine genes, such as IL-6 rs1800796 and IL-8 rs4073, may help stratify patients based on their inherent inflammatory profiles, which in turn could influence tumor progression, immune response, and treatment sensitivity. These genetic markers can inform long-term risk and possibly therapy. For example, IL-8 polymorphisms associated with higher cytokine expression have been linked to shorter survival and may predict poorer response to immunotherapies, thus helping to identify candidates for alternative or intensified regimens[31]. Carriers of these high-risk alleles (common in Asian populations)[27] could be prioritized for surveillance or enrolled in prevention trials. In the future, one could imagine a “cytokine-genotype” profile guiding personalized therapy: An IL-6 × CC genotype patient with high serum IL-6 might be pre-selected for IL-6R antagonist trials. However, their clinical utility remains exploratory and requires validation in larger, prospective cohorts with diverse ethnic representation.

Although one single biomarker may only have a limited diagnostic value, biomarker panels (e.g., combining cytokines with CA-19-9 or imaging) show promise. One study combined 19 serum proteins (including IL-7, CA9, transforming growth factor-alpha, and others) to achieve approximately 100% specificity[32].

Furthermore, many inflammatory markers track with tumor stage. Ren et al[1] found serum IL-1β and IL-6 strongly correlated with T and N stage in GC. Thong-Ngam et al[21] similarly showed IL-6 Levels were higher in GC patients with distant metastases than in those without. Baj-Krzyworzeka et al[23] found that plasma MIG (CXCL9) and MCP-1 (CCL2) rose significantly only in advanced (stage III–IV) GC. Chemokine profiling shows that CCL2 (MCP-1) and CXCL9 (MIG) rise only in stage III–IV disease, whereas CCL4 (MIP-1β), CCL5, and CXCL8 are elevated even in early stages. These correlations suggest that rising cytokine levels can indicate tumor progression. As tumors progress, they elicit a broader and stronger systemic inflammatory response. Conversely, anti-inflammatory signals like IL-10 surge in late stages[19] and portend worse outcomes. Table 2 summarizes the function of key biomarkers and their stage association[1,5,12,19-23,25-29]. Integrating such stage associations can aid risk stratification: A patient with modest elevation of IL-6 but very high IL-10 may have occult advanced disease.

While several cytokines (e.g., IL-1β, IL-6, IL-8) demonstrate moderate diagnostic accuracy with ROC AUC values > 0.70, their true clinical utility lies beyond statistical metrics. In practice, these markers could help identify high-risk individuals, particularly in regions with limited access to endoscopy. For example, elevated IL-6 or IL-8 Levels in asymptomatic patients could prompt earlier surveillance, potentially detecting GC at a more curable stage. IL-10 and IFN-γ levels may also inform immunotherapy responsiveness, guiding therapeutic stratification. Thus, integration of cytokine panels into clinical workflows could personalize screening, improve prognostication, and enable earlier or more effective interventions, ultimately improving patient outcomes.

Table 2 Selected inflammation-related biomarkers in gastric cancer.

Biomarker	Function (immune role)	Diagnostic (AUC, sens/spec)	Stage association	Therapy relevance	Ref.
IL-1β	Pro-inflammatory, fever response; promotes tumor inflammation	AUC > 0.7 for GC	Increased with higher T/N stage	Not specific	Ren et al[1], Sánchez-Zauco et al[5]
IL-6	Pro-inflammatory, growth factor; STAT3 activator	AUC > 0.7; specificity approximately 97%, sensitivity approximately 39%	Increased with T/N stage; Increased in metastasis	Drives cisplatin resistance; targetable by anti-IL-6R therapy	Ren et al[1], Sánchez-Zauco et al[5], Wang et al[12], Thong-Ngam et al[21]
IL-8 (CXCL8)	Chemokine, neutrophil attractant; angiogenesis	AUC > 0.7	Likely increased in advanced/invasive GC (Helicobacter pylori linked)	Promotes metastasis; CXC chemokine receptor 1 and 2 inhibitors in trials	Ren et al[1]
IFN-γ	Th1 cytokine, anti-tumor effector	Increased in GC	Data limited	Reflects T-cell response; immunotherapy marker	Ren et al[1], Sánchez-Zauco et al[5]
IL-10	Anti-inflammatory, immunosuppressive (Tregs)	Low diagnostic yield alone	Increased in advanced disease, poor prognosis	Immunosuppressive tumor microenvironment; high IL-10 may predict poor ICI response	Szaflarska et al[19]
IL-11	IL-6 family, gp130/STAT3 activator (epithelial mitogen)	Not established for screening	Increased tumor/mucosal expression with stage	Mediates chemoresistance; anti-IL-11Rα agents under study	Necula et al[20]
IL-18	IFN-γ–inducer, Th1 cytokine	Sensitivity approximately 52.2%, specificity approximately 83.3% at 40 pg/mL	Likely increased with tumor burden	May potentiate immunotherapy via IFN-γ; possible adjuvant target	Thong-Ngam et al[21]
IL-24 (melanoma differentiation-associated gene-7)	Tumor-suppressor cytokine, induces cancer apoptosis	Investigational	Declined in tumors (anti-tumor effects)	Gene therapy for radiosensitization (preclinical)	Mao et al[22]
MIG (CXCL9)	T-cell chemoattractant (IFN-inducible)	Not used diagnostically	Increased in advanced GC	May predict T-cell infiltration; synergizes with checkpoint blockade	Baj-Krzyworzeka et al[23]
Macrophage inflammatory protein-1β (C-C motif ligands 4)	Monocyte/T-cell chemoattractant	Not used diagnostically	Increased in GC vs control (stage-independent)	May reflect myeloid infiltration	Baj-Krzyworzeka et al[23]
SIL-2Rα (CD25)	Marker of T-cell activation/regulation	Measured as immune activation index	Increased in advanced disease (likely)	Elevated by Tregs; may guide IL-2 or ICI therapy	Muhammad et al[25], Nakata et al[26], Park et al[28]
IL-6 rs1800796 (gene)	Promoter SNP (G/C) affecting IL-6 Levels	Not diagnostic	Not staging, but risk factor	High-risk allele may inform surveillance	Wang et al[29], Wang et al[27]
IL-8 rs4073 (gene)	Promoter SNP (T/A) affecting IL-8 Levels	Not diagnostic	Risk variant in Asians	Carriers may benefit from chemokine-targeted approaches	Wang et al[29]

Function and performance data are drawn from clinical studies. AUC: Area under the curve; CXCL: C-X-C motif ligand; GC: Gastric carcinoma; ICI: Immune checkpoint inhibitor; IFN-γ: Interferon-gamma; IL: Interleukin; SNP: Single nucleotide polymorphism; STAT3: Signal transducer and activator of transcription 3.

While several cytokines (e.g., IL-1β, IL-6, IL-8) demonstrate moderate diagnostic accuracy with ROC AUC values > 0.70, their true clinical utility lies beyond statistical metrics. In practice, these markers could help identify high-risk individuals, particularly in regions with limited access to endoscopy. For example, elevated IL-6 or IL-8 Levels in asymptomatic patients could prompt earlier surveillance, potentially detecting GC at a more curable stage. IL-10 and IFN-γ levels may also inform immunotherapy responsiveness, guiding therapeutic stratification. Thus, integration of cytokine panels into clinical workflows could personalize screening, improve prognostication, and enable earlier or more effective interventions, ultimately improving patient outcomes.

RELEVANCE TO THERAPY AND CHEMO RESPONSE

Inflammatory biomarkers may guide therapy selection and predict resistance in GC[33,34]. Beyond diagnosis, these cytokines are biologically active in GC and thus are potential therapeutic targets. IL-6 and IL-8 drive oncogenic pathways (e.g., STAT3, NF-κB, VEGF) in GC cells and the tumor stroma. Targeting these pathways has shown some promise. For example, IL-6/STAT3 activation is a known driver of chemoresistance in GC. High IL-6 Levels have been implicated in reducing cisplatin efficacy via STAT3-mediated survival signals (preclinical studies)[17,20,34]. Indeed, IL-6/STAT3 inhibitors are under study in GC models. Thus, an IL-6–high patient might benefit from combining chemotherapy with an IL-6 axis inhibitor (e.g., tocilizumab or STAT3 inhibitors).

Likewise, IL-11 shares that pathway. Preclinical models show IL-11 blockade (e.g., with IL-11 mutein or anti-IL-11Rα antibody) dramatically shrinks tumors[35], suggesting trials of IL-11 pathway inhibitors in GC.

Similarly, IL-8 mediates angiogenesis and chemoresistance. A recent preclinical study used reparixin (a CXCR1/2 inhibitor) to block IL-8 signaling, which reversed chemotherapy resistance and suppressed tumor growth in GC models[15,16]. Notably, Jiang et al[15] showed that IL-8 expression markedly increased in chemoresistant tumors, and that CXCR1/2 blockade restored platinum sensitivity. These findings align with clinical observations: GC patients who responded poorly to platinum-based chemo had higher IL-8 Levels, whereas IL-8 decreased in sensitive tumors[16]. Thus, IL-8 and IL-6 Levels may predict chemotherapy response, and their inhibition may enhance treatment efficacy.

IFN-γ’s role is more complex. While elevated IFN-γ can indicate immune activation, chronic IFN-γ signaling in the TME may also promote immune suppression or resistance to immunotherapy[36]. Therapeutically, exogenous IFN-γ has shown anti-tumor effects, but systemic IFN-γ can also induce PD-L1 and counterproductive effects[36,37].

While preclinical data on cytokine inhibition, such as IL-6 or IL-1β blockade, are promising, their translation to clinical settings is complex. Cytokines are pleiotropic molecules with roles in both tumor suppression and immune regulation, and their systemic blockade can lead to off-target immune suppression, infection risk, or loss of anti-tumor immunity[38].

Several cytokine-targeting agents are in early-phase clinical trials, but few have shown efficacy in GC specifically. For example, while IL-6 inhibitors like tocilizumab have shown activity in inflammatory malignancies, their efficacy in solid tumors remains underexplored[39].

To improve clinical translation, ongoing efforts are focusing on cytokine engineering and tumor-targeted delivery to reduce systemic toxicity while preserving local efficacy[40]. These innovations will be critical in harnessing cytokines as safe, effective components of combinatorial or personalized cancer therapies.

On the immunotherapy front, markers of immune suppression are key[33]. High IL-10 and sCD25 indicate an immunosuppressive milieu. Such patients might need priming (e.g., IL-10 blockade to deplete Tregs) before checkpoint inhibitors. Conversely, elevated MIG (CXCL9) implies a brisk IFN-γ–driven T-cell response, potentially predicting better responses to PD-1/PD-L1 blockade[41,42]. IL-2Rα levels may serve as a real-time readout of T-cell activation[26]. Rising sCD25[24] during therapy could reflect immune activation or immune exhaustion (depending on context) and might be monitored as a pharmacodynamic marker. Immunotherapies such as checkpoint inhibitors, which also modulate cytokine pathways, have gained traction in advanced GC, yet treatment resistance and biomarker heterogeneity remain major obstacles[43].

Emerging studies suggest that cytokines such as IL-6, IFN-γ, and IL-10 may serve as biomarkers for predicting response to immunotherapy in GC. Elevated IL-6 Levels have been linked to poorer outcomes with PD-1 inhibitors, potentially due to an immunosuppressive TME[44]. Conversely, higher baseline levels of IFN-γ have been associated with improved survival and better response to checkpoint blockade[41], likely reflecting a more activated immune profile.

Despite their promise, most findings remain retrospective and small-scale, necessitating large prospective validation studies. Without standardized assay thresholds and prospective trials, the clinical utility of cytokines as immunotherapy biomarkers remains preliminary and investigational. Future directions should include real-time cytokine monitoring during immunotherapy and multi-biomarker modeling that integrates cytokines with genomic and imaging data.

MOLECULAR AND CLINICAL EVIDENCE

The rationale for some cytokines as GC markers is supported by mechanistic and epidemiologic data. H. pylori infection activates the NLR family pyrin domain containing 3 inflammasome[45], leading to IL-1β production in the gastric mucosa. IL-1β drives mucosal inflammation and suppresses acid secretion, fostering atrophic gastritis and tumorigenesis. IL-6 is induced by H. pylori and forms an autocrine loop between macrophages and epithelial cells. High IL-6 promotes proliferation and inhibits apoptosis in GC cell lines[46,47], and IL-6 knockout mice develop fewer tumors[48].

Clinically, multiple studies report higher circulating IL-6 and IL-1β in GC patients. The meta-analysis by Wang et al[12] corroborates that IL-6 is consistently higher in GC (including TCGA data). Baek et al[11] conducted a prospective cohort analysis in Korea and found a graded increase in GC risk across IL-6 quartiles (hazard ratio = 3.5 for highest vs lowest) and significant associations for IL-1β and IFN-γ. These prospective data strengthen the link between chronic cytokinemia and GC incidence. In addition, Sánchez-Zauco et al[5] found that IL-10 (immunosuppressive) was elevated alongside IL-6 and IFN-γ in GC, suggesting an immune dysregulation signature.

LIMITATIONS OF CURRENT EVIDENCE

Despite encouraging signals, significant caveats remain. The Ren et al[1] study and many others are relatively small (tens to low hundreds of patients) and cross-sectional. Sánchez-Zauco et al’s study[5], for example, included 162 cases vs 201 controls, but had unmatched controls (blood donors).

From a clinical standpoint, the use of cytokines to “detect” or “diagnose” GC remains controversial. Some practicing oncologists emphasize, cytokines are inherently non-specific markers of inflammation, influenced by numerous confounding factors such as H. pylori infection, chronic or atrophic gastritis, systemic inflammation, or unrelated pro-inflammatory conditions. In the Ren et al[1] study and others, such variables were not adequately matched or controlled for. Historically, inflammatory markers like erythrocyte sedimentation rate and C-reactive protein, and neutrophil-to-lymphocyte ratio were occasionally checked, but these have largely been abandoned in the modern era of targeted therapy and precision diagnostics.

Ren et al[1] matched controls on health status but did not report H. pylori or age-matching details. Cytokine levels can be influenced by age, sex, body mass index, infections, and comorbidities; rigorous matching or multivariate adjustment is often lacking. Many studies use surgical patients and mostly advanced GC, so it is unclear how early GC or premalignant lesions behave.

In clinical practice today, cytokines are not used to guide diagnosis due to their low specificity. Thus, their specificity for GC vs gastritis or other tumors is limited. The measurement of IL-6 for diagnosing GC has the limitation of lacking diagnostic specificity, as levels of this marker, alongside other pro-inflammatory cytokines, can be elevated in acute or chronic inflammatory conditions, such as gastritis, autoimmune diseases, and infectious processes[5,49,50]. Several studies have demonstrated elevated IL-6 in non-malignant gastrointestinal disorders, including H. pylori-associated gastritis and autoimmune gastritis, which can confound its use as a cancer-specific marker[49,51]. In addition, systemic inflammatory states can also influence IL-6 Levels, limiting its utility for differentiating early-stage GC from benign disease[51,52].

These confounding variables underscore the need for multi-marker panels, stricter patient stratification, and prospective validation studies to improve diagnostic precision. Further research is necessary to delineate specific thresholds, kinetics, and marker combinations that can reliably distinguish malignant from benign gastrointestinal inflammation.

One of the other key barriers to implementing biomarker panels in routine cancer care is the lack of robust data on cost-effectiveness and clinical integration workflows. For most blood-based biomarkers, including inflammatory cytokines, optimal testing intervals and surveillance strategies remain undefined. This stems from a paucity of prospective studies evaluating their use alongside radiologic imaging and clinical examinations. Moreover, there is no consensus among major oncology guidelines regarding standardized biomarker use across tumor types, partly due to biological heterogeneity and limited validation. Evaluating cost-effectiveness also requires longitudinal data on patient-centered outcomes, including survival benefits, quality of life, and potential harms from false positives, such as unnecessary treatments or anxiety.

Technical factors also vary: (1) Different assays, such as ELISA vs multiplex; and (2) Specimens, such as serum vs plasma, yield inconsistent absolute levels. For example, Ren et al[1] found IL-8 up in GC, but Sánchez-Zauco et al[5] found no IL-8 difference. Such discordance may reflect population or methodological differences. Finally, many reports focus on statistical significance rather than clinical utility; e.g., an AUC of 0.72, while above chance, may not suffice for screening without a combination.

While cytokine profiling is biologically interesting, its clinical applicability for diagnosis is limited, and this must temper enthusiasm about its routine use. The shift toward circulating tumor DNA (ctDNA), minimal residual disease (MRD) testing, and personalized gene panels supports a move away from broad inflammatory markers toward highly specific molecular signatures. These platforms allow for real-time treatment monitoring and relapse prediction with far greater accuracy than cytokine-based tests.

The role of ctDNA technology in the diagnosis and surveillance of solid tumors, including GC, is rapidly evolving. Several studies have shed light on the utility of this technology to detect actionable genomic alterations early on, which can inform treatment options in treatment-naïve patients. Additionally, ultra-sensitive MRD testing can be used to detect small amounts of ctDNA in a personalized fashion. The MRD testing, in particular, has been used in several cancer types to guide clinicians in the escalation or de-escalation of cancer care. With the expanded use of these tests in the era of personalized medicine, the utility of measuring inflammatory cytokines to diagnose and survey cancers may be limited in the near future. However, ctDNA assays are currently costly and technically demanding, especially in low-burden disease. Furthermore, its sensitivity in early-stage GC remains limited[50,53-55]. Thus, cytokine-based panels and ctDNA are complementary. Cytokines may aid in early detection or risk stratification, while ctDNA excels at tumor-specific tracking and monitoring recurrence. Integration of both modalities could yield a more comprehensive diagnostic framework.

CLINICAL APPLICATIONS

For practicing oncologists, what actionable steps emerge? First, incorporating cytokine panels (beyond traditional tumor markers like CEA or CA72-4) could improve early detection, especially in high-incidence regions. A combined panel (IL-6, IL-8, IL-1β, IL-10) might achieve higher sensitivity/specificity than any single marker. Second, tracking these markers longitudinally could monitor response and recurrence. For example, falling IL-6/IL-8 after surgery or chemo might signal a good response, whereas rising IL-10 could warn of relapses.

Clinicians should also interpret these biomarkers in context. A mildly elevated IL-6 in an early-stage patient might be less worrisome than a similar IL-6 spike in a patient with radiologic disease burden. Integrating cytokine levels with imaging and endoscopy is key. Moreover, elevated markers may prompt additional evaluation: Unexplained high IL-18 or IL-10 might lead to more thorough staging or screening for synchronous lesions.

Therapeutically, anti-cytokine treatments are on the horizon. Currently, IL-6 and IL-11 inhibitors are approved or in trials for other diseases; immuno-oncology trials in GC should stratify patients by baseline cytokines. Oncology teams could consider adjunct anti-inflammatory strategies (like aspirin/non-steroidal anti-inflammatory drugs in some studies) for patients with high inflammatory biomarker loads.

Despite promising diagnostic and prognostic data, translation of cytokine panels into clinical practice faces several hurdles. First, assay variability, due to differences in detection platforms, sample handling, and quantification thresholds, limits reproducibility across institutions. Second, cost-effectiveness analyses remain limited, especially in low-resource settings where biomarker-driven screening must be balanced against economic constraints. Third, the feasibility of longitudinal monitoring using cytokine panels is not well defined. Unlike genomic biomarkers, cytokine levels can fluctuate with comorbid inflammation or infection, complicating interpretation. Standardizing time points, establishing dynamic cut-offs, and integrating cytokine trends with imaging and clinical metrics will be essential for real-world applications. As such, prospective trials that embed cytokine testing into diagnostic or therapeutic algorithms are critical for validating clinical impact.

A key limitation in interpreting cytokine biomarker data is their susceptibility to confounding by non-cancer-related inflammation. For instance, H. pylori infection significantly elevates serum IL-6 and TNF-α levels, even in non-malignant gastric conditions, leading to reduced specificity of these markers in distinguishing cancer from chronic gastritis[5,49,50,56]. Additionally, chronic comorbidities and other inflammatory conditions. can elevate cytokines independent of cancer status. These factors complicate the use of cytokines as standalone diagnostic tools.

Few studies to date have rigorously adjusted for these confounders or stratified control populations accordingly. This lack of adjustment may lead to overestimation of diagnostic accuracy in retrospective analyses. Future biomarker research must incorporate matched controls, multivariable adjustments, and standardized assay protocols to account for baseline inflammatory states and improve clinical interpretability.

FUTURE DIRECTIONS

While many studies evaluating cytokine biomarkers in GC report promising diagnostic metrics, their findings must be interpreted with caution due to methodological limitations. Most studies are retrospective, with relatively small sample sizes and heterogeneous control groups (e.g., healthy vs dyspeptic patients). The lack of standardized assay platforms and cut-off values further limits inter-study comparability. Few investigations include external validation cohorts or control for confounders such as comorbid inflammation or concurrent medications. These design features weaken the generalizability of reported sensitivity, specificity, and AUC values. Thus, future biomarker research should emphasize prospective design, standardized methodology, and clinical endpoint correlation to strengthen translational applicability.

In addition to technical variability, the absence of unified clinical guidelines for interpreting cytokine results presents a major obstacle to clinical adoption. Unlike established tumor markers, cytokine assays lack standardized reference ranges, assay calibration protocols, and defined clinical thresholds for diagnostic or therapeutic decisions. Therefore, the development of consensus guidelines by oncology societies and laboratory medicine bodies is urgently needed to ensure reliable integration of cytokine-based diagnostics into real-world clinical workflows.

Furthermore, most available studies on cytokine biomarkers in GC are derived from relatively small, single-center cohorts, often with limited ethnic or geographic diversity. This constrains the external validity of reported findings. Additionally, heterogeneity in study design, such as variation in control groups, assay platforms, and diagnostic thresholds, further limits the comparability and reproducibility of results. These issues underscore the need for well-powered, multicenter trials with standardized methodologies and independent validation cohorts to confirm the diagnostic and prognostic utility of cytokine panels across diverse patient populations.

Cytokine panels have the potential to complement existing diagnostic modalities rather than replace them. Endoscopy, while the current gold standard for GC detection, is invasive, costly, and resource-intensive, limiting its accessibility in low-resource settings. In contrast, cytokine-based assays offer a non-invasive and scalable alternative for initial risk stratification[57].

Compared to ctDNA, which excels in molecular profiling and MRD detection, cytokine assays capture aspects of the host-tumor immune interaction, which may precede detectable genetic alterations[58]. This complementary role is particularly important in early or low-burden disease, where ctDNA may be absent. Integrating cytokine panels with ctDNA and imaging can yield a multi-parametric diagnostic framework, potentially enhancing early detection, monitoring, and treatment personalization[8].

Moving forward, we advocate multi-pronged research. Prospective studies must test combined biomarker panels, including cytokines, chemokines, and genetic SNPs, in large cohorts to establish robust sensitivity/specificity and determine optimal cutoffs. Longitudinal cohorts are essential: Following high-risk or early-stage GC patients over time will clarify how cytokine dynamics predict progression or recurrence. Coupling cytokine profiling with genomics, transcriptomics, and microbiome data could yield composite risk models, improving upon single-marker tests[9]. For example, a model that includes IL-6 Levels, IL-6/IL-10 genotype, and H. pylori status might identify subgroups for targeted prevention.

To advance this field, larger prospective studies are needed. These should enroll asymptomatic high-risk individuals like those with H. pylori or atrophic gastritis and serially measure cytokines to assess the prediction of future GC. Rigorous matching by age, H. pylori status, and inclusion of multiple control groups, including benign gastric diseases, will clarify specificity. Integrative omics, such as proteomics and transcriptomics, may identify additional cytokines or receptors (e.g., IL-6R, CXCR1/2) as markers. Mechanistic studies should dissect when and how cytokines rise: For instance, does IL-6 increase only at invasion, or earlier?

Therapeutically, clinical trials could explore cytokine blockade in GC. IL-6R antibodies or JAK inhibitors may be tested as adjuncts to chemotherapy, given the role of IL-6/STAT3 in chemoresistance[14]. IL-8 axis inhibitors warrant clinical evaluation, especially in chemoresistant disease, as preclinical data are compelling[15]. Biomarker-driven trials could stratify patients by baseline cytokine levels to see if high-cytokine GC benefits from targeted agents.

Combining cytokine levels with other immune markers (e.g., circulating T-cell profiles, checkpoint ligands) could yield predictors of response to immunotherapy in GC. The evolving landscape of GC treatment suggests cytokine signatures might also guide these modalities in the future.

Cytokines may hold more promise as predictive rather than diagnostic biomarkers, particularly in the context of immunotherapy. While cytokines are not used in clinical decision-making for GC diagnosis, their potential role in predicting response to immune checkpoint inhibitors is intriguing. Inflammatory biomarkers might help identify subtypes of gastric cancer with more robust immune activation or resistance, supplementing known markers like PD-L1 and tumor mutational burden. As published data emerge, stratifying cytokine profiles in responders vs non-responders to immunotherapy in GC could offer novel insights, though validation in prospective clinical trials is essential.

Finally, therapy-guided diagnostics should be developed. Predictive models that incorporate inflammatory markers to guide chemotherapy choice or immunotherapy need research. For example, a predictive nomogram could combine baseline IL-6, IL-10, and clinical stage to estimate the benefit from adding an IL-6 inhibitor. In sum, translating these biomarkers into practice will require interdisciplinary collaboration: (1) Laboratory assays must be standardized and cost-effective; and (2) Guidelines must be created for interpreting cytokine panels. Clinicians must be educated on integrating these inflammatory signals into GC care.

CONCLUSION

Ren et al[1] contribute valuable data that IL-1β, IL-6, and IL-8 are elevated in GC and correlate with tumor stage. However, these cytokines alone do not suffice as a stand-alone diagnostic test. Their greatest utility may lie in multi-marker panels and as adjuncts to risk models. In parallel, IL-6 and IL-8 are emerging as actionable targets and predictors of chemoresistance[15,16,59]. Ren et al's study[1] complements and extends prior literature by suggesting that a composite cytokine panel may offer improved diagnostic accuracy compared to single markers alone. The limitations of current evidence, small cohorts, confounding inflammation, and inter-study variability must be addressed in future research. Ultimately, a comprehensive strategy integrating cytokine biomarkers with clinical risk factors could improve early GC detection and personalized therapy.