Gastric cancer (GC) is among the most prevalent malignant tumors of the digestive system. Global cancer statistics indicate that in 2021, there were 968,350 new cases and 659,853 deaths due to gastric cancer worldwide (1). The insidious onset, high invasiveness, and malignant nature of GC lead most patients to be diagnosed at intermediate or advanced stages, resulting in a poor prognosis (2, 3). The TNM staging system is widely used for clinical prognosis evaluation (4); however, due to the heterogeneity of GC, clinical outcomes can vary significantly, even among patients at the same TNM stage receiving similar treatments (5). Therefore, it is crucial to identify more precise biomarkers for predicting the prognosis of GC.

With advancements in cancer prognosis research, evidence increasingly suggests that inflammatory responses and nutritional status are crucial (6, 7). Inflammation can promote tumor growth, invasion, and metastasis (8), whereas nutritional status reflects overall health and immune function (9). Inflammatory markers, such as the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and pan-immune-inflammation value, are confirmed reliable prognostic biomarkers for GC patients (10, 11). Additionally, markers reflecting nutritional status, such as C-reactive protein, albumin (ALB) levels, and the prognostic nutritional index, also predict GC prognosis (12, 13). However, individual inflammatory and nutritional markers cannot comprehensively reflect the body’s status, limiting their prognostic value. LANR is a novel biomarker composed of lymphocytes, ALB, and neutrophils. By integrating inflammation, immunity, and nutritional status, it offers a more comprehensive tool for prognostic assessment. Existing studies show that LANR holds independent prognostic value in evaluating pancreatic cancer (14), nasopharyngeal carcinoma (15), and colorectal cancer (16). However, the prognostic significance of LANR in GC patients remains unexplored.

This study aims to use preoperative LANR, reflecting inflammation, immunity, and nutritional status, to explore its relationship with prognosis in GC patients. Additionally, it seeks to develop a new nomogram predictive model for effectively predicting overall survival (OS) in GC patients.

The incidence and mortality of GC are continually rising, significantly impacting human life and health. Despite the use of various factors, such as TNM staging, for prognostic evaluation, the risks of recurrence and death remain unclear. Inflammation, immune status, and nutritional condition have increasingly drawn attention in the pathogenesis and prognosis of GC. Integrating these three factors to comprehensively assess the prognosis of GC and provide treatment guidance is of great significance.

Inflammation is closely linked to tumors and plays a crucial role in tumorigenesis, progression, and metastasis (18). Neutrophils, important leukocytes in the immune system, exert a dual role within the tumor microenvironment. They promote tumor growth, angiogenesis, and metastasis by secreting cytokines, chemokines, and proteases (19). Simultaneously, they directly kill tumor cells by releasing reactive oxygen species and nitrogen oxides, or indirectly enhance the immune system’s attack on tumors by promoting T cell activity (20). Neutrophils can also secrete inhibitory cytokines that suppress T cell and natural killer cell functions, leading to immune escape and tumor progression (21, 22). Additionally, neutrophils can promote tumor metastasis by forming neutrophil extracellular traps that capture and assist tumor cells in colonizing new environments (23). Lymphocytes, major components of the tumor immune barrier, directly contribute to the killing of tumor cells and inhibit tumor cell proliferation and migration by secreting cytokines, inducing cytotoxic cell death, and playing a key role in tumor immune surveillance (24). Hematological biomarkers associated with neutrophils and lymphocytes have been shown to be independent prognostic factors in cancer patients, effectively predicting patient prognosis (25–27). Serum albumin, one of the most abundant proteins in the blood, plays a key role in maintaining plasma colloid osmotic pressure and overall nutrition and is commonly used in clinical assessments of nutritional status (28). In addition, serum albumin has been implicated tumor immune escape, growth, and metastasis. Nutrition is closely linked to the immune system, and malnutrition can activate systemic inflammation, impairing immune function and affecting the prognosis of cancer patients (9, 29). Studies have shown that serum albumin is an independent risk factor for the prognosis of various malignancies, including cardia adenocarcinoma (30), nasopharyngeal carcinoma (31), kidney cancer (32), and head and neck cancer (33). Therefore, changes in serum albumin levels provide important prognostic information for clinical decision-making, aiding in the evaluation of treatment outcomes and prognosis in cancer patients.

As an integrative metric, LANR captures three key biological dimensions of host–tumor interaction. Lower LANR values—reflecting neutrophilia, lymphopenia, and hypoalbuminemia—may mark a high−risk host–tumor milieu characterized by systemic inflammation, impaired cellular immunity, and reduced tolerance to therapy. Such a milieu may facilitate tumor invasion, metastasis, and immune evasion. These mechanisms could partly explain the poorer survival observed in our cohort. Conversely, higher LANR values indicate preserved immune surveillance, attenuated systemic inflammation, and adequate nutritional reserves, consistent with better outcomes. Our study found that LANR is a strong prognostic indicator for GC patients, consistent with previous research findings.

In this study, we developed a novel index, LANR, which comprehensively reflects inflammation, immunity, and nutrition. This index is more comprehensive than single markers of immunity, inflammation, or nutrition alone. To our knowledge, this is the first study to investigate the prognostic value of LANR in GC patients. Several clinical studies have confirmed the prognostic significance of LANR. For instance, Wang et al. (34) found that LANR can predict relapse-free survival in endometrial cancer. Zhuang et al. (14) demonstrated that LANR is a reliable predictor of OS in resectable pancreatic ductal adenocarcinoma. Our study shown that lower preoperative LANR levels are associated with poor prognosis in GC patients, and that LANR is an independent prognostic factor for OS in GC patients. The associations between LANR and clinicopathological features differed between the two cohorts, possibly reflecting differences in sample size and baseline characteristics. In addition, the independent prognostic performance of LANR is superior compared to NLR, PNI and PLR. By integrating LANR with clinical and pathological parameters, we constructed a nomogram to predict 3-year, 5-year, and 7-year OS in GC patients, visually illustrating the impact of immunity, inflammation, and nutrition on survival outcomes in these patients. Calibration curves demonstrated good agreement between predicted and observed survival and DCA indicated net benefit across a range of clinically plausible threshold probabilities, supporting the nomogram’s reliability and potential clinical utility. The model may mitigate limitations of TNM staging by providing individualized risk estimates that complement stage-based categories. As an adjunctive risk-stratification tool, the nomogram may identify high-risk patients and guide closer surveillance and tailored management.

However, this study has several limitations. First, it is a single-center retrospective study with a limited sample size, which may introduce bias into the results. Therefore, large-scale, multicenter prospective studies are needed in the future to further validate these findings. Second, although we established a validation cohort for internal validation, external validation is still lacking. In subsequent studies, we plan to conduct multicenter external validation to enhance the reliability and generalizability of our findings.

In conclusion, our study demonstrates that preoperative LANR is an independent prognostic factor for GC patients. Based on LANR, we developed a new nomogram model that demonstrates high accuracy and potential clinical utility. Clinicians can use risk stratification to identify high-risk patients and tailor personalized interventions, providing scientific guidance and recommendations for the treatment of gastric cancer patients.