Pancreatic adenocarcinoma (PAAD) has become one of the most challenging malignancies in everyday clinical practice, as its incidence and mortality keep rising globally. Worldwide, around 12.5 new cases per 100,000 people are reported each year, and the numbers continue to climb. Unfortunately, fewer than 20% of cases are caught early; most patients are diagnosed at advanced stages, leading to a 5-year overall survival (OS) rate below 10%, with mortality nearly matching incidence [1][2]. The lack of reliable screening tools and the absence of specific early symptoms often cause delayed diagnosis, which in turn lowers the chance of surgical resection and limits curative options. Even when standard treatments are given, patients face high risks of recurrence and distant spread, resulting in very poor survival [3][4]. Over the past few years, progress has been made in molecular subtyping, genetic profiling, and tumor microenvironment studies of pancreatic cancer, and several biomarkers have been proposed as potentially useful. Still, advances in early diagnosis, risk prediction, and mechanism-guided personalized therapy remain slow. Only a handful of genes have been firmly linked to patient prognosis [5]-[8]. Therefore, digging deeper into the molecular drivers and biomarkers that underlie pancreatic cancer progression is a pressing scientific need, especially for improving early detection, refining risk stratification, and laying a theoretical foundation for precision diagnostics and therapies that work within the complex tumor microenvironment [9][10]. Systematic exploration of these molecular mechanisms could open up new ideas and approaches for early intervention and personalized treatment [11][12].

Lumican (LUM) was selected as the research candidate gene in advance rather than screened from genome-wide differential expression genes. Lumican (LUM) is a key member of the small leucine-rich proteoglycan (SLRP) family and is mainly found in the extracellular matrix (ECM), where it participates in collagen fibrillogenesis, cell migration, and tissue remodeling [13]. Although earlier studies have pointed to LUM’s involvement in several cancers, its specific expression pattern and functional role within the pancreatic cancer immune microenvironment are still not well understood. In healthy tissues, Lumican helps maintain tissue structure and supports cell-cell communication by regulating collagen fiber assembly and stability [13]. In different cancers, LUM expression shows distinct patterns depending on the tumor type. It can influence cancer cell growth, movement, and invasion through ECM remodeling and by modulating signaling cascades such as focal adhesion kinase (FAK), mitogen-activated protein kinase (MAPK), and matrix metalloproteinases (MMPs) [13][14]. Within the tumor microenvironment, LUM has been linked to cancer-associated fibroblasts (CAFs), immunosuppressive factors, and immune escape mechanisms, thereby affecting immune infiltration, epithelial-mesenchymal transition (EMT), and the recruitment of tumor-associated immune cells [15][16]. Interestingly, LUM seems to play context-dependent roles in cancer progression [17]. For example, in hepatocellular carcinoma, LUM influences tumor growth and metastatic potential by altering ECM composition [18]-[20]; in breast cancer, elevated LUM expression is tied to greater invasiveness and reprogramming of the immune microenvironment [21][22], underscoring its multifunctional regulatory nature. Evidence from pancreatic cancer suggests that pancreatic stellate cells are the main source of Lumican production. LUM expression is controlled by the transforming growth factor-beta/SMAD family member 4 (TGF-β/SMAD4) pathway and affects stromal collagen dynamics, playing an important part in cancer cell adhesion, migration, and microenvironment remodeling [23]. Existing reports have uncovered complex regulatory mechanisms of LUM expression and its autophagic degradation under hypoxia, and some have noted associations with patient outcomes in pancreatic cancer. However, current knowledge often focuses on isolated cellular or molecular aspects, lacking a comprehensive view of LUM’s integrated role in cancer initiation, progression, and immune microenvironment dynamics [24]. These observations provide good reasons to systematically investigate LUM function in pancreatic cancer and highlight the need to clarify its molecular regulation and interactions within the tumor microenvironment.

Building on this background, the present study used comprehensive public datasets of pancreatic cancer samples to systematically examine LUM expression patterns, their links with clinical variables, and their prognostic significance. Our goal was to better understand LUM’s role in pancreatic cancer pathogenesis and its clinical relevance. We consolidated high-quality RNA-seq expression data, detailed clinical information from UCSC XENA and GTEx databases, applying rigorous preprocessing and sample quality filtering to ensure analytical robustness and cross-platform consistency. The research approach consisted of four main parts: 1) genome-wide differential expression analysis of LUM; 2) GSEA to explore functional pathway differences between high- and low-LUM expression states; 3) immune infiltration characterization using ssGSEA and the Tumor and Immune System Interactions Database (TISIDB), which allowed quantitative assessment of the relationships between LUM expression and 28 immune cell types; and 4) survival and prognostic evaluation using Kaplan-Meier analysis and multivariate Cox proportional hazards regression to assess the impact of LUM expression on OS, progression-free interval (PFI), and disease-specific survival (DSS), supplemented by receiver operating characteristic (ROC) curve analysis to evaluate diagnostic accuracy. In the statistical analysis phase, we used the Wilcoxon rank-sum test, Kruskal-Wallis test, and logistic regression to thoroughly assess associations between LUM expression and patient clinical parameters. With a particular focus on the LUM-immune microenvironment relationship, this study systematically examined these correlations across different clinical subgroups, thereby clarifying the previously ambiguous role of LUM in pancreatic cancer pathological mechanisms. The findings suggest that LUM holds considerable promise as a new biomarker for pancreatic cancer diagnosis, molecular subtype classification, and prognostic stratification, thus providing a theoretical foundation for future research into precision therapeutics.

Through systematic bioinformatic analysis of transcriptomic and clinical data from public repositories (UCSC XENA and GTEx), this investigation comprehensively characterized LUM expression in pancreatic cancer and yielded several key findings. First, LUM was markedly upregulated in pancreatic cancer tissues compared with normal specimens, and it showed excellent diagnostic discrimination (AUC = 0.964), pointing to its potential as a diagnostic biomarker. Second, LUM expression levels did not depend on major clinicopathological variables such as age, sex, ethnicity, or tumor stage, suggesting that traditional clinical factors do not confound LUM expression. Third, GSEA revealed that high LUM expression was significantly enriched in multiple immune-related pathways, especially those involving complement activation, humoral immune responses, and B-cell receptor signaling, implicating LUM in immune modulation. Fourth, ssGSEA-based immune infiltration analysis showed that LUM expression significantly correlated with infiltration of various immune cell subsets, with the strongest association observed for central memory CD8+ T cells. Taken together, these findings offer new mechanistic insights into LUM’s potential role in immune microenvironment remodeling and provide a biological rationale for exploring LUM as a molecular target and biomarker in pancreatic cancer.

LUM is generally highly expressed across many tumor types and has been widely implicated in immunosuppression, tumor progression, and poor clinical outcomes. Numerous large-scale cohort studies and functional experiments have confirmed its role in promoting malignant phenotypes and establishing immunosuppressive microenvironments [15][37]. For example, in solid tumors such as gastric and bladder cancers, LUM expression is enriched in pathways related to ECM remodeling and EMT, which facilitate tumor cell invasion and immune evasion through interactions with stromal cells, fibroblasts, and immunomodulatory cells [38][39]. In breast cancer, elevated LUM expression is strongly associated with faster tumor cell proliferation, greater metastatic capacity, and activation of CAFs; moreover, LUM can enhance immunosuppression by regulating TGF-β signaling pathways [15]. However, in contrast to findings in some malignancies where high LUM expression correlates with significantly worse survival, our study observed that LUM expression did not stand out as an independent prognostic factor for overall survival in pancreatic adenocarcinoma. This discrepancy may indicate that LUM’s role in pancreatic cancer is more focused on tumor initiation and microenvironmental modulation rather than directly dictating survival outcomes. Overall, our work confirms high LUM expression in pancreatic cancer and its robust link to immune pathway activation from multiple analytical angles, thereby enriching our cross-tumor understanding of LUM’s multifaceted roles in immune microenvironment regulation and tumor biology.

The markedly elevated LUM expression in pancreatic cancer tissues and its excellent diagnostic performance in ROC analysis (AUC reaching 0.964) provide strong molecular evidence for potential clinical use in early disease detection and differential diagnosis [40][41]. Current evidence suggests that multi-biomarker panels, including LUM, can effectively identify pancreatic cancer at various stages and help with molecular subtype stratification [40]. Our investigation further shows that LUM expression does not correlate significantly with routine clinical variables (e.g., age, gender, tumor stage), indicating that LUM expression is largely independent of traditional clinicopathological stratification factors. This independence minimizes potential confounding and enhances its practical utility for risk stratification and molecular subtype identification [42]. Although survival analysis did not establish LUM as an independent prognostic factor, both the existing literature and our findings suggest that LUM retains substantial value for facilitating molecular subtype classification and mechanistic elucidation, particularly in shedding light on processes such as tumor cell proliferation, migration, drug resistance, and immune regulation [41][43][44]. Therefore, LUM shows considerable promise as a biomarker for clinical translation in pancreatic cancer early diagnosis, molecular classification, and mechanistic investigation.

Furthermore, the ssGSEA-based immune characterization revealed that LUM expression is prominently associated with the infiltration intensity of multiple immune cell populations, and notably, it shows a remarkably strong positive correlation with central memory CD8+ T cell enrichment. This observation carries substantial scientific and clinical significance [45]. Traditionally, LUM research has emphasized its ECM component function in regulating tumor cell behaviors [13][46]; however, our study uncovered a close relationship between LUM and immune cell populations, suggesting that LUM is significantly correlated with the infiltration abundance of multiple immune cell subsets and immune-related signaling pathways, suggesting its potential regulatory association with the pancreatic tumor immune microenvironment. Currently, the clinical efficacy of immunotherapy in pancreatic cancer remains suboptimal, partly because of the highly complex and immunosuppressive regulation of the tumor immune microenvironment [47][48]. Thus, these findings offer new perspectives and a theoretical foundation for understanding the immune characteristics of pancreatic cancer and identifying immunotherapeutic targets. Future fundamental and translational investigations focused on clarifying the interaction mechanisms between LUM and immune cells are expected to advance our understanding of the molecular pathways that mediate immune evasion and progressive tumor development in pancreatic cancer, while also creating new therapeutic avenues that target the tumor immune microenvironment [49]. Notably, as an extracellular matrix gene quantified via bulk RNA-seq, elevated LUM expression may mirror stromal abundance rather than solely representing intrinsic tumor biological features, which acts as a confounding factor for the correlation between LUM and immune infiltration.

By integrating the GSEA and immune infiltration analysis results, LUM may facilitate immune microenvironment remodeling and intercellular signaling through the regulation of multiple immune response pathways, including immunoglobulin receptor binding, complement activation, antigen recognition, and B-cell receptor signaling cascades [50]. The strong correlation between LUM and diverse immune cell subsets, particularly central memory CD8+ T cells, further suggests that LUM could be involved in orchestrating tumor immune dynamics and modulating the infiltration and activation status of these immune populations [51]. The proposed mechanistic models await further validation through targeted in vitro and in vivo functional assays to rigorously establish LUM’s precise roles in pancreatic cancer initiation and progression, as well as to clarify its utility as a molecular therapeutic target.

This study relies on publicly available transcriptomic databases (UCSC XENA and GTEx) and has not verified the biological functions of LUM through in vitro or in vivo experimental approaches. In addition, the combination of TCGA and GTEx datasets without batch correction may introduce platform-specific technical bias, which may overestimate the diagnostic AUC value of LUM; the diagnostic performance of LUM needs further verification in unified single-center sequencing cohorts. The limited sample sizes in these databases, together with missing data at some clinical and molecular levels, may affect statistical robustness and the generalizability of the conclusions. Moreover, the available data are primarily transcriptomic, lacking protein-level validation and functional experimental evidence; consequently, the clinical applicability of these findings is substantially constrained by data availability and current analytical methods. Future investigations should integrate large-scale, multi-institutional clinical datasets with experimental validation to strengthen the research framework and enhance the translational relevance of these molecular insights.

This systematic investigation demonstrates that the LUM gene is significantly upregulated in pancreatic adenocarcinoma and shows excellent diagnostic discrimination (AUC = 0.964), yet it does not exhibit a significant independent association with patient survival outcomes. Notably, elevated LUM expression is prominently enriched in immune-related biological pathways and shows a strong positive correlation with infiltration of multiple immune cell types, especially central memory CD8+ T cells (ρ = 0.759; P < 0.001). These findings suggest that LUM may contribute to pancreatic cancer pathogenesis through immunomodulation involving complement activation, humoral immune responses, and B-cell receptor signaling. Although LUM does not function as an independent prognostic factor, its substantial role in molecular subtyping and immune microenvironment regulation underscores its potential value as both a diagnostic biomarker and an immunomodulatory target. Future efforts should prioritize rigorous experimental validation and multicenter clinical investigations to translate these findings into clinical diagnostic and therapeutic applications, thereby advancing precision medicine approaches for pancreatic cancer management.

This research was funded by the Shenzhen Medical Research Fund (A2302051).

All data supporting the findings are included within the manuscript and supplementary materials. Transcriptomic and clinical datasets analyzed in this work were retrieved from UCSC XENA (TCGA-PAAD) and GTEx public databases (https://xenabrowser.net/, https://gtexportal.org/). Additional raw data are available from the corresponding author upon reasonable request.

Chen and Li conceived and designed the study. Li performed data curation, formal analysis, methodology, and software. Chen conducted an investigation, visualization, and wrote the original draft. All authors participated in validation, project administration, resource provision, and critical review and editing of the manuscript. All authors reviewed the manuscript.