SLAMF6 Enhances the Efficacy of Anti‐PD‐L1 Immunotherapy in CRC Through the STAT1/CXCL10 Signaling Axis

ABSTRACT

As a T‐cell receptor co‐stimulatory protein, signaling lymphocyte activation molecule family 6 (SLAMF6) is a member of the immune cell activating receptor family and is expressed on T cells, B cells, natural killer cells (NK cells), and tumor cells. To date, the biological functions and clinical significance of SLAMF6 in certain solid tumors remain to be elucidated. We analyzed the transcriptional expression pattern of SLAMF6 and its relationship with clinical outcomes using clinical specimens and pancancer databases. Next, multispectral immunofluorescence was applied to assess the correlation between SLAMF6 expression and CD8⁺ T‐cell activation and infiltration in clinical samples, with additional validation through immune‐infiltration analysis. In parallel, using a colorectal cancer xenograft model, we examined how upregulation of SLAMF6 combined with immune‐checkpoint blockade (anti‐PD‐L1) influences immunotherapy efficacy. Ultimately, our findings indicate that SLAMF6 modulates CD8⁺ T‐cell activation and infiltration through the STAT1/CXCL10 axis, thereby enhancing the recruitment of these effector cells to tumor sites.

SLAMF6 recruits SHP‐2 to activate STAT1, upregulates CXCL10 and PD‐L1, promotes CD8⁺T cell infiltration, and enhances the efficacy of anti‐PD‐L1 therapy.

Abbreviations

BLCA

bladder urothelial carcinoma

BRCA

breast invasive carcinoma

CCL

C‐C motif chemokine ligand

CESC

cervical squamous cell carcinoma and endocervical adenocarcinoma

ChIP

chromatin immunoprecipitation

ChIP‐qPCR

chromatin immunoprecipitation quantitative PCR

CHOL

cholangiocarcinoma

CIBERSORT

Cell‐type Identification By Estimating Relative Subsets Of RNA Transcripts

COAD

colon adenocarcinoma

Co‐IP

co‐immunoprecipitation

CPS

combined positive score

CRC

colorectal cancer

CTLA‐4

cytotoxic T‐lymphocyte‐associated protein 4

CXCL10

C‐X‐C motif chemokine ligand 10

CXCL9

C‐X‐C motif chemokine ligand 9

CYT

cytolytic activity

DAB

3,3′‐diaminobenzidine

DAPI

4′,6‐diamidino‐2‐phenylindole

DLBC

lymphoid neoplasm diffuse large B‐cell lymphoma

DMEM

Dulbecco's modified Eagle medium

DNMT1

DNA methyltransferase 1

DNMT/DNMTs

DNA methyltransferase(s)

DNMTis

DNA methyltransferase inhibitors

dsRNA

double‐stranded RNA

ESCA

esophageal carcinoma

ESTIMATE

Estimation of STromal and Immune cells in MAlignant Tumors using Expression data

FFPE

formalin‐fixed paraffin‐embedded

GABA

gamma‐aminobutyric acid

GAPDH

glyceraldehyde‐3‐phosphate dehydrogenase

GBM

glioblastoma multiforme

GSEA

gene set enrichment analysis

GSVA

gene set variation analysis

HAVCR2

hepatitis A virus cellular receptor 2

HCC

hepatocellular carcinoma

HNSC

head and neck squamous cell carcinoma

HR

hazard ratio

HRP

horseradish peroxidase

ICI/ICIs

immune checkpoint inhibitor(s)

ICP

immune checkpoint

IFN‐γ

interferon gamma

IHC

immunohistochemistry

ITSM

immunoreceptor tyrosine‐based switch motif

JAK/STAT

Janus kinase/signal transducer and activator of transcription

JASPAR

transcription factor binding profile database

KICH

kidney chromophobe

KIRC

kidney renal clear cell carcinoma

KIRP

kidney renal papillary cell carcinoma

KRAS

Kirsten rat sarcoma viral oncogene homolog

LAIR1

leukocyte‐associated immunoglobulin‐like receptor 1

LGG

brain lower grade glioma

LIHC

liver hepatocellular carcinoma

LUSC

lung squamous cell carcinoma

MCPCOUNTER

Microenvironment Cell Populations‐counter

MDSC

myeloid‐derived suppressor cell

mIHC

multiplex immunohistochemistry

MSI

microsatellite instability

NK cells

natural killer cells

NRP1

neuropilin 1

NTB‐A

NK‐T‐B‐cell antigen

ORR

objective response rate

OS

overall survival

OV

ovarian serous cystadenocarcinoma

PAAD

pancreatic adenocarcinoma

PCPG

pheochromocytoma and paraganglioma

PD‐1

programmed cell death protein 1

PD‐L1

programmed death‐ligand 1

PFS

progression‐free survival

PRAD

prostate adenocarcinoma

p‐STAT1/pSTAT1

phosphorylated signal transducer and activator of transcription 1

PVDF

polyvinylidene fluoride

qPCR

quantitative polymerase chain reaction

qRT‐PCR

quantitative reverse transcription polymerase chain reaction

READ

rectum adenocarcinoma

SARC

sarcoma

SDS‐PAGE

sodium dodecyl sulfate‐polyacrylamide gel electrophoresis

seSLAMF6

soluble extracellular SLAMF6

SHP‐2/SHP2

Src homology 2 domain‐containing protein tyrosine phosphatase 2

SKCM

skin cutaneous melanoma

SLAM

signaling lymphocytic activation molecule

SLAMF6

signaling lymphocytic activation molecule family member 6

SPF

specific pathogen‐free

STAD

stomach adenocarcinoma

STAT1

signal transducer and activator of transcription 1

TAE

Tris‐acetate‐EDTA

TBS

Tris‐buffered saline

TBST

Tris‐buffered saline with Tween 20

TCGA

The Cancer Genome Atlas

TCR

T‐cell receptor

TGCT

testicular germ cell tumors

TGF‐β

transforming growth factor beta

THCA

thyroid carcinoma

THYM

thymoma

TIMER

Tumor Immune Estimation Resource

TISIDB

Tumor‐Immune System Interactions Database

TMA/TMAs

tissue microarray/tissue microarrays

TMB

tumor mutational burden

TME

tumor microenvironment

TNF‐α

tumor necrosis factor alpha

Tregs

regulatory T cells

TSA

tyramide signal amplification

TU

transducing unit

UCEC

uterine corpus endometrial carcinoma

UCS

uterine carcinosarcoma

UVM

uveal melanoma

XCELL

xCell cell‐type enrichment analysis

1. Introduction

While immune checkpoint inhibitor (ICI) therapy has markedly enhanced cancer patients' survival outcomes and is now recognized as a cornerstone of anticancer treatment, a substantial proportion of patients still do not achieve meaningful clinical benefit from these agents [1, 2, 3]. This limited response can be attributed to patient‐specific genetic and immunological profiles, which may give rise to either primary or acquired resistance. Moreover, emerging evidence indicates that dysregulated intracellular signaling pathways further compromise the efficacy of ICI therapy [4, 5]. For instance, Liao et al. demonstrated that in colorectal cancer (CRC), activation of the KRAS signaling pathway promotes an immunosuppressive tumor microenvironment (TME), thereby aggravating resistance to ICIs [6]. Similarly, in metastatic urothelial carcinoma, the TGF‐β signaling pathway impairs the effectiveness of anti‐PD‐L1 therapy by limiting T‐cell infiltration into tumors [7]. Additional studies have shown that β‐catenin signaling, triggered by the neurotransmitter GABA, inhibits both the infiltration and cytotoxic activity of CD8⁺ T cells, ultimately contributing to ICI treatment failure [8].

Clinical evidence indicates that the overall efficacy of immune checkpoint inhibitors (ICIs) in treating solid tumors remains limited. For example, the objective response rate (ORR) to ICIs in colorectal cancer (CRC) is only 5%–10% [1, 9], while the ORR to ICI monotherapy in hepatocellular carcinoma (HCC) is approximately 15%–20% [10]. Previous studies suggest that responses to ICIs are closely linked to the immunological features of the tumor microenvironment (TME) [11, 12]. An inflammatory TME, characterized by robust T‐cell infiltration and an immunologically active state, generally predicts favorable responses to immunotherapy. Conversely, a non‐inflammatory TME is often associated with T‐cell exhaustion, exclusion, and immunosuppressive mechanisms, leading to diminished therapeutic benefit [8, 12]. Therefore, strategies aimed at enhancing T‐cell infiltration and converting a non‐inflammatory TME into an inflamed phenotype hold promise for improving ICI efficacy [13].

Signaling lymphocytic activation molecule family member 6 (SLAMF6; also known as CD352, Ly108, or NTB‐A) is a key regulator of T cell activation, broadly expressed on T cells, B cells, NK cells, and certain tumor cells [14]. SLAMF6 functions as a homophilic receptor through self‐ligand engagement and belongs to the immunoglobulin superfamily as a type I transmembrane protein, structurally containing a membrane‐distal IgV domain, a membrane‐proximal IgC2 domain, and three cytoplasmic tyrosine‐based signaling motifs [15]. Through “head‐to‐head” homotypic or heterotypic intercellular interactions, SLAMF6 participates in modulating immune cell activation and differentiation, thereby coordinating both innate and adaptive immune responses. Accumulating evidence indicates that SLAMF6 promotes T cell activation, proliferation, and effector functions [16, 17]: its soluble extracellular domain (seSLAMF6) triggers SLAMF6 receptor dephosphorylation, stimulates IFN‐γ production from CD8⁺ T cells, and enhances their cytolytic activity [18]; the splice isoform SLAMF6 Δ17‐65 fine‐tunes T cell cytotoxicity [15]; and as a co‐receptor, SLAMF6 clusters with the TCR to synergistically amplify T cell responses upon TCR engagement [17]. Collectively, these findings establish SLAMF6 as a central player in orchestrating antitumor immunity. However, the role of SLAMF6 in shaping TME immunological features and regulating T cell activation in most solid tumors remains poorly understood [19, 20]. Given that insufficient T cell infiltration in the TME is a major constraint on ICI efficacy, targeting SLAMF6 signaling to enhance T cell recruitment and activation represents a promising strategy to improve ICI outcomes. This study focuses on colorectal cancer (CRC), aiming to systematically define the regulatory function of SLAMF6 in the tumor immune microenvironment and assess its potential as a combinatorial therapeutic target, demonstrating that SLAMF6 promotes CD8⁺ T cell infiltration and activation through the STAT1–CXCL10 axis and synergizes with anti‐PD‐L1 therapy to enhance antitumor efficacy.

2. Materials and Methods

2.1. Cell Lines and Cell Culture

The human CRC cell lines SW620, the acute T‐cell leukemia cell line Jurkat and the mouse colon cancer cell line MC38 were both purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). Authentication of each cell line was confirmed via short tandem repeat analysis, and the cells were cultured for fewer than 6 months after testing. Authentication of each cell line was confirmed via short tandem repeat analysis, and the cells were cultured for fewer than 6 months after testing. All cell lines were cultured in DMEM (Thermo, NY, USA) containing 10% fetal bovine serum (Gibco, CA, USA) and kept at 37°C under a 5% CO₂ atmosphere. Overexpression lentiviral particles targeting SLAMF6 were obtained from GenChem (Shanghai, China). Seed MC38 cells into 6‐well plates at a density preferably below 50%. When the cells exhibit good growth status and reach approximately 70% confluence, they are ready for lentiviral transfection. Dilute the viral titer to a final concentration of 1 × 10⁸ TU/ml using complete medium. Use puromycin at a final concentration of 2 ng/mL (prepared by adding 4 μL puromycin stock solution to 2 mL complete medium) to eliminate untransfected cells, thereby retaining only successfully transfected ones. After 16–24 h of incubation at 37°C, replace the culture medium. Assess fluorescence efficiency 48–96 h post‐transfection before proceeding with subsequent experiments.

2.2. Tissue Samples

In this study, three pairs of tumor and adjacent normal tissue specimens from patients with colorectal cancer (COAD), hepatocellular carcinoma (LIHC), and gastric adenocarcinoma (STAD), respectively, were collected at the Affiliated Hospital of Nantong University from March to December 2025.

2.3. Western Blotting Analysis

The procedures for SDS‐PAGE gel electrophoresis, membrane transfer, blocking, antibody incubation, and development were followed. First, separating and stacking gels were prepared for protein separation via electrophoresis. Subsequently, proteins were transferred onto a PVDF membrane using the wet transfer method, and non‐specific binding sites were blocked with skim milk. The membrane was then incubated sequentially with primary antibodies at 4°C overnight, thoroughly washed with TBST, labeled by second antibody at room temperature for 90 min, then washed with TBST. Finally, protein bands were detected using developing solution in an imaging system. The primary antibodies used in the experiments included: SLAMF6 (Abcam, ab213690), STAT1 (Proteintech, 10144‐2‐AP), Phospho‐STAT1 (Tyr701) (Cell Signaling Technology, #9167), GAPDH (Proteintech, 10494‐1‐AP), SHP‐2 (1:1000, CST, #3397).

2.4. Immunohistochemistry (IHC)

Human CRC and mouse tissue sections from mice inoculated with MC38 colorectal cancer cells underwent pre‐treatment including baking, deparaffinization, and rehydration. Antigen retrieval was performed by microwave heating in sodium citrate buffer. Following blocking of endogenous peroxidase activity and nonspecific binding sites with 5% BSA, tissue sections were incubated with primary antibody at 4°C overnight, followed by labeling with an HRP‐conjugated secondary antibody (rabbit) at room temperature for 30 min. Finally, DAB solution was applied for chromogenic detection. The primary antibodies used in this study were as follows: anti‐SLAMF6 (1:100, Abcam, ab213690), anti‐CD3 (1:100, Abcam, ab16669), anti‐CD8 (1:500, Cell Signaling Technology, #98941, Danvers, MA, USA), anti‐Ki67 (1:200, Proteintech, 27309‐1‐AP), anti‐CXCL10 (1:100, absin, abs135937), anti‐IFN‐γ (1:300, Proteintech, 15365‐1‐AP), and anti‐PD‐L1 (1:1000, Proteintech, 28076‐1‐AP).

2.5. Multiplex Immunohistochemistry (mIHC) Based on Fluorescence

Human tissue microarrays (TMAs) of CRC, gastric cancer, liver cancer, and breast cancer underwent pre‐treatment including baking, deparaffinization, rehydration, and fixation. Antigen retrieval was performed via microwave heating, and a blocking solution was used to reduce non‐specific binding. Sections were sequentially subjected to overnight incubation with primary antibody at 4°C, room temperature incubation with HRP‐labeled secondary antibody, and sequential rounds of staining with various TSA fluorescent dyes (Opal series) (Opal 620, 650, 690, 520, 540, 570, Akoya) interspersed with TBST washes. Finally, nuclei were counterstained with DAPI and sections were mounted, completing the multiplex immunofluorescence staining preparation. The primary antibodies used in the experiments included: SLAMF6 (1:100, Abcam, ab213690), CD3 (1:100, Abcam, ab16669), CD8 (1:500, Cell Signaling Technology, #98,941, Danvers, MA, USA), CXCL10 (1:100, absin, abs135937), and anti‐PD‐L1 antibody (1:1000, Proteintech, 28076‐1‐AP).

2.6. qRT‐PCR

The PCR protocol consisted of an initial denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 s, annealing at 60°C for 30 s, and extension at 72°C for 30 s. GAPDH was used as the internal reference gene, and the relative gene expression levels of the target genes were calculated using the 2^−ΔΔCt method. The primer sequences for the target genes are listed in the Table S1.

2.7. CHIP‐qPCR

Chromatin Immunoprecipitation (ChIP) was performed using the SimpleChIP Enzymatic Chromatin IP Kit (Magnetic Beads) according to the manufacturer's instructions (Cell Signaling Technology). Steps included: cross‐linking and sample preparation of cells, nuclear processing, and chromatin digestion using the kit's enzyme for 10 min, chromatin immunoprecipitation using anti‐STAT1 antibody (#9167, Cell Signaling Technology), elution of chromatin from antibody/protein G magnetic beads and reversal of cross‐links, DNA purification using spin columns, and detection of ChIP enrichment efficiency by real‐time quantitative PCR (qPCR). Purified DNA samples were used for ChIP‐qPCR experiments with primers targeting the promoter region of CXCL10 (sequences listed in Table S2).

2.8. Cell Immunofluorescence

Cells were seeded onto coverslips placed in 24‐well plates and cultured until reaching appropriate density. Subsequently, samples were prepared sequentially through fixation, permeabilization, and blocking. Next, target antigens were labeled by incubation with specific primary antibodies (Phospho‐STAT1 (Tyr701) (Cell Signaling Technology, #9167)) at 4°C overnight. On the second day, add the fluorescent secondary antibody (Alexa Fluor 488‐conjugated anti‐rabbit IgG, Jackson) and incubate at room temperature for 1 h. Counterstain the nuclei with DAPI, incubate for 5 min protected from light, and then observe and image the samples using a fluorescence microscope.

2.9. Clinical Specimens and Patient Clinical Profiles

Cancer tissues and their paired adjacent normal tissues were collected from patients diagnosed with CRC at the Affiliated Hospital of Nantong University. None of the patients had received chemotherapy or preoperative radiotherapy. Written informed consent was obtained from all patients, and this study was approved by the Ethics Committee of the Affiliated Hospital of Nantong University (Approval Number: 2019‐L053).

2.10. Agarose Gel Electrophoresis

A 3% agarose gel was prepared and poured into a casting tray containing a comb. The gel was allowed to solidify at room temperature to form loading wells. Once solidified, it was transferred to an electrophoresis chamber and submerged in 1× TAE buffer. The DNA marker and DNA samples, pre‐mixed with loading buffer, were then sequentially loaded into the wells. Electrophoresis was conducted at a constant voltage of 120 V for 10–15 min, and the results were visualized and analyzed using a gel imaging system.

2.11. Co‐Immunoprecipitation

(1) Prepare lysis buffer with protease inhibitors (Lysis Buffer: Protease Inhibitor Cocktail (100×) = 100:1, v/v); (2) Bead pretreatment: Vortex to resuspend beads. Transfer 20 μL beads per 500 μL sample, add TBS to 0.5 mL, separate on magnetic stand for 10 s, remove supernatant. Repeat wash twice; (3) Remove medium, wash cells once with PBS. Add 100–200 μL lysis buffer, incubate on ice for 30 min. Centrifuge at 10,000–14,000 × g for 3–5 min at 4°C. Collect supernatant (total protein lysate); (4) Add primary antibody to pre‐washed beads from step (2). Incubate at room temperature for 1 h on a rotator; (5) Add 500 μL TBS to resuspend, separate on magnetic stand for 10 s, remove supernatant. Repeat wash three times; (6) Add protein lysate from step (3) to antibody‐coated beads from step (5). Incubate overnight at 4°C with gentle rotation; (7) Separate on magnetic stand for 10 s, remove supernatant. Add 0.5 mL lysis buffer with protease inhibitors, resuspend, separate, remove supernatant. Wash beads three times; (8) Add 100 μL SDS‐PAGE Sample Loading Buffer to bead pellet (derived from 20 μL original beads). Heat at 95°C for 5 min; (9) Place on magnetic stand for 10 s, collect supernatant. Eluted samples are ready for SDS‐PAGE or Western blot analysis.

2.12. Construction of a Mouse Colon Cancer Xenograft Model

Five‐week‐old female C57BL/6 mice were maintained under specific pathogen‐free (SPF) conditions. To generate a xenograft tumor model, MC38 colon cancer cells were subcutaneously injected into the right forelimb of each mouse. Tumor volume was measured regularly beginning 1 week post‐inoculation. Treatment commenced when the tumor volume reached approximately 200 mm³; mice in the experimental group were administered an anti‐PD‐L1 antibody, whereas the control group received PBS injections. Following 20 days of treatment, the mice were euthanized, tumors were harvested intact, and tumor volume and weight were recorded to assess the antitumor efficacy of the respective treatment regimens.

2.13. Tumor Dissociation and Flow Cytometry

Single‐cell suspensions were generated from mouse tumor tissues through enzymatic digestion and mechanical dissociation. The cells were subsequently purified via sequential filtration, centrifugation to remove debris, and red blood cell lysis, with final cell counts adjusted to 10⁶–10⁷. Cells were resuspended in PBS supplemented with serum and stained by incubation with flow‐cytometry antibodies under dark conditions. Following staining, cells were washed with PBS, resuspended, and analyzed by flow cytometry. Data were analyzed using FlowJo software.

2.14. Gene Set Enrichment Analysis (GSEA)

To investigate the biological functions and potential signaling pathways associated with SLAMF6, we performed Gene Set Enrichment Analysis (GSEA). Using pan‐cancer transcriptome data from TCGA, we compared the top 30% of samples with high SLAMF6 expression and the bottom 30% of samples with low SLAMF6 expression.

2.15. SLAMF6 and Immune Cell Infiltration

We employed the Tumor Immune Estimation Resource (TIMER; http://timer.cistrome.org/), the ESTIMATE algorithm, and CIBERSORT to evaluate the relationship between SLAMF6 expression and the extent of immune cell infiltration in tumor tissues.

2.16. Statistical Analysis

Kaplan–Meier survival analysis was performed using the log‐rank test and Cox regression, with graphs generated using GraphPad Prism 8. GSVA was employed to evaluate the association between SLAMF6 expression and T cell activation signatures (IFN‐γ, CCL, and CYT scores). Kaplan–Meier Plotter was used to analyze the prognostic impact of SLAMF6 in combination with ICIs. All bioinformatics analyses were conducted using R software, and p < 0.05 was considered statistically significant.

3. Results

3.1. SLAMF6 Expression Is Dysregulated in Pan‐Cancer and Strongly Associated With Prognosis in Various Cancer Types

The differential expression of SLAMF6 in normal and malignant tumor tissues across various tumors was investigated using student t‐test. Compared to the normal counterparts, SLAMF6 was found to be considerably overexpressed in KIRP (p < 0.05), STAD (p < 0.05), HNSC (p < 0.05), and KIRC (p < 0.0001). Conversely, SLAMF6 expression was significantly lower in LIHC (p < 0.05), COAD (p < 0.0001), LUSC (p < 0.0001), THCA (p < 0.0001), READ (p < 0.05), BLCA (p < 0.05), and KICH (p < 0.01) (Figure 1A). High expression of SLAMF6 was demonstrated in representative tumor tissues, such as STAD and LIHC via Western blotting (Figure 1B). Against the baseline of low SLAMF6 expression in tumor tissues established in Figure 1A, we further explored its expression patterns across clinicopathological stages and immunological subtypes. Notably, SLAMF6 expression exhibited significant inter‐stage heterogeneity in COAD, LIHC, and STAD (p < 0.05), with a progressive downward trend as the disease advanced and the lowest expression levels observed in patients with Stage III–IV disease (Figure 1D). Cox regression and Kaplan–Meier survival analyses revealed that high SLAMF6 expression was significantly associated with favorable OS and PFS in SKCM, HNSC, CESC, and LIHC (HR = 0.83–0.93, p < 0.05), whereas it was significantly correlated with poor prognosis in GBM, LGG, UVM, and KIRP (HR = 1.24–1.52, p < 0.05) (Figure 1C,D, Figure S1). Collectively, these findings indicate that SLAMF6 expression is closely associated with prognosis across multiple cancer types in a cancer type‐dependent manner.

FIGURE 1.

SLAMF6 is dysregulated and prognostic across diverse cancers. (A) SLAMF6 expression among diverse tumor types. (B) Western blot validation. (C) Kaplan–Meier survival analysis was performed to assess the prognostic impact of SLAMF6 in various cancer patients. (D) High SLAMF6 linked to divergent prognosis. (E) SLAMF6 expression varied significantly across different immune subtypes.

3.2. Immune‐Related Characteristics of SLAMF6 Expression in Pan‐Cancer

Using the TISIDB database, we examined the association between SLAMF6 expression and immune/molecular subtypes across multiple cancer types. Immunophenotypes were categorized into six subtypes (C1–C6). Notably, SLAMF6 expression varied significantly among these subtypes in COAD, LIHC, and STAD, with the highest levels observed in subtype C2 of COAD and LIHC, and subtype C3 of STAD (Figure 1E), suggesting that SLAMF6 is differentially expressed across immune subtypes in a cancer‐type‐specific manner.

To further explore its role in antitumor immunity, we assessed the correlations of SLAMF6 expression with tumor neoantigens, TMB, and MSI. SLAMF6 expression was positively correlated with neoantigen burden in UCEC, SKCM, CESC, and LGG (Figure 2A). Regarding TMB, SLAMF6 showed positive associations in BLCA, BRCA, LGG, OV, SARC, UCEC, and UCS, whereas negative correlations were observed in GBM, KIRP, PAAD, PRAD, STAD, THCA, and THYM (Figure 2B). As for MSI, SLAMF6 expression was positively correlated with high MSI in COAD, READ, and UCEC, but negatively correlated in DLBC, ESCA, HNSC, KIRP, LIHC, LUSC, OV, PAAD, SARC, SKCM, STAD, and TGCT (Figure 2C). Collectively, these findings indicate a potential crosstalk between SLAMF6 expression and tumor immunity.

FIGURE 2.

The role of SLAMF6 expression in anti‐Tumor immunity across cancers. (A) A correlation analysis was performed between SLAMF6 expression and tumor neoantigens, tumor mutational burden (TMB), and microsatellite instability (MSI). (B) SLAMF6 expression is positively and negatively associated with TMB across cancer types. (C) The dual role of SLAMF6 in correlation with microsatellite instability.

3.3. SLAMF6 Positively Correlates With T‐Lymphocyte Infiltration in Multiple Cancers

To establish the connection between SLAMF6 expression and immune cell infiltration, we utilized the TCGA pan‐cancer dataset and applied multiple algorithms, including CIBERSORT, XCELL, TIMER, and MCPCOUNTER, to quantify immune cells in bulk tumor tissues. Intriguingly, SLAMF6 expression exhibited a strong positive correlation with CD8⁺ T cell infiltration in almost all cancer types, whereas it was significantly negatively associated with myeloid‐derived suppressor cell (MDSC) infiltration in most cancers (Figure 3A). SLAMF6 showed predominantly negative correlations with M2‐polarized macrophages across most cancer types, while its correlations with M1 macrophages were more variable, suggesting that SLAMF6 may be associated with an M1‐like anti‐tumor microenvironment. Furthermore, SLAMF6 demonstrated consistently positive correlations with resting NK cells in multiple cancers and showed weak‐to‐moderate positive correlations with Tregs in several cancer types, implying a potential counter‐regulatory mechanism. Thereafter, we performed multispectral immunofluorescence staining using clinical FFPE tissues to validate the correlation between SLAMF6 expression and CD8⁺ T cell infiltration in the tumor microenvironment of COAD, BRCA, LIHC, and STAD. Consistently, the immunofluorescence data indicated a positive correlation between SLAMF6 expression and CD8⁺ T cell infiltration in these cancer types (Figure 3B, Figure S2). Collectively, these observations suggest that high SLAMF6 expression is associated with increased CD8⁺ T cell infiltration across multiple tumors, and that its role extends beyond cytotoxic T cells to a broader immunoregulatory network.

FIGURE 3.

SLAMF6 positively correlates with T‐lymphocyte infiltration in multiple cancers. (A) Strong positive correlation between SLAMF6 and CD8⁺T cell infiltration. (B) Positive correlation between SLAMF6 and CD8+ T cells by multispectral immunofluorescence, Scale bar: 50 μm.

3.4. SLAMF6 High Expression Is Associated With Immune Activation and Cytotoxic T Cell Response

Transcriptomic data of each tumor type were stratified by S6 expression levels, with the top and bottom 30th percentile samples selected for differential gene enrichment analysis to identify S6‐associated signaling pathways. GSEA results indicated that SLAMF6 was significantly positively correlated with the activation of multiple immune‐related signaling pathways, including the Interleukin signaling pathway and the JAK/STAT signaling pathway (Figure 4A). In addition, SLAMF6 expression was found to be strongly associated with the cytotoxic T cell activation signature scores (CCL‐score, IFN‐γ score, and CYT‐score) in COAD (CCL‐score: R = 0.43, p < 2.2e‐16; IFN‐γ score: R = 0.4, p < 2.2e‐16; CYT‐score: R = 0.27, p = 7.3e‐9) (Figure 4B), BRCA (CCL‐score: R = 0.85, p < 2.2e‐16; IFN‐γ score: R = 0.8, p < 2.2e‐16; CYT‐score: R = 0.85, p < 2.2e‐16) (Figure 4C), LIHC (CCL‐score: R = 0.81, p < 2.2e‐16; IFN‐γ score: R = 0.76, p < 2.2e‐16; CYT‐score: R = 0.81, p < 2.2e‐16) (Figure 4D), and STAD (CCL‐score: R = 0.64, p < 2.2e‐16; IFN‐γ score: R = 0.56, p < 2.2e‐16; CYT‐score: R = 0.61, p < 2.2e‐16) (Figure 4E). The correlation between SLAMF6 expression and cytotoxic T cell activation signature scores in other tumors can be inquired in Figure S3. Collectively, these findings suggested SLAMF6 had immunomodulatory effects on the infiltration and activation of cytotoxic T cells.

FIGURE 4.

SLAMF6 Activates Immune‐Related Pathways and Is Linked to Cytotoxic T‐Cell Signatures. (A) SLAMF6 was significantly positively correlated with the activation of multiple immune‐related signaling pathways. (B–E) SLAMF6 expression demonstrated strong positive correlations with cytotoxic T cell activation signature scores across (B) COAD, (C) BRCA, (D) LIHC, and (E) STAD.

3.5. SLAMF6 Enhances T Cell Recruitment by Upregulating the Transcription of the Key Chemokine CXCL10 in CRC

To investigate the relationship between SLAMF6 and transcription factors, we analyzed culture supernatants from control and lentiviral overexpression groups (three replicates each) using a protein microarray. The results showed that CXCL10 was the most significantly upregulated factor upon SLAMF6 overexpression, exhibiting the highest fold change (Figure 5A). Volcano plots revealed that high SLAMF6 expression was associated with elevated expression of multiple cytokines (fold change > 2, p < 0.05), with CXCL10 being significantly increased in COAD, BRCA, LIHC, HNSC, and SKCM (Figure 5B, Figure S4). Moreover, CXCL10 expression was positively correlated with SLAMF6 expression (Figure 5C). IHC staining confirmed higher CXCL10 expression in early‐stage CRC compared with advanced‐stage CRC (Figure 5D), and TCGA data validation was consistent (p = 0.014) (Figure 5E). To directly verify the regulatory effect of SLAMF6 on T lymphocytes, we performed in vitro T cell migration assays using Jurkat cells as a T cell model. The results demonstrated that SLAMF6 overexpression in SW620 cells significantly promoted Jurkat cell migration and upregulated CXCL10 expression (Figure 5F,G), whereas CXCL10 knockdown significantly inhibited Jurkat cell migration and increased apoptosis (Figure 5H). This experimental design excluded any direct contribution from SLAMF6 expressed on T cells themselves, providing unambiguous evidence that tumor cell‐derived SLAMF6 drives T cell migration through CXCL10 secretion.

FIGURE 5.

SLAMF6 enhances T cell recruitment by upregulating the transcription of the key chemokine CXCL10 in CRC. (A) Protein microarray analysis confirmed CXCL10 as a key upregulated factor. (B) Volcano plots show gene expression changes in the SLAMF6 high‐expression group (red: upregulated, blue: downregulated, and gray: not significant). (C) The expression of CXCL10 was positively correlated with that of SLAMF6. (D) Immunohistochemical staining demonstrated a marked decrease in CXCL10 expression from early to advanced stages of colorectal cancer. (E) TCGA validation (p = 0.014). (F) Transwell migration model. (G) Quantification of migrated Jurkat cells and detection of CXCL10 expression in SW620 cell. (H) Quantification of migrated Jurkat cell count and viability.(*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).

3.6. SLAMF6 Increases CXCL10 Expression by Activating p‐STAT1 in CRC

Previous studies have reported that CXCL10 is modulated by phosphorylation of the STAT1 signaling cascade and that p‐STAT1 is negatively modulated by protein tyrosine phosphatase SHP‐2 in CRC cells [21]. Thus, we assumed that SLAMF6 may regulate CXCL10 expression through STAT1 signaling. SLAMF6‐overexpressing MC38 cells showed significantly enhanced p‐STAT1 phosphorylation and increased nuclear translocation of p‐STAT1 (Figure 6A,B). Co‐IP assays demonstrated a specific direct physical association between SLAMF6 and SHP‐2, consistent with the observation that SLAMF6 overexpression markedly downregulated SHP‐2 protein expression (Figure 6A). In addition, the expressions of CXCL10 and p‐STAT1 were increased in the xenograft tumor tissues of mice with SLAMF6 overexpression compared with the control group (Figure 6C). To determine whether p‐STAT1 signaling directly regulates CXCL10 transcription, we predicted several potential binding sites for STAT1 binding to the CXCL10 promoter region using the JASPAR dataset (Figure S5). Two STAT1 binding sites in the CXCL10 promoter region (–1931 to –1923, –779 to –771) were identified by ChIP‐qPCR and agarose gel electrophoresis (Figure 6D–F). Recovery assays were conducted to confirm whether p‐STAT1 was indispensable for SLAMF6‐induced T cell migration. We found that SLAMF6 overexpression on the migratory ability of T cells and the CXCL10 mRNA levels in SW620 cells could be diminished with Fludarabine (Selleck), a STAT1 phosphorylation inhibitor (Figure 6G,H). In summary, these observations identified the SLAMF6–STAT1–CXCL10 axis as a regulator of T cell infiltration in CRC and suggested that SLAMF6 overexpression could be a potentially viable strategy for immunotherapy.

FIGURE 6.

SLAMF6 increases CXCL10 expression by activating p‐STAT1 in CRC. (A, B) SLAMF6 overexpression reduced SHP2, elevated p‐STAT1, and enhanced nuclear p‐STAT1 expression. (C) CXCL10 and p‐STAT1 were upregulated in xenograft tumor tissues from SLAMF6‐overexpressing mice. (D–F) The application of ChIP‐qPCR (D, E) and agarose gel electrophoresis (F) revealed two STAT1 binding sites in the CXCL10 promoter region. (G, H) Inhibition of STAT1 phosphorylation by fludarabine attenuated SLAMF6‐induced T cell migration (G) and CXCL10 expression (H). (SLAMF6‐overexpressing SW620 cells were divided into two groups: One group was treated with fludarabine (10 μM, a STAT1 phosphorylation inhibitor), and the other served as an untreated control. After incubation at 37°C for 4 h, the migrated Jurkat cells in the lower chambers were quantified.).

3.7. SLAMF6 Overcomes Immunotherapy Resistance by Promoting CD8+ T Cell Infiltration and Activation in CRC

Decreased T cell infiltration is regarded as the predominant cause of resistance to ICIs. As SLAMF6 expression correlates with T cell infiltration, we hypothesized that SLAMF6 might be associated with the sensitivity of CRC to immunotherapy. We implemented a treatment schedule to determine whether SLAMF6 overexpression influenced immunotherapy responses of MC38 colorectal tumors (Figure 7B). MC38 cells with stable overexpression of SLAMF6 were constructed (Figure 7A, Figure S6) and subcutaneously inoculated into C57BL/6 mice. We next treated C57BL/6 bearing MC38 tumors with intraperitoneal injections of anti‐PD‐L1 or control PBS. MC38 tumors with SLAMF6 overexpression showed decreased volume and weight compared with tumors from the vector group. While treated with anti‐PD‐L1, MC38 tumors with SLAMF6 overexpression displayed the most remarkable response to immunotherapy (Figure 7C,D). Given that SLAMF6 overexpression enhances anti‐PD‐L1 response, we further performed Flow cytometry analysis, qRT‐PCR, and IHC to confirm that T‐lymphocyte infiltration was responsible for the enhanced immunotherapy response. As expected, we observed more CD8+ T cell infiltration in SLAMF6 overexpressing tumor tissues treated with anti‐PD‐L1 than in those from the control groups (Figure 7F,G). The IHC staining from this group displayed significant inhibition of tumor cell proliferation, decreased PD‐L1 expression, increased IFN‐γ expression, and CD8⁺ T cell infiltration compared to other groups (Figure 7E). These results indicate that SLAMF6 sensitizes colorectal cancer to immunotherapy by enhancing CD8⁺ T cell activation and infiltration.

FIGURE 7.

SLAMF6 overexpression sensitizes colorectal cancer to immunotherapy. (A) The MC38 cell line stably overexpressing SLAMF6 was generated using a lentiviral vector. (B, C) Images of the mouse and its tumor. (D) Tumor growth curves and tumor weight comparison in mice. (E) IHC analysis of mouse tumor sections (SLAMF6, CD3, CD8, IFN‐γ, HE, Ki67, and PD‐L1). Scale bar: 50 μm. (F) Flow cytometry was performed to detect the infiltration of CD8+ T cells in mouse tumors. (G) RT‐qPCR was performed to detect the mRNA expression of CD8A and IFN‐γ in mouse tumors.

3.8. High Expression of SLAMF6 Predicts the Favorable Response to ICIs

To further explore the potential mechanisms of SLAMF6 in tumor immunotherapy, we analyzed the correlation between SLAMF6 and immune checkpoint (ICP) genes in pan‐cancer. Significantly, SLAMF6 expression was positively related with these immune checkpoint genes, including neuronilin‐1 (NRP1), leukocyte‐associated immunoglobulin‐like receptor‐1 (LAIR1), CD48, CD28, HAVCR2, CD276, CD80, CD70, CD274, CD86, and CD44 in multiple cancers such as CHOL, COAD, KICH, LGG, PCPG, READ, etc. (Figure 8A). This implied that SLAMF6 might be involved in coordinating these ICP gene interactions and potentially serve as a promising biomarker for immunotherapy. We evaluated the impact of SLAMF6 expression on immunotherapy outcomes using anti‐PD‐1, anti‐PD‐L1, and anti‐CTLA‐4 treated cohorts from the Kaplan–Meier Plotter platform. Our analysis revealed that high SLAMF6 expression was significantly associated with favorable overall survival (OS) in patients receiving immune checkpoint inhibitor (ICI) therapy (p < 0.05) (Figure 8B). Likewise, patients with high CXCL10 expression exhibited significantly better prognosis than those with low CXCL10 expression in ICI‐treated cohorts (Figure 8C).

FIGURE 8.

High expression of SLAMF6 predicts the favorable response to ICIs. (A) SLAMF6 expression showed a positive correlation with multiple immune checkpoint genes across various cancer types, including CHOL, COAD, and LGG. (B) High SLAMF6 expression predicts a favorable response to immune checkpoint inhibitors (ICIs). (C) Elevated CXCL10 expression was associated with superior clinical outcomes following ICI treatment.

In summary, SLAMF6 could become a predictive biomarker for evaluating the prognosis or therapeutic outcomes of tumor patients receiving ICIs immunotherapy.

4. Discussion

Our pan‐cancer analysis revealed that SLAMF6 serves as a favorable prognostic marker in CRC and SKCM, but is associated with poorer prognosis in GBM, LGG, and UVM. This context‐dependent effect may be attributable to: (1) differential net outcomes of SLAMF6 signaling in distinct tumor immune microenvironments—promoting antitumor immunity in T‐cell‐inflamed “hot” tumors, while being converted into pro‐tumorigenic signals in myeloid cell‐dominated immunosuppressive tumors [17]; (2) differences in SLAMF6‐expressing cell types—expressed in tumor epithelial cells in CRC, but in macrophages/microglia in GBM [22]; and (3) as a SLAM family member, SLAMF6 contains ITSM motifs that can recruit both activating and inhibitory downstream molecules, with the net effect depending on cellular context and disease setting [23].

We discovered that SLAMF6 expression is correlated with clinical outcomes in cancer patients. Liu et al. reported that SLAMF6 expression is significantly lower in hepatocellular carcinoma (HCC) tissues compared to adjacent normal tissues [19]. Their study also indicated that high SLAMF6 expression predicts a favorable prognosis for HCC patients. Moreover, SLAMF6 expression is closely associated with CD8+ T cells and moderately correlated with B cells and dendritic cells. We further found in multiple clinical trial cohorts that high SLAMF6 expression is associated with a favorable prognosis in tumor patients receiving anti‐PD‐1 and anti‐PD‐L1. This finding implies that SLAMF6 could be a valuable predictive factor for ICIs [24].

Previous studies have reported that a high PD‐L1 combined positive score (CPS) and high tumor mutational burden (TMB) are predictive biomarkers for anti‐PD‐1, anti‐PD‐L1 immunotherapies. To investigate the role of SLAMF6 in anti‐PD‐L1 immunotherapy, we selected CRC as an immunotherapy model in this study. Currently, anti‐PD‐1 and anti‐PD‐L1 immunotherapies have been applied in the first‐line treatment of metastatic CRC. Clinical trial reports have shown that only a minority of CRC patients benefit from anti‐PD‐1 and anti‐PD‐L1 immunotherapies, with most CRC patients (approximately 85%) exhibiting response rates of only 5%–10% [25, 26]. These clinical trial results indicate that the efficacy of immunotherapy is largely limited by low CD8+ T cell infiltration in the TME [25, 27]. Here, we demonstrate that in a mouse model of CRC xenografts, upregulation of SLAMF6 expression combined with anti‐PD‐L1 therapy shows more significant efficacy compared to anti‐PD‐L1 monotherapy. Furthermore, a significant increase in the expression of SLAMF6, infiltrating CD8+ T cells, and IFN‐γ was observed in the xenograft tissues receiving combination therapy. Therefore, SLAMF6 plays a crucial role in the activation and infiltration of CD8+ T cells. This observation is consistent with the report by Conti et al., which indicated that activated CD8+ tumor‐infiltrating lymphocytes in melanoma and colon cancer are positively correlated with the expression of the T‐cell receptor co‐stimulatory protein SLAMF6, CD28, and the pro‐inflammatory cytokines IFN‐γ, TNF‐α, and granzyme B [28].

To elucidate the potential mechanism by which SLAMF6 activates and recruits CD8+ T cells, we compared the top 30% of samples with high SLAMF6 expression against the bottom 30% with low SLAMF6 expression, followed by GSEA analysis using TCGA pan‐cancer transcriptome data. As expected, high SLAMF6 expression was significantly associated with multiple immune‐related signaling pathways, including the TNF‐α signaling pathway, IFN‐α/γ response signaling pathway, STAT1 signaling pathway, and chemokine signaling pathway, all of which are involved in T cell activation and recruitment. SLAMF6 expression was found to be closely correlated with the CCL signature score, which is calculated based on the expression levels of CCL4, CCL5, CXCL9, and CXCL10. We performed protein tissue microarray analysis using lentivirus‐mediated SLAMF6 overexpression and found that the most significantly differentially expressed factor was the chemokine CXCL10, which also showed the highest fold change value.

Our in vivo and in vitro data show that overexpression of SLAMF6 significantly upregulates CXCL10 expression and improves CD8+ T cell infiltration. This observation aligns with the report by Cheng et al., who found that CD8+ T cells can be recruited by CXCL10 in the melanoma TME, significantly suppressing tumor progression. Furthermore, Shang et al. detected that TNF‐α initiates the phosphorylation of the STAT1 signaling cascade in inflammatory lung disease, leading to a marked increase in CXCL10 expression [29]. Following SLAMF6 overexpression, the levels of STAT1 phosphorylation and CXCL10 were elevated in xenograft tissues. ChIP‐qPCR and agarose gel electrophoresis results confirmed that the transcription factor STAT1 can bind to the promoter region of CXCL10 (−1931/−1923, −779/−771), accelerating CXCL10 transcription in CRC cells. Consequently, more CD8+ T cells are recruited to the TME and activated.

The epigenetic regulation of tumor cell proliferation and survival is critically mediated by DNA methyltransferases (DNMTs) [30]. Numerous studies have highlighted the significant association between aberrant DNA methylation and the development or progression of colorectal cancer. Our research group previously demonstrated that the low expression of the SLAMF6 gene is closely related to its methylation level. Compared to other subtypes, the CMS4 subtype exhibits a significantly higher methylation level of SLAMF6 [24]. CMS (Consensus Molecular Subtypes) is a widely used molecular classification system for colorectal cancer that categorizes CRC into four subtypes (CMS1–CMS4) based on gene expression profiles. Among these, the CMS4 subtype is characterized by a mesenchymal phenotype, high TGF‐β signaling activity, and enrichment of cancer‐associated fibroblasts, and is associated with the poorest prognosis, as well as immune exclusion and poor response to immunotherapy [24, 31]. By targeting DNMT1, hypomethylating agents like 5‐azacytidine and 5‐aza‐2′‐deoxycytidine demethylate the SLAMF6 promoter, leading to increased SLAMF6 expression and a resultant boost in the therapeutic response to PD‐1 antibodies [24]. Huang et al. discovered that DNMT inhibitors (DNMTis) induce viral mimicry in breast cancer cells by promoting the expression of endogenous retroviral elements [32]. This process leads to the accumulation of dsRNA, thereby triggering a cascade that enhances the production of interferons and chemokines, and upregulates interferon‐stimulated genes and PD‐L1. Consequently, combining DNMT inhibitors with anti‐PD‐L1 therapy significantly augments antitumor immunity in breast cancer.

This study demonstrates a positive correlation between SLAMF6 expression and T‐lymphocyte infiltration across multiple cancer types. In colorectal cancer (CRC) models, SLAMF6 activates the STAT1 signaling pathway, leading to upregulated CXCL10 expression in CRC cells. Elevated CXCL10 in turn promotes the recruitment and infiltration of CD8⁺ T cells into the tumor microenvironment. This enhanced CD8⁺ T‐cell infiltration, together with anti‐PD‐L1 blockade, synergistically improves the efficacy of immune checkpoint inhibitors (ICIs) against CRC. Moreover, SLAMF6 may negatively regulate SHP‐2, thereby contributing to the modulation of IFN‐γ‐mediated antitumor immune responses (Figure 9).

FIGURE 9.

SLAMF6 enhances anti‐PD‐L1 immunotherapy in CRC via the STAT1/CXCL10 axis. SLAMF6 activates STAT1 to upregulate CXCL10, promoting CD8⁺ T‐cell recruitment into CRC tumor microenvironment. Together with anti‐PD‐L1, this enhances ICI efficacy.

Author Contributions

Yu Wu: project administration, writing – original draft, writing – review and editing. Xinhui Lv: writing – review and editing, conceptualization. Shunhao Zhang: methodology, formal analysis. Yafang Chen: methodology, visualization. Sicong Liu: formal analysis. Feiyang Song: methodology. Chunmei Zhao: resources, data curation. Guihua Wang: resources, project administration. Xudong Wang: project administration, supervision, resources.

Disclosure

Animal Studies: All animal experiments were performed in accordance with the ARRIVE guidelines and approved by the Animal Experimental Ethics Committee of Nantong University (Approval No. S20211217‐005).

Ethics Statement

Approval of the research protocol by an Institutional Reviewer Board: The study protocol was approved by the Clinical Research Ethics Committee of the Affiliated Hospital of Nantong University (Approval No. 2019‐L053) and the Animal Experimental Ethics Committee of Nantong University (Approval No. S20211217‐005).

Consent

Written informed consent was obtained from all patients participating in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: Kaplan–Meier analysis revealed that high SLAMF6 expression significantly improved survival in COAD, BRCA, CESC, HNSC, and SKCM patients (median cutoff).

Figure S2: SLAMF6 expression was positively correlated with CD8 expression.

Figure S3: Correlation between SLAMF6 expression and cytotoxic T cell activation signature scores in other tumors.

Figure S4: CXCL10 expression was significantly increased in HNSC and SKCM.

Figure S5: The JASPAR database predicted STAT1 binding sites in the CXCL10 promoter region.

Figure S6: Fluorescence images of lentiviral transfection with SLAMF6 overexpression vector. Scale bar: 50 μm.

Table S1: The primer sequences for the target genes.

Table S2: Primer sequences for ChIP‐qPCR targeting the CXCL10 promoter region.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.