Literature DB >> 34488711

Circulating activated immune cells as a potential blood biomarkers of non-small cell lung cancer occurrence and progression.

Yingyi Wang1, Na Zhou1, Rui Zhu2, Xiaoyuan Li1, Zhao Sun1, Yang Gao1, Wei Liu3, Changting Meng4, Yuping Ge1, Chunmei Bai1, Taisheng Li5, Hongsheng Liu6.   

Abstract

BACKGROUND: Treatment for non-small cell lung cancer (NSCLC) has greatly improved in recent years. However, noninvasive early screening for carcinogenesis and progression unclear. The aim of this study was to explore the predictive value of peripheral blood immune cells in untreated NSCLC patients.
METHODS: We retrospectively enrolled 305 untreated NSCLC patients and 132 healthy participants from February 2016 to August 2019 in Peking Union Medical College Hospital. Immune cell levels were determined by flow cytometry and routine blood tests.
RESULTS: NSCLC patients had lower levels of T lymphocytes, NK cells, CD8+ T cells, naïve CD4+/CD4+, naïve CD4+ T cells and higher levels of CD4+ T cells, memory CD4+/CD4+ T cells, memory CD4+ T cells, CD4+CD28+/CD4+ T cells, CD4+CD28+ T cells, CD8+CD28+/CD8+ T cells, CD8+HLA-DR+/CD8+ T cells, CD8+HLA-DR+ T cells T cells, CD8+CD38+/CD8+ T cells, CD8+CD38+ T cells and CD4+/CD8+ T cells than those in controls. The percentages of specific lymphocyte subtypes were significantly different in cancer patients versus healthy individuals. For instance, cancer patients had lower levels of B cells, CD4+ T cells, naïve CD4+/CD4+ T cells, naïve CD4+ T cells, CD4+CD28+ T cells, CD8+CD28+ T cells and higher levels of NK cells, white blood cells (WBC), monocytes, neutrophils, eosinophils, basophils, monocytes to lymphocyte ratio (MLR), neutrophils to lymphocyte ratio (NLR), eosinophil to lymphocyte ratio (ELR), basophil to lymphocyte ratio (BLR), and blood platelet to lymphocyte ratio (PLR).
CONCLUSIONS: Abnormal T cell levels can be used as an independent predictive biomarker for noninvasive early screening in NSCLC occurrence and progression.
© 2021. The Author(s).

Entities:  

Keywords:  Advance cancer stage; Cancer occurrence; Clinicopathologic characteristics; Immune cells; NSCLC

Mesh:

Substances:

Year:  2021        PMID: 34488711      PMCID: PMC8420051          DOI: 10.1186/s12890-021-01636-x

Source DB:  PubMed          Journal:  BMC Pulm Med        ISSN: 1471-2466            Impact factor:   3.317


Background

Lung cancer is the leading cause of cancer-related disease incidence and mortality worldwide (11.6% and 18.4% of the total cases, respectively) [1, 2]. NSCLC accounts for approximately 80–85% of lung cancers with a 5-year survival rate of less than 15% for advanced cancer [3, 4]. The 5-year survival ranges from 50 to 80% for early stage NSCLC treated with surgical resection. However, the diagnosis of early-stage NSCLC occurs in less than 20% of cases [5]. Improving the accuracy of prediction could contribute to enabling a better treatment strategy [6]. Thus, it is important to identify markers to predict the advanced cancer stage of patients with lung cancer upon noninvasive method. In recent years, the role of the immune system has been an increasingly recognized in cancer development and progression. Immune cells play critical roles in the anti-tumor response basing on promoting or suppressing tumor progression and subsequent invasion and metastasis [7]. To identify new predictive markers, tumor infiltrating T-lymphocytes have become a hot topic of research and several researches have demonstrated their predictive role in cancer [8]. However, the detection of TILs is complex and cannot be dynamically monitored. In this context, there has been a great focus on peripheral blood, which is the main source of immune cells, which has several advantages including simpler handling, noninvasive, and the possibility of dynamic monitoring. Several studies have reported the levels and roles of peripheral blood lymphocyte subsets in NSCLC, such as B cells, CD4+ T cells, and CD4/CD8+ T cell ratio [9, 10]. The relationships between lymphocyte subsets and gender, age and stage were also reported [11]. However, the predictive values of immune cells in untreated lung cancer patients have not been well studied. In this study, we analyzed peripheral blood immune cells to provide basic data for further exploration of tumor predictive indicators.

Methods

Patients and clinical data

A total of 437 participants were recruited atPeking Union Medical College Hospital (PUMCH) between February 2016 and August 2019 and had not received anti-tumor therapies before enrollment. 305 untreated NSCLC patients (141 male and 164 female) were selected with ages between 25 and 84 years (mean age: 59.67 years). 135 patients had no active disease with surgery before diagnosed lung cancer and 43 patients had received two surgeries. 211 patients had conformed history of diseases before being diagnosed with lung lung cancer including 142 patients who suffered from two diseases. 84 patients had smoking history with 1 to 63 years including 51 patients with a smoking cessation from 0.1 to 30 years. 67 patients had a drinking history including abstinence for 10 patients. 132 age- and sex-matched healthy volunteers (96 men and 53 women) were selected with age from 25 to 80 years (mean age: 59.19 years). Age was divided into three groups upon World Health Organization (Yong: 0–44 years; Middle people: 45–59 years; Elderly people: over 59 year). The clinical data of untreated patients are summarized in Table 1. All participants gave informed consent. This study was approved by the Ethical Committee of PUMCH (JS-1405).
Table 1

Clinicophthological characterstics of the untreated lung cancer patients in this study

CharactersticsN = 305
Gender
 Male141
 Female164
Age
 Yong25
 Middle116
 Elder164
Allergic history
 Antibiotic31
 Other6
 No allergic239
Unkown29
Surgery
 Uterine27
 Caesarean section11
 Epityphlon24
 Thyroid17
 Intestines13
 Other86
 No surgery146
 Unkown24
History of diseases
 Hypertension110
 Diabetes40
 Coronary heart disease21
 Thyroid nodule19
 Fatty liver11
 Other152
 No Medical75
 Unkown19
Smoking history
 Yes33
 Cessation51
 No193
 Unkown19
Drinking history
 Yes57
 Abstinence10
 No219
 Unkown19
ECOG PS
 0247
 135
 29
 32
 Unkown12
Histology
 Adenocarcinoma277
 Squamous carcinoma27
 Adenosquamous carcinoma1
Stage
 I203
 II18
 III27
 IV46
 Unkown11
Tumour stage
 T1207
 T242
 T316
 T422
 Unkown18
Lymph nodes metastases
 N0215
 N112
 N233
 N324
 Unkown21
Distant metastases
 M0243
 M146
 Unkown16
Clinicophthological characterstics of the untreated lung cancer patients in this study

Flow cytometry and blood routine tests

Lymphocyte immunophenotyping was conducted by three-color flow cytometry (Epics XL flow cytometry; Beckman Coulter, USA). Specific monoclonal antibodies against CD19, CD16CD56, CD4, CD8, CD45RO, CD45RA, CD28, HLA-DR, and CD38 were used to identify lymphocyte subsets. A dual-platform method was performed to calculate lymphocyte subsets upon WBC counts. Inflammatory cells including lymphocytes, monocytes, neutrophils, eosinophils, basophils, red blood cells (RBC), hemoglobin, platelet were acquired from routine blood tests of the same sample. In addition, the levels of MLR, NLR, ELR, BLR, red blood cells to lymphocyte ratio (RLR), hemoglobin to lymphocyte ratio (HLR), and PLR were evaluated.

Statistical analysis

Statistical analysis was performed using SPSS 22.0 software (IBM Corporation, USA) and GraphPad Prism 7.0 software (San Diego, USA). The data were expressed using means ± standard deviation. Kolmogorov–Smirnov test was performed for the distribution test. Normally distributed were analyzed by t-test and one-way analysis. Non-parametric data were compared by Mann–Whitney test and Kruskal–Wallis. Spearman’s rank correlation test was used for correlation analysis. Probability value was performed 2-sided tests and p < 0.05 was considered statistically significant.

Results

Comparison of immune parameters in NSCLC versus healthy individuals

To explore the predictive role of immune cells in untreated NSCLC patients, a total of 487 Chinese adults (305 lung cancer patients and 132 healthy controls) were enrolled in this study. We did not analyze inflammatory cells due to a lack of these data for controls.The levels of lymphocyte subsets were significantly associated with gender and age in healthy controls and cancer patients, thus we carefully avoided age- and sex-related biases. We compared the levels of immune cells in all patients and controls based on t-test and Mann–Whitney test. In this study, low levels of T lymphocytes (p < 0.001), NK cells (p < 0.001), CD8+ T cells (p = 0.008), naïve CD4+/CD4+ (p < 0.001), and naïve CD4+ T cells (p < 0.001) was observed in lung cancer patients compared to controls. However, levels of CD4+ T cells (p = 0.042), memory CD4+/CD4+ (p < 0.001), memory CD4+ T cells (p < 0.001), CD4+CD28+/CD4+(p < 0.001), CD4+CD28+ T cells (p = 0.002), CD8+CD28+/CD8+ (p = 0.004), CD8+HLA-DR+/CD8+ (p < 0.001), CD8+HLA-DR+ T cells (p = 0.022), CD8+CD38+/CD8+ (p < 0.001), CD8+CD38+ T cells (p = 0.001) and CD4+/CD8+(p < 0.001) were higher in patients than those in controls. There was no significant difference for B cells and CD8+CD28+ T cell counts between patients and controls (p > 0.05). The result was shown in Table 2.
Table 2

Differences of immune parameters in untreated lung cancer patients and healthy controls

Lymphocyte subsetsHealthy controls (N = 132)Lung cancer patients (N = 357)P value
T Lymphocyte (cells/10^12ul)1.97 ± 0.531.73 ± 0.61 < 0.001
B cells (cells/ul)201.69 ± 91.56184.85 ± 98.290.054
NK cells (cells/ul)390.99 ± 251.48269.15 ± 213.78 < 0.001
CD4+ T cells (cells/ul)689.83 ± 255.28745 ± 302.80.042
CD8+ T cells (cells/ul)511.43 ± 255.09439.25 ± 212.90.008
Memory CD4+/CD4+ (%)65.89 ± 13.873.55 ± 12.88 < 0.001
Memory CD4+ T cells (cells/ul)441.8 ± 166.31539.09 ± 220.41 < 0.001
Naïve CD4+/CD4+ (%)34.11 ± 13.824.21 ± 12.2 < 0.001
Naïve CD4+ T cells (cells/ul)248.05 ± 160.27183.7 ± 128.13 < 0.001
CD4+CD28+/CD4+ (%)87.12 ± 10.9792.42 ± 8.95 < 0.001
CD4+CD28+ T cells (cells/ul)600.64 ± 239.99674.78 ± 271.480.002
CD8+CD28+/CD8+ (%)50.95 ± 15.5455.84 ± 17.260.004
CD8+CD28+ T cells (cells/ul)249.24 ± 119.32230.43 ± 106.650.156
CD8+HLA-DR+/CD8+ (%)28.4 ± 10.738.37 ± 14.13 < 0.001
CD8+HLA-DR+ T cells (cells/ul)148.75 ± 102.86175.18 ± 129.290.022
CD8+CD38+/CD8+ (%)22.34 ± 14.7131.04 ± 13.35 < 0.001
CD8+CD38+ T cells (cells/ul)114.11 ± 96.19136.43 ± 95.690.001
CD4+/CD8+ (%)1.62 ± 0.911.97 ± 1.00 < 0.001

Bold represents p <0.05, the difference was statistically significant

Differences of immune parameters in untreated lung cancer patients and healthy controls Bold represents p <0.05, the difference was statistically significant

Evaluation of relationships between lymphocyte subsets/myeloid cells and lung cancer stage

To further analyze the role of immune cells in NSCLC progression, the 305 NSCLC patients were divided into 4 group by the stages. In this study, a trend of decrease in B cell counts (r = −0.193, p = 0.001, Fig. 1a), CD4+ T cell counts (r = −0.135, p = 0.020, Fig. 1c), naïve CD4+/CD4+ percentage (r = −0.122, p = 0.037, Fig. 1d), naïve CD4+ T cell counts (r = −0.144, p = 0.013, Fig. 1e), CD4+ CD28+ T cell counts (r = −0.137, p = 0.019, Fig. 1f), and CD8+CD28+ T cell counts (r = −0.186, p = 0.001, Fig. 1g) was noted for patients in advanced stages. In contrast,there were increasingly advanced stage related trend for NK cell counts (r = 0.117, p = 0.045, Fig. 1b), WBC counts (r = 0.177, p = 0.002, Fig. 1h), monocytes (r = 0.186, p = 0.001, Fig. 1i), neutrophils (r = 0.158 p = 0.007, Fig. 1j), eosinophils (r = 0.171, p = 0.003, Fig. 1k), basophils (r = 0.203, p < 0.001, Fig. 1l), MLR (r = 0.206, p < 0.001, Fig. 1m), NLR (r = 0.165, p = 0.005, Fig. 1n), ELR (r = 0.188, p = 0.001, Fig. 1o), BLR (r = 0.230, p < 0.001, Fig. 1p), PLR (r = 0.121, p = 0.038, Fig. 1q).There were no significant correlation between other immune cell levels and advanced stages (Additional file 1: Table S1). Notably, stage II patients had highest levels of T lymphocytes, NK cells, CD4+ T cells, CD8+ T cells, memory CD4+ T cells, CD4+CD28+ T cells, CD8+CD28+ T cells, CD8+HLA-DR+ T cells, lymphocytes and lowest counts of WBC, neutrophils than those patients in other stages.
Fig. 1

Predictive values of immune cell levels in progress of lung cancer. Distribution of B cell counts (a), NK cell counts (b), CD4+ T cell counts (c), naïve CD4+/CD4+ percentage, (d) naïve CD4+ T counts (e), CD4+CD28+ T counts (f), CD8+CD28+ T counts (g), WBC counts (h), monocytes counts (i), neutrophils counts (j), eosinophils counts (k), basophils counts (l), MLR (m), NLR (n), ELR (o), BLR (p), PLR (q)

Predictive values of immune cell levels in progress of lung cancer. Distribution of B cell counts (a), NK cell counts (b), CD4+ T cell counts (c), naïve CD4+/CD4+ percentage, (d) naïve CD4+ T counts (e), CD4+CD28+ T counts (f), CD8+CD28+ T counts (g), WBC counts (h), monocytes counts (i), neutrophils counts (j), eosinophils counts (k), basophils counts (l), MLR (m), NLR (n), ELR (o), BLR (p), PLR (q)

Assessment of relationships between lymphocyte subsets/myeloid cells and clinical parameters immune cell levels

To further demonstrate the relationship between immune cell levels and clinicopathologic characteristics we performed t text, Mann–Whitney test for 2 group, and Spearman’s rank correlation test for more than 2 groups, and the results weresummarized in Tables 3 and 4 and Fig. 2. There were high B cell counts (p < 0.001) and CD8+CD28+/CD8+ percentage (p = 0.047) in female patients than those in male. On the contrary, we discovered low counts of WBC (p = 0.005), monocytes (p < 0.001), neutrophils (p = 0.001), eosinophils (p = 0.006), RBC (p < 0.001), hemoglobins (p < 0.001), and MLR (p < 0.001), NLR (p = 0.001), ELR (p = 0.002), HLR (p = 0.007) in the female patients compared to those in the male patients. cell countsLow CD8+CD28+/CD8+ percentage (p = 0.008), CD4+/CD8+ ratio (p = 0.039), and high percentage of CD8+HLA-DR+ T cells (p = 0.019), CD8+CD38+/CD8+ (p = 0.016), CD8+CD38+ T cells (p = 0.013), RBC (p = 0.001), and hemoglobins (p < 0.001) were discovered in patients with surgery than patients without surgery. There were significant differences for memory CD4+/CD4+ percentage (p = 0.034), naïve CD4+/CD4+ percentage (p = 0.034), CD8+CD28+ T cells (p = 0.031), and monocytes (p = 0.002) in various histologies.
Table 3

Relationship between lymphocytes levels and clinicopathologic characteristics

T lymphocytes (cells/ul)B cells (cells/ul)NK cells (cells/ul)CD4+ T cells (cells/ul)CD8+ T cells (cells/ul)Memory CD4+/CD4+ (%)Memory CD4+ T cells (cells/ul)Naïve CD4+/ CD4+ (%)Naïve CD4+ T cells (cells/ul)CD4+CD28+/CD4+ (%)CD4+CD28+ T cells (cells/ul)CD8+CD28+/CD8+ (%)CD8+CD28+ T cells (cells/ul)CD8+HLA-DR/ CD8+ (%)CD8+HLA-DR T cells (cells/ul)CD8+CD38+/CD8+ (%)CD8+CD38+ T cells (cells/ul)CD4+/CD8+
Gender
 Male1220.79 ± 428.8162.41 ± 92.49294.41 ± 257.20733.74 ± 329.37443.59 ± 215.8874.40 ± 13.31532.37 ± 227.2422.94 ± 11.97169.68 ± 122.1091.99 ± 9.66649.61 ± 268.0053.9 ± 17.42224.69 ± 105.8139.77 ± 14.11184.25 ± 135.2230.16 ± 13.31135.34 ± 102.451.95 ± 1.14
 Female1277.29 ± 474.83204.14 ± 99.30247.43 ± 165.50754.67 ± 278.59435.51 ± 210.9072.81 ± 12.50544.86 ± 214.8925.30 ± 12.32195.75 ± 132.2892.80 ± 8.30696.41 ± 273.3957.51 ± 16.99235.36 ± 107.4337.16 ± 14.07167.39 ± 123.8531.79 ± 13.37137.36 ± 89.771.99 ± 0.88
 P0.431 < 0.0010.3180.2870.6570.2260.2260.5600.1220.0670.3600.1200.0470.4010.0840.1290.2030.141
Age
 Yong1220.60 ± 432.39184.20 ± 96.01239.06 ± 178.45665.40 ± 311.44464.27 ± 211.4970.42 ± 12.80450.16 ± 161.8228.35 ± 12.75207.01 ± 186.3795.36 ± 4.36611.66 ± 327.8865.3 ± 13.68288.07 ± 118.4629.66 ± 11.17143.33 ± 95.1338.78 ± 13.86174.12 ± 92.711.71 ± 0.92
 Middle1274.92 ± 452.69193.84 ± 103.67261.69 ± 203.82745.08 ± 269.35449.80 ± 219.6673.16 ± 12.48542.60 ± 217.9825.27 ± 12.33190.65 ± 122.1592.76 ± 8.42689.79 ± 256.3557.03 ± 17.84238.78 ± 102.1137.58 ± 13.74178.92 ± 133.6532.53 ± 13.13143.6 ± 86.671.90 ± 0.85
 Elder1239.03 ± 460.52178.59 ± 94.77279.02 ± 225.75757.07 ± 323.13427.96 ± 208.8274.29 ± 13.17550.16 ± 227.7722.84 ± 11.88175.23 ± 121.6091.73 ± 9.73673.78 ± 272.9253.56 ± 16.83215.74 ± 104.9440.25 ± 14.32177.39 ± 130.6528.80 ± 12.90125.61 ± 100.692.06 ± 1.11
 P0.6880.5500.4460.1520.4250.2750.0770.0550.3380.1210.1690.0060.0030.0020.521 < 0.0010.0010.123
Allergic history
 Antibiotic1247.95 ± 325.87179.33 ± 111.83213.09 ± 121.54714.35 ± 243.96447.59 ± 190.5975.65 ± 11.83533.42 ± 183.0621.00 ± 11.73159.85 ± 119.0991.83 ± 10.97640.66 ± 273.1560.33 ± 17.27250.68 ± 90.5735.95 ± 15.01169.99 ± 135.433.17 ± 16.32146.63 ± 107.451.89 ± 1.07
 Other1397.30 ± 255.23286.59 ± 60.68245.97 ± 195.28834.23 ± 210.96475.6 ± 76.9669.81 ± 9.10590.88 ± 217.9228.21 ± 10.03226.12 ± 79.8594.97 ± 2.95795.26 ± 213.4666.68 ± 9.31320.55 ± 85.9326.80 ± 5.40126.96 ± 30.3828.72 ± 11.96137.68 ± 68.031.76 ± 0.36
 No1245.96 ± 478.24184.37 ± 96.29260.92 ± 195.87752.53 ± 319.46433.62 ± 209.2573.03 ± 13.24540.24 ± 231.0624.81 ± 12.38188.6 ± 131.4592.42 ± 8.83683.06 ± 276.7355.43 ± 17.11227.6 ± 109.0338.18 ± 13.92171.09 ± 120.4630.92 ± 13.24133.85 ± 91.741.99 ± 1.01
 P0.4310.0180.5680.5270.4170.3230.7800.1380.1580.9750.3670.1070.0260.0330.7470.8070.7510.723
Surgery
 Yes1285.26 ± 471.23182.04 ± 95.87269.73 ± 203.91749.71 ± 321.18461.57 ± 221.2173.04 ± 14.00531.97 ± 210.3524.12 ± 12.70185.17 ± 136.1791.56 ± 9.34671.28 ± 269.3853.28 ± 17.43230.14 ± 108.0739.62 ± 14.65190.36 ± 136.5532.75 ± 13.90151.70 ± 106.331.88 ± 0.98
 No1231.11 ± 436.88187.04 ± 98.35245.17 ± 178.12752.79 ± 294.67421.08 ± 203.9773.73 ± 11.76553.58 ± 238.9324.55 ± 11.76186.15 ± 121.1793.30 ± 8.54687.78 ± 284.4158.65 ± 17.11234.36 ± 109.4936.27 ± 13.26158.90 ± 122.3828.62 ± 11.73118.04 ± 72.552.09 ± 1.07
 P0.4280.8660.2720.7080.0980.8980.4560.5520.6530.1410.5430.0080.5930.0720.0190.0140.0130.039
History of diseases
 No1301.63 ± 413.78187.44 ± 97.57294.99 ± 271.76752.48 ± 256.8462.89 ± 233.9473.22 ± 12.76545.68 ± 193.0425.08 ± 12.72193.87 ± 139.9391.08 ± 8.93686.59 ± 249.4455.50 ± 16.87238.56 ± 106.9038.49 ± 14.95185.52 ± 142.8233.55 ± 12.46154.74 ± 96.262.00 ± 1.07
 Yes1234.46 ± 470.19183.60 ± 96.63252.92 ± 188.98747.32 ± 322.23431.22 ± 204.7573.54 ± 13.19539.69 ± 233.4723.99 ± 12.24181.21 ± 124.6193.01 ± 8.92674.79 ± 283.156.31 ± 17.74229.26 ± 108.5638.13 ± 14.15170.82 ± 125.0830.13 ± 13.64128.74 ± 90.761.98 ± 1.00
 P0.3180.6700.1960.6000.4530.8080.5660.6010.4680.0430.6290.6440.5410.7410.4550.0120.0220.864
Smoking history
 No1249.36 ± 463.71194.16 ± 98.74240.88 ± 167.3744.68 ± 317.46436.33 ± 214.3872.58 ± 13.3528.07 ± 217.825.19 ± 12.45191.36 ± 137.9392.66 ± 8.77672.86 ± 272.0555.95 ± 17.32228.75 ± 105.6737.11 ± 13.89168.54 ± 130.1631.02 ± 12.18134.95 ± 87.041.95 ± 0.97
 Yes1395.45 ± 460.14204.81 ± 106.52267.17 ± 174.27854.83 ± 322.1471.48 ± 185.9974.52 ± 11.83541.63 ± 201.0922.63 ± 11.47167.39 ± 103.9891.2 ± 9.42653.13 ± 253.2754.51 ± 15.95228.12 ± 105.9439.96 ± 14.98185.87 ± 139.0230.78 ± 14.5138.87 ± 111.42.01 ± 0.86
 Cessation1220.78 ± 388.34151.82 ± 90.12329.4 ± 260.19728.75 ± 246.2441.08 ± 209.8675.07 ± 12.07634.99 ± 265.6423.24 ± 12.14204.1 ± 122.5593.16 ± 9.43791.84 ± 313.2858.35 ± 18.73264.2 ± 115.0937.68 ± 13.03185.99 ± 109.1426.63 ± 10.94122.51 ± 78.832.05 ± 1.17
 P0.1240.0070.1700.0860.3430.5270.0620.3820.3770.1360.0880.6380.2000.4370.1790.1330.7670.882
Drinking history
 No1261.05 ± 464.45194.59 ± 103.37248.44 ± 175.23752.68 ± 323.32451.27 ± 223.0373.12 ± 13.24541.44 ± 234.8324.47 ± 12.37185.61 ± 130.7392.61 ± 9.08678.53 ± 287.0555.91 ± 17.39237.64 ± 113.0738.02 ± 14.7180.04 ± 139.5931.42 ± 13.64140.47 ± 95.311.92 ± 0.98
 Yes1261.86 ± 459.97160.90 ± 77.59303.90 ± 251.43762.52 ± 255.07409.57 ± 187.1277.26 ± 14.85528.60 ± 176.7620.22 ± 14.72151.40 ± 132.3691.04 ± 6.82636.21 ± 206.0355.11 ± 12.18231.52 ± 67.8737.27 ± 9.00154.28 ± 35.4329.04 ± 10.35120.53 ± 43.692.22 ± 1.13
 Abstinence1193.52 ± 242.43124.90 ± 67.65219.10 ± 116.42698.20 ± 219.11426.90 ± 104.6772.98 ± 12.51547.67 ± 185.7725.24 ± 12.38200.74 ± 131.1191.99 ± 8.7699.64 ± 244.2855.65 ± 17.8212.66 ± 90.3338.86 ± 13.23162.34 ± 104.6829.20 ± 12.78122.15 ± 94.931.76 ± 0.80
 P0.9020.0200.6510.5890.5420.4540.7380.3640.3120.2910.6260.9370.4380.6760.9250.4580.1770.152
ECOG PS
 01249.01 ± 470.92189.54 ± 97.22256.76 ± 188.20755.79 ± 314.37433.64 ± 208.8473.07 ± 13.01542.99 ± 227.8424.55 ± 12.23188.23 ± 130.9692.41 ± 9.11687.18 ± 275.9656.88 ± 17.01233.15 ± 108.5337.34 ± 14.28168.51 ± 125.7730.31 ± 12.37129.85 ± 84.492.00 ± 1.00
 11269.76 ± 376.02157.46 ± 88.47314.7 ± 345.09723.17 ± 241.1463.12 ± 259.2274.22 ± 12.16531.84 ± 187.0424.57 ± 11.79181.96 ± 110.5193.97 ± 5.72638.85 ± 261.1451.87 ± 18.1214.82 ± 99.1440.64 ± 13.28194.72 ± 158.133.24 ± 15.22161.51 ± 137.982.02 ± 1.15
 21202.74 ± 242.49181.56 ± 165.45390.44 ± 282.96632.00 ± 218.54422.78 ± 129.9577.45 ± 16.10462.00 ± 79.9019.88 ± 15.63153.11 ± 176.0888.14 ± 14.21572.20 ± 257.7349.58 ± 18.76199.06 ± 87.6444.74 ± 13.11197.60 ± 117.3538.93 ± 18.6177.33 ± 133.091.58 ± 0.57
 31268 ± 534.57257 ± 96.17312 ± 91.92633.5 ± 297.69589 ± 260.2290.59 ± 3.75579.5 ± 293.457.69 ± 4.5142.00 ± 5.6696.05 ± 0.49608 ± 282.8452.1 ± 10.04294 ± 76.3745.05 ± 13.51283 ± 196.5820.95 ± 7.42133.5 ± 98.291.07 ± 0.04
 P0.9660.0930.2670.5410.7760.1380.7790.1150.0750.8810.6170.2640.3950.1040.4270.2800.7050.188
Histology
 LAC1239.83 ± 463.04186.72 ± 98.1262.97 ± 207.77741.78 ± 309.04432.47 ± 215.1173.16 ± 12.97533.68 ± 223.5724.59 ± 12.26185.23 ± 129.6892.36 ± 9.22669.8 ± 275.2655.87 ± 17.38226.45 ± 107.4538.19 ± 14.1171.93 ± 129.3731.34 ± 12.95135.01 ± 90.692.00 ± 1.03
 LSC1355.94 ± 346.96161.44 ± 98.52308.93 ± 241.53766.33 ± 231.97508.07 ± 182.778.18 ± 10.83593.22 ± 184.4419.62 ± 10.23157.22 ± 97.1592.73 ± 5.56711.58 ± 223.7254.83 ± 16.04266.91 ± 91.2940.11 ± 14.84208.43 ± 128.5728.67 ± 16.78153.82 ± 138.51.69 ± 0.73
 LASC1562.36298.00909.001060.00459.0054.34576.0044.72474.00100.00106075.90348.3838.70177.6312.6057.832.31
 P0.1890.1110.2060.2990.0710.0340.1890.0340.1780.1320.1850.4300.0310.9080.1210.0720.4920.336
Tumor stage
 T11287.03 ± 461.46199.48 ± 97.84251.40 ± 185.00771.03 ± 306.11452.45 ± 209.3472.5 ± 12.94548.64 ± 209.3825.08 ± 12.12195.9 ± 134.2592.84 ± 8.03700.98 ± 270.5255.8 ± 16.78241.11 ± 109.8137.68 ± 13.55175.94 ± 127.5429.33 ± 11.65132.03 ± 81.941.93 ± 0.92
 T21132.15 ± 467.27151.1 ± 86.35237.71 ± 174.92651.4 ± 307.11393.92 ± 221.1875.83 ± 11.66486.99 ± 232.9122.24 ± 11.46151.16 ± 110.9591.5 ± 9.2580.82 ± 302.2457.08 ± 17.45206.53 ± 106.0438.86 ± 14.46161.27 ± 128.6732.53 ± 14.45128.38 ± 103.222.00 ± 1.03
 T31249.3 ± 474.78138.25 ± 67.27306.25 ± 230.88766.37 ± 303.9410.42 ± 206.3678.33 ± 10.56598.67 ± 258.3320.01 ± 10.82155.53 ± 92.0893.41 ± 5.16715.91 ± 297.659.04 ± 16.63226.78 ± 116.1136.41 ± 13.99164.79 ± 133.5429.23 ± 13.01120.75 ± 104.332.17 ± 0.80
 T41226.94 ± 342.63167.96 ± 107.62349.64 ± 223.54725.14 ± 207.8427 ± 229.0975.31 ± 12.43541.55 ± 176.5422.98 ± 12.26170.36 ± 102.2892.89 ± 9.07670.33 ± 195.4753.65 ± 21.62199.97 ± 80.240.49 ± 14.87173.75 ± 117.9335.83 ± 15.59163.63 ± 144.562.17 ± 1.28
P0.0850.0020.0930.0330.2570.1420.1000.1880.1290.9230.0160.7020.0880.6120.6690.1910.4300.532
Lymph nodes metastases
 N01273.8 ± 446.29195.1 ± 97.38251.71 ± 181.65768.04 ± 303.92441.54 ± 198.4772.86 ± 12.89549.78 ± 211.1224.95 ± 12.09193.59 ± 131.9593.11 ± 7.56697.13 ± 272.6257.11 ± 16.46241.44 ± 109.4737.11 ± 13.59168.68 ± 117.4529.45 ± 11.66128.97 ± 77.581.96 ± 0.93
 N11400.43 ± 633.16212.75 ± 108.69282.25 ± 206.57779.17 ± 316.94472.25 ± 267.6676.96 ± 13.38583.42 ± 222.6821.28 ± 13.32179.58 ± 140.9390.83 ± 11.91698.56 ± 266.351.27 ± 20.07215.31 ± 91.7340.2 ± 12.8197.74 ± 138.0233.98 ± 19.63155.51 ± 121.061.91 ± 0.86
 N21241.51 ± 463.87158.63 ± 85.08254.33 ± 146.18686.63 ± 320.14477.71 ± 276.7075.19 ± 11.33511.32 ± 248.9721.63 ± 10.81154.41 ± 107.890.83 ± 9.74630.08 ± 318.8650.32 ± 17.87217.47 ± 116.0641.15 ± 14.88213.69 ± 183.4230.12 ± 14.02149.22 ± 131.71.84 ± 1.01
 N31068.74 ± 429.88136.71 ± 91.75271.63 ± 179.01650.58 ± 231.06360.04 ± 211.5674.49 ± 13.07478.46 ± 182.7323.75 ± 12.99161.13 ± 110.3991.98 ± 9.08595.73 ± 212.1656.8 ± 20.42180.36 ± 78.8940.46 ± 14.02147.53 ± 108.8736.11 ± 13.48140.09 ± 133.642.23 ± 1.22
 P0.2480.0080.7290.1270.1150.5450.2270.3850.2660.5560.1520.2020.0300.2170.4920.1140.9360.696
Distant metastases
 M01281.78 ± 462.6193.06 ± 97.13254.16 ± 190.11763.80 ± 308.98448.96 ± 214.5873.1 ± 12.83548.94 ± 218.4624.6 ± 12.05190.51 ± 13193.00 ± 7.89694.48 ± 279.0256.38 ± 16.78239.97 ± 110.1237.69 ± 13.94175.8 ± 131.1929.61 ± 12.1132.35 ± 87.171.94 ± 0.91
 M11141.48 ± 396.68145.72 ± 90.52330.67 ± 302.36671.32 ± 279.37397.7 ± 198.375.95 ± 12.17507.09 ± 242.8821.89 ± 12.04149.67 ± 101.1888.73 ± 13.12583.34 ± 219.8152.2 ± 18.79186.2 ± 81.840.76 ± 12.99168.68 ± 109.1835.05 ± 15.59146.02 ± 121.532.12 ± 1.40
 P0.0990.0010.0490.0400.1210.2780.1030.2080.0490.0400.0150.0990.0010.0650.8270.0530.9080.926

Bold represents p <0.05, the difference was statistically significant

LAC lung adenocarcinoma, LSC squamous carcinoma, LASC lung adenosquamous carcinoma

Table 4

Relationship between inflammatory cells levels and clinicopathologic characteristics

WBC (cells/10^12ul)Lymphocytes (cells/10^12ul)Monocytes (cells/ul)Neutrophils (cells/ul)Eosnophils (cells/ul)Basophils (cells/ul)RBC (cells/ul)Hemoglobins (cells/ul)Blood platelets (cells/ul)MLRNLRELRBLRRLRHLRPLR
Gender
 Male7.10 ± 2.991.71 ± 0.570.44 ± 0.184.79 ± 2.980.15 ± 0.150.03 ± 0.024.68 ± 0.61144.94 ± 13.64223.76 ± 63.840.28 ± 0.153.18 ± 2.60.13 ± 0.430.03 ± 0.133.07 ± 1.3896.81 ± 45.58146.20 ± 78.14
 Female6.42 ± 2.791.76 ± 0.620.33 ± 0.144.14 ± 2.810.12 ± 0.130.03 ± 0.024.37 ± 0.51132.6 ± 12.14231.43 ± 62.20.21 ± 0.152.82 ± 2.860.07 ± 0.080.02 ± 0.012.82 ± 1.2185.59 ± 36.44146.73 ± 63.55
 P0.0050.693 < 0.0010.0010.0060.574 < 0.001 < 0.0010.217 < 0.0010.0010.0020.6490.0540.0070.570
Age
 Yong6.39 ± 2.911.79 ± 0.840.37 ± 0.143.99 ± 2.20.1 ± 0.090.02 ± 0.014.39 ± 0.59130.24 ± 21.42231.48 ± 73.20.23 ± 0.122.81 ± 3.30.07 ± 0.070.01 ± 0.012.89 ± 1.2785.83 ± 41.37150.75 ± 76.23
 Middle7.06 ± 3.141.75 ± 0.580.38 ± 0.174.77 ± 3.260.14 ± 0.180.03 ± 0.024.6 ± 0.45140.82 ± 13.48235.03 ± 58.010.24 ± 0.153.29 ± 3.210.12 ± 0.470.03 ± 0.152.96 ± 1.3692.60 ± 46.07153.95 ± 87.09
 Elder6.55 ± 2.711.72 ± 0.570.38 ± 0.164.27 ± 2.710.13 ± 0.110.03 ± 0.014.47 ± 0.65137.71 ± 12.93222.26 ± 64.530.25 ± 0.152.81 ± 2.260.09 ± 0.090.02 ± 0.012.93 ± 1.2590.19 ± 37.56140.53 ± 54.57
 P0.2040.8680.9480.2430.1980.3850.0290.0100.1480.7660.4010.1570.2780.9980.7180.693
Allergic history
 Antibiotic6.48 ± 3.011.68 ± 0.440.36 ± 0.154.29 ± 2.910.15 ± 0.220.03 ± 0.024.39 ± 0.93137.84 ± 13.4217.74 ± 50.390.22 ± 0.092.64 ± 1.770.09 ± 0.120.02 ± 0.012.81 ± 0.9587.96 ± 25.82138.27 ± 54.36
 Other8.45 ± 5.031.94 ± 0.190.44 ± 0.276.01 ± 5.120.13 ± 0.120.02 ± 0.014.51 ± 0.34132.83 ± 18.74196.17 ± 47.630.23 ± 0.133.06 ± 2.560.06 ± 0.060.01 ± 0.012.33 ± 0.1968.34 ± 7.28101.13 ± 24.55
 No6.75 ± 2.951.72 ± 0.630.38 ± 0.174.46 ± 2.970.13 ± 0.130.03 ± 0.024.54 ± 0.46138.65 ± 14.4228.96 ± 64.090.25 ± 0.163.11 ± 2.980.08 ± 0.10.02 ± 0.013.02 ± 1.3893.26 ± 44.67150.07 ± 74.34
 P0.4130.3150.7500.5530.7820.7300.8910.6650.3730.7770.9570.8930.4090.3630.2140.096
Surgery history
 Yes6.97 ± 3.21.75 ± 0.590.4 ± 0.184.65 ± 3.250.14 ± 0.150.03 ± 0.024.57 ± 0.6140.82 ± 15.29229.88 ± 62.680.25 ± 0.163.13 ± 30.09 ± 0.10.02 ± 0.012.99 ± 1.4391.69 ± 43.48147.11 ± 72.87
 No6.53 ± 2.721.72 ± 0.610.37 ± 0.154.26 ± 2.70.12 ± 0.140.03 ± 0.024.46 ± 0.43135.53 ± 12.88223.73 ± 62.250.24 ± 0.142.88 ± 2.610.08 ± 0.090.02 ± 0.012.94 ± 1.1989.57 ± 36.65142.06 ± 53.96
 P0.2730.4220.3050.1900.1130.6400.0160.0010.3920.2480.2900.1250.8020.9610.9320.724
History of diseases
 Yes6.78 ± 3.041.84 ± 0.660.38 ± 0.164.39 ± 2.960.13 ± 0.160.03 ± 0.024.59 ± 0.44139.17 ± 13.08224.72 ± 59.420.23 ± 0.132.74 ± 2.480.08 ± 0.10.02 ± 0.012.77 ± 0.9584.33 ± 29.28134.86 ± 55.33
 No6.73 ± 2.951.69 ± 0.590.38 ± 0.174.48 ± 2.990.13 ± 0.140.03 ± 0.024.5 ± 0.56137.9 ± 14.86227.4 ± 64.640.25 ± 0.163.13 ± 2.930.09 ± 0.10.02 ± 0.013.03 ± 1.4193.82 ± 45.67151.01 ± 76.92
 P0.6240.1580.9090.2760.5580.6400.4840.7320.7340.1280.0580.3150.1240.3660.3540.164
Smoking history
 No6.45 ± 2.741.72 ± 0.610.35 ± 0.144.22 ± 2.750.13 ± 0.140.03 ± 0.024.48 ± 0.41135.79 ± 13.4226.4 ± 61.110.23 ± 0.162.96 ± 2.920.08 ± 0.10.02 ± 0.012.98 ± 1.2790.32 ± 39.30146.68 ± 62.1
 Yes8.29 ± 3.921.89 ± 0.570.47 ± 0.245.87 ± 4.010.13 ± 0.090.03 ± 0.024.67 ± 0.54144.21 ± 15.72238.48 ± 69.310.27 ± 0.143.53 ± 3.420.22 ± 0.860.06 ± 0.272.86 ± 1.7288.19 ± 52.90143.81 ± 87.75
 Cessation7.1 ± 2.831.75 ± 0.530.44 ± 0.164.6 ± 2.870.15 ± 0.120.03 ± 0.024.56 ± 0.78143.95 ± 13.42227.61 ± 65.450.27 ± 0.162.85 ± 1.690.09 ± 0.070.02 ± 0.012.88 ± 1.1091.01 ± 32.92139.32 ± 50.79
 P0.0010.121 < 0.0010.0020.0980.1450.004 < 0.0010.810 < 0.0010.0390.1450.4930.2910.4360.544
Drinking history
 No6.61 ± 2.961.74 ± 0.620.36 ± 0.164.35 ± 2.960.13 ± 0.130.03 ± 0.024.49 ± 0.52136.56 ± 13.76226.67 ± 65.260.24 ± 0.162.96 ± 2.830.08 ± 0.090.02 ± 0.012.95 ± 1.3090.67 ± 42.41146.45 ± 71.94
 Yes7.5 ± 3.111.76 ± 0.580.45 ± 0.195.06 ± 3.210.13 ± 0.140.03 ± 0.024.58 ± 0.54142.33 ± 16.02237.23 ± 56.720.28 ± 0.143.37 ± 2.990.17 ± 0.660.04 ± 0.212.93 ± 1.4390.94 ± 43.80150.91 ± 75.76
 Abstinence5.88 ± 0.781.55 ± 0.370.36 ± 0.073.71 ± 0.670.15 ± 0.080.03 ± 0.014.64 ± 0.3147 ± 8.94202.7 ± 44.870.24 ± 0.052.52 ± 0.830.11 ± 0.070.02 ± 0.013.14 ± 0.7599.63 ± 23.28137.85 ± 43.66
 P0.0260.6080.0020.0660.3990.7470.2670.0020.2240.0030.0620.2270.5110.3910.2080.860
ECOG
 06.63 ± 2.951.73 ± 0.610.37 ± 0.164.35 ± 2.930.13 ± 0.130.03 ± 0.024.52 ± 0.6138.95 ± 13.76223.09 ± 56.850.24 ± 0.152.95 ± 2.770.1 ± 0.330.02 ± 0.12.97 ± 1.359.20 ± 43.06144.96 ± 71.59
 17.69 ± 3.021.76 ± 0.580.44 ± 0.215.28 ± 3.310.15 ± 0.210.03 ± 0.024.52 ± 0.54135.51 ± 17.79243.46 ± 85.240.28 ± 0.163.67 ± 3.270.09 ± 0.120.02 ± 0.012.85 ± 1.0985.63 ± 34.63153.77 ± 74.35
 27.14 ± 2.051.78 ± 0.560.41 ± 0.094.78 ± 1.570.12 ± 0.030.03 ± 0.014.41 ± 0.47128.44 ± 15.29299.33 ± 81.730.25 ± 0.062.79 ± 0.890.07 ± 0.030.02 ± 02.7 ± 0.9178.28 ± 25.33177.7 ± 58.41
 37.52 ± 1.231.85 ± 0.540.39 ± 0.094.96 ± 1.50.27 ± 0.170.05 ± 0.024.79 ± 0.2145.5 ± 6.36286.5 ± 30.410.23 ± 0.112.92 ± 1.660.17 ± 0.140.03 ± 0.022.72 ± 0.9082.63 ± 27.44159.19 ± 29.81
 P0.0080.9740.0690.0270.4260.1460.4480.1160.0130.2070.1460.6700.3570.9490.7140.206
Histology
 LAC6.65 ± 2.881.72 ± 0.610.37 ± 0.154.39 ± 2.910.13 ± 0.140.03 ± 0.024.52 ± 0.59138.32 ± 14.25227.25 ± 63.480.24 ± 0.153.02 ± 2.840.08 ± 0.10.02 ± 0.012.98 ± 1.3392.06 ± 42.41147.99 ± 72.41
 LSC7.5 ± 2.991.85 ± 0.480.5 ± 0.244.9 ± 2.890.17 ± 0.120.03 ± 0.014.45 ± 0.42136.85 ± 13.66234.58 ± 59.290.28 ± 0.142.68 ± 1.430.27 ± 0.950.07 ± 0.32.44 ± 0.8478.06 ± 22.37132.90 ± 44.88
 LASC10.302.780.856.290.120.055.17163.00234.000.312.260.040.021.8658.6384.17
 P0.0760.0890.0020.1530.0780.2230.1730.2330.8640.0730.7870.1480.9180.0900.1060.281
Tumor stage
 T16.73 ± 3.11.78 ± 0.60.37 ± 0.164.46 ± 3.180.12 ± 0.110.03 ± 0.024.54 ± 0.43139.19 ± 12.52220.86 ± 50.950.23 ± 0.152.93 ± 2.890.07 ± 0.060.02 ± 0.012.87 ± 1.1687.98 ± 35.62136.47 ± 54.37
 T26.07 ± 2.751.5 ± 0.610.37 ± 0.173.89 ± 2.510.15 ± 0.190.03 ± 0.024.39 ± 0.83136.91 ± 16.88212.38 ± 72.670.28 ± 0.172.9 ± 2.140.12 ± 0.160.02 ± 0.013.45 ± 1.65106.71 ± 49.24158.63 ± 68.37
 T37.6 ± 2.691.71 ± 0.60.5 ± 0.255.22 ± 2.490.13 ± 0.080.04 ± 0.024.58 ± 0.59137.56 ± 17.66275.56 ± 97.810.32 ± 0.173.86 ± 4.250.38 ± 1.230.12 ± 0.393.18 ± 2.2396.30 ± 69.57184.22 ± 116.91
 T47.48 ± 1.631.76 ± 0.40.44 ± 0.144.77 ± 1.770.25 ± 0.250.04 ± 0.024.61 ± 0.46136.77 ± 16.46264.46 ± 62.890.27 ± 0.13.03 ± 1.150.15 ± 0.150.03 ± 0.022.77 ± 0.7281.86 ± 21.57160.05 ± 60.92
 P0.0010.0120.0010.0050.010 < 0.0010.7930.763 < 0.0010.0010.0090.0040.0010.0790.0550.054
Lymph nodes metastasesLymph nodes metastases
 N06.66 ± 3.191.76 ± 0.60.37 ± 0.164.42 ± 3.20.12 ± 0.110.03 ± 0.024.52 ± 0.43138.51 ± 12.6221.37 ± 54.060.23 ± 0.142.88 ± 2.80.07 ± 0.060.02 ± 0.012.89 ± 1.1788.64 ± 36.07137.98 ± 54.92
 N16.37 ± 1.861.91 ± 0.780.38 ± 0.173.8 ± 1.40.19 ± 0.310.04 ± 0.034.55 ± 0.47136.08 ± 20.46242.17 ± 53.110.21 ± 0.082.29 ± 1.240.11 ± 0.180.02 ± 0.022.72 ± 1.0180.3 ± 30.07146.62 ± 65.04
 N26.92 ± 2.371.61 ± 0.560.42 ± 0.214.56 ± 2.330.16 ± 0.20.03 ± 0.024.58 ± 0.47137.76 ± 15.24233.91 ± 87.640.29 ± 0.183.23 ± 2.120.1 ± 0.140.02 ± 0.013.23 ± 1.3697.25 ± 42.04158.95 ± 71.24
 N37.18 ± 1.851.52 ± 0.460.45 ± 0.144.67 ± 2.210.19 ± 0.170.04 ± 0.024.74 ± 0.46143.75 ± 17.54246.29 ± 69.550.34 ± 0.194.05 ± 3.960.35 ± 10.09 ± 0.323.61 ± 2.06109.83 ± 64.92181.93 ± 98.02
 P0.0200.2380.0100.0960.1080.0410.2750.4470.284 < 0.0010.0070.0120.0010.0930.1240.048
Distant metastases
 M06.68 ± 3.081.76 ± 0.610.37 ± 0.174.4 ± 3.10.12 ± 0.120.03 ± 0.024.52 ± 0.42138.12 ± 13.03221.55 ± 54.660.24 ± 0.152.89 ± 2.720.07 ± 0.080.02 ± 0.012.91 ± 1.1988.82 ± 36.55139.34 ± 56.81
 M17.13 ± 2.11.65 ± 0.530.42 ± 0.154.7 ± 2.090.2 ± 0.210.04 ± 0.024.69 ± 0.56140.78 ± 18.37255.59 ± 88.440.29 ± 0.173.49 ± 3.070.24 ± 0.730.06 ± 0.233.26 ± 1.7398.76 ± 54.84170.25 ± 86.91
 P0.0030.4150.0110.0040.0030.0010.0340.1830.0130.0030.002 < 0.001 < 0.0010.2330.3520.011

Bold represents p <0.05, the difference was statistically significant

LAC lung adenocarcinoma, LSC squamous carcinoma, LASC lung adenosquamous carcinoma

Fig. 2

Relationship between immune cell levels and basic parameters for NSCLC patients. Age related change of CD8CD28/CD8+ percentage (a), CD8+CD38+/CD8+ percentage (b), CD8+HLA-DR+/CD8+ percentage (c); Smoking history related change of WBC counts (d), monocytes counts (e), neutrophils counts (f), RBC counts (g), hemoglobins counts (h), MLR (i), NLR (j); Drinking history related change of B cell counts (k), WBCcounts (l), monocytes counts (m), hemoglobins counts (n), MLR (o); ECOG related change of WBC counts (p), neutrophils counts (q), platelets counts (r)

Relationship between lymphocytes levels and clinicopathologic characteristics Bold represents p <0.05, the difference was statistically significant LAC lung adenocarcinoma, LSC squamous carcinoma, LASC lung adenosquamous carcinoma Relationship between inflammatory cells levels and clinicopathologic characteristics Bold represents p <0.05, the difference was statistically significant LAC lung adenocarcinoma, LSC squamous carcinoma, LASC lung adenosquamous carcinoma Relationship between immune cell levels and basic parameters for NSCLC patients. Age related change of CD8CD28/CD8+ percentage (a), CD8+CD38+/CD8+ percentage (b), CD8+HLA-DR+/CD8+ percentage (c); Smoking history related change of WBC counts (d), monocytes counts (e), neutrophils counts (f), RBC counts (g), hemoglobins counts (h), MLR (i), NLR (j); Drinking history related change of B cell counts (k), WBCcounts (l), monocytes counts (m), hemoglobins counts (n), MLR (o); ECOG related change of WBC counts (p), neutrophils counts (q), platelets counts (r) A trend of decreased CD8+CD28+/CD8+ percentage (r = −0.170, p = 0.006, Fig. 2a), CD8+CD38+/CD8+ percentage (r = −0.264, p < 0.001, Fig. 2b), and increased CD8+HLA-DR+/CD8+ percentage (r = 0.179, p = 0.002, Fig. 2c) with age was found in our study. However, we did not find asimilar trend in RBC and hemoglobins in spite of statistically significant difference (r = −0.047, p = 0.416; r = 0.004, p = 0.943) for these data. There were increased WBC (r = 0.227, p < 0.001, Fig. 2d), monocytes (r = 0.293, p < 0.001, Fig. 2e), neutrophils (r = 0.207, p < 0.001, Fig. 2f), RBC (r = 0.194, p = 0.001, Fig. 2g), hemoglobins (r = 0.277, p < 0.001, Fig. 2h), and MLR (r = 0.226, p < 0.001, Fig. 2i), NLR (r = 0.150, p = 0.011, Fig. 2j) with in patientswith various smoking history statuses. In addition, we also found patients with smoking cessation had lower B cell counts (r = −0.082, p = 0.166) compared to that in patients with smoking or without smoking. There wasa decreased trend in B cell counts (r = −0.139, p = 0.018, Fig. 2k) and increased trend in WBC (r = 0.146, p = 0.013, Fig. 2l), monocyte counts (r = 210, p < 0.001, Fig. 2m), hemoglobin counts (r = 0.194, p = 0.001, Fig. 2n) and MLR (r = 0.200, p < 0.001, Fig. 2o) with in patients with various drinking history statuses. A trend of an increase in WBC (r = 0.198, p = 0.001, Fig. 2p), neutrophils (r = 0.174, p = 0.003, Fig. 2q), and platelets (r = 0.140, p = 0.017, Fig. 2r) was found with increased ECOG. In the lung cancer cohorts, we discovered that there were high percentages of people who always smoked, women, and patients with adenocarcinoma, which may be a clinical feature of lung cancer patients in China, or it may be the cause of a unique subgroup of cases.

Discussion

To our knowledge, this is the most comprehensive report to evaluate associations of lymphocyte subsets in relation to the presence of cancer occurrence and lung cancer stage. We discovered that levels of NK cells, CD4+ T cells, naïve CD4+/CD4+, naïve CD4+ T cells, CD4+CD28+ T cells were significantly different in lung cancer patients versus healthy individuals and that the percentages of the different cell subsets are associated with lung cancer stage. Several reports have demonstrated the predictive role of lymphocyte subsets in cancers, however, those results are controversial and not comprehensive. We evaluated the predictive role of lymphocyte subsets in carcinogenesis. In this study, we found that lymphocyte subsets were associated with cancer occurrence and lung cancer stage, which is consistent with other previously published studies articles [12-14]. However, conflicting results have also been reported in several studies, such as high CD8+ T cells and decreased CD4+ T cell counts, and CD4+/CD8+ ratio in patients with NSCLC than those in controls [15]. CD8+ T cells and CD4+ T cells undergo a period of massive expansion, activation, differentiation into effector cells, and apoptosis, which might lead to these disparate results. As the cytotoxicity cells, low NK cell counts and CD8+ T cell counts might imply that weakened immunological system contributes to growth of cancer cells by effectively reducing the killing effect toward the cancer cells.. As the helper cells, decreased naïve CD4+/CD4+ percentages and increased CD4+ T cell counts, memory CD4+/CD4+ percentages might suggest that the anti-tumor immune response was activated and naïve CD4+ T cells were differentiated into CD4+ T cells and memory CD4+ T cells [16]. CD28 are a very important co-stimulatory marker, which is required as a secondary signal for activated CD8+ T cells and CD4+ T cells exerting anti-tumor response. We discovered patients had higher CD4+CD28+/CD4+ percentage and CD4+CD28+ T cell counts than those in controls, which might imply that CD4+ T cells were activated in cancer occurrence. Noteworthily, patients had high CD8+CD28+/CD8+ percentage than that in controls, but there was no significant difference in the counts of CD8+CD28+ between patients and controls. These results might imply that the activation CD8+ T cells was limited, as a result cancer occurrence based on the reduced antitumor. HLA-DR and CD38, as markers of CD8+ T cell activation, play a crucial predictive value in CD8+ T cells activation and CD4+ T cells depletion [17]. Elevated levels of HLA-DR and CD38 have suggested the immune system was activated during tumorigenesis. The CD4+/CD8+ ratio is a marker of cell-mediated immunity in cancer patients [18]. Decreased ratio is reported to link with a low immunological function [19]. Immune status is closely associated with the pathogenesis and development of cancer. Less research has been reported on the role of peripheral blood immune cells in advance cancer stage, which focus on B cells, NK cells, CD4+ T cells, CD8+ T cells and CD4+/CD8+ [12, 14]. In addition, there is no consensus regarding change of lymphocyte subsets in the advance cancer stage. Liang et al. reported that there was decreased trend in counts of NK cells, CD4+ T cells and CD4+/CD8+ ratio with advanced NSCLC (including stage III, IV and controls groups), and no relationship between CD8+ T cells and stage [14]. Mazzoccoli et al. reported that there were decreasing trend for B cells and increasing trend for NK cells in cancer stage [12]. Those results were not exactly the same as ours. In our study, advance cancer stage was negatively associated with levels of B cells, CD4+ T cells, naïve CD4+/CD4+, naïve CD4+ T cells, CD4+CD28+ T cells, CD8+CD28+ T cells and positively associated with NK cells, WBC counts, monocytes, neutrophils, eosinophils, basophils, MLR, NLR, ELR, BLR, PLR. A possible explanation for this finding could be immune function disorder associated with clinical staging. B cells can recognize antigens, regulate process and presentation of antigen, present antigens, provide co-stimulation [20]. As to our results of lymphocyte subsets might suggest that immune function is severely damaged with advancing stage causing growth and metastasis of cancer cells. The reason is likely that decreased expression of co-stimulatory molecule (CD28) can suppress anti-tumor response by limiting aggregation of CD4+ T cells, CD8+ T cells and immune system were not activated during disease progression due to no significant difference for HLA and CD38 in each stage. WBC and neutrophils can contrubite to disease progression and metastasis, which could reflect the tumor burden in patients [21]. Increased neutrophil levels might inhibit the antitumor effects of T cells and NK cells Increased NLR levels represents increased inflammation and decreased immune reaction [22]. Several reports have been demonstated that the change of WBC, monocytes, neutrophils, eosinophils, basophils, MLR, NLR, ELR, BLR, PLR were associated with cancer prognosis in some solid tumors [23, 24]. However, there is no reported for the predictive value of those cells in cancer occurrence and progression. In this study, results about elevated levels of inflammatory cells might demonstrate that those cells play an important role in anti-tumor response and can predict cancer progression not just prognosis. In short, those immune cells are gradually destroyed with advancing cancer, which restricts the recognition and killing of cancer cells and triggers the extensive dissemination of cancer cells. There are several limitations in this study. First, threshold value had not been provided in this work which needs further investigations. Second, limited numbers of patients with stage II and III and in homogenous clinicopathologic characteristics of samples. Last, this paper lacks a validation queue, and we will continue to collect samples to further verify the results. Despite these limitations, this study demonstrated that immune cells play a predictive role in the NSCLC development and progression. In summary, our findings show a significant relationship between lymphocyte subset/myeloid cells in the presence of lung cancer compared to healthy individuals and significant relationship to these immune parameters and lung cancer stage. Those results of our study may suggest potential strategies for screening, prevention or treatment of lung cancer. Additional file 1. Table S1: Relationship between immune cells levels and basic parameters for NSCLC patients.
  23 in total

Review 1.  Eosinophils in Cancer: Favourable or Unfavourable?

Authors:  Samy Sakkal; Sarah Miller; Vasso Apostolopoulos; Kulmira Nurgali
Journal:  Curr Med Chem       Date:  2016       Impact factor: 4.530

Review 2.  The Emerging Role of B Cells in Tumor Immunity.

Authors:  Peiling Tsou; Hiroyuki Katayama; Edwin J Ostrin; Samir M Hanash
Journal:  Cancer Res       Date:  2016-09-15       Impact factor: 12.701

Review 3.  Lung cancer epigenetics: From knowledge to applications.

Authors:  Michaël Duruisseaux; Manel Esteller
Journal:  Semin Cancer Biol       Date:  2017-09-14       Impact factor: 15.707

4.  Increase of regulatory T cells in metastatic stage and CTLA-4 over expression in lymphocytes of patients with non-small cell lung cancer (NSCLC).

Authors:  Nasrollah Erfani; Shayesteh Mofakhami Mehrabadi; Mohammad Ali Ghayumi; Mohammad Reza Haghshenas; Zahra Mojtahedi; Abbas Ghaderi; Davar Amani
Journal:  Lung Cancer       Date:  2012-05-17       Impact factor: 5.705

5.  Comparison of circadian characteristics for cytotoxic lymphocyte subsets in non-small cell lung cancer patients versus controls.

Authors:  Gianluigi Mazzoccoli; Robert B Sothern; Paola Parrella; Lucia A Muscarella; Vito Michele Fazio; Francesco Giuliani; Victoria Polyakova; Igor M Kvetnoy
Journal:  Clin Exp Med       Date:  2011-09-11       Impact factor: 3.984

6.  The prognostic values of tumor-infiltrating neutrophils, lymphocytes and neutrophil/lymphocyte rates in bladder urothelial cancer.

Authors:  Kangkang Liu; Kun Zhao; Lining Wang; Erlin Sun
Journal:  Pathol Res Pract       Date:  2018-05-20       Impact factor: 3.250

7.  Stereotactic body radiation therapy (SBRT) improves local control and overall survival compared to conventionally fractionated radiation for stage I non-small cell lung cancer (NSCLC).

Authors:  Donata von Reibnitz; Fauzia Shaikh; Abraham J Wu; Gregory C Treharne; Rosalind Dick-Godfrey; Amanda Foster; Kaitlin M Woo; Weiji Shi; Zhigang Zhang; Shaun U Din; Daphna Y Gelblum; Ellen D Yorke; Kenneth E Rosenzweig; Andreas Rimner
Journal:  Acta Oncol       Date:  2018-06-06       Impact factor: 4.089

Review 8.  The Influence of Host Factors on the Prognosis of Breast Cancer: Stroma and Immune Cell Components as Cancer Biomarkers.

Authors:  Thomas Karn; Lajos Pusztai; Achim Rody; Uwe Holtrich; Sven Becker
Journal:  Curr Cancer Drug Targets       Date:  2015       Impact factor: 3.428

9.  Variation of blood T lymphocyte subgroups in patients with non- small cell lung cancer.

Authors:  Wen-Jing Wang; Zhen Tao; Wei Gu; Li-Hua Sun
Journal:  Asian Pac J Cancer Prev       Date:  2013

10.  Increased CD8+CD28+ T cells independently predict better early response to stereotactic ablative radiotherapy in patients with lung metastases from non-small cell lung cancer.

Authors:  Chao Liu; Qinyong Hu; Kai Hu; Huichao Su; Fang Shi; Li Kong; Hui Zhu; Jinming Yu
Journal:  J Transl Med       Date:  2019-04-11       Impact factor: 5.531

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