Dysregulated Th1 cells in lung squamous cell carcinoma

Abstract

Lung squamous cell carcinoma (LUSC) is a common subtype of lung cancer. Th1 cells contribute to antitumor immune responses. However, there are few studies on Th1 cells in LUSC. CD8⁺ T cells are the main driver of the antitumor immunity, targeting tumor cells killing. Th1 cells play an important auxiliary role in this process. Here, we used single-cell RNA-seq (scRNA-seq) to analyze qualified CD4⁺ T cells and Th1 cells (defined CD4⁺ T cells with 1 or more of STAT1⁺, STAT4⁺, T-bet⁺, and IFN-γ⁺ as Th1 cells) from tissues of 8 LUSC patients. Then, we validated Th1 cells and CD8⁺ T cells of 32 LUSC patients by multiplex immunofluorescence staining and immunohistochemistry. Finally, we used flow cytometry to detect IFN-γ of CD4⁺ T cells in human PBMCs coincubated with LUSC-derived supernatant to simulate a tumor inhibitory microenvironment. ScRNA-seq showed IFN-γ⁺ Th1 cells account for 25.28% of all Th1 cells. Gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses of differentially expressed genes between IFN-γ⁺ Th1 cells and IFN-γ^– Th1 cells confirmed the decreased IFN-γ is associated with endoplasmic reticulum stress (ER stress). Multiplex immunofluorescence staining and immunohistochemistry proved there was a positive correlation between IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells and CD8⁺ T cells. Flow cytometry showed IFN-γ secreted by Th1 cells is decreased. These findings support the claim that Th1 cells’ function is suppressed in LUSC. Through scRNA-seq, we found that the decreased Th1 cells’ function is associated with ER stress, which requires further study. Overall, these findings may produce a new method for the treatment of LUSC.

IFN-γ, lung squamous cell carcinoma, single-cell RNA-seq, Th1 cells

INTRODUCTION

Lung cancer ranks first in morbidity and mortality among all malignant tumors.¹ Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are both common subtypes of non-small cell lung cancer (NSCLC). Compared with LUAD, LUSC has a poor prognosis and lacks targets for effective targeted therapy.^2–3 Therefore, it is of great importance to find new treatments for patients with LUSC.

Th1 cells are the first subgroup discovered in CD4⁺ T cells. In a study of 125 frozen specimens of colorectal cancer analyzed for immune-related genes, researchers found that patients with high expression of Th1 cell-related genes had prolonged disease-free survival (DFS).⁴ Another study of 79 fresh human cervical cancer specimens showed that stage I patients had higher levels of circulating Th1 cells compared with stage II patients.⁵ However, there are few studies on Th1 cells in LUSC. The IL-2, TNF-α, and IFN-γ secreted by Th1 cells can activate Th1-type immune responses and mediate cellular immunity. Th1 cells play important role in the activation of CD8⁺ T cells and NK cells. In addition, IFN-γ itself also has an antitumor effect.^6–7 During the differentiation of Th1 cells, the STAT1 signal activated by IL-27 can enhance the expression of T-bet and IFN-γ.^8–9 T-bet is a master regulator of Th1 cell differentiation and IFN-γ production.¹⁰ IL-12 activates STAT4 signal and increases the expression level of IFN-γ.¹¹ IFN-γ can maintain the expression of T-bet and positively regulate the activation state of STAT1 and STAT4. Based on Th1 cell differentiation pathways, we defined Th1 cells using 3 important transcription factors during Th1 cells differentiation and the hallmark effector cytokine IFN-γ as indicators.

Nascent peptides are folded and modified in the endoplasmic reticulum (ER) to ensure precise conformation and function. However, many factors, including infection, hypoxia, oxidative damage, ER Ca²⁺ depletion, and nutrient deprivation can affect the normal function of ER, leading to the accumulation of misfolded and unfolded proteins in the lumen of ER, and which is known as ER stress.¹² Higher eukaryotic cells activate a collection of conserved pathways termed the unfolded protein response (UPR) to recover the homeostasis of ER.

In our study, we found that in LUSC, the level of IFN-γ secreted by Th1 cells decreases, and this suppressed function is related to ER stress by scRNA-seq, which may highlight a new therapeutic target.

MATERIALS AND METHODS

Tissue sample source

Tumor tissues, paracancerous tissues, normal tissues, lymphoid tissues, pretreatment blood samples, and preoperative blood samples of 8 patients used for single-cell RNA-seq (scRNA-seq) were obtained from Tianjin Medical University Cancer Institute and Hospital. The tissue samples used for multiplex immunofluorescence staining and immunohistochemistry were fixed in a formalin solution and embedded in paraffin to prepare 3 μm sections of 32 LUSC patients undergoing surgery without preoperative treatment at Tianjin Medical University Cancer Institute and Hospital between March 2018 and August 2020. Clinical features, including age, sex, smoking status, and T-category were recorded for each patient.

ScRNA-Seq

The Seurat package (version 3.2.1) was employed for quality control. Cells with 200–6000 feature genes and less than 10% of transcripts of mitochondrial genes were retained for further analysis. Expression data were normalized with the LogNormalize method. Gene variances were calculated via the “FindVariableFeatures” function, and the cells were clustered through the “FindNeighbors” and “FindClusters” functions. Markers were identified for each cluster using the “FindAllMarkers” function. In this study, we define Th1 cells as CD4⁺ T cells expressing 1 or more of the 4 genes, 3 important transcription factors T-bet, STAT1, and STAT4 in Th1 cells differentiation and the effector gene IFN-γ. Traditional Th1 cells are defined as IFN-γ positive CD4⁺ T cells. Our definition expands Th1 cells subsets using another more 3 transcription factors. Because these transcription factors play important roles in Th1 cells differentiation, we consider these transcription factors positive cells to have the ability to differentiate toward Th1 cells, in other words, these cells are potential Th1 cells. The biologic functions and pathways of differentially expressed genes (DEGs) were interpreted via the “clusterProfiler” package (version 3.14.3). Biologic processes (BPs) of gene ontology (GO) were functionally annotated for these DEGs. Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis was employed to understand signaling pathways enriched by these DEGs. Terms with FDR < 0.05 were considered significant enrichment.

Immunohistochemistry staining

The paraffin sections were dewaxed in an oven at 70°C for 1 h and then immersed in different concentrations of xylene and ethanol for deparaffinization and rehydration. The sections were then subjected to high-temperature antigen retrieval in a citrate restorative solution. After cooling, the samples were immersed in 3% hydrogen peroxide for 20 minutes to quench endogenous peroxidase activity. The blocking of nonspecific binding was performed with normal goat serum for blocking (ZSGB-BIO, Beijing, China; Cat. ZLI-9021) for 1 h at room temperature. The sections were then incubated with an anti-CD8α antibody (1:1000 dilution) (Abcam, Cambridge, MA, USA; Cat. ab237710) overnight at 4°C. The next day, the sections were rewarmed to room temperature, rinsed 3 times with PBS for 5 min, and then incubated with secondary antibody (Elivision™ plus Polyer HRP (Mouse/Rabbit) IHC Kit) (MXB Biotechnologies, FuJian, China; Cat. KIT-9903) at room temperature for 30 min. Thereafter, the DAB Chromogenic Kit (ZSGB-BIO; Cat. ZLI-9019) was used to illuminate the positive staining signals, and hematoxylin was used as counterstain. After dehydration, the sections were mounted in neutral resin and covered with coverslips.

Multiplex immunofluorescence staining

Multiplex immunofluorescence staining was performed using the Opal™ 7-Color Manual IHC Kit (PerkinElmer, Waltham, MA, USA; Cat. NEL811001KT). Similar to the immunohistochemistry staining, wax melting, dewaxing, and rehydration were carried out. Then, fixed with 10% neutral-buffered formalin for 10 min, and the following staining process was carried out 6 consecutive times. Antigen retrieval was performed with AR6 Buffer or EDTA antigen retrieval solution PH 9.0 (ZSGB-BIO; Cat. ZLI-9079) using microwave incubation. After that, the sections were blocked with Plus Amplification Diluent for 10 min at room temperature and then incubated with a primary antibody (anti-CD4 antibody (1:1000 dilution) (Abcam; Cat. ab133616), T-bet/TBX21 (D6N8B) XP Rabbit mAb (1:500 dilution) (Cell Signaling Technology, Danvers, MA, USA; Cat. 13232S), Human IFN-γ antibody (1:60 dilution) (R&D System, Minneapolis, MN, USA; Cat. MAB2853), anti-STAT4 antibody [EP1900Y] (1:100 dilution) (Abcam; Cat. ab68156), anti-PD1 antibody [EPR4877(2)] (1:150 dilution) (Abcam; Cat. ab137132), Stat1 (D1K9Y) Rabbit mAb (1:3000 dilution) (Cell Signaling Technology; Cat. 14994S)), a HRP-conjugated secondary antibody, and sequentially, an Opal fluorophore. Finally, the nuclei were stained with DAPI. The stained slides were visualized using Vectra spectral imaging system (PerkinElmer), and the obtained images were processed using InForm image analysis software (PerkinElmer)

Cell culture and treatment

The human LUSC cell lines H-1703 (Cat. 101663) and H226 (Cat. 100405) were purchased from BeNa Culture Collection in Henan, China. The cells were cultured in RPMI-1640 media (BasalMedia, ShangHai, China; Cat. L220KJ) with 10% Tecono FBS (Biocode Biotechnology, ZheJiang, China; Cat. F801-500), and incubated at 37°C with 5% CO₂. When the cell density reached 70%, the RPMI-1640 media containing 10% FBS was replaced by RPMI-1640 media containing 2% FBS. After 48 h, the supernatants were centrifuged at 4°C, 500 g/min for 10 min, and then were collected and stored at −80°C.

Human PBMCs were derived from lung cancer patients and stored in liquid nitrogen. PBMCs were resuscitated in X-VIVO™15 (Lonza Group Ltd, Basel, Switzerland; Cat. 04–418Q) with Human IL-2 (PeproTech, Rocky Hill, NJ, USA; Cat. AF-200-02-1MG), 300 IU/ml incubated at 37°C with 5% CO₂. Prepare 24-well plate with 1 μg/ml Anti-Human CD3 (Invitrogen Corporation, Carlsbad, CA, USA; Cat. 16-0037-85), 200 μl per well and left at 4°C overnight. The next day Anti-Human CD3 was aspirated from the 24-well plate, and 2×10⁶ PBMCs were placed in each well. The culture medium for each well was 0.5 ml of one kind of the above-mentioned tumor supernatants and 0.5 ml of X-VIVO™15. Then, 0.5 ml of RPMI-1640 media containing 2% FBS and X-VIVO™15 0.5 ml was used as control group. The PBMCs were incubated at 37°C with 5% CO₂ for 72 h and then used for flow cytometry.

Flow cytometry

The PBMCs coincubated with each tumor supernatant were treated with Protein Transport Inhibitor (BD Biosciences, San Jose, CA, USA; Cat. No.555029) and Leukocyte Activation Cocktail with BD GolgiPlug (BD Biosciences; Cat. 550583), respectively at 37 ℃ for 4 h to activate T cells and stimulate the accumulation of intracellular IFN-γ. Then PBMCs were stained with PerCP/Cyanine5.5 Anti-Human CD4 Antibody (BioLegend Inc., San Diego, CA, USA, Cat. 344608) and PE-Cy7 Mouse Anti-Human IFN-γ (BD Biosciences; Cat. 557643). Samples were acquired in the BD FACSCanto™ Flow Cytometry Systems with DIVA software. Flow data were analyzed using FlowJo Software.

Statistical analysis

All statistical analyses were performed using GraphPad Prism (GraphPad 7.0 Software, La Jolla, CA, USA). Differences between groups were determined by one-way ANOVA or nonparametric Spearman correlation. A p value below 0.05 was considered significant.

RESULTS

ScRNA-Seq-based identification of LUSC associated CD4⁺ T cell populations

To generate a map of CD4⁺ T cells of human LUSC, we performed scRNA-seq of qualified 44969 CD4⁺ T cells from the tissues of 8 LUSC patients. The basic clinical information of 8 patients are shown in Table 1 and their tissue samples include all or part of tumor tissues, paracancerous tissues, normal tissues, lymphoid tissues, pretreatment blood samples, and preoperative blood samples.

TABLE 1

Patient and clinical characteristics for sing-cell RNA-seq

	Number (%)
Total patients	8
Age (years)
Median	67.5
Range	51–73
Sex
Male	1 (12.5)
Female	7 (87.5)
Smoking status
Never	2 (25.0)
Current	6 (75.0)
T-category
T2	5 (62.5)
T3	2 (25.0)
T4	1 (12.5)
Lymph node status
N0	2 (25.0)
N2	5 (62.5)
N3	1 (12.5)
Treatment mode
Neoadjuvant	6 (75.0)
Surgery	1 (12.5)
Chemotherapy	1 (12.5)

To properly distinguish the traditional Th1 cells (IFNG, IL2, and TNF), we clustered CD4⁺ T cells and obtained 14 groups. The overall distribution of CD4⁺ T cells is shown in Figure 1(B). Heat maps depict the top 10 differential genes of the 14 clusters (Figure 1(C)). This demonstrates that in general Th1-like cells can be concentrated in a small group (No.7 cluster). Next, we describe the distribution of Th1 cells we defined in CD4⁺ T cells. It is clear that, unlike traditional Th1 cells, the 22971 Th1 cells we defined are widely distributed in CD4⁺ T cells (Figure 1(D)), accounting for about 51.08%.

FIGURE 1

Single-cell RNA-seq analysis of CD4+ T cells and Th1 cells in LUSC and a workflow. (A) A total of 8 patients' samples were collected for scRNA-seq, 1 patient underwent direct surgery, and the other 7 patients received 2 cycles of neoadjuvant therapy before surgery, 6 of them for paclitaxel liposomes, cisplatin, and pembrolizumab and 1 of them for paclitaxel liposomes and cisplatin and venous blood was taken before neoadjuvant therapy. Venous blood was collected from all patients before surgery, and tumor tissue, paracancerous tissue, normal lung tissue, and lymphoid tissue samples were collected during surgery. (B) Visualization of CD4⁺ T cells clusters marked by different colors by t-SNE method. (C) Heatmap of the scaled expression of the top 10 marker-genes for each cell cluster. (D) Distribution of Th1 cells in CD4⁺ T cells clusters

The function of most Th1 cells suppressed in LUSC

IFN-γ is the main effector of Th1 cells, and in the tumor microenvironment (TME), IFN-γ has an antitumor response; it can significantly induce the activation of CD8⁺ T lymphocytes and NK cells and reduce tumor angiogenesis. Through scRNA-seq, we identified 22971 Th1 cells. This included 5807 IFN-γ⁺ Th1 cells (Figure 2(A)), accounting for about 25.28% of the total Th1 cells, which amounted to only about one-third of IFN-γ^– Th1 cells (Figure 2(B)). It is evident that in LUSC the function of most Th1 cells is suppressed.

FIGURE 2

Quantity comparison of IFN-γ⁺ Th1 cells and IFN-γ^– Th1 cells and GO and KEGG enrichment analysis of DEGs. (A) Distribution of IFN-γ⁺ Th1 cells and IFN-γ^– Th1 cells in CD4⁺ T cells. (B) Histogram of IFN-γ⁺ Th1 cells and IFN-γ^– Th1 cells in CD4⁺ T cells. (C) Scatter plot of enriched KEGG pathways statistics. The color and size of the dots represent the range of the p-value and the number of DEGs mapped to the indicated pathways, respectively. p Value < 0.05 enriched pathways are shown in the figure. (D) GO analysis of DEGs related to ER, UPR, and protein folding process. The distributions are summarized in 3 main categories: BP, CC, and MF. The x-axis indicates different GO terms and the y-axis indicates the number of genes in each category

Th1 cells’ function suppression correlates with ER stress by ScRNA-seq

To understand the mechanism of Th1 cells’ function inhibition, we performed GO and KEGG pathway enrichment analyses of the DEGs between IFN-γ⁺ Th1 cells and IFN-γ^– Th1 cells. KEGG pathway enrichment analyses showed that the DEGs, in addition to being enriched in some autoimmune diseases and microbial infections (not shown in figure), were mainly concentrated in ribosomes, antigen presentation, cells differentiation, cell-to-cell interactions, apoptosis, protein processing in ER, and some signaling pathways (Figure 2(C)). GO analyses results showed that there are 13 BPs, 7 cellular components (CCs), and 3 molecular functions (MFs) related to ER, UPR, and protein folding process (Figure 2(D)).

The proportion of Th1 cells in human LUSC

To determine the proportion of Th1 cells in patients with LUSC, multiplex immunofluorescence staining was used to detect the expression of CD4, IFN-γ, STAT1, STAT4, and T-bet in serial sections from formalin-fixed, paraffin-embedded tumor specimens in 32 LUSC patients undergoing surgery without preoperative treatment at the Tianjin Medical University Cancer Institute and Hospital between March 2018 and August 2020 (Figure 3(A)). In addition, to some extent, PD-1 can reflect the exhausted state of T cells and may be used in subsequent experiments, so PD-1 was detected together. The clinical characteristics of these 32 patients are summarized in Table 2. (Two patients had quit smoking for 20 years and more than 30 years, respectively, and were defined along with never smokers as “never smoking”; the remaining patients were defined as “current smoking.”)

FIGURE 3

Multiplex immunofluorescence for selected markers in LUSC and correlation between clinical characteristics and different subpopulations of Th1 cells. (A) Representative images of biomarkers in LUSC tissue. CD4 staining is shown in green; STAT4 staining is shown in cyan; PD-1 staining is shown in yellow; T-bet staining is shown in red; IFN-γ staining is shown in pink; STAT1 staining is shown in violet and DAPI staining is shown in blue. (B) One-way ANOVA analysis showed the proportion of the proportion of IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells in Th1 cells, CD4⁺ T cells, and all cells were correlated with age (<60 years old compared with ≥60 years old; p = 0.012, 0.016, and 0.04). Meanwhile, IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells, CD4⁺ T cells, and all cells were correlated with smoking status (“never” compared with “current”; p = 0.047, 0.046, and 0.048)

TABLE 2

Patient and clinical characteristics for multiplex immunofluorescence staining and immunohistochemistry

Characteristic	Number (%)
Total patients	32
Age (years)
Median	64
Range	56–75
Sex
Male	3 (9.4)
Female	29 (90.6)
Smoking status
Never	6 (18.8)
Current	26 (81.2)
T-category
T1	16 (50)
T2	9 (28.1)
T3	6 (18.8)
T4	1 (3.1)

The results showed that the average proportion of CD4⁺ T cells in all the cells from the 32 patients was 54.50%. The average proportion of Th1 cells in CD4⁺ T cells was 69.93%. Because IFN-γ is the main cytokine secreted by Th1 cells for effector function, we next calculated the proportion of IFN-γ⁺ and double-positive, triple-positive, and tetra-positive cells which IFN-γ⁺ combined with transcription factor STAT1⁺, STAT4⁺, and T-bet⁺ in Th1 cells, CD4⁺ T cells, and all cells respectively. The results are summarized in Table S1.

Association between Th1 cells and clinical characteristics

To explore the relationship between Th1 cells and clinical characteristics of patients with LUSC, we performed correlation analysis between clinical characteristics and the proportion of different subpopulations of Th1 cells (IFN-γ⁺ or double-positive, triple-positive, and tetra-positive cells, which IFN-γ⁺ combined with STAT1⁺, STAT4⁺, and T-bet⁺) accounted for Th1 cells, CD4⁺ T cells, and all cells, respectively, of above mentioned 32 patients.

We found that the proportion of IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells, CD4⁺ T cells, and all cells were correlated with smoking status (“never” compared with “current”; p = 0.047, 0.046, and 0.048). Meanwhile, the proportion of IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells in Th1 cells, CD4⁺ T cells, and all cells were correlated with age (<60 years old compared with ≥60 years old; p = 0.012, 0.016, and 0.04) (Figure 3(B)).

Association between Th1 cells and CD8⁺ T lymphocytes

Th1 cells play a crucial role in activating CD8⁺ T lymphocytes to target and kill tumors. To determine whether the individual subpopulations of Th1 cells listed above contribute to the activation of CD8⁺ T cells, we performed immunohistochemical staining for the CD8 protein in the adjacent paraffin sections of multiplex immunofluorescence staining we did previously (Figure 4(A)). Paraffin sections of 2 patients without tumor cells were excluded.

FIGURE 4

Immunohistochemical staining for the CD8 protein in LUSC and correlation between different subpopulations of Th1 cells and CD8⁺ T cells. (A) Representative immunohistochemical staining for the CD8 protein in LUSC tumor tissue. Original magnification, 20× and 40×. (B) Nonparametric Spearman correlation showed the proportion of CD8⁺ T cells in the tumor stromal compartments was negatively correlated with the proportion of IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells (R = 0.0385; p = 0.036), and positively correlated with the proportion of IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells in Th1 cells (R = 0.0385; p = 0.036)

Next, we performed correlation analysis between the proportion of different subpopulations of Th1 cells and the proportion of CD8⁺ T cells in tumor tissues or tumor stromal compartments. The results showed the proportion of IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells was inversely correlated with the proportion of CD8⁺ T cells in tumor stromal compartments (R = 0.0385; p = 0.036). Furthermore, there was a positive correlation between the proportion of IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells in Th1 cells and the proportion of CD8⁺ T cells in tumor stromal compartments (R = 0.0385; p = 0.036) (Figure 4(B)).

LUSC-derived supernatant inhibits IFN-γ level in Th1 cells

To find out whether Th1 cells’ function is inhibited in the TME of LUSC, we used H1703 and H226 LUSC-derived supernatants, respectively, and X-VIVO™15 in a 1:1 ratio to culture human PBMCs. RPMI-1640 media containing 2% FBS and X-VIVO™15 were mixed in a ratio of 1:1 as the control group. After 72 h, the above PBMCs were treated with Protein Transport Inhibitor and Leukocyte Activation Cocktail with BD GolgiPlug, respectively, for 4 h to simulate the resting and activated states and then flow cytometry was used to detect the IFN-γ level in CD4⁺ T cells. The difference of IFN-γ secretion levels of each group between resting and activated PBMCs in the 3 groups (2 tumor supernatant groups and 1 control group) was regarded as the actual IFN-γ secretion level. The results showed that, compared with the control group, the IFN-γ level of Th1 cells in 2 LUSC cell supernatant groups decreased in varying degrees (Figure 5).

FIGURE 5

LUSC-derived supernatant inhibits IFN-γ level in Th1 cells. (A) PBMCs were coincubated with H1703 and H226 LUSC-derived supernatants for 72 h, RPMI-1640 media containing 2% FBS as the control group. Then treated with Protein Transport Inhibitor (as resting state, shown in the bottom row) and Leukocyte Activation Cocktail with BD GolgiPlug (as activated state, shown in the top row) for each tumor supernatant group and control group, respectively, at 37℃ for 4 h. IFN-γ secretion of CD4⁺ T cells were analyzed by flow cytometry. (B) The difference of IFN-γ secretion levels between resting and activated PBMCs was regarded as the actual IFN-γ secretion level. Histogram of actual IFN-γ secretion level for each tumor supernatant group and control group were shown

DISCUSSION

Cytotoxic T lymphocytes are effective weapons for our body to fight against tumors, and CD4⁺ T helper cells can enhance the antitumor response of CD8⁺ T cells.^13–15 CD4⁺ T cells can differentiate into distinct subpopulations in the face of different transcriptional signals. The differentiation of each kind of T helper cell is not a one-off, but rather the result of mutual inhibition, promotion, and transformation under the delicate regulation of various transcription factors and stimulatory signals. Therefore, compared with the traditional definition of Th1 cells, the distribution of Th1 cells under our definition is more extensive and heterogeneous in CD4⁺ T cells (Figure 1).

In our scRNA-seq results, there are only a small number of IFN-γ⁺ cells in Th1 cells, indicating that most Th1 cells in LUSC do not express IFN-γ; in other words, their function is inhibited. Similar to our findings, another study exploring the proportion of T cell subsets in patients with salivary gland tumors analyzed the proportion of Th1 cells (CD4⁺ and IFN-γ⁺) in the peripheral blood of 30 patients and 15 healthy controls by flow cytometry, and found that the average percentage of Th1 cells in tumor patients was significantly lower than healthy controls.¹⁶ Another study cultured spleen cells with head and neck squamous cell carcinoma supernatants and precancerous supernatants, respectively, and found that spleen cells cultured with cancer supernatants had reduced levels of Th1-related cytokines (IL-2 and IFN-γ).¹⁷ In conclusion, the immune stimulation of Th1 cells in tumors decreased significantly (Figure 2).

To obtain more comprehensive information, we performed scRNA-seq with all available specimens, and the obtained number of Th1 cells accounted for approximately 51.08% of CD4⁺ T cells. Next, we used multiplex immunofluorescence staining to identify CD4⁺ T cells and Th1 cells in the tumor tissues. The obtained number of Th1 cells accounted for about 69.93% of CD4⁺ T cells, which was almost 20% higher than the result of scRNA-seq. We thought it likely that this was caused by different specimens, so we separately calculated the number of CD4⁺ T cells and Th1 cells at the tumor tissues in scRNA-seq, and the obtained ratio was about 60.70%. It is evident that the proportion of Th1 cells in CD4⁺ T cells at the tumor tissues is higher than the proportion calculated with all samples. A study showed that in NSCLC, 37 types and subtypes of immune cells were increased compared to normal lung tissue, including CD4⁺ T cells.¹⁸ In our study, Th1 cells are widely distributed in CD4⁺ T cells. In a sense, it is not contradictory to our results that Th1 cells have a higher proportion in tumor tissues. Although this proportion is still lower than the proportion of multiplex immunofluorescence staining, one possible reason for this may be that there were only 8 patients with scRNA-seq and 7 of them were treated before operation.

In our study, we found that the proportion of IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells in Th1 cells, CD4⁺ T cells, and all cells were correlated with age. The proportion of these groups of cells are reduced in elderly patients. We all know that aging has a wide range of effects on CD4⁺ T cells. Thymus degenerates in the elderly and both T cells numbers and TCR repertories are reduced compared with younger people.^19–20 This also coincides with our statistical results. Perhaps this is part of the reason for the poor immunotherapy results in some elderly patients. We also found that the proportion of IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells, CD4⁺ T cells, and all cells were correlated with smoking status. The proportion of cells in these groups are increased in nonsmoking patients. It has been shown that smoking suppresses the host's innate immune response, leading to a decrease in Th1 cells.²¹ In addition, in a study of oropharyngeal squamous cell carcinoma, the authors found that smoking reduced Th1 responses and increased Th2 responses, which is not contrary to our results.²² Combined with our statistical results, maybe younger nonsmoking patients have stronger Th1 responses in clinical treatment, but this requires further study.

There is no doubt that CD8⁺ T cells play an active role in fighting malignancies. Ruffini et al.²³ pointed out that CD8⁺ T cells were related to prolonged survival in LUSC. A large study of 797 NSCLC patients proved stromal CD8⁺ TILs density was an independent prognostic factor of DFS, disease-specific survival, and overall survival.²⁴ The antitumor effect of CD8⁺ T cells needs to be initiated and maintained by CD4⁺ T cells, and Th1 cells play an important role in this process. Given this, we wondered whether different subsets of Th1 cells correlated with CD8⁺ T cells. After statistic analysis, we found that the proportion of CD8⁺ T cells in the tumor stromal compartments was negatively correlated with the proportion of IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells and positively correlated with the proportion of IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells in Th1 cells. Th1 cells promote the activation of CD8⁺ cytotoxic T lymphocytes, and this has been confirmed in many studies. For example, Snell et al.²⁵ demonstrated that therapeutically reconstituting Th1 cells enhance the numbers and function of antiviral CD8⁺ T cells in persistent virus infection and achieve infection control. But why do our results showed the proportion of IFN-γ⁺ T-bet⁺ Th1 cells in Th1 cells was inversely correlated with the proportion of CD8+ T cells in tumor stromal compartment? The main difference between these 2 subgroups of Th1 cells lies in the expression of STAT1, so we speculate that this diametrically opposed result for CD8⁺ T cells may be due to the difference of STAT1 expression. A study confirms that in a mouse model of head and neck squamous cell carcinoma, STAT1-deficient mice have impaired CD8⁺ T cell expansion and severely attenuated antitumor effects.²⁶ Gil et al.²⁷ also confirmed that STAT1 regulates the proliferation of CD8⁺ T cells as a key mediator of IFN-α. More importantly, by performing KEGG pathway enrichment of the differential genes of the 2 groups of cells by scRNA-seq, we found that the differential genes of the 2 groups of cells were significantly associated with antigen processing and presentation, perhaps indicating that IFN-γ⁺ STAT1⁺ T-bet⁺ Th1 cells could more actively regulate APCs to provide stronger antigenic signals to naive CD8⁺ T cells to stimulate their activation. Therefore, we have reason to believe that Th1 cells with STAT1 expression may play a positive role in the proliferation of CD8⁺ T cells.

We used the supernatant of LUSC cells to simulate a tumor inhibitory microenvironment to culture PBMCs. Interestingly, the supernatants of 2 kinds of tumor cells can effectively inhibit the secretion of IFN-γ by Th1 cells. Rayman et al.²⁸ cultured T cells from healthy volunteers and patients with renal cell carcinoma, in the presence and absence of supernatant derived from renal cell carcinoma explants, and then assessed type 1 or type 2 responses in terms of cytokine production and gene expression. The results showed that the tumor supernatant could effectively inhibit the Th1-type responses and reduce the level of IFN-γ.²⁸ An animal study of a B16 melanoma model also demonstrated a gradual shift in CD4⁺ T cell responses from a Th1:Th2 mixed type to a Th2 type response during tumor progression.²⁹ It is clear that IFN-γ secretion by Th1 cells is inhibited in various tumors. Similarly, in our work, there was inhibition of IFN-γ secretion by Th1 cells in LUSC.

Theoretically, there are many factors affecting the secretion of IFN-γ by Th1 cells in the complex process of cell differentiation and activation. Perhaps ER stress is not the most important factor affecting the function of Th1 cells, but both GO and KEGG analyses confirmed that it was related to the function of Th1 cells. Furthermore, the process of ER protein synthesis is closely related to the life activities of cells. Next, we will further investigate whether ER stress is related to the inhibition of Th1 cells’ function and whether regulation of ER stress-related pathways can partially restore the IFN-γ secretion of Th1 cells.

In conclusion, this study confirms that the majority of Th1 cells’ functions in LUSC are in a suppressed state. Through scRNA-seq, we found that this inhibitory effect is related to ER stress. Going forward, we will investigate the relationship between ER stress and IFN-γ levels in Th1 cells. Our study may shed new light on the treatment of LUSC.

ACKNOWLEDGMENTS

We express gratitude to Yangyang Niu (Postgraduate Student of Pathology Department, Harbin Medical University Cancer Hospital, Harbin, China) for helping us evaluating the Immunohistochemistry staining of slice. We also thank Liuqing Zheng, Shanshan Xiao, and Tao Wang (Department of R&D, Hangzhou Repugene Technology Co., Ltd., Hangzhou, China) for helping us carry out scRNA-seq. This work was supported by grants from the National Natural Science Foundation of China (No. U20A20375, 81872166, 81972772).

AUTHORSHIP

X. R. and C. Y. conceived and designed the experiments. J. W. performed the experiments and wrote the paper. J. Z. and Q. Z. participated in the data analysis. Y. Q. and P. Z. contributed part of reagents and materials. All authors read and approved the final manuscript.

DISCLOSURES

The authors declare no conflicts of interest.

Abbreviations

 
• BP

  biologic process

 
• CC

  cellular component

 
• DFS

  disease-free survival

 
• ER

  endoplasmic reticulum

 
• ER stress

  endoplasmic reticulum stress

 
• GO

  gene ontology

 
• KEGG

  Kyoto encyclopedia of genes and genomes

 
• LUAD

  lung adenocarcinoma

 
• LUSC

  lung squamous cell carcinoma

 
• MF

  molecular function

 
• NSCLC

  non-small cell lung cancer

 
• scRNA-seq

  single-cell RNA-seq

 
• TME

  tumor microenvironment

 
• UPR

  unfolded protein response

Author notes

Jiahui Wang is the first author.