Double-negative T cells with a distinct transcriptomic profile are abundant in the peripheral blood of patients with breast cancer

doi:10.21203/rs.3.rs-4714931/v1

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Research Article

Double-negative T cells with a distinct transcriptomic profile are abundant in the peripheral blood of patients with breast cancer

https://doi.org/10.21203/rs.3.rs-4714931/v1

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Background

Double-negative T (DNT) cells comprise a distinctive subset of T lymphocytes that play a significant role in the immune system. This study characterized peripheral DNT cells in individuals diagnosed with breast cancer (BC).

Methods

Peripheral blood DNT cells were collected from patients with BC and healthy controls by flow cytometry. The sorted DNT cells were analyzed by Smart-seq2 for single-cell full-length transcriptome profiling. Conducting bioinformatics analysis to pinpoint pivotal genes and investigate potential underlying mechanisms. RT -PCR was used to measure the relative expression of TMEM176B, EGR1, C1QB and C1QC.

Result

The percentage of DNT cells was higher in patients with BC than in healthy controls. In total, 289 differentially expressed genes (DEGs) were identified (|log₂FC| > 2, P < 0.05). Gene enrichment analysis indicated that the DEGs were significantly associated with complement activation, and B cell receptor signaling. We identified 2 module-related and 10 hub genes, including IFIT1, IFI27, RSAD2, IFIT3, EGR1, IFI44L, C1QB, C1QC, TMEM176A, TMEM176B, NGFR, and VCAM1. The results of RT-qPCR showed significant differential expression of TMEM176B, EGR1, C1QB and C1QC between the DNT cells of BC patients and healthy controls (P < 0.05).

Conclusions

DNT cells are abundant in patients with BC, and they might exert anti-tumor immune responses by regulating genes such as TMEM176B and EGR1.

Breast cancer

Double-negative T cells

Smart-seq2

Differentially expressed genes

Breast cancer (BC) is currently the most common cancer affecting women, and its incidence has been increasing on an annual basis [1]. The tumor microenvironment, which consists of cancer cells, immune cells, fibroblasts, endothelial cells, and cytokines, is a key determinant of malignant growth, the induction of angiogenesis, and tumor invasion and metastasis [2]. The heterogeneity and dynamics of these components influence tumorigenesis and progression and represent potential diagnostic markers or therapeutic targets [3]. CD3⁺CD4⁻CD8⁻ double-negative T (DNT) cells comprise a rare population accounting for only 3–5% of peripheral T lymphocytes, and these cells have been demonstrated to infiltrate solid tumors [4, 5]. Patients with chronic B cell lymphoid leukemia have significantly higher peripheral blood DNT cell counts than healthy controls, and the number of DNT cells is positively correlated with the number of CD3⁺ T cells [6]. Furthermore, thyroid tumors have significantly more DNT cells than benign nodules, and the percentage of DNT cells is a potential preoperative diagnostic indicator of thyroid cancer [7]. Zhang et al. reported successful outcomes of adoptive immunotherapy based on DNT cells against hematological malignancies [8–10]. In addition, several studies observed the significant anti-tumor effects of DNT cells in non-small cell lung cancer, pancreatic cancer, and triple-negative breast cancer [11–13]. These reports suggest that DNT cells function as immunomodulatory or immunosuppressive cells in various tumors. Through single-cell sequencing experiments, recent studies suggested that DNT cells comprise a functionally heterogeneous population consisting of subtypes such as cytotoxic, helper, and innate DNT cells [14].

This study aimed to explore the genetic and functional differences of peripheral blood DNT cells between patients with BC and healthy controls. To this end, we analyzed the proportion of DNT cells in both groups and screened the differentially expressed genes (DEGs) between the DNT cell populations of patients with BC and healthy controls using the Smart-seq2 technique. Smart-seq2 full-length transcriptome sequencing technology is suitable for analyzing specific cells and small numbers of samples. By improving reverse transcription, template switching, and preamplification, Smart-seq2 provides complete mRNA information with high sensitivity, precision, flexibility, and coverage [15, 16]. The putative functions of the DNT cells in BC were identified by bioinformatics analysis.

2.1 Clinical samples and ethics statement

Forty-eight participants, including 26 patients with BC and 22 healthy subjects, were enrolled in February 2023 at the 960th Hospital of the PLA Joint Logistics Support Force, China. The age at diagnosis ranged from 30 to 80 years. Patients lacking a pathologically confirmed diagnosis of BC and those with other malignancies, immunological disorders, or infections were excluded. The healthy subjects were examined at our hospital, and they exhibited no clinical evidence of any disease. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013), and the protocol was approved by the Ethics Commission of the 960th Hospital of the PLA Joint Logistics Support Force, China (No. 2023107).

2.2 Flow cytometry

Peripheral blood samples (2 mL) were collected from the subjects, and peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll gradient centrifugation. The PBMCs were stained with fluorochrome-labeled monoclonal antibodies against the following proteins [BD Biosciences (San Jose, CA, USA) or BioLegend (San Diego, CA, USA)]: 7AAD, CD8a (Clone: HIT8a) CD3 (Clone: UCTHT1), CD4 (Clone: RPA-T4), and CD19 (Clone: SJ25C1). Flow cytometry was performed using the FACSAria III system (BD Biosciences) and FlowJo software.

2.3 SMART-Seq2 sequencing and identification of DEGs

Total RNA was obtained from the lysed PBMCs, reverse-transcribed into cDNA, and purified to construct a high-quality library. The cDNA library was sequenced on the Agilent 2100 platform (Agilent Technologies, CA, USA). The DEGs between the BC and control groups were screened by DESeq2 software using |log₂FC| > 2 and P < 0.05 as the criteria. The Ggplot2 package was used to draw a volcano map to visualize the results.

2.4 Functional annotation of DEGs

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler R package. The results were visualized in the form of bubble charts using R software (R Foundation for Statistical Computing, Vienna, Austria).

2.5 Protein–protein interaction (PPI) network of the DEGs

The PPI network of the DEGs was constructed using the STRING (https://cn.string-db.org/) database [17] with confidence score ≥ 0.4 as the cutoff criterion. Cytoscape (version 3.9.1) [18] was used to visualize the PPI network. The top 10 hub genes in the network were identified using the cytoHubba plug-in of Cytoscape by applying the MCC algorithm. Significant modules in the PPI network were also screened by the MCODE plug-in using the following parameter settings: degree of cutoff = 2, node score cutoff = 0.2, k-core = 2, and maximum depth = 100.

2.6 RT-qPCR

Total RNA was extracted from the DNT cells using TRIzol reagent (Thermo Fisher Scientific, Waltham, MA, USA) and reverse-transcribed using the FastKing gDNA Dispelling RT SuperMix (Tiangen Biotech, Beijing, China) according to the manufacturers’ instructions. The cDNA was amplified by RT-qPCR using SYBR Green on a LightCycler 480 instrument (Roche Diagnostics, Basel, Switzerland). The thermal cycling conditions were initial denaturation at 95°C for 15 min followed by 40 cycles of denaturation at 95°C for 10 s, annealing at 60°C for 20 s, and extension at 72°C for 30 s. GAPDH was used as the internal reference gene. The relative expression of TMEM176B, EGR1, C1QB, and C1QC was calculated by the 2^−ΔΔCt method [19]. The genes and primer sequences are presented in Table 1.

Table 1

Primer sequences used for RT-qPCR
Gene name	Sequence (5′→3′)
GAPDH	Forward: GGAGCGAGATCCCTCCAAAAT Reverse: GGCTGTTGTCATACTTCTCATGG
TMEM176B	Forward: TACAGATGGATGCGGCGAAGT Reverse: TCAAGACACAGACAGCCAGGAA
EGR1	Forward: TACGAGCACCTGACCGCAG Reverse: AGTGGTTTGGCTGGGGTAACT
C1QB	Forward: TCTCTGCCACAAGAACCATCAAC Reverse: GGCGTGGTAGGTGAAGTAGTAGA
C1QC	Forward: AAGGTAGGGTACGACGGACTG Reverse: GTTCTCCCTTCTGCCCTTTGG

2.7 Statistical analysis

Data analysis was performed using GraphPad Prism 9.4.1 and R v.4.2.1. The Shapiro–Wilk test was used to assess the normality of data. The two-tailed unpaired Student’s t-test was used to compare two groups. P < 0.05 was considered statistically significant.

3.1 The proportion of peripheral DNT cells is increased in BC patients

The preoperative percentage of DNT cells in peripheral blood samples from patients with BC and healthy controls was analyzed by flow cytometry. As presented in Fig. 1, the percentage of DNT cells was significantly higher in patients with BC (P < 0.05). There were no significant differences between the two groups in terms of demographic parameters like age and gender.

3.2 Identification and functional characterization of DEGs

The DEGs in the DNT cells isolated from patients with BC were screened using Smart-seq2. Using |log₂FC| > 2 and P < 0.05 as the criteria, we obtained 289 DEGs, of which 137 were upregulated and 152 were downregulated in the BC group. The volcano map of the DEGs is presented in Fig. 2.

To further explore the potential biological functions of these DEGs, we performed GO and KEGG enrichment analyses using the clusterProfiler package of R software. The categories of biological processes (BP), molecular functions (MF), and cellular components (CC) were included in the GO analysis. The significantly enriched BP terms for the DEGs included immunoglobulin mediated immune response, complement activation, classical pathway, humoral immune response mediated by circulating immunoglobulin, complement activation, and B cell receptor signaling pathway. In addition, the DEGs were significantly associated with CC terms including external side of plasma membrane, immunoglobulin complex, and postsynaptic membrane. Regarding MF terms, DEGs were enriched in antigen binding and immunoglobulin receptor binding. Finally, KEGG analysis revealed that the DEGs were mainly enriched in pathways related to protein digestion and absorption, hematopoietic cell lineage, B cell receptor signaling, ATP-binding cassette transporters, and complement and coagulation cascades (Fig. 3).

3.3 Identification of core genes related to the DNT cells

To investigate possible associations between the DEGs, we constructed a PPI network using the STRING website. As presented in Fig. 4A, the PPI network consisted of 183 nodes with 121 edges. Using the MCODE plug-in of Cytoscape, we filtered five modules and obtained two pivotal modules. One module included IFIT1, IFIT3, IFI27, IFI44L, RSAD2, and EGR1 (Fig. 4B), and the second module included C1QB, TMEM176A, C1QC, and TMEM176B (Fig. 4C). The top 10 hub genes were identified by cytoHubba (ranked in MCC), and they included nine upregulated genes (IFIT1, RSAD2, IFI27, IFIT3, EGR1, IFI44L, C1QB, C1QC, NGFR) and one downregulated gene (VCAM1, Fig. 4D).

3.4 Gene expression validation by RT-qPCR

To confirm the results of Smart seq-2 RNA-seq, the expression of TMEM176B, EGR1, C1QB, and C1QC was further analyzed by RT-qPCR using GAPDH as the internal control. Compared to the controls, TMEM176B was significantly downregulated, whereas EGR1, C1QB, and C1QC were upregulated in the BC samples (P < 0.05, Fig. 5).

DNT cells account for only 3–5% of peripheral blood T-lymphocytes, and they play crucial roles in both innate and adaptive immune responses [20]. In addition, DNT cells are closely related to autoimmune diseases, inflammatory infections, and tumor progression [21]. Some studies reported an increased percentage of DNT cells in hematological and solid tumors. For instance, the proportion of TCR-αβ⁺ DNT cells is significantly higher in the peripheral blood of patients with acquired aplastic anemia than in healthy controls, and these patients are more responsive to immunosuppressive therapy [22]. In our study, we similarly found that the percentage of peripheral DNT cells was higher in patients with BC than in healthy subjects. There is considerable ambiguity regarding the function of DNT cells in different types of tumors. For example, although DNT cells have been revealed to exert immunosuppressive functions in mouse melanoma and glioma models, they have the ability to inhibit the growth of malignant cells in most tumors [23]. In vitro-expanded DNT cells induced cytotoxic effects in co-cultured triple-negative BC cells through the classic cell-killing mechanisms, including direct interaction via NKG2D and DNAM-1 and secretion of perforin and granzyme B. Therefore, we further explored the function and potential mechanism of DNT cells in BC by full-length transcriptome sequencing and bioinformatic analysis.

We identified 289 DEGs, including 137 upregulated and 152 downregulated genes, in DNT cells from patients with BC. Per the results of GO enrichment analysis, the DEGs are likely involved in immunoglobulin mediated humoral immune responses, the classical pathway of complement activation, and the B cell receptor signaling pathway. KEGG analysis also revealed significant enrichment of the B cell receptor signaling pathway and the complement and coagulation cascade cell signaling pathways among these DEGs. Taken together, these results suggest a close association between DNT cells and B cells. DNT cells are key coordinators of the immune response, and they might play a role in tumor immunity by regulating B cells.

The results of GO and KEGG enrichment analyses also demonstrated the involvement of DEGs in the classical complement activation pathway. In addition, the complement components C1QB and C1QC were identified as hub genes, and they were highly expressed in the BC group. The complement system is an important branch of innate immunity [24], and complement activation has been revealed to play a role in tumor progression [25]. C1Q promotes T cell activation and IFN-γ production and facilitates the subsequent immune response by activating the complement classical pathway [26, 27]. IFN-γ stimulates cellular immune responses and mediates the anti-tumor effects of DNT cells [21, 28]. Therefore, we hypothesized that C1Q activates DNT cells in the breast tumor microenvironment and triggers an anti-tumor immune response.

The PPI network comprised 2 modules and 10 hub genes, of which TMEM176A and TMEM176B displayed the most significant differences in expression between the BC and control groups. TMEM176B was significantly downregulated in patients with BC compared to the healthy controls. It encodes a cation channel protein of the MS4A transmembrane 4A family, and it is mainly expressed on lymphocytes and hematopoietic cells [29]. Segovia et al. found that TMEM176B controls the pH in phagosomes by modulating cation currents, which in turn affects antigen cross-presentation by dendritic cells [30]. Ion channels also play an important role in enhancing anti-tumor immunity as regulatory checkpoints and therapeutic targets [31]. Therefore, TMEM176B might influence the differentiation and immunomodulatory function of DNT cells, and the higher percentage of DNT cells in patients with BC relative to healthy controls could be related to difference in TMEM176B expression between the two groups. In addition, TMEM176B directly promotes the growth of triple-negative BC cells by activating the AKT/mTOR signaling pathway, and TMEM176B blockade using monoclonal antibodies significantly inhibited cancer cell proliferation. Taken together, DNT cells might exert an anti-tumor effect in BC by inhibiting TMEM176B.

EGR1, a transcriptional regulator containing a zinc-finger DNA-binding domain, is poorly expressed in resting T cells, and its expression rapidly increases upon the induction of TCR signaling [32]. The TCR signaling cascade regulates T cell proliferation, survival, and differentiation. EGR1 binds to the T-bet promoter homeostatic element and induces T-bet transcription, thereby activating and synergizing the TCR signaling pathway [33]. Furthermore, EGR1 can activate TNF-α and FasL transcription in response to TCR signaling [34, 35]. Several studies revealed that DNT cells exert anti-tumor effects by promoting the secretion of TNF-α, IFN-γ, and FasL [21]. In this study, EGR1 was highly expressed in the BC group compared to the healthy controls. This led us to hypothesize that EGR1 promotes the growth and differentiation of DNT cells via the TCR signaling pathway, which in turn elicits an anti-tumor immune response.

IFIT1, IFIT3, IFI27, IFI44L, and RSAD2 are interferon-stimulated genes (ISGs) that are highly expressed in a subset of patients with BC [36], and they belonged to module 1 in the PPI network. ISG-encoded proteins are induced by type I IFN signaling, and they regulate innate and adaptive immune responses involved in the development of multiple autoimmune diseases and tumors [37]. Type I promotes the survival of CD8⁺ T cells and enhances their anti-tumor capacity [38]. Thus, DNT cells might regulate the immune system by activating the IFN signaling pathway, thereby enhancing the anti-tumor immune response.

DNT cells are present in higher numbers in patients with BC, and they exhibit a distinct transcriptomic profile. TMEM176B and EGR1 were identified as likely factors regulating the differentiation and functions of DNT cells. Our findings provide new insights into the function of DNT cells and novel immunotherapeutic strategies against BC.

Funding

This study was supported by the Natural Science Foundation of Shandong Province of China (No. ZR2021MC137).

Author Contributions

Xiaofei Liu: Conceptualization, Methodology, Resources, Writing - Review & Editing, Funding acquisition. Huiru Zhu: Validation, Writing - Original Draft, Visualization. Jiaqi Guo: Formal analysis. Yunbo Wei: Conceptualization, Resources.

Data Availability

All data that support the findings are included in this manuscript.

Declaration of Competing Interest

The authors declare that they have no conflicts of interest.

Ethics approval

This study was approved by the Ethics Commission of the 960th Hospital of the PLA Joint Logistics Support Force, China (No. 2023107).

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You are reading this latest preprint version

Double-negative T cells with a distinct transcriptomic profile are abundant in the peripheral blood of patients with breast cancer

Status:

Version 1

Abstract

Background

Methods

Result

Conclusions

Figures

1. Introduction

2. Methods

2.1 Clinical samples and ethics statement

2.2 Flow cytometry

2.3 SMART-Seq2 sequencing and identification of DEGs

2.4 Functional annotation of DEGs

2.5 Protein–protein interaction (PPI) network of the DEGs

2.6 RT-qPCR

2.7 Statistical analysis

3. Results

3.1 The proportion of peripheral DNT cells is increased in BC patients

3.2 Identification and functional characterization of DEGs

3.3 Identification of core genes related to the DNT cells

3.4 Gene expression validation by RT-qPCR

4. Discussion

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1