RESEARCH
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* and Hongsheng Liu6*
Abstract
Background: Treatment for non-small cell lung cancer (NSCLC) has greatly improved in recent years. However, non- invasive early screening for carcinogenesis and progression unclear. The aim of this study was to explore the predic- tive 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 cytom- etry 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.
Keywords: Immune cells, NSCLC, Cancer occurrence, Advance cancer stage, Clinicopathologic characteristics
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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
Open Access
*Correspondence: litaisheng7373@163.com; lhs04391@163.com
†Yingyi Wang, Na Zhou and Rui Zhu are co first author.
Taisheng Li and Hongsheng Liu are co-corresponding authors.
5 Department of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing 100730, China
6 Department of Thoracic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan Wangfujing Dongcheng District, Beijing 100730, China Full list of author information is available at the end of the article
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 suppress- ing 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, non- invasive, 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 volun- teers (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
Table 1 Clinicophthological characterstics of the untreated lung cancer patients in this study
Characterstics N = 305
Gender
Male 141
Female 164
Age
Yong 25
Middle 116
Elder 164
Allergic history
Antibiotic 31
Other 6
No allergic 239
Unkown 29
Surgery
Uterine 27
Caesarean section 11
Epityphlon 24
Thyroid 17
Intestines 13
Other 86
No surgery 146
Unkown 24
History of diseases
Hypertension 110
Diabetes 40
Coronary heart disease 21
Thyroid nodule 19
Fatty liver 11
Other 152
No Medical 75
Unkown 19
Smoking history
Yes 33
Cessation 51
No 193
Unkown 19
Drinking history
Yes 57
Abstinence 10
No 219
Unkown 19
ECOG PS
0 247
1 35
2 9
3 2
Unkown 12
Histology
Adenocarcinoma 277
Squamous carcinoma 27
informed consent. This study was approved by the Ethical Committee of PUMCH (JS-1405).
Flow cytometry and blood routine tests
Lymphocyte immunophenotyping was conducted by three-color flow cytometry (Epics XL flow cytometry;
Beckman Coulter, USA). Specific monoclonal antibod- ies 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 soft- ware (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 sta- tistically 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 con- trols. 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.
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 Table 1 (continued)
Characterstics N = 305
Adenosquamous carcinoma 1
Stage
I 203
II 18
III 27
IV 46
Unkown 11
Tumour stage
T1 207
T2 42
T3 16
T4 22
Unkown 18
Lymph nodes metastases
N0 215
N1 12
N2 33
N3 24
Unkown 21
Distant metastases
M0 243
M1 46
Unkown 16
(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, lympho- cytes and lowest counts of WBC, neutrophils than those patients in other stages.
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), mono- cytes (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 signifi- cant 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.
A trend of decreased CD8+CD28+/CD8+ percent- age (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+ percent- age (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 sig- nificant 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), hemoglob- ins (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 ces- sation had lower B cell counts (r = −0.082, p = 0.166) compared to that in patients with smoking or without Table 2 Differences of immune parameters in untreated lung cancer patients and healthy controls
Bold represents p <0.05, the difference was statistically significant
Lymphocyte subsets Healthy controls (N = 132) Lung cancer patients (N = 357) P value
T Lymphocyte (cells/10^12ul) 1.97 ± 0.53 1.73 ± 0.61 < 0.001
B cells (cells/ul) 201.69 ± 91.56 184.85 ± 98.29 0.054
NK cells (cells/ul) 390.99 ± 251.48 269.15 ± 213.78 < 0.001
CD4+ T cells (cells/ul) 689.83 ± 255.28 745 ± 302.8 0.042
CD8+ T cells (cells/ul) 511.43 ± 255.09 439.25 ± 212.9 0.008
Memory CD4+/CD4+ (%) 65.89 ± 13.8 73.55 ± 12.88 < 0.001
Memory CD4+ T cells (cells/ul) 441.8 ± 166.31 539.09 ± 220.41 < 0.001
Naïve CD4+/CD4+ (%) 34.11 ± 13.8 24.21 ± 12.2 < 0.001
Naïve CD4+ T cells (cells/ul) 248.05 ± 160.27 183.7 ± 128.13 < 0.001
CD4+CD28+/CD4+ (%) 87.12 ± 10.97 92.42 ± 8.95 < 0.001
CD4+CD28+ T cells (cells/ul) 600.64 ± 239.99 674.78 ± 271.48 0.002
CD8+CD28+/CD8+ (%) 50.95 ± 15.54 55.84 ± 17.26 0.004
CD8+CD28+ T cells (cells/ul) 249.24 ± 119.32 230.43 ± 106.65 0.156
CD8+HLA-DR+/CD8+ (%) 28.4 ± 10.7 38.37 ± 14.13 < 0.001
CD8+HLA-DR+ T cells (cells/ul) 148.75 ± 102.86 175.18 ± 129.29 0.022
CD8+CD38+/CD8+ (%) 22.34 ± 14.71 31.04 ± 13.35 < 0.001
CD8+CD38+ T cells (cells/ul) 114.11 ± 96.19 136.43 ± 95.69 0.001
CD4+/CD8+ (%) 1.62 ± 0.91 1.97 ± 1.00 < 0.001
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 drink- ing 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 per- centages 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.
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)
Table 3 Relationship between lymphocytes levels and clinicopathologic characteristics T lympho cytes (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+CD 28+/CD4+ (%)
CD4+CD28 + T cells (cells/ul)
CD8+CD 28+/CD8 + (%)
CD8+CD28 + T cells (cells/ul)
CD8+HLA- DR/ CD8+ (%)
CD8+HLA -DR T cells (cells/ul)
CD8+CD 38+/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 Antibi- otic1247.95 ± 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
Table 3(continued) T lympho cytes (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+CD 28+/CD4+ (%)
CD4+CD28 + T cells (cells/ul)
CD8+CD 28+/CD8 + (%)
CD8+CD28 + T cells (cells/ul)
CD8+HLA- DR/ CD8+ (%)
CD8+HLA -DR T cells (cells/ul)
CD8+CD 38+/CD8 + (%)
CD8+CD38+ T cells (cells/ul)
CD4+ /CD8+ 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 Cessa- tion1220.78 ± 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 Absti- nence1193.52 ± 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
