Circulating CD3+CD8+ T Lymphocytes as Indicators of Disease Status in Patients With Early Breast Cancer

Breast cancer, a complex and heterogeneous disease, is grouped into four subtypes [Luminal A, Luminal B, Her-2–enriched, and triple-negative breast cancer (TNBC)] according to immunohistochemical markers, including estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 (Her-2/neu), and cell proliferative index Ki-67 [1]. Standard breast cancer treatments encompass surgery, chemotherapy, radiotherapy, endocrine therapy, targeted therapy, and immunotherapy; however, despite standard therapy, recurrence can follow. Importantly, recurrence is potentially driven by cancer–immune cell interaction.

The tumor microenvironment, a complex blend of cells and molecules, is pivotal in breast cancer progression and metastasis. Components of breast cancer include tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages, cancer-associated fibroblasts, endothelial cells, myeloid-derived suppressive cells (MDSCs), the extracellular matrix, secreted cytokines, and exosomes [2]. Cytokines, including tumor necrosis factor-α, interleukin (IL)-6, IL-10, IL-12, IL-17, transforming growth factor-β, chemokine (C–C motif) ligand 2 (CCL2; also known as monocyte chemoattractant protein 1), chemokine (C–X–C motif) ligand 1, and macrophage migration inhibitory factor, influence tumor development [3]. Additionally, immune metagene scores predict survival and recurrence, particularly regarding intrinsic subtypes and estrogen receptor status in highly proliferative tumors [4]. Breast cancer cells manipulate the immune system via cytokines and receptor expression, evading immune surveillance in a process termed immune escape. Immunosuppression regulates tumor-infiltrating immune cells, with the process involving suppressive factors, regulatory T cells, macrophage differentiation, and natural killer cell suppression. Direct cell–cell contact also inhibits tumor-specific cytotoxic T cells. Disseminated cancer cells, especially those in systemic circulation (circulating tumor cells (CTCs)) or bone marrow/lymph nodes, display potent immune escape, leading to metastasis and death [5].

Immune response dynamics drive breast cancer progression. Ductal carcinoma in situ lacks metastatic potential but hosts an active immune milieu, enriched in cytotoxic T cells and diverse T-cell receptors. In contrast, invasive carcinoma displays immune suppression, fewer cytotoxic cells, higher programmed death-ligand 1 (PD-L1) expression levels, and less diverse T-cell receptors [6]. High TIL levels correlate with improved disease-free survival and neoadjuvant chemotherapy response in TNBC but not Her-2–enriched breast cancer [7, 8]. Estrogen receptor–negative breast cancer with TIL presence responds to anthracycline-based chemotherapy. CD8⁺ cytotoxic T lymphocytes (CTLs), vital TIL components, synergize with chemotherapeutic agents [9]. Antitumor activity is associated with natural killer cells, CTLs, T helper cells, and T follicular helper cells in the tumor microenvironment [10]. Cancer-secreted chemokines recruit MDSCs, promoting postcytotoxic treatment survival in cancer cells [11, 12].

Early cancer recurrence biomarkers are crucial. Serum markers, such as carcinoembryonic antigen, cancer antigen 15–3, and cancer antigen 27–29 (also known as mucin 1), are common in breast cancer [13], but their diagnostic and prognostic utility is limited due to low sensitivity and specificity. New biomarkers, including CTCs, microRNAs, tumor antigens, and extracellular vesicles, aid monitoring and early detection of recurrence or metastasis [14]. Liquid biopsy offers diagnostic, predictive, and treatment-monitoring potential [15], albeit with limited clinical validity. Additionally, assay sensitivity, specificity, and cost must be considered, and establishing tools with heightened sensitivity, ease of use, and affordability is imperative. Because of the importance and convenience of liquid biopsy, other clinical biomarkers are required.

Circulating immune cells hold potential as biomarkers for detecting recurrence or metastasis in patients with cancer. Peripheral granulocytic myeloid cells mirror tumor-infiltrating immune subtypes in colorectal cancer [16]. Baseline CD4⁺/CD8⁺ ratio predicts prognosis in patients with advanced gastric and esophageal cancer receiving immune checkpoint inhibitor treatment [17]. Regarding non-small cell lung cancer, responders to immune checkpoint inhibitors exhibit elevated circulating CD4⁺ and CD8⁺ T-cell proportions [18]. Robust tumor-circulating immune cell abundance and interactions benefit patients with advanced gastrointestinal cancer considered responders, distinct from those considered progressors [19]. Diminished circulating CD3⁻CD56⁺ natural killer cell levels predict shorter overall survival and progression-free survival in patients with advanced non-small cell lung cancer [20]. Fewer circulating CD4⁺PD-L1⁺ and CD8⁺PD-L1⁺ T cells correlate with improved progression-free survival in patients with renal cell carcinoma receiving immune checkpoint inhibitors [21]. The mRNA levels of immune regulators in PBMCs predict disease status of breast cancer, including PD-L1, FOXP3, CD80, CD40, and CD14 [22]. Based on these previous findings, we hypothesize that circulating immune cells potentially indicate breast cancer status. In the present study, we aim to explore T lymphocyte and MDSC subtypes in this context.

In this study, our objective was to identify potential biomarkers for breast cancer by investigating circulating T lymphocytes, CTLs, and MDSCs across various stages of breast cancer and in an orthotopic breast cancer model. We found that circulating CD3⁺CD8⁺ CTL levels decreased in patients with breast cancer, increased after treatment, and decreased again upon recurrence. Thus, plasma levels of CD3⁺CD8⁺ CTLs hold promise as potential biomarkers reflecting disease status in breast cancer.

TILs are carried through the tributaries of the axillary vein, and circulating immune cells may mirror the composition of tumor-infiltrating immune cells in breast cancer [27]. The proportions of specific lymphocyte subtypes differ among patients with cancer. In non-small cell lung cancer patients, levels of T lymphocytes, natural killer cells, CD8⁺ T cells, and CD4⁺ T cells are diminished compared with those in healthy individuals [28]. Additionally, elevated circulating PMN-MDSC levels are associated with poorer recurrence-free survival of patients with hepatocellular carcinoma [29]. Colorectal cancer–diagnosed patients with higher CD16⁺ natural killer T-cell counts exhibit shorter disease-free survival [30]. In patients with hepatocellular carcinoma, an increased number of circulating CD8⁺ T cells enhances the effectiveness of immunotherapy [31]. Notably, in patients with breast cancer, CD117⁺ granulocytes correlate with cancer status, and CD45RO⁺ CD4⁺ memory T-cell counts rise after adjuvant radiotherapy [32]. Using flow cytometry, we analyzed circulating immune cells. Our findings indicate that the level of CD3⁺CD8⁺ CTLs is lower in preoperative patients with breast cancer than in healthy individuals and inversely correlates with tumor stage, positive lymphatic tumor emboli, and nodal stage N3. Following treatment, circulating CD3⁺CD8⁺ CTL levels increase, whereas patients exhibiting disease progression show decreased CD3⁺CD8⁺ CTL levels (Figure 7). We observed a similar trend in a mouse model of breast cancer. Levels of CD3⁺CD8⁺ CTLs and activated CTLs are higher in healthy mice (Day 0, before implantation of mouse breast cancer cells), decreased in tumor-carrying mice (Day 8, after tumor growth), then returned to higher level after resection of cancer (Day 28). Therefore, our study confirms circulating CD3⁺CD8⁺ CTLs as a valuable prognostic biomarker for breast cancer.

MDSCs play a pivotal role on immune suppression in breast cancer by generating reactive oxygen species, arginase, and cytokines that hinder the activity of other immune cells, including T cells, dendritic cells, and natural killer cells [33]. Their presence in peripheral blood or tumors is linked to cancer stage, grade, and patient survival. Furthermore, MDSCs are involved in regulating cancer dissemination [34]. Distinct surface markers distinguish between PMN-MDSCs and M-MDSCs [35]. M-MDSCs promote the acquisition of a mesenchymal phenotype and stemness characteristics, facilitating cancer dissemination from the primary site. Conversely, PMN-MDSCs promote metastatic growth by reverting the epithelial phenotype of already disseminated tumor cells [36]. We used CD11b⁺CD14⁻, CD33⁺CD15⁺, and CD33⁺CD14⁻ to identify human PMN-MDSCs and CD11b⁺CD14⁺, CD33⁺CD15⁻, and CD33⁺CD14⁺ for human M-MDSCs, and we observed strong correlations among these markers within each group. However, PMN-MDSCs and M-MDSCs exhibited contrasting expression patterns. Patients with breast cancer displayed elevated levels of CD33⁺CD15⁻ M-MDSCs compared with healthy controls. Additionally, CD33⁺CD14⁻ PMN-MDSC levels increased in patients with larger tumors, whereas CD11b⁺CD14⁺/CD33⁺CD14⁺ M-MDSC levels decreased in those with lymphatic tumor emboli. Posttreatment, CD11b⁺CD14⁻/CD33⁺CD14⁻ PMN-MDSC levels decreased, whereas CD11b⁺CD14⁺/ CD33⁺CD14⁺ M-MDSC levels increased. The opposing expression pattern of PMN-MDSCs and M-MDSCs suggests that low PMN-MDSC and high M-MDSC levels could potentially serve as biomarkers for a cancer-free status.

The intricate interplay between cancer and immune cells depends on secretory cytokines. CCL2, binding to its receptor C–C chemokine receptor type 2 (CCR2), acts as a chemokine, attracting monocytes during cancer progression. CCL2/CCR2 signaling also promotes early breast tumorigenesis and invasive properties [37]. Specifically, CCL2 triggers phosphorylation of MET receptor tyrosine kinases, inducing proliferation, migration, and glycolysis in breast cancer cells [38]. Blocking CCL2 activates CD8⁺ CTLs, leading to reduced tumorigenesis of lung cancer [39]. Secreted into the tumor microenvironment, CCL2 promotes angiogenesis, as well as the recruitment of tumor-associated macrophages and MDSCs in breast cancer [40], and plasma CCL2 levels are higher in patients with breast cancer compared with healthy individuals [41]. Elevated CCL2 expression in breast cancer cells is associated with early recurrence [42]. Propagermanium, a CCL2 inhibitor, has shown promising results, downregulating serum IL-6 levels in a phase I clinical trial, as well as demonstrating clinical safety and holding potential as an antimetastatic agent in breast cancer treatment [43]. Our study confirms elevated CCL2 levels exist in patients with breast cancer relative to healthy controls with large overlapping CCL2. Additionally, although CCL2 was not correlated with pathological factors or cancer subtypes, it exhibited decreased levels posttreatment, suggesting that it is a potential prognostic marker for breast cancer.

NLR has been used as a prognostic indicator in previous studies for solid tumor [44], and elevated NLR is associated with advanced breast cancer and poorer patient survival rates [45, 46]. However, NLR cutoff values have varied across studies of cancer, ranging from 2.96 to 5.7 [44-47]. In our study, patients with grade III breast cancer exhibited a lower NLR, whereas NLR was not correlated with other pathological factors. Despite its accessibility and cost-effectiveness, the inconsistent findings surrounding NLR have rendered its clinical application challenging.

A major limitation of the present study arises from the relatively small patient cohort. Considerable interindividual variation exists in certain types of circulating immune cells, including CD33⁺CD15⁺ and CD33⁺CD15⁻ cells. In an effort to assess changes in circulating immune cells, we employed a murine model. Interestingly, both human patients with breast cancer and the orthotopic breast cancer mouse model displayed a congruent dynamic pattern in circulating CD3⁺CD8⁺ CTL levels. Conversely, changes in MDSCs were inconsistent between the human breast cancer group and murine model. Markers for human and mouse MDSCs are dissimilar. Human M-MDSCs are described as HLA-DR⁻CD11b⁺CD14⁺CD15⁻CD33^High and PMN-MDSCs as HLA-DR⁻CD11b⁺CD14⁻CD15⁺CD33^Mild cells. Mouse M-MDSCs are represented as CD11b⁺Ly6C⁺Ly6G⁻ and PMN-MDSCs as CD11b⁺Ly6C⁻Ly6G⁺ cells [48]. In our study, we used CD11b⁺CD14⁺, CD33⁺CD15⁻, and CD33⁺CD14⁺ to identify human M-MDSCs, and CD11b⁺CD14⁻, CD33⁺CD15⁺, and CD33⁺CD14⁻ for human PMN-MDSCs. Dissimilar MDSC markers in two species might yield decreased correlations with disease status in breast cancer.

In conclusion, our study highlights the reduced levels of CD3⁺CD8⁺ CTLs in breast cancer–diagnosed patients, which subsequently increase following treatment. Additionally, we observed elevated CCL2 levels in these patients, which subsequently decreased posttreatment. We conclude that levels of circulating CD3⁺CD8⁺ CTLs represent candidates for prognostic biomarkers and treatment targets in breast cancer. To my best knowledge, this is the first report analyzed circulating immune cells in breast cancer including patients and orthotopic mouse model. Future research should focus on elucidating the complex interplay between immune subsets and their influence on breast cancer progression. Exploring MDSC dynamics, tumor microenvironment interactions, and larger patient cohorts are essential for advancing personalized therapeutic approaches in breast cancer management.

Han-Kun Chen: writing – original draft (equal). Yi-Ling Chen: conceptualization (equal), writing – review and editing (equal). Wei-Pang Chung: investigation (equal), writing – review and editing (equal). Zhu-Jun Loh: methodology (equal). Kuo-Ting Lee: methodology (equal). Hui-Ping Hsu: conceptualization (equal), data curation (equal), formal analysis (equal), investigation (equal), methodology (equal), validation (equal), writing – review and editing (equal).

The study was reviewed and monitored by Institutional Review Board of National Cheng Kung University Hospital (B-ER-108-400). All experimental protocols were approved by the IRB and all methods were performed in accordance with relevant guidelines and regulations for Good Clinical Practice.

The authors declare no conflicts of interest.